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Sample records for reliable cancer classification

  1. Reliability of Oronasal Fistula Classification.

    Science.gov (United States)

    Sitzman, Thomas J; Allori, Alexander C; Matic, Damir B; Beals, Stephen P; Fisher, David M; Samson, Thomas D; Marcus, Jeffrey R; Tse, Raymond W

    2018-01-01

    Objective Oronasal fistula is an important complication of cleft palate repair that is frequently used to evaluate surgical quality, yet reliability of fistula classification has never been examined. The objective of this study was to determine the reliability of oronasal fistula classification both within individual surgeons and between multiple surgeons. Design Using intraoral photographs of children with repaired cleft palate, surgeons rated the location of palatal fistulae using the Pittsburgh Fistula Classification System. Intrarater and interrater reliability scores were calculated for each region of the palate. Participants Eight cleft surgeons rated photographs obtained from 29 children. Results Within individual surgeons reliability for each region of the Pittsburgh classification ranged from moderate to almost perfect (κ = .60-.96). By contrast, reliability between surgeons was lower, ranging from fair to substantial (κ = .23-.70). Between-surgeon reliability was lowest for the junction of the soft and hard palates (κ = .23). Within-surgeon and between-surgeon reliability were almost perfect for the more general classification of fistula in the secondary palate (κ = .95 and κ = .83, respectively). Conclusions This is the first reliability study of fistula classification. We show that the Pittsburgh Fistula Classification System is reliable when used by an individual surgeon, but less reliable when used among multiple surgeons. Comparisons of fistula occurrence among surgeons may be subject to less bias if they use the more general classification of "presence or absence of fistula of the secondary palate" rather than the Pittsburgh Fistula Classification System.

  2. Proteomic classification of breast cancer.

    LENUS (Irish Health Repository)

    Kamel, Dalia

    2012-11-01

    Being a significant health problem that affects patients in various age groups, breast cancer has been extensively studied to date. Recently, molecular breast cancer classification has advanced significantly with the availability of genomic profiling technologies. Proteomic technologies have also advanced from traditional protein assays including enzyme-linked immunosorbent assay, immunoblotting and immunohistochemistry to more comprehensive approaches including mass spectrometry and reverse phase protein lysate arrays (RPPA). The purpose of this manuscript is to review the current protein markers that influence breast cancer prediction and prognosis and to focus on novel advances in proteomic classification of breast cancer.

  3. Scapula Fractures: Interobserver Reliability of Classification and Treatment

    NARCIS (Netherlands)

    Neuhaus, Valentin; Bot, Arjan G. J.; Guitton, Thierry G.; Ring, David C.; Abdel-Ghany, Mahmoud I.; Abrams, Jeffrey; Abzug, Joshua M.; Adolfsson, Lars E.; Balfour, George W.; Bamberger, H. Brent; Barquet, Antonio; Baskies, Michael; Batson, W. Arnold; Baxamusa, Taizoon; Bayne, Grant J.; Begue, Thierry; Behrman, Michael; Beingessner, Daphne; Biert, Jan; Bishop, Julius; Alves, Mateus Borges Oliveira; Boyer, Martin; Brilej, Drago; Brink, Peter R. G.; Brunton, Lance M.; Buckley, Richard; Cagnone, Juan Carlos; Calfee, Ryan P.; Campinhos, Luiz Augusto B.; Cassidy, Charles; Catalano, Louis; Chivers, Karel; Choudhari, Pradeep; Cimerman, Matej; Conflitti, Joseph M.; Costanzo, Ralph M.; Crist, Brett D.; Cross, Brian J.; Dantuluri, Phani; Darowish, Michael; de Bedout, Ramon; DeCoster, Thomas; Dennison, David G.; DeNoble, Peter H.; DeSilva, Gregory; Dienstknecht, Thomas; Duncan, Scott F.; Duralde, Xavier A.; Durchholz, Holger; Egol, Kenneth; Ekholm, Carl; Elias, Nelson; Erickson, John M.; Esparza, J. Daniel Espinosa; Fernandes, C. H.; Fischer, Thomas J.; Fischmeister, Martin; Forigua Jaime, E.; Getz, Charles L.; GIlbert, Richard S.; Giordano, Vincenzo; Glaser, David L.; Gosens, Taco; Grafe, Michael W.; Filho, Jose Eduardo Grandi Ribeiro; Gray, Robert R. L.; Gulotta, Lawrence V.; Gummerson, Nigel William; Hammerberg, Eric Mark; Harvey, Edward; Haverlag, R.; Henry, Patrick D. G.; Hobby, Jonathan L.; Hofmeister, Eric P.; Hughes, Thomas; Itamura, John; Jebson, Peter; Jenkinson, Richard; Jeray, Kyle; Jones, Christopher M.; Jones, Jedediah; Jubel, Axel; Kaar, Scott G.; Kabir, K.; Kaplan, F. Thomas D.; Kennedy, Stephen A.; Kessler, Michael W.; Kimball, Hervey L.; Kloen, Peter; Klostermann, Cyrus; Kohut, Georges; Kraan, G. A.; Kristan, Anze; Loebenberg, Mark I.; Malone, Kevin J.; Marsh, L.; Martineau, Paul A.; McAuliffe, John; McGraw, Iain; Mehta, Samir; Merchant, Milind; Metzger, Charles; Meylaerts, S. A.; Miller, Anna N.; Wolf, Jennifer Moriatis; Murachovsky, Joel; Murthi, Anand; Nancollas, Michael; Nolan, Betsy M.; Omara, Timothy; Omid, Reza; Ortiz, Jose A.; Overbeck, Joachim P.; Castillo, Alberto Pérez; Pesantez, Rodrigo; Polatsch, Daniel; Porcellini, G.; Prayson, Michael; Quell, M.; Ragsdell, Matthew M.; Reid, James G.; Reuver, J. M.; Richard, Marc J.; Richardson, Martin; Rizzo, Marco; Rowinski, Sergio; Rubio, Jorge; Guerrero, Carlos G. Sánchez; Satora, Wojciech; Schandelmaier, Peter; Scheer, Johan H.; Schmidt, Andrew; Schubkegel, Todd A.; Schulte, Leah M.; Schumer, Evan D.; Sears, Benjamin W.; Shafritz, Adam B.; Shortt, Nicholas L.; Siff, Todd; Silva, Dario Mejia; Smith, Raymond Malcolm; Spruijt, Sander; Stein, Jason A.; Pemovska, Emilija Stojkovska; Streubel, Philipp N.; Swigart, Carrie; Swiontkowski, Marc; Thomas, George; Tolo, Eric T.; Turina, Matthias; Tyllianakis, Minos; van den Bekerom, Michel P. J.; van der Heide, Huub; van de Sande, M. A. J.; van Eerten, P. V.; Verbeek, Diederik O. F.; Hoffmann, David Victoria; Vochteloo, A. J. H.; Wagenmakers, Robert; Wall, Christopher J.; Wallensten, Richard; Wascher, Daniel C.; Weiss, Lawrence; Wiater, J. Michael; Wills, Brian P. D.; Wint, Jeffrey; Wright, Thomas; Young, Jason P.; Zalavras, Charalampos; Zura, Robert D.; Zyto, Karol

    2014-01-01

    Objectives:There is substantial variation in the classification and management of scapula fractures. The first purpose of this study was to analyze the interobserver reliability of the OTA/AO classification and the New International Classification for Scapula Fractures. The second purpose was to

  4. The classification of osteonecrosis in patients with cancer: validation of a new radiological classification system

    International Nuclear Information System (INIS)

    Niinimäki, T.; Niinimäki, J.; Halonen, J.; Hänninen, P.; Harila-Saari, A.; Niinimäki, R.

    2015-01-01

    Aim: To validate a new, non-joint-specific radiological classification system that is suitable regardless of the site of the osteonecrosis (ON) in patients with cancer. Material and methods: Critical deficiencies in the existing ON classification systems were identified and a new, non-joint-specific radiological classification system was developed. Seventy-two magnetic resonance imaging (MRI) images of patients with cancer and ON lesions were graded, and the validation of the new system was performed by assessing inter- and intra-observer reliability. Results: Intra-observer reliability of ON grading was good or very good, with kappa values of 0.79–0.86. Interobserver agreement was lower but still good, with kappa values of 0.62–0.77. Ninety-eight percent of all intra- or interobserver differences were within one grade. Interobserver reliability of assessing the location of ON was very good, with kappa values of 0.93–0.98. Conclusion: All the available radiological ON classification systems are joint specific. This limitation has spurred the development of multiple systems, which has led to the insufficient use of classifications in ON studies among patients with cancer. The introduced radiological classification system overcomes the problem of joint-specificity, was found to be reliable, and can be used to classify all ON lesions regardless of the affected site. - Highlights: • Patients with cancer may have osteonecrosis lesions at multiple sites. • There is no non-joint-specific osteonecrosis classification available. • We introduced a new non-joint-specific osteonecrosis classification. • The validation was performed by assessing inter- and intra-observer reliability. • The classification was reliable and could be used regardless of the affected site.

  5. The reliability and reproducibility of the Hertel classification for comminuted proximal humeral fractures compared with the Neer classification

    NARCIS (Netherlands)

    Iordens, Gijs I. T.; Mahabier, Kiran C.; Buisman, Florian E.; Schep, Niels W. L.; Muradin, Galied S. R.; Beenen, Ludo F. M.; Patka, Peter; van Lieshout, Esther M. M.; den Hartog, Dennis

    2016-01-01

    The Neer classification is the most commonly used fracture classification system for proximal humeral fractures. Inter- and intra-observer agreement is limited, especially for comminuted fractures. A possibly more straightforward and reliable classification system is the Hertel classification. The

  6. Correcting Fallacies in Validity, Reliability, and Classification

    Science.gov (United States)

    Sijtsma, Klaas

    2009-01-01

    This article reviews three topics from test theory that continue to raise discussion and controversy and capture test theorists' and constructors' interest. The first topic concerns the discussion of the methodology of investigating and establishing construct validity; the second topic concerns reliability and its misuse, alternative definitions…

  7. Interrater reliability of a Pilates movement-based classification system.

    Science.gov (United States)

    Yu, Kwan Kenny; Tulloch, Evelyn; Hendrick, Paul

    2015-01-01

    To determine the interrater reliability for identification of a specific movement pattern using a Pilates Classification system. Videos of 5 subjects performing specific movement tasks were sent to raters trained in the DMA-CP classification system. Ninety-six raters completed the survey. Interrater reliability for the detection of a directional bias was excellent (Pi = 0.92, and K(free) = 0.89). Interrater reliability for classifying an individual into a specific subgroup was moderate (Pi = 0.64, K(free) = 0.55) however raters who had completed levels 1-4 of the DMA-CP training and reported using the assessment daily demonstrated excellent reliability (Pi = 0.89 and K(free) = 0.87). The reliability of the classification system demonstrated almost perfect agreement in determining the existence of a specific movement pattern and classifying into a subgroup for experienced raters. There was a trend for greater reliability associated with increased levels of training and experience of the raters. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. Novelty detection for breast cancer image classification

    Science.gov (United States)

    Cichosz, Pawel; Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz; Nowak, Robert M.; Okuniewski, Rafał; Oleszkiewicz, Witold

    2016-09-01

    Using classification learning algorithms for medical applications may require not only refined model creation techniques and careful unbiased model evaluation, but also detecting the risk of misclassification at the time of model application. This is addressed by novelty detection, which identifies instances for which the training set is not sufficiently representative and for which it may be safer to restrain from classification and request a human expert diagnosis. The paper investigates two techniques for isolated instance identification, based on clustering and one-class support vector machines, which represent two different approaches to multidimensional outlier detection. The prediction quality for isolated instances in breast cancer image data is evaluated using the random forest algorithm and found to be substantially inferior to the prediction quality for non-isolated instances. Each of the two techniques is then used to create a novelty detection model which can be combined with a classification model and used at the time of prediction to detect instances for which the latter cannot be reliably applied. Novelty detection is demonstrated to improve random forest prediction quality and argued to deserve further investigation in medical applications.

  9. Molecular Classification and Correlates in Colorectal Cancer

    OpenAIRE

    Ogino, Shuji; Goel, Ajay

    2008-01-01

    Molecular classification of colorectal cancer is evolving. As our understanding of colorectal carcinogenesis improves, we are incorporating new knowledge into the classification system. In particular, global genomic status [microsatellite instability (MSI) status and chromosomal instability (CIN) status] and epigenomic status [CpG island methylator phenotype (CIMP) status] play a significant role in determining clinical, pathological and biological characteristics of colorectal cancer. In thi...

  10. Reliability of classification for post-traumatic ankle osteoarthritis.

    Science.gov (United States)

    Claessen, Femke M A P; Meijer, Diederik T; van den Bekerom, Michel P J; Gevers Deynoot, Barend D J; Mallee, Wouter H; Doornberg, Job N; van Dijk, C Niek

    2016-04-01

    The purpose of this study was to identify the most reliable classification system for clinical outcome studies to categorize post-traumatic-fracture-osteoarthritis. A total of 118 orthopaedic surgeons and residents-gathered in the Ankle Platform Study Collaborative Science of Variation Group-evaluated 128 anteroposterior and lateral radiographs of patients after a bi- or trimalleolar ankle fracture on a Web-based platform in order to rate post-traumatic osteoarthritis according to the classification systems coined by (1) van Dijk, (2) Kellgren, and (3) Takakura. Reliability was evaluated with the use of the Siegel and Castellan's multirater kappa measure. Differences between classification systems were compared using the two-sample Z-test. Interobserver agreement of surgeons who participated in the survey was fair for the van Dijk osteoarthritis scale (k = 0.24), and poor for the Takakura (k = 0.19) and the Kellgren systems (k = 0.18) according to the categorical rating of Landis and Koch. This difference in one categorical rating was found to be significant (p osteoarthritis scale, and poor interobserver agreement for the Takakura and Kellgren osteoarthritis classification systems. Because of the low interobserver agreement for the van Dijk, Kellgren, and Takakura classification systems, those systems cannot be used for clinical decision-making. Development of diagnostic criteria on basis of consecutive patients, Level II.

  11. The reliability and validity of the Saliba Postural Classification System.

    Science.gov (United States)

    Collins, Cristiana Kahl; Johnson, Vicky Saliba; Godwin, Ellen M; Pappas, Evangelos

    2016-07-01

    To determine the reliability and validity of the Saliba Postural Classification System (SPCS). Two physical therapists classified pictures of 100 volunteer participants standing in their habitual posture for inter and intra-tester reliability. For validity, 54 participants stood on a force plate in a habitual and a corrected posture, while a vertical force was applied through the shoulders until the clinician felt a postural give. Data were extracted at the time the give was felt and at a time in the corrected posture that matched the peak vertical ground reaction force (VGRF) in the habitual posture. Inter-tester reliability demonstrated 75% agreement with a Kappa = 0.64 (95% CI = 0.524-0.756, SE = 0.059). Intra-tester reliability demonstrated 87% agreement with a Kappa = 0.8, (95% CI = 0.702-0.898, SE = 0.05) and 80% agreement with a Kappa = 0.706, (95% CI = 0.594-0818, SE = 0.057). The examiner applied a significantly higher (p < 0.001) peak vertical force in the corrected posture prior to a postural give when compared to the habitual posture. Within the corrected posture, the %VGRF was higher when the test was ongoing vs. when a postural give was felt (p < 0.001). The %VGRF was not different between the two postures when comparing the peaks (p = 0.214). The SPCS has substantial agreement for inter- and intra-tester reliability and is largely a valid postural classification system as determined by the larger vertical forces in the corrected postures. Further studies on the correlation between the SPCS and diagnostic classifications are indicated.

  12. Pathohistological classification systems in gastric cancer: diagnostic relevance and prognostic value.

    Science.gov (United States)

    Berlth, Felix; Bollschweiler, Elfriede; Drebber, Uta; Hoelscher, Arnulf H; Moenig, Stefan

    2014-05-21

    Several pathohistological classification systems exist for the diagnosis of gastric cancer. Many studies have investigated the correlation between the pathohistological characteristics in gastric cancer and patient characteristics, disease specific criteria and overall outcome. It is still controversial as to which classification system imparts the most reliable information, and therefore, the choice of system may vary in clinical routine. In addition to the most common classification systems, such as the Laurén and the World Health Organization (WHO) classifications, other authors have tried to characterize and classify gastric cancer based on the microscopic morphology and in reference to the clinical outcome of the patients. In more than 50 years of systematic classification of the pathohistological characteristics of gastric cancer, there is no sole classification system that is consistently used worldwide in diagnostics and research. However, several national guidelines for the treatment of gastric cancer refer to the Laurén or the WHO classifications regarding therapeutic decision-making, which underlines the importance of a reliable classification system for gastric cancer. The latest results from gastric cancer studies indicate that it might be useful to integrate DNA- and RNA-based features of gastric cancer into the classification systems to establish prognostic relevance. This article reviews the diagnostic relevance and the prognostic value of different pathohistological classification systems in gastric cancer.

  13. Characteristics and application study of AP1000 NPPs equipment reliability classification method

    International Nuclear Information System (INIS)

    Guan Gao

    2013-01-01

    AP1000 nuclear power plant applies an integrated approach to establish equipment reliability classification, which includes probabilistic risk assessment technique, maintenance rule administrative, power production reliability classification and functional equipment group bounding method, and eventually classify equipment reliability into 4 levels. This classification process and result are very different from classical RCM and streamlined RCM. It studied the characteristic of AP1000 equipment reliability classification approach, considered that equipment reliability classification should effectively support maintenance strategy development and work process control, recommended to use a combined RCM method to establish the future equipment reliability program of AP1000 nuclear power plants. (authors)

  14. Pathological Bases for a Robust Application of Cancer Molecular Classification

    Directory of Open Access Journals (Sweden)

    Salvador J. Diaz-Cano

    2015-04-01

    Full Text Available Any robust classification system depends on its purpose and must refer to accepted standards, its strength relying on predictive values and a careful consideration of known factors that can affect its reliability. In this context, a molecular classification of human cancer must refer to the current gold standard (histological classification and try to improve it with key prognosticators for metastatic potential, staging and grading. Although organ-specific examples have been published based on proteomics, transcriptomics and genomics evaluations, the most popular approach uses gene expression analysis as a direct correlate of cellular differentiation, which represents the key feature of the histological classification. RNA is a labile molecule that varies significantly according with the preservation protocol, its transcription reflect the adaptation of the tumor cells to the microenvironment, it can be passed through mechanisms of intercellular transference of genetic information (exosomes, and it is exposed to epigenetic modifications. More robust classifications should be based on stable molecules, at the genetic level represented by DNA to improve reliability, and its analysis must deal with the concept of intratumoral heterogeneity, which is at the origin of tumor progression and is the byproduct of the selection process during the clonal expansion and progression of neoplasms. The simultaneous analysis of multiple DNA targets and next generation sequencing offer the best practical approach for an analytical genomic classification of tumors.

  15. Intra- and Interobserver Reliability of Three Classification Systems for Hallux Rigidus.

    Science.gov (United States)

    Dillard, Sarita; Schilero, Christina; Chiang, Sharon; Pham, Peter

    2018-04-18

    There are over ten classification systems currently used in the staging of hallux rigidus. This results in confusion and inconsistency with radiographic interpretation and treatment. The reliability of hallux rigidus classification systems has not yet been tested. The purpose of this study was to evaluate intra- and interobserver reliability using three commonly used classifications for hallux rigidus. Twenty-one plain radiograph sets were presented to ten ACFAS board-certified foot and ankle surgeons. Each physician classified each radiograph based on clinical experience and knowledge according to the Regnauld, Roukis, and Hattrup and Johnson classification systems. The two-way mixed single-measure consistency intraclass correlation was used to calculate intra- and interrater reliability. The intrarater reliability of individual sets for the Roukis and Hattrup and Johnson classification systems was "fair to good" (Roukis, 0.62±0.19; Hattrup and Johnson, 0.62±0.28), whereas the intrarater reliability of individual sets for the Regnauld system bordered between "fair to good" and "poor" (0.43±0.24). The interrater reliability of the mean classification was "excellent" for all three classification systems. Conclusions Reliable and reproducible classification systems are essential for treatment and prognostic implications in hallux rigidus. In our study, Roukis classification system had the best intrarater reliability. Although there are various classification systems for hallux rigidus, our results indicate that all three of these classification systems show reliability and reproducibility.

  16. Gastric cancer: epidemiology, prevention, classification, and treatment

    Directory of Open Access Journals (Sweden)

    Sitarz R

    2018-02-01

    Full Text Available Robert Sitarz,1–3 Małgorzata Skierucha,1,2 Jerzy Mielko,1 G Johan A Offerhaus,3 Ryszard Maciejewski,2 Wojciech P Polkowski1 1Department of Surgical Oncology, Medical University of Lublin, Lublin, Poland; 2Department of Human Anatomy, Medical University of Lublin, Lublin, Poland; 3Department of Pathology, University Medical Centre, Utrecht, The Netherlands Abstract: Gastric cancer is the second most common cause of cancer-related deaths in the world, the epidemiology of which has changed within last decades. A trend of steady decline in gastric cancer incidence rates is the effect of the increased standards of hygiene, conscious nutrition, and Helicobacter pylori eradication, which together constitute primary prevention. Avoidance of gastric cancer remains a priority. However, patients with higher risk should be screened for early detection and chemoprevention. Surgical resection enhanced by standardized lymphadenectomy remains the gold standard in gastric cancer therapy. This review briefly summarizes the most important aspects of gastric cancers, which include epidemiology, risk factors, classification, diagnosis, prevention, and treatment. The paper is mostly addressed to physicians who are interested in updating the state of art concerning gastric carcinoma from easily accessible and credible source. Keywords: gastric cancer, epidemiology, classification, risk factors, treatment

  17. Intra- and interobserver reliability of glenoid fracture classifications by Ideberg, Euler and AO.

    Science.gov (United States)

    Gilbert, F; Eden, L; Meffert, R; Konietschke, F; Lotz, J; Bauer, L; Staab, W

    2018-03-27

    Representing 3%-5% of shoulder girdle injuries scapula fractures are rare. Furthermore, approximately 1% of scapula fractures are intraarticularfractures of the glenoid fossa. Because of uncertain fracture morphology and limited experience, the treatment of glenoid fossa fractures is difficult. The glenoid fracture classification by Ideberg (1984) and Euler (1996) is still commonly used in literature. In 2013 a new glenoid fracture classification was introduced by the AO. The purpose of this study was to examine the new AO classification in clinical practice in comparison with the classifications by Ideberg and Euler. In total CT images of 84 patients with glenoid fossa fractures from 2005 to 2018 were included. Parasagittal, paracoronary and axial reconstructions were examined according to the classifications of Ideberg, Euler and the AO by 3 investigators (orthopedic surgeon, radiologist, student of medicine) at three individual time settings. Inter- and intraobserver reliability of the three classification systems were ascertained by computing Inter- and Intraclass (ICCs) correlation coefficients using Spearman's rank correlation coefficient, 95%-confidence intervals as well as F-tests for correlation coefficients. Inter- and intraobserver reliability for the AO classification showed a perspicuous coherence (R = 0.74 and R = 0.79). Low to moderate intraobserver reliability for Ideberg (R = 0.46) and Euler classification (R = 0.41) was found. Furthermore, data show a low Interobserver reliability for both Ideberg and Euler classification (R reliability using AO is significantly higher than those using Ideberg and Euler (p reliable grading of glenoid fossa fractures with high inter- and intraobserver reliability in 84 patients using CT images. It should possibly be applied in order to enable a valid, reliable and consistent academic description of glenoid fossa fractures. The established classifications by Euler and Ideberg are not capable of

  18. Intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injuries.

    Science.gov (United States)

    Wangensteen, Arnlaug; Tol, Johannes L; Roemer, Frank W; Bahr, Roald; Dijkstra, H Paul; Crema, Michel D; Farooq, Abdulaziz; Guermazi, Ali

    2017-04-01

    To assess and compare the intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injury. Male athletes (n=40) with clinical diagnosis of acute hamstring injury and MRI ≤5days were selected from a prospective cohort. Two radiologists independently evaluated the MRIs using standardised scoring form including the modified Peetrons grading system, the Chan acute muscle strain injury classification and the British Athletics Muscle Injury Classification. Intra-and interrater reliability was assessed with linear weighted kappa (κ) or unweighted Cohen's κ and percentage agreement was calculated. We observed 'substantial' to 'almost perfect' intra- (κ range 0.65-1.00) and interrater reliability (κ range 0.77-1.00) with percentage agreement 83-100% and 88-100%, respectively, for severity gradings, overall anatomical sites and overall classifications for the three MRI systems. We observed substantial variability (κ range -0.05 to 1.00) for subcategories within the Chan classification and the British Athletics Muscle Injury Classification, however, the prevalence of positive scorings was low for some subcategories. The modified Peetrons grading system, overall Chan classification and overall British Athletics Muscle Injury Classification demonstrated 'substantial' to 'almost perfect' intra- and interrater reliability when scored by experienced radiologists. The intra- and interrater reliability for the anatomical subcategories within the classifications remains unclear. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injuries

    International Nuclear Information System (INIS)

    Wangensteen, Arnlaug; Tol, Johannes L.; Roemer, Frank W.; Bahr, Roald; Dijkstra, H. Paul; Crema, Michel D.; Farooq, Abdulaziz; Guermazi, Ali

    2017-01-01

    Highlights: • Three different MRI grading and classification systems for acute hamstring injuries are overall reliable. • Reliability for the subcategories within these MRI grading and classification systems remains, however, unclear. - Abstract: Objective: To assess and compare the intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injury. Methods: Male athletes (n = 40) with clinical diagnosis of acute hamstring injury and MRI ≤5 days were selected from a prospective cohort. Two radiologists independently evaluated the MRIs using standardised scoring form including the modified Peetrons grading system, the Chan acute muscle strain injury classification and the British Athletics Muscle Injury Classification. Intra-and interrater reliability was assessed with linear weighted kappa (κ) or unweighted Cohen's κ and percentage agreement was calculated. Results: We observed ‘substantial’ to ‘almost perfect’ intra- (κ range 0.65–1.00) and interrater reliability (κ range 0.77–1.00) with percentage agreement 83–100% and 88–100%, respectively, for severity gradings, overall anatomical sites and overall classifications for the three MRI systems. We observed substantial variability (κ range −0.05 to 1.00) for subcategories within the Chan classification and the British Athletics Muscle Injury Classification, however, the prevalence of positive scorings was low for some subcategories. Conclusions: The modified Peetrons grading system, overall Chan classification and overall British Athletics Muscle Injury Classification demonstrated ‘substantial' to ‘almost perfect' intra- and interrater reliability when scored by experienced radiologists. The intra- and interrater reliability for the anatomical subcategories within the classifications remains unclear.

  20. Intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injuries

    Energy Technology Data Exchange (ETDEWEB)

    Wangensteen, Arnlaug, E-mail: arnlaug.wangensteen@nih.no [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Oslo Sports Trauma Research Center, Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo (Norway); Tol, Johannes L., E-mail: johannes.tol@aspetar.com [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Amsterdam Center for Evidence Sports Medicine, Academic Medical Center (Netherlands); The Sports Physician Group, OLVG, Amsterdam (Netherlands); Roemer, Frank W. [Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, MA (United States); Department of Radiology, University of Erlangen-Nuremberg, Erlangen (Germany); Bahr, Roald [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Oslo Sports Trauma Research Center, Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo (Norway); Dijkstra, H. Paul [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Crema, Michel D. [Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, MA (United States); Department of Radiology, Saint-Antoine Hospital, University Paris VI, Paris (France); Farooq, Abdulaziz [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Guermazi, Ali [Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, MA (United States)

    2017-04-15

    Highlights: • Three different MRI grading and classification systems for acute hamstring injuries are overall reliable. • Reliability for the subcategories within these MRI grading and classification systems remains, however, unclear. - Abstract: Objective: To assess and compare the intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injury. Methods: Male athletes (n = 40) with clinical diagnosis of acute hamstring injury and MRI ≤5 days were selected from a prospective cohort. Two radiologists independently evaluated the MRIs using standardised scoring form including the modified Peetrons grading system, the Chan acute muscle strain injury classification and the British Athletics Muscle Injury Classification. Intra-and interrater reliability was assessed with linear weighted kappa (κ) or unweighted Cohen's κ and percentage agreement was calculated. Results: We observed ‘substantial’ to ‘almost perfect’ intra- (κ range 0.65–1.00) and interrater reliability (κ range 0.77–1.00) with percentage agreement 83–100% and 88–100%, respectively, for severity gradings, overall anatomical sites and overall classifications for the three MRI systems. We observed substantial variability (κ range −0.05 to 1.00) for subcategories within the Chan classification and the British Athletics Muscle Injury Classification, however, the prevalence of positive scorings was low for some subcategories. Conclusions: The modified Peetrons grading system, overall Chan classification and overall British Athletics Muscle Injury Classification demonstrated ‘substantial' to ‘almost perfect' intra- and interrater reliability when scored by experienced radiologists. The intra- and interrater reliability for the anatomical subcategories within the classifications remains unclear.

  1. Inter- and intraobserver reliability of the MTM-classification for proximal humeral fractures

    DEFF Research Database (Denmark)

    Bahrs, Christian; Schmal, Hagen; Lingenfelter, Erich

    2008-01-01

    tool. METHODS: Three observers classified plain radiographs of 22 fractures using both a simple version (fracture displacement, number of parts) and an extensive version (individual topographic fracture type and morphology) of the MTM classification. Kappa-statistics were used to determine reliability....... RESULTS: An acceptable reliability was found for the simple version classifying fracture displacement and fractured main parts. Fair interobserver agreement was found for the extensive version with individual topographic fracture type and morphology. CONCLUSION: Although the MTM-classification covers...

  2. Perceptual and Acoustic Reliability Estimates for the Speech Disorders Classification System (SDCS)

    Science.gov (United States)

    Shriberg, Lawrence D.; Fourakis, Marios; Hall, Sheryl D.; Karlsson, Heather B.; Lohmeier, Heather L.; McSweeny, Jane L.; Potter, Nancy L.; Scheer-Cohen, Alison R.; Strand, Edythe A.; Tilkens, Christie M.; Wilson, David L.

    2010-01-01

    A companion paper describes three extensions to a classification system for paediatric speech sound disorders termed the Speech Disorders Classification System (SDCS). The SDCS uses perceptual and acoustic data reduction methods to obtain information on a speaker's speech, prosody, and voice. The present paper provides reliability estimates for…

  3. Reliability testing of two classification systems for osteoarthritis and post-traumatic arthritis of the elbow.

    Science.gov (United States)

    Amini, Michael H; Sykes, Joshua B; Olson, Stephen T; Smith, Richard A; Mauck, Benjamin M; Azar, Frederick M; Throckmorton, Thomas W

    2015-03-01

    The severity of elbow arthritis is one of many factors that surgeons must evaluate when considering treatment options for a given patient. Elbow surgeons have historically used the Broberg and Morrey (BM) and Hastings and Rettig (HR) classification systems to radiographically stage the severity of post-traumatic arthritis (PTA) and primary osteoarthritis (OA). We proposed to compare the intraobserver and interobserver reliability between systems for patients with either PTA or OA. The radiographs of 45 patients were evaluated at least 2 weeks apart by 6 evaluators of different levels of training. Intraobserver and interobserver reliability were calculated by Spearman correlation coefficients with 95% confidence intervals. Agreement was considered almost perfect for coefficients >0.80 and substantial for coefficients of 0.61 to 0.80. In patients with both PTA and OA, intraobserver reliability and interobserver reliability were substantial, with no difference between classification systems. There were no significant differences in intraobserver or interobserver reliability between attending physicians and trainees for either classification system (all P > .10). The presence of fracture implants did not affect reliability in the BM system but did substantially worsen reliability in the HR system (intraobserver P = .04 and interobserver P = .001). The BM and HR classifications both showed substantial intraobserver and interobserver reliability for PTA and OA. Training level differences did not affect reliability for either system. Both trainees and fellowship-trained surgeons may easily and reliably apply each classification system to the evaluation of primary elbow OA and PTA, although the HR system was less reliable in the presence of fracture implants. Copyright © 2015 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

  4. The influence of spine surgeons' experience on the classification and intraobserver reliability of the novel AOSpine thoracolumbar spine injury classification system : an international study

    NARCIS (Netherlands)

    Sadiqi, Said; Oner, F. Cumhur; Dvorak, Marcel F.; Aarabi, Bizhan; Schroeder, Gregory D.; Vaccaro, Alexander R.

    2015-01-01

    Study Design. International validation study. Objective. To investigate the influence of the spine surgeons' level of experience on the intraobserver reliability of the novel AOSpine Thoracolumbar Spine Injury Classification system, and the appropriate classification according to this system.

  5. Is our Ground-Truth for Traffic Classification Reliable?

    DEFF Research Database (Denmark)

    Carela-Español, Valentín; Bujlow, Tomasz; Barlet-Ros, Pere

    2014-01-01

    . In order to evaluate these tools we have carefully built a labeled dataset of more than 500 000 flows, which contains traffic from popular applications. Our results present PACE, a commercial tool, as the most reliable solution for ground-truth generation. However, among the open-source tools available...

  6. Intra- and interobserver reliability of the Eaton classification for trapeziometacarpal arthritis: a systematic review.

    Science.gov (United States)

    Berger, Aaron J; Momeni, Arash; Ladd, Amy L

    2014-04-01

    Trapeziometacarpal, or thumb carpometacarpal (CMC), arthritis is a common problem with a variety of treatment options. Although widely used, the Eaton radiographic staging system for CMC arthritis is of questionable clinical utility, as disease severity does not predictably correlate with symptoms or treatment recommendations. A possible reason for this is that the classification itself may not be reliable, but the literature on this has not, to our knowledge, been systematically reviewed. We therefore performed a systematic review to determine the intra- and interobserver reliability of the Eaton staging system. We systematically reviewed English-language studies published between 1973 and 2013 to assess the degree of intra- and interobserver reliability of the Eaton classification for determining the stage of trapeziometacarpal joint arthritis and pantrapezial arthritis based on plain radiographic imaging. Search engines included: PubMed, Scopus(®), and CINAHL. Four studies, which included a total of 163 patients, met our inclusion criteria and were evaluated. The level of evidence of the studies included in this analysis was determined using the Oxford Centre for Evidence Based Medicine Levels of Evidence Classification by two independent observers. A limited number of studies have been performed to assess intra- and interobserver reliability of the Eaton classification system. The four studies included were determined to be Level 3b. These studies collectively indicate that the Eaton classification demonstrates poor to fair interobserver reliability (kappa values: 0.11-0.56) and fair to moderate intraobserver reliability (kappa values: 0.54-0.657). Review of the literature demonstrates that radiographs assist in the assessment of CMC joint disease, but there is not a reliable system for classification of disease severity. Currently, diagnosis and treatment of thumb CMC arthritis are based on the surgeon's qualitative assessment combining history, physical

  7. Lauren classification and individualized chemotherapy in gastric cancer

    OpenAIRE

    MA, JUNLI; SHEN, HONG; KAPESA, LINDA; ZENG, SHAN

    2016-01-01

    Gastric cancer is one of the most common malignancies worldwide. During the last 50 years, the histological classification of gastric carcinoma has been largely based on Lauren's criteria, in which gastric cancer is classified into two major histological subtypes, namely intestinal type and diffuse type adenocarcinoma. This classification was introduced in 1965, and remains currently widely accepted and employed, since it constitutes a simple and robust classification approach. The two histol...

  8. The Reliability of Classifications of Proximal Femoral Fractures with 3-Dimensional Computed Tomography: The New Concept of Comprehensive Classification

    Directory of Open Access Journals (Sweden)

    Hiroaki Kijima

    2014-01-01

    Full Text Available The reliability of proximal femoral fracture classifications using 3DCT was evaluated, and a comprehensive “area classification” was developed. Eleven orthopedists (5–26 years from graduation classified 27 proximal femoral fractures at one hospital from June 2013 to July 2014 based on preoperative images. Various classifications were compared to “area classification.” In “area classification,” the proximal femur is divided into 4 areas with 3 boundary lines: Line-1 is the center of the neck, Line-2 is the border between the neck and the trochanteric zone, and Line-3 links the inferior borders of the greater and lesser trochanters. A fracture only in the first area was classified as a pure first area fracture; one in the first and second area was classified as a 1-2 type fracture. In the same way, fractures were classified as pure 2, 3-4, 1-2-3, and so on. “Area classification” reliability was highest when orthopedists with varying experience classified proximal femoral fractures using 3DCT. Other classifications cannot classify proximal femoral fractures if they exceed each classification’s particular zones. However, fractures that exceed the target zones are “dangerous” fractures. “Area classification” can classify such fractures, and it is therefore useful for selecting osteosynthesis methods.

  9. An Adaptive Classification Strategy for Reliable Locomotion Mode Recognition

    Directory of Open Access Journals (Sweden)

    Ming Liu

    2017-09-01

    Full Text Available Algorithms for locomotion mode recognition (LMR based on surface electromyography and mechanical sensors have recently been developed and could be used for the neural control of powered prosthetic legs. However, the variations in input signals, caused by physical changes at the sensor interface and human physiological changes, may threaten the reliability of these algorithms. This study aimed to investigate the effectiveness of applying adaptive pattern classifiers for LMR. Three adaptive classifiers, i.e., entropy-based adaptation (EBA, LearnIng From Testing data (LIFT, and Transductive Support Vector Machine (TSVM, were compared and offline evaluated using data collected from two able-bodied subjects and one transfemoral amputee. The offline analysis indicated that the adaptive classifier could effectively maintain or restore the performance of the LMR algorithm when gradual signal variations occurred. EBA and LIFT were recommended because of their better performance and higher computational efficiency. Finally, the EBA was implemented for real-time human-in-the-loop prosthesis control. The online evaluation showed that the applied EBA effectively adapted to changes in input signals across sessions and yielded more reliable prosthesis control over time, compared with the LMR without adaptation. The developed novel adaptive strategy may further enhance the reliability of neurally-controlled prosthetic legs.

  10. Interobserver and intraobserver reliability of radiographic classification of acromioclavicular joint dislocations.

    Science.gov (United States)

    Ringenberg, Jonathan D; Foughty, Zachary; Hall, Adam D; Aldridge, J Mack; Wilson, Joseph B; Kuremsky, Marshall A

    2018-03-01

    The classification and treatment of acromioclavicular (AC) joint dislocations remain controversial. The purpose of this study was to determine the interobserver and intraobserver reliability of the Rockwood classification system. We hypothesized poor interobserver and intraobserver reliability, limiting the role of the Rockwood classification system in determining severity of AC joint dislocations and accurately guiding treatment decisions. We identified 200 patients with AC joint injuries using the International Classification of Diseases, Ninth Revision code 831.04. Fifty patients met inclusion criteria. Deidentified radiographs were compiled and presented to 6 fellowship-trained upper extremity orthopedic surgeons. The surgeons classified each patient into 1 of the 6 classification types described by Rockwood. A second review was performed several months later by 2 surgeons. A κ value was calculated to determine the interobserver and intraobserver reliability. The interobserver and intraobserver κ values were fair (κ = 0.278) and moderate (κ = 0.468), respectively. Interobserver results showed that 4 of the 50 radiographic images had a unanimous classification. Intraobserver results for the 2 surgeons showed that 18 of the 50 images were rated the same on second review by the first surgeon and 38 of the 50 images were rated the same on second review by the second surgeon. We found that the Rockwood classification system has limited interobserver and intraobserver reliability. We believe that unreliable classification may account for some of the inconsistent treatment outcomes among patients with similarly classified injuries. We suggest that a better classification system is needed to use radiographic imaging for diagnosis and treatment of AC joint dislocations. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

  11. Reliability of a treatment-based classification system for subgrouping people with low back pain.

    Science.gov (United States)

    Henry, Sharon M; Fritz, Julie M; Trombley, Andrea R; Bunn, Janice Y

    2012-09-01

    Observational, cross-sectional reliability study. To examine the interrater reliability of novice raters in their use of the treatment-based classification (TBC) system for low back pain and to explore the patterns of disagreement in classification errors. Although the interrater reliability of individual test items in the TBC system is moderate to good, some error persists in classification decision making. Understanding which classification errors are common could direct further refinement of the TBC system. Using previously recorded patient data (n = 24), 12 novice raters classified patients according to the TBC schema. These classification results were combined with those of 7 other raters, allowing examination of the overall agreement using the kappa statistic, as well as agreement/disagreement among pairwise comparisons in classification assignments. A chi-square test examined differences in percent agreement between the novice and more experienced raters and differences in classification distributions between these 2 groups of raters. Among 12 novice raters, there was 80.9% agreement in the pairs of classification (κ = 0.62; 95% confidence interval: 0.59, 0.65) and an overall 75.5% agreement (κ = 0.57; 95% confidence interval: 0.55, 0.69) for the combined data set. Raters were least likely to agree on a classification of stabilization (77.5% agreement). The overall percentage of pairwise classification judgments that disagreed was 24.5%, with the most common disagreement being between manipulation and stabilization (11.0%), followed by a mismatch between stabilization and specific exercise (8.2%). Additional refinement is needed to reduce rater disagreement that persists in the TBC decision-making algorithm, particularly in the stabilization category. J Orthop Sports Phys Ther 2012;42(9):797-805, Epub 7 June 2012. doi:10.2519/jospt.2012.4078.

  12. Cancer classification in the genomic era: five contemporary problems.

    Science.gov (United States)

    Song, Qingxuan; Merajver, Sofia D; Li, Jun Z

    2015-10-19

    Classification is an everyday instinct as well as a full-fledged scientific discipline. Throughout the history of medicine, disease classification is central to how we develop knowledge, make diagnosis, and assign treatment. Here, we discuss the classification of cancer and the process of categorizing cancer subtypes based on their observed clinical and biological features. Traditionally, cancer nomenclature is primarily based on organ location, e.g., "lung cancer" designates a tumor originating in lung structures. Within each organ-specific major type, finer subgroups can be defined based on patient age, cell type, histological grades, and sometimes molecular markers, e.g., hormonal receptor status in breast cancer or microsatellite instability in colorectal cancer. In the past 15+ years, high-throughput technologies have generated rich new data regarding somatic variations in DNA, RNA, protein, or epigenomic features for many cancers. These data, collected for increasingly large tumor cohorts, have provided not only new insights into the biological diversity of human cancers but also exciting opportunities to discover previously unrecognized cancer subtypes. Meanwhile, the unprecedented volume and complexity of these data pose significant challenges for biostatisticians, cancer biologists, and clinicians alike. Here, we review five related issues that represent contemporary problems in cancer taxonomy and interpretation. (1) How many cancer subtypes are there? (2) How can we evaluate the robustness of a new classification system? (3) How are classification systems affected by intratumor heterogeneity and tumor evolution? (4) How should we interpret cancer subtypes? (5) Can multiple classification systems co-exist? While related issues have existed for a long time, we will focus on those aspects that have been magnified by the recent influx of complex multi-omics data. Exploration of these problems is essential for data-driven refinement of cancer classification

  13. Reliability of McConnell's classification of patellar orientation in symptomatic and asymptomatic subjects.

    Science.gov (United States)

    Watson, C J; Propps, M; Galt, W; Redding, A; Dobbs, D

    1999-07-01

    Test-retest reliability study with blinded testers. To determine the intratester reliability of the McConnell classification system and to determine whether the intertester reliability of this system would be improved by one-on-one training of the testers, increasing the variability and numbers of subjects, blinding the testers to the absence or presence of patellofemoral pain syndrome, and adhering to the McConnell classification system as it is taught in the "McConnell Patellofemoral Treatment Plan" continuing education course. The McConnell classification system is currently used by physical therapy clinicians to quantify static patellar orientation. The measurements generated from this system purportedly guide the therapist in the application of patellofemoral tape and in assessment of the efficacy of treatment interventions on changing patellar orientation. Fifty-six subjects (age range, 21-65 years) provided a total of 101 knees for assessment. Seventy-six knees did not produce symptoms. A researcher who did not participate in the measuring process determined that 17 subjects had patellofemoral pain syndrome in 25 knees. Two testers concurrently measured static patellar orientation (anterior/posterior and medial/lateral tilt, medial/lateral glide, and patellar rotation) on subjects, using the McConnell classification system. Repeat measures were performed 3-7 days later. A kappa (kappa) statistic was used to assess the degree of agreement within each tester and between testers. The kappa coefficients for intratester reliability varied from -0.06 to 0.35. Intertester reliability ranged from -0.03 to 0.19. The McConnell classification system, in its current form, does not appear to be very reliable. Intratester reliability ranged from poor to fair, and intertester reliability was poor to slight. This system should not be used as a measurement tool or as a basis for treatment decisions.

  14. Osteochondritis dissecans of the humeral capitellum: reliability of four classification systems using radiographs and computed tomography.

    Science.gov (United States)

    Claessen, Femke M A P; van den Ende, Kimberly I M; Doornberg, Job N; Guitton, Thierry G; Eygendaal, Denise; van den Bekerom, Michel P J

    2015-10-01

    The radiographic appearance of osteochondritis dissecans (OCD) of the humeral capitellum varies according to the stage of the lesion. It is important to evaluate the stage of OCD lesion carefully to guide treatment. We compared the interobserver reliability of currently used classification systems for OCD of the humeral capitellum to identify the most reliable classification system. Thirty-two musculoskeletal radiologists and orthopaedic surgeons specialized in elbow surgery from several countries evaluated anteroposterior and lateral radiographs and corresponding computed tomography (CT) scans of 22 patients to classify the stage of OCD of the humeral capitellum according to the classification systems developed by (1) Minami, (2) Berndt and Harty, (3) Ferkel and Sgaglione, and (4) Anderson on a Web-based study platform including a Digital Imaging and Communications in Medicine viewer. Magnetic resonance imaging was not evaluated as part of this study. We measured agreement among observers using the Siegel and Castellan multirater κ. All OCD classification systems, except for Berndt and Harty, which had poor agreement among observers (κ = 0.20), had fair interobserver agreement: κ was 0.27 for the Minami, 0.23 for Anderson, and 0.22 for Ferkel and Sgaglione classifications. The Minami Classification was significantly more reliable than the other classifications (P reliable for classifying different stages of OCD of the humeral capitellum. However, it is unclear whether radiographic evidence of OCD of the humeral capitellum, as categorized by the Minami Classification, guides treatment in clinical practice as a result of this fair agreement. Copyright © 2015 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

  15. An interobserver reliability comparison between the Orthopaedic Trauma Association's open fracture classification and the Gustilo and Anderson classification.

    Science.gov (United States)

    Ghoshal, A; Enninghorst, N; Sisak, K; Balogh, Z J

    2018-02-01

    To evaluate interobserver reliability of the Orthopaedic Trauma Association's open fracture classification system (OTA-OFC). Patients of any age with a first presentation of an open long bone fracture were included. Standard radiographs, wound photographs, and a short clinical description were given to eight orthopaedic surgeons, who independently evaluated the injury using both the Gustilo and Anderson (GA) and OTA-OFC classifications. The responses were compared for variability using Cohen's kappa. The overall interobserver agreement was ĸ = 0.44 for the GA classification and ĸ = 0.49 for OTA-OFC, which reflects moderate agreement (0.41 to 0.60) for both classifications. The agreement in the five categories of OTA-OFC was: for skin, ĸ = 0.55 (moderate); for muscle, ĸ = 0.44 (moderate); for arterial injury, ĸ = 0.74 (substantial); for contamination, ĸ = 0.35 (fair); and for bone loss, ĸ = 0.41 (moderate). Although the OTA-OFC, with similar interobserver agreement to GA, offers a more detailed description of open fractures, further development may be needed to make it a reliable and robust tool. Cite this article: Bone Joint J 2018;100-B:242-6. ©2018 The British Editorial Society of Bone & Joint Surgery.

  16. Light-water reactors reference system classification for the European reliability data system (ERDS)

    International Nuclear Information System (INIS)

    Melis, M.; Mancini, G.

    1982-01-01

    The reference system classification represents a basic stage in the organization of the European reliability data system (ERDS) for light-water reactors, a project actually in development at the Joint Research Centre, Ispra. This project is concerned with operational reliability data collection from the various ''national'' data banks, and centralization in a European reliability data system, so improving the significance of the resulting reliability evaluations. In the framework of the ERDS project, the reference system classification provides a LWR functional break-down and represents a plant-unique identification in the process of homogenization of event-data coming from the various ''national'' organizations. The report, after a brief description of the main objectives of the ERDS project, reviews the criteria followed in the elaboration of the reference system classification; then the detailed classification is presented. The nuclear power station is subdivided in about 180 systems. To each system a sheet is associated, containing: a comprehensive description of system-functions and boundaries; a descritpion of the plant operating mode, linked to the various system functions; a list of the main interface system; and finally, a list of the main components, including type and safety classification

  17. Reliability and reproducibility analysis of the AOSpine thoracolumbar spine injury classification system by Chinese spinal surgeons.

    Science.gov (United States)

    Cheng, Jie; Liu, Peng; Sun, Dong; Qin, Tingzheng; Ma, Zikun; Liu, Jingpei

    2017-05-01

    The objective of this study was to analyze the interobserver reliability and intraobserver reproducibility of the new AOSpine thoracolumbar spine injury classification system in young Chinese orthopedic surgeons with different levels of experience in spinal trauma. Previous reports suggest that the new AOSpine thoracolumbar spine injury classification system demonstrates acceptable interobserver reliability and intraobserver reproducibility. However, there are few studies in Asia, especially in China. The AOSpine thoracolumbar spine injury classification system was applied to 109 patients with acute, traumatic thoracolumbar spinal injuries by two groups of spinal surgeons with different levels of clinical experience. The Kappa coefficient was used to determine interobserver reliability and intraobserver reproducibility. The overall Kappa coefficient for all cases was 0.362, which represents fair reliability. The Kappa statistic was 0.385 for A-type injuries and 0.292 for B-type injuries, which represents fair reliability, and 0.552 for C-type injuries, which represents moderate reliability. The Kappa coefficient for intraobserver reproducibility was 0.442 for A-type injuries, 0.485 for B-type injuries, and 0.412 for C-type injuries. These values represent moderate reproducibility for all injury types. The raters in Group A provided significantly better interobserver reliability than Group B (P < 0.05). There were no between-group differences in intraobserver reproducibility. This study suggests that the new AO spine injury classification system may be applied in day-to-day clinical practice in China following extensive training of healthcare providers. Further prospective studies in different healthcare providers and clinical settings are essential for validation of this classification system and to assess its utility.

  18. Lauren classification and individualized chemotherapy in gastric cancer.

    Science.gov (United States)

    Ma, Junli; Shen, Hong; Kapesa, Linda; Zeng, Shan

    2016-05-01

    Gastric cancer is one of the most common malignancies worldwide. During the last 50 years, the histological classification of gastric carcinoma has been largely based on Lauren's criteria, in which gastric cancer is classified into two major histological subtypes, namely intestinal type and diffuse type adenocarcinoma. This classification was introduced in 1965, and remains currently widely accepted and employed, since it constitutes a simple and robust classification approach. The two histological subtypes of gastric cancer proposed by the Lauren classification exhibit a number of distinct clinical and molecular characteristics, including histogenesis, cell differentiation, epidemiology, etiology, carcinogenesis, biological behaviors and prognosis. Gastric cancer exhibits varied sensitivity to chemotherapy drugs and significant heterogeneity; therefore, the disease may be a target for individualized therapy. The Lauren classification may provide the basis for individualized treatment for advanced gastric cancer, which is increasingly gaining attention in the scientific field. However, few studies have investigated individualized treatment that is guided by pathological classification. The aim of the current review is to analyze the two major histological subtypes of gastric cancer, as proposed by the Lauren classification, and to discuss the implications of this for personalized chemotherapy.

  19. Reliability of classification of cerebral palsy in low-birthweight children in four countries

    NARCIS (Netherlands)

    Paneth, N.; Qiu, H.; Rosenbaum, P.; Saigal, S.; Bishai, S.; Jetton, J.; Ouden, L. den; Broyles, S.; Tyson, J.; Kugler, K.

    2003-01-01

    The reliability of classification of cerebral palsy (CP) in low-birthweight children was assessed by using clinical and research study records sampled from population-based cohort studies in the USA, the Netherlands, Canada, and Germany. Records of neurological examination findings and functional

  20. Inter- and intrarater reliability of the Chicago Classification in pediatric high-resolution esophageal manometry recordings

    NARCIS (Netherlands)

    Singendonk, M. M. J.; Smits, M. J.; Heijting, I. E.; van Wijk, M. P.; Nurko, S.; Rosen, R.; Weijenborg, P. W.; Abu-Assi, R.; Hoekman, D. R.; Kuizenga-Wessel, S.; Seiboth, G.; Benninga, M. A.; Omari, T. I.; Kritas, S.

    2015-01-01

    The Chicago Classification (CC) facilitates interpretation of high-resolution manometry (HRM) recordings. Application of this adult based algorithm to the pediatric population is unknown. We therefore assessed intra and interrater reliability of software-based CC diagnosis in a pediatric cohort.

  1. Rater Reliability of the Hardy Classification for Pituitary Adenomas in the Magnetic Resonance Imaging Era.

    Science.gov (United States)

    Mooney, Michael A; Hardesty, Douglas A; Sheehy, John P; Bird, C Roger; Chapple, Kristina; White, William L; Little, Andrew S

    2017-10-01

    Objectives  The Hardy classification is used to classify pituitary tumors for clinical and research purposes. The scale was developed using lateral skull radiographs and encephalograms, and its reliability has not been evaluated in the magnetic resonance imaging (MRI) era. Design  Fifty preoperative MRI scans of biopsy-proven pituitary adenomas using the sellar invasion and suprasellar extension components of the Hardy scale were reviewed. Setting  This study was a cohort study set at a single institution. Participants  There were six independent raters. Main Outcome Measures  The main outcome measures of this study were interrater reliability, intrarater reliability, and percent agreement. Results  Overall interrater reliability of both Hardy subscales on MRI was strong. However, reliability of the intermediate scores was weak, and percent agreement among raters was poor (12-16%) using the full scales. Dichotomizing the scale into clinically useful groups maintained strong interrater reliability for the sellar invasion scale and increased the percent agreement for both scales. Conclusion  This study raises important questions about the reliability of the original Hardy classification. Editing the measure to a clinically relevant dichotomous scale simplifies the rating process and may be useful for preoperative tumor characterization in the MRI era. Future research studies should use the dichotomized Hardy scale (sellar invasion Grades 0-III versus Grade IV, suprasellar extension Types 0-C versus Type D).

  2. The reliability of AO classification for distal radius fracture, using CT findings

    International Nuclear Information System (INIS)

    Nakanishi, Yasuaki; Ono, Hiroshi; Furuta, Kazuhiko; Fujitani, Ryoutarou; Ota, Hiroyoshi

    2006-01-01

    The purpose of this study was to assess the reliability of the AO (Association for the Study of Internal Fixation) classification of distal radius fracture, using plain radiographs and 2 cross-sectional computed tomographic (CT) surface images. Five observers independently classified 32 distal radius fractures into 9 groups under AO classification. We established 4 methods for observation. First, using only two-directional radiographs; second, four-directional radiographs; third, CT (axial view) with four-directional radiographs; and fourth, CT (axial and sagittal views) with four-directional radiographs. Kappa statistics were used to establish the relative level of agreement between the observers. Interobserver reliability was poor in both first and second methods in which only plain radiographs were used (κ=0.30 and 0.23, respectively). Furthermore, reliability did not increase in the third method with the addition of 1 CT surface image (κ=0.29). In the fourth method, with the addition of 2 cross-sectional CT surface images, the reliability increased to a moderate level (κ=0.44). Interobserver reliability of the AO system of the classification of distal radius fractures was observed on using 2 cross-sectional CT surface images with four-directional radiographs. (author)

  3. Reliability of the Crowe und Hartofilakidis classifications used in the assessment of the adult dysplastic hip

    Energy Technology Data Exchange (ETDEWEB)

    Decking, Ralf; Brunner, Alexander; Puhl, Wolfhart [University of Ulm, Orthopaedic Department, RKU, Ulm (Germany); Decking, Jens [Johannes Gutenberg University School of Medicine, Department of Orthopaedic Surgery, Mainz (Germany); Guenther, Klaus-Peter [University of Ulm, Orthopaedic Department, RKU, Ulm (Germany); University-Hospital Carl Gustav Carus, Department of Orthopaedics, Dresden (Germany)

    2006-05-15

    To assess the inter-observer and intra-observer reliability of two commonly used radiographic classification systems in the evaluation of hip dysplasia in skeletally mature adults. Three observers with different levels of training independently classified 62 dysplastic hips on 51 standard anteriorposterior pelvis radiographs according to the criteria defined by Crowe and by Hartofilakidis. To assess intra-observer reliability, the same radiographs were reviewed 3 months later by the same observers. At the time of the radiographic examination, the mean age of the 51 patients had been 54 years (range 18-82 years). A high correlation concerning the inter- and intra-observer reliability of both systems was demonstrated. Inter-observer reliability displayed a weighted kappa coefficient of 0.82 for the Crowe and 0.75 for the Hartofilakidis classification. Intra-observer reliability showed a kappa coefficient of 0.86 and 0.79, respectively. Both classification systems can be recommended to compare collectives of adult patients with congenital dysplasia of the hip. However, for future clinical practice, it would be advisable to agree on one universally accepted system as a standard in the literature. (orig.)

  4. Reliability of the Crowe und Hartofilakidis classifications used in the assessment of the adult dysplastic hip

    International Nuclear Information System (INIS)

    Decking, Ralf; Brunner, Alexander; Puhl, Wolfhart; Decking, Jens; Guenther, Klaus-Peter

    2006-01-01

    To assess the inter-observer and intra-observer reliability of two commonly used radiographic classification systems in the evaluation of hip dysplasia in skeletally mature adults. Three observers with different levels of training independently classified 62 dysplastic hips on 51 standard anteriorposterior pelvis radiographs according to the criteria defined by Crowe and by Hartofilakidis. To assess intra-observer reliability, the same radiographs were reviewed 3 months later by the same observers. At the time of the radiographic examination, the mean age of the 51 patients had been 54 years (range 18-82 years). A high correlation concerning the inter- and intra-observer reliability of both systems was demonstrated. Inter-observer reliability displayed a weighted kappa coefficient of 0.82 for the Crowe and 0.75 for the Hartofilakidis classification. Intra-observer reliability showed a kappa coefficient of 0.86 and 0.79, respectively. Both classification systems can be recommended to compare collectives of adult patients with congenital dysplasia of the hip. However, for future clinical practice, it would be advisable to agree on one universally accepted system as a standard in the literature. (orig.)

  5. Interobserver and intraobserver reliability of two classification systems for intra-articular calcaneal fractures.

    Science.gov (United States)

    Lauder, Anthony J; Inda, David J; Bott, Aaron M; Clare, Michael P; Fitzgibbons, Timothy C; Mormino, Matthew A

    2006-04-01

    For a fracture classification to be useful it must provide prognostic significance, interobserver reliability, and intraobserver reproducibility. Most studies have found reliability and reproducibility to be poor for fracture classification schemes. The purpose of this study was to evaluate the interobserver and intraobserver reliability of the Sanders and Crosby-Fitzgibbons classification systems, two commonly used methods for classifying intra-articular calcaneal fractures. Twenty-five CT scans of intra-articular calcaneal fractures occurring at one trauma center were reviewed. The CT images were presented to eight observers (two orthopaedic surgery chief residents, two foot and ankle fellows, two fellowship-trained orthopaedic trauma surgeons, and two fellowship-trained foot and ankle surgeons) on two separate occasions 8 weeks apart. On each viewing, observers were asked to classify the fractures according to both the Sanders and Crosby-Fitzgibbons systems. Interobserver reliability and intraobserver reproducibility were assessed with computer-generated kappa statistics (SAS software; SAS Institute Inc., Cary, North Carolina). Total unanimity (eight of eight observers assigned the same fracture classification) was achieved only 24% (six of 25) of the time with the Sanders system and 36% (nine of 25) of the time with the Crosby-Fitzgibbons scheme. Interobserver reliability for the Sanders classification method reached a moderate (kappa = 0.48, 0.50) level of agreement, when the subclasses were included. The agreement level increased but remained in the moderate (kappa = 0.55, 0.55) range when the subclasses were excluded. Interobserver agreement reached a substantial (kappa = 0.63, 0.63) level with the Crosby-Fitzgibbons system. Intraobserver reproducibility was better for both schemes. The Sanders system with subclasses included reached moderate (kappa = 0.57) agreement, while ignoring the subclasses brought agreement into the substantial (kappa = 0.77) range

  6. Developing a contributing factor classification scheme for Rasmussen's AcciMap: Reliability and validity evaluation.

    Science.gov (United States)

    Goode, N; Salmon, P M; Taylor, N Z; Lenné, M G; Finch, C F

    2017-10-01

    One factor potentially limiting the uptake of Rasmussen's (1997) Accimap method by practitioners is the lack of a contributing factor classification scheme to guide accident analyses. This article evaluates the intra- and inter-rater reliability and criterion-referenced validity of a classification scheme developed to support the use of Accimap by led outdoor activity (LOA) practitioners. The classification scheme has two levels: the system level describes the actors, artefacts and activity context in terms of 14 codes; the descriptor level breaks the system level codes down into 107 specific contributing factors. The study involved 11 LOA practitioners using the scheme on two separate occasions to code a pre-determined list of contributing factors identified from four incident reports. Criterion-referenced validity was assessed by comparing the codes selected by LOA practitioners to those selected by the method creators. Mean intra-rater reliability scores at the system (M = 83.6%) and descriptor (M = 74%) levels were acceptable. Mean inter-rater reliability scores were not consistently acceptable for both coding attempts at the system level (M T1  = 68.8%; M T2  = 73.9%), and were poor at the descriptor level (M T1  = 58.5%; M T2  = 64.1%). Mean criterion referenced validity scores at the system level were acceptable (M T1  = 73.9%; M T2  = 75.3%). However, they were not consistently acceptable at the descriptor level (M T1  = 67.6%; M T2  = 70.8%). Overall, the results indicate that the classification scheme does not currently satisfy reliability and validity requirements, and that further work is required. The implications for the design and development of contributing factors classification schemes are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. NIM: A Node Influence Based Method for Cancer Classification

    Directory of Open Access Journals (Sweden)

    Yiwen Wang

    2014-01-01

    Full Text Available The classification of different cancer types owns great significance in the medical field. However, the great majority of existing cancer classification methods are clinical-based and have relatively weak diagnostic ability. With the rapid development of gene expression technology, it is able to classify different kinds of cancers using DNA microarray. Our main idea is to confront the problem of cancer classification using gene expression data from a graph-based view. Based on a new node influence model we proposed, this paper presents a novel high accuracy method for cancer classification, which is composed of four parts: the first is to calculate the similarity matrix of all samples, the second is to compute the node influence of training samples, the third is to obtain the similarity between every test sample and each class using weighted sum of node influence and similarity matrix, and the last is to classify each test sample based on its similarity between every class. The data sets used in our experiments are breast cancer, central nervous system, colon tumor, prostate cancer, acute lymphoblastic leukemia, and lung cancer. experimental results showed that our node influence based method (NIM is more efficient and robust than the support vector machine, K-nearest neighbor, C4.5, naive Bayes, and CART.

  8. Reliability of a four-column classification for tibial plateau fractures.

    Science.gov (United States)

    Martínez-Rondanelli, Alfredo; Escobar-González, Sara Sofía; Henao-Alzate, Alejandro; Martínez-Cano, Juan Pablo

    2017-09-01

    A four-column classification system offers a different way of evaluating tibial plateau fractures. The aim of this study is to compare the intra-observer and inter-observer reliability between four-column and classic classifications. This is a reliability study, which included patients presenting with tibial plateau fractures between January 2013 and September 2015 in a level-1 trauma centre. Four orthopaedic surgeons blindly classified each fracture according to four different classifications: AO, Schatzker, Duparc and four-column. Kappa, intra-observer and inter-observer concordance were calculated for the reliability analysis. Forty-nine patients were included. The mean age was 39 ± 14.2 years, with no gender predominance (men: 51%; women: 49%), and 67% of the fractures included at least one of the posterior columns. The intra-observer and inter-observer concordance were calculated for each classification: four-column (84%/79%), Schatzker (60%/71%), AO (50%/59%) and Duparc (48%/58%), with a statistically significant difference among them (p = 0.001/p = 0.003). Kappa coefficient for intr-aobserver and inter-observer evaluations: Schatzker 0.48/0.39, four-column 0.61/0.34, Duparc 0.37/0.23, and AO 0.34/0.11. The proposed four-column classification showed the highest intra and inter-observer agreement. When taking into account the agreement that occurs by chance, Schatzker classification showed the highest inter-observer kappa, but again the four-column had the highest intra-observer kappa value. The proposed classification is a more inclusive classification for the posteromedial and posterolateral fractures. We suggest, therefore, that it be used in addition to one of the classic classifications in order to better understand the fracture pattern, as it allows more attention to be paid to the posterior columns, it improves the surgical planning and allows the surgical approach to be chosen more accurately.

  9. A Classification Framework Applied to Cancer Gene Expression Profiles

    Directory of Open Access Journals (Sweden)

    Hussein Hijazi

    2013-01-01

    Full Text Available Classification of cancer based on gene expression has provided insight into possible treatment strategies. Thus, developing machine learning methods that can successfully distinguish among cancer subtypes or normal versus cancer samples is important. This work discusses supervised learning techniques that have been employed to classify cancers. Furthermore, a two-step feature selection method based on an attribute estimation method (e.g., ReliefF and a genetic algorithm was employed to find a set of genes that can best differentiate between cancer subtypes or normal versus cancer samples. The application of different classification methods (e.g., decision tree, k-nearest neighbor, support vector machine (SVM, bagging, and random forest on 5 cancer datasets shows that no classification method universally outperforms all the others. However, k-nearest neighbor and linear SVM generally improve the classification performance over other classifiers. Finally, incorporating diverse types of genomic data (e.g., protein-protein interaction data and gene expression increase the prediction accuracy as compared to using gene expression alone.

  10. British athletics muscle injury classification: a reliability study for a new grading system

    International Nuclear Information System (INIS)

    Patel, A.; Chakraverty, J.; Pollock, N.; Chakraverty, R.; Suokas, A.K.; James, S.L.

    2015-01-01

    Aim: To implement and validate the newly proposed British athletics muscle injury classification in the assessment of hamstring injuries in track and field athletes and to analyse the nature and frequency of the discrepancies. Materials and methods: This was a retrospective study analysing hamstring injuries in elite British athletes using the proposed classification system. Classification of 65 hamstring injuries in 45 high-level athletes by two radiologists at two time points 4 months apart to determine interrater variability, intrarater variability, and feasibility of the classification system was undertaken. Results: Interrater Kappa values of 0.80 (95% confidence interval [CI]: 0.67–0.92; p<0.0001) for Round 1 and 0.88 (95% CI: 0.76–1.00; p<0.0001) for Round 2 of the review were observed. Percentages of agreement were 85% for Round 1 and 91% for Round 2. The intrarater Kappa value for the two reviewers were 0.76 (95% CI: 0.63–0.88; p<0.0001) and 0.65 (95% CI: 0.53–0.76; p<0.0001) and the average was 0.71 suggesting substantial overall agreement. The percentages of agreement were 82% and 72%, respectively. Conclusions: This classification system is straightforward to use and produces both reproducible and consistent results based on interrater and intrarater Kappa values with at least substantial agreement in all groups. Further work is ongoing to investigate whether individual grades within this classification system provide prognostic information and could guide clinical management. - Highlights: • This classification system is based on MRI parameters shown to have prognostic relevance. • It is simple to use, reproducible and clinically relevant which will enhance clinical practice. • Once clinicians are familiar with the classification inter & intrarater reliability will improve.

  11. Magnetic resonance imaging texture analysis classification of primary breast cancer

    International Nuclear Information System (INIS)

    Waugh, S.A.; Lerski, R.A.; Purdie, C.A.; Jordan, L.B.; Vinnicombe, S.; Martin, P.; Thompson, A.M.

    2016-01-01

    Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75 %, AUROC = 0.816; test: 72.5 %, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2 %, AUROC = 0.754; test: 57.0 %, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. (orig.)

  12. Magnetic resonance imaging texture analysis classification of primary breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Waugh, S.A.; Lerski, R.A. [Ninewells Hospital and Medical School, Department of Medical Physics, Dundee (United Kingdom); Purdie, C.A.; Jordan, L.B. [Ninewells Hospital and Medical School, Department of Pathology, Dundee (United Kingdom); Vinnicombe, S. [University of Dundee, Division of Imaging and Technology, Ninewells Hospital and Medical School, Dundee (United Kingdom); Martin, P. [Ninewells Hospital and Medical School, Department of Clinical Radiology, Dundee (United Kingdom); Thompson, A.M. [University of Texas MD Anderson Cancer Center, Department of Surgical Oncology, Houston, TX (United States)

    2016-02-15

    Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75 %, AUROC = 0.816; test: 72.5 %, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2 %, AUROC = 0.754; test: 57.0 %, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. (orig.)

  13. Significance and Application of Digital Breast Tomosynthesis for the BI-RADS Classification of Breast Cancer.

    Science.gov (United States)

    Cai, Si-Qing; Yan, Jian-Xiang; Chen, Qing-Shi; Huang, Mei-Ling; Cai, Dong-Lu

    2015-01-01

    Full-field digital mammography (FFDM) with dense breasts has a high rate of missed diagnosis, and digital breast tomosynthesis (DBT) could reduce organization overlapping and provide more reliable images for BI-RADS classification. This study aims to explore application of COMBO (FFDM+DBT) for effect and significance of BI-RADS classification of breast cancer. In this study, we selected 832 patients who had been treated from May 2013 to November 2013. Classify FFDM and COMBO examination according to BI-RADS separately and compare the differences for glands in the image of the same patient in judgment, mass characteristics display and indirect signs. Employ Paired Wilcoxon rank sum test was used in 79 breast cancer patients to find differences between two examine methods. The results indicated that COMBO pattern is able to observe more details in distribution of glands when estimating content. Paired Wilcoxon rank sum test showed that overall classification level of COMBO is higher significantly compared to FFDM to BI-RADS diagnosis and classification of breast (PBI-RADS classification in breast cancer in clinical.

  14. Influence of nuclei segmentation on breast cancer malignancy classification

    Science.gov (United States)

    Jelen, Lukasz; Fevens, Thomas; Krzyzak, Adam

    2009-02-01

    Breast Cancer is one of the most deadly cancers affecting middle-aged women. Accurate diagnosis and prognosis are crucial to reduce the high death rate. Nowadays there are numerous diagnostic tools for breast cancer diagnosis. In this paper we discuss a role of nuclear segmentation from fine needle aspiration biopsy (FNA) slides and its influence on malignancy classification. Classification of malignancy plays a very important role during the diagnosis process of breast cancer. Out of all cancer diagnostic tools, FNA slides provide the most valuable information about the cancer malignancy grade which helps to choose an appropriate treatment. This process involves assessing numerous nuclear features and therefore precise segmentation of nuclei is very important. In this work we compare three powerful segmentation approaches and test their impact on the classification of breast cancer malignancy. The studied approaches involve level set segmentation, fuzzy c-means segmentation and textural segmentation based on co-occurrence matrix. Segmented nuclei were used to extract nuclear features for malignancy classification. For classification purposes four different classifiers were trained and tested with previously extracted features. The compared classifiers are Multilayer Perceptron (MLP), Self-Organizing Maps (SOM), Principal Component-based Neural Network (PCA) and Support Vector Machines (SVM). The presented results show that level set segmentation yields the best results over the three compared approaches and leads to a good feature extraction with a lowest average error rate of 6.51% over four different classifiers. The best performance was recorded for multilayer perceptron with an error rate of 3.07% using fuzzy c-means segmentation.

  15. Manual Ability Classification System (MACS: reliability between therapists and parents in Brazil

    Directory of Open Access Journals (Sweden)

    Daniela B. R. Silva

    2015-02-01

    Full Text Available BACKGROUND: The Manual Ability Classification System (MACS has been widely used to describe the manual ability of children with cerebral palsy (CP; however its reliability has not been verified in Brazil. OBJECTIVE: To establish the inter- and intra-rater reliability of the Portuguese-Brazil version of the MACS by comparing the classifications given by therapists and parents of children with CP. METHOD: Data were obtained from 90 children with CP between the ages of 4 and 18 years, who were treated at the neurology and rehabilitation clinics of a Brazilian hospital. Therapists (an occupational therapist and a student classified manual ability (MACS through direct observation and information provided by parents. Therapists and parents used the Portuguese-Brazil version of the MACS. Intra- and inter-rater reliability was obtained using unweighted Kappa coefficient (k and intra-class correlation coefficient (ICC. The Chi-square test was used to identify the predominance of disagreements in the classification of parents and therapists. RESULTS: An almost perfect agreement resulted among therapists [K=0.90 (95% CI 0.83-0.97; ICC=0.97 (95%CI 0.96-0.98], as well as with intra-rater (therapists, with Kappa ranging between 0.83 and 0.95 and ICC between 0.96 and 0.99 for the evaluator with more and less experience in rehabilitation, respectively. The agreement between therapists and parents was fair [K=0.36 (95% CI 0.22-0.50; ICC=0.79 (95% CI 0.70-0.86]. CONCLUSIONS: The Portuguese version of the MACS is a reliable instrument to be used jointly by parents and therapists.

  16. Classification of treatment-related mortality in children with cancer

    DEFF Research Database (Denmark)

    Alexander, Sarah; Pole, Jason D; Gibson, Paul

    2015-01-01

    Treatment-related mortality is an important outcome in paediatric cancer clinical trials. An international group of experts in supportive care in paediatric cancer developed a consensus-based definition of treatment-related mortality and a cause-of-death attribution system. The reliability and va...

  17. Cancer classification using the Immunoscore: a worldwide task force.

    Science.gov (United States)

    Galon, Jérôme; Pagès, Franck; Marincola, Francesco M; Angell, Helen K; Thurin, Magdalena; Lugli, Alessandro; Zlobec, Inti; Berger, Anne; Bifulco, Carlo; Botti, Gerardo; Tatangelo, Fabiana; Britten, Cedrik M; Kreiter, Sebastian; Chouchane, Lotfi; Delrio, Paolo; Arndt, Hartmann; Asslaber, Martin; Maio, Michele; Masucci, Giuseppe V; Mihm, Martin; Vidal-Vanaclocha, Fernando; Allison, James P; Gnjatic, Sacha; Hakansson, Leif; Huber, Christoph; Singh-Jasuja, Harpreet; Ottensmeier, Christian; Zwierzina, Heinz; Laghi, Luigi; Grizzi, Fabio; Ohashi, Pamela S; Shaw, Patricia A; Clarke, Blaise A; Wouters, Bradly G; Kawakami, Yutaka; Hazama, Shoichi; Okuno, Kiyotaka; Wang, Ena; O'Donnell-Tormey, Jill; Lagorce, Christine; Pawelec, Graham; Nishimura, Michael I; Hawkins, Robert; Lapointe, Réjean; Lundqvist, Andreas; Khleif, Samir N; Ogino, Shuji; Gibbs, Peter; Waring, Paul; Sato, Noriyuki; Torigoe, Toshihiko; Itoh, Kyogo; Patel, Prabhu S; Shukla, Shilin N; Palmqvist, Richard; Nagtegaal, Iris D; Wang, Yili; D'Arrigo, Corrado; Kopetz, Scott; Sinicrope, Frank A; Trinchieri, Giorgio; Gajewski, Thomas F; Ascierto, Paolo A; Fox, Bernard A

    2012-10-03

    Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J

  18. Reliable Fault Classification of Induction Motors Using Texture Feature Extraction and a Multiclass Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Jia Uddin

    2014-01-01

    Full Text Available This paper proposes a method for the reliable fault detection and classification of induction motors using two-dimensional (2D texture features and a multiclass support vector machine (MCSVM. The proposed model first converts time-domain vibration signals to 2D gray images, resulting in texture patterns (or repetitive patterns, and extracts these texture features by generating the dominant neighborhood structure (DNS map. The principal component analysis (PCA is then used for the purpose of dimensionality reduction of the high-dimensional feature vector including the extracted texture features due to the fact that the high-dimensional feature vector can degrade classification performance, and this paper configures an effective feature vector including discriminative fault features for diagnosis. Finally, the proposed approach utilizes the one-against-all (OAA multiclass support vector machines (MCSVMs to identify induction motor failures. In this study, the Gaussian radial basis function kernel cooperates with OAA MCSVMs to deal with nonlinear fault features. Experimental results demonstrate that the proposed approach outperforms three state-of-the-art fault diagnosis algorithms in terms of fault classification accuracy, yielding an average classification accuracy of 100% even in noisy environments.

  19. Call for a Computer-Aided Cancer Detection and Classification Research Initiative in Oman.

    Science.gov (United States)

    Mirzal, Andri; Chaudhry, Shafique Ahmad

    2016-01-01

    Cancer is a major health problem in Oman. It is reported that cancer incidence in Oman is the second highest after Saudi Arabia among Gulf Cooperation Council countries. Based on GLOBOCAN estimates, Oman is predicted to face an almost two-fold increase in cancer incidence in the period 2008-2020. However, cancer research in Oman is still in its infancy. This is due to the fact that medical institutions and infrastructure that play central roles in data collection and analysis are relatively new developments in Oman. We believe the country requires an organized plan and efforts to promote local cancer research. In this paper, we discuss current research progress in cancer diagnosis using machine learning techniques to optimize computer aided cancer detection and classification (CAD). We specifically discuss CAD using two major medical data, i.e., medical imaging and microarray gene expression profiling, because medical imaging like mammography, MRI, and PET have been widely used in Oman for assisting radiologists in early cancer diagnosis and microarray data have been proven to be a reliable source for differential diagnosis. We also discuss future cancer research directions and benefits to Oman economy for entering the cancer research and treatment business as it is a multi-billion dollar industry worldwide.

  20. Bladder cancer: Analysis of the 2004 WHO classification in ...

    African Journals Online (AJOL)

    Objectives: Bladder cancer (BCA) is aworldwide disease and shows a wide range of geographical variation. The aim of this study is to analyze the prevalence of schistosomal and non-schistosomal associated BCA as well as compare our findings with the 2004 WHO consensus classification of urothelial neoplasms and ...

  1. Classification of mitocans, anti-cancer drugs acting on mitochondria

    Czech Academy of Sciences Publication Activity Database

    Neužil, Jiří; Dong, L. F.; Rohlena, Jakub; Truksa, Jaroslav; Ralph, S. J.

    2013-01-01

    Roč. 13, č. 3 (2013), s. 199-208 ISSN 1567-7249 Institutional research plan: CEZ:AV0Z50520701 Keywords : Mitocans * Anti-cancer therapeutics * Classification Subject RIV: EB - Gene tics ; Molecular Biology Impact factor: 3.524, year: 2013

  2. Classification of mitocans, anti-cancer drugs acting on mitochondria

    Czech Academy of Sciences Publication Activity Database

    Neužil, Jiří; Dong, L. F.; Rohlena, Jakub; Truksa, Jaroslav; Ralph, S. J.

    2013-01-01

    Roč. 13, č. 3 (2013), s. 199-208 ISSN 1567-7249 Institutional research plan: CEZ:AV0Z50520701 Keywords : Mitocans * Anti-cancer therapeutics * Classification Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.524, year: 2013

  3. Association between gastric cancer and the Kyoto classification of gastritis.

    Science.gov (United States)

    Shichijo, Satoki; Hirata, Yoshihiro; Niikura, Ryota; Hayakawa, Yoku; Yamada, Atsuo; Koike, Kazuhiko

    2017-09-01

    Histological gastritis is associated with gastric cancer, but its diagnosis requires biopsy. Many classifications of endoscopic gastritis are available, but not all are useful for risk stratification of gastric cancer. The Kyoto Classification of Gastritis was proposed at the 85th Congress of the Japan Gastroenterological Endoscopy Society. This cross-sectional study evaluated the usefulness of the Kyoto Classification of Gastritis for risk stratification of gastric cancer. From August 2013 to September 2014, esophagogastroduodenoscopy was performed and the gastric findings evaluated according to the Kyoto Classification of Gastritis in a total of 4062 patients. The following five endoscopic findings were selected based on previous reports: atrophy, intestinal metaplasia, enlarged folds, nodularity, and diffuse redness. A total of 3392 patients (1746 [51%] men and 1646 [49%] women) were analyzed. Among them, 107 gastric cancers were diagnosed. Atrophy was found in 2585 (78%) and intestinal metaplasia in 924 (27%). Enlarged folds, nodularity, and diffuse redness were found in 197 (5.8%), 22 (0.6%), and 573 (17%), respectively. In univariate analyses, the severity of atrophy, intestinal metaplasia, diffuse redness, age, and male sex were associated with gastric cancer. In a multivariate analysis, atrophy and male sex were found to be independent risk factors. Younger age and severe atrophy were determined to be associated with diffuse-type gastric cancer. Endoscopic detection of atrophy was associated with the risk of gastric cancer. Thus, patients with severe atrophy should be examined carefully and may require intensive follow-up. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  4. Gastric cancer: epidemiology, prevention, classification, and treatment

    OpenAIRE

    Sitarz, Robert; Skierucha, Małgorzata; Mielko, Jerzy; Offerhaus, G Johan A; Maciejewski, Ryszard; Polkowski, Wojciech P

    2018-01-01

    Robert Sitarz,1–3 Małgorzata Skierucha,1,2 Jerzy Mielko,1 G Johan A Offerhaus,3 Ryszard Maciejewski,2 Wojciech P Polkowski1 1Department of Surgical Oncology, Medical University of Lublin, Lublin, Poland; 2Department of Human Anatomy, Medical University of Lublin, Lublin, Poland; 3Department of Pathology, University Medical Centre, Utrecht, The Netherlands Abstract: Gastric cancer is the second most common cause of cancer-related deaths in the world, the epidemiology of which has ch...

  5. Reliability assessment of AOSpine thoracolumbar spine injury classification system and Thoracolumbar Injury Classification and Severity Score (TLICS) for thoracolumbar spine injuries: results of a multicentre study.

    Science.gov (United States)

    Kaul, Rahul; Chhabra, Harvinder Singh; Vaccaro, Alexander R; Abel, Rainer; Tuli, Sagun; Shetty, Ajoy Prasad; Das, Kali Dutta; Mohapatra, Bibhudendu; Nanda, Ankur; Sangondimath, Gururaj M; Bansal, Murari Lal; Patel, Nishit

    2017-05-01

    The aim of this multicentre study was to determine whether the recently introduced AOSpine Classification and Injury Severity System has better interrater and intrarater reliability than the already existing Thoracolumbar Injury Classification and Severity Score (TLICS) for thoracolumbar spine injuries. Clinical and radiological data of 50 consecutive patients admitted at a single centre with a diagnosis of an acute traumatic thoracolumbar spine injury were distributed to eleven attending spine surgeons from six different institutions in the form of PowerPoint presentation, who classified them according to both classifications. After time span of 6 weeks, cases were randomly rearranged and sent again to same surgeons for re-classification. Interobserver and intraobserver reliability for each component of TLICS and new AOSpine classification were evaluated using Fleiss Kappa coefficient (k value) and Spearman rank order correlation. Moderate interrater and intrarater reliability was seen for grading fracture type and integrity of posterior ligamentous complex (Fracture type: k = 0.43 ± 0.01 and 0.59 ± 0.16, respectively, PLC: k = 0.47 ± 0.01 and 0.55 ± 0.15, respectively), and fair to moderate reliability (k = 0.29 ± 0.01 interobserver and 0.44+/0.10 intraobserver, respectively) for total score according to TLICS. Moderate interrater (k = 0.59 ± 0.01) and substantial intrarater reliability (k = 0.68 ± 0.13) was seen for grading fracture type regardless of subtype according to AOSpine classification. Near perfect interrater and intrarater agreement was seen concerning neurological status for both the classification systems. Recently proposed AOSpine classification has better reliability for identifying fracture morphology than the existing TLICS. Additional studies are clearly necessary concerning the application of these classification systems across multiple physicians at different level of training and trauma centers to evaluate not

  6. New Atrophic Acne Scar Classification: Reliability of Assessments Based on Size, Shape, and Number.

    Science.gov (United States)

    Kang, Sewon; Lozada, Vicente Torres; Bettoli, Vincenzo; Tan, Jerry; Rueda, Maria Jose; Layton, Alison; Petit, Lauren; Dréno, Brigitte

    2016-06-01

    Post-acne atrophic scarring is a major concern for which standardized outcome measures are needed. Traditionally, this type of scar has been classified based on shape; but survey of practicing dermatologists has shown that atrophic scar morphology has not been well enough defined to allow good agreement in clinical classification. Reliance on clinical assessment is still needed at the current time, since objective tools are not yet available in routine practice. Evaluate classification for atrophic acne scars by shape, size, and facial location and establish reliability in assessments. We conducted a non-interventional study with dermatologists performing live clinical assessments of atrophic acne scars. To objectively compare identification of lesions, individual lesions were marked on a high-resolution photo of the patient that was displayed on a computer during the clinical evaluation. The Jacob clinical classification system was used to define three primary shapes of scars 1) icepick, 2) boxcar, and 3) rolling. To determine agreement for classification by size, independent technicians assessed the investigators' markings on digital images. Identical localization of scars was denoted if the maximal distance between their centers was ≤ 60 pixels (approximately 3 mm). Raters assessed scars on the same patients twice (morning/afternoon). Aggregate models of rater assessments were created and analyzed for agreement. Raters counted a mean scar count per subject ranging from 15.75 to 40.25 scars. Approximately 50% of scars were identified by all raters and ~75% of scars were identified by at least 2 of 3 raters (weak agreement, Kappa pairwise agreement 0.30). Agreement between consecutive counts was moderate, with Kappa index ranging from 0.26 to 0.47 (after exclusion of one outlier investigator who had significantly higher counts than all others). Shape classifications of icepick, boxcar, and rolling differed significantly between raters and even for same raters at

  7. Classification of neuropathic pain in cancer patients

    DEFF Research Database (Denmark)

    Brunelli, Cinzia; Bennett, Michael I; Kaasa, Stein

    2014-01-01

    and on the relevance of patient-reported outcome (PRO) descriptors for the screening of NP in this population. An international group of 42 experts was invited to participate in a consensus process through a modified 2-round Internet-based Delphi survey. Relevant topics investigated were: peculiarities of NP...... in patients with cancer, IASP NeuPSIG diagnostic criteria adaptation and assessment, and standardized PRO assessment for NP screening. Median consensus scores (MED) and interquartile ranges (IQR) were calculated to measure expert consensus after both rounds. Twenty-nine experts answered, and good agreement...... was proposed. Clinical research on PRO in the screening phase and on the application of the algorithm will be needed to examine their effectiveness in classifying NP in cancer patients....

  8. Quality of nursing intensity data: inter-rater reliability of the patient classification after two decades in clinical use.

    Science.gov (United States)

    Liljamo, Pia; Kinnunen, Ulla-Mari; Ohtonen, Pasi; Saranto, Kaija

    2017-09-01

    The aim of this study was to measure the inter-rater reliability of the Oulu Patient Classification and to discuss existing methods of reliability testing. The Oulu Patient Classification, part of the RAFAELA ® System, has been developed to assist nursing managers with the proper allocation of nursing resources. Due to the increased intensity of inpatient care during recent years, there is a need for the reliability testing of the classification, which has been in clinical use for 20 years. Retrospective statistical study. To test inter-rater reliability, a pair of nurses classified the same patients, without knowledge of each other's ratings, as a part of annually conducted standardization. Data on the parallel classifications (n = 19,997) was obtained from inpatient units (n = 32) with different specialties at a university hospital in Finland during 2010-2015. Parallel classification practices were also analysed. The reliability of the overall classification and its subareas were calculated using suitable statistical coefficients. Inter-rater reliability coefficients were a reliable or almost perfect means of considering the nursing intensity category and various practices, but there were detectable differences between subareas. The lowest agreement levels occurred in the subareas 'Planning and Coordination of Nursing Care' and 'Guiding of Care/Continued Care and Emotional Support'. There is a need to develop the descriptions of subareas and to clarify the related concepts. Precise nursing documentation can promote a high level of agreement and reliable results. The traditional overall proportion of agreement does not provide an adequate picture of reliability - weighted kappa coefficients should be used instead. © 2017 John Wiley & Sons Ltd.

  9. Vabrasio is a reliable test to rule out endometrial cancer

    DEFF Research Database (Denmark)

    Andersen, Anita; Lauszus, Finn Friis

    2015-01-01

    Introduction: Endometrial cancer is the most common gynaecological cancer in Denmark, and its incidence peaks in the postmenopausal years. The aim of the present study was to evaluate the effectiveness of vacuum aspirator (vabrasio) for the detection of endometrial cancer in terms of sensitivity......, specificity and predictive value. Methods: A cohort counting 503 women who had vabrasio was evaluated retrospectively. The women included were consecutive patients who had received vabrasio at the 
Department of Gynaecology and Obstetrics at Herning Hos­pital, Denmark, during a two-year period. They were iden......­tified by searching the hospital database for the Inter­na­tional Classification of Diseases, tenth version (ICD-10) code for vabrasio.
 Results: The indications for vabrasio were postmeno­pausal bleeding (45%), meno/metrorrhagia (43%) and thickened endometrium/polyp (6%). The first evaluation by vabrasio was normal...

  10. Cancer classification using the Immunoscore: a worldwide task force

    Directory of Open Access Journals (Sweden)

    Galon Jérôme

    2012-10-01

    Full Text Available Abstract Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification summarizes data on tumor burden (T, presence of cancer cells in draining and regional lymph nodes (N and evidence for metastases (M. However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the ‘Immunoscore’ into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of

  11. Reliability of a New Radiographic Classification for Developmental Dysplasia of the Hip.

    Science.gov (United States)

    Narayanan, Unni; Mulpuri, Kishore; Sankar, Wudbhav N; Clarke, Nicholas M P; Hosalkar, Harish; Price, Charles T

    2015-01-01

    Existing radiographic classification schemes (eg, Tönnis criteria) for DDH quantify the severity of disease based on the position of the ossific nucleus relative to Hilgenreiner's and Perkin's lines. By definition, this method requires the presence of an ossification centre, which can be delayed in appearance and eccentric in location within the femoral head. A new radiographic classification system has been developed by the International Hip Dysplasia Institute (IHDI), which uses the mid-point of the proximal femoral metaphysis as a reference landmark, and can therefore be applied to children of all ages. The purpose of this study was to compare the reliability of this new method with that of Tönnis, as the first step in establishing its validity and clinical utility. Twenty standardized anteroposterior pelvic radiographs of children with untreated DDH were selected purposefully to capture the spectrum of age (range, 3 to 32 mo) at presentation and disease severity. Each of the hips was classified separately by the IHDI and Tönnis methods by 6 experienced pediatric orthopaedists from the United States, Canada, Mexico, United Kingdom, and by 2 orthopaedic senior residents. The inter-rater reliability was tested using the Intra Class Correlation coefficient (ICC) to measure concordance between raters. All 40 hips were classifiable by the IHDI method by all raters. Ten of the 40 hips could not be classified by the Tönnis method because of the absence of the ossific nucleus on one or both sides. The ICC (95% confidence interval) for the IHDI method for all raters was 0.90 (0.83-0.95) and 0.95 (0.91-0.98) for the right and left hips, respectively. The corresponding ICCs for the Tönnis method were 0.63 (0.46-0.80) and 0.60 (0.43-0.78), respectively. There was no significant difference between the ICCs of the 6 experts and 2 trainees. The IHDI method of classification has excellent inter-rater reliability, both among experts and novices, and is more widely

  12. The Communication Function Classification System: cultural adaptation, validity, and reliability of the Farsi version for patients with cerebral palsy.

    Science.gov (United States)

    Soleymani, Zahra; Joveini, Ghodsiye; Baghestani, Ahmad Reza

    2015-03-01

    This study developed a Farsi language Communication Function Classification System and then tested its reliability and validity. Communication Function Classification System is designed to classify the communication functions of individuals with cerebral palsy. Up until now, there has been no instrument for assessment of this communication function in Iran. The English Communication Function Classification System was translated into Farsi and cross-culturally modified by a panel of experts. Professionals and parents then assessed the content validity of the modified version. A backtranslation of the Farsi version was confirmed by the developer of the English Communication Function Classification System. Face validity was assessed by therapists and parents of 10 patients. The Farsi Communication Function Classification System was administered to 152 individuals with cerebral palsy (age, 2 to 18 years; median age, 10 years; mean age, 9.9 years; standard deviation, 4.3 years). Inter-rater reliability was analyzed between parents, occupational therapists, and speech and language pathologists. The test-retest reliability was assessed for 75 patients with a 14 day interval between tests. The inter-rater reliability of the Communication Function Classification System was 0.81 between speech and language pathologists and occupational therapists, 0.74 between parents and occupational therapists, and 0.88 between parents and speech and language pathologists. The test-retest reliability was 0.96 for occupational therapists, 0.98 for speech and language pathologists, and 0.94 for parents. The findings suggest that the Farsi version of Communication Function Classification System is a reliable and valid measure that can be used in clinical settings to assess communication function in patients with cerebral palsy. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. Molecular classification of gastric cancer: a new paradigm.

    Science.gov (United States)

    Shah, Manish A; Khanin, Raya; Tang, Laura; Janjigian, Yelena Y; Klimstra, David S; Gerdes, Hans; Kelsen, David P

    2011-05-01

    Gastric cancer may be subdivided into 3 distinct subtypes--proximal, diffuse, and distal gastric cancer--based on histopathologic and anatomic criteria. Each subtype is associated with unique epidemiology. Our aim is to test the hypothesis that these distinct gastric cancer subtypes may also be distinguished by gene expression analysis. Patients with localized gastric adenocarcinoma being screened for a phase II preoperative clinical trial (National Cancer Institute, NCI #5917) underwent endoscopic biopsy for fresh tumor procurement. Four to 6 targeted biopsies of the primary tumor were obtained. Macrodissection was carried out to ensure more than 80% carcinoma in the sample. HG-U133A GeneChip (Affymetrix) was used for cDNA expression analysis, and all arrays were processed and analyzed using the Bioconductor R-package. Between November 2003 and January 2006, 57 patients were screened to identify 36 patients with localized gastric cancer who had adequate RNA for expression analysis. Using supervised analysis, we built a classifier to distinguish the 3 gastric cancer subtypes, successfully classifying each into tightly grouped clusters. Leave-one-out cross-validation error was 0.14, suggesting that more than 85% of samples were classified correctly. Gene set analysis with the false discovery rate set at 0.25 identified several pathways that were differentially regulated when comparing each gastric cancer subtype to adjacent normal stomach. Subtypes of gastric cancer that have epidemiologic and histologic distinctions are also distinguished by gene expression data. These preliminary data suggest a new classification of gastric cancer with implications for improving our understanding of disease biology and identification of unique molecular drivers for each gastric cancer subtype. ©2011 AACR.

  14. Using fuzzy association rule mining in cancer classification

    International Nuclear Information System (INIS)

    Mahmoodian, Hamid; Marhaban, M.H.; Abdulrahim, Raha; Rosli, Rozita; Saripan, Iqbal

    2011-01-01

    Full text: The classification of the cancer tumors based on gene expression profiles has been extensively studied in numbers of studies. A wide variety of cancer datasets have been implemented by the various methods of gene selec tion and classification to identify the behavior of the genes in tumors and find the relationships between them and outcome of diseases. Interpretability of the model, which is developed by fuzzy rules and linguistic variables in this study, has been rarely considered. In addition, creating a fuzzy classifier with high performance in classification that uses a subset of significant genes which have been selected by different types of gene selection methods is another goal of this study. A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. At first, different subset of genes which have been selected by different methods, were used to generate primary fuzzy classifiers separately and then proposed algorithm was implemented to mix the genes which have been associated in the primary classifiers and generate a new classifier. The results show that fuzzy classifier can classify the tumors with high performance while presenting the relationships between the genes by linguistic variables

  15. [New molecular classification of colorectal cancer, pancreatic cancer and stomach cancer: Towards "à la carte" treatment?].

    Science.gov (United States)

    Dreyer, Chantal; Afchain, Pauline; Trouilloud, Isabelle; André, Thierry

    2016-01-01

    This review reports 3 of recently published molecular classifications of the 3 main gastro-intestinal cancers: gastric, pancreatic and colorectal adenocarcinoma. In colorectal adenocarcinoma, 6 independent classifications were combined to finally hold 4 molecular sub-groups, Consensus Molecular Subtypes (CMS 1-4), linked to various clinical, molecular and survival data. CMS1 (14% MSI with immune activation); CMS2 (37%: canonical with epithelial differentiation and activation of the WNT/MYC pathway); CMS3 (13% metabolic with epithelial differentiation and RAS mutation); CMS4 (23%: mesenchymal with activation of TGFβ pathway and angiogenesis with stromal invasion). In gastric adenocarcinoma, 4 groups were established: subtype "EBV" (9%, high frequency of PIK3CA mutations, hypermetylation and amplification of JAK2, PD-L1 and PD-L2), subtype "MSI" (22%, high rate of mutation), subtype "genomically stable tumor" (20%, diffuse histology type and mutations of RAS and genes encoding integrins and adhesion proteins including CDH1) and subtype "tumors with chromosomal instability" (50%, intestinal type, aneuploidy and receptor tyrosine kinase amplification). In pancreatic adenocarcinomas, a classification in four sub-groups has been proposed, stable subtype (20%, aneuploidy), locally rearranged subtype (30%, focal event on one or two chromosoms), scattered subtype (36%,200 structural variation events, defects in DNA maintenance). Although currently away from the care of patients, these classifications open the way to "à la carte" treatment depending on molecular biology. Copyright © 2016 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

  16. Reliable classification of facial phenotypic variation in craniofacial microsomia: a comparison of physical exam and photographs.

    Science.gov (United States)

    Birgfeld, Craig B; Heike, Carrie L; Saltzman, Babette S; Leroux, Brian G; Evans, Kelly N; Luquetti, Daniela V

    2016-03-31

    Craniofacial microsomia is a common congenital condition for which children receive longitudinal, multidisciplinary team care. However, little is known about the etiology of craniofacial microsomia and few outcome studies have been published. In order to facilitate large, multicenter studies in craniofacial microsomia, we assessed the reliability of phenotypic classification based on photographs by comparison with direct physical examination. Thirty-nine children with craniofacial microsomia underwent a physical examination and photographs according to a standardized protocol. Three clinicians completed ratings during the physical examination and, at least a month later, using respective photographs for each participant. We used descriptive statistics for participant characteristics and intraclass correlation coefficients (ICCs) to assess reliability. The agreement between ratings on photographs and physical exam was greater than 80 % for all 15 categories included in the analysis. The ICC estimates were higher than 0.6 for most features. Features with the highest ICC included: presence of epibulbar dermoids, ear abnormalities, and colobomas (ICC 0.85, 0.81, and 0.80, respectively). Orbital size, presence of pits, tongue abnormalities, and strabismus had the lowest ICC, values (0.17 or less). There was not a strong tendency for either type of rating, physical exam or photograph, to be more likely to designate a feature as abnormal. The agreement between photographs and physical exam regarding the presence of a prior surgery was greater than 90 % for most features. Our results suggest that categorization of facial phenotype in children with CFM based on photographs is reliable relative to physical examination for most facial features.

  17. X-ray diagnosis of esophageal cancer and application of Borrmann's classification

    International Nuclear Information System (INIS)

    Chin, Soo Yil

    1985-01-01

    In 126 cases and who were diagnosed as esophageal cancer and treated by radiation at Cancer Research Hospital, K. A. E. R. I., from January 1974 to July 1979, a study on the x-ray diagnosis of esophageal cancer was carried out mainly as to the type classification. The ordinary classification od esophageal cancer by x-ray picture was reviewed and Borrmann's classification using gastric cancer was tried to apply to the macroscopic classification of esophageal cancer, and also the application of this classification to x-ray diagnosis was discussed. And the effect of radiotherapy as to each type of cancer according to the ordinary x-ray classification and Borrmann's classification was studied too. The results were as follows: 1. The ordinary x-ray classification was not simple, because the degree of progression of cancer, difference of mural invasion, and position and method of radiography could make misinterpretation of the type of cancer and the therapeutic effect by radiation as to each type according to this classification did not represent a significant characteristic too, although the radiation was most effective in the polypoidal type and least effective in funnel type. 2. The Borrmann's classification was relatively easy even on the radiogram because of little overlapping between each type and the type became more evident on the resected specimen after operation. And also some correlation was recognized between the type of Borrmann's classification and radiotherapeutic effect. The effect was best in type I and It was gradually decreased in type II, III, and IV in the other. The radiotherapy was ineffective in about three quarters of type IV. 3. The Borrmann's classification is now employed to the carcinoma of large bowel, as well as to the gastric cancer. If it is applied to the esophageal cancer, the macroscopic classification for the cancer of digestive tract can be systemized and it will be convenient in clinical study.

  18. Classification of breast cancer cytological specimen using convolutional neural network

    Science.gov (United States)

    Żejmo, Michał; Kowal, Marek; Korbicz, Józef; Monczak, Roman

    2017-01-01

    The paper presents a deep learning approach for automatic classification of breast tumors based on fine needle cytology. The main aim of the system is to distinguish benign from malignant cases based on microscopic images. Experiment was carried out on cytological samples derived from 50 patients (25 benign cases + 25 malignant cases) diagnosed in Regional Hospital in Zielona Góra. To classify microscopic images, we used convolutional neural networks (CNN) of two types: GoogLeNet and AlexNet. Due to the very large size of images of cytological specimen (on average 200000 × 100000 pixels), they were divided into smaller patches of size 256 × 256 pixels. Breast cancer classification usually is based on morphometric features of nuclei. Therefore, training and validation patches were selected using Support Vector Machine (SVM) so that suitable amount of cell material was depicted. Neural classifiers were tuned using GPU accelerated implementation of gradient descent algorithm. Training error was defined as a cross-entropy classification loss. Classification accuracy was defined as the percentage ratio of successfully classified validation patches to the total number of validation patches. The best accuracy rate of 83% was obtained by GoogLeNet model. We observed that more misclassified patches belong to malignant cases.

  19. Side effects of cancer therapies. International classification and documentation systems

    International Nuclear Information System (INIS)

    Seegenschmiedt, M.H.

    1998-01-01

    The publication presents and explains verified, international classification and documentation systems for side effects induced by cancer treatments, applicable in general and clinical practice and clinical research, and covers in a clearly arranged manner the whole range of treatments, including acute and chronic side effects of chemotherapy and radiotherapy, surgery, or combined therapies. The book fills a long-felt need in tumor documentation and is a major contribution to quality assurance in clinical oncology in German-speaking countries. As most parts of the book are bilingual, presenting German and English texts and terminology, it satisfies the principles of interdisciplinarity and internationality. The tabulated form chosen for presentation of classification systems and criteria facilitate the user's approach as well as application in daily work. (orig./CB) [de

  20. Geometric classification of scalp hair for valid drug testing, 6 more reliable than 8 hair curl groups.

    Directory of Open Access Journals (Sweden)

    K Mkentane

    Full Text Available Curly hair is reported to contain higher lipid content than straight hair, which may influence incorporation of lipid soluble drugs. The use of race to describe hair curl variation (Asian, Caucasian and African is unscientific yet common in medical literature (including reports of drug levels in hair. This study investigated the reliability of a geometric classification of hair (based on 3 measurements: the curve diameter, curl index and number of waves.After ethical approval and informed consent, proximal virgin (6cm hair sampled from the vertex of scalp in 48 healthy volunteers were evaluated. Three raters each scored hairs from 48 volunteers at two occasions each for the 8 and 6-group classifications. One rater applied the 6-group classification to 80 additional volunteers in order to further confirm the reliability of this system. The Kappa statistic was used to assess intra and inter rater agreement.Each rater classified 480 hairs on each occasion. No rater classified any volunteer's 10 hairs into the same group; the most frequently occurring group was used for analysis. The inter-rater agreement was poor for the 8-groups (k = 0.418 but improved for the 6-groups (k = 0.671. The intra-rater agreement also improved (k = 0.444 to 0.648 versus 0.599 to 0.836 for 6-groups; that for the one evaluator for all volunteers was good (k = 0.754.Although small, this is the first study to test the reliability of a geometric classification. The 6-group method is more reliable. However, a digital classification system is likely to reduce operator error. A reliable objective classification of human hair curl is long overdue, particularly with the increasing use of hair as a testing substrate for treatment compliance in Medicine.

  1. Classification of breast cancer histology images using Convolutional Neural Networks.

    Directory of Open Access Journals (Sweden)

    Teresa Araújo

    Full Text Available Breast cancer is one of the main causes of cancer death worldwide. The diagnosis of biopsy tissue with hematoxylin and eosin stained images is non-trivial and specialists often disagree on the final diagnosis. Computer-aided Diagnosis systems contribute to reduce the cost and increase the efficiency of this process. Conventional classification approaches rely on feature extraction methods designed for a specific problem based on field-knowledge. To overcome the many difficulties of the feature-based approaches, deep learning methods are becoming important alternatives. A method for the classification of hematoxylin and eosin stained breast biopsy images using Convolutional Neural Networks (CNNs is proposed. Images are classified in four classes, normal tissue, benign lesion, in situ carcinoma and invasive carcinoma, and in two classes, carcinoma and non-carcinoma. The architecture of the network is designed to retrieve information at different scales, including both nuclei and overall tissue organization. This design allows the extension of the proposed system to whole-slide histology images. The features extracted by the CNN are also used for training a Support Vector Machine classifier. Accuracies of 77.8% for four class and 83.3% for carcinoma/non-carcinoma are achieved. The sensitivity of our method for cancer cases is 95.6%.

  2. Application of machine learning on brain cancer multiclass classification

    Science.gov (United States)

    Panca, V.; Rustam, Z.

    2017-07-01

    Classification of brain cancer is a problem of multiclass classification. One approach to solve this problem is by first transforming it into several binary problems. The microarray gene expression dataset has the two main characteristics of medical data: extremely many features (genes) and only a few number of samples. The application of machine learning on microarray gene expression dataset mainly consists of two steps: feature selection and classification. In this paper, the features are selected using a method based on support vector machine recursive feature elimination (SVM-RFE) principle which is improved to solve multiclass classification, called multiple multiclass SVM-RFE. Instead of using only the selected features on a single classifier, this method combines the result of multiple classifiers. The features are divided into subsets and SVM-RFE is used on each subset. Then, the selected features on each subset are put on separate classifiers. This method enhances the feature selection ability of each single SVM-RFE. Twin support vector machine (TWSVM) is used as the method of the classifier to reduce computational complexity. While ordinary SVM finds single optimum hyperplane, the main objective Twin SVM is to find two non-parallel optimum hyperplanes. The experiment on the brain cancer microarray gene expression dataset shows this method could classify 71,4% of the overall test data correctly, using 100 and 1000 genes selected from multiple multiclass SVM-RFE feature selection method. Furthermore, the per class results show that this method could classify data of normal and MD class with 100% accuracy.

  3. Classification of Cancer-related Death Certificates using Machine Learning

    Directory of Open Access Journals (Sweden)

    Luke Butt

    2013-05-01

    Full Text Available BackgroundCancer monitoring and prevention relies on the critical aspect of timely notification of cancer cases. However, the abstraction and classification of cancer from the free-text of pathology reports and other relevant documents, such as death certificates, exist as complex and time-consuming activities.AimsIn this paper, approaches for the automatic detection of notifiable cancer cases as the cause of death from free-text death certificates supplied to Cancer Registries are investigated.Method A number of machine learning classifiers were studied. Features were extracted using natural language techniques and the Medtex toolkit. The numerous features encompassed stemmed words, bi-grams, and concepts from the SNOMED CT medical terminology. The baseline consisted of a keyword spotter using keywords extracted from the long description of ICD-10 cancer related codes.ResultsDeath certificates with notifiable cancer listed as the cause of death can be effectively identified with the methods studied in this paper. A Support Vector Machine (SVM classifier achieved best performance with an overall F-measure of 0.9866 when evaluated on a set of 5,000 free-text death certificates using the token stem feature set. The SNOMED CT concept plus token stem feature set reached the lowest variance (0.0032 and false negative rate (0.0297 while achieving an F-measure of 0.9864. The SVM classifier accounts for the first 18 of the top 40 evaluated runs, and entails the most robust classifier with a variance of 0.001141, half the variance of the other classifiers.ConclusionThe selection of features significantly produced the most influences on the performance of the classifiers, although the type of classifier employed also affects performance. In contrast, the feature weighting schema created a negligible effect on performance. Specifically, it is found that stemmed tokens with or without SNOMED CT concepts create the most effective feature when combined with

  4. COII "long fragment" reliability in characterisation and classification of forensically important flies

    Science.gov (United States)

    Aly, Sanaa M; Mahmoud, Shereen M

    2016-01-01

    Molecular identification of collected flies is important in forensic entomological analysis guided with accurate evaluation of the chosen genetic marker. The selected mitochondrial DNA segments can be used to properly identify species. The aim of the present study was to determine the reliability of the 635-bp-long cytochrome oxidase II gene (COII) in identification of forensically important flies. Forty-two specimens belonging to 11 species (Calliphoridae: Chrysomya albiceps, C. rufifacies, C. megacephala, Lucilia sericata, L. cuprina; Sarcophagidae: Sarcophaga carnaria, S. dux, S. albiceps, Wohlfahrtia nuba; Muscidae: Musca domestica, M. autumnalis) were analysed. The selected marker was amplified using PCR followed by sequencing. Nucleotide sequence divergences were calculated using the K2P (Kimura two-parameter) distance model, and a NJ (neighbour-joining) phylogenetic tree was constructed. All examined specimens were assigned to the correct species, formed distinct monophyletic clades and ordered in accordance with their taxonomic classification. Intraspecific variation ranged from 0 to 1% and interspecific variation occurred between 2 and 20%. The 635-bp-long COII marker is suitable for clear differentiation and identification of forensically relevant flies.

  5. Reliable classification of moving waste materials with LIBS in concrete recycling.

    Science.gov (United States)

    Xia, Han; Bakker, M C M

    2014-03-01

    Effective discrimination between different waste materials is of paramount importance for inline quality inspection of recycle concrete aggregates from demolished buildings. The moving targeted materials in the concrete waste stream are wood, PVC, gypsum block, glass, brick, steel rebar, aggregate and cement paste. For each material, up to three different types were considered, while thirty particles of each material were selected. Proposed is a reliable classification methodology based on integration of the LIBS spectral emissions in a fixed time window, starting from the deployment of the laser shot. PLS-DA (multi class) and the hybrid combination PCA-Adaboost (binary class) were investigated as efficient classifiers. In addition, mean centre and auto scaling approaches were compared for both classifiers. Using 72 training spectra and 18 test spectra per material, each averaged by ten shots, only PLS-DA achieved full discrimination, and the mean centre approach made it slightly more robust. Continuing with PLS-DA, the relation between data averaging and convergence to 0.3% average error was investigated using 9-fold cross-validations. Single-shot PLS-DA presented the highest challenge and most desirable methodology, which converged with 59 PC. The degree of success in practical testing will depend on the quality of the training set and the implications of the possibly remaining false positives. © 2013 Published by Elsevier B.V.

  6. COII ”long fragment” reliability in characterisation and classification of forensically important flies

    Directory of Open Access Journals (Sweden)

    Sanaa M. Aly

    2017-01-01

    Full Text Available Introduction : Molecular identification of collected flies is important in forensic entomological analysis guided with accurate evaluation of the chosen genetic marker. The selected mitochondrial DNA segments can be used to properly identify species. The aim of the present study was to determine the reliability of the 635-bp-long cytochrome oxidase II gene (COII in identification of forensically important flies. Material and methods: Forty-two specimens belonging to 11 species ( Calliphoridae: Chrysomya albiceps , C. rufifacies , C. megacephala , Lucilia sericata , L. cuprina ; Sarcophagidae: Sarcophaga carnaria , S. dux , S. albiceps , Wohlfahrtia nuba ; Muscidae: Musca domestica , M. autumnalis were analysed. The selected marker was amplified using PCR followed by sequencing. Nucleotide sequence divergences were calculated using the K2P (Kimura two-parameter distance model, and a NJ (neighbour-joining phylogenetic tree was constructed. Results : All examined specimens were assigned to the correct species, formed distinct monophyletic clades and ordered in accordance with their taxonomic classification. Intraspecific variation ranged from 0 to 1% and interspecific variation occurred between 2 and 20%. Conclusions : The 635-bp-long COII marker is suitable for clear differentiation and identification of forensically relevant flies.

  7. Breast cancer molecular subtype classification using deep features: preliminary results

    Science.gov (United States)

    Zhu, Zhe; Albadawy, Ehab; Saha, Ashirbani; Zhang, Jun; Harowicz, Michael R.; Mazurowski, Maciej A.

    2018-02-01

    Radiogenomics is a field of investigation that attempts to examine the relationship between imaging characteris- tics of cancerous lesions and their genomic composition. This could offer a noninvasive alternative to establishing genomic characteristics of tumors and aid cancer treatment planning. While deep learning has shown its supe- riority in many detection and classification tasks, breast cancer radiogenomic data suffers from a very limited number of training examples, which renders the training of the neural network for this problem directly and with no pretraining a very difficult task. In this study, we investigated an alternative deep learning approach referred to as deep features or off-the-shelf network approach to classify breast cancer molecular subtypes using breast dynamic contrast enhanced MRIs. We used the feature maps of different convolution layers and fully connected layers as features and trained support vector machines using these features for prediction. For the feature maps that have multiple layers, max-pooling was performed along each channel. We focused on distinguishing the Luminal A subtype from other subtypes. To evaluate the models, 10 fold cross-validation was performed and the final AUC was obtained by averaging the performance of all the folds. The highest average AUC obtained was 0.64 (0.95 CI: 0.57-0.71), using the feature maps of the last fully connected layer. This indicates the promise of using this approach to predict the breast cancer molecular subtypes. Since the best performance appears in the last fully connected layer, it also implies that breast cancer molecular subtypes may relate to high level image features

  8. Reliability

    OpenAIRE

    Condon, David; Revelle, William

    2017-01-01

    Separating the signal in a test from the irrelevant noise is a challenge for all measurement. Low test reliability limits test validity, attenuates important relationships, and can lead to regression artifacts. Multiple approaches to the assessment and improvement of reliability are discussed. The advantages and disadvantages of several different approaches to reliability are considered. Practical advice on how to assess reliability using open source software is provided.

  9. Reliability in content analysis: The case of semantic feature norms classification.

    Science.gov (United States)

    Bolognesi, Marianna; Pilgram, Roosmaryn; van den Heerik, Romy

    2017-12-01

    Semantic feature norms (e.g., STIMULUS: car → RESPONSE: ) are commonly used in cognitive psychology to look into salient aspects of given concepts. Semantic features are typically collected in experimental settings and then manually annotated by the researchers into feature types (e.g., perceptual features, taxonomic features, etc.) by means of content analyses-that is, by using taxonomies of feature types and having independent coders perform the annotation task. However, the ways in which such content analyses are typically performed and reported are not consistent across the literature. This constitutes a serious methodological problem that might undermine the theoretical claims based on such annotations. In this study, we first offer a review of some of the released datasets of annotated semantic feature norms and the related taxonomies used for content analysis. We then provide theoretical and methodological insights in relation to the content analysis methodology. Finally, we apply content analysis to a new dataset of semantic features and show how the method should be applied in order to deliver reliable annotations and replicable coding schemes. We tackle the following issues: (1) taxonomy structure, (2) the description of categories, (3) coder training, and (4) sustainability of the coding scheme-that is, comparison of the annotations provided by trained versus novice coders. The outcomes of the project are threefold: We provide methodological guidelines for semantic feature classification; we provide a revised and adapted taxonomy that can (arguably) be applied to both concrete and abstract concepts; and we provide a dataset of annotated semantic feature norms.

  10. Histopathological Breast Cancer Image Classification by Deep Neural Network Techniques Guided by Local Clustering.

    Science.gov (United States)

    Nahid, Abdullah-Al; Mehrabi, Mohamad Ali; Kong, Yinan

    2018-01-01

    Breast Cancer is a serious threat and one of the largest causes of death of women throughout the world. The identification of cancer largely depends on digital biomedical photography analysis such as histopathological images by doctors and physicians. Analyzing histopathological images is a nontrivial task, and decisions from investigation of these kinds of images always require specialised knowledge. However, Computer Aided Diagnosis (CAD) techniques can help the doctor make more reliable decisions. The state-of-the-art Deep Neural Network (DNN) has been recently introduced for biomedical image analysis. Normally each image contains structural and statistical information. This paper classifies a set of biomedical breast cancer images (BreakHis dataset) using novel DNN techniques guided by structural and statistical information derived from the images. Specifically a Convolutional Neural Network (CNN), a Long-Short-Term-Memory (LSTM), and a combination of CNN and LSTM are proposed for breast cancer image classification. Softmax and Support Vector Machine (SVM) layers have been used for the decision-making stage after extracting features utilising the proposed novel DNN models. In this experiment the best Accuracy value of 91.00% is achieved on the 200x dataset, the best Precision value 96.00% is achieved on the 40x dataset, and the best F -Measure value is achieved on both the 40x and 100x datasets.

  11. Involvement of Machine Learning for Breast Cancer Image Classification: A Survey

    OpenAIRE

    Nahid, Abdullah-Al; Kong, Yinan

    2017-01-01

    Breast cancer is one of the largest causes of women’s death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors’ and physicians’ time. Despite the various publications on breast image classification, very few review papers are available w...

  12. Gene selection for cancer classification with the help of bees.

    Science.gov (United States)

    Moosa, Johra Muhammad; Shakur, Rameen; Kaykobad, Mohammad; Rahman, Mohammad Sohel

    2016-08-10

    Development of biologically relevant models from gene expression data notably, microarray data has become a topic of great interest in the field of bioinformatics and clinical genetics and oncology. Only a small number of gene expression data compared to the total number of genes explored possess a significant correlation with a certain phenotype. Gene selection enables researchers to obtain substantial insight into the genetic nature of the disease and the mechanisms responsible for it. Besides improvement of the performance of cancer classification, it can also cut down the time and cost of medical diagnoses. This study presents a modified Artificial Bee Colony Algorithm (ABC) to select minimum number of genes that are deemed to be significant for cancer along with improvement of predictive accuracy. The search equation of ABC is believed to be good at exploration but poor at exploitation. To overcome this limitation we have modified the ABC algorithm by incorporating the concept of pheromones which is one of the major components of Ant Colony Optimization (ACO) algorithm and a new operation in which successive bees communicate to share their findings. The proposed algorithm is evaluated using a suite of ten publicly available datasets after the parameters are tuned scientifically with one of the datasets. Obtained results are compared to other works that used the same datasets. The performance of the proposed method is proved to be superior. The method presented in this paper can provide subset of genes leading to more accurate classification results while the number of selected genes is smaller. Additionally, the proposed modified Artificial Bee Colony Algorithm could conceivably be applied to problems in other areas as well.

  13. Inter-rater reliability in the classification of supraspinatus tendon tears using 3D ultrasound – a question of experience?

    Directory of Open Access Journals (Sweden)

    Giorgio Tamborrini

    2016-09-01

    Full Text Available Background: Three-dimensional (3D ultrasound of the shoulder is characterized by a comparable accuracy to two-dimensional (2D ultrasound. No studies investigating 2D versus 3D inter-rater reliability in the detection of supraspinatus tendon tears taking into account the level of experience of the raters have been carried out so far. Objectives: The aim of this study was to determine the inter-rater reliability in the analysis of 3D ultrasound image sets of the supraspinatus tendon between sonographer with different levels of experience. Patients and methods: Non-interventional, prospective, observational pilot study of 2309 images of 127 adult patients suffering from unilateral shoulder pain. 3D ultrasound image sets were scored by three raters independently. The intra-and interrater reliabilities were calculated. Results: There was an excellent intra-rater reliability of rater A in the overall classification of supraspinatus tendon tears (2D vs 3D κ = 0.892, pairwise reliability 93.81%, 3D scoring round 1 vs 3D scoring round 2 κ = 0.875, pairwise reliability 92.857%. The inter-rater reliability was only moderate compared to rater B on 3D (κ = 0.497, pairwise reliability 70.95% and fair compared to rater C (κ = 0.238, pairwise reliability 42.38%. Conclusions: The reliability of 3D ultrasound of the supraspinatus tendon depends on the level of experience of the sonographer. Experience in 2D ultrasound does not seem to be sufficient for the analysis of 3D ultrasound imaging sets. Therefore, for a 3D ultrasound analysis new diagnostic criteria have to be established and taught even to experienced 2D sonographers to improve reproducibility.

  14. Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value.

    Directory of Open Access Journals (Sweden)

    Laetitia Marisa

    Full Text Available Colon cancer (CC pathological staging fails to accurately predict recurrence, and to date, no gene expression signature has proven reliable for prognosis stratification in clinical practice, perhaps because CC is a heterogeneous disease. The aim of this study was to establish a comprehensive molecular classification of CC based on mRNA expression profile analyses.Fresh-frozen primary tumor samples from a large multicenter cohort of 750 patients with stage I to IV CC who underwent surgery between 1987 and 2007 in seven centers were characterized for common DNA alterations, including BRAF, KRAS, and TP53 mutations, CpG island methylator phenotype, mismatch repair status, and chromosomal instability status, and were screened with whole genome and transcriptome arrays. 566 samples fulfilled RNA quality requirements. Unsupervised consensus hierarchical clustering applied to gene expression data from a discovery subset of 443 CC samples identified six molecular subtypes. These subtypes were associated with distinct clinicopathological characteristics, molecular alterations, specific enrichments of supervised gene expression signatures (stem cell phenotype-like, normal-like, serrated CC phenotype-like, and deregulated signaling pathways. Based on their main biological characteristics, we distinguished a deficient mismatch repair subtype, a KRAS mutant subtype, a cancer stem cell subtype, and three chromosomal instability subtypes, including one associated with down-regulated immune pathways, one with up-regulation of the Wnt pathway, and one displaying a normal-like gene expression profile. The classification was validated in the remaining 123 samples plus an independent set of 1,058 CC samples, including eight public datasets. Furthermore, prognosis was analyzed in the subset of stage II-III CC samples. The subtypes C4 and C6, but not the subtypes C1, C2, C3, and C5, were independently associated with shorter relapse-free survival, even after

  15. Gross Motor Function Classification System Expanded & Revised (GMFCS E & R: reliability between therapists and parents in Brazil

    Directory of Open Access Journals (Sweden)

    Daniela B. R. Silva

    2013-10-01

    Full Text Available BACKGROUND: Several studies have demonstrated the importance of using the Gross Motor Function Classification System (GMFCS to classify gross motor function in children with cerebral palsy, but the reliability of the expanded and revised version has not been examined in Brazil (GMFCS E & R. OBJECTIVE:: To determine the intra- and inter-rater reliability of the Portuguese-Brazil version of the GMFCS E & R applied by therapists and compare to classification provided by parents of children with cerebral palsy. METHOD: Data were obtained from 90 children with cerebral palsy, aged 4 to 18 years old, attending the neurology or rehabilitation service of a Brazilian hospital. Therapists classified the children's motor function using the GMFCS E & R and parents used the Brazilian Portuguese version of the GMFCS Family Report Questionnaire. Intra- and inter-rater reliability was obtained through percentage agreement and Cohen's unweighted Kappa statistics (k. The Chi-square test was used to identify significant differences in the classification of parents and therapists. RESULTS: Almost perfect agreement was reached between the therapists [K=0.90 (95% confidence interval 0.83-0.97] and intra-raters (therapists with K=1.00 [95% confidence interval (1.00-1.00], p<0.001. Agreement between therapists and parents was substantial (k=0.716, confidence interval 0.596-0.836, though parents classify gross motor impairment more severely than therapists (p=0.04. CONCLUSIONS: The Portuguese version of the GMFCS E & R is reliable for use by parents and therapists. Parents tend to classify their children's limitations more severely, because they know their performance in different environments.

  16. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  17. Three-class classification in computer-aided diagnosis of breast cancer by support vector machine

    Science.gov (United States)

    Sun, Xuejun; Qian, Wei; Song, Dansheng

    2004-05-01

    Design of classifier in computer-aided diagnosis (CAD) scheme of breast cancer plays important role to its overall performance in sensitivity and specificity. Classification of a detected object as malignant lesion, benign lesion, or normal tissue on mammogram is a typical three-class pattern recognition problem. This paper presents a three-class classification approach by using two-stage classifier combined with support vector machine (SVM) learning algorithm for classification of breast cancer on mammograms. The first classification stage is used to detect abnormal areas and normal breast tissues, and the second stage is for classification of malignant or benign in detected abnormal objects. A series of spatial, morphology and texture features have been extracted on detected objects areas. By using genetic algorithm (GA), different feature groups for different stage classification have been investigated. Computerized free-response receiver operating characteristic (FROC) and receiver operating characteristic (ROC) analyses have been employed in different classification stages. Results have shown that obvious performance improvement in both sensitivity and specificity was observed through proposed classification approach compared with conventional two-class classification approaches, indicating its effectiveness in classification of breast cancer on mammograms.

  18. Quantum Cascade Laser-Based Infrared Microscopy for Label-Free and Automated Cancer Classification in Tissue Sections.

    Science.gov (United States)

    Kuepper, Claus; Kallenbach-Thieltges, Angela; Juette, Hendrik; Tannapfel, Andrea; Großerueschkamp, Frederik; Gerwert, Klaus

    2018-05-16

    A feasibility study using a quantum cascade laser-based infrared microscope for the rapid and label-free classification of colorectal cancer tissues is presented. Infrared imaging is a reliable, robust, automated, and operator-independent tissue classification method that has been used for differential classification of tissue thin sections identifying tumorous regions. However, long acquisition time by the so far used FT-IR-based microscopes hampered the clinical translation of this technique. Here, the used quantum cascade laser-based microscope provides now infrared images for precise tissue classification within few minutes. We analyzed 110 patients with UICC-Stage II and III colorectal cancer, showing 96% sensitivity and 100% specificity of this label-free method as compared to histopathology, the gold standard in routine clinical diagnostics. The main hurdle for the clinical translation of IR-Imaging is overcome now by the short acquisition time for high quality diagnostic images, which is in the same time range as frozen sections by pathologists.

  19. Detection and classification of Breast Cancer in Wavelet Sub-bands of Fractal Segmented Cancerous Zones.

    Science.gov (United States)

    Shirazinodeh, Alireza; Noubari, Hossein Ahmadi; Rabbani, Hossein; Dehnavi, Alireza Mehri

    2015-01-01

    Recent studies on wavelet transform and fractal modeling applied on mammograms for the detection of cancerous tissues indicate that microcalcifications and masses can be utilized for the study of the morphology and diagnosis of cancerous cases. It is shown that the use of fractal modeling, as applied to a given image, can clearly discern cancerous zones from noncancerous areas. In this paper, for fractal modeling, the original image is first segmented into appropriate fractal boxes followed by identifying the fractal dimension of each windowed section using a computationally efficient two-dimensional box-counting algorithm. Furthermore, using appropriate wavelet sub-bands and image Reconstruction based on modified wavelet coefficients, it is shown that it is possible to arrive at enhanced features for detection of cancerous zones. In this paper, we have attempted to benefit from the advantages of both fractals and wavelets by introducing a new algorithm. By using a new algorithm named F1W2, the original image is first segmented into appropriate fractal boxes, and the fractal dimension of each windowed section is extracted. Following from that, by applying a maximum level threshold on fractal dimensions matrix, the best-segmented boxes are selected. In the next step, the segmented Cancerous zones which are candidates are then decomposed by utilizing standard orthogonal wavelet transform and db2 wavelet in three different resolution levels, and after nullifying wavelet coefficients of the image at the first scale and low frequency band of the third scale, the modified reconstructed image is successfully utilized for detection of breast cancer regions by applying an appropriate threshold. For detection of cancerous zones, our simulations indicate the accuracy of 90.9% for masses and 88.99% for microcalcifications detection results using the F1W2 method. For classification of detected mictocalcification into benign and malignant cases, eight features are identified and

  20. Reliability analysis of the AOSpine thoracolumbar spine injury classification system by a worldwide group of naïve spinal surgeons.

    Science.gov (United States)

    Kepler, Christopher K; Vaccaro, Alexander R; Koerner, John D; Dvorak, Marcel F; Kandziora, Frank; Rajasekaran, Shanmuganathan; Aarabi, Bizhan; Vialle, Luiz R; Fehlings, Michael G; Schroeder, Gregory D; Reinhold, Maximilian; Schnake, Klaus John; Bellabarba, Carlo; Cumhur Öner, F

    2016-04-01

    The aims of this study were (1) to demonstrate the AOSpine thoracolumbar spine injury classification system can be reliably applied by an international group of surgeons and (2) to delineate those injury types which are difficult for spine surgeons to classify reliably. A previously described classification system of thoracolumbar injuries which consists of a morphologic classification of the fracture, a grading system for the neurologic status and relevant patient-specific modifiers was applied to 25 cases by 100 spinal surgeons from across the world twice independently, in grading sessions 1 month apart. The results were analyzed for classification reliability using the Kappa coefficient (κ). The overall Kappa coefficient for all cases was 0.56, which represents moderate reliability. Kappa values describing interobserver agreement were 0.80 for type A injuries, 0.68 for type B injuries and 0.72 for type C injuries, all representing substantial reliability. The lowest level of agreement for specific subtypes was for fracture subtype A4 (Kappa = 0.19). Intraobserver analysis demonstrated overall average Kappa statistic for subtype grading of 0.68 also representing substantial reproducibility. In a worldwide sample of spinal surgeons without previous exposure to the recently described AOSpine Thoracolumbar Spine Injury Classification System, we demonstrated moderate interobserver and substantial intraobserver reliability. These results suggest that most spine surgeons can reliably apply this system to spine trauma patients as or more reliably than previously described systems.

  1. Classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2017-01-01

    This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

  2. Interobserver and intraobserver reliability and validity of the Vancouver classification system of periprosthetic femoral fractures after hip arthroplasty.

    LENUS (Irish Health Repository)

    Naqvi, Gohar A

    2012-06-01

    The Vancouver classification system of periprosthetic fractures has been revalidated in this study, using the radiographs of 45 patients. Three consultants and 3 trainees reviewed the radiographs independently, on 2 separate occasions, at least 2 weeks apart. Interobserver and intraobserver agreement and validity were analyzed, using weighted κ statistics. The mean κ value for interobserver agreement was found to be 0.69 (0.63-0.72) for consultants and 0.61 (0.56-0.65) for the trainees, both representing substantial agreement. Intraobserver κ values ranged from 0.74 to 0.90, showing substantial agreement. Validity analysis of 37 type B cases revealed 81% agreement within B1, B2, and B3 subgroups with a κ value of 0.68 (substantial agreement). This study has reconfirmed the reliability and validity of the Vancouver classification while it also emphasizes the intraoperative assessment of implant stability.

  3. Fluorescently labeled bevacizumab in human breast cancer: defining the classification threshold

    Science.gov (United States)

    Koch, Maximilian; de Jong, Johannes S.; Glatz, Jürgen; Symvoulidis, Panagiotis; Lamberts, Laetitia E.; Adams, Arthur L. L.; Kranendonk, Mariëtte E. G.; Terwisscha van Scheltinga, Anton G. T.; Aichler, Michaela; Jansen, Liesbeth; de Vries, Jakob; Lub-de Hooge, Marjolijn N.; Schröder, Carolien P.; Jorritsma-Smit, Annelies; Linssen, Matthijs D.; de Boer, Esther; van der Vegt, Bert; Nagengast, Wouter B.; Elias, Sjoerd G.; Oliveira, Sabrina; Witkamp, Arjen J.; Mali, Willem P. Th. M.; Van der Wall, Elsken; Garcia-Allende, P. Beatriz; van Diest, Paul J.; de Vries, Elisabeth G. E.; Walch, Axel; van Dam, Gooitzen M.; Ntziachristos, Vasilis

    2017-07-01

    In-vivo fluorescently labelled drug (bevacizumab) breast cancer specimen where obtained from patients. We propose a new structured method to determine the optimal classification threshold in targeted fluorescence intra-operative imaging.

  4. Cancer Classification Based on Support Vector Machine Optimized by Particle Swarm Optimization and Artificial Bee Colony.

    Science.gov (United States)

    Gao, Lingyun; Ye, Mingquan; Wu, Changrong

    2017-11-29

    Intelligent optimization algorithms have advantages in dealing with complex nonlinear problems accompanied by good flexibility and adaptability. In this paper, the FCBF (Fast Correlation-Based Feature selection) method is used to filter irrelevant and redundant features in order to improve the quality of cancer classification. Then, we perform classification based on SVM (Support Vector Machine) optimized by PSO (Particle Swarm Optimization) combined with ABC (Artificial Bee Colony) approaches, which is represented as PA-SVM. The proposed PA-SVM method is applied to nine cancer datasets, including five datasets of outcome prediction and a protein dataset of ovarian cancer. By comparison with other classification methods, the results demonstrate the effectiveness and the robustness of the proposed PA-SVM method in handling various types of data for cancer classification.

  5. EPA`s program for risk assessment guidelines: Cancer classification issues

    Energy Technology Data Exchange (ETDEWEB)

    Wiltse, J. [Environmental Protection Agency, Washington, DC (United States)

    1990-12-31

    Issues presented are related to classification of weight of evidence in cancer risk assessments. The focus in this paper is on lines of evidence used in constructing a conclusion about potential human carcinogenicity. The paper also discusses issues that are mistakenly addressed as classification issues but are really part of the risk assessment process. 2 figs.

  6. Interobserver reliability of coronoid fracture classification: two-dimensional versus three-dimensional computed tomography

    NARCIS (Netherlands)

    Lindenhovius, Anneluuk; Karanicolas, Paul Jack; Bhandari, Mohit; van Dijk, Niek; Ring, David; Allan, Christopher; Anglen, Jeffrey; Axelrod, Terry; Baratz, Mark; Beingessner, Daphne; Brink, Peter; Cassidy, Charles; Coles, Chad; Conflitti, Joe; Crist, Brett; Della Rocca, Gregory; Dijkstra, Sander; Elmans, L. H. G. J.; Feibel, Roger; Flores, Luis; Frihagen, Frede; Gosens, Taco; Goslings, J. C.; Greenberg, Jeffrey; Grosso, Elena; Harness, Neil; van der Heide, Huub; Jeray, Kyle; Kalainov, David; van Kampen, Albert; Kawamura, Sumito; Kloen, Peter; McKee, Michael; Nork, Sean; Page, Richard; Pesantez, Rodrigo; Peters, Anil; Poolman, Rudolf; Prayson, Michael; Richardson, Martin; Seiler, John; Swiontkowski, Marc; Thomas, George; Trumble, Tom; van Vugt, Arie; Wright, Thomas; Zalavras, Charalampos; Zura, Robert

    2009-01-01

    This study tests the hypothesis that 3-dimensional computed tomography (CT) reconstructions improve interobserver agreement on classification and treatment of coronoid fractures compared with 2-dimensional CT. A total of 29 orthopedic surgeons evaluated 10 coronoid fractures on 2 occasions (first

  7. Reliable nanomaterial classification of powders using the volume-specific surface area method

    Energy Technology Data Exchange (ETDEWEB)

    Wohlleben, Wendel, E-mail: wendel.wohlleben@basf.com [Department of Material Physics, BASF SE (Germany); Mielke, Johannes [BAM–Federal Institute for Materials Research and Testing (Germany); Bianchin, Alvise [MBN Nanomaterialia s.p.a (Italy); Ghanem, Antoine [R& I Centre Brussels, Solvay (Belgium); Freiberger, Harald [Department of Material Physics, BASF SE (Germany); Rauscher, Hubert [European Commission, Nanobiosciences Unit, Joint Research Centre (Italy); Gemeinert, Marion; Hodoroaba, Vasile-Dan, E-mail: dan.hodoroaba@bam.de [BAM–Federal Institute for Materials Research and Testing (Germany)

    2017-02-15

    The volume-specific surface area (VSSA) of a particulate material is one of two apparently very different metrics recommended by the European Commission for a definition of “nanomaterial” for regulatory purposes: specifically, the VSSA metric may classify nanomaterials and non-nanomaterials differently than the median size in number metrics, depending on the chemical composition, size, polydispersity, shape, porosity, and aggregation of the particles in the powder. Here we evaluate the extent of agreement between classification by electron microscopy (EM) and classification by VSSA on a large set of diverse particulate substances that represent all the anticipated challenges except mixtures of different substances. EM and VSSA are determined in multiple labs to assess also the level of reproducibility. Based on the results obtained on highly characterized benchmark materials from the NanoDefine EU FP7 project, we derive a tiered screening strategy for the purpose of implementing the definition of nanomaterials. We finally apply the screening strategy to further industrial materials, which were classified correctly and left only borderline cases for EM. On platelet-shaped nanomaterials, VSSA is essential to prevent false-negative classification by EM. On porous materials, approaches involving extended adsorption isotherms prevent false positive classification by VSSA. We find no false negatives by VSSA, neither in Tier 1 nor in Tier 2, despite real-world industrial polydispersity and diverse composition, shape, and coatings. The VSSA screening strategy is recommended for inclusion in a technical guidance for the implementation of the definition.

  8. Reliable nanomaterial classification of powders using the volume-specific surface area method

    International Nuclear Information System (INIS)

    Wohlleben, Wendel; Mielke, Johannes; Bianchin, Alvise; Ghanem, Antoine; Freiberger, Harald; Rauscher, Hubert; Gemeinert, Marion; Hodoroaba, Vasile-Dan

    2017-01-01

    The volume-specific surface area (VSSA) of a particulate material is one of two apparently very different metrics recommended by the European Commission for a definition of “nanomaterial” for regulatory purposes: specifically, the VSSA metric may classify nanomaterials and non-nanomaterials differently than the median size in number metrics, depending on the chemical composition, size, polydispersity, shape, porosity, and aggregation of the particles in the powder. Here we evaluate the extent of agreement between classification by electron microscopy (EM) and classification by VSSA on a large set of diverse particulate substances that represent all the anticipated challenges except mixtures of different substances. EM and VSSA are determined in multiple labs to assess also the level of reproducibility. Based on the results obtained on highly characterized benchmark materials from the NanoDefine EU FP7 project, we derive a tiered screening strategy for the purpose of implementing the definition of nanomaterials. We finally apply the screening strategy to further industrial materials, which were classified correctly and left only borderline cases for EM. On platelet-shaped nanomaterials, VSSA is essential to prevent false-negative classification by EM. On porous materials, approaches involving extended adsorption isotherms prevent false positive classification by VSSA. We find no false negatives by VSSA, neither in Tier 1 nor in Tier 2, despite real-world industrial polydispersity and diverse composition, shape, and coatings. The VSSA screening strategy is recommended for inclusion in a technical guidance for the implementation of the definition.

  9. Inter-tester reliability of a new diagnostic classification system for patients with non-specific low back pain

    DEFF Research Database (Denmark)

    Petersen, Tom Erik; Olsen, Steen; Laslett, Mark

    2004-01-01

    Most patients referred to physiotherapy with low back pain are without a precise medical diagnosis. Identification of subgroups of non-specific low back pain patients may improve clinical outcomes and research efficiency. A pathoanatomic classification system has been developed, classifying...... modest level of total agreement (39%) for the system as a whole might indicate that the utility of the system for general screening purposes is limited, compared with the utility in identification of particular syndromes. Due to low prevalence of positive findings in some of the syndromes, future work...... should focus on testing reliability on a larger sample of patients, and testing of validity and feasibility of the system....

  10. Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features

    Directory of Open Access Journals (Sweden)

    Eman Magdy

    2015-01-01

    Full Text Available Computer-aided diagnostic (CAD systems provide fast and reliable diagnosis for medical images. In this paper, CAD system is proposed to analyze and automatically segment the lungs and classify each lung into normal or cancer. Using 70 different patients’ lung CT dataset, Wiener filtering on the original CT images is applied firstly as a preprocessing step. Secondly, we combine histogram analysis with thresholding and morphological operations to segment the lung regions and extract each lung separately. Amplitude-Modulation Frequency-Modulation (AM-FM method thirdly, has been used to extract features for ROIs. Then, the significant AM-FM features have been selected using Partial Least Squares Regression (PLSR for classification step. Finally, K-nearest neighbour (KNN, support vector machine (SVM, naïve Bayes, and linear classifiers have been used with the selected AM-FM features. The performance of each classifier in terms of accuracy, sensitivity, and specificity is evaluated. The results indicate that our proposed CAD system succeeded to differentiate between normal and cancer lungs and achieved 95% accuracy in case of the linear classifier.

  11. Identifying colon cancer risk modules with better classification performance based on human signaling network.

    Science.gov (United States)

    Qu, Xiaoli; Xie, Ruiqiang; Chen, Lina; Feng, Chenchen; Zhou, Yanyan; Li, Wan; Huang, Hao; Jia, Xu; Lv, Junjie; He, Yuehan; Du, Youwen; Li, Weiguo; Shi, Yuchen; He, Weiming

    2014-10-01

    Identifying differences between normal and tumor samples from a modular perspective may help to improve our understanding of the mechanisms responsible for colon cancer. Many cancer studies have shown that signaling transduction and biological pathways are disturbed in disease states, and expression profiles can distinguish variations in diseases. In this study, we integrated a weighted human signaling network and gene expression profiles to select risk modules associated with tumor conditions. Risk modules as classification features by our method had a better classification performance than other methods, and one risk module for colon cancer had a good classification performance for distinguishing between normal/tumor samples and between tumor stages. All genes in the module were annotated to the biological process of positive regulation of cell proliferation, and were highly associated with colon cancer. These results suggested that these genes might be the potential risk genes for colon cancer. Copyright © 2013. Published by Elsevier Inc.

  12. Reliability of a Novel CBCT-Based 3D Classification System for Maxillary Canine Impactions in Orthodontics: The KPG Index

    Science.gov (United States)

    Visconti, Luca; Martin, Conchita

    2013-01-01

    The aim of this study was to evaluate both intra- and interoperator reliability of a radiological three-dimensional classification system (KPG index) for the assessment of degree of difficulty for orthodontic treatment of maxillary canine impactions. Cone beam computed tomography (CBCT) scans of fifty impacted canines, obtained using three different scanners (NewTom, Kodak, and Planmeca), were classified using the KPG index by three independent orthodontists. Measurements were repeated one month later. Based on these two sessions, several recommendations on KPG Index scoring were elaborated. After a joint calibration session, these recommendations were explained to nine orthodontists and the two measurement sessions were repeated. There was a moderate intrarater agreement in the precalibration measurement sessions. After the calibration session, both intra- and interrater agreement were almost perfect. Indexes assessed with Kodak Dental Imaging 3D module software showed a better reliability in z-axis values, whereas indexes assessed with Planmeca Romexis software showed a better reliability in x- and y-axis values. No differences were found between the CBCT scanners used. Taken together, these findings indicate that the application of the instructions elaborated during this study improved KPG index reliability, which was nevertheless variously influenced by the use of different software for images evaluation. PMID:24235889

  13. Reliability of a Novel CBCT-Based 3D Classification System for Maxillary Canine Impactions in Orthodontics: The KPG Index

    Directory of Open Access Journals (Sweden)

    Domenico Dalessandri

    2013-01-01

    Full Text Available The aim of this study was to evaluate both intra- and interoperator reliability of a radiological three-dimensional classification system (KPG index for the assessment of degree of difficulty for orthodontic treatment of maxillary canine impactions. Cone beam computed tomography (CBCT scans of fifty impacted canines, obtained using three different scanners (NewTom, Kodak, and Planmeca, were classified using the KPG index by three independent orthodontists. Measurements were repeated one month later. Based on these two sessions, several recommendations on KPG Index scoring were elaborated. After a joint calibration session, these recommendations were explained to nine orthodontists and the two measurement sessions were repeated. There was a moderate intrarater agreement in the precalibration measurement sessions. After the calibration session, both intra- and interrater agreement were almost perfect. Indexes assessed with Kodak Dental Imaging 3D module software showed a better reliability in z-axis values, whereas indexes assessed with Planmeca Romexis software showed a better reliability in x- and y-axis values. No differences were found between the CBCT scanners used. Taken together, these findings indicate that the application of the instructions elaborated during this study improved KPG index reliability, which was nevertheless variously influenced by the use of different software for images evaluation.

  14. Classification of Amazonian rosewood essential oil by Raman spectroscopy and PLS-DA with reliability estimation.

    Science.gov (United States)

    Almeida, Mariana R; Fidelis, Carlos H V; Barata, Lauro E S; Poppi, Ronei J

    2013-12-15

    The Amazon tree Aniba rosaeodora Ducke (rosewood) provides an essential oil valuable for the perfume industry, but after decades of predatory extraction it is at risk of extinction. The extraction of the essential oil from wood implies the cutting of the tree, and then the study of oil extracted from the leaves is important as a sustainable alternative. The goal of this study was to test the applicability of Raman spectroscopy and Partial Least Square Discriminant Analysis (PLS-DA) as means to classify the essential oil extracted from different parties (wood, leaves and branches) of the Brazilian tree A. rosaeodora. For the development of classification models, the Raman spectra were split into two sets: training and test. The value of the limit that separates the classes was calculated based on the distribution of samples of training. This value was calculated in a manner that the classes are divided with a lower probability of incorrect classification for future estimates. The best model presented sensitivity and specificity of 100%, predictive accuracy and efficiency of 100%. These results give an overall vision of the behavior of the model, but do not give information about individual samples; in this case, the confidence interval for each sample of classification was also calculated using the resampling bootstrap technique. The methodology developed have the potential to be an alternative for standard procedures used for oil analysis and it can be employed as screening method, since it is fast, non-destructive and robust. © 2013 Elsevier B.V. All rights reserved.

  15. Cancer survival classification using integrated data sets and intermediate information.

    Science.gov (United States)

    Kim, Shinuk; Park, Taesung; Kon, Mark

    2014-09-01

    Although numerous studies related to cancer survival have been published, increasing the prediction accuracy of survival classes still remains a challenge. Integration of different data sets, such as microRNA (miRNA) and mRNA, might increase the accuracy of survival class prediction. Therefore, we suggested a machine learning (ML) approach to integrate different data sets, and developed a novel method based on feature selection with Cox proportional hazard regression model (FSCOX) to improve the prediction of cancer survival time. FSCOX provides us with intermediate survival information, which is usually discarded when separating survival into 2 groups (short- and long-term), and allows us to perform survival analysis. We used an ML-based protocol for feature selection, integrating information from miRNA and mRNA expression profiles at the feature level. To predict survival phenotypes, we used the following classifiers, first, existing ML methods, support vector machine (SVM) and random forest (RF), second, a new median-based classifier using FSCOX (FSCOX_median), and third, an SVM classifier using FSCOX (FSCOX_SVM). We compared these methods using 3 types of cancer tissue data sets: (i) miRNA expression, (ii) mRNA expression, and (iii) combined miRNA and mRNA expression. The latter data set included features selected either from the combined miRNA/mRNA profile or independently from miRNAs and mRNAs profiles (IFS). In the ovarian data set, the accuracy of survival classification using the combined miRNA/mRNA profiles with IFS was 75% using RF, 86.36% using SVM, 84.09% using FSCOX_median, and 88.64% using FSCOX_SVM with a balanced 22 short-term and 22 long-term survivor data set. These accuracies are higher than those using miRNA alone (70.45%, RF; 75%, SVM; 75%, FSCOX_median; and 75%, FSCOX_SVM) or mRNA alone (65.91%, RF; 63.64%, SVM; 72.73%, FSCOX_median; and 70.45%, FSCOX_SVM). Similarly in the glioblastoma multiforme data, the accuracy of miRNA/mRNA using IFS

  16. Inter-rater reliability of a modified version of Delitto et al.’s classification-based system for low back pain : a pilot study

    NARCIS (Netherlands)

    Apeldoorn, Adri T.; van Helvoirt, Hans; Ostelo, Raymond W.; Meihuizen, Hanneke; Kamper, Steven J.; van Tulder, Maurits W.; de Vet, Henrica C W

    2016-01-01

    Study design:: Observational inter-rater reliability study. Objectives: To examine: (1) the inter-rater reliability of a modified version of Delitto et al.’s classification-based algorithm for patients with low back pain; (2) the influence of different levels of familiarity with the system; and (3)

  17. On the International Agency for Research on Cancer classification of glyphosate as a probable human carcinogen.

    Science.gov (United States)

    Tarone, Robert E

    2018-01-01

    The recent classification by International Agency for Research on Cancer (IARC) of the herbicide glyphosate as a probable human carcinogen has generated considerable discussion. The classification is at variance with evaluations of the carcinogenic potential of glyphosate by several national and international regulatory bodies. The basis for the IARC classification is examined under the assumptions that the IARC criteria are reasonable and that the body of scientific studies determined by IARC staff to be relevant to the evaluation of glyphosate by the Monograph Working Group is sufficiently complete. It is shown that the classification of glyphosate as a probable human carcinogen was the result of a flawed and incomplete summary of the experimental evidence evaluated by the Working Group. Rational and effective cancer prevention activities depend on scientifically sound and unbiased assessments of the carcinogenic potential of suspected agents. Implications of the erroneous classification of glyphosate with respect to the IARC Monograph Working Group deliberative process are discussed.

  18. Efficacy of hidden markov model over support vector machine on multiclass classification of healthy and cancerous cervical tissues

    Science.gov (United States)

    Mukhopadhyay, Sabyasachi; Kurmi, Indrajit; Pratiher, Sawon; Mukherjee, Sukanya; Barman, Ritwik; Ghosh, Nirmalya; Panigrahi, Prasanta K.

    2018-02-01

    In this paper, a comparative study between SVM and HMM has been carried out for multiclass classification of cervical healthy and cancerous tissues. In our study, the HMM methodology is more promising to produce higher accuracy in classification.

  19. Involvement of Machine Learning for Breast Cancer Image Classification: A Survey

    Directory of Open Access Journals (Sweden)

    Abdullah-Al Nahid

    2017-01-01

    Full Text Available Breast cancer is one of the largest causes of women’s death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors’ and physicians’ time. Despite the various publications on breast image classification, very few review papers are available which provide a detailed description of breast cancer image classification techniques, feature extraction and selection procedures, classification measuring parameterizations, and image classification findings. We have put a special emphasis on the Convolutional Neural Network (CNN method for breast image classification. Along with the CNN method we have also described the involvement of the conventional Neural Network (NN, Logic Based classifiers such as the Random Forest (RF algorithm, Support Vector Machines (SVM, Bayesian methods, and a few of the semisupervised and unsupervised methods which have been used for breast image classification.

  20. Involvement of Machine Learning for Breast Cancer Image Classification: A Survey.

    Science.gov (United States)

    Nahid, Abdullah-Al; Kong, Yinan

    2017-01-01

    Breast cancer is one of the largest causes of women's death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors' and physicians' time. Despite the various publications on breast image classification, very few review papers are available which provide a detailed description of breast cancer image classification techniques, feature extraction and selection procedures, classification measuring parameterizations, and image classification findings. We have put a special emphasis on the Convolutional Neural Network (CNN) method for breast image classification. Along with the CNN method we have also described the involvement of the conventional Neural Network (NN), Logic Based classifiers such as the Random Forest (RF) algorithm, Support Vector Machines (SVM), Bayesian methods, and a few of the semisupervised and unsupervised methods which have been used for breast image classification.

  1. Classification of maltreatment-related mortality by Child Death Review teams: How reliable are they?

    Science.gov (United States)

    Parrish, Jared W; Schnitzer, Patricia G; Lanier, Paul; Shanahan, Meghan E; Daniels, Julie L; Marshall, Stephen W

    2017-05-01

    Accurate estimation of the incidence of maltreatment-related child mortality depends on reliable child fatality review. We examined the inter-rater reliability of maltreatment designation for two Alaskan Child Death Review (CDR) panels. Two different multidisciplinary CDR panels each reviewed a series of 101 infant and child deaths (ages 0-4 years) in Alaska. Both panels independently reviewed identical medical, autopsy, law enforcement, child welfare, and administrative records for each death utilizing the same maltreatment criteria. Percent agreement for maltreatment was 64.7% with a weighted Kappa of 0.61 (95% CI 0.51, 0.70). Across maltreatment subtypes, agreement was highest for abuse (69.3%) and lowest for negligence (60.4%). Discordance was higher if the mother was unmarried or a smoker, if residence was rural, or if there was a family history of child protective services report(s). Incidence estimates did not depend on which panel's data were used. There is substantial room for improvement in the reliability of CDR panel assessment of maltreatment related mortality. Standardized decision guidance for CDR panels may improve the reliability of their data. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. IDM-PhyChm-Ens: intelligent decision-making ensemble methodology for classification of human breast cancer using physicochemical properties of amino acids.

    Science.gov (United States)

    Ali, Safdar; Majid, Abdul; Khan, Asifullah

    2014-04-01

    Development of an accurate and reliable intelligent decision-making method for the construction of cancer diagnosis system is one of the fast growing research areas of health sciences. Such decision-making system can provide adequate information for cancer diagnosis and drug discovery. Descriptors derived from physicochemical properties of protein sequences are very useful for classifying cancerous proteins. Recently, several interesting research studies have been reported on breast cancer classification. To this end, we propose the exploitation of the physicochemical properties of amino acids in protein primary sequences such as hydrophobicity (Hd) and hydrophilicity (Hb) for breast cancer classification. Hd and Hb properties of amino acids, in recent literature, are reported to be quite effective in characterizing the constituent amino acids and are used to study protein foldings, interactions, structures, and sequence-order effects. Especially, using these physicochemical properties, we observed that proline, serine, tyrosine, cysteine, arginine, and asparagine amino acids offer high discrimination between cancerous and healthy proteins. In addition, unlike traditional ensemble classification approaches, the proposed 'IDM-PhyChm-Ens' method was developed by combining the decision spaces of a specific classifier trained on different feature spaces. The different feature spaces used were amino acid composition, split amino acid composition, and pseudo amino acid composition. Consequently, we have exploited different feature spaces using Hd and Hb properties of amino acids to develop an accurate method for classification of cancerous protein sequences. We developed ensemble classifiers using diverse learning algorithms such as random forest (RF), support vector machines (SVM), and K-nearest neighbor (KNN) trained on different feature spaces. We observed that ensemble-RF, in case of cancer classification, performed better than ensemble-SVM and ensemble-KNN. Our

  3. Intraobserver and interobserver reliability of recategorized Neer classification in differentiating 2-part surgical neck fractures from multi-fragmented proximal humeral fractures in 116 patients

    DEFF Research Database (Denmark)

    Sumrein, Bakir O; Mattila, Ville M; Lepola, Vesa

    2018-01-01

    BACKGROUND: Optimal fracture classification should be simple and reproducible and should guide treatment. For proximal humeral fractures, the Neer classification is commonly used. However, intraobserver and interobserver reliability of the Neer classification has been shown to be poor. In clinical...... for interobserver reliability showed substantial correlation (0.61-0.73) and was as follows: 0.73 for radiographs alone, 0.61 for CT scans alone, and 0.72 for radiographs and CT scans viewed together. After 24 weeks, the process was repeated and intraobserver reliability was calculated.The κ coefficient...... for intraobserver reliability showed substantial correlation (0.62-0.75) and was as follows: 0.62 for radiographs alone, 0.64 for CT scans alone, and 0.75 for radiographs and CT scans viewed together. CONCLUSION: Clinicians were able to differentiate 2-part surgical neck fractures from multi-fragmented fractures...

  4. hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine.

    Science.gov (United States)

    Falgreen, Steffen; Ellern Bilgrau, Anders; Brøndum, Rasmus Froberg; Hjort Jakobsen, Lasse; Have, Jonas; Lindblad Nielsen, Kasper; El-Galaly, Tarec Christoffer; Bødker, Julie Støve; Schmitz, Alexander; H Young, Ken; Johnsen, Hans Erik; Dybkær, Karen; Bøgsted, Martin

    2016-01-01

    Dozens of omics based cancer classification systems have been introduced with prognostic, diagnostic, and predictive capabilities. However, they often employ complex algorithms and are only applicable on whole cohorts of patients, making them difficult to apply in a personalized clinical setting. This prompted us to create hemaClass.org, an online web application providing an easy interface to one-by-one RMA normalization of microarrays and subsequent risk classifications of diffuse large B-cell lymphoma (DLBCL) into cell-of-origin and chemotherapeutic sensitivity classes. Classification results for one-by-one array pre-processing with and without a laboratory specific RMA reference dataset were compared to cohort based classifiers in 4 publicly available datasets. Classifications showed high agreement between one-by-one and whole cohort pre-processsed data when a laboratory specific reference set was supplied. The website is essentially the R-package hemaClass accompanied by a Shiny web application. The well-documented package can be used to run the website locally or to use the developed methods programmatically. The website and R-package is relevant for biological and clinical lymphoma researchers using affymetrix U-133 Plus 2 arrays, as it provides reliable and swift methods for calculation of disease subclasses. The proposed one-by-one pre-processing method is relevant for all researchers using microarrays.

  5. A New Direction of Cancer Classification: Positive Effect of Low-Ranking MicroRNAs.

    Science.gov (United States)

    Li, Feifei; Piao, Minghao; Piao, Yongjun; Li, Meijing; Ryu, Keun Ho

    2014-10-01

    Many studies based on microRNA (miRNA) expression profiles showed a new aspect of cancer classification. Because one characteristic of miRNA expression data is the high dimensionality, feature selection methods have been used to facilitate dimensionality reduction. The feature selection methods have one shortcoming thus far: they just consider the problem of where feature to class is 1:1 or n:1. However, because one miRNA may influence more than one type of cancer, human miRNA is considered to be ranked low in traditional feature selection methods and are removed most of the time. In view of the limitation of the miRNA number, low-ranking miRNAs are also important to cancer classification. We considered both high- and low-ranking features to cover all problems (1:1, n:1, 1:n, and m:n) in cancer classification. First, we used the correlation-based feature selection method to select the high-ranking miRNAs, and chose the support vector machine, Bayes network, decision tree, k-nearest-neighbor, and logistic classifier to construct cancer classification. Then, we chose Chi-square test, information gain, gain ratio, and Pearson's correlation feature selection methods to build the m:n feature subset, and used the selected miRNAs to determine cancer classification. The low-ranking miRNA expression profiles achieved higher classification accuracy compared with just using high-ranking miRNAs in traditional feature selection methods. Our results demonstrate that the m:n feature subset made a positive impression of low-ranking miRNAs in cancer classification.

  6. Multiclass classification for skin cancer profiling based on the integration of heterogeneous gene expression series.

    Science.gov (United States)

    Gálvez, Juan Manuel; Castillo, Daniel; Herrera, Luis Javier; San Román, Belén; Valenzuela, Olga; Ortuño, Francisco Manuel; Rojas, Ignacio

    2018-01-01

    Most of the research studies developed applying microarray technology to the characterization of different pathological states of any disease may fail in reaching statistically significant results. This is largely due to the small repertoire of analysed samples, and to the limitation in the number of states or pathologies usually addressed. Moreover, the influence of potential deviations on the gene expression quantification is usually disregarded. In spite of the continuous changes in omic sciences, reflected for instance in the emergence of new Next-Generation Sequencing-related technologies, the existing availability of a vast amount of gene expression microarray datasets should be properly exploited. Therefore, this work proposes a novel methodological approach involving the integration of several heterogeneous skin cancer series, and a later multiclass classifier design. This approach is thus a way to provide the clinicians with an intelligent diagnosis support tool based on the use of a robust set of selected biomarkers, which simultaneously distinguishes among different cancer-related skin states. To achieve this, a multi-platform combination of microarray datasets from Affymetrix and Illumina manufacturers was carried out. This integration is expected to strengthen the statistical robustness of the study as well as the finding of highly-reliable skin cancer biomarkers. Specifically, the designed operation pipeline has allowed the identification of a small subset of 17 differentially expressed genes (DEGs) from which to distinguish among 7 involved skin states. These genes were obtained from the assessment of a number of potential batch effects on the gene expression data. The biological interpretation of these genes was inspected in the specific literature to understand their underlying information in relation to skin cancer. Finally, in order to assess their possible effectiveness in cancer diagnosis, a cross-validation Support Vector Machines (SVM

  7. Validity and reliability of the Greek version of the xerostomia questionnaire in head and neck cancer patients.

    Science.gov (United States)

    Memtsa, Pinelopi Theopisti; Tolia, Maria; Tzitzikas, Ioannis; Bizakis, Ioannis; Pistevou-Gombaki, Kyriaki; Charalambidou, Martha; Iliopoulou, Chrysoula; Kyrgias, George

    2017-03-01

    Xerostomia after radiation therapy for head and neck (H&N) cancer has serious effects on patients' quality of life. The purpose of this study was to validate the Greek version of the self-reported eight-item xerostomia questionnaire (XQ) in patients treated with radiotherapy for H&N cancer. The XQ was translated into Greek and administered to 100 XQ patients. An exploratory factor analysis was performed. Reliability measures were calculated. Several types of validity were evaluated. The observer-rated scoring system was also used. The mean XQ value was 41.92 (SD 22.71). Factor analysis revealed the unidimensional nature of the questionnaire. High reliability measures (ICC, Cronbach's α, Pearson coefficients) were obtained. Patients differed statistically significantly in terms of XQ score, depending on the RTOG/EORTC classification. The Greek version of XQ is valid and reliable. Its score is well related to observer's findings and it can be used to evaluate the impact of radiation therapy on the subjective feeling of xerostomia.

  8. Prognostic classifications of lymph node involvement in lung cancer and current International Association for the Study of Lung Cancer descriptive classification in zones.

    Science.gov (United States)

    Riquet, Marc; Arame, Alex; Foucault, Christophe; Le Pimpec Barthes, Françoise

    2010-09-01

    The lymphatic drainage of solid organ tumors crosses through the lymph nodes (LNs) whose tumoral involvement may still be considered as local disease. Concerning lung cancer, LN involvement may be intrapulmonary (N1), and mediastinal and/or extra-thoracic. More than 30 years ago, mediastinal involved LNs were all considered as N2, and outside the scope of surgery. In 1978, Naruke presented an original article entitled 'Lymph node mapping and curability at various levels of metastasis in resected lung cancer', demonstrating that N2 was not a contraindication to surgery in all patients. The map permitted to localize the favorable N2 on the lung cancer ipsilateral side of the mediastinum. Several maps ensued aiming to discriminate between right and left involvement (1983), and to distinguish N2 (ipsilateral) and N3 (contralateral) mediastinal LN involvement (1983, 1986). The last map (1997 regional LN classification) was recently replaced by a descriptive classification in anatomical zones. This new LN map of the TNM classification for lung cancer is a step toward using anatomical view points which might be the best way to better understand lung cancer lymphatic spread. Nowadays, the LNs are easily identified by current radiological imaging, and their resectability may be anticipated. Each LN chain may be removed by en-bloc lymphadenectomy performed during radical lung resection, a safe procedure which seems to be more oncological based than sampling, and which avoids the source of discrepancies pointed out during the labeling of LN stations by surgeons.

  9. Evolving cancer classification in the era of personalized medicine: A primer for radiologists

    Energy Technology Data Exchange (ETDEWEB)

    O' Neill, Alibhe C.; Jagannathan, Jyothi P.; Ramaiya, Nikhil H. [Dept. of of Imaging, Dana Farber Cancer Institute, Boston (United States)

    2017-01-15

    Traditionally tumors were classified based on anatomic location but now specific genetic mutations in cancers are leading to treatment of tumors with molecular targeted therapies. This has led to a paradigm shift in the classification and treatment of cancer. Tumors treated with molecular targeted therapies often show morphological changes rather than change in size and are associated with class specific and drug specific toxicities, different from those encountered with conventional chemotherapeutic agents. It is important for the radiologists to be familiar with the new cancer classification and the various treatment strategies employed, in order to effectively communicate and participate in the multi-disciplinary care. In this paper we will focus on lung cancer as a prototype of the new molecular classification.

  10. Classification of cancerous cells based on the one-class problem approach

    Science.gov (United States)

    Murshed, Nabeel A.; Bortolozzi, Flavio; Sabourin, Robert

    1996-03-01

    One of the most important factors in reducing the effect of cancerous diseases is the early diagnosis, which requires a good and a robust method. With the advancement of computer technologies and digital image processing, the development of a computer-based system has become feasible. In this paper, we introduce a new approach for the detection of cancerous cells. This approach is based on the one-class problem approach, through which the classification system need only be trained with patterns of cancerous cells. This reduces the burden of the training task by about 50%. Based on this approach, a computer-based classification system is developed, based on the Fuzzy ARTMAP neural networks. Experimental results were performed using a set of 542 patterns taken from a sample of breast cancer. Results of the experiment show 98% correct identification of cancerous cells and 95% correct identification of non-cancerous cells.

  11. [Reliability of nursing outcomes classification label "Knowledge: cardiac disease management (1830)" in outpatients with heart failure].

    Science.gov (United States)

    Cañón-Montañez, Wilson; Oróstegui-Arenas, Myriam

    2015-01-01

    To determine the reliability (internal consistency, inter-rater reproducibility and level of agreement) of nursing outcome: "Knowledge: cardiac disease management (1830)" of the version published in Spanish, in outpatients with heart failure. A reliability study was conducted on 116 outpatients with heart failure. Six indicators of nursing outcome were operationalized. All participants were assessed simultaneously by two evaluators. Three evaluation periods were defined: initial (at baseline), final (a month later), and follow-up (two months later). Internal consistency by Cronbach alpha coefficient, inter-rater reproducibility with intraclass correlation coefficient of reproducibility or agreement and level agreement using the 95% limits of Bland and Altman. Cronbach's alpha was 0.83 (95% CI: 0.77 - 0.89) in the final evaluation, and follow-up values of 0.85 (95% CI: 0.82-0.89) and 0.83 (95% CI: 0.78 - 0.88) were found for the first and second evaluator, respectively. The intraclass correlation coefficient showed values greater 0.9 in the three evaluation periods in both the random and mixed model. The Bland-Altman 95% limits of agreement were close to zero in the three evaluations performed. The questionnaire operationalized to assess the nursing outcome: "Knowledge: cardiac disease management (1830)" in its Spanish version, is a reliable method to measure skills and knowledge in outpatients with heart failure in the Colombian context. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

  12. Lung cancer gene expression database analysis incorporating prior knowledge with support vector machine-based classification method

    Directory of Open Access Journals (Sweden)

    Huang Desheng

    2009-07-01

    Full Text Available Abstract Background A reliable and precise classification is essential for successful diagnosis and treatment of cancer. Gene expression microarrays have provided the high-throughput platform to discover genomic biomarkers for cancer diagnosis and prognosis. Rational use of the available bioinformation can not only effectively remove or suppress noise in gene chips, but also avoid one-sided results of separate experiment. However, only some studies have been aware of the importance of prior information in cancer classification. Methods Together with the application of support vector machine as the discriminant approach, we proposed one modified method that incorporated prior knowledge into cancer classification based on gene expression data to improve accuracy. A public well-known dataset, Malignant pleural mesothelioma and lung adenocarcinoma gene expression database, was used in this study. Prior knowledge is viewed here as a means of directing the classifier using known lung adenocarcinoma related genes. The procedures were performed by software R 2.80. Results The modified method performed better after incorporating prior knowledge. Accuracy of the modified method improved from 98.86% to 100% in training set and from 98.51% to 99.06% in test set. The standard deviations of the modified method decreased from 0.26% to 0 in training set and from 3.04% to 2.10% in test set. Conclusion The method that incorporates prior knowledge into discriminant analysis could effectively improve the capacity and reduce the impact of noise. This idea may have good future not only in practice but also in methodology.

  13. Efficacy of the Kyoto Classification of Gastritis in Identifying Patients at High Risk for Gastric Cancer.

    Science.gov (United States)

    Sugimoto, Mitsushige; Ban, Hiromitsu; Ichikawa, Hitomi; Sahara, Shu; Otsuka, Taketo; Inatomi, Osamu; Bamba, Shigeki; Furuta, Takahisa; Andoh, Akira

    2017-01-01

    Objective The Kyoto gastritis classification categorizes the endoscopic characteristics of Helicobacter pylori (H. pylori) infection-associated gastritis and identifies patterns associated with a high risk of gastric cancer. We investigated its efficacy, comparing scores in patients with H. pylori-associated gastritis and with gastric cancer. Methods A total of 1,200 patients with H. pylori-positive gastritis alone (n=932), early-stage H. pylori-positive gastric cancer (n=189), and successfully treated H. pylori-negative cancer (n=79) were endoscopically graded according to the Kyoto gastritis classification for atrophy, intestinal metaplasia, fold hypertrophy, nodularity, and diffuse redness. Results The prevalence of O-II/O-III-type atrophy according to the Kimura-Takemoto classification in early-stage H. pylori-positive gastric cancer and successfully treated H. pylori-negative cancer groups was 45.1%, which was significantly higher than in subjects with gastritis alone (12.7%, pgastritis scores of atrophy and intestinal metaplasia in the H. pylori-positive cancer group were significantly higher than in subjects with gastritis alone (all pgastritis classification may thus be useful for detecting these patients.

  14. An enhanced topologically significant directed random walk in cancer classification using gene expression datasets

    Directory of Open Access Journals (Sweden)

    Choon Sen Seah

    2017-12-01

    Full Text Available Microarray technology has become one of the elementary tools for researchers to study the genome of organisms. As the complexity and heterogeneity of cancer is being increasingly appreciated through genomic analysis, cancerous classification is an emerging important trend. Significant directed random walk is proposed as one of the cancerous classification approach which have higher sensitivity of risk gene prediction and higher accuracy of cancer classification. In this paper, the methodology and material used for the experiment are presented. Tuning parameter selection method and weight as parameter are applied in proposed approach. Gene expression dataset is used as the input datasets while pathway dataset is used to build a directed graph, as reference datasets, to complete the bias process in random walk approach. In addition, we demonstrate that our approach can improve sensitive predictions with higher accuracy and biological meaningful classification result. Comparison result takes place between significant directed random walk and directed random walk to show the improvement in term of sensitivity of prediction and accuracy of cancer classification.

  15. Intra- and interrater reliability of the Chicago Classification of achalasia subtypes in pediatric high-resolution esophageal manometry (HRM) recordings.

    Science.gov (United States)

    Singendonk, M M J; Rosen, R; Oors, J; Rommel, N; van Wijk, M P; Benninga, M A; Nurko, S; Omari, T I

    2017-11-01

    Subtyping achalasia by high-resolution manometry (HRM) is clinically relevant as response to therapy and prognosis have shown to vary accordingly. The aim of this study was to assess inter- and intrarater reliability of diagnosing achalasia and achalasia subtyping in children using the Chicago Classification (CC) V3.0. Six observers analyzed 40 pediatric HRM recordings (22 achalasia and 18 non-achalasia) twice by using dedicated analysis software (ManoView 3.0, Given Imaging, Los Angeles, CA, USA). Integrated relaxation pressure (IRP4s), distal contractile integral (DCI), intrabolus pressurization pattern (IBP), and distal latency (DL) were extracted and analyzed hierarchically. Cohen's κ (2 raters) and Fleiss' κ (>2 raters) and the intraclass correlation coefficient (ICC) were used for categorical and ordinal data, respectively. Based on the results of dedicated analysis software only, intra- and interrater reliability was excellent and moderate (κ=0.89 and κ=0.52, respectively) for differentiating achalasia from non-achalasia. For subtyping achalasia, reliability decreased to substantial and fair (κ=0.72 and κ=0.28, respectively). When observers were allowed to change the software-driven diagnosis according to their own interpretation of the manometric patterns, intra- and interrater reliability increased for diagnosing achalasia (κ=0.98 and κ=0.92, respectively) and for subtyping achalasia (κ=0.79 and κ=0.58, respectively). Intra- and interrater agreement for diagnosing achalasia when using HRM and the CC was very good to excellent when results of automated analysis software were interpreted by experienced observers. More variability was seen when relying solely on the software-driven diagnosis and for subtyping achalasia. Therefore, diagnosing and subtyping achalasia should be performed in pediatric motility centers with significant expertise. © 2017 John Wiley & Sons Ltd.

  16. NMD Classifier: A reliable and systematic classification tool for nonsense-mediated decay events.

    Directory of Open Access Journals (Sweden)

    Min-Kung Hsu

    Full Text Available Nonsense-mediated decay (NMD degrades mRNAs that include premature termination codons to avoid the translation and accumulation of truncated proteins. This mechanism has been found to participate in gene regulation and a wide spectrum of biological processes. However, the evolutionary and regulatory origins of NMD-targeted transcripts (NMDTs have been less studied, partly because of the complexity in analyzing NMD events. Here we report NMD Classifier, a tool for systematic classification of NMD events for either annotated or de novo assembled transcripts. This tool is based on the assumption of minimal evolution/regulation-an event that leads to the least change is the most likely to occur. Our simulation results indicate that NMD Classifier can correctly identify an average of 99.3% of the NMD-causing transcript structural changes, particularly exon inclusions/exclusions and exon boundary alterations. Researchers can apply NMD Classifier to evolutionary and regulatory studies by comparing NMD events of different biological conditions or in different organisms.

  17. A New Feature Ensemble with a Multistage Classification Scheme for Breast Cancer Diagnosis

    Directory of Open Access Journals (Sweden)

    Idil Isikli Esener

    2017-01-01

    Full Text Available A new and effective feature ensemble with a multistage classification is proposed to be implemented in a computer-aided diagnosis (CAD system for breast cancer diagnosis. A publicly available mammogram image dataset collected during the Image Retrieval in Medical Applications (IRMA project is utilized to verify the suggested feature ensemble and multistage classification. In achieving the CAD system, feature extraction is performed on the mammogram region of interest (ROI images which are preprocessed by applying a histogram equalization followed by a nonlocal means filtering. The proposed feature ensemble is formed by concatenating the local configuration pattern-based, statistical, and frequency domain features. The classification process of these features is implemented in three cases: a one-stage study, a two-stage study, and a three-stage study. Eight well-known classifiers are used in all cases of this multistage classification scheme. Additionally, the results of the classifiers that provide the top three performances are combined via a majority voting technique to improve the recognition accuracy on both two- and three-stage studies. A maximum of 85.47%, 88.79%, and 93.52% classification accuracies are attained by the one-, two-, and three-stage studies, respectively. The proposed multistage classification scheme is more effective than the single-stage classification for breast cancer diagnosis.

  18. Median Filter Noise Reduction of Image and Backpropagation Neural Network Model for Cervical Cancer Classification

    Science.gov (United States)

    Wutsqa, D. U.; Marwah, M.

    2017-06-01

    In this paper, we consider spatial operation median filter to reduce the noise in the cervical images yielded by colposcopy tool. The backpropagation neural network (BPNN) model is applied to the colposcopy images to classify cervical cancer. The classification process requires an image extraction by using a gray level co-occurrence matrix (GLCM) method to obtain image features that are used as inputs of BPNN model. The advantage of noise reduction is evaluated by comparing the performances of BPNN models with and without spatial operation median filter. The experimental result shows that the spatial operation median filter can improve the accuracy of the BPNN model for cervical cancer classification.

  19. Comparative Study of Classification Techniques on Breast Cancer FNA Biopsy Data

    Directory of Open Access Journals (Sweden)

    George Rumbe

    2010-12-01

    Full Text Available Accurate diagnostic detection of the cancerous cells in a patient is critical and may alter the subsequent treatment and increase the chances of survival rate. Machine learning techniques have been instrumental in disease detection and are currently being used in various classification problems due to their accurate prediction performance. Various techniques may provide different desired accuracies and it is therefore imperative to use the most suitable method which provides the best desired results. This research seeks to provide comparative analysis of Support Vector Machine, Bayesian classifier and other Artificial neural network classifiers (Backpropagation, linear programming, Learning vector quantization, and K nearest neighborhood on the Wisconsin breast cancer classification problem.

  20. Pathogenesis of Gastric Cancer: Genetics and Molecular Classification.

    Science.gov (United States)

    Figueiredo, Ceu; Camargo, M C; Leite, Marina; Fuentes-Pananá, Ezequiel M; Rabkin, Charles S; Machado, José C

    Gastric cancer is the fifth most incident and the third most common cause of cancer-related death in the world. Infection with Helicobacter pylori is the major risk factor for this disease. Gastric cancer is the final outcome of a cascade of events that takes decades to occur and results from the accumulation of multiple genetic and epigenetic alterations. These changes are crucial for tumor cells to expedite and sustain the array of pathways involved in the cancer development, such as cell cycle, DNA repair, metabolism, cell-to-cell and cell-to-matrix interactions, apoptosis, angiogenesis, and immune surveillance. Comprehensive molecular analyses of gastric cancer have disclosed the complex heterogeneity of this disease. In particular, these analyses have confirmed that Epstein-Barr virus (EBV)-positive gastric cancer is a distinct entity. The identification of gastric cancer subtypes characterized by recognizable molecular profiles may pave the way for a more personalized clinical management and to the identification of novel therapeutic targets and biomarkers for screening, prognosis, prediction of response to treatment, and monitoring of gastric cancer progression.

  1. DJ-1 is a reliable serum biomarker for discriminating high-risk endometrial cancer.

    Science.gov (United States)

    Di Cello, Annalisa; Di Sanzo, Maddalena; Perrone, Francesca Marta; Santamaria, Gianluca; Rania, Erika; Angotti, Elvira; Venturella, Roberta; Mancuso, Serafina; Zullo, Fulvio; Cuda, Giovanni; Costanzo, Francesco

    2017-06-01

    New reliable approaches to stratify patients with endometrial cancer into risk categories are highly needed. We have recently demonstrated that DJ-1 is overexpressed in endometrial cancer, showing significantly higher levels both in serum and tissue of patients with high-risk endometrial cancer compared with low-risk endometrial cancer. In this experimental study, we further extended our observation, evaluating the role of DJ-1 as an accurate serum biomarker for high-risk endometrial cancer. A total of 101 endometrial cancer patients and 44 healthy subjects were prospectively recruited. DJ-1 serum levels were evaluated comparing cases and controls and, among endometrial cancer patients, between high- and low-risk patients. The results demonstrate that DJ-1 levels are significantly higher in cases versus controls and in high- versus low-risk patients. The receiver operating characteristic curve analysis shows that DJ-1 has a very good diagnostic accuracy in discriminating endometrial cancer patients versus controls and an excellent accuracy in distinguishing, among endometrial cancer patients, low- from high-risk cases. DJ-1 sensitivity and specificity are the highest when high- and low-risk patients are compared, reaching the value of 95% and 99%, respectively. Moreover, DJ-1 serum levels seem to be correlated with worsening of the endometrial cancer grade and histotype, making it a reliable tool in the preoperative decision-making process.

  2. Zone-specific logistic regression models improve classification of prostate cancer on multi-parametric MRI

    Energy Technology Data Exchange (ETDEWEB)

    Dikaios, Nikolaos; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit [University College London, Centre for Medical Imaging, London (United Kingdom); University College London Hospital, Departments of Radiology, London (United Kingdom); Alkalbani, Jokha; Sidhu, Harbir Singh [University College London, Centre for Medical Imaging, London (United Kingdom); Abd-Alazeez, Mohamed; Ahmed, Hashim U.; Emberton, Mark [University College London, Research Department of Urology, Division of Surgery and Interventional Science, London (United Kingdom); Kirkham, Alex [University College London Hospital, Departments of Radiology, London (United Kingdom); Freeman, Alex [University College London Hospital, Department of Histopathology, London (United Kingdom)

    2015-09-15

    To assess the interchangeability of zone-specific (peripheral-zone (PZ) and transition-zone (TZ)) multiparametric-MRI (mp-MRI) logistic-regression (LR) models for classification of prostate cancer. Two hundred and thirty-one patients (70 TZ training-cohort; 76 PZ training-cohort; 85 TZ temporal validation-cohort) underwent mp-MRI and transperineal-template-prostate-mapping biopsy. PZ and TZ uni/multi-variate mp-MRI LR-models for classification of significant cancer (any cancer-core-length (CCL) with Gleason > 3 + 3 or any grade with CCL ≥ 4 mm) were derived from the respective cohorts and validated within the same zone by leave-one-out analysis. Inter-zonal performance was tested by applying TZ models to the PZ training-cohort and vice-versa. Classification performance of TZ models for TZ cancer was further assessed in the TZ validation-cohort. ROC area-under-curve (ROC-AUC) analysis was used to compare models. The univariate parameters with the best classification performance were the normalised T2 signal (T2nSI) within the TZ (ROC-AUC = 0.77) and normalized early contrast-enhanced T1 signal (DCE-nSI) within the PZ (ROC-AUC = 0.79). Performance was not significantly improved by bi-variate/tri-variate modelling. PZ models that contained DCE-nSI performed poorly in classification of TZ cancer. The TZ model based solely on maximum-enhancement poorly classified PZ cancer. LR-models dependent on DCE-MRI parameters alone are not interchangeable between prostatic zones; however, models based exclusively on T2 and/or ADC are more robust for inter-zonal application. (orig.)

  3. Stepwise classification of cancer samples using clinical and molecular data

    Directory of Open Access Journals (Sweden)

    Obulkasim Askar

    2011-10-01

    Full Text Available Abstract Background Combining clinical and molecular data types may potentially improve prediction accuracy of a classifier. However, currently there is a shortage of effective and efficient statistical and bioinformatic tools for true integrative data analysis. Existing integrative classifiers have two main disadvantages: First, coarse combination may lead to subtle contributions of one data type to be overshadowed by more obvious contributions of the other. Second, the need to measure both data types for all patients may be both unpractical and (cost inefficient. Results We introduce a novel classification method, a stepwise classifier, which takes advantage of the distinct classification power of clinical data and high-dimensional molecular data. We apply classification algorithms to two data types independently, starting with the traditional clinical risk factors. We only turn to relatively expensive molecular data when the uncertainty of prediction result from clinical data exceeds a predefined limit. Experimental results show that our approach is adaptive: the proportion of samples that needs to be re-classified using molecular data depends on how much we expect the predictive accuracy to increase when re-classifying those samples. Conclusions Our method renders a more cost-efficient classifier that is at least as good, and sometimes better, than one based on clinical or molecular data alone. Hence our approach is not just a classifier that minimizes a particular loss function. Instead, it aims to be cost-efficient by avoiding molecular tests for a potentially large subgroup of individuals; moreover, for these individuals a test result would be quickly available, which may lead to reduced waiting times (for diagnosis and hence lower the patients distress. Stepwise classification is implemented in R-package stepwiseCM and available at the Bioconductor website.

  4. Classification of normal and abnormal images of lung cancer

    Science.gov (United States)

    Bhatnagar, Divyesh; Tiwari, Amit Kumar; Vijayarajan, V.; Krishnamoorthy, A.

    2017-11-01

    To find the exact symptoms of lung cancer is difficult, because of the formation of the most cancers tissues, wherein large structure of tissues is intersect in a different way. This problem can be evaluated with the help of digital images. In this strategy images will be examined with basic operation of PCA Algorithm. In this paper, GLCM method is used for pre-processing of the snap shots and function extraction system and to test the level of diseases of a patient in its premature stage get to know it is regular or unusual. With the help of result stage of cancer will be evaluated. With the help of dataset and result survival rate of cancer patient can be estimated. Result is based totally on the precise and wrong arrangement of the patterns of tissues.

  5. Immunogenomic Classification of Colorectal Cancer and Therapeutic Implications

    NARCIS (Netherlands)

    Roelands, Jessica; Kuppen, Peter J. K.; Vermeulen, Louis; Maccalli, Cristina; Decock, Julie; Wang, Ena; Marincola, Francesco M.; Bedognetti, Davide; Hendrickx, Wouter

    2017-01-01

    The immune system has a substantial effect on colorectal cancer (CRC) progression. Additionally, the response to immunotherapeutics and conventional treatment options (e.g., chemotherapy, radiotherapy and targeted therapies) is influenced by the immune system. The molecular characterization of

  6. Reliability of Smartphone-Based Instant Messaging Application for Diagnosis, Classification, and Decision-making in Pediatric Orthopedic Trauma.

    Science.gov (United States)

    Stahl, Ido; Katsman, Alexander; Zaidman, Michael; Keshet, Doron; Sigal, Amit; Eidelman, Mark

    2017-07-11

    Smartphones have the ability to capture and send images, and their use has become common in the emergency setting for transmitting radiographic images with the intent to consult an off-site specialist. Our objective was to evaluate the reliability of smartphone-based instant messaging applications for the evaluation of various pediatric limb traumas, as compared with the standard method of viewing images of a workstation-based picture archiving and communication system (PACS). X-ray images of 73 representative cases of pediatric limb trauma were captured and transmitted to 5 pediatric orthopedic surgeons by the Whatsapp instant messaging application on an iPhone 6 smartphone. Evaluators were asked to diagnose, classify, and determine the course of treatment for each case over their personal smartphones. Following a 4-week interval, revaluation was conducted using the PACS. Intraobserver agreement was calculated for overall agreement and per fracture site. The overall results indicate "near perfect agreement" between interpretations of the radiographs on smartphones compared with computer-based PACS, with κ of 0.84, 0.82, and 0.89 for diagnosis, classification, and treatment planning, respectively. Looking at the results per fracture site, we also found substantial to near perfect agreement. Smartphone-based instant messaging applications are reliable for evaluation of a wide range of pediatric limb fractures. This method of obtaining an expert opinion from the off-site specialist is immediately accessible and inexpensive, making smartphones a powerful tool for doctors in the emergency department, primary care clinics, or remote medical centers, enabling timely and appropriate treatment for the injured child. This method is not a substitution for evaluation of the images in the standard method over computer-based PACS, which should be performed before final decision-making.

  7. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

    Directory of Open Access Journals (Sweden)

    Eils Roland

    2005-11-01

    Full Text Available Abstract Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85% were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and

  8. Five systems of psychiatric classification for preschool children: do differences in validity, usefulness and reliability make for competitive or complimentary constellations?

    Science.gov (United States)

    Postert, Christian; Averbeck-Holocher, Marlies; Beyer, Thomas; Müller, Jörg; Furniss, Tilman

    2009-03-01

    DSM-IV and ICD-10 have limitations in the diagnostic classification of psychiatric disorders at preschool age (0-5 years). The publication of the Diagnostic Classification 0-3 (DC:0-3) in 1994, its basically revised second edition (DC:0-3R) in 2005 and the Research Diagnostic Criteria-Preschool Age (RDC-PA) in 2004 have provided several modifications of these manuals. Taking into account the growing empirical evidence highlighting the need for a diagnostic classification system for psychiatric disorders in preschool children, the main categorical classification systems in preschool psychiatry will be presented and discussed. The paper will focus on issues of validity, usefulness and reliability in DSM-IV, ICD-10, RDC-PA, DC:0-3, and DC:0-3R. The reasons for including or excluding postulated psychiatric disorder categories for preschool children with variable degrees of empirical evidence into the different diagnostic systems will be discussed.

  9. Recursive Partitioning Analysis for New Classification of Patients With Esophageal Cancer Treated by Chemoradiotherapy

    International Nuclear Information System (INIS)

    Nomura, Motoo; Shitara, Kohei; Kodaira, Takeshi; Kondoh, Chihiro; Takahari, Daisuke; Ura, Takashi; Kojima, Hiroyuki; Kamata, Minoru; Muro, Kei; Sawada, Satoshi

    2012-01-01

    Background: The 7th edition of the American Joint Committee on Cancer staging system does not include lymph node size in the guidelines for staging patients with esophageal cancer. The objectives of this study were to determine the prognostic impact of the maximum metastatic lymph node diameter (ND) on survival and to develop and validate a new staging system for patients with esophageal squamous cell cancer who were treated with definitive chemoradiotherapy (CRT). Methods: Information on 402 patients with esophageal cancer undergoing CRT at two institutions was reviewed. Univariate and multivariate analyses of data from one institution were used to assess the impact of clinical factors on survival, and recursive partitioning analysis was performed to develop the new staging classification. To assess its clinical utility, the new classification was validated using data from the second institution. Results: By multivariate analysis, gender, T, N, and ND stages were independently and significantly associated with survival (p < 0.05). The resulting new staging classification was based on the T and ND. The four new stages led to good separation of survival curves in both the developmental and validation datasets (p < 0.05). Conclusions: Our results showed that lymph node size is a strong independent prognostic factor and that the new staging system, which incorporated lymph node size, provided good prognostic power, and discriminated effectively for patients with esophageal cancer undergoing CRT.

  10. Reliability and validity study of a tool to measure cancer stigma: Patient version

    Directory of Open Access Journals (Sweden)

    Medine Yilmaz

    2017-01-01

    Full Text Available Objective: The aim of this methodological study is to establish the validity and reliability of the Turkish version of “A Questionnaire for Measuring Attitudes toward Cancer (Cancer Stigma - Patient version.” Methods: The sample comprised oncology patients who had active cancer treatment. The construct validity was assessed using the confirmatory and exploratory factor analysis. Results: The mean age of the participants was 54.9±12.3 years. In the confirmatory factor analysis, fit values were determined as comparative fit index = 0.93, goodness of fit index = 0.91, normed-fit index=0.91, and root mean square error of approximation RMSEA = 0.09 (P<0.05 (Kaiser–Meyer–Olkin = 0.88, χ2 = 1084.41, Df = 66, and Barletta's test P<0.000. The first factor was “impossibility of recovery and experience of social discrimination” and the second factor was “stereotypes of cancer patients.” The two-factor structure accounted for 56.74% of the variance. The Cronbach's alpha value was determined as 0.88 for the two-factor scale. Conclusions: “A questionnaire for measuring attitudes toward cancer (cancer stigma - Patient version” is a reliable and valid questionnaire to assess stigmatization of cancer in cancer patients.

  11. Reliability and Validity Study of a Tool to Measure Cancer Stigma: Patient Version.

    Science.gov (United States)

    Yılmaz, Medine; Dişsiz, Gülçin; Demir, Filiz; Irız, Sibel; Alacacioglu, Ahmet

    2017-01-01

    The aim of this methodological study is to establish the validity and reliability of the Turkish version of "A Questionnaire for Measuring Attitudes toward Cancer (Cancer Stigma) - Patient version." The sample comprised oncology patients who had active cancer treatment. The construct validity was assessed using the confirmatory and exploratory factor analysis. The mean age of the participants was 54.9±12.3 years. In the confirmatory factor analysis, fit values were determined as comparative fit index = 0.93, goodness of fit index = 0.91, normed-fit index=0.91, and root mean square error of approximation RMSEA = 0.09 ( P Kaiser-Meyer-Olkin = 0.88, χ 2 = 1084.41, Df = 66, and Barletta's test P <0.000). The first factor was "impossibility of recovery and experience of social discrimination" and the second factor was "stereotypes of cancer patients." The two-factor structure accounted for 56.74% of the variance. The Cronbach's alpha value was determined as 0.88 for the two-factor scale. "A questionnaire for measuring attitudes toward cancer (cancer stigma) - Patient version" is a reliable and valid questionnaire to assess stigmatization of cancer in cancer patients.

  12. Evaluation Methodology between Globalization and Localization Features Approaches for Skin Cancer Lesions Classification

    Science.gov (United States)

    Ahmed, H. M.; Al-azawi, R. J.; Abdulhameed, A. A.

    2018-05-01

    Huge efforts have been put in the developing of diagnostic methods to skin cancer disease. In this paper, two different approaches have been addressed for detection the skin cancer in dermoscopy images. The first approach uses a global method that uses global features for classifying skin lesions, whereas the second approach uses a local method that uses local features for classifying skin lesions. The aim of this paper is selecting the best approach for skin lesion classification. The dataset has been used in this paper consist of 200 dermoscopy images from Pedro Hispano Hospital (PH2). The achieved results are; sensitivity about 96%, specificity about 100%, precision about 100%, and accuracy about 97% for globalization approach while, sensitivity about 100%, specificity about 100%, precision about 100%, and accuracy about 100% for Localization Approach, these results showed that the localization approach achieved acceptable accuracy and better than globalization approach for skin cancer lesions classification.

  13. Reliability and Validity of the Korean Version of the Cancer Stigma Scale.

    Science.gov (United States)

    So, Hyang Sook; Chae, Myeong Jeong; Kim, Hye Young

    2017-02-01

    In this study the reliability and validity of the Korean version of the Cancer Stigma Scale (KCSS) was evaluated. The KCSS was formed through translation and modification of Cataldo Lung Cancer Stigma Scale. The KCSS, Psychological Symptom Inventory (PSI), and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire - Core 30 (EORTC QLQ-C30) were administered to 247 men and women diagnosed with one of the five major cancers. Construct validity, item convergent and discriminant validity, concurrent validity, known-group validity, and internal consistency reliability of the KCSS were evaluated. Exploratory factor analysis supported the construct validity with a six-factor solution; that explained 65.7% of the total variance. The six-factor model was validated by confirmatory factor analysis (Q (χ²/df)= 2.28, GFI=.84, AGFI=.81, NFI=.80, TLI=.86, RMR=.03, and RMSEA=.07). Concurrent validity was demonstrated with the QLQ-C30 (global: r=-.44; functional: r=-.19; symptom: r=.42). The KCSS had known-group validity. Cronbach's alpha coefficient for the 24 items was .89. The results of this study suggest that the 24-item KCSS has relatively acceptable reliability and validity and can be used in clinical research to assess cancer stigma and its impacts on health-related quality of life in Korean cancer patients. © 2017 Korean Society of Nursing Science

  14. Breast cancer tumor classification using LASSO method selection approach

    International Nuclear Information System (INIS)

    Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M.

    2016-10-01

    Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

  15. Breast cancer tumor classification using LASSO method selection approach

    Energy Technology Data Exchange (ETDEWEB)

    Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M., E-mail: morvymm@yahoo.com.mx [Universidad Autonoma de Zacatecas, Av. Ramon Lopez Velarde 801, Col. Centro, 98000 Zacatecas, Zac. (Mexico)

    2016-10-15

    Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

  16. Examining applying high performance genetic data feature selection and classification algorithms for colon cancer diagnosis.

    Science.gov (United States)

    Al-Rajab, Murad; Lu, Joan; Xu, Qiang

    2017-07-01

    This paper examines the accuracy and efficiency (time complexity) of high performance genetic data feature selection and classification algorithms for colon cancer diagnosis. The need for this research derives from the urgent and increasing need for accurate and efficient algorithms. Colon cancer is a leading cause of death worldwide, hence it is vitally important for the cancer tissues to be expertly identified and classified in a rapid and timely manner, to assure both a fast detection of the disease and to expedite the drug discovery process. In this research, a three-phase approach was proposed and implemented: Phases One and Two examined the feature selection algorithms and classification algorithms employed separately, and Phase Three examined the performance of the combination of these. It was found from Phase One that the Particle Swarm Optimization (PSO) algorithm performed best with the colon dataset as a feature selection (29 genes selected) and from Phase Two that the Support Vector Machine (SVM) algorithm outperformed other classifications, with an accuracy of almost 86%. It was also found from Phase Three that the combined use of PSO and SVM surpassed other algorithms in accuracy and performance, and was faster in terms of time analysis (94%). It is concluded that applying feature selection algorithms prior to classification algorithms results in better accuracy than when the latter are applied alone. This conclusion is important and significant to industry and society. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Alternative Polyadenylation Patterns for Novel Gene Discovery and Classification in Cancer

    Directory of Open Access Journals (Sweden)

    Oguzhan Begik

    2017-07-01

    Full Text Available Certain aspects of diagnosis, prognosis, and treatment of cancer patients are still important challenges to be addressed. Therefore, we propose a pipeline to uncover patterns of alternative polyadenylation (APA, a hidden complexity in cancer transcriptomes, to further accelerate efforts to discover novel cancer genes and pathways. Here, we analyzed expression data for 1045 cancer patients and found a significant shift in usage of poly(A signals in common tumor types (breast, colon, lung, prostate, gastric, and ovarian compared to normal tissues. Using machine-learning techniques, we further defined specific subsets of APA events to efficiently classify cancer types. Furthermore, APA patterns were associated with altered protein levels in patients, revealed by antibody-based profiling data, suggesting functional significance. Overall, our study offers a computational approach for use of APA in novel gene discovery and classification in common tumor types, with important implications in basic research, biomarker discovery, and precision medicine approaches.

  18. Immunogenomic Classification of Colorectal Cancer and Therapeutic Implications

    Directory of Open Access Journals (Sweden)

    Jessica Roelands

    2017-10-01

    Full Text Available The immune system has a substantial effect on colorectal cancer (CRC progression. Additionally, the response to immunotherapeutics and conventional treatment options (e.g., chemotherapy, radiotherapy and targeted therapies is influenced by the immune system. The molecular characterization of colorectal cancer (CRC has led to the identification of favorable and unfavorable immunological attributes linked to clinical outcome. With the definition of consensus molecular subtypes (CMSs based on transcriptomic profiles, multiple characteristics have been proposed to be responsible for the development of the tumor immune microenvironment and corresponding mechanisms of immune escape. In this review, a detailed description of proposed immune phenotypes as well as their interaction with different therapeutic modalities will be provided. Finally, possible strategies to shift the CRC immune phenotype towards a reactive, anti-tumor orientation are proposed per CMS.

  19. Impact of full field digital mammography on the classification and mammographic characteristics of interval breast cancers

    Energy Technology Data Exchange (ETDEWEB)

    Knox, Mark, E-mail: marktknox@gmail.com; O’Brien, Angela, E-mail: angelaobrien@doctors.org.uk; Szabó, Endre, E-mail: endrebacsi@freemail.hu; Smith, Clare S., E-mail: csmith@mater.ie; Fenlon, Helen M., E-mail: helen.fenlon@cancerscreening.ie; McNicholas, Michelle M., E-mail: michelle.mcnicholas@cancerscreening.ie; Flanagan, Fidelma L., E-mail: fidelma.flanagan@cancerscreening.ie

    2015-06-15

    Highlights: • Digital mammography has changed the presentation of interval breast cancer. • Less interval breast cancers are associated with microcalcifications following FFDM. • Interval breast cancer audit remains a key feature of any breast screening program. - Abstract: Objective: Full field digital mammography (FFDM) is increasingly replacing screen film mammography (SFM) in breast screening programs. Interval breast cancers are an issue in all screening programs and the purpose of our study is to assess the impact of FFDM on the classification of interval breast cancers at independent blind review and to compare the mammographic features of interval cancers at FFDM and SFM. Materials and methods: This study included 138 cases of interval breast cancer, 76 following an FFDM screening examination and 62 following screening with SFM. The prior screening mammogram was assessed by each of five consultant breast radiologists who were blinded to the site of subsequent cancer. Subsequent review of the diagnostic mammogram was performed and cases were classified as missed, minimal signs, occult or true interval. Mammographic features of the interval cancer at diagnosis and any abnormality identified on the prior screening mammogram were recorded. Results: The percentages of cancers classified as missed at FFDM and SFM did not differ significantly, 10.5% (8 of 76) at FFDM and 8.1% (5 of 62) at SFM (p = .77). There were significantly less interval cancers presenting as microcalcifications (alone or in association with another abnormality) following screening with FFDM, 16% (12 of 76) than following a SFM examination, 32% (20 of 62) (p = .02). Conclusion: Interval breast cancers continue to pose a problem at FFDM. The switch to FFDM has changed the mammographic presentation of interval breast cancer, with less interval cancers presenting in association with microcalcifications.

  20. Impact of full field digital mammography on the classification and mammographic characteristics of interval breast cancers

    International Nuclear Information System (INIS)

    Knox, Mark; O’Brien, Angela; Szabó, Endre; Smith, Clare S.; Fenlon, Helen M.; McNicholas, Michelle M.; Flanagan, Fidelma L.

    2015-01-01

    Highlights: • Digital mammography has changed the presentation of interval breast cancer. • Less interval breast cancers are associated with microcalcifications following FFDM. • Interval breast cancer audit remains a key feature of any breast screening program. - Abstract: Objective: Full field digital mammography (FFDM) is increasingly replacing screen film mammography (SFM) in breast screening programs. Interval breast cancers are an issue in all screening programs and the purpose of our study is to assess the impact of FFDM on the classification of interval breast cancers at independent blind review and to compare the mammographic features of interval cancers at FFDM and SFM. Materials and methods: This study included 138 cases of interval breast cancer, 76 following an FFDM screening examination and 62 following screening with SFM. The prior screening mammogram was assessed by each of five consultant breast radiologists who were blinded to the site of subsequent cancer. Subsequent review of the diagnostic mammogram was performed and cases were classified as missed, minimal signs, occult or true interval. Mammographic features of the interval cancer at diagnosis and any abnormality identified on the prior screening mammogram were recorded. Results: The percentages of cancers classified as missed at FFDM and SFM did not differ significantly, 10.5% (8 of 76) at FFDM and 8.1% (5 of 62) at SFM (p = .77). There were significantly less interval cancers presenting as microcalcifications (alone or in association with another abnormality) following screening with FFDM, 16% (12 of 76) than following a SFM examination, 32% (20 of 62) (p = .02). Conclusion: Interval breast cancers continue to pose a problem at FFDM. The switch to FFDM has changed the mammographic presentation of interval breast cancer, with less interval cancers presenting in association with microcalcifications

  1. Classification of human cancers based on DNA copy number amplification modeling

    Directory of Open Access Journals (Sweden)

    Knuutila Sakari

    2008-05-01

    Full Text Available Abstract Background DNA amplifications alter gene dosage in cancer genomes by multiplying the gene copy number. Amplifications are quintessential in a considerable number of advanced cancers of various anatomical locations. The aims of this study were to classify human cancers based on their amplification patterns, explore the biological and clinical fundamentals behind their amplification-pattern based classification, and understand the characteristics in human genomic architecture that associate with amplification mechanisms. Methods We applied a machine learning approach to model DNA copy number amplifications using a data set of binary amplification records at chromosome sub-band resolution from 4400 cases that represent 82 cancer types. Amplification data was fused with background data: clinical, histological and biological classifications, and cytogenetic annotations. Statistical hypothesis testing was used to mine associations between the data sets. Results Probabilistic clustering of each chromosome identified 111 amplification models and divided the cancer cases into clusters. The distribution of classification terms in the amplification-model based clustering of cancer cases revealed cancer classes that were associated with specific DNA copy number amplification models. Amplification patterns – finite or bounded descriptions of the ranges of the amplifications in the chromosome – were extracted from the clustered data and expressed according to the original cytogenetic nomenclature. This was achieved by maximal frequent itemset mining using the cluster-specific data sets. The boundaries of amplification patterns were shown to be enriched with fragile sites, telomeres, centromeres, and light chromosome bands. Conclusions Our results demonstrate that amplifications are non-random chromosomal changes and specifically selected in tumor tissue microenvironment. Furthermore, statistical evidence showed that specific chromosomal features

  2. From Molecular Classification to Targeted Therapeutics: The Changing Face of Systemic Therapy in Metastatic Gastroesophageal Cancer

    Directory of Open Access Journals (Sweden)

    Adrian Murphy

    2015-01-01

    Full Text Available Histological classification of adenocarcinoma or squamous cell carcinoma for esophageal cancer or using the Lauren classification for intestinal and diffuse type gastric cancer has limited clinical utility in the management of advanced disease. Germline mutations in E-cadherin (CDH1 or mismatch repair genes (Lynch syndrome were identified many years ago but given their rarity, the identification of these molecular alterations does not substantially impact treatment in the advanced setting. Recent molecular profiling studies of upper GI tumors have added to our knowledge of the underlying biology but have not led to an alternative classification system which can guide clinician’s therapeutic decisions. Recently the Cancer Genome Atlas Research Network has proposed four subtypes of gastric cancer dividing tumors into those positive for Epstein-Barr virus, microsatellite unstable tumors, genomically stable tumors, and tumors with chromosomal instability. Unfortunately to date, many phase III clinical trials involving molecularly targeted agents have failed to meet their survival endpoints due to their use in unselected populations. Future clinical trials should utilize molecular profiling of individual tumors in order to determine the optimal use of targeted therapies in preselected patients.

  3. A protein and mRNA expression-based classification of gastric cancer.

    Science.gov (United States)

    Setia, Namrata; Agoston, Agoston T; Han, Hye S; Mullen, John T; Duda, Dan G; Clark, Jeffrey W; Deshpande, Vikram; Mino-Kenudson, Mari; Srivastava, Amitabh; Lennerz, Jochen K; Hong, Theodore S; Kwak, Eunice L; Lauwers, Gregory Y

    2016-07-01

    The overall survival of gastric carcinoma patients remains poor despite improved control over known risk factors and surveillance. This highlights the need for new classifications, driven towards identification of potential therapeutic targets. Using sophisticated molecular technologies and analysis, three groups recently provided genetic and epigenetic molecular classifications of gastric cancer (The Cancer Genome Atlas, 'Singapore-Duke' study, and Asian Cancer Research Group). Suggested by these classifications, here, we examined the expression of 14 biomarkers in a cohort of 146 gastric adenocarcinomas and performed unsupervised hierarchical clustering analysis using less expensive and widely available immunohistochemistry and in situ hybridization. Ultimately, we identified five groups of gastric cancers based on Epstein-Barr virus (EBV) positivity, microsatellite instability, aberrant E-cadherin, and p53 expression; the remaining cases constituted a group characterized by normal p53 expression. In addition, the five categories correspond to the reported molecular subgroups by virtue of clinicopathologic features. Furthermore, evaluation between these clusters and survival using the Cox proportional hazards model showed a trend for superior survival in the EBV and microsatellite-instable related adenocarcinomas. In conclusion, we offer as a proposal a simplified algorithm that is able to reproduce the recently proposed molecular subgroups of gastric adenocarcinoma, using immunohistochemical and in situ hybridization techniques.

  4. An NRG Oncology/GOG study of molecular classification for risk prediction in endometrioid endometrial cancer.

    Science.gov (United States)

    Cosgrove, Casey M; Tritchler, David L; Cohn, David E; Mutch, David G; Rush, Craig M; Lankes, Heather A; Creasman, William T; Miller, David S; Ramirez, Nilsa C; Geller, Melissa A; Powell, Matthew A; Backes, Floor J; Landrum, Lisa M; Timmers, Cynthia; Suarez, Adrian A; Zaino, Richard J; Pearl, Michael L; DiSilvestro, Paul A; Lele, Shashikant B; Goodfellow, Paul J

    2018-01-01

    The purpose of this study was to assess the prognostic significance of a simplified, clinically accessible classification system for endometrioid endometrial cancers combining Lynch syndrome screening and molecular risk stratification. Tumors from NRG/GOG GOG210 were evaluated for mismatch repair defects (MSI, MMR IHC, and MLH1 methylation), POLE mutations, and loss of heterozygosity. TP53 was evaluated in a subset of cases. Tumors were assigned to four molecular classes. Relationships between molecular classes and clinicopathologic variables were assessed using contingency tests and Cox proportional methods. Molecular classification was successful for 982 tumors. Based on the NCI consensus MSI panel assessing MSI and loss of heterozygosity combined with POLE testing, 49% of tumors were classified copy number stable (CNS), 39% MMR deficient, 8% copy number altered (CNA) and 4% POLE mutant. Cancer-specific mortality occurred in 5% of patients with CNS tumors; 2.6% with POLE tumors; 7.6% with MMR deficient tumors and 19% with CNA tumors. The CNA group had worse progression-free (HR 2.31, 95%CI 1.53-3.49) and cancer-specific survival (HR 3.95; 95%CI 2.10-7.44). The POLE group had improved outcomes, but the differences were not statistically significant. CNA class remained significant for cancer-specific survival (HR 2.11; 95%CI 1.04-4.26) in multivariable analysis. The CNA molecular class was associated with TP53 mutation and expression status. A simple molecular classification for endometrioid endometrial cancers that can be easily combined with Lynch syndrome screening provides important prognostic information. These findings support prospective clinical validation and further studies on the predictive value of a simplified molecular classification system. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Test-retest Agreement and Reliability of Quantitative Sensory Testing 1 Year After Breast Cancer Surgery

    DEFF Research Database (Denmark)

    Andersen, Kenneth Geving; Kehlet, Henrik; Aasvang, Eske Kvanner

    2015-01-01

    .5 SD) than within-patient variation (0.23 to 3.55 SD). There were no significant differences between pain and pain-free patients. The individual test-retest variability was higher on the operated side compared with the nonoperated side. DISCUSSION: The QST protocol reliability allows for group......OBJECTIVES: Quantitative sensory testing (QST) is used to assess sensory dysfunction and nerve damage by examining psychophysical responses to controlled, graded stimuli such as mechanical and thermal detection and pain thresholds. In the breast cancer population, 4 studies have used QST to examine...... persistent pain after breast cancer treatment, suggesting neuropathic pain being a prominent pain mechanism. However, the agreement and reliability of QST has not been described in the postsurgical breast cancer population, hindering exact interpretation of QST studies in this population. The aim...

  6. AN ADABOOST OPTIMIZED CCFIS BASED CLASSIFICATION MODEL FOR BREAST CANCER DETECTION

    Directory of Open Access Journals (Sweden)

    CHANDRASEKAR RAVI

    2017-06-01

    Full Text Available Classification is a Data Mining technique used for building a prototype of the data behaviour, using which an unseen data can be classified into one of the defined classes. Several researchers have proposed classification techniques but most of them did not emphasis much on the misclassified instances and storage space. In this paper, a classification model is proposed that takes into account the misclassified instances and storage space. The classification model is efficiently developed using a tree structure for reducing the storage complexity and uses single scan of the dataset. During the training phase, Class-based Closed Frequent ItemSets (CCFIS were mined from the training dataset in the form of a tree structure. The classification model has been developed using the CCFIS and a similarity measure based on Longest Common Subsequence (LCS. Further, the Particle Swarm Optimization algorithm is applied on the generated CCFIS, which assigns weights to the itemsets and their associated classes. Most of the classifiers are correctly classifying the common instances but they misclassify the rare instances. In view of that, AdaBoost algorithm has been used to boost the weights of the misclassified instances in the previous round so as to include them in the training phase to classify the rare instances. This improves the accuracy of the classification model. During the testing phase, the classification model is used to classify the instances of the test dataset. Breast Cancer dataset from UCI repository is used for experiment. Experimental analysis shows that the accuracy of the proposed classification model outperforms the PSOAdaBoost-Sequence classifier by 7% superior to other approaches like Naïve Bayes Classifier, Support Vector Machine Classifier, Instance Based Classifier, ID3 Classifier, J48 Classifier, etc.

  7. Computed tomography and the TNM classification of lung cancer

    International Nuclear Information System (INIS)

    Sparup, J.; Friis, M.; Brenoee, J.; Vejlsted, H.; Villumsen, B.; Olesen, K.P.; Borgeskov, S.; Bertelsen, S.

    1990-01-01

    Computed tomography (CT)of the thorax and upper abdomen was prospectively evaluated in 84 patients with potentially operable lung cancer. Invasion into the thoracic wall and the mediastinal structures was not accurately demonstrated by CT. For metastatic mediastinal lymph nodes, the sensitivity and specificity of CT were, respectively, 86 per cent and 61 per cent and the positive and negative predictive indices 49 per cent and 91 per cent. For T1, T2 and T3 tumours the negative indices were 100 per cent, 96 per cent and 71 per cent. Positive predictive index did not differ between squamous cell carcinoma and adenocarcinoma. Adrenal metastases were CT-suspected in 17 cases and liver metastases in eight, but were verified by ultrasonography in only one and four cases. CT should be used in preoperative investigation of lung cancer, irrespective of stage. Demonstration of thoracic-wall or mediastinal invasion need not exclude tumour resection. Preoperative mediastinoscopy is indicated if CT shows nodal metastases or if there are signs of tumour invasion, but not in CT-negative T1 or T2 tumour. Abdominal metastases indicated by CT should be investigated with CT-guided needle biopsy. (authors)

  8. FEATURE EXTRACTION BASED WAVELET TRANSFORM IN BREAST CANCER DIAGNOSIS USING FUZZY AND NON-FUZZY CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    Pelin GORGEL

    2013-01-01

    Full Text Available This study helps to provide a second eye to the expert radiologists for the classification of manually extracted breast masses taken from 60 digital mammıgrams. These mammograms have been acquired from Istanbul University Faculty of Medicine Hospital and have 78 masses. The diagnosis is implemented with pre-processing by using feature extraction based Fast Wavelet Transform (FWT. Afterwards Adaptive Neuro-Fuzzy Inference System (ANFIS based fuzzy subtractive clustering and Support Vector Machines (SVM methods are used for the classification. It is a comparative study which uses these methods respectively. According to the results of the study, ANFIS based subtractive clustering produces ??% while SVM produces ??% accuracy in malignant-benign classification. The results demonstrate that the developed system could help the radiologists for a true diagnosis and decrease the number of the missing cancerous regions or unnecessary biopsies.

  9. Reliability of a novel, semi-quantitative scale for classification of structural brain magnetic resonance imaging in children with cerebral palsy.

    Science.gov (United States)

    Fiori, Simona; Cioni, Giovanni; Klingels, Katrjin; Ortibus, Els; Van Gestel, Leen; Rose, Stephen; Boyd, Roslyn N; Feys, Hilde; Guzzetta, Andrea

    2014-09-01

    To describe the development of a novel rating scale for classification of brain structural magnetic resonance imaging (MRI) in children with cerebral palsy (CP) and to assess its interrater and intrarater reliability. The scale consists of three sections. Section 1 contains descriptive information about the patient and MRI. Section 2 contains the graphical template of brain hemispheres onto which the lesion is transposed. Section 3 contains the scoring system for the quantitative analysis of the lesion characteristics, grouped into different global scores and subscores that assess separately side, regions, and depth. A larger interrater and intrarater reliability study was performed in 34 children with CP (22 males, 12 females; mean age at scan of 9 y 5 mo [SD 3 y 3 mo], range 4 y-16 y 11 mo; Gross Motor Function Classification System level I, [n=22], II [n=10], and level III [n=2]). Very high interrater and intrarater reliability of the total score was found with indices above 0.87. Reliability coefficients of the lobar and hemispheric subscores ranged between 0.53 and 0.95. Global scores for hemispheres, basal ganglia, brain stem, and corpus callosum showed reliability coefficients above 0.65. This study presents the first visual, semi-quantitative scale for classification of brain structural MRI in children with CP. The high degree of reliability of the scale supports its potential application for investigating the relationship between brain structure and function and examining treatment response according to brain lesion severity in children with CP. © 2014 Mac Keith Press.

  10. Cross-Disciplinary Analysis of Lymph Node Classification in Lung Cancer on CT Scanning.

    Science.gov (United States)

    El-Sherief, Ahmed H; Lau, Charles T; Obuchowski, Nancy A; Mehta, Atul C; Rice, Thomas W; Blackstone, Eugene H

    2017-04-01

    Accurate and consistent regional lymph node classification is an important element in the staging and multidisciplinary management of lung cancer. Regional lymph node definition sets-lymph node maps-have been created to standardize regional lymph node classification. In 2009, the International Association for the Study of Lung Cancer (IASLC) introduced a lymph node map to supersede all preexisting lymph node maps. Our aim was to study if and how lung cancer specialists apply the IASLC lymph node map when classifying thoracic lymph nodes encountered on CT scans during lung cancer staging. From April 2013 through July 2013, invitations were distributed to all members of the Fleischner Society, Society of Thoracic Radiology, General Thoracic Surgical Club, and the American Association of Bronchology and Interventional Pulmonology to participate in an anonymous online image-based and text-based 20-question survey regarding lymph node classification for lung cancer staging on CT imaging. Three hundred thirty-seven people responded (approximately 25% participation). Respondents consisted of self-reported thoracic radiologists (n = 158), thoracic surgeons (n = 102), and pulmonologists who perform endobronchial ultrasonography (n = 77). Half of the respondents (50%; 95% CI, 44%-55%) reported using the IASLC lymph node map in daily practice, with no significant differences between subspecialties. A disparity was observed between the IASLC definition sets and their interpretation and application on CT scans, in particular for lymph nodes near the thoracic inlet, anterior to the trachea, anterior to the tracheal bifurcation, near the ligamentum arteriosum, between the bronchus intermedius and esophagus, in the internal mammary space, and adjacent to the heart. Use of older lymph node maps and inconsistencies in interpretation and application of definitions in the IASLC lymph node map may potentially lead to misclassification of stage and suboptimal management of lung

  11. Reliability and Validity of the Sensory Component of the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI): A Systematic Review.

    Science.gov (United States)

    Hales, M; Biros, E; Reznik, J E

    2015-01-01

    Since 1982, the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) has been used to classify sensation of spinal cord injury (SCI) through pinprick and light touch scores. The absence of proprioception, pain, and temperature within this scale creates questions about its validity and accuracy. To assess whether the sensory component of the ISNCSCI represents a reliable and valid measure of classification of SCI. A systematic review of studies examining the reliability and validity of the sensory component of the ISNCSCI published between 1982 and February 2013 was conducted. The electronic databases MEDLINE via Ovid, CINAHL, PEDro, and Scopus were searched for relevant articles. A secondary search of reference lists was also completed. Chosen articles were assessed according to the Oxford Centre for Evidence-Based Medicine hierarchy of evidence and critically appraised using the McMasters Critical Review Form. A statistical analysis was conducted to investigate the variability of the results given by reliability studies. Twelve studies were identified: 9 reviewed reliability and 3 reviewed validity. All studies demonstrated low levels of evidence and moderate critical appraisal scores. The majority of the articles (~67%; 6/9) assessing the reliability suggested that training was positively associated with better posttest results. The results of the 3 studies that assessed the validity of the ISNCSCI scale were confounding. Due to the low to moderate quality of the current literature, the sensory component of the ISNCSCI requires further revision and investigation if it is to be a useful tool in clinical trials.

  12. Reliability and cross-cultural validation of the Turkish version of Manual Ability Classification System (MACS) for children with cerebral palsy.

    Science.gov (United States)

    Akpinar, Pinar; Tezel, Canan G; Eliasson, Ann-Christin; Icagasioglu, Afitap

    2010-01-01

    To determine the reliability and cross-cultural validation of the Turkish translation of the Manual Ability Classification System (MACS) for children with cerebral palsy (CP) and to investigate the relation to gross motor function and other comorbidities. After the forward and backward translation procedures, inter-rater and test-retest reliability was assessed between parents, physiotherapists and physicians using the intra-class correlation coefficient (ICC). Children (N = 118, 4 to 18 years, mean age 9 years 4 months; 68 boys, 50 girls) with various types of CP were classified. Additional data on the Gross Motor Function Classification System (GMFCS), intellectual delay, visual acuity, and epilepsy were collected. The inter-rater reliability was high; the ICC ranged from 0.89 to 0.96 among different professionals and parents. Between two persons of the same profession it ranged from 0.97 to 0.98. For the test-retest reliability it ranged from 0.91 to 0.98. Total agreement between the GMFCS and the MACS occurred in only 45% of the children. The level of the MACS was found to correlate with the accompanying comorbidities, namely intellectual delay and epilepsy. The Turkish version of the MACS is found to be valid and reliable, and is suggested to be appropriate for the assessment of manual ability within the Turkish population.

  13. Reliability and validity of Champion's Health Belief Model Scale for breast cancer screening among Malaysian women.

    Science.gov (United States)

    Parsa, P; Kandiah, M; Mohd Nasir, M T; Hejar, A R; Nor Afiah, M Z

    2008-11-01

    Breast cancer is the leading cause of cancer deaths in Malaysian women, and the use of breast self-examination (BSE), clinical breast examination (CBE) and mammography remain low in Malaysia. Therefore, there is a need to develop a valid and reliable tool to measure the beliefs that influence breast cancer screening practices. The Champion's Health Belief Model Scale (CHBMS) is a valid and reliable tool to measure beliefs about breast cancer and screening methods in the Western culture. The purpose of this study was to translate the use of CHBMS into the Malaysian context and validate the scale among Malaysian women. A random sample of 425 women teachers was taken from 24 secondary schools in Selangor state, Malaysia. The CHBMS was translated into the Malay language, validated by an expert's panel, back translated, and pretested. Analyses included descriptive statistics of all the study variables, reliability estimates, and construct validity using factor analysis. The mean age of the respondents was 37.2 (standard deviation 7.1) years. Factor analysis yielded ten factors for BSE with eigenvalue greater than 1 (four factors more than the original): confidence 1 (ability to differentiate normal and abnormal changes in the breasts), barriers to BSE, susceptibility for breast cancer, benefits of BSE, health motivation 1 (general health), seriousness 1 (fear of breast cancer), confidence 2 (ability to detect size of lumps), seriousness 2 (fear of long-term effects of breast cancer), health motivation 2 (preventive health practice), and confidence 3 (ability to perform BSE correctly). For CBE and mammography scales, seven factors each were identified. Factors for CBE scale include susceptibility, health motivation 1, benefits of CBE, seriousness 1, barriers of CBE, seriousness 2 and health motivation 2. For mammography the scale includes benefits of mammography, susceptibility, health motivation 1, seriousness 1, barriers to mammography seriousness 2 and health

  14. Rough set soft computing cancer classification and network: one stone, two birds.

    Science.gov (United States)

    Zhang, Yue

    2010-07-15

    Gene expression profiling provides tremendous information to help unravel the complexity of cancer. The selection of the most informative genes from huge noise for cancer classification has taken centre stage, along with predicting the function of such identified genes and the construction of direct gene regulatory networks at different system levels with a tuneable parameter. A new study by Wang and Gotoh described a novel Variable Precision Rough Sets-rooted robust soft computing method to successfully address these problems and has yielded some new insights. The significance of this progress and its perspectives will be discussed in this article.

  15. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin

    DEFF Research Database (Denmark)

    Hoadley, Katherine A; Yau, Christina; Wolf, Denise M

    2014-01-01

    Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform...... on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset...

  16. Early detection of lung cancer from CT images: nodule segmentation and classification using deep learning

    Science.gov (United States)

    Sharma, Manu; Bhatt, Jignesh S.; Joshi, Manjunath V.

    2018-04-01

    Lung cancer is one of the most abundant causes of the cancerous deaths worldwide. It has low survival rate mainly due to the late diagnosis. With the hardware advancements in computed tomography (CT) technology, it is now possible to capture the high resolution images of lung region. However, it needs to be augmented by efficient algorithms to detect the lung cancer in the earlier stages using the acquired CT images. To this end, we propose a two-step algorithm for early detection of lung cancer. Given the CT image, we first extract the patch from the center location of the nodule and segment the lung nodule region. We propose to use Otsu method followed by morphological operations for the segmentation. This step enables accurate segmentation due to the use of data-driven threshold. Unlike other methods, we perform the segmentation without using the complete contour information of the nodule. In the second step, a deep convolutional neural network (CNN) is used for the better classification (malignant or benign) of the nodule present in the segmented patch. Accurate segmentation of even a tiny nodule followed by better classification using deep CNN enables the early detection of lung cancer. Experiments have been conducted using 6306 CT images of LIDC-IDRI database. We achieved the test accuracy of 84.13%, with the sensitivity and specificity of 91.69% and 73.16%, respectively, clearly outperforming the state-of-the-art algorithms.

  17. Classification of breast cancer patients using somatic mutation profiles and machine learning approaches.

    Science.gov (United States)

    Vural, Suleyman; Wang, Xiaosheng; Guda, Chittibabu

    2016-08-26

    The high degree of heterogeneity observed in breast cancers makes it very difficult to classify the cancer patients into distinct clinical subgroups and consequently limits the ability to devise effective therapeutic strategies. Several classification strategies based on ER/PR/HER2 expression or the expression profiles of a panel of genes have helped, but such methods often produce misleading results due to their dynamic nature. In contrast, somatic DNA mutations are relatively stable and lead to initiation and progression of many sporadic cancers. Hence in this study, we explore the use of gene mutation profiles to classify, characterize and predict the subgroups of breast cancers. We analyzed the whole exome sequencing data from 358 ethnically similar breast cancer patients in The Cancer Genome Atlas (TCGA) project. Somatic and non-synonymous single nucleotide variants identified from each patient were assigned a quantitative score (C-score) that represents the extent of negative impact on the gene function. Using these scores with non-negative matrix factorization method, we clustered the patients into three subgroups. By comparing the clinical stage of patients, we identified an early-stage-enriched and a late-stage-enriched subgroup. Comparison of the mutation scores of early and late-stage-enriched subgroups identified 358 genes that carry significantly higher mutations rates in the late stage subgroup. Functional characterization of these genes revealed important functional gene families that carry a heavy mutational load in the late state rich subgroup of patients. Finally, using the identified subgroups, we also developed a supervised classification model to predict the stage of the patients. This study demonstrates that gene mutation profiles can be effectively used with unsupervised machine-learning methods to identify clinically distinguishable breast cancer subgroups. The classification model developed in this method could provide a reasonable

  18. Long-term Prostate-specific Antigen Velocity in Improved Classification of Prostate Cancer Risk and Mortality

    DEFF Research Database (Denmark)

    Ørsted, David Dynnes; Bojesen, Stig E; Kamstrup, Pia R

    2013-01-01

    BACKGROUND: It remains unclear whether adding long-term prostate-specific antigen velocity (PSAV) to baseline PSA values improves classification of prostate cancer (PCa) risk and mortality in the general population. OBJECTIVE: To determine whether long-term PSAV improves classification of PCa risk...

  19. Setting a generalized functional linear model (GFLM for the classification of different types of cancer

    Directory of Open Access Journals (Sweden)

    Miguel Flores

    2016-11-01

    Full Text Available This work aims to classify the DNA sequences of healthy and malignant cancer respectively. For this, supervised and unsupervised classification methods from a functional context are used; i.e. each strand of DNA is an observation. The observations are discretized, for that reason different ways to represent these observations with functions are evaluated. In addition, an exploratory study is done: estimating the mean and variance of each functional type of cancer. For the unsupervised classification method, hierarchical clustering with different measures of functional distance is used. On the other hand, for the supervised classification method, a functional generalized linear model is used. For this model the first and second derivatives are used which are included as discriminating variables. It has been verified that one of the advantages of working in the functional context is to obtain a model to correctly classify cancers by 100%. For the implementation of the methods it has been used the fda.usc R package that includes all the techniques of functional data analysis used in this work. In addition, some that have been developed in recent decades. For more details of these techniques can be consulted Ramsay, J. O. and Silverman (2005 and Ferraty et al. (2006.

  20. Training ANFIS structure using genetic algorithm for liver cancer classification based on microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Bülent Haznedar

    2017-02-01

    Full Text Available Classification is an important data mining technique, which is used in many fields mostly exemplified as medicine, genetics and biomedical engineering. The number of studies about classification of the datum on DNA microarray gene expression is specifically increased in recent years. However, because of the reasons as the abundance of gene numbers in the datum as microarray gene expressions and the nonlinear relations mostly across those datum, the success of conventional classification algorithms can be limited. Because of these reasons, the interest on classification methods which are based on artificial intelligence to solve the problem on classification has been gradually increased in recent times. In this study, a hybrid approach which is based on Adaptive Neuro-Fuzzy Inference System (ANFIS and Genetic Algorithm (GA are suggested in order to classify liver microarray cancer data set. Simulation results are compared with the results of other methods. According to the results obtained, it is seen that the recommended method is better than the other methods.

  1. A multicenter validation of an endoscopic classification with narrow band imaging for gastric precancerous and cancerous lesions

    NARCIS (Netherlands)

    Pimentel-Nunes, P.; Dinis-Ribeiro, M.; Soares, J. B.; Marcos-Pinto, R.; Santos, C.; Rolanda, C.; Bastos, R. P.; Areia, M.; Afonso, L.; Bergman, J.; Sharma, P.; Gotoda, T.; Henrique, R.; Moreira-Dias, L.

    2012-01-01

    Background and study aim: The reliability and external validity of narrow band imaging (NBI) in the stomach have not been described consistently. The aim of the current study was to describe and estimate the accuracy and reliability of a simplified classification system for NBI in the diagnosis of

  2. Apparent diffusion coefficient value of gastric cancer by diffusion-weighted imaging: Correlations with the histological differentiation and Lauren classification

    International Nuclear Information System (INIS)

    Liu, Song; Guan, Wenxian; Wang, Hao; Pan, Liang; Zhou, Zhuping; Yu, Haiping; Liu, Tian; Yang, Xiaofeng; He, Jian; Zhou, Zhengyang

    2014-01-01

    Highlights: • Gastric cancers’ ADC values were significantly lower than normal gastric wall. • Gastric adenocarcinomas with different differentiation had different ADC values. • Gastric adenocarcinomas’ ADC values correlated with histologic differentiations. • Gastric cancers’ ADC values correlated with Lauren classifications. • Mean ADC value was better than min ADC value in characterizing gastric cancers. - Abstract: Objective: The purpose of this study was to evaluate the correlations between histological differentiation and Lauren classification of gastric cancer and the apparent diffusion coefficient (ADC) value of diffusion weighted imaging (DWI). Materials and methods: Sixty-nine patients with gastric cancer lesions underwent preoperative magnetic resonance imaging (MRI) (3.0T) and surgical resection. DWI was obtained with a single-shot, echo-planar imaging sequence in the axial plane (b values: 0 and 1000 s/mm 2 ). Mean and minimum ADC values were obtained for each gastric cancer and normal gastric walls by two radiologists, who were blinded to the histological findings. Histological type, degree of differentiation and Lauren classification of each resected specimen were determined by one pathologist. Mean and minimum ADC values of gastric cancers with different histological types, degrees of differentiation and Lauren classifications were compared. Correlations between ADC values and histological differentiation and Lauren classification were analyzed. Results: The mean and minimum ADC values of gastric cancers, as a whole and separately, were significantly lower than those of normal gastric walls (all p values <0.001). There were significant differences in the mean and minimum ADC values among gastric cancers with different histological types, degrees of differentiation and Lauren classifications (p < 0.05). Mean and minimum ADC values correlated significantly (all p < 0.001) with histological differentiation (r = 0.564, 0.578) and Lauren

  3. Feature selection and classification of MAQC-II breast cancer and multiple myeloma microarray gene expression data.

    Directory of Open Access Journals (Sweden)

    Qingzhong Liu

    Full Text Available Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray data for the purpose of, e.g., predicting gene-disease association, feature selection is very important because it provides a way to handle the high dimensionality by exploiting information redundancy induced by associations among genetic markers. Judicious feature selection in microarray data analysis can result in significant reduction of cost while maintaining or improving the classification or prediction accuracy of learning machines that are employed to sort out the datasets. In this paper, we propose a gene selection method called Recursive Feature Addition (RFA, which combines supervised learning and statistical similarity measures. We compare our method with the following gene selection methods: Support Vector Machine Recursive Feature Elimination (SVMRFE, Leave-One-Out Calculation Sequential Forward Selection (LOOCSFS, Gradient based Leave-one-out Gene Selection (GLGS. To evaluate the performance of these gene selection methods, we employ several popular learning classifiers on the MicroArray Quality Control phase II on predictive modeling (MAQC-II breast cancer dataset and the MAQC-II multiple myeloma dataset. Experimental results show that gene selection is strictly paired with learning classifier. Overall, our approach outperforms other compared methods. The biological functional analysis based on the MAQC-II breast cancer dataset convinced us to apply our method for phenotype prediction. Additionally, learning classifiers also play important roles in the classification of microarray data and our experimental results indicate that the Nearest Mean Scale Classifier (NMSC is a good choice due to its prediction reliability and its stability across the three performance measurements: Testing accuracy, MCC values, and

  4. Visualization and tissue classification of human breast cancer images using ultrahigh-resolution OCT (Conference Presentation)

    Science.gov (United States)

    Yao, Xinwen; Gan, Yu; Chang, Ernest W.; Hibshoosh, Hanina; Feldman, Sheldon; Hendon, Christine P.

    2017-02-01

    We employed a home-built ultrahigh resolution (UHR) OCT system at 800nm to image human breast cancer sample ex vivo. The system has an axial resolution of 2.72µm and a lateral resolution of 5.52µm with an extended imaging range of 1.78mm. Over 900 UHR OCT volumes were generated on specimens from 23 breast cancer cases. With better spatial resolution, detailed structures in the breast tissue were better defined. Different types of breast cancer as well as healthy breast tissue can be well delineated from the UHR OCT images. To quantitatively evaluate the advantages of UHR OCT imaging of breast cancer, features derived from OCT intensity images were used as inputs to a machine learning model, the relevance vector machine. A trained machine learning model was employed to evaluate the performance of tissue classification based on UHR OCT images for differentiating tissue types in the breast samples, including adipose tissue, healthy stroma and cancerous region. For adipose tissue, grid-based local features were extracted from OCT intensity data, including standard deviation, entropy, and homogeneity. We showed that it was possible to enhance the classification performance on distinguishing fat tissue from non-fat tissue by using the UHR images when compared with the results based on OCT images from a commercial 1300 nm OCT system. For invasive ductal carcinoma (IDC) and normal stroma differentiation, the classification was based on frame-based features that portray signal penetration depth and tissue reflectivity. The confusing matrix indicated a sensitivity of 97.5% and a sensitivity of 77.8%.

  5. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    Directory of Open Access Journals (Sweden)

    Reinders Marcel JT

    2009-11-01

    Full Text Available Abstract Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical

  6. Reliability and Validity of the Korean Cancer Pain Assessment Tool (KCPAT)

    Science.gov (United States)

    Kim, Jeong A; Lee, Juneyoung; Park, Jeanno; Lee, Myung Ah; Yeom, Chang Hwan; Jang, Se Kwon; Yoon, Duck Mi; Kim, Jun Suk

    2005-01-01

    The Korean Cancer Pain Assessment Tool (KCPAT), which was developed in 2003, consists of questions concerning the location of pain, the nature of pain, the present pain intensity, the symptoms associated with the pain, and psychosocial/spiritual pain assessments. This study was carried out to evaluate the reliability and validity of the KCPAT. A stratified, proportional-quota, clustered, systematic sampling procedure was used. The study population (903 cancer patients) was 1% of the target population (90,252 cancer patients). A total of 314 (34.8%) questionnaires were collected. The results showed that the average pain score (5 point on Likert scale) according to the cancer type and the at-present average pain score (VAS, 0-10) were correlated (r=0.56, p<0.0001), and showed moderate agreement (kappa=0.364). The mean satisfaction score was 3.8 (1-5). The average time to complete the questionnaire was 8.9 min. In conclusion, the KCPAT is a reliable and valid instrument for assessing cancer pain in Koreans. PMID:16224166

  7. reliability reliability

    African Journals Online (AJOL)

    eobe

    Corresponding author, Tel: +234-703. RELIABILITY .... V , , given by the code of practice. However, checks must .... an optimization procedure over the failure domain F corresponding .... of Concrete Members based on Utility Theory,. Technical ...

  8. Classification of Breast Cancer Subtypes by combining Gene Expression and DNA Methylation Data

    Directory of Open Access Journals (Sweden)

    List Markus

    2014-06-01

    Full Text Available Selecting the most promising treatment strategy for breast cancer crucially depends on determining the correct subtype. In recent years, gene expression profiling has been investigated as an alternative to histochemical methods. Since databases like TCGA provide easy and unrestricted access to gene expression data for hundreds of patients, the challenge is to extract a minimal optimal set of genes with good prognostic properties from a large bulk of genes making a moderate contribution to classification. Several studies have successfully applied machine learning algorithms to solve this so-called gene selection problem. However, more diverse data from other OMICS technologies are available, including methylation. We hypothesize that combining methylation and gene expression data could already lead to a largely improved classification model, since the resulting model will reflect differences not only on the transcriptomic, but also on an epigenetic level. We compared so-called random forest derived classification models based on gene expression and methylation data alone, to a model based on the combined features and to a model based on the gold standard PAM50. We obtained bootstrap errors of 10-20% and classification error of 1-50%, depending on breast cancer subtype and model. The gene expression model was clearly superior to the methylation model, which was also reflected in the combined model, which mainly selected features from gene expression data. However, the methylation model was able to identify unique features not considered as relevant by the gene expression model, which might provide deeper insights into breast cancer subtype differentiation on an epigenetic level.

  9. Automatic classification of ovarian cancer types from cytological images using deep convolutional neural networks.

    Science.gov (United States)

    Wu, Miao; Yan, Chuanbo; Liu, Huiqiang; Liu, Qian

    2018-06-29

    Ovarian cancer is one of the most common gynecologic malignancies. Accurate classification of ovarian cancer types (serous carcinoma, mucous carcinoma, endometrioid carcinoma, transparent cell carcinoma) is an essential part in the different diagnosis. Computer-aided diagnosis (CADx) can provide useful advice for pathologists to determine the diagnosis correctly. In our study, we employed a Deep Convolutional Neural Networks (DCNN) based on AlexNet to automatically classify the different types of ovarian cancers from cytological images. The DCNN consists of five convolutional layers, three max pooling layers, and two full reconnect layers. Then we trained the model by two group input data separately, one was original image data and the other one was augmented image data including image enhancement and image rotation. The testing results are obtained by the method of 10-fold cross-validation, showing that the accuracy of classification models has been improved from 72.76 to 78.20% by using augmented images as training data. The developed scheme was useful for classifying ovarian cancers from cytological images. © 2018 The Author(s).

  10. Gene selection and classification for cancer microarray data based on machine learning and similarity measures

    Directory of Open Access Journals (Sweden)

    Liu Qingzhong

    2011-12-01

    Full Text Available Abstract Background Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. Associations among genetic markers mean one can exploit information redundancy to potentially reduce classification cost in terms of time and money. Results To deal with redundant information and improve classification, we propose a gene selection method, Recursive Feature Addition, which combines supervised learning and statistical similarity measures. To determine the final optimal gene set for prediction and classification, we propose an algorithm, Lagging Prediction Peephole Optimization. By using six benchmark microarray gene expression data sets, we compared Recursive Feature Addition with recently developed gene selection methods: Support Vector Machine Recursive Feature Elimination, Leave-One-Out Calculation Sequential Forward Selection and several others. Conclusions On average, with the use of popular learning machines including Nearest Mean Scaled Classifier, Support Vector Machine, Naive Bayes Classifier and Random Forest, Recursive Feature Addition outperformed other methods. Our studies also showed that Lagging Prediction Peephole Optimization is superior to random strategy; Recursive Feature Addition with Lagging Prediction Peephole Optimization obtained better testing accuracies than the gene selection method varSelRF.

  11. Inter-examiner reliability of a standardized Ultra-sonographic method for classification of changes related to supraspinatus tendinopathy – a pilot study

    DEFF Research Database (Denmark)

    Larsen, Camilla Marie; Ingwersen, Kim Gordon; Hjarnbæk, John

    2015-01-01

    Inter-examiner reliability of a standardized Ultra-sonographic method for classification of changes related to supraspinatus tendinopathy – a pilot study Ingwersen KG1, 2, Hjarbaek J3, Eshøj H1, Larsen CM1, 4, Vobbe J5, Juul-Kristensen B1, 6 1Institute of Sports Science and Clinical Biomechanics......, University of Southern Denmark, Odense, Denmark. 2Physiotherapy Department, Hospital Lillebaelt, Vejle Hospital, Vejle, Denmark 3Department of Radiology, Musculoskeletal section, Odense University Hospital, Odense, Denmark 4Health Sciences Research Centre, University College Lillebaelt, Odense Denmark 5...... athletes. For optimizing rehabilitation to the different stages of tendinopathy (1) ultra-sonography (US) may be used. Reliability of such method for RT is lacking. Aims. To develop and test inter-examiner reliability of US for classifying RT. Materials and Methods. A three-phased standardized protocol...

  12. A pilot study to explore the feasibility of using theClinical Care Classification System for developing a reliable costing method for nursing services.

    Science.gov (United States)

    Dykes, Patricia C; Wantland, Dean; Whittenburg, Luann; Lipsitz, Stuart; Saba, Virginia K

    2013-01-01

    While nursing activities represent a significant proportion of inpatient care, there are no reliable methods for determining nursing costs based on the actual services provided by the nursing staff. Capture of data to support accurate measurement and reporting on the cost of nursing services is fundamental to effective resource utilization. Adopting standard terminologies that support tracking both the quality and the cost of care could reduce the data entry burden on direct care providers. This pilot study evaluated the feasibility of using a standardized nursing terminology, the Clinical Care Classification System (CCC), for developing a reliable costing method for nursing services. Two different approaches are explored; the Relative Value Unit RVU and the simple cost-to-time methods. We found that the simple cost-to-time method was more accurate and more transparent in its derivation than the RVU method and may support a more consistent and reliable approach for costing nursing services.

  13. Resolving breast cancer heterogeneity by searching reliable protein cancer biomarkers in the breast fluid secretome

    International Nuclear Information System (INIS)

    Mannello, Ferdinando; Ligi, Daniela

    2013-01-01

    One of the major goals in cancer research is to find and evaluate the early presence of biomarkers in human fluids and tissues. To resolve the complex cell heterogeneity of a tumor mass, it will be useful to characterize the intricate biomolecular composition of tumor microenvironment (the so called cancer secretome), validating secreted proteins as early biomarkers of cancer initiation and progression. This approach is not broadly applicable because of the paucity of well validated and FDA-approved biomarkers and because most of the candidate biomarkers are mainly organ-specific rather than tumor-specific. For these reasons, there is an urgent need to identify and validate a panel of biomarker combinations for early detection of human tumors. This is especially important for breast cancer, the cancer spread most worldwide among women. It is well known that patients with early diagnosed breast cancer live longer, require less extensive treatment and fare better than patients with more aggressive and/or advanced disease. In the frame of searching breast cancer biomarkers (especially using nipple aspirate fluid mirroring breast microenvironment), studies have highlighted an optimal combination of well-known biomarkers: uPA + PAI-1 + TF. When individually investigated they did not show perfect accuracy in predicting the presence of breast cancer, whereas the triple combination has been demonstrated to be highly predictive of pre-cancer and/or cancerous conditions, approaching 97-100% accuracy. Despite the heterogeneous composition of breast cancer and the difficulties to find specific breast cancer biomolecules, the noninvasive analysis of the nipple aspirate fluid secretome may significantly improve the discovery of promising biomarkers, helping also the differentiation among benign and invasive breast diseases, opening new frontiers in early oncoproteomics

  14. Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modules

    International Nuclear Information System (INIS)

    Teschendorff, Andrew E; Gomez, Sergio; Arenas, Alex; El-Ashry, Dorraya; Schmidt, Marcus; Gehrmann, Mathias; Caldas, Carlos

    2010-01-01

    Elucidating the activation pattern of molecular pathways across a given tumour type is a key challenge necessary for understanding the heterogeneity in clinical response and for developing novel more effective therapies. Gene expression signatures of molecular pathway activation derived from perturbation experiments in model systems as well as structural models of molecular interactions ('model signatures') constitute an important resource for estimating corresponding activation levels in tumours. However, relatively few strategies for estimating pathway activity from such model signatures exist and only few studies have used activation patterns of pathways to refine molecular classifications of cancer. Here we propose a novel network-based method for estimating pathway activation in tumours from model signatures. We find that although the pathway networks inferred from cancer expression data are highly consistent with the prior information contained in the model signatures, that they also exhibit a highly modular structure and that estimation of pathway activity is dependent on this modular structure. We apply our methodology to a panel of 438 estrogen receptor negative (ER-) and 785 estrogen receptor positive (ER+) breast cancers to infer activation patterns of important cancer related molecular pathways. We show that in ER negative basal and HER2+ breast cancer, gene expression modules reflecting T-cell helper-1 (Th1) and T-cell helper-2 (Th2) mediated immune responses play antagonistic roles as major risk factors for distant metastasis. Using Boolean interaction Cox-regression models to identify non-linear pathway combinations associated with clinical outcome, we show that simultaneous high activation of Th1 and low activation of a TGF-beta pathway module defines a subtype of particularly good prognosis and that this classification provides a better prognostic model than those based on the individual pathways. In ER+ breast cancer, we find that

  15. Classification of Dukes' B and C colorectal cancers using expression arrays

    DEFF Research Database (Denmark)

    Frederiksen, C.M.; Knudsen, Steen; Laurberg, S.

    2003-01-01

    Purpose. Colorectal cancer is one of the most common malignancies. Substaging of the cancer is of importance not only to prognosis but also to treatment. Classification of substages based on DNA microarray technology is currently the most promising approach. We therefore investigated if gene...... expression microarrays could be used to classify colorectal tumors. Methods. We used the Affymetrix oligonucleotide arrays to analyze the expression of more than 5,000 genes in samples from the sigmoid and upper rectum of the left colon. Five samples were from normal mucosa and five samples from each...... expression of one of the most common malignancies, colorectal cancer, now seems to be within reach. The data indicates that it is possible at least to classify Dukes' B and C colorectal tumors with microarrays....

  16. Artificial neural networks as classification and diagnostic tools for lymph node-negative breast cancers

    Energy Technology Data Exchange (ETDEWEB)

    Eswari J, Satya; Chandrakar, Neha [National Institute of Technology Raipur, Raipur (India)

    2016-04-15

    Artificial neural networks (ANNs) can be used to develop a technique to classify lymph node negative breast cancer that is prone to distant metastases based on gene expression signatures. The neural network used is a multilayered feed forward network that employs back propagation algorithm. Once trained with DNA microarraybased gene expression profiles of genes that were predictive of distant metastasis recurrence of lymph node negative breast cancer, the ANNs became capable of correctly classifying all samples and recognizing the genes most appropriate to the classification. To test the ability of the trained ANN models in recognizing lymph node negative breast cancer, we analyzed additional idle samples that were not used beforehand for the training procedure and obtained the correctly classified result in the validation set. For more substantial result, bootstrapping of training and testing dataset was performed as external validation. This study illustrates the potential application of ANN for breast tumor diagnosis and the identification of candidate targets in patients for therapy.

  17. [Classification and characteristics of interval cancers in the Principality of Asturias's Breast Cancer Screening Program].

    Science.gov (United States)

    Prieto García, M A; Delgado Sevillano, R; Baldó Sierra, C; González Díaz, E; López Secades, A; Llavona Amor, J A; Vidal Marín, B

    2013-09-01

    To review and classify the interval cancers found in the Principality of Asturias's Breast Cancer Screening Program (PDPCM). A secondary objective was to determine the histological characteristics, size, and stage of the interval cancers at the time of diagnosis. We included the interval cancers in the PDPCM in the period 2003-2007. Interval cancers were classified according to the breast cancer screening program protocol, with double reading without consensus, without blinding, with arbitration. Mammograms were interpreted by 10 radiologists in the PDPCM. A total of 33.7% of the interval cancers could not be classified; of the interval cancers that could be classified, 40.67% were labeled true interval cancers, 31.4% were labeled false negatives on screening, 23.7% had minimal signs, and 4.23% were considered occult. A total of 70% of the interval cancers were diagnosed in the year of the period between screening examinations and 71.7% were diagnosed after subsequent screening. A total of 76.9% were invasive ductal carcinomas, 61.1% were stage II when detected, and 78.7% were larger than 10mm when detected. The rate of interval cancers and the rate of false negatives in the PDPCM are higher than those recommended in the European guidelines. Interval cancers are diagnosed later than the tumors detected at screening. Studying interval cancers provides significant training for the radiologists in the PDPCM. Copyright © 2011 SERAM. Published by Elsevier Espana. All rights reserved.

  18. CrossLink: a novel method for cross-condition classification of cancer subtypes.

    Science.gov (United States)

    Ma, Chifeng; Sastry, Konduru S; Flore, Mario; Gehani, Salah; Al-Bozom, Issam; Feng, Yusheng; Serpedin, Erchin; Chouchane, Lotfi; Chen, Yidong; Huang, Yufei

    2016-08-22

    We considered the prediction of cancer classes (e.g. subtypes) using patient gene expression profiles that contain both systematic and condition-specific biases when compared with the training reference dataset. The conventional normalization-based approaches cannot guarantee that the gene signatures in the reference and prediction datasets always have the same distribution for all different conditions as the class-specific gene signatures change with the condition. Therefore, the trained classifier would work well under one condition but not under another. To address the problem of current normalization approaches, we propose a novel algorithm called CrossLink (CL). CL recognizes that there is no universal, condition-independent normalization mapping of signatures. In contrast, it exploits the fact that the signature is unique to its associated class under any condition and thus employs an unsupervised clustering algorithm to discover this unique signature. We assessed the performance of CL for cross-condition predictions of PAM50 subtypes of breast cancer by using a simulated dataset modeled after TCGA BRCA tumor samples with a cross-validation scheme, and datasets with known and unknown PAM50 classification. CL achieved prediction accuracy >73 %, highest among other methods we evaluated. We also applied the algorithm to a set of breast cancer tumors derived from Arabic population to assign a PAM50 classification to each tumor based on their gene expression profiles. A novel algorithm CrossLink for cross-condition prediction of cancer classes was proposed. In all test datasets, CL showed robust and consistent improvement in prediction performance over other state-of-the-art normalization and classification algorithms.

  19. In vivo subsite classification and diagnosis of oral cancers using Raman spectroscopy

    Directory of Open Access Journals (Sweden)

    Aditi Sahu

    2016-09-01

    Full Text Available Oral cancers suffer from poor disease-free survival rates due to delayed diagnosis. Noninvasive, rapid, objective approaches as adjuncts to visual inspection can help in better management of oral cancers. Raman spectroscopy (RS has shown potential in identification of oral premalignant and malignant conditions and also in the detection of early cancer changes like cancer-field-effects (CFE at buccal mucosa subsite. Anatomic differences between different oral subsites have also been reported using RS. In this study, anatomical differences between subsites and their possible influence on healthy vs pathological classification were evaluated on 85 oral cancer and 72 healthy subjects. Spectra were acquired from buccal mucosa, lip and tongue in healthy, contralateral (internal healthy control, premalignant and cancer conditions using fiber-optic Raman spectrometer. Mean spectra indicate predominance of lipids in healthy buccal mucosa, contribution of both lipids and proteins in lip while major dominance of protein in tongue spectra. From healthy to tumor, changes in protein secondary-structure, DNA and heme-related features were observed. Principal component linear discriminant analysis (PC-LDA followed by leave-one-out-cross-validation (LOOCV was used for data analysis. Findings indicate buccal mucosa and tongue are distinct entities, while lip misclassifies with both these subsites. Additionally, the diagnostic algorithm for individual subsites gave improved classification efficiencies with respect to the pooled subsites model. However, as the pooled subsites model yielded 98% specificity and 100% sensitivity, this model may be more useful for preliminary screening applications. Large-scale validation studies are a pre-requisite before envisaging future clinical applications.

  20. Prediction of Depression in Cancer Patients With Different Classification Criteria, Linear Discriminant Analysis versus Logistic Regression.

    Science.gov (United States)

    Shayan, Zahra; Mohammad Gholi Mezerji, Naser; Shayan, Leila; Naseri, Parisa

    2015-11-03

    Logistic regression (LR) and linear discriminant analysis (LDA) are two popular statistical models for prediction of group membership. Although they are very similar, the LDA makes more assumptions about the data. When categorical and continuous variables used simultaneously, the optimal choice between the two models is questionable. In most studies, classification error (CE) is used to discriminate between subjects in several groups, but this index is not suitable to predict the accuracy of the outcome. The present study compared LR and LDA models using classification indices. This cross-sectional study selected 243 cancer patients. Sample sets of different sizes (n = 50, 100, 150, 200, 220) were randomly selected and the CE, B, and Q classification indices were calculated by the LR and LDA models. CE revealed the a lack of superiority for one model over the other, but the results showed that LR performed better than LDA for the B and Q indices in all situations. No significant effect for sample size on CE was noted for selection of an optimal model. Assessment of the accuracy of prediction of real data indicated that the B and Q indices are appropriate for selection of an optimal model. The results of this study showed that LR performs better in some cases and LDA in others when based on CE. The CE index is not appropriate for classification, although the B and Q indices performed better and offered more efficient criteria for comparison and discrimination between groups.

  1. Classification of prostate cancer grade using temporal ultrasound: in vivo feasibility study

    Science.gov (United States)

    Ghavidel, Sahar; Imani, Farhad; Khallaghi, Siavash; Gibson, Eli; Khojaste, Amir; Gaed, Mena; Moussa, Madeleine; Gomez, Jose A.; Siemens, D. Robert; Leveridge, Michael; Chang, Silvia; Fenster, Aaron; Ward, Aaron D.; Abolmaesumi, Purang; Mousavi, Parvin

    2016-03-01

    Temporal ultrasound has been shown to have high classification accuracy in differentiating cancer from benign tissue. In this paper, we extend the temporal ultrasound method to classify lower grade Prostate Cancer (PCa) from all other grades. We use a group of nine patients with mostly lower grade PCa, where cancerous regions are also limited. A critical challenge is to train a classifier with limited aggressive cancerous tissue compared to low grade cancerous tissue. To resolve the problem of imbalanced data, we use Synthetic Minority Oversampling Technique (SMOTE) to generate synthetic samples for the minority class. We calculate spectral features of temporal ultrasound data and perform feature selection using Random Forests. In leave-one-patient-out cross-validation strategy, an area under receiver operating characteristic curve (AUC) of 0.74 is achieved with overall sensitivity and specificity of 70%. Using an unsupervised learning approach prior to proposed method improves sensitivity and AUC to 80% and 0.79. This work represents promising results to classify lower and higher grade PCa with limited cancerous training samples, using temporal ultrasound.

  2. Classification tree analysis of second neoplasms in survivors of childhood cancer

    International Nuclear Information System (INIS)

    Jazbec, Janez; Todorovski, Ljupčo; Jereb, Berta

    2007-01-01

    Reports on childhood cancer survivors estimated cumulative probability of developing secondary neoplasms vary from 3,3% to 25% at 25 years from diagnosis, and the risk of developing another cancer to several times greater than in the general population. In our retrospective study, we have used the classification tree multivariate method on a group of 849 first cancer survivors, to identify childhood cancer patients with the greatest risk for development of secondary neoplasms. In observed group of patients, 34 develop secondary neoplasm after treatment of primary cancer. Analysis of parameters present at the treatment of first cancer, exposed two groups of patients at the special risk for secondary neoplasm. First are female patients treated for Hodgkin's disease at the age between 10 and 15 years, whose treatment included radiotherapy. Second group at special risk were male patients with acute lymphoblastic leukemia who were treated at the age between 4,6 and 6,6 years of age. The risk groups identified in our study are similar to the results of studies that used more conventional approaches. Usefulness of our approach in study of occurrence of second neoplasms should be confirmed in larger sample study, but user friendly presentation of results makes it attractive for further studies

  3. Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles

    Directory of Open Access Journals (Sweden)

    Wong G William

    2008-06-01

    Full Text Available Abstract Background Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detection of this cancer type is urgently needed. In recent years, proteomics profiling techniques combined with various data analysis methods have been successfully used to gain critical insights into processes and mechanisms underlying pathologic conditions, particularly as they relate to cancer. However, the high dimensionality of proteomics data combined with their relatively small sample sizes poses a significant challenge to current data mining methodology where many of the standard methods cannot be applied directly. Here, we propose a novel methodological framework using machine learning method, in which decision tree based classifier ensembles coupled with feature selection methods, is applied to proteomics data generated from premalignant pancreatic cancer. Results This study explores the utility of three different feature selection schemas (Student t test, Wilcoxon rank sum test and genetic algorithm to reduce the high dimensionality of a pancreatic cancer proteomic dataset. Using the top features selected from each method, we compared the prediction performances of a single decision tree algorithm C4.5 with six different decision-tree based classifier ensembles (Random forest, Stacked generalization, Bagging, Adaboost, Logitboost and Multiboost. We show that ensemble classifiers always outperform single decision tree classifier in having greater accuracies and smaller prediction errors when applied to a pancreatic cancer proteomics dataset. Conclusion In our cross validation framework, classifier ensembles generally have better classification accuracies compared to that of a single decision tree when applied to a pancreatic cancer proteomic dataset, thus suggesting its utility in future proteomics data analysis. Additionally, the use of feature selection

  4. Development of a Taiwan cancer-related fatigue cognition questionnaire: reliability and validity.

    Science.gov (United States)

    Lai, Shih-Chiung; Lin, Wei-Chun; Chen, Chien-Hsin; Wu, Szu-Yuan

    2017-04-25

    We prospectively designed a Taiwan cancer-related fatigue cognition questionnaire, version 1.0 (TCRFCQ-V1.0), for Taiwanese patients with cancer and investigated the reliability and validity of this questionnaire. The completion rate of the TCRFCQ-V1.0 was high (97% of the patients completed all items), and the rate of missing data was low (0.2%-1.1% for each item). Moreover, the Cronbach alpha value was 0.889. We eliminated 5 items because their respective Cronbach alpha values were higher than the total mean value of Cronbach's alpha. Overall, the TCRFCQ-V1.0 had adequate Cronbach alpha coefficients (range, from 0.882 to 0.889). In addition, the results of Bartlett's test were significant (chi-squared, 2390.11; p Kaiser-Meyer-Olkin statistic of 0.868. Through exploratory factor analysis, we identified 6 factors with eigenvalues of > 1, and the scree plot indicated no flattening factors. Overall, 28 items achieved a factor loading of ≥ 0.55. We enrolled patients with cancer who were aged > 18 years, had received a pathological diagnosis of cancer, and had undergone cancer treatments such as surgery, chemotherapy, radiotherapy, or concurrent chemoradiotherapy at a single institute in Taiwan. Of the identified 167 eligible patients, 161 (96.4%) were approached. Of these patients, 6 (7.2%) declined to participate and 155 (92.8%) were interviewed. The initial 43 items in the TCRFCQ-V1.0 were assessed for ceiling and floor effects. The TCRFCQ-V1.0 is a reliable and valid instrument for measuring CRF cognition in Taiwanese patients with cancer.

  5. [Clinical Study of 2014 ISUP New Grade Group Classification for Prostate Cancer Patients Treated by Androgen Deprivation Therapy].

    Science.gov (United States)

    Uno, Masahiro; Kawase, Makoto; Kato, Daiki; Ishida, Takashi; Kato, Seiichi; Fujimoto, Yoshinori

    2018-01-01

    The 2014 International Society of Urological Pathology (ISUP) has proposed a new grade group (GG) classification for Gleason scores (GS). The usefulness of the new GG classification was investigated with 518 prostate cancer patients who underwent androgen deprivation therapy. According to the new GG classification, Stages B‒D and the new GG classification relapse-free rate for each stage were calculated using the Kaplan‒Meier method. The new GG classification revealed a significant difference for the relapse-free rate only between some groups. Analysis using the Cox proportional hazards model indicated that the risk of relapse was higher in GGs 4 and 5 than in GG 1. The usefulness about the relapse-free rate in androgen deprivation therapy of the 2014 ISUP new grade group classification a waits future examination.

  6. Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team

    DEFF Research Database (Denmark)

    Bjørn, Signe Frahm; Schnack, Tine Henrichsen; Lajer, Henrik

    2017-01-01

    multidisciplinary team (MDT) decisions. Materials and Methods Four hundred eighteen women diagnosed with ovarian cancers (n = 351) or borderline tumors (n = 66) were selected for primary debulking surgery from January 2008 to July 2013. At an MDT meeting, women were allocated into 3 groups named "pre-COVA" 1 to 3...... classifying the expected extent of the primary surgery and need for postoperative care. On the basis of the operative procedures performed, women were allocated into 1 of the 3 corresponding COVA 1 to 3 groups. The outcome measure was the predictive value of the pre-COVA score compared with the actual COVA......-COVA classification predicted the actual COVA group in 79 (49%) FIGO stages I to IIIB and in 85 (45%) FIGO stages IIIC to IV. Conclusions The COVA classification system is a simple and useful tool in the MDT setting where specialists make treatment decisions based on advanced technology. The use of pre...

  7. Assessment of fatty degeneration of the gluteal muscles in patients with THA using MRI: reliability and accuracy of the Goutallier and quartile classification systems.

    Science.gov (United States)

    Engelken, Florian; Wassilew, Georgi I; Köhlitz, Torsten; Brockhaus, Sebastian; Hamm, Bernd; Perka, Carsten; Diederichs, und Gerd

    2014-01-01

    The purpose of this study was to quantify the performance of the Goutallier classification for assessing fatty degeneration of the gluteus muscles from magnetic resonance (MR) images and to compare its performance to a newly proposed system. Eighty-four hips with clinical signs of gluteal insufficiency and 50 hips from asymptomatic controls were analyzed using a standard classification system (Goutallier) and a new scoring system (Quartile). Interobserver reliability and intraobserver repeatability were determined, and accuracy was assessed by comparing readers' scores with quantitative estimates of the proportion of intramuscular fat based on MR signal intensities (gold standard). The existing Goutallier classification system and the new Quartile system performed equally well in assessing fatty degeneration of the gluteus muscles, both showing excellent levels of interrater and intrarater agreement. While the Goutallier classification system has the advantage of being widely known, the benefit of the Quartile system is that it is based on more clearly defined grades of fatty degeneration. Copyright © 2014 Elsevier Inc. All rights reserved.

  8. Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

    Science.gov (United States)

    Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

    2015-06-01

    Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Reliability and Validity of the Sensory Component of the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI): A Systematic Review

    Science.gov (United States)

    Hales, M.; Biros, E.

    2015-01-01

    Background: Since 1982, the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) has been used to classify sensation of spinal cord injury (SCI) through pinprick and light touch scores. The absence of proprioception, pain, and temperature within this scale creates questions about its validity and accuracy. Objectives: To assess whether the sensory component of the ISNCSCI represents a reliable and valid measure of classification of SCI. Methods: A systematic review of studies examining the reliability and validity of the sensory component of the ISNCSCI published between 1982 and February 2013 was conducted. The electronic databases MEDLINE via Ovid, CINAHL, PEDro, and Scopus were searched for relevant articles. A secondary search of reference lists was also completed. Chosen articles were assessed according to the Oxford Centre for Evidence-Based Medicine hierarchy of evidence and critically appraised using the McMasters Critical Review Form. A statistical analysis was conducted to investigate the variability of the results given by reliability studies. Results: Twelve studies were identified: 9 reviewed reliability and 3 reviewed validity. All studies demonstrated low levels of evidence and moderate critical appraisal scores. The majority of the articles (~67%; 6/9) assessing the reliability suggested that training was positively associated with better posttest results. The results of the 3 studies that assessed the validity of the ISNCSCI scale were confounding. Conclusions: Due to the low to moderate quality of the current literature, the sensory component of the ISNCSCI requires further revision and investigation if it is to be a useful tool in clinical trials. PMID:26363591

  10. Can we improve accuracy and reliability of MRI interpretation in children with optic pathway glioma? Proposal for a reproducible imaging classification

    Energy Technology Data Exchange (ETDEWEB)

    Lambron, Julien; Frampas, Eric; Toulgoat, Frederique [University Hospital, Department of Radiology, Nantes (France); Rakotonjanahary, Josue [University Hospital, Department of Pediatric Oncology, Angers (France); University Paris Diderot, INSERM CIE5 Robert Debre Hospital, Assistance Publique-Hopitaux de Paris (AP-HP), Paris (France); Loisel, Didier [University Hospital, Department of Radiology, Angers (France); Carli, Emilie de; Rialland, Xavier [University Hospital, Department of Pediatric Oncology, Angers (France); Delion, Matthieu [University Hospital, Department of Neurosurgery, Angers (France)

    2016-02-15

    Magnetic resonance (MR) images from children with optic pathway glioma (OPG) are complex. We initiated this study to evaluate the accuracy of MR imaging (MRI) interpretation and to propose a simple and reproducible imaging classification for MRI. We randomly selected 140 MRIs from among 510 MRIs performed on 104 children diagnosed with OPG in France from 1990 to 2004. These images were reviewed independently by three radiologists (F.T., 15 years of experience in neuroradiology; D.L., 25 years of experience in pediatric radiology; and J.L., 3 years of experience in radiology) using a classification derived from the Dodge and modified Dodge classifications. Intra- and interobserver reliabilities were assessed using the Bland-Altman method and the kappa coefficient. These reviews allowed the definition of reliable criteria for MRI interpretation. The reviews showed intraobserver variability and large discrepancies among the three radiologists (kappa coefficient varying from 0.11 to 1). These variabilities were too large for the interpretation to be considered reproducible over time or among observers. A consensual analysis, taking into account all observed variabilities, allowed the development of a definitive interpretation protocol. Using this revised protocol, we observed consistent intra- and interobserver results (kappa coefficient varying from 0.56 to 1). The mean interobserver difference for the solid portion of the tumor with contrast enhancement was 0.8 cm{sup 3} (limits of agreement = -16 to 17). We propose simple and precise rules for improving the accuracy and reliability of MRI interpretation for children with OPG. Further studies will be necessary to investigate the possible prognostic value of this approach. (orig.)

  11. Nottingham Prognostic Index in Triple-Negative Breast Cancer: a reliable prognostic tool?

    International Nuclear Information System (INIS)

    Albergaria, André; Ricardo, Sara; Milanezi, Fernanda; Carneiro, Vítor; Amendoeira, Isabel; Vieira, Daniella; Cameselle-Teijeiro, Jorge; Schmitt, Fernando

    2011-01-01

    A breast cancer prognostic tool should ideally be applicable to all types of invasive breast lesions. A number of studies have shown histopathological grade to be an independent prognostic factor in breast cancer, adding prognostic power to nodal stage and tumour size. The Nottingham Prognostic Index has been shown to accurately predict patient outcome in stratified groups with a follow-up period of 15 years after primary diagnosis of breast cancer. Clinically, breast tumours that lack the expression of Oestrogen Receptor, Progesterone Receptor and Human Epidermal growth factor Receptor 2 (HER2) are identified as presenting a 'triple-negative' phenotype or as triple-negative breast cancers. These poor outcome tumours represent an easily recognisable prognostic group of breast cancer with aggressive behaviour that currently lack the benefit of available systemic therapy. There are conflicting results on the prevalence of lymph node metastasis at the time of diagnosis in triple-negative breast cancer patients but it is currently accepted that triple-negative breast cancer does not metastasize to axillary nodes and bones as frequently as the non-triple-negative carcinomas, favouring instead, a preferentially haematogenous spread. Hypothetically, this particular tumour dissemination pattern would impair the reliability of using Nottingham Prognostic Index as a tool for triple-negative breast cancer prognostication. The present study tested the effectiveness of the Nottingham Prognostic Index in stratifying breast cancer patients of different subtypes with special emphasis in a triple-negative breast cancer patient subset versus non- triple-negative breast cancer. We demonstrated that besides the fact that TNBC disseminate to axillary lymph nodes as frequently as luminal or HER2 tumours, we also showed that TNBC are larger in size compared with other subtypes and almost all grade 3. Additionally, survival curves demonstrated that these prognostic factors are

  12. The Reliability and Validity of Prostate Cancer Fatalism Inventory in Turkish Language.

    Science.gov (United States)

    Aydoğdu, Nihal Gördes; Çapık, Cantürk; Ersin, Fatma; Kissal, Aygul; Bahar, Zuhal

    2017-10-01

    This study aimed to conduct the reliability and validity study of the Prostate Cancer Fatalism Inventory in Turkish language. The study carried out in methodological type and consisted of 171 men. The ages of the participants ranged between 40 and 82. The content validity index was determined to be 0.80, Kaiser-Meyer-Olkin value 0.825, Bartlett's test X 2  = 750.779 and p = 0.000. Then the principal component analysis was applied to the 15-item inventory. The inventory consisted of one dimension, and the load factors were over 0.30 for all items. The explained variance of the inventory was found 33.3 %. The Kuder-Richardson-20 coefficient was determined to be 0.849 and the item-total correlations ranged between 0.335 and 0.627. The Prostate Cancer Fatalism Inventory was a reliable and valid measurement tool in Turkish language. Integrating psychological strategies for prostate cancer screening may be required to strengthen the positive effects of nursing education.

  13. ParSel: Parallel Selection of Micro-RNAs for Survival Classification in Cancers.

    Science.gov (United States)

    Sinha, Debajyoti; Sengupta, Debarka; Bandyopadhyay, Sanghamitra

    2017-07-01

    It is known that tumor micro-RNAs (miRNA) can define patient survival and treatment response. We present a framework to identify miRNAs which are predictive of cancer survival. The framework attempts to rank the miRNAs by exploring their collaborative role in gene regulation. Our approach tests a significantly large number of combinatorial cases leveraging parallel computation. We carefully avoided parametric assumptions involved in evaluations of miRNA expressions but used rigorous statistical computation to assign an importance score to a miRNA. Experimental results on three cancer types namely, KIRC, OV and GBM verify that the top ranked miRNAs obtained using the proposed framework produce better classification accuracy as compared to some best practice variable selection methods. Some of these top ranked miRNA are also known to be associated with related diseases. © 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Improving breast cancer classification with mammography, supported on an appropriate variable selection analysis

    Science.gov (United States)

    Pérez, Noel; Guevara, Miguel A.; Silva, Augusto

    2013-02-01

    This work addresses the issue of variable selection within the context of breast cancer classification with mammography. A comprehensive repository of feature vectors was used including a hybrid subset gathering image-based and clinical features. It aimed to gather experimental evidence of variable selection in terms of cardinality, type and find a classification scheme that provides the best performance over the Area Under Receiver Operating Characteristics Curve (AUC) scores using the ranked features subset. We evaluated and classified a total of 300 subsets of features formed by the application of Chi-Square Discretization, Information-Gain, One-Rule and RELIEF methods in association with Feed-Forward Backpropagation Neural Network (FFBP), Support Vector Machine (SVM) and Decision Tree J48 (DTJ48) Machine Learning Algorithms (MLA) for a comparative performance evaluation based on AUC scores. A variable selection analysis was performed for Single-View Ranking and Multi-View Ranking groups of features. Features subsets representing Microcalcifications (MCs), Masses and both MCs and Masses lesions achieved AUC scores of 0.91, 0.954 and 0.934 respectively. Experimental evidence demonstrated that classification performance was improved by combining image-based and clinical features. The most important clinical and image-based features were StromaDistortion and Circularity respectively. Other less important but worth to use due to its consistency were Contrast, Perimeter, Microcalcification, Correlation and Elongation.

  15. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Maolong Xi

    2016-01-01

    Full Text Available This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO for cancer feature gene selection, coupling support vector machine (SVM for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV. Finally, the BQPSO coupling SVM (BQPSO/SVM, binary PSO coupling SVM (BPSO/SVM, and genetic algorithm coupling SVM (GA/SVM are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms.

  16. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

    Science.gov (United States)

    Sun, Jun; Liu, Li; Fan, Fangyun; Wu, Xiaojun

    2016-01-01

    This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO) for cancer feature gene selection, coupling support vector machine (SVM) for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV). Finally, the BQPSO coupling SVM (BQPSO/SVM), binary PSO coupling SVM (BPSO/SVM), and genetic algorithm coupling SVM (GA/SVM) are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms. PMID:27642363

  17. Ultrasonographic characteristics and BI-RADS-US classification of BRCA1 mutation-associated breast cancer in Guangxi, China.

    Science.gov (United States)

    Li, Cheng; Liu, Junjie; Wang, Sida; Chen, Yuanyuan; Yuan, Zhigang; Zeng, Jian; Li, Zhixian

    2015-01-01

    To retrospectively analyze and compare the ultrasonographic characteristics and BI-RADS-US classification between patients with BRCA1 mutation-associated breast cancer and those without BRCA1 gene mutation in Guangxi, China. The study was performed in 36 lesions from 34 BRCA1 mutation-associated breast cancer patients. A total of 422 lesions from 422 breast cancer patients without BRCA1 mutations served as control group. The comparison of the ultrasonographic features and BI-RADS-US classification between two the groups were reviewed. More complex inner echo was disclosed in BRCA1 mutation-associated breast cancer patients (x(2) = 4.741, P = 0.029). The BI-RADS classification of BRCA1 mutation-associated breast cancer was lower (U = 6094.0, P = 0.022). BRCA1 mutation-associated breast cancer frequently displays as microlobulated margin and complex echo. It also shows more benign characteristics in morphology, and the BI-RADS classification is prone to be underestimated.

  18. The Functional Living Index-Cancer is a reliable and valid instrument in Chinese cancer patients.

    Science.gov (United States)

    Fong, Daniel Y T; Lee, Alvina H K; Tung, Stewart Y; Wong, Janet Y H; Chan, Y M; Goh, Cynthia R; Cheung, Y B

    2014-02-01

    To evaluate the linguistic and psychometric properties of the Functional Living Index-Cancer (FLIC) in assessing the quality of life of Chinese cancer patients. The English FLIC was translated into Traditional Chinese by the standard forward-backward procedure. After cognitive debriefing, a Traditional Chinese FLIC was administered to 500 cancer patients in a major public hospital in Hong Kong. Of which, 200 were invited to complete the questionnaire in 2 weeks. To identify a scale structure appropriate to Chinese, exploratory and confirmatory factor analyses were performed on two randomly split halves of the sample. We identified five scales of the Traditional Chinese FLIC which assess the physical, psychological, hardship, nausea and social aspects. These five scales and the overall scale demonstrated satisfactory fit and had the alpha coefficient ranged from 0.68 to 0.92. The intra-class correlation coefficient ranged from 0.67 to 0.88. In addition, all FLIC scales were negatively associated with the Eastern Cooperative Oncology Group performance status and, also except for the psychological scale, had lower scores in patients who were treated by chemotherapy. The Traditional Chinese FLIC is an appropriate health indicator for Chinese cancer patients.

  19. Actionable gene-based classification toward precision medicine in gastric cancer

    Directory of Open Access Journals (Sweden)

    Hiroshi Ichikawa

    2017-10-01

    Full Text Available Abstract Background Intertumoral heterogeneity represents a significant hurdle to identifying optimized targeted therapies in gastric cancer (GC. To realize precision medicine for GC patients, an actionable gene alteration-based molecular classification that directly associates GCs with targeted therapies is needed. Methods A total of 207 Japanese patients with GC were included in this study. Formalin-fixed, paraffin-embedded (FFPE tumor tissues were obtained from surgical or biopsy specimens and were subjected to DNA extraction. We generated comprehensive genomic profiling data using a 435-gene panel including 69 actionable genes paired with US Food and Drug Administration-approved targeted therapies, and the evaluation of Epstein-Barr virus (EBV infection and microsatellite instability (MSI status. Results Comprehensive genomic sequencing detected at least one alteration of 435 cancer-related genes in 194 GCs (93.7% and of 69 actionable genes in 141 GCs (68.1%. We classified the 207 GCs into four The Cancer Genome Atlas (TCGA subtypes using the genomic profiling data; EBV (N = 9, MSI (N = 17, chromosomal instability (N = 119, and genomically stable subtype (N = 62. Actionable gene alterations were not specific and were widely observed throughout all TCGA subtypes. To discover a novel classification which more precisely selects candidates for targeted therapies, 207 GCs were classified using hypermutated phenotype and the mutation profile of 69 actionable genes. We identified a hypermutated group (N = 32, while the others (N = 175 were sub-divided into six clusters including five with actionable gene alterations: ERBB2 (N = 25, CDKN2A, and CDKN2B (N = 10, KRAS (N = 10, BRCA2 (N = 9, and ATM cluster (N = 12. The clinical utility of this classification was demonstrated by a case of unresectable GC with a remarkable response to anti-HER2 therapy in the ERBB2 cluster. Conclusions This actionable gene

  20. Collection and classification of human reliability data for use in probabilistic safety assessments. Final report of a co-ordinated research programme 1995-1998

    International Nuclear Information System (INIS)

    1998-10-01

    One of the most important lessons from abnormal events in NPPs is that they often result from incorrect human action. The awareness of the importance of human factors and human reliability has increased significantly over 10-15 years primarily owing to the fact that some major incidents (nuclear or non-nuclear) have had significant human error contributions. Each of these incidents have revealed different types of human errors, some of which were not generally recognized prior to the incident. The analysis of these events led to wide recognition of the fact that more information about human actions and errors is needed to improve the safety and operation of nuclear power plants. At the same time, the need or proper human reliability data was recognised in view of probabilistic safety assessment (PSA). No PSA study can be regarded as complete and accurate without adequate incorporation of human reliability analysis (HRA). In order to support incorporation of human reliability data into PSA the IAEA established a coordinated research programme with the objective to develop a common data base structure for human errors that might have important contributions to risk in different types of reactors. This report is a product of four years of coordinated research and describes the data collection and classification schemes currently in use in Member States as well as an outlook into future, discussing what types of data might be needed to support the new improved HRA methods which are currently under development

  1. [Molecular classification of breast cancer patients obtained through the technique of chromogenic in situ hybridization (CISH)].

    Science.gov (United States)

    Fernández, Angel; Reigosa, Aldo

    2013-12-01

    Breast cancer is a heterogeneous disease composed of a growing number of biological subtypes, with substantial variability of the disease progression within each category. The aim of this research was to classify the samples object of study according to the molecular classes of breast cancer: luminal A, luminal B, HER2 and triple negative, as a result of the state of HER2 amplification obtained by the technique of chromogenic in situ hybridization (CISH). The sample consisted of 200 biopsies fixed in 10% formalin, processed by standard techniques up to paraffin embedding, corresponding to patients diagnosed with invasive ductal carcinoma of the breast. These biopsies were obtained from patients from private practice and the Institute of Oncology "Dr. Miguel Pérez Carreño", for immunohistochemistry (IHC) of hormone receptors and HER2 made in the Hospital Metropolitano del Norte, Valencia, Venezuela. The molecular classification of the patient's tumors considering the expression of estrogen and progesterone receptors by IHC and HER2 amplification by CISH, allowed those cases originally classified as unknown, since they had an indeterminate (2+) outcome for HER2 expression by IHC, to be grouped into the different molecular classes. Also, this classification permitted that some cases, initially considered as belonging to a molecular class, were assigned to another class, after the revaluation of the HER2 status by CISH.

  2. Does the use of the 2009 FIGO classification of endometrial cancer impact on indications of the sentinel node biopsy?

    Directory of Open Access Journals (Sweden)

    Ballester Marcos

    2010-08-01

    Full Text Available Abstract Background Lymphadenectomy is debated in early stages endometrial cancer. Moreover, a new FIGO classification of endometrial cancer, merging stages IA and IB has been recently published. Therefore, the aims of the present study was to evaluate the relevance of the sentinel node (SN procedure in women with endometrial cancer and to discuss whether the use of the 2009 FIGO classification could modify the indications for SN procedure. Methods Eighty-five patients with endometrial cancer underwent the SN procedure followed by pelvic lymphadenectomy. SNs were detected with a dual or single labelling method in 74 and 11 cases, respectively. All SNs were analysed by both H&E staining and immunohistochemistry. Presumed stage before surgery was assessed for all patients based on MR imaging features using the 1988 FIGO classification and the 2009 FIGO classification. Results An SN was detected in 88.2% of cases (75/85 women. Among the fourteen patients with lymph node metastases one-half were detected by serial sectioning and immunohistochemical analysis. There were no false negative case. Using the 1988 FIGO classification and the 2009 FIGO classification, the correlation between preoperative MRI staging and final histology was moderate with Kappa = 0.24 and Kappa = 0.45, respectively. None of the patients with grade 1 endometrioid carcinoma on biopsy and IA 2009 FIGO stage on MR imaging exhibited positive SN. In patients with grade 2-3 endometrioid carcinoma and stage IA on MR imaging, the rate of positive SN reached 16.6% with an incidence of micrometastases of 50%. Conclusions The present study suggests that sentinel node biopsy is an adequate technique to evaluate lymph node status. The use of the 2009 FIGO classification increases the accuracy of MR imaging to stage patients with early stages of endometrial cancer and contributes to clarify the indication of SN biopsy according to tumour grade and histological type.

  3. Does the use of the 2009 FIGO classification of endometrial cancer impact on indications of the sentinel node biopsy?

    International Nuclear Information System (INIS)

    Ballester, Marcos; Koskas, Martin; Coutant, Charles; Chéreau, Elisabeth; Seror, Jeremy; Rouzier, Roman; Daraï, Emile

    2010-01-01

    Lymphadenectomy is debated in early stages endometrial cancer. Moreover, a new FIGO classification of endometrial cancer, merging stages IA and IB has been recently published. Therefore, the aims of the present study was to evaluate the relevance of the sentinel node (SN) procedure in women with endometrial cancer and to discuss whether the use of the 2009 FIGO classification could modify the indications for SN procedure. Eighty-five patients with endometrial cancer underwent the SN procedure followed by pelvic lymphadenectomy. SNs were detected with a dual or single labelling method in 74 and 11 cases, respectively. All SNs were analysed by both H&E staining and immunohistochemistry. Presumed stage before surgery was assessed for all patients based on MR imaging features using the 1988 FIGO classification and the 2009 FIGO classification. An SN was detected in 88.2% of cases (75/85 women). Among the fourteen patients with lymph node metastases one-half were detected by serial sectioning and immunohistochemical analysis. There were no false negative case. Using the 1988 FIGO classification and the 2009 FIGO classification, the correlation between preoperative MRI staging and final histology was moderate with Kappa = 0.24 and Kappa = 0.45, respectively. None of the patients with grade 1 endometrioid carcinoma on biopsy and IA 2009 FIGO stage on MR imaging exhibited positive SN. In patients with grade 2-3 endometrioid carcinoma and stage IA on MR imaging, the rate of positive SN reached 16.6% with an incidence of micrometastases of 50%. The present study suggests that sentinel node biopsy is an adequate technique to evaluate lymph node status. The use of the 2009 FIGO classification increases the accuracy of MR imaging to stage patients with early stages of endometrial cancer and contributes to clarify the indication of SN biopsy according to tumour grade and histological type

  4. Structural and reliability analysis of quality of relationship index in cancer patients.

    Science.gov (United States)

    Cousson-Gélie, Florence; de Chalvron, Stéphanie; Zozaya, Carole; Lafaye, Anaïs

    2013-01-01

    Among psychosocial factors affecting emotional adjustment and quality of life, social support is one of the most important and widely studied in cancer patients, but little is known about the perception of support in specific significant relationships in patients with cancer. This study examined the psychometric properties of the Quality of Relationship Inventory (QRI) by evaluating its factor structure and its convergent and discriminant validity in a sample of cancer patients. A total of 388 patients completed the QRI. Convergent validity was evaluated by testing the correlations between the QRI subscales and measures of general social support, anxiety and depression symptoms. Discriminant validity was examined by testing group comparison. The QRI's longitudinal invariance across time was also tested. Principal axis factor analysis with promax rotation identified three factors accounting for 42.99% of variance: perceived social support, depth, and interpersonal conflict. Estimates of reliability with McDonald's ω coefficient were satisfactory for all the QRI subscales (ω ranging from 0.75 - 0.85). Satisfaction from general social support was negatively correlated with the interpersonal conflict subscale and positively with the depth subscale. The interpersonal conflict and social support scales were correlated with depression and anxiety scores. We also found a relative stability of QRI subscales (measured 3 months after the first evaluation) and differences between partner status and gender groups. The Quality of Relationship Inventory is a valid tool for assessing the quality of social support in a particular relationship with cancer patients.

  5. Is Preoperative Neutrophil Lymphocyte Ratio a Reliable Prognostic Parameter for Localized Prostate Cancer?

    Directory of Open Access Journals (Sweden)

    Tümay İpekçi

    2017-12-01

    Full Text Available Objective: In spite of all efforts, prostate cancer is still the 2nd highest cause of cancer-related deaths in men. For this reason new developments are needed in diagnosis, treatment and follow-up of prostate cancer. Neutrophil/lymphocyte (N/L ratio is a cheap and effective parameter used for research into many solid tumors; but there are not enough studies on the reliability of this parameter in prostate cancer. In this study we researched the efficacy of N/L ratio in localized prostate cancer. Materials and Methods: Between March 9, 2012 and April 23, 2017, the data of 140 patients who underwent radical prostatectomy with localized prostate cancer were screened retrospectively. The patients’ ages, preoperative prostate specific antigen (PSA and N/L ratio, pathologic stage, pathologic Gleason score, tumor volume, lymph node involvement, surgical margin positivity and presence or absence of 3rd month biochemical recurrence were noted. The correlations between N/L ratio with age, PSA, pathologic parameters, surgical margin positivity and biochemical recurrence were investigated. Results: The mean age of patients was 63.0±5.9 years, mean PSA value was 10.8±8.5 ng/mL and mean N/L ratio was 2.5±1.9. There was no correlation found between N/L ratio and PSA, pathologic stage, Gleason score, lymph node involvement, tumor volume, surgical margin positivity and biochemical recurrence (p>0.05. Conclusion: In our study investigating 140 patients with localized prostate cancer, we did not identify any correlation between N/L ratio and PSA, surgical stage and Gleason score, surgical margin positivity, and 3rd month biochemical recurrence. When the literature is investigated, it appears that N/L ratio is effective for metastatic prostate cancer. To provide a more accurate judgment of the role of N/L ratio in localized prostate cancer, there is a need for new studies with broader patient series.

  6. Are preoperative histology and MRI useful for classification of endometrial cancer risk?

    International Nuclear Information System (INIS)

    Body, Noemie; Lavoué, Vincent; De Kerdaniel, Olivier; Foucher, Fabrice; Henno, Sébastien; Cauchois, Aurélie; Laviolle, Bruno; Leblanc, Marc; Levêque, Jean

    2016-01-01

    The 2010 guidelines of the French National Cancer Institute (INCa) classify patients with endometrial cancer into three risk groups for lymph node invasion and recurrence on the basis of MRI and histological analysis of an endometrial specimen obtained preoperatively. The classification guides therapeutic choices, which may include pelvic and/or para-aortic lymphadenectomy. The purpose of this study was to evaluate the diagnostic performance of preoperative assessment to help identify intermediate- or high-risk patients requiring lymphadenectomy. The study included all patients who underwent surgery for endometrial cancer between January 2010 and December 2013 at either Rennes University Hospital or Vannes Regional Hospital. The criteria for eligibility included a preoperative assessment with MRI and histological examination of an endometrial sample. A histological comparison was made between the preoperative and surgical specimens. Among the 91 patients who underwent a full preoperative assessment, the diagnosis of intermediate- or high-risk endometrial cancer was established by MRI and histology with a sensitivity of 70 %, specificity of 82 %, positive predictive value (PPV) of 87 %, negative predictive value (NPV) of 61 %, positive likelihood ratio (LR+) of 3.8 and negative likelihood ratio (LR-) of 0.3. The risk group was underestimated in 32 % of patients and overestimated in 7 % of patients. MRI underestimated endometrial cancer stage in 20 % of cases, while endometrial sampling underestimated the histological type in 4 % of cases and the grade in 9 % of cases. The preoperative assessment overestimated or underestimated the risk of recurrence in nearly 40 % of cases, with errors in lesion type, grade or stage. Erroneous preoperative risk assessment leads to suboptimal initial surgical management of patients with endometrial cancer

  7. Collection and classification of human error and human reliability data from Indian nuclear power plants for use in PSA

    International Nuclear Information System (INIS)

    Subramaniam, K.; Saraf, R.K.; Sanyasi Rao, V.V.S.; Venkat Raj, V.; Venkatraman, R.

    2000-01-01

    Complex systems such as NPPs involve a large number of Human Interactions (HIs) in every phase of plant operations. Human Reliability Analysis (HRA) in the context of a PSA, attempts to model the HIs and evaluate/predict their impact on safety and reliability using human error/human reliability data. A large number of HRA techniques have been developed for modelling and integrating HIs into PSA but there is a significant lack of HAR data. In the face of insufficient data, human reliability analysts have had to resort to expert judgement methods in order to extend the insufficient data sets. In this situation, the generation of data from plant operating experience assumes importance. The development of a HRA data bank for Indian nuclear power plants was therefore initiated as part of the programme of work on HRA. Later, with the establishment of the coordinated research programme (CRP) on collection of human reliability data and use in PSA by IAEA in 1994-95, the development was carried out under the aegis of the IAEA research contract No. 8239/RB. The work described in this report covers the activities of development of a data taxonomy and a human error reporting form (HERF) based on it, data structuring, review and analysis of plant event reports, collection of data on human errors, analysis of the data and calculation of human error probabilities (HEPs). Analysis of plant operating experience does yield a good amount of qualitative data but obtaining quantitative data on human reliability in the form of HEPs is seen to be more difficult. The difficulties have been highlighted and some ways to bring about improvements in the data situation have been discussed. The implementation of a data system for HRA is described and useful features that can be incorporated in future systems are also discussed. (author)

  8. BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data.

    Science.gov (United States)

    Guo, Yang; Liu, Shuhui; Li, Zhanhuai; Shang, Xuequn

    2018-04-11

    The classification of cancer subtypes is of great importance to cancer disease diagnosis and therapy. Many supervised learning approaches have been applied to cancer subtype classification in the past few years, especially of deep learning based approaches. Recently, the deep forest model has been proposed as an alternative of deep neural networks to learn hyper-representations by using cascade ensemble decision trees. It has been proved that the deep forest model has competitive or even better performance than deep neural networks in some extent. However, the standard deep forest model may face overfitting and ensemble diversity challenges when dealing with small sample size and high-dimensional biology data. In this paper, we propose a deep learning model, so-called BCDForest, to address cancer subtype classification on small-scale biology datasets, which can be viewed as a modification of the standard deep forest model. The BCDForest distinguishes from the standard deep forest model with the following two main contributions: First, a named multi-class-grained scanning method is proposed to train multiple binary classifiers to encourage diversity of ensemble. Meanwhile, the fitting quality of each classifier is considered in representation learning. Second, we propose a boosting strategy to emphasize more important features in cascade forests, thus to propagate the benefits of discriminative features among cascade layers to improve the classification performance. Systematic comparison experiments on both microarray and RNA-Seq gene expression datasets demonstrate that our method consistently outperforms the state-of-the-art methods in application of cancer subtype classification. The multi-class-grained scanning and boosting strategy in our model provide an effective solution to ease the overfitting challenge and improve the robustness of deep forest model working on small-scale data. Our model provides a useful approach to the classification of cancer subtypes

  9. Malingering in Toxic Exposure. Classification Accuracy of Reliable Digit Span and WAIS-III Digit Span Scaled Scores

    Science.gov (United States)

    Greve, Kevin W.; Springer, Steven; Bianchini, Kevin J.; Black, F. William; Heinly, Matthew T.; Love, Jeffrey M.; Swift, Douglas A.; Ciota, Megan A.

    2007-01-01

    This study examined the sensitivity and false-positive error rate of reliable digit span (RDS) and the WAIS-III Digit Span (DS) scaled score in persons alleging toxic exposure and determined whether error rates differed from published rates in traumatic brain injury (TBI) and chronic pain (CP). Data were obtained from the files of 123 persons…

  10. The Reliability of Classification Decisions for the Furtado-Gallagher Computerized Observational Movement Pattern Assessment System--FG-COMPASS

    Science.gov (United States)

    Furtado, Ovande, Jr.; Gallagher, Jere D.

    2012-01-01

    Mastery of fundamental movement skills (FMS) is an important factor in preventing weight gain and increasing physical activity. To master FMS, performance evaluation is necessary. In this study, we investigated the reliability of a new observational assessment tool. In Phase I, 110 video clips of children performing five locomotor, and six…

  11. Intra- and interrater reliability of the Chicago Classification of achalasia subtypes in pediatric high-resolution esophageal manometry (HRM) recordings

    NARCIS (Netherlands)

    Singendonk, M. M. J.; Rosen, R.; Oors, J.; Rommel, N.; van Wijk, M. P.; Benninga, M. A.; Nurko, S.; Omari, T. I.

    2017-01-01

    BackgroundSubtyping achalasia by high-resolution manometry (HRM) is clinically relevant as response to therapy and prognosis have shown to vary accordingly. The aim of this study was to assess inter- and intrarater reliability of diagnosing achalasia and achalasia subtyping in children using the

  12. Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study.

    Science.gov (United States)

    Vidić, Igor; Egnell, Liv; Jerome, Neil P; Teruel, Jose R; Sjøbakk, Torill E; Østlie, Agnes; Fjøsne, Hans E; Bathen, Tone F; Goa, Pål Erik

    2018-05-01

    Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentially be improved by machine learning. To evaluate classification of malignant and benign tumors and breast cancer subtypes using support vector machine (SVM). Prospective. Fifty-one patients with benign (n = 23) and malignant (n = 28) breast tumors (26 ER+, whereof six were HER2+). Patients were imaged with DW-MRI (3T) using twice refocused spin-echo echo-planar imaging with echo time / repetition time (TR/TE) = 9000/86 msec, 90 × 90 matrix size, 2 × 2 mm in-plane resolution, 2.5 mm slice thickness, and 13 b-values. Apparent diffusion coefficient (ADC), relative enhanced diffusivity (RED), and the intravoxel incoherent motion (IVIM) parameters diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The histogram properties (median, mean, standard deviation, skewness, kurtosis) were used as features in SVM (10-fold cross-validation) for differentiation of lesions and subtyping. Accuracies of the SVM classifications were calculated to find the combination of features with highest prediction accuracy. Mann-Whitney tests were performed for univariate comparisons. For benign versus malignant tumors, univariate analysis found 11 histogram properties to be significant differentiators. Using SVM, the highest accuracy (0.96) was achieved from a single feature (mean of RED), or from three feature combinations of IVIM or ADC. Combining features from all models gave perfect classification. No single feature predicted HER2 status of ER + tumors (univariate or SVM), although high accuracy (0.90) was achieved with SVM combining several features. Importantly, these features had to include higher-order statistics (kurtosis and skewness), indicating the importance to account for heterogeneity. Our

  13. How to use the ENEA data bank for the classification and reliability processing of fast reactor component event data

    International Nuclear Information System (INIS)

    Righini, R.

    1987-01-01

    This report describes the input and inquiry procedures for the Data Bank set-up by ENEA for reliability studies on fast reactors. With reference to the structure and to the codes to be applied in the data entry and in the inquiry, see Report (2) in references. The data contained into the Bank are absolutely confidential. The input and inquiry procedures describes in this report may be applied only by the user who have previously specified the suitable password

  14. MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

    Energy Technology Data Exchange (ETDEWEB)

    Young, M; Craft, D [Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States)

    2016-06-15

    Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchical clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve

  15. Finding Combination of Features from Promoter Regions for Ovarian Cancer-related Gene Group Classification

    KAUST Repository

    Olayan, Rawan S.

    2012-12-01

    In classification problems, it is always important to use the suitable combination of features that will be employed by classifiers. Generating the right combination of features usually results in good classifiers. In the situation when the problem is not well understood, data items are usually described by many features in the hope that some of these may be the relevant or most relevant ones. In this study, we focus on one such problem related to genes implicated in ovarian cancer (OC). We try to recognize two important OC-related gene groups: oncogenes, which support the development and progression of OC, and oncosuppressors, which oppose such tendencies. For this, we use the properties of promoters of these genes. We identified potential “regulatory features” that characterize OC-related oncogenes and oncosuppressors promoters. In our study, we used 211 oncogenes and 39 oncosuppressors. For these, we identified 538 characteristic sequence motifs from their promoters. Promoters are annotated by these motifs and derived feature vectors used to develop classification models. We made a comparison of a number of classification models in their ability to distinguish oncogenes from oncosuppressors. Based on 10-fold cross-validation, the resultant model was able to separate the two classes with sensitivity of 96% and specificity of 100% with the complete set of features. Moreover, we developed another recognition model where we attempted to distinguish oncogenes and oncosuppressors as one group from other OC-related genes. That model achieved accuracy of 82%. We believe that the results of this study will help in discovering other OC-related oncogenes and oncosuppressors not identified as yet.

  16. Finding Combination of Features from Promoter Regions for Ovarian Cancer-related Gene Group Classification

    KAUST Repository

    Olayan, Rawan S.

    2012-01-01

    In classification problems, it is always important to use the suitable combination of features that will be employed by classifiers. Generating the right combination of features usually results in good classifiers. In the situation when the problem is not well understood, data items are usually described by many features in the hope that some of these may be the relevant or most relevant ones. In this study, we focus on one such problem related to genes implicated in ovarian cancer (OC). We try to recognize two important OC-related gene groups: oncogenes, which support the development and progression of OC, and oncosuppressors, which oppose such tendencies. For this, we use the properties of promoters of these genes. We identified potential “regulatory features” that characterize OC-related oncogenes and oncosuppressors promoters. In our study, we used 211 oncogenes and 39 oncosuppressors. For these, we identified 538 characteristic sequence motifs from their promoters. Promoters are annotated by these motifs and derived feature vectors used to develop classification models. We made a comparison of a number of classification models in their ability to distinguish oncogenes from oncosuppressors. Based on 10-fold cross-validation, the resultant model was able to separate the two classes with sensitivity of 96% and specificity of 100% with the complete set of features. Moreover, we developed another recognition model where we attempted to distinguish oncogenes and oncosuppressors as one group from other OC-related genes. That model achieved accuracy of 82%. We believe that the results of this study will help in discovering other OC-related oncogenes and oncosuppressors not identified as yet.

  17. Cancer cell detection and classification using transformation invariant template learning methods

    International Nuclear Information System (INIS)

    Talware, Rajendra; Abhyankar, Aditya

    2011-01-01

    In traditional cancer cell detection, pathologists examine biopsies to make diagnostic assessments, largely based on cell morphology and tissue distribution. The process of image acquisition is very much subjective and the pattern undergoes unknown or random transformations during data acquisition (e.g. variation in illumination, orientation, translation and perspective) results in high degree of variability. Transformed Component Analysis (TCA) incorporates a discrete, hidden variable that accounts for transformations and uses the Expectation Maximization (EM) algorithm to jointly extract components and normalize for transformations. Further the TEMPLAR framework developed takes advantage of hierarchical pattern models and adds probabilistic modeling for local transformations. Pattern classification is based on Expectation Maximization algorithm and General Likelihood Ratio Tests (GLRT). Performance of TEMPLAR is certainly improved by defining area of interest on slide a priori. Performance can be further enhanced by making the kernel function adaptive during learning. (author)

  18. Gene Expression Profiles for Predicting Metastasis in Breast Cancer: A Cross-Study Comparison of Classification Methods

    Directory of Open Access Journals (Sweden)

    Mark Burton

    2012-01-01

    Full Text Available Machine learning has increasingly been used with microarray gene expression data and for the development of classifiers using a variety of methods. However, method comparisons in cross-study datasets are very scarce. This study compares the performance of seven classification methods and the effect of voting for predicting metastasis outcome in breast cancer patients, in three situations: within the same dataset or across datasets on similar or dissimilar microarray platforms. Combining classification results from seven classifiers into one voting decision performed significantly better during internal validation as well as external validation in similar microarray platforms than the underlying classification methods. When validating between different microarray platforms, random forest, another voting-based method, proved to be the best performing method. We conclude that voting based classifiers provided an advantage with respect to classifying metastasis outcome in breast cancer patients.

  19. Support vector machine classification and validation of cancer tissue samples using microarray expression data.

    Science.gov (United States)

    Furey, T S; Cristianini, N; Duffy, N; Bednarski, D W; Schummer, M; Haussler, D

    2000-10-01

    DNA microarray experiments generating thousands of gene expression measurements, are being used to gather information from tissue and cell samples regarding gene expression differences that will be useful in diagnosing disease. We have developed a new method to analyse this kind of data using support vector machines (SVMs). This analysis consists of both classification of the tissue samples, and an exploration of the data for mis-labeled or questionable tissue results. We demonstrate the method in detail on samples consisting of ovarian cancer tissues, normal ovarian tissues, and other normal tissues. The dataset consists of expression experiment results for 97,802 cDNAs for each tissue. As a result of computational analysis, a tissue sample is discovered and confirmed to be wrongly labeled. Upon correction of this mistake and the removal of an outlier, perfect classification of tissues is achieved, but not with high confidence. We identify and analyse a subset of genes from the ovarian dataset whose expression is highly differentiated between the types of tissues. To show robustness of the SVM method, two previously published datasets from other types of tissues or cells are analysed. The results are comparable to those previously obtained. We show that other machine learning methods also perform comparably to the SVM on many of those datasets. The SVM software is available at http://www.cs. columbia.edu/ approximately bgrundy/svm.

  20. A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification

    Directory of Open Access Journals (Sweden)

    Wang Lily

    2008-07-01

    Full Text Available Abstract Background Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular signatures on their way toward clinical deployment. Use of the most accurate classification algorithms available for microarray gene expression data is a critical ingredient in order to develop the best possible molecular signatures for patient care. As suggested by a large body of literature to date, support vector machines can be considered "best of class" algorithms for classification of such data. Recent work, however, suggests that random forest classifiers may outperform support vector machines in this domain. Results In the present paper we identify methodological biases of prior work comparing random forests and support vector machines and conduct a new rigorous evaluation of the two algorithms that corrects these limitations. Our experiments use 22 diagnostic and prognostic datasets and show that support vector machines outperform random forests, often by a large margin. Our data also underlines the importance of sound research design in benchmarking and comparison of bioinformatics algorithms. Conclusion We found that both on average and in the majority of microarray datasets, random forests are outperformed by support vector machines both in the settings when no gene selection is performed and when several popular gene selection methods are used.

  1. An Entropy-based gene selection method for cancer classification using microarray data

    Directory of Open Access Journals (Sweden)

    Krishnan Arun

    2005-03-01

    Full Text Available Abstract Background Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of non-redundant but relevant genes is difficult. The selected gene set should be small enough to allow diagnosis even in regular clinical laboratories and ideally identify genes involved in cancer-specific regulatory pathways. Here an entropy-based method is proposed that selects genes related to the different cancer classes while at the same time reducing the redundancy among the genes. Results The present study identifies a subset of features by maximizing the relevance and minimizing the redundancy of the selected genes. A merit called normalized mutual information is employed to measure the relevance and the redundancy of the genes. In order to find a more representative subset of features, an iterative procedure is adopted that incorporates an initial clustering followed by data partitioning and the application of the algorithm to each of the partitions. A leave-one-out approach then selects the most commonly selected genes across all the different runs and the gene selection algorithm is applied again to pare down the list of selected genes until a minimal subset is obtained that gives a satisfactory accuracy of classification. The algorithm was applied to three different data sets and the results obtained were compared to work done by others using the same data sets Conclusion This study presents an entropy-based iterative algorithm for selecting genes from microarray data that are able to classify various cancer sub-types with high accuracy. In addition, the feature set obtained is very compact, that is, the redundancy between genes is reduced to a large extent. This implies that classifiers can be built with a smaller subset of genes.

  2. Reliability of the Dutch-language version of the Communication Function Classification System and its association with language comprehension and method of communication.

    Science.gov (United States)

    Vander Zwart, Karlijn E; Geytenbeek, Joke J; de Kleijn, Maaike; Oostrom, Kim J; Gorter, Jan Willem; Hidecker, Mary Jo Cooley; Vermeulen, R Jeroen

    2016-02-01

    The aims of this study were to determine the intra- and interrater reliability of the Dutch-language version of the Communication Function Classification System (CFCS-NL) and to investigate the association between the CFCS level and (1) spoken language comprehension and (2) preferred method of communication in children with cerebral palsy (CP). Participants were 93 children with CP (50 males, 43 females; mean age 7y, SD 2y 6mo, range 2y 9mo-12y 10mo; unilateral spastic [n=22], bilateral spastic [n=51], dyskinetic [n=15], ataxic [n=3], not specified [n=2]; Gross Motor Function Classification System level I [n=16], II [n=14], III, [n=7], IV [n=24], V [n=31], unknown [n=1]), recruited from rehabilitation centres throughout the Netherlands. Because some centres only contributed to part of the study, different numbers of participants are presented for different aspects of the study. Parents and speech and language therapists (SLTs) classified the communication level using the CFCS. Kappa was used to determine the intra- and interrater reliability. Spearman's correlation coefficient was used to determine the association between CFCS level and spoken language comprehension, and Fisher's exact test was used to examine the association between the CFCS level and method of communication. Interrater reliability of the CFCS-NL between parents and SLTs was fair (r=0.54), between SLTs good (r=0.78), and the intrarater (SLT) reliability very good (r=0.85). The association between the CFCS and spoken language comprehension was strong for SLTs (r=0.63) and moderate for parents (r=0.51). There was a statistically significant difference between the CFCS level and the preferred method of communication of the child (pcommunication in children with CP. Preferably, professionals should classify the child's CFCS level in collaboration with the parents to acquire the most comprehensive information about the everyday communication of the child in various situations both with familiar and

  3. Classification of samples into two or more ordered populations with application to a cancer trial.

    Science.gov (United States)

    Conde, D; Fernández, M A; Rueda, C; Salvador, B

    2012-12-10

    In many applications, especially in cancer treatment and diagnosis, investigators are interested in classifying patients into various diagnosis groups on the basis of molecular data such as gene expression or proteomic data. Often, some of the diagnosis groups are known to be related to higher or lower values of some of the predictors. The standard methods of classifying patients into various groups do not take into account the underlying order. This could potentially result in high misclassification rates, especially when the number of groups is larger than two. In this article, we develop classification procedures that exploit the underlying order among the mean values of the predictor variables and the diagnostic groups by using ideas from order-restricted inference. We generalize the existing methodology on discrimination under restrictions and provide empirical evidence to demonstrate that the proposed methodology improves over the existing unrestricted methodology. The proposed methodology is applied to a bladder cancer data set where the researchers are interested in classifying patients into various groups. Copyright © 2012 John Wiley & Sons, Ltd.

  4. Clinical classification of cancer cachexia: phenotypic correlates in human skeletal muscle.

    Directory of Open Access Journals (Sweden)

    Neil Johns

    Full Text Available BACKGROUND: Cachexia affects the majority of patients with advanced cancer and is associated with a reduction in treatment tolerance, response to therapy, and duration of survival. One impediment towards the effective treatment of cachexia is a validated classification system. METHODS: 41 patients with resectable upper gastrointestinal (GI or pancreatic cancer underwent characterisation for cachexia based on weight-loss (WL and/or low muscularity (LM. Four diagnostic criteria were used >5%WL, >10%WL, LM, and LM+>2%WL. All patients underwent biopsy of the rectus muscle. Analysis included immunohistochemistry for fibre size and type, protein and nucleic acid concentration, Western blots for markers of autophagy, SMAD signalling, and inflammation. FINDINGS: Compared with non-cachectic cancer patients, patients with LM or LM+>2%WL, mean muscle fibre diameter was reduced by about 25% (p = 0.02 and p = 0.001 respectively. No significant difference in fibre diameter was observed if patients had WL alone. Regardless of classification, there was no difference in fibre number or proportion of fibre type across all myosin heavy chain isoforms. Mean muscle protein content was reduced and the ratio of RNA/DNA decreased in patients with either >5%WL or LM+>2%WL. Compared with non-cachectic patients, SMAD3 protein levels were increased in patients with >5%WL (p = 0.022 and with >10%WL, beclin (p = 0.05 and ATG5 (p = 0.01 protein levels were increased. There were no differences in phospho-NFkB or phospho-STAT3 levels across any of the groups. CONCLUSION: Muscle fibre size, biochemical composition and pathway phenotype can vary according to whether the diagnostic criteria for cachexia are based on weight loss alone, a measure of low muscularity alone or a combination of the two. For intervention trials where the primary end-point is a change in muscle mass or function, use of combined diagnostic criteria may allow identification of a more

  5. Human reliability

    International Nuclear Information System (INIS)

    Embrey, D.E.

    1987-01-01

    Concepts and techniques of human reliability have been developed and are used mostly in probabilistic risk assessment. For this, the major application of human reliability assessment has been to identify the human errors which have a significant effect on the overall safety of the system and to quantify the probability of their occurrence. Some of the major issues within human reliability studies are reviewed and it is shown how these are applied to the assessment of human failures in systems. This is done under the following headings; models of human performance used in human reliability assessment, the nature of human error, classification of errors in man-machine systems, practical aspects, human reliability modelling in complex situations, quantification and examination of human reliability, judgement based approaches, holistic techniques and decision analytic approaches. (UK)

  6. The korean version of the body image scale-reliability and validity in a sample of breast cancer patients.

    Science.gov (United States)

    Khang, Dongwoo; Rim, Hyo-Deog; Woo, Jungmin

    2013-03-01

    The Body Image Scale (BIS) developed in collaboration with the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Study Group is a brief questionnaire for measuring body image concerns in patients with cancer. This study sought to assess the reliability and validity of the Korean version of the Body Image Scale (K-BIS). The participants consisted of 155 postoperative breast cancer patients (56 breast conserving surgery, 56 mastectomy, and 43 oncoplastic surgery). Subjects were evaluated using the K-BIS, the Body-Esteem Scale for Adolescents and Adults (BESAA), the Rosenberg Self-Esteem Scale (RSES), the Hospital Anxiety and Depression Scale (HADS), and the World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-BREF). Test-retest reliability and internal consistency were examined as a measure of reliability and validity was evaluated by convergent validity, discriminant validity and factor analysis. Cronbach's α value was 0.943. The total score of the K-BIS was negatively correlated with the BESAA (r=0.301, p59% variance. The K-BIS showed good reliability and validity for assessment of body image in Korean breast cancer patients.

  7. Laser Raman detection for oral cancer based on a Gaussian process classification method

    International Nuclear Information System (INIS)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Zhang, Chijun; Chen, He; Luo, Yusheng; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Shen, Aiguo; Hu, Jiming; Jia, Jun

    2013-01-01

    Oral squamous cell carcinoma is the most common neoplasm of the oral cavity. The incidence rate accounts for 80% of total oral cancer and shows an upward trend in recent years. It has a high degree of malignancy and is difficult to detect in terms of differential diagnosis, as a consequence of which the timing of treatment is always delayed. In this work, Raman spectroscopy was adopted to differentially diagnose oral squamous cell carcinoma and oral gland carcinoma. In total, 852 entries of raw spectral data which consisted of 631 items from 36 oral squamous cell carcinoma patients, 87 items from four oral gland carcinoma patients and 134 items from five normal people were collected by utilizing an optical method on oral tissues. The probability distribution of the datasets corresponding to the spectral peaks of the oral squamous cell carcinoma tissue was analyzed and the experimental result showed that the data obeyed a normal distribution. Moreover, the distribution characteristic of the noise was also in compliance with a Gaussian distribution. A Gaussian process (GP) classification method was utilized to distinguish the normal people and the oral gland carcinoma patients from the oral squamous cell carcinoma patients. The experimental results showed that all the normal people could be recognized. 83.33% of the oral squamous cell carcinoma patients could be correctly diagnosed and the remaining ones would be diagnosed as having oral gland carcinoma. For the classification process of oral gland carcinoma and oral squamous cell carcinoma, the correct ratio was 66.67% and the erroneously diagnosed percentage was 33.33%. The total sensitivity was 80% and the specificity was 100% with the Matthews correlation coefficient (MCC) set to 0.447 213 595. Considering the numerical results above, the application prospects and clinical value of this technique are significantly impressive. (letter)

  8. Laser Raman detection for oral cancer based on a Gaussian process classification method

    Science.gov (United States)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Zhang, Chijun; Chen, He; Luo, Yusheng; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming

    2013-06-01

    Oral squamous cell carcinoma is the most common neoplasm of the oral cavity. The incidence rate accounts for 80% of total oral cancer and shows an upward trend in recent years. It has a high degree of malignancy and is difficult to detect in terms of differential diagnosis, as a consequence of which the timing of treatment is always delayed. In this work, Raman spectroscopy was adopted to differentially diagnose oral squamous cell carcinoma and oral gland carcinoma. In total, 852 entries of raw spectral data which consisted of 631 items from 36 oral squamous cell carcinoma patients, 87 items from four oral gland carcinoma patients and 134 items from five normal people were collected by utilizing an optical method on oral tissues. The probability distribution of the datasets corresponding to the spectral peaks of the oral squamous cell carcinoma tissue was analyzed and the experimental result showed that the data obeyed a normal distribution. Moreover, the distribution characteristic of the noise was also in compliance with a Gaussian distribution. A Gaussian process (GP) classification method was utilized to distinguish the normal people and the oral gland carcinoma patients from the oral squamous cell carcinoma patients. The experimental results showed that all the normal people could be recognized. 83.33% of the oral squamous cell carcinoma patients could be correctly diagnosed and the remaining ones would be diagnosed as having oral gland carcinoma. For the classification process of oral gland carcinoma and oral squamous cell carcinoma, the correct ratio was 66.67% and the erroneously diagnosed percentage was 33.33%. The total sensitivity was 80% and the specificity was 100% with the Matthews correlation coefficient (MCC) set to 0.447 213 595. Considering the numerical results above, the application prospects and clinical value of this technique are significantly impressive.

  9. Stratification and Prognostic Relevance of Jass’s Molecular Classification of Colorectal Cancer

    International Nuclear Information System (INIS)

    Zlobec, Inti; Bihl, Michel P.; Foerster, Anja; Rufle, Alex; Terracciano, Luigi; Lugli, Alessandro

    2012-01-01

    Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into five subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: Three hundred two patients were included in this study. Molecular analysis was performed for five CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1), MGMT, MSI, KRAS, and BRAF. Methylation in at least 4 promoters or in one to three promoters was considered CIMP-high and CIMP-low (CIMP-H/L), respectively. Results: CIMP-H, CIMP-L, and CIMP-negative were found in 7.1, 43, and 49.9% cases, respectively. One hundred twenty-three tumors (41%) could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-L, 14 CIMP-H, and two CIMP-negative cases. The 10 year survival rate for CIMP-high patients [22.6% (95%CI: 7–43)] was significantly lower than for CIMP-L or CIMP-negative (p = 0.0295). Only the combined analysis of BRAF and CIMP (negative versus L/H) led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

  10. Stratification and Prognostic Relevance of Jass’s Molecular Classification of Colorectal Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Zlobec, Inti [Institute of Pathology, University of Bern, Bern (Switzerland); Institute for Pathology, University Hospital Basel, Basel (Switzerland); Bihl, Michel P.; Foerster, Anja; Rufle, Alex; Terracciano, Luigi [Institute for Pathology, University Hospital Basel, Basel (Switzerland); Lugli, Alessandro, E-mail: inti.zlobec@pathology.unibe.ch [Institute of Pathology, University of Bern, Bern (Switzerland); Institute for Pathology, University Hospital Basel, Basel (Switzerland)

    2012-02-27

    Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into five subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: Three hundred two patients were included in this study. Molecular analysis was performed for five CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1), MGMT, MSI, KRAS, and BRAF. Methylation in at least 4 promoters or in one to three promoters was considered CIMP-high and CIMP-low (CIMP-H/L), respectively. Results: CIMP-H, CIMP-L, and CIMP-negative were found in 7.1, 43, and 49.9% cases, respectively. One hundred twenty-three tumors (41%) could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-L, 14 CIMP-H, and two CIMP-negative cases. The 10 year survival rate for CIMP-high patients [22.6% (95%CI: 7–43)] was significantly lower than for CIMP-L or CIMP-negative (p = 0.0295). Only the combined analysis of BRAF and CIMP (negative versus L/H) led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

  11. Stratification and prognostic relevance of Jass’s molecular classification of colorectal cancer

    Directory of Open Access Journals (Sweden)

    Inti eZlobec

    2012-02-01

    Full Text Available Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP, microsatellite instability (MSI, KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT and classifies tumors into 5 subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: 302 patients were included in this study. Molecular analysis was performed for 5 CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1, MGMT, MSI, KRAS and BRAF. Tumors were CIMP-high or CIMP-low if ≥4 and 1-3 promoters were methylated, respectively. Results: CIMP-high, CIMP-low and CIMP–negative were found in 7.1%, 43% and 49.9% cases, respectively. 123 tumors (41% could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-low, 14 CIMP-high and 2 CIMP-negative cases. The 10-year survival rate for CIMP-high patients (22.6% (95%CI: 7-43 was significantly lower than for CIMP-low or CIMP-negative (p=0.0295. Only the combined analysis of BRAF and CIMP (negative versus low/high led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

  12. Cross-cultural adaptation, reliability, and validity of the Turkish version of the Cancer Fatigue Scale in patients with breast cancer

    Science.gov (United States)

    Şahin, Sedef; Huri, Meral; Aran, Orkun Tahir; Uyanık, Mine

    2018-02-23

    Background/aim: The Cancer Fatigue Scale (CFS) was developed to evaluate the severity of fatigue in patients with breast cancer. The aim of this study is to translate and culturally adapt a Turkish version and investigate the validity and reliability of the CFS in Turkish patients with fatigue symptoms. Materials and methods: Eighty participants completed the Turkish version of the CFS for breast cancer and the European Organization for Research and Treatment of Cancer Quality of Life Core Questionnaire ″Core 30″ (EORTC QLQ-C30). Test-retest reliability was evaluated by repeating the CFS with a 7-day interval. Results: The CFS demonstrated high test-retest reliability (ICC = 0.95) and good internal consistency (Cronbach′s alpha = 0.74) for all domains. The Kaiser-Meyer-Olkin measure of sampling adequacy was found to be 0.819, which is considered to be satisfactory (>0.5). Correlations between domains of CFS physical and EORTC physical (r: 0.77), CFS cognitive and EORTC cognitive (r: 0.70), and CFS physical and EORTC fatigue (r: 0.80) were found to be significant. Conclusion: The Turkish version of the CFS is a reliable and valid instrument to assess physical, effective, and cognitive dimensions of fatigue. The CFS may be used to evaluate the severity of fatigue in Turkish-speaking breast cancer patients.

  13. Application of objective clinical human reliability analysis (OCHRA) in assessment of technical performance in laparoscopic rectal cancer surgery.

    Science.gov (United States)

    Foster, J D; Miskovic, D; Allison, A S; Conti, J A; Ockrim, J; Cooper, E J; Hanna, G B; Francis, N K

    2016-06-01

    Laparoscopic rectal resection is technically challenging, with outcomes dependent upon technical performance. No robust objective assessment tool exists for laparoscopic rectal resection surgery. This study aimed to investigate the application of the objective clinical human reliability analysis (OCHRA) technique for assessing technical performance of laparoscopic rectal surgery and explore the validity and reliability of this technique. Laparoscopic rectal cancer resection operations were described in the format of a hierarchical task analysis. Potential technical errors were defined. The OCHRA technique was used to identify technical errors enacted in videos of twenty consecutive laparoscopic rectal cancer resection operations from a single site. The procedural task, spatial location, and circumstances of all identified errors were logged. Clinical validity was assessed through correlation with clinical outcomes; reliability was assessed by test-retest. A total of 335 execution errors identified, with a median 15 per operation. More errors were observed during pelvic tasks compared with abdominal tasks (p technical performance of laparoscopic rectal surgery.

  14. Establishing magnetic resonance imaging as an accurate and reliable tool to diagnose and monitor esophageal cancer in a rat model.

    Directory of Open Access Journals (Sweden)

    Juliann E Kosovec

    Full Text Available OBJECTIVE: To assess the reliability of magnetic resonance imaging (MRI for detection of esophageal cancer in the Levrat model of end-to-side esophagojejunostomy. BACKGROUND: The Levrat model has proven utility in terms of its ability to replicate Barrett's carcinogenesis by inducing gastroduodenoesophageal reflux (GDER. Due to lack of data on the utility of non-invasive methods for detection of esophageal cancer, treatment efficacy studies have been limited, as adenocarcinoma histology has only been validated post-mortem. It would therefore be of great value if the validity and reliability of MRI could be established in this setting. METHODS: Chronic GDER reflux was induced in 19 male Sprague-Dawley rats using the modified Levrat model. At 40 weeks post-surgery, all animals underwent endoscopy, MRI scanning, and post-mortem histological analysis of the esophagus and anastomosis. With post-mortem histology serving as the gold standard, assessment of presence of esophageal cancer was made by five esophageal specialists and five radiologists on endoscopy and MRI, respectively. RESULTS: The accuracy of MRI and endoscopic analysis to correctly identify cancer vs. no cancer was 85.3% and 50.5%, respectively. ROC curves demonstrated that MRI rating had an AUC of 0.966 (p<0.001 and endoscopy rating had an AUC of 0.534 (p = 0.804. The sensitivity and specificity of MRI for identifying cancer vs. no-cancer was 89.1% and 80% respectively, as compared to 45.5% and 57.5% for endoscopy. False positive rates of MRI and endoscopy were 20% and 42.5%, respectively. CONCLUSIONS: MRI is a more reliable diagnostic method than endoscopy in the Levrat model. The non-invasiveness of the tool and its potential to volumetrically quantify the size and number of tumors likely makes it even more useful in evaluating novel agents and their efficacy in treatment studies of esophageal cancer.

  15. Prediction of lung cancer patient survival via supervised machine learning classification techniques.

    Science.gov (United States)

    Lynch, Chip M; Abdollahi, Behnaz; Fuqua, Joshua D; de Carlo, Alexandra R; Bartholomai, James A; Balgemann, Rayeanne N; van Berkel, Victor H; Frieboes, Hermann B

    2017-12-01

    Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large datasets such as the Surveillance, Epidemiology, and End Results (SEER) program database. In particular for lung cancer, it is not well understood which types of techniques would yield more predictive information, and which data attributes should be used in order to determine this information. In this study, a number of supervised learning techniques is applied to the SEER database to classify lung cancer patients in terms of survival, including linear regression, Decision Trees, Gradient Boosting Machines (GBM), Support Vector Machines (SVM), and a custom ensemble. Key data attributes in applying these methods include tumor grade, tumor size, gender, age, stage, and number of primaries, with the goal to enable comparison of predictive power between the various methods The prediction is treated like a continuous target, rather than a classification into categories, as a first step towards improving survival prediction. The results show that the predicted values agree with actual values for low to moderate survival times, which constitute the majority of the data. The best performing technique was the custom ensemble with a Root Mean Square Error (RMSE) value of 15.05. The most influential model within the custom ensemble was GBM, while Decision Trees may be inapplicable as it had too few discrete outputs. The results further show that among the five individual models generated, the most accurate was GBM with an RMSE value of 15.32. Although SVM underperformed with an RMSE value of 15.82, statistical analysis singles the SVM as the only model that generated a distinctive output. The results of the models are consistent with a classical Cox proportional hazards model used as a reference technique. We conclude that application of these supervised learning techniques to lung cancer data in the SEER database may be of use to estimate patient survival time

  16. The validity and reliability of the Socioeconomic Status Instrument for assessing prostate cancer patients.

    Science.gov (United States)

    Cyrus-David, Mfon

    2010-08-01

    Because of the lack of consistency in the associations of the socioeconomic status (SES) of prostate cancer (PC) patients from diverse racial and ethnic backgrounds with PC health outcomes, I created the Socioeconomic Status Instrument (SESI) from the Demographic and Health Access components of the Behavioral Risk Factor Surveillance System 2004 Questionnaires and the socioeconomic indices of the subjects' residential counties to better assess the SES of PC patients. The SESI was tested on 220 consecutive subjects with pathologically confirmed PC at the Veterans Affairs Medical Center in Houston, TX. A team that included an epidemiologist, a validation statistician/health services research scientist, and PC survivors assessed the content validity of the SESI. The construct validity of the SESI was assessed with factor analysis by extracting and analyzing 5 principal components based on the subjects' individual responses on the assessment: county socioeconomic characteristics, individual socioeconomic characteristics, financial distress, increased domestic burden with limited earnings, and affluence. The internal consistency reliability of the SESI was assessed with Cronbach's alpha coefficients. Based on the reviews of the SESI, all of the initial 10 items were retained. The correlations between individual responses on the SESI were similar to the results of previous studies. The 5 principal components that I assessed accounted for 71.5% of the variance. Factor loadings ranged from 0.66 to 0.98 and communalities ranged from 0.55 to 0.94. County socioeconomic characteristics accounted for 22.6% of the variance, whereas individual socioeconomic characteristics accounted for 14.6% of the variance. The overall Cronbach's alpha coefficient was 0.78. The SESI is valid and reliable. Accurate measurements of the SES of PC patients would provide better guidance for future research and care deliveries.

  17. Reliability of multiparametric prostatic MRI quantitative data in the evaluation of prostate cancer aggressiveness

    Directory of Open Access Journals (Sweden)

    Haisam Atta

    2017-09-01

    Full Text Available Purpose: To compare the quantitative data of multiparametric prostatic MRI with Gleason scores of histopathological analysis. Materials and methods: One hundred twenty-two patients performed Multiparametric MRI of the prostate. Functional MRI quantitative data (including diffusion with mean ADC value and spectroscopic metabolic ratio where the DWI is employing b 50, 400, 800, 1000 and 2000 sec/mm2 and multivoxel MR spectroscopy compared with of Gleason scores of histopathological results. Malignant cases are classified into three groups according to their Gleason score as group I with Gleason score ≤6, group II Gleason score 7, while Gleason score 8–10 stratified as Group III. Results: The histopathological analysis reveals 78 malignant cases and 44 benign Cases. The significant statistical difference between group I and the other two groups (p < 0.001 regarding the quantitative mean ADC value and metabolic spectroscopic ratio. No significant statistical difference between group II and III with p = 0.2 for mean ADC difference and p = 0.8 for the metabolic spectroscopic ratio with a weak negative correlation between ADCand Gleason score [rs = −0.26] and significant positive correlation (p = 0.02 for MRSI metabolic ratio [rs = 0.2]. Conclusion: The quantitative data of functional imaging of the prostate is reliable in evaluating prostatic cancer aggressiveness and proper construction of therapeutic plan. Keywords: mpMRI prostate cancer aggressiveness

  18. Prevent cervical cancer by screening with reliable human papillomavirus detection and genotyping

    International Nuclear Information System (INIS)

    Ge, Shichao; Gong, Bo; Cai, Xushan; Yang, Xiaoer; Gan, Xiaowei; Tong, Xinghai; Li, Haichuan; Zhu, Meijuan; Yang, Fengyun; Zhou, Hongrong; Hong, Guofan

    2012-01-01

    The incidence of cervical cancer is expected to rise sharply in China. A reliable routine human papillomavirus (HPV) detection and genotyping test to be supplemented by the limited Papanicolaou cytology facilities is urgently needed to help identify the patients with cervical precancer for preventive interventions. To this end, we evaluated a nested polymerase chain reaction (PCR) protocol for detection of HPV L1 gene DNA in cervicovaginal cells. The PCR amplicons were genotyped by direct DNA sequencing. In parallel, split samples were subjected to a Digene HC2 HPV test which has been widely used for “cervical cancer risk” screen. Of the 1826 specimens, 1655 contained sufficient materials for analysis and 657 were truly negative. PCR/DNA sequencing showed 674 infected by a single high-risk HPV, 188 by a single low-risk HPV, and 136 by multiple HPV genotypes with up to five HPV genotypes in one specimen. In comparison, the HC2 test classified 713 specimens as infected by high-risk HPV, and 942 as negative for HPV infections. The high-risk HC2 test correctly detected 388 (57.6%) of the 674 high-risk HPV isolates in clinical specimens, mislabeled 88 (46.8%) of the 188 low-risk HPV isolates as high-risk genotypes, and classified 180 (27.4%) of the 657 “true-negative” samples as being infected by high-risk HPV. It was found to cross-react with 20 low-risk HPV genotypes. We conclude that nested PCR detection of HPV followed by short target DNA sequencing can be used for screening and genotyping to formulate a paradigm in clinical management of HPV-related disorders in a rapidly developing economy

  19. Classification of Breast Cancer Resistant Protein (BCRP) Inhibitors and Non-Inhibitors Using Machine Learning Approaches.

    Science.gov (United States)

    Belekar, Vilas; Lingineni, Karthik; Garg, Prabha

    2015-01-01

    The breast cancer resistant protein (BCRP) is an important transporter and its inhibitors play an important role in cancer treatment by improving the oral bioavailability as well as blood brain barrier (BBB) permeability of anticancer drugs. In this work, a computational model was developed to predict the compounds as BCRP inhibitors or non-inhibitors. Various machine learning approaches like, support vector machine (SVM), k-nearest neighbor (k-NN) and artificial neural network (ANN) were used to develop the models. The Matthews correlation coefficients (MCC) of developed models using ANN, k-NN and SVM are 0.67, 0.71 and 0.77, and prediction accuracies are 85.2%, 88.3% and 90.8% respectively. The developed models were tested with a test set of 99 compounds and further validated with external set of 98 compounds. Distribution plot analysis and various machine learning models were also developed based on druglikeness descriptors. Applicability domain is used to check the prediction reliability of the new molecules.

  20. Cell nuclei attributed relational graphs for efficient representation and classification of gastric cancer in digital histopathology

    Science.gov (United States)

    Sharma, Harshita; Zerbe, Norman; Heim, Daniel; Wienert, Stephan; Lohmann, Sebastian; Hellwich, Olaf; Hufnagl, Peter

    2016-03-01

    This paper describes a novel graph-based method for efficient representation and subsequent classification in histological whole slide images of gastric cancer. Her2/neu immunohistochemically stained and haematoxylin and eosin stained histological sections of gastric carcinoma are digitized. Immunohistochemical staining is used in practice by pathologists to determine extent of malignancy, however, it is laborious to visually discriminate the corresponding malignancy levels in the more commonly used haematoxylin and eosin stain, and this study attempts to solve this problem using a computer-based method. Cell nuclei are first isolated at high magnification using an automatic cell nuclei segmentation strategy, followed by construction of cell nuclei attributed relational graphs of the tissue regions. These graphs represent tissue architecture comprehensively, as they contain information about cell nuclei morphology as vertex attributes, along with knowledge of neighborhood in the form of edge linking and edge attributes. Global graph characteristics are derived and ensemble learning is used to discriminate between three types of malignancy levels, namely, non-tumor, Her2/neu positive tumor and Her2/neu negative tumor. Performance is compared with state of the art methods including four texture feature groups (Haralick, Gabor, Local Binary Patterns and Varma Zisserman features), color and intensity features, and Voronoi diagram and Delaunay triangulation. Texture, color and intensity information is also combined with graph-based knowledge, followed by correlation analysis. Quantitative assessment is performed using two cross validation strategies. On investigating the experimental results, it can be concluded that the proposed method provides a promising way for computer-based analysis of histopathological images of gastric cancer.

  1. Body mass index: different nutritional status according to WHO, OPAS and Lipschitz classifications in gastrointestinal cancer patients.

    Science.gov (United States)

    Barao, Katia; Forones, Nora Manoukian

    2012-01-01

    The body mass index (BMI) is the most common marker used on diagnoses of the nutritional status. The great advantage of this index is the easy way to measure, the low cost, the good correlation with the fat mass and the association to morbidity and mortality. To compare the BMI differences according to the WHO, OPAS and Lipschitz classification. A prospective study on 352 patients with esophageal, gastric or colorectal cancer was done. The BMI was calculated and analyzed by the classification of WHO, Lipschitz and OPAS. The mean age was 62.1 ± 12.4 years and 59% of them had more than 59 years. The BMI had not difference between the genders in patients cancer had more than 65 years. A different cut off must be used for this patients, because undernourished patients may be wrongly considered well nourished.

  2. Prognostic classification index in Iranian colorectal cancer patients: Survival tree analysis

    Directory of Open Access Journals (Sweden)

    Amal Saki Malehi

    2016-01-01

    Full Text Available Aims: The aim of this study was to determine the prognostic index for separating homogenous subgroups in colorectal cancer (CRC patients based on clinicopathological characteristics using survival tree analysis. Methods: The current study was conducted at the Research Center of Gastroenterology and Liver Disease, Shahid Beheshti Medical University in Tehran, between January 2004 and January 2009. A total of 739 patients who already have been diagnosed with CRC based on pathologic report were enrolled. The data included demographic and clinical-pathological characteristic of patients. Tree-structured survival analysis based on a recursive partitioning algorithm was implemented to evaluate prognostic factors. The probability curves were calculated according to the Kaplan-Meier method, and the hazard ratio was estimated as an interest effect size. Result: There were 526 males (71.2% of these patients. The mean survival time (from diagnosis time was 42.46± (3.4. Survival tree identified three variables as main prognostic factors and based on their four prognostic subgroups was constructed. The log-rank test showed good separation of survival curves. Patients with Stage I-IIIA and treated with surgery as the first treatment showed low risk (median = 34 months whereas patients with stage IIIB, IV, and more than 68 years have the worse survival outcome (median = 9.5 months. Conclusion: Constructing the prognostic classification index via survival tree can aid the researchers to assess interaction between clinical variables and determining the cumulative effect of these variables on survival outcome.

  3. A scale space approach for unsupervised feature selection in mass spectra classification for ovarian cancer detection.

    Science.gov (United States)

    Ceccarelli, Michele; d'Acierno, Antonio; Facchiano, Angelo

    2009-10-15

    Mass spectrometry spectra, widely used in proteomics studies as a screening tool for protein profiling and to detect discriminatory signals, are high dimensional data. A large number of local maxima (a.k.a. peaks) have to be analyzed as part of computational pipelines aimed at the realization of efficient predictive and screening protocols. With this kind of data dimensions and samples size the risk of over-fitting and selection bias is pervasive. Therefore the development of bio-informatics methods based on unsupervised feature extraction can lead to general tools which can be applied to several fields of predictive proteomics. We propose a method for feature selection and extraction grounded on the theory of multi-scale spaces for high resolution spectra derived from analysis of serum. Then we use support vector machines for classification. In particular we use a database containing 216 samples spectra divided in 115 cancer and 91 control samples. The overall accuracy averaged over a large cross validation study is 98.18. The area under the ROC curve of the best selected model is 0.9962. We improved previous known results on the problem on the same data, with the advantage that the proposed method has an unsupervised feature selection phase. All the developed code, as MATLAB scripts, can be downloaded from http://medeaserver.isa.cnr.it/dacierno/spectracode.htm.

  4. Subtype classification for prediction of prognosis of breast cancer from a biomarker panel: correlations and indications

    Directory of Open Access Journals (Sweden)

    Chen C

    2014-02-01

    positive correlation (P<0.001 between the estrogen receptor and the progesterone receptor (r=0.588, but a significant negative correlation (P<0.001, r=-0.618 with the HHR subtype. There were significant differences between the estrogen receptor, progesterone receptor, and HER2 subtypes with regard to total HER2 load and hormone receptor subtypes. The rates of androgen receptor and p53 positivity were 46.3% and 57.0%, respectively. Other than the androgen receptor, differences in expression of Ki67, EGFR, and p53 did not achieve statistical significance (P>0.05 between the five subtypes. EGFR and Ki67 had prognostic significance for 5-year disease-free survival in univariate analysis, but the androgen receptor and p53 did not. Multivariate analysis identified that EGFR expression had predictive significance for 5-year disease-free survival in hormone-receptor positive patients and in those with the lymph node-positive breast cancer subtype. Conclusion: Hormone receptor expression was indeed one of the molecular profiles in the subtypes identified by quantitative HER2 and vice versa. EGFR status may provide discriminative prognostic information in addition to HER2 and hormone receptor status, and should be integrated into routine practice to help formulate more specific prediction of the prognosis and appropriate individualized treatment. Keywords: quantum dots, breast cancer, molecular classification, prognosis, prediction

  5. Genetic Fuzzy System (GFS based wavelet co-occurrence feature selection in mammogram classification for breast cancer diagnosis

    Directory of Open Access Journals (Sweden)

    Meenakshi M. Pawar

    2016-09-01

    Full Text Available Breast cancer is significant health problem diagnosed mostly in women worldwide. Therefore, early detection of breast cancer is performed with the help of digital mammography, which can reduce mortality rate. This paper presents wrapper based feature selection approach for wavelet co-occurrence feature (WCF using Genetic Fuzzy System (GFS in mammogram classification problem. The performance of GFS algorithm is explained using mini-MIAS database. WCF features are obtained from detail wavelet coefficients at each level of decomposition of mammogram image. At first level of decomposition, 18 features are applied to GFS algorithm, which selects 5 features with an average classification success rate of 39.64%. Subsequently, at second level it selects 9 features from 36 features and the classification success rate is improved to 56.75%. For third level, 16 features are selected from 54 features and average success rate is improved to 64.98%. Lastly, at fourth level 72 features are applied to GFS, which selects 16 features and thereby increasing average success rate to 89.47%. Hence, GFS algorithm is the effective way of obtaining optimal set of feature in breast cancer diagnosis.

  6. Restaging and Survival Analysis of 4036 Ovarian Cancer Patients According to the 2013 FIGO Classification for Ovarian, Fallopian Tube, and Primary Peritoneal Cancer

    DEFF Research Database (Denmark)

    Rosendahl, Mikkel; Høgdall, Claus Kim; Mosgaard, Berit Jul

    2016-01-01

    OBJECTIVE: With the 2013 International Federation of Gynecology and Obstetrics (FIGO) staging for ovarian, fallopian tube, and primary peritoneal cancer, the number of substages changed from 10 to 14. Any classification of a malignancy should easily assign patients to prognostic groups, refer....... MATERIALS AND METHODS: Demographic, surgical, histological, and survival data from 4036 ovarian cancer patients were used in the analysis. Five-year survival rates (5YSR) and hazard ratios for the old and revised FIGO staging were calculated using Kaplan-Meier curves and Cox regression. RESULTS: A total...

  7. Comparison of Computational Algorithms for the Classification of Liver Cancer using SELDI Mass Spectrometry: A Case Study

    Directory of Open Access Journals (Sweden)

    Robert J Hickey

    2007-01-01

    Full Text Available Introduction: As an alternative to DNA microarrays, mass spectrometry based analysis of proteomic patterns has shown great potential in cancer diagnosis. The ultimate application of this technique in clinical settings relies on the advancement of the technology itself and the maturity of the computational tools used to analyze the data. A number of computational algorithms constructed on different principles are available for the classification of disease status based on proteomic patterns. Nevertheless, few studies have addressed the difference in the performance of these approaches. In this report, we describe a comparative case study on the classification accuracy of hepatocellular carcinoma based on the serum proteomic pattern generated from a Surface Enhanced Laser Desorption/Ionization (SELDI mass spectrometer.Methods: Nine supervised classifi cation algorithms are implemented in R software and compared for the classification accuracy.Results: We found that the support vector machine with radial function is preferable as a tool for classification of hepatocellular carcinoma using features in SELDI mass spectra. Among the rest of the methods, random forest and prediction analysis of microarrays have better performance. A permutation-based technique reveals that the support vector machine with a radial function seems intrinsically superior in learning from the training data since it has a lower prediction error than others when there is essentially no differential signal. On the other hand, the performance of the random forest and prediction analysis of microarrays rely on their capability of capturing the signals with substantial differentiation between groups.Conclusions: Our finding is similar to a previous study, where classification methods based on the Matrix Assisted Laser Desorption/Ionization (MALDI mass spectrometry are compared for the prediction accuracy of ovarian cancer. The support vector machine, random forest and prediction

  8. North American Magazine Coverage of Skin Cancer and Recreational Tanning Before and After the WHO/IARC 2009 Classification of Indoor Tanning Devices as Carcinogenic.

    Science.gov (United States)

    McWhirter, Jennifer E; Hoffman-Goetz, Laurie

    2015-09-01

    The mass media is an influential source of skin cancer information for the public. In 2009, the World Health Organization's International Agency for Research on Cancer classified UV radiation from tanning devices as carcinogenic. Our objective was to determine if media coverage of skin cancer and recreational tanning increased in volume or changed in nature after this classification. We conducted a directed content analysis on 29 North American popular magazines (2007-2012) to investigate the overall volume of articles on skin cancer and recreational tanning and, more specifically, the presence of skin cancer risk factors, UV behaviors, and early detection information in article text (n = 410) and images (n = 714). The volume of coverage on skin cancer and recreational tanning did not increase significantly after the 2009 classification of tanning beds as carcinogenic. Key-related messages, including that UV exposure is a risk factor for skin cancer and that indoor tanning should be avoided, were not reported more frequently after the classification, but the promotion of the tanned look as attractive was conveyed more often in images afterwards (p skin cancer risk factors, other UV behaviors, or early detection information over time. The classification of indoor tanning beds as carcinogenic had no significant impact on the volume or nature of skin cancer and recreational tanning coverage in magazines.

  9. Classification of hospital pathways in the management of cancer: application to lung cancer in the region of burgundy.

    Science.gov (United States)

    Nuemi, G; Afonso, F; Roussot, A; Billard, L; Cottenet, J; Combier, E; Diday, E; Quantin, C

    2013-10-01

    The evaluation of national cancer plans is an important aspect of their implementation. For this evaluation, the principal actors in the field (doctors, nurses, etc.) as well as decision-makers must have access to information that is reliable, synthetic and easy to interpret, and which reflects the implementation process in the field. We propose here a methodology to make this type of information available in the context of reducing inequalities with regard to access to healthcare for patients with lung cancer in the region of Burgundy. We used the national medico-administrative DRG-type database, which gathers together all hospital stays. By using this database, it was possible to identify and reconstruct the care management history of these patients. That is, by linking together all attended hospitals, sorted chronologically. Eligible patients were at least 18 years old, whatever the gender and had undergone surgery for their lung cancer. They had to be residents of Burgundy at the time of the first operation between 2006 and 2008. Patient's pathway was defined as the sequence of all attended hospitals (hospital stays) during the year of follow up linked together using an anonymised patient identifier. We then constructed a pathway typology of pathway using an unsupervised clustering method, and conducted a spatial analysis of this typology. Between 2006 and 2008, we selected 495 patients in the 4 administrative departments of the Burgundy region. They accounted for a total of 3821 stays during the year of follow-up. There were 393 men (79%) and the mean age was 64 (95% confidence interval: 63-65) years. We reconstructed 94 pathways (about five per patient). Here, neighbourhood's cares accounted for 41% of them, while 44% included a surgical intervention outside the region of Burgundy. We constructed a pathway typology with five classes. Spatial analysis showed that the vast majority of initial surgeries took place in the major regional centres. The construction

  10. Psychosocial Adjustment to Illness Scale: Factor structure, reliability, and validity assessment in a sample of Greek breast cancer patients.

    Science.gov (United States)

    Kolokotroni, Philippa; Anagnostopoulos, Fotios; Missitzis, Ioannis

    2017-07-01

    The study and measurement of psychosocial adjustment is important for evaluating patients' well-being, and assessing the illness's course, treatment's success, and patients' recovery. In this study, internal consistency reliability and construct validity of the Greek version of the Psychosocial Adjustment to Illness Scale-Self-Report (PAIS-SR) were examined. Demographic and psychosocial data were collected from a sample of 243 women with breast cancer, recruited from September 2011 to December 2012. With some exceptions in specific items, the original conceptually-derived PAIS-SR subscales emerged in a seven-factor solution. Social Environment, Job and Household Duties, and Psychological Distress accounted for more of the total variance than other subscales. PAIS-SR showed good internal consistency reliability, with Cronbach's alpha coefficients >0.62. Correlations of PAIS-SR domains with measures of quality of life and posttraumatic stress symptoms supported the convergent validity of the PAIS-SR and its significance for cancer research. The Greek version of the PAIS-SR has acceptable internal consistency reliability and construct validity, as well as satisfactory convergent validity. Results provide some suggestions for the development of programs to evaluate adjustment status and implement psychosocial interventions among breast cancer survivors.

  11. Mastectomy or breast conserving surgery? Factors affecting type of surgical treatment for breast cancer – a classification tree approach

    International Nuclear Information System (INIS)

    Martin, Michael A; Meyricke, Ramona; O'Neill, Terry; Roberts, Steven

    2006-01-01

    A critical choice facing breast cancer patients is which surgical treatment – mastectomy or breast conserving surgery (BCS) – is most appropriate. Several studies have investigated factors that impact the type of surgery chosen, identifying features such as place of residence, age at diagnosis, tumor size, socio-economic and racial/ethnic elements as relevant. Such assessment of 'propensity' is important in understanding issues such as a reported under-utilisation of BCS among women for whom such treatment was not contraindicated. Using Western Australian (WA) data, we further examine the factors associated with the type of surgical treatment for breast cancer using a classification tree approach. This approach deals naturally with complicated interactions between factors, and so allows flexible and interpretable models for treatment choice to be built that add to the current understanding of this complex decision process. Data was extracted from the WA Cancer Registry on women diagnosed with breast cancer in WA from 1990 to 2000. Subjects' treatment preferences were predicted from covariates using both classification trees and logistic regression. Tumor size was the primary determinant of patient choice, subjects with tumors smaller than 20 mm in diameter preferring BCS. For subjects with tumors greater than 20 mm in diameter factors such as patient age, nodal status, and tumor histology become relevant as predictors of patient choice. Classification trees perform as well as logistic regression for predicting patient choice, but are much easier to interpret for clinical use. The selected tree can inform clinicians' advice to patients

  12. The correlation study of radiological findings with pathological classification of superficial depressed (IIc type) early gastric cancer

    International Nuclear Information System (INIS)

    Liu Linxiang; Deng Bingxing; Liu Yujin; Iinuma, G.; Moriyama, N.

    2007-01-01

    Objective: To investigate the relations between radiological findings and pathological classification of superficial depressed (II c type) early gastric cancer. Methods: Radiological features in subtonic double contrast barium examination and the endoscopic pictures of early gastric cancer compared with the global pathological specimens and micro-pathological features were prospectively studied. Combined with the gastric endoscopic pictures, the sharpness of margin of the lesions, the changes of converging mucosal folds and the changes of the depressed surface on the film of double contrast barium examination were analyzed. The correlation between the radiological features and histological classification of gastric cancer including well differentiated tubular adenocarcinoma (tub1), moderately differentiated tubular adenocarcinoma (tub2), poorly differentiated adenocarcinoma (por) and signet-ring cell carcinoma (sig) were studied. Results: In 102 cases of II c type early gastric cancer, there were tub1 27 cases, tub2 11, por 26 and sig 38 cases histologically. The margin of the depressed lesions of tubl (24 cases) and tub2 (9 cases) cancers were mostly unsharply demarcated or with fine spicular border, while the margin of lesions of por(15 cases) and sig(31 cases) were mostly clearly and sharply demarcated, with statistical significance (P<0.01). The depressed surface of tub1 and tub2 lesions (17 cases) revealed little unevenness, sometimes with evenly granulations, single nodule and scar-like depression, while that of por and sig lesions (41 cases) manifested as nodules of varying sizes, with statistical significance (P<0.01). Conclusion: The radiological findings of superficial depressed early gastric cancer in different histological types were different, the possible histological type could be speculated according to the radiological findings of the lesions. (authors)

  13. Validity and reliability of the persian version of templer death anxiety scale in family caregivers of cancer patients.

    Science.gov (United States)

    Soleimani, Mohammad Ali; Bahrami, Nasim; Yaghoobzadeh, Ameneh; Banihashemi, Hedieh; Nia, Hamid Sharif; Haghdoost, Ali Akbar

    2016-01-01

    Due to increasing recognition of the importance of death anxiety for understanding human nature, it is important that researchers who investigate death anxiety have reliable and valid methodology to measure. The purpose of this study was to evaluate the validity and reliability of the Persian version of Templer Death Anxiety Scale (TDAS) in family caregivers of cancer patients. A sample of 326 caregivers of cancer patients completed a 15-item questionnaire. Principal components analysis (PCA) followed by a varimax rotation was used to assess factor structure of the DAS. The construct validity of the scale was assessed using exploratory and confirmatory factor analyses. Convergent and discriminant validity were also examined. Reliability was assessed with Cronbach's alpha coefficients and construction reliability. Based on the results of the PCA and consideration of the meaning of our items, a three-factor solution, explaining 60.38% of the variance, was identified. A confirmatory factor analysis (CFA) then supported the adequacy of the three-domain structure of the DAS. Goodness-of-fit indices showed an acceptable fit overall with the full model {χ(2)(df) = 262.32 (61), χ(2)/df = 2.04 [adjusted goodness of fit index (AGFI) = 0.922, parsimonious comparative fit index (PCFI) = 0.703, normed fit Index (NFI) = 0.912, CMIN/DF = 2.048, root mean square error of approximation (RMSEA) = 0.055]}. Convergent and discriminant validity were shown with construct fulfilled. The Cronbach's alpha and construct reliability were greater than 0.70. The findings show that the Persian version of the TDAS has a three-factor structure and acceptable validity and reliability.

  14. Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

    International Nuclear Information System (INIS)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Shen, Aiguo; Hu, Jiming; Jia, Jun

    2013-01-01

    The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory. (paper)

  15. Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

    Science.gov (United States)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming

    2013-03-01

    The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory.

  16. Gene masking - a technique to improve accuracy for cancer classification with high dimensionality in microarray data.

    Science.gov (United States)

    Saini, Harsh; Lal, Sunil Pranit; Naidu, Vimal Vikash; Pickering, Vincel Wince; Singh, Gurmeet; Tsunoda, Tatsuhiko; Sharma, Alok

    2016-12-05

    High dimensional feature space generally degrades classification in several applications. In this paper, we propose a strategy called gene masking, in which non-contributing dimensions are heuristically removed from the data to improve classification accuracy. Gene masking is implemented via a binary encoded genetic algorithm that can be integrated seamlessly with classifiers during the training phase of classification to perform feature selection. It can also be used to discriminate between features that contribute most to the classification, thereby, allowing researchers to isolate features that may have special significance. This technique was applied on publicly available datasets whereby it substantially reduced the number of features used for classification while maintaining high accuracies. The proposed technique can be extremely useful in feature selection as it heuristically removes non-contributing features to improve the performance of classifiers.

  17. Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification

    Directory of Open Access Journals (Sweden)

    D. Ramyachitra

    2015-09-01

    Full Text Available Microarray technology allows simultaneous measurement of the expression levels of thousands of genes within a biological tissue sample. The fundamental power of microarrays lies within the ability to conduct parallel surveys of gene expression using microarray data. The classification of tissue samples based on gene expression data is an important problem in medical diagnosis of diseases such as cancer. In gene expression data, the number of genes is usually very high compared to the number of data samples. Thus the difficulty that lies with data are of high dimensionality and the sample size is small. This research work addresses the problem by classifying resultant dataset using the existing algorithms such as Support Vector Machine (SVM, K-nearest neighbor (KNN, Interval Valued Classification (IVC and the improvised Interval Value based Particle Swarm Optimization (IVPSO algorithm. Thus the results show that the IVPSO algorithm outperformed compared with other algorithms under several performance evaluation functions.

  18. Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification.

    Science.gov (United States)

    Ramyachitra, D; Sofia, M; Manikandan, P

    2015-09-01

    Microarray technology allows simultaneous measurement of the expression levels of thousands of genes within a biological tissue sample. The fundamental power of microarrays lies within the ability to conduct parallel surveys of gene expression using microarray data. The classification of tissue samples based on gene expression data is an important problem in medical diagnosis of diseases such as cancer. In gene expression data, the number of genes is usually very high compared to the number of data samples. Thus the difficulty that lies with data are of high dimensionality and the sample size is small. This research work addresses the problem by classifying resultant dataset using the existing algorithms such as Support Vector Machine (SVM), K-nearest neighbor (KNN), Interval Valued Classification (IVC) and the improvised Interval Value based Particle Swarm Optimization (IVPSO) algorithm. Thus the results show that the IVPSO algorithm outperformed compared with other algorithms under several performance evaluation functions.

  19. Breast cancer surgery and diagnosis-related groups (DRGs): patient classification and hospital reimbursement in 11 European countries.

    Science.gov (United States)

    Scheller-Kreinsen, David; Quentin, Wilm; Geissler, Alexander; Busse, Reinhard

    2013-10-01

    Researchers from eleven countries (i.e. Austria, England, Estonia, Finland, France, Germany, Ireland, Netherlands, Poland, Spain, and Sweden) compared how their DRG systems deal with breast cancer surgery patients. DRG algorithms and indicators of resource consumption were assessed for those DRGs that individually contain at least 1% of all breast cancer surgery patients. Six standardised case vignettes were defined and quasi prices according to national DRG-based hospital payment systems were ascertained. European DRG systems classify breast cancer surgery patients according to different sets of classification variables into three to seven DRGs. Quasi prices for an index case treated with partial mastectomy range from €577 in Poland to €5780 in the Netherlands. Countries award their highest payments for very different kinds of patients. Breast cancer specialists and national DRG authorities should consider how other countries' DRG systems classify breast cancer patients in order to identify potential scope for improvement and to ensure fair and appropriate reimbursement. Copyright © 2012 Elsevier Ltd. All rights reserved.

  20. PI-RADS version 2: quantitative analysis aids reliable interpretation of diffusion-weighted imaging for prostate cancer

    Energy Technology Data Exchange (ETDEWEB)

    Park, Sung Yoon; Jung, Dae Chul; Oh, Young Taik [Yonsei University College of Medicine, Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Seoul (Korea, Republic of); Shin, Su-Jin [Yonsei University College of Medicine, Department of Pathology, Seoul (Korea, Republic of); Hanyang University College of Medicine, Department of Pathology, Seoul (Korea, Republic of); Cho, Nam Hoon [Yonsei University College of Medicine, Department of Pathology, Seoul (Korea, Republic of); Choi, Young Deuk; Rha, Koon Ho; Hong, Sung Joon [Yonsei University College of Medicine, Department of Urology, Seoul (Korea, Republic of)

    2017-07-15

    To determine whether apparent diffusion coefficient (ADC) ratio aids reliable interpretation of diffusion-weighted imaging (DWI) for prostate cancer (PCa). Seventy-six consecutive patients with PCa who underwent DWI and surgery were included. Based on pathologic tumour location, two readers independently performed DWI scoring according to the revised Prostate Imaging Reporting and Data System (PI-RADSv2). ADC ratios of benign to cancerous prostatic tissue were then measured independently and compared between cases showing concordant and discordant DWI scores ≥4. Area under the curve (AUC) and threshold of ADC ratio were analyzed for DWI scores ≥4. The rate of inter-reader disagreement for DWI score ≥4 was 11.8% (9/76). ADC ratios were higher in concordant vs. discordant DWI scores ≥4 (median, 1.7 vs. 1.1-1.2; p < 0.001). For DWI scores ≥4, the AUCs of ADC ratios were 0.970 for reader 1 and 0.959 for reader 2. In patients with an ADC ratio >1.3, the rate of inter-reader disagreement for DWI score ≥4 decreased to 5.9-6.0%. An ADC ratio >1.3 yielded 100% (reader 1, 54/54; reader 2, 51/51) positive predictive value for clinically significant cancer. ADC ratios may be useful for reliable interpretation of DWI score ≥4 in PI-RADSv2. (orig.)

  1. Deep learning based classification for head and neck cancer detection with hyperspectral imaging in an animal model

    Science.gov (United States)

    Ma, Ling; Lu, Guolan; Wang, Dongsheng; Wang, Xu; Chen, Zhuo Georgia; Muller, Susan; Chen, Amy; Fei, Baowei

    2017-03-01

    Hyperspectral imaging (HSI) is an emerging imaging modality that can provide a noninvasive tool for cancer detection and image-guided surgery. HSI acquires high-resolution images at hundreds of spectral bands, providing big data to differentiating different types of tissue. We proposed a deep learning based method for the detection of head and neck cancer with hyperspectral images. Since the deep learning algorithm can learn the feature hierarchically, the learned features are more discriminative and concise than the handcrafted features. In this study, we adopt convolutional neural networks (CNN) to learn the deep feature of pixels for classifying each pixel into tumor or normal tissue. We evaluated our proposed classification method on the dataset containing hyperspectral images from 12 tumor-bearing mice. Experimental results show that our method achieved an average accuracy of 91.36%. The preliminary study demonstrated that our deep learning method can be applied to hyperspectral images for detecting head and neck tumors in animal models.

  2. The validity and reliability of the 'Cancer Caregiving Tasks, Consequences and Needs Questionnaire' (CaTCoN)

    DEFF Research Database (Denmark)

    Lund, Line; Ross, Lone; Petersen, Morten A

    2014-01-01

    and reliability of the multi-item scales in the CaTCoN using psychometric analyses as well as tests of convergent and discriminant validity with the existing instruments FAMCARE and Family Inventory of Needs (FIN). Material and methods. Based on theoretical considerations, a subscale structure in the Ca......TCoN and the existing questionnaires FAMCARE and FIN. Conclusion. Taken together the psychometric analyses and tests of convergent and discriminant validity indicate that the validity and reliability of the CaTCoN are satisfactory.......Background. Caregivers are often involved in and affected by the patient's disease. The questionnaire 'Cancer Caregiving Tasks, Consequences and Needs Questionnaire' (CaTCoN) was developed to measure caregivers' experiences. The aim of this study is to evaluate the construct validity...

  3. Thermographic image analysis for classification of ACL rupture disease, bone cancer, and feline hyperthyroid, with Gabor filters

    Science.gov (United States)

    Alvandipour, Mehrdad; Umbaugh, Scott E.; Mishra, Deependra K.; Dahal, Rohini; Lama, Norsang; Marino, Dominic J.; Sackman, Joseph

    2017-05-01

    Thermography and pattern classification techniques are used to classify three different pathologies in veterinary images. Thermographic images of both normal and diseased animals were provided by the Long Island Veterinary Specialists (LIVS). The three pathologies are ACL rupture disease, bone cancer, and feline hyperthyroid. The diagnosis of these diseases usually involves radiology and laboratory tests while the method that we propose uses thermographic images and image analysis techniques and is intended for use as a prescreening tool. Images in each category of pathologies are first filtered by Gabor filters and then various features are extracted and used for classification into normal and abnormal classes. Gabor filters are linear filters that can be characterized by the two parameters wavelength λ and orientation θ. With two different wavelength and five different orientations, a total of ten different filters were studied. Different combinations of camera views, filters, feature vectors, normalization methods, and classification methods, produce different tests that were examined and the sensitivity, specificity and success rate for each test were produced. Using the Gabor features alone, sensitivity, specificity, and overall success rates of 85% for each of the pathologies was achieved.

  4. mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

    Directory of Open Access Journals (Sweden)

    Hala Alshamlan

    2015-01-01

    Full Text Available An artificial bee colony (ABC is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR, and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO. The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

  5. mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

    Science.gov (United States)

    Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

    2015-01-01

    An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

  6. Computerized three-class classification of MRI-based prognostic markers for breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Bhooshan, Neha; Giger, Maryellen; Edwards, Darrin; Yuan Yading; Jansen, Sanaz; Li Hui; Lan Li; Newstead, Gillian [Department of Radiology, University of Chicago, Chicago, IL 60637 (United States); Sattar, Husain, E-mail: bhooshan@uchicago.edu [Department of Pathology, University of Chicago, Chicago, IL 60637 (United States)

    2011-09-21

    The purpose of this study is to investigate whether computerized analysis using three-class Bayesian artificial neural network (BANN) feature selection and classification can characterize tumor grades (grade 1, grade 2 and grade 3) of breast lesions for prognostic classification on DCE-MRI. A database of 26 IDC grade 1 lesions, 86 IDC grade 2 lesions and 58 IDC grade 3 lesions was collected. The computer automatically segmented the lesions, and kinetic and morphological lesion features were automatically extracted. The discrimination tasks-grade 1 versus grade 3, grade 2 versus grade 3, and grade 1 versus grade 2 lesions-were investigated. Step-wise feature selection was conducted by three-class BANNs. Classification was performed with three-class BANNs using leave-one-lesion-out cross-validation to yield computer-estimated probabilities of being grade 3 lesion, grade 2 lesion and grade 1 lesion. Two-class ROC analysis was used to evaluate the performances. We achieved AUC values of 0.80 {+-} 0.05, 0.78 {+-} 0.05 and 0.62 {+-} 0.05 for grade 1 versus grade 3, grade 1 versus grade 2, and grade 2 versus grade 3, respectively. This study shows the potential for (1) applying three-class BANN feature selection and classification to CADx and (2) expanding the role of DCE-MRI CADx from diagnostic to prognostic classification in distinguishing tumor grades.

  7. CDX2 prognostic value in stage II/III resected colon cancer is related to CMS classification.

    Science.gov (United States)

    Pilati, C; Taieb, J; Balogoun, R; Marisa, L; de Reyniès, A; Laurent-Puig, P

    2017-05-01

    Caudal-type homeobox transcription factor 2 (CDX2) is involved in colon cancer (CC) oncogenesis and has been proposed as a prognostic biomarker in patients with stage II or III CC. We analyzed CDX2 expression in a series of 469 CC typed for the new international consensus molecular subtype (CMS) classification, and we confirmed results in a series of 90 CC. Here, we show that lack of CDX2 expression is only present in the mesenchymal subgroup (CMS4) and in MSI-immune tumors (CMS1) and not in CMS2 and CMS3 colon cancer. Although CDX2 expression was a globally independent prognostic factor, loss of CDX2 expression is not associated with a worse prognosis in the CMS1 group, but is highly prognostic in CMS4 patients for both relapse free and overall survival. Similarly, lack of CDX2 expression was a bad prognostic factor in MSS patients, but not in MSI. Our work suggests that combination of the consensual CMS classification and lack of CDX2 expression could be a useful marker to identify CMS4/CDX2-negative patients with a very poor prognosis. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  8. [Magnetic resonance semiotics of prostate cancer according to the PI-RADS classification. The clinical diagnostic algorithm of a study].

    Science.gov (United States)

    Korobkin, A S; Shariya, M A; Chaban, A S; Voskanvan, G A; Vinarov, A Z

    2015-01-01

    to elaborate the magnetic resonance imaging (MRI) signs of prostate cancer (PC) in accordance with the PI-RADS classification during multiparametric MRI (mpMRI). A total of 89 men aged 20 to 82 years were examined. A control group consisted of 8 (9%) healthy volunteers younger than 30 years of age with no urological history to obtain control images and MRI plots and 20 (22.5%) men aged 26-76 years, whose morphological changes were inflammatory and hyperplastic. The second age-matched group included 61 (68.5%) patients diagnosed with prostate cancer at morphological examination. A set of studies included digital rectal examination, serum prostate-specific antigen, and transrectal ultrasound-guided prostate biopsy. All the patients underwent prostate mpMRI applying a 3.0 T Achieva MRI scanner (Philips, the Netherlands). The patients have been found to have mpMRI signs that were typical of PC; its MRI semiotics according to the PI-RADS classification is presented. Each mpMRI procedure has been determined to be of importance and informative value in detecting PC. The comprehensive mpMRI approach to diagnosing PC improves the quality and diagnostic value of prostate MRI.

  9. A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification [version 2; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Jessica Roelands

    2018-02-01

    Full Text Available The increased application of high-throughput approaches in translational research has expanded the number of publicly available data repositories. Gathering additional valuable information contained in the datasets represents a crucial opportunity in the biomedical field. To facilitate and stimulate utilization of these datasets, we have recently developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB. In this note, we describe a curated compendium of 13 public datasets on human breast cancer, representing a total of 2142 transcriptome profiles. We classified the samples according to different immune based classification systems and integrated this information into the datasets. Annotated and harmonized datasets were uploaded to GXB. Study samples were categorized in different groups based on their immunologic tumor response profiles, intrinsic molecular subtypes and multiple clinical parameters. Ranked gene lists were generated based on relevant group comparisons. In this data note, we demonstrate the utility of GXB to evaluate the expression of a gene of interest, find differential gene expression between groups and investigate potential associations between variables with a specific focus on immunologic classification in breast cancer. This interactive resource is publicly available online at: http://breastcancer.gxbsidra.org/dm3/geneBrowser/list.

  10. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Directory of Open Access Journals (Sweden)

    Enrico Glaab

    Full Text Available Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  11. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Science.gov (United States)

    Glaab, Enrico; Bacardit, Jaume; Garibaldi, Jonathan M; Krasnogor, Natalio

    2012-01-01

    Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  12. Diagnostic serum vitamin D level is not a reliable prognostic factor for resectable breast cancer.

    Science.gov (United States)

    Mizrak Kaya, Dilsa; Ozturk, Bengi; Kubilay, Pinar; Onur, Handan; Utkan, Gungor; Cay Senler, Filiz; Alkan, Ali; Yerlikaya, Halis; Koksoy, Elif B; Karci, Ebru; Demirkazik, Ahmet; Akbulut, Hakan; Icli, Fikri

    2018-05-09

    There are inconsistent results about the effects of vitamin D level on breast cancer prognosis. We aimed to investigate the effect of vitamin D levels on the prognosis of resectable breast cancer in a patient group with highly different clothing styles. A total of 186 breast cancer patients were enrolled in the study. Vitamin D level was sufficient, insufficient and deficient in 17.2, 52.2 and 30.6% of patients, respectively. There was a significant relationship between clothing style and serum 25 (OH) D levels. We could not establish any relation between vitamin D level and tumor characteristics or survival. Vitamin D supplementation can be more important than diagnostic serum vitamin D level on prognosis of breast cancer.

  13. Mechanism-based classification and physical therapy management of persons with cancer pain: A prospective case series

    Directory of Open Access Journals (Sweden)

    Senthil P Kumar

    2013-01-01

    Full Text Available Context: Mechanism-based classification (MBC was established with current evidence and physical therapy (PT management methods for both cancer and for noncancer pain. Aims: This study aims to describe the efficacy of MBC-based PT in persons with primary complaints of cancer pain. Settings and Design: A prospective case series of patients who attended the physiotherapy department of a multispecialty university-affiliated teaching hospital. Material and Methods: A total of 24 adults (18 female, 6 male aged 47.5 ± 10.6 years, with primary diagnosis of heterogeneous group of cancer, chief complaints of chronic disabling pain were included in the study on their consent for participation The patients were evaluated and classified on the basis of five predominant mechanisms for pain. Physical therapy interventions were recommended based on mechanisms identified and home program was prescribed with a patient log to ensure compliance. Treatments were given in five consecutive weekly sessions for five weeks each of 30 min duration. Statistical Analysis Used: Pre-post comparisons for pain severity (PS and pain interference (PI subscales of Brief pain inventory-Cancer pain (BPI-CP and, European organization for research and treatment in cancer-quality of life questionnaire (EORTC-QLQ-C30 were done using Wilcoxon signed-rank test at 95% confidence interval using SPSS for Windows version 16.0 (SPSS Inc, Chicago, IL. Results: There were statistically significant ( P < 0.05 reduction in pain severity, pain interference and total BPI-CP scores, and the EORTC-QLQ-C30. Conclusion: MBC-PT was effective for improving BPI-CP and EORTC-QLQ-C30 scores in people with cancer pain.

  14. Mammographic casting-type calcification associated with small screen-detected invasive breast cancers: is this a reliable prognostic indicator?

    International Nuclear Information System (INIS)

    Peacock, C.; Given-Wilson, R.M.; Duffy, S.W.

    2004-01-01

    AIM: The aim of the present study was to establish whether mammographic casting-type calcification associated with small screen-detected invasive breast cancers is a reliable prognostic indicator. METHODS AND MATERIALS: We retrospectively identified 50 consecutive women diagnosed with an invasive cancer less than 15 mm who showed associated casting calcification on their screening mammograms. Controls were identified that showed no microcalcification and were matched for tumour size, histological type and lymph node status. A minimum of 5 years follow-up was obtained, noting recurrence and outcome. Conditional and unconditional logistic regression, depending on the outcome variable, were used to analyse the data, taking the matched design into account in both cases. Where small numbers prohibited the use of logistic regression, Fisher's exact test was used. RESULTS: Five deaths from breast cancer occurred out of the 50 cases, of which three were lymph node positive, two were lymph node negative and none were grade 3. None of the 78 control cases died from breast cancer. The difference in breast cancer death rates was significant by Fisher's exact test (p=0.02). Risk of recurrence was also significantly increased in the casting cases (OR=3.55, 95% CI 1.02-12.33, p=0.046). CONCLUSION: Although the overall outcome for small screen-detected breast cancers is good, our study suggests that casting calcification is a poorer prognostic factor. The advantage of a mammographic feature as an independent prognostic indicator lies in early identification of high-risk patients, allowing optimization of management

  15. Breast Cancer Survival Defined by the ER/PR/HER2 Subtypes and a Surrogate Classification according to Tumor Grade and Immunohistochemical Bio markers

    International Nuclear Information System (INIS)

    Parise, C. A.; Caggiano, V.

    2014-01-01

    ER, PR, and HER2 are routinely available in breast cancer specimens. The purpose of this study is to contrast breast cancer-specific survival for the eight ER/PR/HER2 subtypes with survival of an immunohistochemical surrogate for the molecular subtype based on the ER/PR/HER2 subtypes and tumor grade. Methods. We identified 123,780 cases of stages 1-3 primary female invasive breast cancer from California Cancer Registry. The surrogate classification was derived using ER/PR/HER2 and tumor grade. Kaplan-Meier survival analysis and Cox proportional hazards modeling were used to assess differences in survival and risk of mortality for the ER/PR/HER2 subtypes and surrogate classification within each stage. Results. The luminal B/HER2− surrogate classification had a higher risk of mortality than the luminal B/HER2+ for all stages of disease. There was no difference in risk of mortality between the ER+/PR+/HER2− and ER+/PR+/HER2+ in stage 3. With one exception in stage 3, the ER-negative subtypes all had an increased risk of mortality when compared with the ER-positive subtypes. Conclusions. Assessment of survival using ER/PR/HER2 illustrates the heterogeneity of HER2+ subtypes. The surrogate classification provides clear separation in survival and adjusted mortality but underestimates the wide variability within the subtypes that make up the classification.

  16. Breast Cancer Survival Defined by the ER/PR/HER2 Subtypes and a Surrogate Classification according to Tumor Grade and Immunohistochemical Biomarkers

    Directory of Open Access Journals (Sweden)

    Carol A. Parise

    2014-01-01

    Full Text Available Introduction. ER, PR, and HER2 are routinely available in breast cancer specimens. The purpose of this study is to contrast breast cancer-specific survival for the eight ER/PR/HER2 subtypes with survival of an immunohistochemical surrogate for the molecular subtype based on the ER/PR/HER2 subtypes and tumor grade. Methods. We identified 123,780 cases of stages 1–3 primary female invasive breast cancer from California Cancer Registry. The surrogate classification was derived using ER/PR/HER2 and tumor grade. Kaplan-Meier survival analysis and Cox proportional hazards modeling were used to assess differences in survival and risk of mortality for the ER/PR/HER2 subtypes and surrogate classification within each stage. Results. The luminal B/HER2− surrogate classification had a higher risk of mortality than the luminal B/HER2+ for all stages of disease. There was no difference in risk of mortality between the ER+/PR+/HER2− and ER+/PR+/HER2+ in stage 3. With one exception in stage 3, the ER-negative subtypes all had an increased risk of mortality when compared with the ER-positive subtypes. Conclusions. Assessment of survival using ER/PR/HER2 illustrates the heterogeneity of HER2+ subtypes. The surrogate classification provides clear separation in survival and adjusted mortality but underestimates the wide variability within the subtypes that make up the classification.

  17. Classification of Breast Cancer Subtypes by combining Gene Expression and DNA Methylation Data

    DEFF Research Database (Denmark)

    List, Markus; Hauschild, Anne-Christin; Tan, Qihua

    2014-01-01

    expression data for hundreds of patients, the challenge is to extract a minimal optimal set of genes with good prognostic properties from a large bulk of genes making a moderate contribution to classification. Several studies have successfully applied machine learning algorithms to solve this so-called gene...... on the transcriptomic, but also on an epigenetic level. We compared so-called random forest derived classification models based on gene expression and methylation data alone, to a model based on the combined features and to a model based on the gold standard PAM50. We obtained bootstrap errors of 10...

  18. Assessing Unmet Information Needs of Breast Cancer Survivors: Exploratory Study of Online Health Forums Using Text Classification and Retrieval.

    Science.gov (United States)

    McRoy, Susan; Rastegar-Mojarad, Majid; Wang, Yanshan; Ruddy, Kathryn J; Haddad, Tufia C; Liu, Hongfang

    2018-05-15

    Patient education materials given to breast cancer survivors may not be a good fit for their information needs. Needs may change over time, be forgotten, or be misreported, for a variety of reasons. An automated content analysis of survivors' postings to online health forums can identify expressed information needs over a span of time and be repeated regularly at low cost. Identifying these unmet needs can guide improvements to existing education materials and the creation of new resources. The primary goals of this project are to assess the unmet information needs of breast cancer survivors from their own perspectives and to identify gaps between information needs and current education materials. This approach employs computational methods for content modeling and supervised text classification to data from online health forums to identify explicit and implicit requests for health-related information. Potential gaps between needs and education materials are identified using techniques from information retrieval. We provide a new taxonomy for the classification of sentences in online health forum data. 260 postings from two online health forums were selected, yielding 4179 sentences for coding. After annotation of data and training alternative one-versus-others classifiers, a random forest-based approach achieved F1 scores from 66% (Other, dataset2) to 90% (Medical, dataset1) on the primary information types. 136 expressions of need were used to generate queries to indexed education materials. Upon examination of the best two pages retrieved for each query, 12% (17/136) of queries were found to have relevant content by all coders, and 33% (45/136) were judged to have relevant content by at least one. Text from online health forums can be analyzed effectively using automated methods. Our analysis confirms that breast cancer survivors have many information needs that are not covered by the written documents they typically receive, as our results suggest that at most

  19. Clinical significance of combined detection of CYFRA21-1, NSE and CEA in classification and staging of patients with lung cancer

    International Nuclear Information System (INIS)

    Hu He; Li Yanhua; Liang Weida; Zhang Qin

    2011-01-01

    To explore clinical value of combined detection of CYFRA21-1, NSE and CEA in classification and staging of patients with lung cancer, the CYFRA21-1, NSE and CEA levels in pleural effusion in 330 patients with lung cancer and in 43 patients with benign were detected by the electrochemiluminescence. The results showed that CYFRA21-1, NSE and CEA levels in pleural effusion in patients with lung cancer group were significantly higher than that of in benign group (P<0.01). The positive rate of tumor markers in different pathological type lung cancer were different,which CYFRA21-1 positive rate in squamous cell cancer group was highest with 65.5%; CEA positive rate in glands cancer group was supreme with 65.0%; the NSE positive rate in differentiation cancer group was highest with 79.5%. The positive rate in three markers combined detection was higher than that in one item detection. The tumor marker levels in lung cancer were positively related with clinical staging. The higher of tumor marker levels and the more late of clinical staging, and the clinical III∼IV period was obviously higher than that I∼II period (P<0.05). The combined detection of CYFRA21-1, NSE and CEA may enhance the positive rate in lung cancer detection, and may have significant clinical value in the classification and staging of patients with lung cancer. (authors)

  20. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks | Center for Cancer Research

    Science.gov (United States)

    The purpose of this study was to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial neural networks (ANNs). We trained the ANNs using the small, round blue-cell tumors (SRBCTs) as a model. These cancers belong to four distinct diagnostic categories and often present diagnostic dilemmas in

  1. The 2016 revision of the World Health Organization classification of lymphoid neoplasms | Center for Cancer Research

    Science.gov (United States)

    A revision of the nearly 8-year-old World Health Organization classification of the lymphoid neoplasms and the accompanying monograph is being published. It reflects a consensus among hematopathologists, geneticists, and clinicians regarding both updates to current entities as well as the addition of a limited number of new provisional entities.

  2. Latent structure and reliability analysis of the measure of body apperception: cross-validation for head and neck cancer patients.

    Science.gov (United States)

    Jean-Pierre, Pascal; Fundakowski, Christopher; Perez, Enrique; Jean-Pierre, Shadae E; Jean-Pierre, Ashley R; Melillo, Angelica B; Libby, Rachel; Sargi, Zoukaa

    2013-02-01

    Cancer and its treatments are associated with psychological distress that can negatively impact self-perception, psychosocial functioning, and quality of life. Patients with head and neck cancers (HNC) are particularly susceptible to psychological distress. This study involved a cross-validation of the Measure of Body Apperception (MBA) for HNC patients. One hundred and twenty-two English-fluent HNC patients between 20 and 88 years of age completed the MBA on a Likert scale ranging from "1 = disagree" to "4 = agree." We assessed the latent structure and internal consistency reliability of the MBA using Principal Components Analysis (PCA) and Cronbach's coefficient alpha (α), respectively. We determined convergent and divergent validities of the MBA using correlations with the Hospital Anxiety and Depression Scale (HADS), observer disfigurement rating, and patients' clinical and demographic variables. The PCA revealed a coherent set of items that explained 38 % of the variance. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.73 and the Bartlett's test of sphericity was statistically significant (χ (2) (28) = 253.64; p 0.05). The MBA is a valid and reliable screening measure of body apperception for HNC patients.

  3. Comparison of the prevalence of malnutrition diagnosis in head and neck, gastrointestinal and lung cancer patients by three classification methods

    Science.gov (United States)

    Platek, Mary E.; Popp KPf, Johann V.; Possinger, Candi S.; DeNysschen, Carol A.; Horvath, Peter; Brown, Jean K.

    2011-01-01

    Background Malnutrition is prevalent among patients within certain cancer types. There is lack of universal standard of care for nutrition screening, lack of agreement on an operational definition and on validity of malnutrition indicators. Objective In a secondary data analysis, we investigated prevalence of malnutrition diagnosis by three classification methods using data from medical records of a National Cancer Institute (NCI)-designated comprehensive cancer center. Interventions/Methods Records of 227 patients hospitalized during 1998 with head and neck, gastrointestinal or lung cancer were reviewed for malnutrition based on three methods: 1) physician diagnosed malnutrition related ICD-9 codes; 2) in-hospital nutritional assessment summary conducted by Registered Dietitians; and 3) body mass index (BMI). For patients with multiple admissions, only data from the first hospitalization was included. Results Prevalence of malnutrition diagnosis ranged from 8.8% based on BMI to approximately 26% of all cases based on dietitian assessment. Kappa coefficients between any methods indicated a weak (kappa=0.23, BMI and Dietitians and kappa=0.28, Dietitians and Physicians) to fair strength of agreement (kappa=0.38, BMI and Physicians). Conclusions Available methods to identify patients with malnutrition in an NCI designated comprehensive cancer center resulted in varied prevalence of malnutrition diagnosis. Universal standard of care for nutrition screening that utilizes validated tools is needed. Implications for Practice The Joint Commission on the Accreditation of Healthcare Organizations requires nutritional screening of patients within 24 hours of admission. For this purpose, implementation of a validated tool that can be used by various healthcare practitioners, including nurses, needs to be considered. PMID:21242767

  4. Validity and reliability testing of two instruments to measure breast cancer patients' concerns and information needs relating to radiation therapy

    Directory of Open Access Journals (Sweden)

    Kristjanson Linda J

    2007-11-01

    Full Text Available Abstract Background It is difficult to determine the most effective approach to patient education or tailor education interventions for patients in radiotherapy without tools that assess patients' specific radiation therapy information needs and concerns. Therefore, the aim of this study was to develop psychometrically sound tools to adequately determine the concerns and information needs of cancer patients during radiation therapy. Patients and Methods Two tools were developed to (1 determine patients concerns about radiation therapy (RT Concerns Scale and (2 ascertain patient's information needs at different time point during their radiation therapy (RT Information Needs Scale. Tools were based on previous research by the authors, published literature on breast cancer and radiation therapy and information behaviour research. Thirty-one breast cancer patients completed the questionnaire on one occasion and thirty participants completed the questionnaire on a second occasion to facilitate test-retest reliability. One participant's responses were removed from the analysis. Results were analysed for content validity, internal consistency and stability over time. Results Both tools demonstrated high internal consistency and adequate stability over time. The nine items in the RT Concerns Scale were retained because they met all pre-set psychometric criteria. Two items were deleted from the RT Information Needs Scale because they did not meet content validity criteria and did not achieve pre-specified criteria for internal consistency. This tool now contains 22 items. Conclusion This paper provides preliminary data suggesting that the two tools presented are reliable and valid and would be suitable for use in trials or in the clinical setting.

  5. The mammographic correlations of a new immunohistochemical classification of invasive breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Taneja, S. [Nottingham Breast Institute, City Hospital, Hucknall Road, Nottingham NG5 1PB (United Kingdom)], E-mail: sheeba_taneja@yahoo.co.uk; Evans, A.J. [Nottingham Breast Institute, City Hospital, Hucknall Road, Nottingham NG5 1PB (United Kingdom); Rakha, E.A.; Green, A.R. [Division of Pathology, School of Molecular Medical Sciences, Nottingham University Hospitals NHS Trust and University of Nottingham, Nottingham (United Kingdom); Ball, G. [Nottingham Trent University, School of Biomedical and Natural Sciences, Nottingham (United Kingdom); Ellis, I.O. [Division of Pathology, School of Molecular Medical Sciences, Nottingham University Hospitals NHS Trust and University of Nottingham, Nottingham (United Kingdom)

    2008-11-15

    Aim: Recent protein expression profiling of breast cancer has identified specific subtypes with clinical, biological, and therapeutic implications. The aim of this study was to identify the mammographic correlates of these novel molecular classes of invasive breast cancer. Materials and methods: The mammographic findings of 415 patients with operable breast cancer were correlated with the previously described protein expression classes identified by our group using immunohistochemical (IHC) assessment of a large series of breast cancer cases prepared as tissue microarrays (TMAs). Twenty-five proteins of known relevance in breast cancer were assessed, including hormone receptors, HER-2 status, basal and luminal markers, p53 expression, and E-cadherin. Results: The mammographic background pattern and proportion of lesions that were mammographically occult were similar in all groups. Groups characterized by luminal and hormone receptor positivity had significantly more spiculate lesions at mammography. Groups characterized by HER-2 overexpression, basal characteristics, and E-cadherin positivity had a significantly higher proportion of ill-defined masses. These findings were independent of histological grade. Conclusion: The mammographic features of breast cancer show significant correlation with molecular classes of invasive breast cancer identified by protein expression IHC analysis. The biological reasons for the findings and implications of these regarding imaging protocols require further study and may provide mechanisms for improvement of detection of these lesions.

  6. Can surgical oncologists reliably predict the likelihood for non-SLN metastases in breast cancer patients?

    NARCIS (Netherlands)

    Smidt, M.L.; Strobbe, L.J.; Groenewoud, J.M.M.; Wilt, G.J. van der; Zee, K.J. van; Wobbes, Th.

    2007-01-01

    BACKGROUND: In approximately 40% of the breast cancer patients with sentinel lymph node (SLN) metastases, additional nodal metastases are detected in the completion axillary lymph node dissection (cALND). The MSKCC nomogram can help to quantify a patient's individual risk for non-SLN metastases with

  7. Validity and Reliability of Psychosocial Factors Related to Breast Cancer Screening.

    Science.gov (United States)

    Zapka, Jane G.; And Others

    1991-01-01

    The construct validity of hypothesized survey items and data reduction procedures for selected psychosocial constructs frequently used in breast cancer screening research were investigated in telephone interviews with randomly selected samples of 1,184 and 903 women and a sample of 169 Hispanic clinic clients. Validity of the constructs is…

  8. Classification of follicular cell-derived thyroid cancer by global RNA profiling

    DEFF Research Database (Denmark)

    Rossing, Maria

    2013-01-01

    The incidence of thyroid cancer is increasing worldwide and thyroid nodules are a frequent clinical finding. Diagnosing follicular cell-derived cancers is, however, challenging both histopathologically and especially cytopathologically. The advent of high-throughput molecular technologies has...... profiling of follicular cell-derived thyroid cancers....... prompted many researchers to explore the transcriptome and, in recent years, also the miRNome in order to generate new molecular classifiers capable of classifying thyroid tumours more accurately than by conventional cytopathological and histopathological methods. This has led to a number of molecular...

  9. Value and reliability of findings from previous epidemiologic studies in the assessment of radiation-related cancer risks. Pt. 3

    International Nuclear Information System (INIS)

    Frasch, G.; Martignoni, K.

    1990-01-01

    The theories put forward here are predominantly based on pooled data from previous studies in a number of cohorts made up by mostly non-average individuals. These studies were carried out by various researchers and differed in procedures and aims. Factors of major importance to the validity and reliability of the conclusions drawn from this study are pointed out. In one chapter some light is thrown on factors known to bear a relation to the incidence of radiation-induced cancer of the breast, even though at present this can only very vaguely be described on a quantitative basis. These factors include fractionated dose regimens, pregnancies and parturitions, menarche, menopause, synergisms as well as secondary cancer of the breast. The available body of evidence suggests that exposure of each of 1 million women to a dose of 10 mGy (rad) can be linked with approx. 3 additional cases of mammary cancer reported on an average per year after the latency period. The fact that there is some statistical scatter around this value is chiefly attributable to age-related causes at the beginning of exposure. Differences in ethnic and cultural characteristics between the populations investigated appeared to be less important here. (orig./MG) [de

  10. Stratification and prognostic relevance of Jass’s molecular classification of colorectal cancer

    OpenAIRE

    Inti eZlobec; Inti eZlobec; Michel P Bihl; Anja eFoerster; Alex eRufle; Luigi eTerracciano; Alessandro eLugli; Alessandro eLugli

    2012-01-01

    Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into 5 subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: 302 patients were included in this study. Molecular analysis was performed for 5 CIMP-related pro...

  11. Towards precise classification of cancers based on robust gene functional expression profiles

    Directory of Open Access Journals (Sweden)

    Zhu Jing

    2005-03-01

    Full Text Available Abstract Background Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. The accumulated experiment evidence supports the assumption that genes express and perform their functions in modular fashions in cells. Therefore, there is an open space for development of the timely and relevant computational algorithms that use robust functional expression profiles towards precise classification of complex human diseases at the modular level. Results Inspired by the insight that genes act as a module to carry out a highly integrated cellular function, we thus define a low dimension functional expression profile for data reduction. After annotating each individual gene to functional categories defined in a proper gene function classification system such as Gene Ontology applied in this study, we identify those functional categories enriched with differentially expressed genes. For each functional category or functional module, we compute a summary measure (s for the raw expression values of the annotated genes to capture the overall activity level of the module. In this way, we can treat the gene expressions within a functional module as an integrative data point to replace the multiple values of individual genes. We compare the classification performance of decision trees based on functional expression profiles with the conventional gene expression profiles using four publicly available datasets, which indicates that precise classification of tumour types and improved interpretation can be achieved with the reduced functional expression profiles. Conclusion This modular approach is demonstrated to be a powerful alternative approach to analyzing high dimension microarray data and is robust to high measurement noise and intrinsic biological variance inherent in microarray data. Furthermore, efficient integration with current biological knowledge

  12. Classification of a palliative care population in a comprehensive cancer centre

    DEFF Research Database (Denmark)

    Benthien, K.S; Nordly, M.; Videbæk, K.

    2016-01-01

    PURPOSE: The purposes of the present study were to classify the palliative care population (PCP) in a comprehensive cancer centre by using information on antineoplastic treatment options and to analyse associations between socio-demographic factors, cancer diagnoses, treatment characteristics...... and receiving specialist palliative care (SPC). METHODS: This is a cross-sectional screening study of patients with cancer in the Department of Oncology, Rigshospitalet, Copenhagen University Hospital for 6 months. Patients were assessed to be included in the DOMUS study: a randomised controlled trial...... of accelerated transition to SPC at home (NCT01885637). The PCP was classified as patients with incurable cancer and limited or no antineoplastic treatment options. Patients with performance status 2-4 were further classified as the essential palliative care population (EPCP). RESULTS: During the study period...

  13. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    NARCIS (Netherlands)

    Sontrop, H.M.J.; Moerland, P.D.; Van den Ham, R.; Reinders, M.J.T.; Verhaegh, W.F.J.

    2009-01-01

    Background: Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for

  14. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    NARCIS (Netherlands)

    Sontrop, Herman M. J.; Moerland, Perry D.; van den Ham, René; Reinders, Marcel J. T.; Verhaegh, Wim F. J.

    2009-01-01

    Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the

  15. Decision Tree of Occupational Lung Cancer Using Classification and Regression Analysis

    Directory of Open Access Journals (Sweden)

    Tae-Woo Kim

    2010-12-01

    Conclusion: We found that exposure to lung carcinogens, latency and smoking history were predictive factors of approval for occupational lung cancer. Further studies for work-relatedness of occupational disease are needed.

  16. Development of a computer aided diagnosis model for prostate cancer classification on multi-parametric MRI

    Science.gov (United States)

    Alfano, R.; Soetemans, D.; Bauman, G. S.; Gibson, E.; Gaed, M.; Moussa, M.; Gomez, J. A.; Chin, J. L.; Pautler, S.; Ward, A. D.

    2018-02-01

    Multi-parametric MRI (mp-MRI) is becoming a standard in contemporary prostate cancer screening and diagnosis, and has shown to aid physicians in cancer detection. It offers many advantages over traditional systematic biopsy, which has shown to have very high clinical false-negative rates of up to 23% at all stages of the disease. However beneficial, mp-MRI is relatively complex to interpret and suffers from inter-observer variability in lesion localization and grading. Computer-aided diagnosis (CAD) systems have been developed as a solution as they have the power to perform deterministic quantitative image analysis. We measured the accuracy of such a system validated using accurately co-registered whole-mount digitized histology. We trained a logistic linear classifier (LOGLC), support vector machine (SVC), k-nearest neighbour (KNN) and random forest classifier (RFC) in a four part ROI based experiment against: 1) cancer vs. non-cancer, 2) high-grade (Gleason score ≥4+3) vs. low-grade cancer (Gleason score work will form the basis for a tool that enhances the radiologist's ability to detect malignancies, potentially improving biopsy guidance, treatment selection, and focal therapy for prostate cancer patients, maximizing the potential for cure and increasing quality of life.

  17. Classification of bladder cancer cell lines using Raman spectroscopy: a comparison of excitation wavelength, sample substrate and statistical algorithms

    Science.gov (United States)

    Kerr, Laura T.; Adams, Aine; O'Dea, Shirley; Domijan, Katarina; Cullen, Ivor; Hennelly, Bryan M.

    2014-05-01

    Raman microspectroscopy can be applied to the urinary bladder for highly accurate classification and diagnosis of bladder cancer. This technique can be applied in vitro to bladder epithelial cells obtained from urine cytology or in vivo as an optical biopsy" to provide results in real-time with higher sensitivity and specificity than current clinical methods. However, there exists a high degree of variability across experimental parameters which need to be standardised before this technique can be utilized in an everyday clinical environment. In this study, we investigate different laser wavelengths (473 nm and 532 nm), sample substrates (glass, fused silica and calcium fluoride) and multivariate statistical methods in order to gain insight into how these various experimental parameters impact on the sensitivity and specificity of Raman cytology.

  18. Clinical Usefulness of the VS Classification System Using Magnifying Endoscopy with Blue Laser Imaging for Early Gastric Cancer

    Directory of Open Access Journals (Sweden)

    Yoshikazu Yoshifuku

    2017-01-01

    Full Text Available Background. Blue laser imaging (BLI enables the acquisition of more information from tumors’ surfaces compared with white light imaging. Few reports confirm the validity of magnifying endoscopy (ME with BLI (ME-BLI for early gastric cancer (EGC. We aimed to assess the detailed endoscopic findings from EGCs using ME-BLI. Methods. We enrolled 386 consecutive patients with 417 EGCs that were diagnosed using ME-BLI and resected by endoscopic submucosal dissection. Using the VS classification system, three highly experienced endoscopists (HEEs and three less experienced endoscopists (LEEs evaluated the demarcation line (DL, microsurface pattern (MSP, and microvascular pattern (MVP within the endoscopic images of EGCs obtained using ME-BLI, assigning high-confidence (HC or low-confidence (LC levels. We investigated the clinicopathological features associated with each confidence level. Results. The HEEs’ evaluations determined the presence of DL in 99%, irregular MSP in 96%, and irregular MVP in 96%, and the LEEs’ evaluations determined the presence of DL in 98%, irregular MSP in 95%, and irregular MVP in 95% of the EGCs. When DL was present, HC levels in the Helicobacter pylori- (H. pylori- eradicated group and noneradicated group were evident in 65% and 89%, a difference that was significant (p<0.001. Conclusions. In the diagnosis of EGC with ME-BLI, the VS classification system with ME-NBI can be applied, but identifying the DL after H. pylori was difficult.

  19. An iterated Laplacian based semi-supervised dimensionality reduction for classification of breast cancer on ultrasound images.

    Science.gov (United States)

    Liu, Xiao; Shi, Jun; Zhou, Shichong; Lu, Minhua

    2014-01-01

    The dimensionality reduction is an important step in ultrasound image based computer-aided diagnosis (CAD) for breast cancer. A newly proposed l2,1 regularized correntropy algorithm for robust feature selection (CRFS) has achieved good performance for noise corrupted data. Therefore, it has the potential to reduce the dimensions of ultrasound image features. However, in clinical practice, the collection of labeled instances is usually expensive and time costing, while it is relatively easy to acquire the unlabeled or undetermined instances. Therefore, the semi-supervised learning is very suitable for clinical CAD. The iterated Laplacian regularization (Iter-LR) is a new regularization method, which has been proved to outperform the traditional graph Laplacian regularization in semi-supervised classification and ranking. In this study, to augment the classification accuracy of the breast ultrasound CAD based on texture feature, we propose an Iter-LR-based semi-supervised CRFS (Iter-LR-CRFS) algorithm, and then apply it to reduce the feature dimensions of ultrasound images for breast CAD. We compared the Iter-LR-CRFS with LR-CRFS, original supervised CRFS, and principal component analysis. The experimental results indicate that the proposed Iter-LR-CRFS significantly outperforms all other algorithms.

  20. Reliability of up-to-date risk factor between residential radon and lung cancer

    International Nuclear Information System (INIS)

    Tokonami, Shinji; Ishikawa, Tetsuo; Sorimachi, Atsuyuki; Kobayashi, Yosuke; Yoshinaga, Shinji; Quanfu, Sun; Akiba, Suminori

    2008-01-01

    Full text: The WHO launched an international radon project in January, 2005 because two major scientific articles on the residential-radon-and-lung-cancer risk have been published. Furthermore, the ICRP has just issued a new recommendation (Publ. 103). In the publication, radon issues have been mentioned using these references. They show that there is a significant correlation between radon exposures and lung cancer risks even with a somewhat lower radon concentration than an internationally recommended level (200 Bq m -3 ). In most cases, residential radon concentrations were measured by passive integrating radon monitors based on the alpha track detection techniques in their studies. We examined detection responses for the presence of thoron with some typical alpha track detectors (Kf K: Germany, Radtrak: USA and NRPB: UK), which were widely used in many epidemiological studies. In addition, we measured indoor radon and thoron concentrations in cave dwellings in Gansu Province, China, in which the National Cancer Institute (NCI) conducted a large-scale epidemiological study. The NCI concluded that there was also a significant correlation between the two aforementioned parameters, which was a similar value to recently acceptable one. However, our results on radon concentrations were obviously different from them because there was much thoron in that area. The present study demonstrates whether these risk factors are really correct throughout our data or not. Tokonami (2005) has pointed out that some of popular alpha track detectors are sensitive to thoron ( 220 Rn). This finding implies that radon readings will be overestimated and consequently may lead to biased estimates of lung cancer risk. The present study describes thoron interference on accurate radon measurements from the viewpoint of both experimental studies and field experiences. (author)

  1. Computer-aided diagnosis of lung cancer: the effect of training data sets on classification accuracy of lung nodules

    Science.gov (United States)

    Gong, Jing; Liu, Ji-Yu; Sun, Xi-Wen; Zheng, Bin; Nie, Sheng-Dong

    2018-02-01

    This study aims to develop a computer-aided diagnosis (CADx) scheme for classification between malignant and benign lung nodules, and also assess whether CADx performance changes in detecting nodules associated with early and advanced stage lung cancer. The study involves 243 biopsy-confirmed pulmonary nodules. Among them, 76 are benign, 81 are stage I and 86 are stage III malignant nodules. The cases are separated into three data sets involving: (1) all nodules, (2) benign and stage I malignant nodules, and (3) benign and stage III malignant nodules. A CADx scheme is applied to segment lung nodules depicted on computed tomography images and we initially computed 66 3D image features. Then, three machine learning models namely, a support vector machine, naïve Bayes classifier and linear discriminant analysis, are separately trained and tested by using three data sets and a leave-one-case-out cross-validation method embedded with a Relief-F feature selection algorithm. When separately using three data sets to train and test three classifiers, the average areas under receiver operating characteristic curves (AUC) are 0.94, 0.90 and 0.99, respectively. When using the classifiers trained using data sets with all nodules, average AUC values are 0.88 and 0.99 for detecting early and advanced stage nodules, respectively. AUC values computed from three classifiers trained using the same data set are consistent without statistically significant difference (p  >  0.05). This study demonstrates (1) the feasibility of applying a CADx scheme to accurately distinguish between benign and malignant lung nodules, and (2) a positive trend between CADx performance and cancer progression stage. Thus, in order to increase CADx performance in detecting subtle and early cancer, training data sets should include more diverse early stage cancer cases.

  2. Identification of immune cell infiltration in hematoxylin-eosin stained breast cancer samples: texture-based classification of tissue morphologies

    Science.gov (United States)

    Turkki, Riku; Linder, Nina; Kovanen, Panu E.; Pellinen, Teijo; Lundin, Johan

    2016-03-01

    The characteristics of immune cells in the tumor microenvironment of breast cancer capture clinically important information. Despite the heterogeneity of tumor-infiltrating immune cells, it has been shown that the degree of infiltration assessed by visual evaluation of hematoxylin-eosin (H and E) stained samples has prognostic and possibly predictive value. However, quantification of the infiltration in H and E-stained tissue samples is currently dependent on visual scoring by an expert. Computer vision enables automated characterization of the components of the tumor microenvironment, and texture-based methods have successfully been used to discriminate between different tissue morphologies and cell phenotypes. In this study, we evaluate whether local binary pattern texture features with superpixel segmentation and classification with support vector machine can be utilized to identify immune cell infiltration in H and E-stained breast cancer samples. Guided with the pan-leukocyte CD45 marker, we annotated training and test sets from 20 primary breast cancer samples. In the training set of arbitrary sized image regions (n=1,116) a 3-fold cross-validation resulted in 98% accuracy and an area under the receiver-operating characteristic curve (AUC) of 0.98 to discriminate between immune cell -rich and - poor areas. In the test set (n=204), we achieved an accuracy of 96% and AUC of 0.99 to label cropped tissue regions correctly into immune cell -rich and -poor categories. The obtained results demonstrate strong discrimination between immune cell -rich and -poor tissue morphologies. The proposed method can provide a quantitative measurement of the degree of immune cell infiltration and applied to digitally scanned H and E-stained breast cancer samples for diagnostic purposes.

  3. Study on Biopharmaceutics Classification and Oral Bioavailability of a Novel Multikinase Inhibitor NCE for Cancer Therapy

    Directory of Open Access Journals (Sweden)

    Yang Yang

    2014-04-01

    Full Text Available Specific biopharmaceutics classification investigation and study on phamacokinetic profile of a novel drug candidate (2-methylcarbamoyl-4-{4-[3- (trifluoromethyl benzamido] phenoxy} pyridinium 4-methylbenzenesulfonate monohydrate, NCE were carried out. Equilibrium solubility and intrinsic dissolution rate (IDR of NCE were estimated in different phosphate buffers. Effective intestinal permeability (Peff of NCE was determined using single-pass intestinal perfusion technique in rat duodenum, jejunum and ileum at three concentrations. Theophylline (high permeability and ranitidine (low permeability were also applied to access the permeability of NCE as reference compounds. The bioavailability after intragastrical and intravenous administration was measured in beagle dogs. The solubility of NCE in tested phosphate buffers was quite low with the maximum solubility of 81.73 μg/mL at pH 1.0. The intrinsic dissolution ratio of NCE was 1 × 10−4 mg·min−1·cm−2. The Peff value of NCE in all intestinal segments was more proximate to the high-permeability reference theophylline. Therefore, NCE was classified as class II drug according to Biopharmaceutics Classification System due to its low solubility and high intestinal permeability. In addition, concentration-dependent permeability was not observed in all the segments, indicating that there might be passive transportation for NCE. The absolute oral bioavailability of NCE in beagle dogs was 26.75%. Therefore, dissolution promotion will be crucial for oral formulation development and intravenous administration route will also be suggested for further NCE formulation development. All the data would provide a reference for biopharmaceutics classification research of other novel drug candidates.

  4. Study on biopharmaceutics classification and oral bioavailability of a novel multikinase inhibitor NCE for cancer therapy.

    Science.gov (United States)

    Yang, Yang; Fan, Chun-Mei; He, Xuan; Ren, Ke; Zhang, Jin-Kun; He, Ying-Ju; Yu, Luo-Ting; Zhao, Ying-Lan; Gong, Chang-Yang; Zheng, Yu; Song, Xiang-Rong; Zeng, Jun

    2014-04-25

    Specific biopharmaceutics classification investigation and study on phamacokinetic profile of a novel drug candidate (2-methylcarbamoyl-4-{4-[3- (trifluoromethyl) benzamido] phenoxy} pyridinium 4-methylbenzenesulfonate monohydrate, NCE) were carried out. Equilibrium solubility and intrinsic dissolution rate (IDR) of NCE were estimated in different phosphate buffers. Effective intestinal permeability (P(eff)) of NCE was determined using single-pass intestinal perfusion technique in rat duodenum, jejunum and ileum at three concentrations. Theophylline (high permeability) and ranitidine (low permeability) were also applied to access the permeability of NCE as reference compounds. The bioavailability after intragastrical and intravenous administration was measured in beagle dogs. The solubility of NCE in tested phosphate buffers was quite low with the maximum solubility of 81.73 μg/mL at pH 1.0. The intrinsic dissolution ratio of NCE was 1 × 10⁻⁴ mg·min⁻¹·cm⁻². The P(eff) value of NCE in all intestinal segments was more proximate to the high-permeability reference theophylline. Therefore, NCE was classified as class II drug according to Biopharmaceutics Classification System due to its low solubility and high intestinal permeability. In addition, concentration-dependent permeability was not observed in all the segments, indicating that there might be passive transportation for NCE. The absolute oral bioavailability of NCE in beagle dogs was 26.75%. Therefore, dissolution promotion will be crucial for oral formulation development and intravenous administration route will also be suggested for further NCE formulation development. All the data would provide a reference for biopharmaceutics classification research of other novel drug candidates.

  5. Reliability engineering

    International Nuclear Information System (INIS)

    Lee, Chi Woo; Kim, Sun Jin; Lee, Seung Woo; Jeong, Sang Yeong

    1993-08-01

    This book start what is reliability? such as origin of reliability problems, definition of reliability and reliability and use of reliability. It also deals with probability and calculation of reliability, reliability function and failure rate, probability distribution of reliability, assumption of MTBF, process of probability distribution, down time, maintainability and availability, break down maintenance and preventive maintenance design of reliability, design of reliability for prediction and statistics, reliability test, reliability data and design and management of reliability.

  6. Abridged republication of FIGO's staging classification for cancer of the ovary, fallopian tube, and peritoneum.

    Science.gov (United States)

    Prat, Jaime

    2015-10-01

    Ovarian, fallopian tube, and peritoneal cancers have a similar clinical presentation and are treated similarly, and current evidence supports staging all 3 cancers in a single system. The primary site (i.e. ovary, fallopian tube, or peritoneum) should be designated where possible. The histologic type should be recorded. Intraoperative rupture ("surgical spill") is IC1; capsule ruptured before surgery or tumor on ovarian or fallopian tube surface is IC2; and positive peritoneal cytology with or without rupture is IC3. The new staging includes a revision of stage III patients; assignment to stage IIIA1 is based on spread to the retroperitoneal lymph nodes without intraperitoneal dissemination. Extension of tumor from omentum to spleen or liver (stage IIIC) should be differentiated from isolated parenchymal metastases (stage IVB). © 2015 American Cancer Society.

  7. Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data

    Directory of Open Access Journals (Sweden)

    J. Sunil Rao

    2007-01-01

    Full Text Available In gene selection for cancer classifi cation using microarray data, we define an eigenvalue-ratio statistic to measure a gene’s contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalueratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.

  8. Application of SVM classifier in thermographic image classification for early detection of breast cancer

    Science.gov (United States)

    Oleszkiewicz, Witold; Cichosz, Paweł; Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz; Nowak, Robert M.; Okuniewski, Rafał

    2016-09-01

    This article presents the application of machine learning algorithms for early detection of breast cancer on the basis of thermographic images. Supervised learning model: Support vector machine (SVM) and Sequential Minimal Optimization algorithm (SMO) for the training of SVM classifier were implemented. The SVM classifier was included in a client-server application which enables to create a training set of examinations and to apply classifiers (including SVM) for the diagnosis and early detection of the breast cancer. The sensitivity and specificity of SVM classifier were calculated based on the thermographic images from studies. Furthermore, the heuristic method for SVM's parameters tuning was proposed.

  9. Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations

    Science.gov (United States)

    2014-01-01

    Introduction Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts. Methods An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147). Results The original training cohort reached a statistically significant difference (p risk groups. Conclusions Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments. PMID:24996446

  10. Classification and Diagnostic Output Prediction of Cancer Using Gene Expression Profiling and Supervised Machine Learning Algorithms

    DEFF Research Database (Denmark)

    Yoo, C.; Gernaey, Krist

    2008-01-01

    importance in the projection (VIP) information of the DPLS method. The power of the gene selection method and the proposed supervised hierarchical clustering method is illustrated on a three microarray data sets of leukemia, breast, and colon cancer. Supervised machine learning algorithms thus enable...

  11. Prognostic classification with laboratory parameters or imaging techniques in small-cell lung cancer

    NARCIS (Netherlands)

    de Jong, Wouter K.; Fidler, Vaclav; Groen, Harry J. M.

    PURPOSE: Our aim in this study was to compare prognostic models based on laboratory tests with a model including imaging information in small-cell lung cancer. PATIENTS AND METHODS: A retrospective analysis was performed on 156 consecutive patients. Three existing models based on laboratory tests

  12. Towards a molecular classification of colorectal cancer: The role of BRAF

    Directory of Open Access Journals (Sweden)

    Alexandra eThiel

    2013-11-01

    Full Text Available Different genetic aberrations of BRAF have been reported in various malignancies. BRAF is member of the RAS/RAF/MEK/ERK pathway and constitutive activity of this pathway can lead to increased cellular growth, invasion, and metastasis. The most common activating BRAF mutation in colorectal cancer is the V600E mutation, which is present in 5-15% of all tumors, and up to 80% of tumors with high microsatellite instability harbor this mutation. BRAF mutation is associated with proximal location, higher age, female gender, MSI-H, high grade, and mucinous histology, and is a marker of poor prognosis in colorectal cancer. The role of BRAF mutation as a predictive marker in respect of EGFR targeted treatments is controversial. BRAF V600 selective inhibitors have been approved for the treatment of V600 mutation positive metastatic melanoma, but the response rates in colorectal cancer are poor. This might be due to innate resistance mechanisms of colorectal cancers against the treatment solely targeting BRAF. To overcome resistance the combination of treatments, simultaneous inhibition of BRAF and MEK or PI3K/mTOR, might emerge as a successful therapeutic concept.

  13. Structural and reliability analysis of a patient satisfaction with cancer-related care measure: a multisite patient navigation research program study.

    Science.gov (United States)

    Jean-Pierre, Pascal; Fiscella, Kevin; Freund, Karen M; Clark, Jack; Darnell, Julie; Holden, Alan; Post, Douglas; Patierno, Steven R; Winters, Paul C

    2011-02-15

    Patient satisfaction is an important outcome measure of quality of cancer care and 1 of the 4 core study outcomes of the National Cancer Institute (NCI)-sponsored Patient Navigation Research Program to reduce race/ethnicity-based disparities in cancer care. There is no existing patient satisfaction measure that spans the spectrum of cancer-related care. The objective of this study was to develop a Patient Satisfaction With Cancer Care measure that is relevant to patients receiving diagnostic/therapeutic cancer-related care. The authors developed a conceptual framework, an operational definition of Patient Satisfaction With Cancer Care, and an item pool based on literature review, expert feedback, group discussion, and consensus. The 35-item Patient Satisfaction With Cancer Care measure was administered to 891 participants from the multisite NCI-sponsored Patient Navigation Research Program. Principal components analysis (PCA) was conducted for latent structure analysis. Internal consistency was assessed using Cronbach coefficient alpha (α). Divergent analysis was performed using correlation analyses between the Patient Satisfaction With Cancer Care, the Communication and Attitudinal Self-Efficacy-Cancer, and demographic variables. The PCA revealed a 1-dimensional measure with items forming a coherent set explaining 62% of the variance in patient satisfaction. Reliability assessment revealed high internal consistency (α ranging from 0.95 to 0.96). The Patient Satisfaction With Cancer Care demonstrated good face validity, convergent validity, and divergent validity, as indicated by moderate correlations with subscales of the Communication and Attitudinal Self-Efficacy-Cancer (all P .05). The Patient Satisfaction With Cancer Care is a valid tool for assessing satisfaction with cancer-related care for this sample. Copyright © 2010 American Cancer Society.

  14. A multigene mutation classification of 468 colorectal cancers reveals a prognostic role for APC

    Science.gov (United States)

    Schell, Michael J.; Yang, Mingli; Teer, Jamie K.; Lo, Fang Yin; Madan, Anup; Coppola, Domenico; Monteiro, Alvaro N. A.; Nebozhyn, Michael V.; Yue, Binglin; Loboda, Andrey; Bien-Willner, Gabriel A.; Greenawalt, Danielle M.; Yeatman, Timothy J.

    2016-01-01

    Colorectal cancer (CRC) is a highly heterogeneous disease, for which prognosis has been relegated to clinicopathologic staging for decades. There is a need to stratify subpopulations of CRC on a molecular basis to better predict outcome and assign therapies. Here we report targeted exome-sequencing of 1,321 cancer-related genes on 468 tumour specimens, which identified a subset of 17 genes that best classify CRC, with APC playing a central role in predicting overall survival. APC may assume 0, 1 or 2 truncating mutations, each with a striking differential impact on survival. Tumours lacking any APC mutation carry a worse prognosis than single APC mutation tumours; however, two APC mutation tumours with mutant KRAS and TP53 confer the poorest survival among all the subgroups examined. Our study demonstrates a prognostic role for APC and suggests that sequencing of APC may have clinical utility in the routine staging and potential therapeutic assignment for CRC. PMID:27302369

  15. Carcinoma de mama: novos conceitos na classificação Breast cancer: new concepts in classification

    Directory of Open Access Journals (Sweden)

    Daniella Serafin Couto Vieira

    2008-01-01

    and the basis for and improved breast cancer molecular taxonomy. Another important implication is that genetic profiling may lead to the identification of new target for therapy and better predictive markers are needed to guide difficult treatment decisions. Additionally, the current pathology classification system is suboptimal, since patients with identical tumor types and stage of disease present different responses to therapy and different overall outcomes. Basal breast tumor represents one of the most intriguing subtypes and is frequently associated with poor prognosis and absence of putative therapeutic targets. Then, the purpose of this review was to resume the most recent knowledge about the breast carcinoma classification and characterization.

  16. Validation of the RTOG recursive partitioning analysis (RPA) classification for small-cell lung cancer-only brain metastases

    International Nuclear Information System (INIS)

    Videtic, Gregory M.M.; Adelstein, David J.; Mekhail, Tarek M.; Rice, Thomas W.; Stevens, Glen H.J.; Lee, S.-Y.; Suh, John H.

    2007-01-01

    Purpose: Radiation Therapy Oncology Group (RTOG) developed a prognostic classification based on a recursive partitioning analysis (RPA) of patient pretreatment characteristics from three completed brain metastases randomized trials. Clinical trials for patients with brain metastases generally exclude small-cell lung cancer (SCLC) cases. We hypothesize that the RPA classes are valid in the setting of SCLC brain metastases. Methods and Materials: A retrospective review of 154 SCLC patients with brain metastases treated between April 1983 and May 2005 was performed. RPA criteria used for class assignment were Karnofsky performance status (KPS), primary tumor status (PT), presence of extracranial metastases (ED), and age. Results: Median survival was 4.9 months, with 4 patients (2.6%) alive at analysis. Median follow-up was 4.7 months (range, 0.3-40.3 months). Median age was 65 (range, 42-85 years). Median KPS was 70 (range, 40-100). Number of patients with controlled PT and no ED was 20 (13%) and with ED, 27 (18%); without controlled PT and ED, 34 (22%) and with ED, 73 (47%). RPA class distribution was: Class I: 8 (5%); Class II: 96 (62%); Class III: 51 (33%). Median survivals (in months) by RPA class were: Class I: 8.6; Class II: 4.2; Class III: 2.3 (p = 0.0023). Conclusions: Survivals for SCLC-only brain metastases replicate the results from the RTOG RPA classification. These classes are therefore valid for brain metastases from SCLC, support the inclusion of SCLC patients in future brain metastases trials, and may also serve as a basis for historical comparisons

  17. Reliability, Validity, and Minimal Detectable Change of Balance Evaluation Systems Test and Its Short Versions in Older Cancer Survivors: A Pilot Study.

    Science.gov (United States)

    Huang, Min H; Miller, Kara; Smith, Kristin; Fredrickson, Kayle; Shilling, Tracy

    2016-01-01

    Cancer is primarily a disease of older adults. About 77% of all cancers are diagnosed in persons aged 55 years and older. Cancer and its treatment can cause diverse sequelae impacting body systems underlying balance control. No study has examined the psychometric properties of balance assessment tools in older cancer survivors, presenting a significant challenge in the selection of outcome measures for clinicians treating this fast-growing population. This study aimed to determine the reliability, validity, and minimal detectable change (MDC) of the Balance Evaluation System Test (BESTest), Mini-Balance Evaluation Systems Test (Mini-BESTest), and Brief-Balance Evaluation Systems Test (Brief-BESTest) in community-dwelling older cancer survivors. This study was a cross-sectional design. Twenty breast and 8 prostate cancer survivors participated [age (SD) = 68.4 (8.13) years]. The BESTest and Activity-specific Balance Confidence (ABC) Scale were administered during the first session. Scores of Mini-BESTest and Brief-BESTest were extracted on the basis of the scores of BESTest. The BESTest was repeated within 1 to 2 weeks by the same rater to determine the test-retest reliability. For the analysis of the inter-rater reliability, 21 participants were randomly selected to be evaluated by 2 raters. A primary rater administered the test. The 2 raters independently and concurrently scored the performance of the participants. Each rater recorded the ratings separately on the scoring sheet. No discussion among the raters was allowed throughout the testing. Intraclass correlation coefficients (ICCs), standard error of measurement, minimal detectable change (MDC), and Bland-Altman plots were calculated. Concurrent validity of these balance tests with the ABC Scale was examined using the Spearman correlation. The BESTest, Mini-BESTest, and Brief-BESTest had high test-retest (ICC = 0.90-0.94) and interrater reliability (ICC = 0.86-0.96), small standard error of measurement (0

  18. A reliable Raman-spectroscopy-based approach for diagnosis, classification and follow-up of B-cell acute lymphoblastic leukemia

    Science.gov (United States)

    Managò, Stefano; Valente, Carmen; Mirabelli, Peppino; Circolo, Diego; Basile, Filomena; Corda, Daniela; de Luca, Anna Chiara

    2016-04-01

    Acute lymphoblastic leukemia type B (B-ALL) is a neoplastic disorder that shows high mortality rates due to immature lymphocyte B-cell proliferation. B-ALL diagnosis requires identification and classification of the leukemia cells. Here, we demonstrate the use of Raman spectroscopy to discriminate normal lymphocytic B-cells from three different B-leukemia transformed cell lines (i.e., RS4;11, REH, MN60 cells) based on their biochemical features. In combination with immunofluorescence and Western blotting, we show that these Raman markers reflect the relative changes in the potential biological markers from cell surface antigens, cytoplasmic proteins, and DNA content and correlate with the lymphoblastic B-cell maturation/differentiation stages. Our study demonstrates the potential of this technique for classification of B-leukemia cells into the different differentiation/maturation stages, as well as for the identification of key biochemical changes under chemotherapeutic treatments. Finally, preliminary results from clinical samples indicate high consistency of, and potential applications for, this Raman spectroscopy approach.

  19. Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations.

    Science.gov (United States)

    Wang, Dong-Yu; Done, Susan J; Mc Cready, David R; Leong, Wey L

    2014-07-04

    Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts. An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147). The original training cohort reached a statistically significant difference (p value of the triad classification was reproduced in the second independent internal cohort and the new external validation cohort. CMTC achieved even higher prognostic significance when all available patients were analyzed (n = 4,851). Oncogenic pathways Myc, E2F1, Ras and β-catenin were again implicated in the high-risk groups. Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments.

  20. Screening for Psychosocial Risk in Dutch Families of a Child With Cancer: Reliability, Validity, and Usability of the Psychosocial Assessment Tool

    NARCIS (Netherlands)

    Sint Nicolaas, Simone M.; Schepers, Sasja A.; Hoogerbrugge, Peter M.; Caron, Huib N.; Kaspers, Gertjan J. L.; van den Heuvel-Eibrink, Marry M.; Grootenhuis, Martha A.; Verhaak, Chris M.

    2016-01-01

    The Psychosocial Assessment Tool (PAT) was developed to screen for psychosocial risk in families of a child diagnosed with cancer. The current study is the first describing the cross-cultural adaptation, reliability, validity, and usability of the PAT in an European country (Dutch translation).   A

  1. Preoperative carcinoembryonic antigen and prognosis of colorectal cancer. An independent prognostic factor still reliable.

    Science.gov (United States)

    Li Destri, Giovanni; Rubino, Antonio Salvatore; Latino, Rosalia; Giannone, Fabio; Lanteri, Raffaele; Scilletta, Beniamino; Di Cataldo, Antonio

    2015-04-01

    To evaluate whether, in a sample of patients radically treated for colorectal carcinoma, the preoperative determination of the carcinoembryonic antigen (p-CEA) may have a prognostic value and constitute an independent risk factor in relation to disease-free survival. The preoperative CEA seems to be related both to the staging of colorectal neoplasia and to the patient's prognosis, although this-to date-has not been conclusively demonstrated and is still a matter of intense debate in the scientific community. This is a retrospective analysis of prospectively collected data. A total of 395 patients were radically treated for colorectal carcinoma. The preoperative CEA was statistically compared with the 2010 American Joint Committee on Cancer (AJCC) staging, the T and N parameters, and grading. All parameters recorded in our database were tested for an association with disease-free survival (DFS). Only factors significantly associated (P < 0.05) with the DFS were used to build multivariate stepwise forward logistic regression models to establish their independent predictors. A statistically significant relationship was found between p-CEA and tumor staging (P < 0.001), T (P < 0.001) and N parameters (P = 0.006). In a multivariate analysis, the independent prognostic factors found were: p-CEA, stages N1 and N2 according to AJCC, and G3 grading (grade). A statistically significant difference (P < 0.001) was evident between the DFS of patients with normal and high p-CEA levels. Preoperative CEA makes a pre-operative selection possible of those patients for whom it is likely to be able to predict a more advanced staging.

  2. Cancer classification through filtering progressive transductive support vector machine based on gene expression data

    Science.gov (United States)

    Lu, Xinguo; Chen, Dan

    2017-08-01

    Traditional supervised classifiers neglect a large amount of data which not have sufficient follow-up information, only work with labeled data. Consequently, the small sample size limits the advancement of design appropriate classifier. In this paper, a transductive learning method which combined with the filtering strategy in transductive framework and progressive labeling strategy is addressed. The progressive labeling strategy does not need to consider the distribution of labeled samples to evaluate the distribution of unlabeled samples, can effective solve the problem of evaluate the proportion of positive and negative samples in work set. Our experiment result demonstrate that the proposed technique have great potential in cancer prediction based on gene expression.

  3. Inflammation, Adenoma and Cancer: Objective Classification of Colon Biopsy Specimens with Gene Expression Signature

    Directory of Open Access Journals (Sweden)

    Orsolya Galamb

    2008-01-01

    Full Text Available Gene expression analysis of colon biopsies using high-density oligonucleotide microarrays can contribute to the understanding of local pathophysiological alterations and to functional classification of adenoma (15 samples, colorectal carcinomas (CRC (15 and inflammatory bowel diseases (IBD (14. Total RNA was extracted, amplified and biotinylated from frozen colonic biopsies. Genome-wide gene expression profile was evaluated by HGU133plus2 microarrays and verified by RT-PCR. We applied two independent methods for data normalization and used PAM for feature selection. Leave one-out stepwise discriminant analysis was performed. Top validated genes included collagenIVα1, lipocalin-2, calumenin, aquaporin-8 genes in CRC; CD44, met proto-oncogene, chemokine ligand-12, ADAM-like decysin-1 and ATP-binding casette-A8 genes in adenoma; and lipocalin-2, ubiquitin D and IFITM2 genes in IBD. Best differentiating markers between Ulcerative colitis and Crohn's disease were cyclin-G2; tripartite motif-containing-31; TNFR shedding aminopeptidase regulator-1 and AMICA. The discriminant analysis was able to classify the samples in overall 96.2% using 7 discriminatory genes (indoleamine-pyrrole-2,3-dioxygenase, ectodermal-neural cortex, TIMP3, fucosyltransferase-8, collectin sub-family member 12, carboxypeptidase D, and transglutaminase-2. Using routine biopsy samples we successfully performed whole genomic microarray analysis to identify discriminative signatures. Our results provide further insight into the pathophysiological background of colonic diseases. The results set up data warehouse which can be mined further.

  4. Pattern Recognition Approaches for Breast Cancer DCE-MRI Classification: A Systematic Review.

    Science.gov (United States)

    Fusco, Roberta; Sansone, Mario; Filice, Salvatore; Carone, Guglielmo; Amato, Daniela Maria; Sansone, Carlo; Petrillo, Antonella

    2016-01-01

    We performed a systematic review of several pattern analysis approaches for classifying breast lesions using dynamic, morphological, and textural features in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Several machine learning approaches, namely artificial neural networks (ANN), support vector machines (SVM), linear discriminant analysis (LDA), tree-based classifiers (TC), and Bayesian classifiers (BC), and features used for classification are described. The findings of a systematic review of 26 studies are presented. The sensitivity and specificity are respectively 91 and 83 % for ANN, 85 and 82 % for SVM, 96 and 85 % for LDA, 92 and 87 % for TC, and 82 and 85 % for BC. The sensitivity and specificity are respectively 82 and 74 % for dynamic features, 93 and 60 % for morphological features, 88 and 81 % for textural features, 95 and 86 % for a combination of dynamic and morphological features, and 88 and 84 % for a combination of dynamic, morphological, and other features. LDA and TC have the best performance. A combination of dynamic and morphological features gives the best performance.

  5. Clinical and Pathological Staging Validation in the Eighth Edition of the TNM Classification for Lung Cancer: Correlation between Solid Size on Thin-Section Computed Tomography and Invasive Size in Pathological Findings in the New T Classification.

    Science.gov (United States)

    Aokage, Keiju; Miyoshi, Tomohiro; Ishii, Genichiro; Kusumoto, Masahiro; Nomura, Shogo; Katsumata, Shinya; Sekihara, Keigo; Hishida, Tomoyuki; Tsuboi, Masahiro

    2017-09-01

    The aim of this study was to validate the new eighth edition of the TNM classification and to elucidate whether radiological solid size corresponds to pathological invasive size incorporated in this T factor. We analyzed the data on 1792 patients who underwent complete resection from 2003 to 2011 at the National Cancer Center Hospital East, Japan. We reevaluated preoperative thin-section computed tomography (TSCT) to determine solid size and pathological invasive size using the fourth edition of the WHO classification and reclassified them according to the new TNM classification. The discriminative power of survival curves by the seventh edition was compared with that by the eighth edition by using concordance probability estimates and Akaike's information criteria calculated using a univariable Cox regression model. Pearson's correlation coefficient was calculated to elucidate the correlation between radiological solid size using TSCT and pathological invasive size. The overall survival curves in the eighth edition were well distinct at each clinical and pathological stage. The 5-year survival rates of patients with clinical and pathological stage 0 newly defined were both 100%. The concordance probability estimate and Akaike's information criterion values of the eighth edition were higher than those of the seventh edition in discriminatory power for overall survival. Solid size on TSCT scan and pathological invasive size showed a positive linear relationship, and Pearson's correlation coefficient was calculated as 0.83, which indicated strong correlation. This TNM classification will be feasible regarding patient survival, and radiological solid size correlates significantly with pathological invasive size as a new T factor. Copyright © 2017 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

  6. Intra-rater and inter-rater reliability of a medical record abstraction study on transition of care after childhood cancer.

    Directory of Open Access Journals (Sweden)

    Micòl E Gianinazzi

    Full Text Available The abstraction of data from medical records is a widespread practice in epidemiological research. However, studies using this means of data collection rarely report reliability. Within the Transition after Childhood Cancer Study (TaCC which is based on a medical record abstraction, we conducted a second independent abstraction of data with the aim to assess a intra-rater reliability of one rater at two time points; b the possible learning effects between these two time points compared to a gold-standard; and c inter-rater reliability.Within the TaCC study we conducted a systematic medical record abstraction in the 9 Swiss clinics with pediatric oncology wards. In a second phase we selected a subsample of medical records in 3 clinics to conduct a second independent abstraction. We then assessed intra-rater reliability at two time points, the learning effect over time (comparing each rater at two time-points with a gold-standard and the inter-rater reliability of a selected number of variables. We calculated percentage agreement and Cohen's kappa.For the assessment of the intra-rater reliability we included 154 records (80 for rater 1; 74 for rater 2. For the inter-rater reliability we could include 70 records. Intra-rater reliability was substantial to excellent (Cohen's kappa 0-6-0.8 with an observed percentage agreement of 75%-95%. In all variables learning effects were observed. Inter-rater reliability was substantial to excellent (Cohen's kappa 0.70-0.83 with high agreement ranging from 86% to 100%.Our study showed that data abstracted from medical records are reliable. Investigating intra-rater and inter-rater reliability can give confidence to draw conclusions from the abstracted data and increase data quality by minimizing systematic errors.

  7. Prognostic Performance and Reproducibility of the 1973 and 2004/2016 World Health Organization Grading Classification Systems in Non-muscle-invasive Bladder Cancer: A European Association of Urology Non-muscle Invasive Bladder Cancer Guidelines Panel Systematic Review.

    Science.gov (United States)

    Soukup, Viktor; Čapoun, Otakar; Cohen, Daniel; Hernández, Virginia; Babjuk, Marek; Burger, Max; Compérat, Eva; Gontero, Paolo; Lam, Thomas; MacLennan, Steven; Mostafid, A Hugh; Palou, Joan; van Rhijn, Bas W G; Rouprêt, Morgan; Shariat, Shahrokh F; Sylvester, Richard; Yuan, Yuhong; Zigeuner, Richard

    2017-11-01

    Tumour grade is an important prognostic indicator in non-muscle-invasive bladder cancer (NMIBC). Histopathological classifications are limited by interobserver variability (reproducibility), which may have prognostic implications. European Association of Urology NMIBC guidelines suggest concurrent use of both 1973 and 2004/2016 World Health Organization (WHO) classifications. To compare the prognostic performance and reproducibility of the 1973 and 2004/2016 WHO grading systems for NMIBC. A systematic literature search was undertaken incorporating Medline, Embase, and the Cochrane Library. Studies were critically appraised for risk of bias (QUIPS). For prognosis, the primary outcome was progression to muscle-invasive or metastatic disease. Secondary outcomes were disease recurrence, and overall and cancer-specific survival. For reproducibility, the primary outcome was interobserver variability between pathologists. Secondary outcome was intraobserver variability (repeatability) by the same pathologist. Of 3593 articles identified, 20 were included in the prognostic review; three were eligible for the reproducibility review. Increasing tumour grade in both classifications was associated with higher disease progression and recurrence rates. Progression rates in grade 1 patients were similar to those in low-grade patients; progression rates in grade 3 patients were higher than those in high-grade patients. Survival data were limited. Reproducibility of the 2004/2016 system was marginally better than that of the 1973 system. Two studies on repeatability showed conflicting results. Most studies had a moderate to high risk of bias. Current grading classifications in NMIBC are suboptimal. The 1973 system identifies more aggressive tumours. Intra- and interobserver variability was slightly less in the 2004/2016 classification. We could not confirm that the 2004/2016 classification outperforms the 1973 classification in prediction of recurrence and progression. This article

  8. Measurement of the Inter-Rater Reliability Rate Is Mandatory for Improving the Quality of a Medical Database: Experience with the Paulista Lung Cancer Registry.

    Science.gov (United States)

    Lauricella, Leticia L; Costa, Priscila B; Salati, Michele; Pego-Fernandes, Paulo M; Terra, Ricardo M

    2018-06-01

    Database quality measurement should be considered a mandatory step to ensure an adequate level of confidence in data used for research and quality improvement. Several metrics have been described in the literature, but no standardized approach has been established. We aimed to describe a methodological approach applied to measure the quality and inter-rater reliability of a regional multicentric thoracic surgical database (Paulista Lung Cancer Registry). Data from the first 3 years of the Paulista Lung Cancer Registry underwent an audit process with 3 metrics: completeness, consistency, and inter-rater reliability. The first 2 methods were applied to the whole data set, and the last method was calculated using 100 cases randomized for direct auditing. Inter-rater reliability was evaluated using percentage of agreement between the data collector and auditor and through calculation of Cohen's κ and intraclass correlation. The overall completeness per section ranged from 0.88 to 1.00, and the overall consistency was 0.96. Inter-rater reliability showed many variables with high disagreement (>10%). For numerical variables, intraclass correlation was a better metric than inter-rater reliability. Cohen's κ showed that most variables had moderate to substantial agreement. The methodological approach applied to the Paulista Lung Cancer Registry showed that completeness and consistency metrics did not sufficiently reflect the real quality status of a database. The inter-rater reliability associated with κ and intraclass correlation was a better quality metric than completeness and consistency metrics because it could determine the reliability of specific variables used in research or benchmark reports. This report can be a paradigm for future studies of data quality measurement. Copyright © 2018 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

  9. Prognostic significance of visceral pleural invasion in the forthcoming (seventh) edition of TNM classification for lung cancer.

    Science.gov (United States)

    Shim, Hyo Sup; Park, In Kyu; Lee, Chang Young; Chung, Kyung Young

    2009-08-01

    The next revision to the TNM classification for lung cancer (the seventh edition) is scheduled to be released in 2009. However, the definition of visceral pleural invasion (VPI), which is a non-size-based T2 descriptor, still lacks in detail, and its validation is not included. We analyzed 1046 cases of non-small cell lung cancer (NSCLC) with T1, T2, or T3 diseases from 1990 to 2005, and subclassified into p0-p3 according to the degrees of pleural invasion. Survival analyses were performed using Kaplan-Meier method. Then, all patients were subdivided into nine groups according to tumor size and pleural invasion, and we compared survival differences, primarily focusing on T2a and T2b diseases according to the seventh edition. There was no survival difference between patients with p1 and p2, thus we regarded p1 or p2 as VPI. There was survival difference between two groups, which are expected to be classified as T2b. The behavior of tumors larger than 5cm but 7cm or less with VPI was similar to T3 tumors. VPI is a poor prognostic factor of NSCLC, and the penetration through the elastic layer of the visceral pleura regardless of its exposure on the pleural surface (pl and p2) should be defined as VPI. This study also indicates that VPI influences T stage dependent on tumor size, and it can be suggested that tumors of larger than 5cm but 7cm or less with VPI should be upgraded to T3 stage.

  10. Improving supervised classification accuracy using non-rigid multimodal image registration: detecting prostate cancer

    Science.gov (United States)

    Chappelow, Jonathan; Viswanath, Satish; Monaco, James; Rosen, Mark; Tomaszewski, John; Feldman, Michael; Madabhushi, Anant

    2008-03-01

    Computer-aided diagnosis (CAD) systems for the detection of cancer in medical images require precise labeling of training data. For magnetic resonance (MR) imaging (MRI) of the prostate, training labels define the spatial extent of prostate cancer (CaP); the most common source for these labels is expert segmentations. When ancillary data such as whole mount histology (WMH) sections, which provide the gold standard for cancer ground truth, are available, the manual labeling of CaP can be improved by referencing WMH. However, manual segmentation is error prone, time consuming and not reproducible. Therefore, we present the use of multimodal image registration to automatically and accurately transcribe CaP from histology onto MRI following alignment of the two modalities, in order to improve the quality of training data and hence classifier performance. We quantitatively demonstrate the superiority of this registration-based methodology by comparing its results to the manual CaP annotation of expert radiologists. Five supervised CAD classifiers were trained using the labels for CaP extent on MRI obtained by the expert and 4 different registration techniques. Two of the registration methods were affi;ne schemes; one based on maximization of mutual information (MI) and the other method that we previously developed, Combined Feature Ensemble Mutual Information (COFEMI), which incorporates high-order statistical features for robust multimodal registration. Two non-rigid schemes were obtained by succeeding the two affine registration methods with an elastic deformation step using thin-plate splines (TPS). In the absence of definitive ground truth for CaP extent on MRI, classifier accuracy was evaluated against 7 ground truth surrogates obtained by different combinations of the expert and registration segmentations. For 26 multimodal MRI-WMH image pairs, all four registration methods produced a higher area under the receiver operating characteristic curve compared to that

  11. Test-retest reliability of Brazilian version of Memorial Symptom Assessment Scale for assessing symptoms in cancer patients.

    Science.gov (United States)

    Menezes, Josiane Roberta de; Luvisaro, Bianca Maria Oliveira; Rodrigues, Claudia Fernandes; Muzi, Camila Drumond; Guimarães, Raphael Mendonça

    2017-01-01

    To assess the test-retest reliability of the Memorial Symptom Assessment Scale translated and culturally adapted into Brazilian Portuguese. The scale was applied in an interview format for 190 patients with various cancers type hospitalized in clinical and surgical sectors of the Instituto Nacional de Câncer José de Alencar Gomes da Silva and reapplied in 58 patients. Data from the test-retest were double typed into a Microsoft Excel spreadsheet and analyzed by the weighted Kappa. The reliability of the scale was satisfactory in test-retest. The weighted Kappa values obtained for each scale item had to be adequate, the largest item was 0.96 and the lowest was 0.69. The Kappa subscale was also evaluated and values were 0.84 for high frequency physic symptoms, 0.81 for low frequency physical symptoms, 0.81 for psychological symptoms, and 0.78 for Global Distress Index. High level of reliability estimated suggests that the process of measurement of Memorial Symptom Assessment Scale aspects was adequate. Avaliar a confiabilidade teste-reteste da versão traduzida e adaptada culturalmente para o português do Brasil do Memorial Symptom Assessment Scale. A escala foi aplicada em forma de entrevista em 190 pacientes com diversos tipos de câncer internados nos setores clínicos e cirúrgicos do Instituto Nacional de Câncer José de Alencar Gomes da Silva e reaplicada em 58 pacientes. Os dados dos testes-retestes foram inseridos num banco de dados por dupla digitação independente em Excel e analisados pelo Kappa ponderado. A confiabilidade da escala mostrou-se satisfatória nos testes-retestes. Os valores do Kappa ponderado obtidos para cada item da escala apresentaram-se adequados, sendo o maior item de 0,96 e o menor de 0,69. Também se avaliou o Kappa das subescalas, sendo de 0,84 para sintomas físicos de alta frequência, de 0,81 para sintomas físicos de baixa frequência, de 0,81 também para sintomas psicológicos, e de 0,78 para Índice Geral de Sofrimento

  12. Can-CSC-GBE: Developing Cost-sensitive Classifier with Gentleboost Ensemble for breast cancer classification using protein amino acids and imbalanced data.

    Science.gov (United States)

    Ali, Safdar; Majid, Abdul; Javed, Syed Gibran; Sattar, Mohsin

    2016-06-01

    Early prediction of breast cancer is important for effective treatment and survival. We developed an effective Cost-Sensitive Classifier with GentleBoost Ensemble (Can-CSC-GBE) for the classification of breast cancer using protein amino acid features. In this work, first, discriminant information of the protein sequences related to breast tissue is extracted. Then, the physicochemical properties hydrophobicity and hydrophilicity of amino acids are employed to generate molecule descriptors in different feature spaces. For comparison, we obtained results by combining Cost-Sensitive learning with conventional ensemble of AdaBoostM1 and Bagging. The proposed Can-CSC-GBE system has effectively reduced the misclassification costs and thereby improved the overall classification performance. Our novel approach has highlighted promising results as compared to the state-of-the-art ensemble approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Regularization strategies for hyperplane classifiers: application to cancer classification with gene expression data.

    Science.gov (United States)

    Andries, Erik; Hagstrom, Thomas; Atlas, Susan R; Willman, Cheryl

    2007-02-01

    Linear discrimination, from the point of view of numerical linear algebra, can be treated as solving an ill-posed system of linear equations. In order to generate a solution that is robust in the presence of noise, these problems require regularization. Here, we examine the ill-posedness involved in the linear discrimination of cancer gene expression data with respect to outcome and tumor subclasses. We show that a filter factor representation, based upon Singular Value Decomposition, yields insight into the numerical ill-posedness of the hyperplane-based separation when applied to gene expression data. We also show that this representation yields useful diagnostic tools for guiding the selection of classifier parameters, thus leading to improved performance.

  14. Detection of Gastric Cancer with Fourier Transform Infrared Spectroscopy and Support Vector Machine Classification

    Directory of Open Access Journals (Sweden)

    Qingbo Li

    2013-01-01

    Full Text Available Early diagnosis and early medical treatments are the keys to save the patients' lives and improve the living quality. Fourier transform infrared (FT-IR spectroscopy can distinguish malignant from normal tissues at the molecular level. In this paper, programs were made with pattern recognition method to classify unknown samples. Spectral data were pretreated by using smoothing and standard normal variate (SNV methods. Leave-one-out cross validation was used to evaluate the discrimination result of support vector machine (SVM method. A total of 54 gastric tissue samples were employed in this study, including 24 cases of normal tissue samples and 30 cases of cancerous tissue samples. The discrimination results of SVM method showed the sensitivity with 100%, specificity with 83.3%, and total discrimination accuracy with 92.2%.

  15. Constructing Support Vector Machine Ensembles for Cancer Classification Based on Proteomic Profiling

    Institute of Scientific and Technical Information of China (English)

    Yong Mao; Xiao-Bo Zhou; Dao-Ying Pi; You-Xian Sun

    2005-01-01

    In this study, we present a constructive algorithm for training cooperative support vector machine ensembles (CSVMEs). CSVME combines ensemble architecture design with cooperative training for individual SVMs in ensembles. Unlike most previous studies on training ensembles, CSVME puts emphasis on both accuracy and collaboration among individual SVMs in an ensemble. A group of SVMs selected on the basis of recursive classifier elimination is used in CSVME, and the number of the individual SVMs selected to construct CSVME is determined by 10-fold cross-validation. This kind of SVME has been tested on two ovarian cancer datasets previously obtained by proteomic mass spectrometry. By combining several individual SVMs, the proposed method achieves better performance than the SVME of all base SVMs.

  16. Clinical application of a microfluidic chip for immunocapture and quantification of circulating exosomes to assist breast cancer diagnosis and molecular classification.

    Science.gov (United States)

    Fang, Shimeng; Tian, Hongzhu; Li, Xiancheng; Jin, Dong; Li, Xiaojie; Kong, Jing; Yang, Chun; Yang, Xuesong; Lu, Yao; Luo, Yong; Lin, Bingcheng; Niu, Weidong; Liu, Tingjiao

    2017-01-01

    Increasing attention has been attracted by exosomes in blood-based diagnosis because cancer cells release more exosomes in serum than normal cells and these exosomes overexpress a certain number of cancer-related biomarkers. However, capture and biomarker analysis of exosomes for clinical application are technically challenging. In this study, we developed a microfluidic chip for immunocapture and quantification of circulating exosomes from small sample volume and applied this device in clinical study. Circulating EpCAM-positive exosomes were measured in 6 cases breast cancer patients and 3 healthy controls to assist diagnosis. A significant increase in the EpCAM-positive exosome level in these patients was detected, compared to healthy controls. Furthermore, we quantified circulating HER2-positive exosomes in 19 cases of breast cancer patients for molecular classification. We demonstrated that the exosomal HER2 expression levels were almost consistent with that in tumor tissues assessed by immunohistochemical staining. The microfluidic chip might provide a new platform to assist breast cancer diagnosis and molecular classification.

  17. Standardization of the Korean version of Mini-Mental Adjustment to Cancer (K-Mini-MAC) scale: factor structure, reliability and validity.

    Science.gov (United States)

    Kang, Jee In; Chung, Hyun Cheol; Kim, Se Joo; Choi, Hye Jin; Ahn, Joong Bae; Jeung, Hei-Cheul; Namkoong, Kee

    2008-06-01

    Mental adjustment and coping affect the physical outcome and survival as well as quality of life in cancer patients. The Mini-Mental Adjustment to Cancer (Mini-MAC) scale is a new refined, economical and reliable self-rating instrument measuring cognitive and behavioral responses to cancer. The aim of this study was to evaluate the psychometric properties of the Mini-MAC in Korean cancer patients. A total of 208 cancer patients recruited from the Yonsei Cancer Center were assessed with the Mini-MAC and the Hospital Anxiety and Depression Scale (HADS). Principal component analysis with varimax rotation for the Korean version of Mini-MAC (K-Mini-MAC) confirmed four factors. Three had psychometric properties similar to Helpless-Hopeless (HH), Anxious Preoccupation (AP) and Cognitive Avoidance (CA) of the original Mini-MAC. A novel factor, named Positive Attitude, included items of both Fatalism (FA) and Fighting Spirit (FS) from the original version. The five subscales from the original version (AP, HH, FS, FA and CA) and Positive Attitude had acceptable internal reliabilities in our sample (Cronbach's alpha coefficient 0.50-0.86; correlation coefficient of test-retest 0.68-0.88). For the validity, significant interscale correlation was observed in the original five subscales and Positive Attitude. Each subscale including Positive Attitude was also significantly related to Depression and Anxiety of HADS. As a whole, the K-Mini-MAC was a reliable, valid and acceptable tool for Korean cancer patients. These findings can provide information about the cross-cultural validity of Mini-MAC scale's factor structure. Cultural differences were also discussed.

  18. Reliability of Patient-Led Screening with the Malnutrition Screening Tool: Agreement between Patient and Health Care Professional Scores in the Cancer Care Ambulatory Setting.

    Science.gov (United States)

    Di Bella, Alexandra; Blake, Claire; Young, Adrienne; Pelecanos, Anita; Brown, Teresa

    2018-02-01

    The prevalence of malnutrition in patients with cancer is reported as high as 60% to 80%, and malnutrition is associated with lower survival, reduced response to treatment, and poorer functional status. The Malnutrition Screening Tool (MST) is a validated tool when administered by health care professionals; however, it has not been evaluated for patient-led screening. This study aims to assess the reliability of patient-led MST screening through assessment of inter-rater reliability between patient-led and dietitian-researcher-led screening and intra-rater reliability between an initial and a repeat patient screening. This cross-sectional study included 208 adults attending ambulatory cancer care services in a metropolitan teaching hospital in Queensland, Australia, in October 2016 (n=160 inter-rater reliability; n=48 intra-rater reliability measured in a separate sample). Primary outcome measures were MST risk categories (MST 0-1: not at risk, MST ≥2: at risk) as determined by screening completed by patients and a dietitian-researcher, patient test-retest screening, and patient acceptability. Percent and chance-corrected agreement (Cohen's kappa coefficient, κ) were used to determine agreement between patient-MST and dietitian-MST (inter-rater reliability) and MST completed by patient on admission to unit (patient-MSTA) and MST completed by patient 1 to 3 hours after completion of initial MST (patient-MSTB) (intra-rater reliability). High inter-rater reliability and intra-rater reliability were observed. Agreement between patient-MST and dietitian-MST was 96%, with "almost perfect" chance-adjusted agreement (κ=0.92, 95% CI 0.84 to 0.97). Agreement between repeated patient-MSTA and patient-MSTB was 94%, with "almost perfect" chance-adjusted agreement (κ=0.88, 95% CI 0.71 to 1.00). Based on dietitian-MST, 33% (n=53) of patients were identified as being at risk for malnutrition, and 40% of these reported not seeing a dietitian. Of 156 patients who provided

  19. [Evaluation and classification of drug therapy for breast cancer with bone-only metastasis].

    Science.gov (United States)

    Meng, X Y; Song, S T

    2017-03-23

    Skeleton is one of the most common metastatic organs for breast cancer, which has a better prognosis than visceral metastases. Bone-only metastasis was defined"non-measurable" in the RECIST (Response Evaluation Criteria in Solid Tumors) criteria, and was excluded by clinical trials. However, patients with bone-only metastasis are also in need of effective treatment to prolong survival. Endocrine therapy is the most important treatment for bone metastatic patients. Tumor response of bone metastases can be determined objectively by bone-window CT. Effective treatment should be continued if the symptoms are relieved or osteogenesis is observed. Osteoblastic change in bone-window CT is a sign of improvement after treatment. Endocrine therapy is proper for ER-positive patients. The patients with initial osteoblastic metastasis should not be treated with salvage chemotherapy or anti-HER2 treatment, only if osteolytic metastasis or visceral metastasis is observed. Bishosphonates are just auxiliary drugs in bone metastasis, which should not be abused.

  20. Classifying Classifications

    DEFF Research Database (Denmark)

    Debus, Michael S.

    2017-01-01

    This paper critically analyzes seventeen game classifications. The classifications were chosen on the basis of diversity, ranging from pre-digital classification (e.g. Murray 1952), over game studies classifications (e.g. Elverdam & Aarseth 2007) to classifications of drinking games (e.g. LaBrie et...... al. 2013). The analysis aims at three goals: The classifications’ internal consistency, the abstraction of classification criteria and the identification of differences in classification across fields and/or time. Especially the abstraction of classification criteria can be used in future endeavors...... into the topic of game classifications....

  1. IARC use of oxidative stress as key mode of action characteristic for facilitating cancer classification: Glyphosate case example illustrating a lack of robustness in interpretative implementation.

    Science.gov (United States)

    Bus, James S

    2017-06-01

    The International Agency for Research on Cancer (IARC) has formulated 10 key characteristics of human carcinogens to incorporate mechanistic data into cancer hazard classifications. The analysis used glyphosate as a case example to examine the robustness of IARC's determination of oxidative stress as "strong" evidence supporting a plausible cancer mechanism in humans. The IARC analysis primarily relied on 14 human/mammalian studies; 19 non-mammalian studies were uninformative of human cancer given the broad spectrum of test species and extensive use of formulations and aquatic testing. The mammalian studies had substantial experimental limitations for informing cancer mechanism including use of: single doses and time points; cytotoxic/toxic test doses; tissues not identified as potential cancer targets; glyphosate formulations or mixtures; technically limited oxidative stress biomarkers. The doses were many orders of magnitude higher than human exposures determined in human biomonitoring studies. The glyphosate case example reveals that the IARC evaluation fell substantially short of "strong" supporting evidence of oxidative stress as a plausible human cancer mechanism, and suggests that other IARC monographs relying on the 10 key characteristics approach should be similarly examined for a lack of robust data integration fundamental to reasonable mode of action evaluations. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Classification across gene expression microarray studies

    Directory of Open Access Journals (Sweden)

    Kuner Ruprecht

    2009-12-01

    Full Text Available Abstract Background The increasing number of gene expression microarray studies represents an important resource in biomedical research. As a result, gene expression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive and histological grade (low/high of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM, predictive analysis of microarrays (PAM, random forest (RF and k-top scoring pairs (kTSP. Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing. Results For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In

  3. Reliability Engineering

    International Nuclear Information System (INIS)

    Lee, Sang Yong

    1992-07-01

    This book is about reliability engineering, which describes definition and importance of reliability, development of reliability engineering, failure rate and failure probability density function about types of it, CFR and index distribution, IFR and normal distribution and Weibull distribution, maintainability and movability, reliability test and reliability assumption in index distribution type, normal distribution type and Weibull distribution type, reliability sampling test, reliability of system, design of reliability and functionality failure analysis by FTA.

  4. MRI interrReader and intra-reader reliabilities for assessing injury morphology and posterior ligamentous complex integrity of the spine according to the thoracolumbar injury classification system and severity score

    International Nuclear Information System (INIS)

    Lee, Guen Young; Lee, Joon Woo; Choi, Seung Woo; Lim, Hyun Jin; Sun, Hye Young; Kang, Yu Suhn; Kang, Heung Sik; Chai, Jee Won; Kim, Su Jin

    2015-01-01

    To evaluate spine magnetic resonance imaging (MRI) inter-reader and intra-reader reliabilities using the thoracolumbar injury classification system and severity score (TLICS) and to analyze the effects of reader experience on reliability and the possible reasons for discordant interpretations. Six radiologists (two senior, two junior radiologists, and two residents) independently scored 100 MRI examinations of thoracolumbar spine injuries to assess injury morphology and posterior ligamentous complex (PLC) integrity according to the TLICS. Inter-reader and intra-reader agreements were determined and analyzed according to the number of years of radiologist experience. Inter-reader agreement between the six readers was moderate (k = 0.538 for the first and 0.537 for the second review) for injury morphology and fair to moderate (k = 0.440 for the first and 0.389 for the second review) for PLC integrity. No significant difference in inter-reader agreement was observed according to the number of years of radiologist experience. Intra-reader agreements showed a wide range (k = 0.538-0.822 for injury morphology and 0.423-0.616 for PLC integrity). Agreement was achieved in 44 for the first and 45 for the second review about injury morphology, as well as in 41 for the first and 38 for the second review of PLC integrity. A positive correlation was detected between injury morphology score and PLC integrity. The reliability of MRI for assessing thoracolumbar spinal injuries according to the TLICS was moderate for injury morphology and fair to moderate for PLC integrity, which may not be influenced by radiologist' experience

  5. Integrated genomic and immunophenotypic classification of pancreatic cancer reveals three distinct subtypes with prognostic/predictive significance.

    Science.gov (United States)

    Wartenberg, Martin; Cibin, Silvia; Zlobec, Inti; Vassella, Erik; Eppenberger-Castori, Serenella M M; Terracciano, Luigi; Eichmann, Micha; Worni, Mathias; Gloor, Beat; Perren, Aurel; Karamitopoulou, Eva

    2018-04-16

    Current clinical classification of pancreatic ductal adenocarcinoma (PDAC) is unable to predict prognosis or response to chemo- or immunotherapy and does not take into account the host reaction to PDAC-cells. Our aim is to classify PDAC according to host- and tumor-related factors into clinically/biologically relevant subtypes by integrating molecular and microenvironmental findings. A well-characterized PDAC-cohort (n=110) underwent next-generation sequencing with a hotspot cancer panel, while Next-generation Tissue-Microarrays were immunostained for CD3, CD4, CD8, CD20, PD-L1, p63, hyaluronan-mediated motility receptor (RHAMM) and DNA mismatch-repair proteins. Previous data on FOXP3 were integrated. Immune-cell counts and protein expression were correlated with tumor-derived driver mutations, clinicopathologic features (TNM 8. 2017), survival and epithelial-mesenchymal-transition (EMT)-like tumor budding.  Results: Three PDAC-subtypes were identified: the "immune-escape" (54%), poor in T- and B-cells and enriched in FOXP3+Tregs, with high-grade budding, frequent CDKN2A- , SMAD4- and PIK3CA-mutations and poor outcome; the "immune-rich" (35%), rich in T- and B-cells and poorer in FOXP3+Tregs, with infrequent budding, lower CDKN2A- and PIK3CA-mutation rate and better outcome and a subpopulation with tertiary lymphoid tissue (TLT), mutations in DNA damage response genes (STK11, ATM) and the best outcome; and the "immune-exhausted" (11%) with immunogenic microenvironment and two subpopulations: one with PD-L1-expression and high PIK3CA-mutation rate and a microsatellite-unstable subpopulation with high prevalence of JAK3-mutations. The combination of low budding, low stromal FOXP3-counts, presence of TLTs and absence of CDKN2A-mutations confers significant survival advantage in PDAC-patients. Immune host responses correlate with tumor characteristics leading to morphologically recognizable PDAC-subtypes with prognostic/predictive significance. Copyright ©2018

  6. Distinct clinical outcomes of two CIMP-positive colorectal cancer subtypes based on a revised CIMP classification system.

    Science.gov (United States)

    Bae, Jeong Mo; Kim, Jung Ho; Kwak, Yoonjin; Lee, Dae-Won; Cha, Yongjun; Wen, Xianyu; Lee, Tae Hun; Cho, Nam-Yun; Jeong, Seung-Yong; Park, Kyu Joo; Han, Sae Won; Lee, Hye Seung; Kim, Tae-You; Kang, Gyeong Hoon

    2017-04-11

    Colorectal cancer (CRC) is a heterogeneous disease in terms of molecular carcinogenic pathways. Based on recent findings regarding the multiple serrated neoplasia pathway, we revised an eight-marker panel for a new CIMP classification system. 1370 patients who received surgical resection for CRCs were classified into three CIMP subtypes (CIMP-N: 0-4 methylated markers, CIMP-P1: 5-6 methylated markers and CIMP-P2: 7-8 methylated markers). Our findings were validated in a separate set of high-risk stage II or stage III CRCs receiving adjuvant fluoropyrimidine plus oxaliplatin (n=950). A total of 1287/62/21 CRCs cases were classified as CIMP-N/CIMP-P1/CIMP-P2, respectively. CIMP-N showed male predominance, distal location, lower T, N category and devoid of BRAF mutation, microsatellite instability (MSI) and MLH1 methylation. CIMP-P1 showed female predominance, proximal location, advanced TNM stage, mild decrease of CK20 and CDX2 expression, mild increase of CK7 expression, BRAF mutation, MSI and MLH1 methylation. CIMP-P2 showed older age, female predominance, proximal location, advanced T category, markedly reduced CK20 and CDX2 expression, rare KRAS mutation, high frequency of CK7 expression, BRAF mutation, MSI and MLH1 methylation. CIMP-N showed better 5-year cancer-specific survival (CSS; HR=0.47; 95% CI: 0.28-0.78) in discovery set and better 5-year relapse-free survival (RFS; HR=0.50; 95% CI: 0.29-0.88) in validation set compared with CIMP-P1. CIMP-P2 showed marginally better 5-year CSS (HR=0.28, 95% CI: 0.07-1.22) in discovery set and marginally better 5-year RFS (HR=0.21, 95% CI: 0.05-0.92) in validation set compared with CIMP-P1. CIMP subtypes classified using our revised system showed different clinical outcomes, demonstrating the heterogeneity of multiple serrated precursors of CIMP-positive CRCs.

  7. A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection

    Directory of Open Access Journals (Sweden)

    Abdullah M. Iliyasu

    2017-12-01

    Full Text Available A quantum hybrid (QH intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO method with the intuitionistic rationality of traditional fuzzy k-nearest neighbours (Fuzzy k-NN algorithm (known simply as the Q-Fuzzy approach is proposed for efficient feature selection and classification of cells in cervical smeared (CS images. From an initial multitude of 17 features describing the geometry, colour, and texture of the CS images, the QPSO stage of our proposed technique is used to select the best subset features (i.e., global best particles that represent a pruned down collection of seven features. Using a dataset of almost 1000 images, performance evaluation of our proposed Q-Fuzzy approach assesses the impact of our feature selection on classification accuracy by way of three experimental scenarios that are compared alongside two other approaches: the All-features (i.e., classification without prior feature selection and another hybrid technique combining the standard PSO algorithm with the Fuzzy k-NN technique (P-Fuzzy approach. In the first and second scenarios, we further divided the assessment criteria in terms of classification accuracy based on the choice of best features and those in terms of the different categories of the cervical cells. In the third scenario, we introduced new QH hybrid techniques, i.e., QPSO combined with other supervised learning methods, and compared the classification accuracy alongside our proposed Q-Fuzzy approach. Furthermore, we employed statistical approaches to establish qualitative agreement with regards to the feature selection in the experimental scenarios 1 and 3. The synergy between the QPSO and Fuzzy k-NN in the proposed Q-Fuzzy approach improves classification accuracy as manifest in the reduction in number cell features, which is crucial for effective cervical cancer detection and diagnosis.

  8. Normed kernel function-based fuzzy possibilistic C-means (NKFPCM) algorithm for high-dimensional breast cancer database classification with feature selection is based on Laplacian Score

    Science.gov (United States)

    Lestari, A. W.; Rustam, Z.

    2017-07-01

    In the last decade, breast cancer has become the focus of world attention as this disease is one of the primary leading cause of death for women. Therefore, it is necessary to have the correct precautions and treatment. In previous studies, Fuzzy Kennel K-Medoid algorithm has been used for multi-class data. This paper proposes an algorithm to classify the high dimensional data of breast cancer using Fuzzy Possibilistic C-means (FPCM) and a new method based on clustering analysis using Normed Kernel Function-Based Fuzzy Possibilistic C-Means (NKFPCM). The objective of this paper is to obtain the best accuracy in classification of breast cancer data. In order to improve the accuracy of the two methods, the features candidates are evaluated using feature selection, where Laplacian Score is used. The results show the comparison accuracy and running time of FPCM and NKFPCM with and without feature selection.

  9. The use of the SF-36 questionnaire in adult survivors of childhood cancer: evaluation of data quality, score reliability, and scaling assumptions

    Directory of Open Access Journals (Sweden)

    Winter David L

    2006-10-01

    Full Text Available Abstract Background The SF-36 has been used in a number of previous studies that have investigated the health status of childhood cancer survivors, but it never has been evaluated regarding data quality, scaling assumptions, and reliability in this population. As health status among childhood cancer survivors is being increasingly investigated, it is important that the measurement instruments are reliable, validated and appropriate for use in this population. The aim of this paper was to determine whether the SF-36 questionnaire is a valid and reliable instrument in assessing self-perceived health status of adult survivors of childhood cancer. Methods We examined the SF-36 to see how it performed with respect to (1 data completeness, (2 distribution of the scale scores, (3 item-internal consistency, (4 item-discriminant validity, (5 internal consistency, and (6 scaling assumptions. For this investigation we used SF-36 data from a population-based study of 10,189 adult survivors of childhood cancer. Results Overall, missing values ranged per item from 0.5 to 2.9 percent. Ceiling effects were found to be highest in the role limitation-physical (76.7% and role limitation-emotional (76.5% scales. All correlations between items and their hypothesised scales exceeded the suggested standard of 0.40 for satisfactory item-consistency. Across all scales, the Cronbach's alpha coefficient of reliability was found to be higher than the suggested value of 0.70. Consistent across all cancer groups, the physical health related scale scores correlated strongly with the Physical Component Summary (PCS scale scores and weakly with the Mental Component Summary (MCS scale scores. Also, the mental health and role limitation-emotional scales correlated strongly with the MCS scale score and weakly with the PCS scale score. Moderate to strong correlations with both summary scores were found for the general health perception, energy/vitality, and social functioning

  10. Validity, reliability and understanding of the EORTC-C30 and EORTC-BR23, quality of life questionnaires specific for breast cancer

    Directory of Open Access Journals (Sweden)

    Fernanda Alessandra Silva Michels

    2013-06-01

    Full Text Available Objective: To validate and assess reliability and understanding of the EORTC–C30 quality of life questionnaire and its breast cancer specific module, the EORTC-BR23. Methods: This study was conducted at the AC Camargo Cancer Hospital, São Paulo, Brazil. A total of 100 women diagnosed with breast cancer were interviewed. Internal consistency, confirmatory factorial analysis, convergent validity, construct validity and degree of understanding were examined. Reliability was assessed by comparison of means at times 1 and 2, inter-class coefficient and Bland-Altman graphics. Results: Cronbach’s alpha ranged from 0.72 to 0.86 for the EORTC-C30 and from 0.78 to 0.83 for the EORTC-BR23 questionnaire. Most questions were confirmed in the confirmatory factorial analysis. In the construct validity analysis, the questionnaires were capable of differentiating patients with or without lymphedema, apart from the symptom scales of both questionnaires. Both questionnaires presented a significant correlation in most domains of the SF-36, in the convergent validity analysis. Only a few criticisms were reported concerning questions, and the mean grade of understanding was high (C30 = 4.91 and BR23 = 4.89. The questionnaires presented good rates of reliability, with the exception of the functional scale of the C30 and the symptom scale of the BR23. Conclusions: The EORTC-C30 and EORTC-BR23 quality of life questionnaires were validated, presented good rates of reliability and are easily understood, allowing them to be used in Brazil to assess quality of life among women with breast cancer.

  11. Validity and reliability of the Japanese version of the Caregiver Reaction Assessment Scale (CRA-J) for community-dwelling cancer patients.

    Science.gov (United States)

    Misawa, Tomoyo; Miyashita, Mitsunori; Kawa, Masako; Abe, Koji; Abe, Mayumi; Nakayama, Yasuko; Given, Charles W

    2009-01-01

    The aim of this study was to validate the Caregiver Reaction Assessment (CRA) among caregivers of community-dwelling advanced cancer patients in Japan. A cross-sectional questionnaire was administered to advanced cancer patients and their caregivers who were cared for at day hospices and home palliative care services. We translated the CRA into Japanese, and then verified factor validity, reliability, construct validity, concurrent validity, and known groups' validity. To address construct and concurrent validity, we calculated Pearson's correlation coefficient between the Japanese version of the CRA and the Burden Index of Caregivers (BIC). To address known groups' validity, we used the t test or analysis of variance (ANOVA). A total of 57 caregivers participated in the study. Five factors were extracted (''impact on schedule,'' ''caregiver's self-esteem,'' ''lack of family support,'' ''impact on health,'' and ''impact on finances'') and reliability was good. Construct and concurrent validity among the subscales of the BIC were good. Regarding known groups validity, the subscale score of ''impact on schedule'' for the groups that cared 6 hours or more per day was higher than the other group (P = .04). The CRA-J is valid and reliable. This scale is useful for caregivers of cancer patients in Japan.

  12. The classification of lung cancers and their degree of malignancy by FTIR, PCA-LDA analysis, and a physics-based computational model.

    Science.gov (United States)

    Kaznowska, E; Depciuch, J; Łach, K; Kołodziej, M; Koziorowska, A; Vongsvivut, J; Zawlik, I; Cholewa, M; Cebulski, J

    2018-08-15

    Lung cancer has the highest mortality rate of all malignant tumours. The current effects of cancer treatment, as well as its diagnostics, are unsatisfactory. Therefore it is very important to introduce modern diagnostic tools, which will allow for rapid classification of lung cancers and their degree of malignancy. For this purpose, the authors propose the use of Fourier Transform InfraRed (FTIR) spectroscopy combined with Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA) and a physics-based computational model. The results obtained for lung cancer tissues, adenocarcinoma and squamous cell carcinoma FTIR spectra, show a shift in wavenumbers compared to control tissue FTIR spectra. Furthermore, in the FTIR spectra of adenocarcinoma there are no peaks corresponding to glutamate or phospholipid functional groups. Moreover, in the case of G2 and G3 malignancy of adenocarcinoma lung cancer, the absence of an OH groups peak was noticed. Thus, it seems that FTIR spectroscopy is a valuable tool to classify lung cancer and to determine the degree of its malignancy. Copyright © 2018 Elsevier B.V. All rights reserved.

  13. Measuring health-related quality of life in children with cancer living in mainland China: feasibility, reliability and validity of the Chinese mandarin version of PedsQL 4.0 Generic Core Scales and 3.0 Cancer Module

    Directory of Open Access Journals (Sweden)

    Ji Yi

    2011-11-01

    Full Text Available Abstract Background The Pediatric Quality of Life Inventory (PedsQL is widely used instrument to measure pediatric health-related quality of life (HRQOL for children aged 2 to 18 years. The purpose of the current study was to investigate the feasibility, reliability and validity of the Chinese mandarin version of the PedsQL 4.0 Generic Core Scales and 3.0 Cancer Module in a group of Chinese children with cancer. Methods The PedsQL 4.0 Genetic Core Scales and the PedsQL 3.0 Cancer Module were administered to children with cancer (aged 5-18 years and parents of such children (aged 2-18 years. For comparison, a survey on a demographically group-matched sample of the general population with children (aged 5-18 and parents of children (aged 2-18 years was conducted with the PedsQL 4.0 Genetic Core Scales. Result The minimal mean percentage of missing item responses (except the School Functioning scale supported the feasibility of the PedsQL 4.0 Generic Core Scales and 3.0 Cancer Module for Chinese children with cancer. Most of the scales showed satisfactory reliability with Cronbach's α of exceeding 0.70, and all scales demonstrated sufficient test-retest reliability. Assessing the clinical validity of the questionnaires, statistically significant difference was found between healthy children and children with cancer, and between children on-treatment versus off-treatment ≥12 months. Positive significant correlations were observed between the scores of the PedsQL 4.0 Generic Core Scale and the PedsQL 3.0 Cancer Module. Exploratory factor analysis demonstrated sufficient factorial validity. Moderate to good agreement was found between child self- and parent proxy-reports. Conclusion The findings support the feasibility, reliability and validity of the Chinese Mandarin version of PedsQL 4.0 Generic Core Scales and 3.0 Cancer Module in children with cancer living in mainland China.

  14. Using image analysis as a tool for assessment of prognostic and predictive biomarkers for breast cancer: How reliable is it?

    Directory of Open Access Journals (Sweden)

    Mark C Lloyd

    2010-01-01

    Full Text Available Background : Estrogen receptor (ER, progesterone receptor (PR and human epidermal growth factor receptor-2 (HER2 are important and well-established prognostic and predictive biomarkers for breast cancers and routinely tested on patient′s tumor samples by immunohistochemical (IHC study. The accuracy of these test results has substantial impact on patient management. A critical factor that contributes to the result is the interpretation (scoring of IHC. This study investigates how computerized image analysis can play a role in a reliable scoring, and identifies potential pitfalls with common methods. Materials and Methods : Whole slide images of 33 invasive ductal carcinoma (IDC (10 ER and 23 HER2 were scored by pathologist under the light microscope and confirmed by another pathologist. The HER2 results were additionally confirmed by fluorescence in situ hybridization (FISH. The scoring criteria were adherent to the guidelines recommended by the American Society of Clinical Oncology/College of American Pathologists. Whole slide stains were then scored by commercially available image analysis algorithms from Definiens (Munich, Germany and Aperio Technologies (Vista, CA, USA. Each algorithm was modified specifically for each marker and tissue. The results were compared with the semi-quantitative manual scoring, which was considered the gold standard in this study. Results : For HER2 positive group, each algorithm scored 23/23 cases within the range established by the pathologist. For ER, both algorithms scored 10/10 cases within range. The performance of each algorithm varies somewhat from the percentage of staining as compared to the pathologist′s reading. Conclusions : Commercially available computerized image analysis can be useful in the evaluation of ER and HER2 IHC results. In order to achieve accurate results either manual pathologist region selection is necessary, or an automated region selection tool must be employed. Specificity can

  15. Validity and Reliability of the U.S. National Cancer Institute's Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE)

    Science.gov (United States)

    Dueck, Amylou C.; Mendoza, Tito R.; Mitchell, Sandra A.; Reeve, Bryce B.; Castro, Kathleen M.; Rogak, Lauren J.; Atkinson, Thomas M.; Bennett, Antonia V.; Denicoff, Andrea M.; O'Mara, Ann M.; Li, Yuelin; Clauser, Steven B.; Bryant, Donna M.; Bearden, James D.; Gillis, Theresa A.; Harness, Jay K.; Siegel, Robert D.; Paul, Diane B.; Cleeland, Charles S.; Schrag, Deborah; Sloan, Jeff A.; Abernethy, Amy P.; Bruner, Deborah W.; Minasian, Lori M.; Basch, Ethan

    2016-01-01

    Importance Symptomatic adverse events (AEs) in cancer trials are currently reported by clinicians using the National Cancer Institute's (NCI) Common Terminology Criteria for Adverse Events (CTCAE). To integrate the patient perspective, the NCI developed a patient-reported outcomes version of the CTCAE (PRO-CTCAE) to capture symptomatic AEs directly from patients. Objective To assess the construct validity, test-retest reliability, and responsiveness of PRO-CTCAE items. Design Participants completed PRO-CTCAE items on tablet computers in clinic waiting rooms at two visits 1-6 weeks apart. A subset completed PRO-CTCAE items during an additional visit one business day after the first visit. Setting Nine U.S. cancer centers and community oncology practices. Participants 975 adult cancer patients undergoing outpatient chemotherapy and/or radiation enrolled between January 2011 and February 2012. Eligibility required participants to read English and be without clinically significant cognitive impairment. Main Outcome(s) and Measure(s) Primary comparators were clinician-reported Eastern Cooperative Oncology Group Performance Status (ECOG PS) and the European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire (QLQ-C30). Results 940/975 (96%) and 852/940 (91%) participants completed PRO-CTCAE items at each visit. 938/940 (99.8%) participants (53% female, median age 59, 32% high school education or less, 17% ECOG PS 2-4) reported having at least one symptom. All PRO-CTCAE items had at least one correlation in the expected direction with a QLQ-C30 scale (111/124 P<.05). Stronger correlations were seen between PRO-CTCAE items and conceptually-related QLQ-C30 domains. Scores for 94/124 PRO-CTCAE items were higher in the ECOG PS 2-4 versus 0-1 group (58/124 P<.05). Overall, 119/124 items met at least one construct validity criterion. Test-retest reliability was acceptable for 36/49 pre-specified items (median intra-class correlation coefficient

  16. International association for the study of lung cancer/american thoracic society/european respiratory society international multidisciplinary classification of lung adenocarcinoma.

    Science.gov (United States)

    Travis, William D; Brambilla, Elisabeth; Noguchi, Masayuki; Nicholson, Andrew G; Geisinger, Kim R; Yatabe, Yasushi; Beer, David G; Powell, Charles A; Riely, Gregory J; Van Schil, Paul E; Garg, Kavita; Austin, John H M; Asamura, Hisao; Rusch, Valerie W; Hirsch, Fred R; Scagliotti, Giorgio; Mitsudomi, Tetsuya; Huber, Rudolf M; Ishikawa, Yuichi; Jett, James; Sanchez-Cespedes, Montserrat; Sculier, Jean-Paul; Takahashi, Takashi; Tsuboi, Masahiro; Vansteenkiste, Johan; Wistuba, Ignacio; Yang, Pan-Chyr; Aberle, Denise; Brambilla, Christian; Flieder, Douglas; Franklin, Wilbur; Gazdar, Adi; Gould, Michael; Hasleton, Philip; Henderson, Douglas; Johnson, Bruce; Johnson, David; Kerr, Keith; Kuriyama, Keiko; Lee, Jin Soo; Miller, Vincent A; Petersen, Iver; Roggli, Victor; Rosell, Rafael; Saijo, Nagahiro; Thunnissen, Erik; Tsao, Ming; Yankelewitz, David

    2011-02-01

    Adenocarcinoma is the most common histologic type of lung cancer. To address advances in oncology, molecular biology, pathology, radiology, and surgery of lung adenocarcinoma, an international multidisciplinary classification was sponsored by the International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society. This new adenocarcinoma classification is needed to provide uniform terminology and diagnostic criteria, especially for bronchioloalveolar carcinoma (BAC), the overall approach to small nonresection cancer specimens, and for multidisciplinary strategic management of tissue for molecular and immunohistochemical studies. An international core panel of experts representing all three societies was formed with oncologists/pulmonologists, pathologists, radiologists, molecular biologists, and thoracic surgeons. A systematic review was performed under the guidance of the American Thoracic Society Documents Development and Implementation Committee. The search strategy identified 11,368 citations of which 312 articles met specified eligibility criteria and were retrieved for full text review. A series of meetings were held to discuss the development of the new classification, to develop the recommendations, and to write the current document. Recommendations for key questions were graded by strength and quality of the evidence according to the Grades of Recommendation, Assessment, Development, and Evaluation approach. The classification addresses both resection specimens, and small biopsies and cytology. The terms BAC and mixed subtype adenocarcinoma are no longer used. For resection specimens, new concepts are introduced such as adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) for small solitary adenocarcinomas with either pure lepidic growth (AIS) or predominant lepidic growth with ≤ 5 mm invasion (MIA) to define patients who, if they undergo complete resection, will have 100% or near 100

  17. Comparison of Reliability and Validity of the Breast Cancer depression anxiety stress scales (DASS- 21) with the Beck Depression Inventory-(BDI-II) and Hospital Anxiety and Depression Scale (HADS)

    OpenAIRE

    Bener A; Alsulaiman R; Doodson LG; El Ayoubi HR

    2016-01-01

    Background: No study has been conducted to determine the reliability and validity of the Depression, Anxiety and Stress Scale (DASS-21), Hospital Anxiety and Depression [HADS] and Beck Depression Inventory (BDI-II) among the Arab Breast Cancer population. Aim: The aim of this study was to compare the reliability and validity of the Depression, Anxiety, and Stress scale (DASS-21), the Beck Depression Inventory-(BDI-II) and Hospital Anxiety and Depression Scale (HADS) among Breast Cancer women ...

  18. Cross-Cultural Translation, Adaptation and Reliability of the Danish M. D. Andeson Dysphagia Inventory (MDADI) in Patients with Head and Neck Cancer.

    Science.gov (United States)

    Hajdú, Sara Fredslund; Plaschke, Christina Caroline; Johansen, Christoffer; Dalton, Susanne Oksbjerg; Wessel, Irene

    2017-08-01

    The objectives were to translate and culturally adapt the M.D. Anderson Dysphagia Inventory (MDADI) into Danish and subsequently test the reliability of the Danish version. The MDADI was translated into Danish and cross culturally adapted through cognitive interviews. The final version was test-retest evaluated in a group of head and neck cancer (HNC) patients who responded to the questionnaire twice with a mean of eight days apart. Interclass correlation coefficient, Cronbach's alpha, floor and ceiling effects, standard error of measurement and minimal detectable change were investigated. Fourteen patients were interviewed on the comprehensibility of the Danish MDADI, and all found the questionnaire meaningful, easy to understand, non-offensive and to include relevant aspects of dysphagia related to HNC. Sixty-four patients were included in the test-retest study. Especially, one item in the emotional scale (E7) appeared to be often misinterpreted, and ceiling effects were found in all four subdomains (global, emotional, functional and physical). The four subdomains and the composite score showed acceptable test-retest reliability and internal consistency in a Danish population of HNC patients. The Danish MDADI is reliable in terms of internal consistency and test-retest reproducibility and can be used in assessing the health-related quality of life in head and neck cancer patients with dysphagia.

  19. Psychometric validation and reliability analysis of a Spanish version of the patient satisfaction with cancer-related care measure: a patient navigation research program study.

    Science.gov (United States)

    Jean-Pierre, Pascal; Fiscella, Kevin; Winters, Paul C; Paskett, Electra; Wells, Kristen; Battaglia, Tracy

    2012-09-01

    Patient satisfaction (PS), a key measure of quality of cancer care, is a core study outcome of the multi-site National Cancer Institute-funded Patient Navigation Research Program. Despite large numbers of underserved monolingual Spanish speakers (MSS) residing in USA, there is no validated Spanish measure of PS that spans the whole spectrum of cancer-related care. The present study reports on the validation of the Patient Satisfaction with Cancer Care (PSCC) measure for Spanish (PSCC-Sp) speakers receiving diagnostic and therapeutic cancer-related care. Original PSCC items were professionally translated and back translated to ensure cultural appropriateness, meaningfulness, and equivalence. Then, the resulting 18-item PSCC-Sp measure was administered to 285 MSS. We evaluated latent structure and internal consistency of the PSCC-Sp using principal components analysis (PCA) and Cronbach coefficient alpha (α). We used correlation analyses to demonstrate divergence and convergence of the PSCC-Sp with a Spanish version of the Patient Satisfaction with Interpersonal Relationship with Navigator (PSN-I-Sp) measure and patients' demographics. The PCA revealed a coherent set of items that explicates 47% of the variance in PS. Reliability assessment demonstrated that the PSCC-Sp had high internal consistency (α = 0.92). The PSCC-Sp demonstrated good face validity and convergent and divergent validities as indicated by moderate correlations with the PSN-I-Sp (p = 0.003) and nonsignificant correlations with marital status and household income (all p(s) > 0.05). The PSCC-Sp is a valid and reliable measure of PS and should be tested in other MSS populations.

  20. Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification

    Science.gov (United States)

    2018-01-01

    One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes. PMID:29470520

  1. Comparison of the 6th and 7th editions of the UICC-AJCC TNM classification for esophageal cancer

    NARCIS (Netherlands)

    K. Talsma (Koen); P. van Hagen (Pieter); B.A. Grotenhuis (Brechtje); E.W. Steyerberg (Ewout); H.W. Tilanus (Hugo); J.J.B. van Lanschot (Jan); B.P.L. Wijnhoven (Bas)

    2012-01-01

    textabstractBackground. The new 7th edition of the Union for International Cancer Control-American Joint Committee on Cancer (UICC-AJCC) tumor, node, metastasis (TNM) staging system is the ratification of data-driven recommendations from the Worldwide Esophageal Cancer Collaboration database.

  2. The eighth TNM classification system for lung cancer: A consideration based on the degree of pleural invasion and involved neighboring structures.

    Science.gov (United States)

    Sakakura, Noriaki; Mizuno, Tetsuya; Kuroda, Hiroaki; Arimura, Takaaki; Yatabe, Yasushi; Yoshimura, Kenichi; Sakao, Yukinori

    2018-04-01

    The eighth tumor-node-metastasis (TNM) classification system for lung cancer has been used since January 2017 and must be applied to an individual institution's database. We analyzed pathological stage data of 2756 patients who underwent resection of non-small-cell lung cancer, particularly in terms of the degree of visceral pleural invasion and involved neighboring structures. Few patients had stage IIA disease (103, 4%); stratification between stages IB and IIA was insufficient (p = 0.129). When T2a tumors were divided into PL1 and PL2 subgroups based on the degree of pleural invasion, there was a significant prognostic difference between the subgroups (p consideration. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. [Assessment of functioning in patients with head and neck cancer based on the international classification of functioning, disability and health (ICF)].

    Science.gov (United States)

    Tschiesner, U

    2011-09-01

    The article approaches with the question how preservation of function after treatment of head and neck cancer (HNC) can be defined and measured across treatment approaches. On the basis of the "International Classification of Functioning, Disability and Health (ICF)" a series of efforts are summarized how all relevant aspects of the interdisciplinary team can be integrated into a common concept.Different efforts on the development, validation and implementation of ICF Core Sets for head and neck cancer (ICF-HNC) are discussed. The ICF-HNC covers organ-based problems with food ingestion, breathing, and speech, as well as psychosocial difficulties.Relationships between the ICF-HNC and well-established outcome measures are illustrated. This enables the user to integrate different aspects of functional outcome into a consolidated approach towards preservation/rehabilitation of functioning after HNC - applicable for a variety of treatment-approaches and health-professions. George Thieme Verlag KG Stuttgart · New York.

  4. Reliable and valid assessment of competence in endoscopic ultrasonography and fine-needle aspiration for mediastinal staging of non-small cell lung cancer.

    Science.gov (United States)

    Konge, L; Vilmann, P; Clementsen, P; Annema, J T; Ringsted, C

    2012-10-01

    Fine-needle aspiration (FNA) guided by endoscopic ultrasonography (EUS) is important in mediastinal staging of non-small cell lung cancer (NSCLC). Training standards and implementation strategies of this technique are currently under discussion. The aim of this study was to explore the reliability and validity of a newly developed EUS Assessment Tool (EUSAT) designed to measure competence in EUS - FNA for mediastinal staging of NSCLC. A total of 30 patients with proven or suspected NSCLC underwent EUS - FNA for mediastinal staging by three trainees and three experienced physicians. Their performances were assessed prospectively by three experts in EUS under direct observation and again 2 months later in a blinded fashion using digital video-recordings. Based on the assessments, intra-rater reliability, inter-rater reliability, and construct validity were explored. The intra-rater reliability was good (Cronbach's α = 0.80), but comparison of results based on direct observations and blinded video-recordings indicated a significant bias favoring consultants (P = 0.022). Inter-rater reliability was very good (Cronbach's α = 0.93). However, one rater assessing five procedures or two raters each assessing four procedures were necessary to secure a generalizability coefficient of 0.80. The assessment tool demonstrated construct validity by discriminating between trainees and experienced physicians (P = 0.034). Competency in mediastinal staging of NSCLC using EUS and EUS - FNA can be assessed in a reliable and valid way using the EUSAT assessment tool. Measuring and defining competency and training requirements could improve EUS quality and benefit patient care. © Georg Thieme Verlag KG Stuttgart · New York.

  5. Reliability and Validity of the Medical Outcomes Study Short Form-12 Version 2 (SF-12v2) in Adults with Non-Cancer Pain

    Science.gov (United States)

    Hayes, Corey J.; Bhandari, Naleen Raj; Kathe, Niranjan; Payakachat, Nalin

    2017-01-01

    Limited evidence exists on how non-cancer pain (NCP) affects an individual’s health-related quality of life (HRQoL). This study aimed to validate the Medical Outcomes Study Short Form-12 Version 2 (SF-12v2), a generic measure of HRQoL, in a NCP cohort using the Medical Expenditure Panel Survey Longitudinal Files. The SF Mental Component Summary (MCS12) and SF Physical Component Summary (PCS12) were tested for reliability (internal consistency and test-retest reliability) and validity (construct: convergent and discriminant; criterion: concurrent and predictive). A total of 15,716 patients with NCP were included in the final analysis. The MCS12 and PCS12 demonstrated high internal consistency (Cronbach’s alpha and Mosier’s alpha > 0.8), and moderate and high test-retest reliability, respectively (MCS12 intraclass correlation coefficient (ICC): 0.64; PCS12 ICC: 0.73). Both scales were significantly associated with a number of chronic conditions (p reliable and valid measure of HRQoL for patients with NCP. PMID:28445438

  6. Cross-Cultural Translation, Adaptation and Reliability of the Danish M. D. Andeson Dysphagia Inventory (MDADI) in Patients with Head and Neck Cancer

    DEFF Research Database (Denmark)

    Hajdú, Sara Fredslund; Plaschke, Christina Caroline; Johansen, Christoffer

    2017-01-01

    The objectives were to translate and culturally adapt the M.D. Anderson Dysphagia Inventory (MDADI) into Danish and subsequently test the reliability of the Danish version. The MDADI was translated into Danish and cross culturally adapted through cognitive interviews. The final version was test...... patients were interviewed on the comprehensibility of the Danish MDADI, and all found the questionnaire meaningful, easy to understand, non-offensive and to include relevant aspects of dysphagia related to HNC. Sixty-four patients were included in the test-retest study. Especially, one item....... The Danish MDADI is reliable in terms of internal consistency and test-retest reproducibility and can be used in assessing the health-related quality of life in head and neck cancer patients with dysphagia....

  7. Reliable categorisation of visual scoring of coronary artery calcification on low-dose CT for lung cancer screening: validation with the standard Agatston score

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Yi-Luan; Wu, Fu-Zong; Wang, Yen-Chi [Kaohsiung Veterans General Hospital, Department of Radiology, Kaohsiung 813 (China); National Yang Ming University, Faculty of Medicine, School of Medicine, Taipei (China); Ju, Yu-Jeng [National Taiwan University, Department of Psychology, Taipei (China); Mar, Guang-Yuan [Kaohsiung Veterans General Hospital, Division of Cardiology, Department of Medicine, Kaohsiung 813 (China); Chuo, Chiung-Chen [Kaohsiung Veterans General Hospital, Department of Radiology, Kaohsiung 813 (China); Lin, Huey-Shyan [Fooyin University, School of Nursing, Kaohsiung (China); Wu, Ming-Ting [Kaohsiung Veterans General Hospital, Department of Radiology, Kaohsiung 813 (China); National Yang Ming University, Faculty of Medicine, School of Medicine, Taipei (China); National Yang Ming University, Institute of Clinical Medicine, Taipei (China)

    2013-05-15

    To validate the reliability of the visual coronary artery calcification score (VCACS) on low-dose CT (LDCT) for concurrent screening of CAC and lung cancer. We enrolled 401 subjects receiving LDCT for lung cancer screening and ECG-gated CT for the Agatston score (AS). LDCT was reconstructed with 3- and 5-mm slice thickness (LDCT-3mm and LDCT-5mm respectively) for VCACS to obtain VCACS-3mm and VCACS-5mm respectively. After a training session comprising 32 cases, two observers performed four-scale VCACS (absent, mild, moderate, severe) of 369 data sets independently, the results were compared with four-scale AS (0, 1-100, 101-400, >400). CACs were present in 39.6 % (146/369) of subjects. The sensitivity of VCACS-3mm was higher than for VCACS-5mm (83.6 % versus 74.0 %). The median of AS of the 24 false-negative cases in VCACS-3mm was 2.3 (range 1.1-21.1). The false-negative rate for detecting AS {>=} 10 on LDCT-3mm was 1.9 %. VCACS-3mm had higher concordance with AS than VCACS-5mm (k = 0.813 versus k = 0.685). An extended test of VCACS-3mm for four junior observers showed high inter-observer reliability (intra-class correlation = 0.90) and good concordance with AS (k = 0.662-0.747). This study validated the reliability of VCACS on LDCT for lung cancer screening and showed that LDCT-3mm was more feasible than LDCT-5mm for CAD risk stratification. (orig.)

  8. Classification between normal and tumor tissues based on the pair-wise gene expression ratio

    International Nuclear Information System (INIS)

    Yap, YeeLeng; Zhang, XueWu; Ling, MT; Wang, XiangHong; Wong, YC; Danchin, Antoine

    2004-01-01

    Precise classification of cancer types is critically important for early cancer diagnosis and treatment. Numerous efforts have been made to use gene expression profiles to improve precision of tumor classification. However, reliable cancer-related signals are generally lacking. Using recent datasets on colon and prostate cancer, a data transformation procedure from single gene expression to pair-wise gene expression ratio is proposed. Making use of the internal consistency of each expression profiling dataset this transformation improves the signal to noise ratio of the dataset and uncovers new relevant cancer-related signals (features). The efficiency in using the transformed dataset to perform normal/tumor classification was investigated using feature partitioning with informative features (gene annotation) as discriminating axes (single gene expression or pair-wise gene expression ratio). Classification results were compared to the original datasets for up to 10-feature model classifiers. 82 and 262 genes that have high correlation to tissue phenotype were selected from the colon and prostate datasets respectively. Remarkably, data transformation of the highly noisy expression data successfully led to lower the coefficient of variation (CV) for the within-class samples as well as improved the correlation with tissue phenotypes. The transformed dataset exhibited lower CV when compared to that of single gene expression. In the colon cancer set, the minimum CV decreased from 45.3% to 16.5%. In prostate cancer, comparable CV was achieved with and without transformation. This improvement in CV, coupled with the improved correlation between the pair-wise gene expression ratio and tissue phenotypes, yielded higher classification efficiency, especially with the colon dataset – from 87.1% to 93.5%. Over 90% of the top ten discriminating axes in both datasets showed significant improvement after data transformation. The high classification efficiency achieved suggested

  9. Reliability and validity of a survey to measure bowel function and quality of life in long-term rectal cancer survivors.

    Science.gov (United States)

    Wendel, Christopher S; Grant, Marcia; Herrinton, Lisa; Temple, Larissa K F; Hornbrook, Mark C; McMullen, Carmit K; Bulkley, Joanna E; Altschuler, Andrea; Krouse, Robert S

    2014-12-01

    Examination of reliability and validity of a specialized health-related quality of life questionnaire for rectal cancer (RC) survivors (≥5 years post-diagnosis). We mailed 1,063 Kaiser Permanente (KP) RC survivors (313 ostomy and 750 anastomosis) a questionnaire containing the Modified City of Hope Quality of Life-Ostomy (mCOH-QOL-O), SF-12v2, Duke-UNC Functional Social Support Questionnaire (FSSQ), and Memorial Sloan-Kettering Cancer Center Bowel Function Index (BFI). We adapted certain BFI items for use by subjects with intestinal ostomies. We evaluated reliability for all instruments with inter-item correlations and Cronbach's alpha. We assessed construct validity only for the BFI in the ostomy group, because such use has not been reported. The overall response rate was 60.5 % (577 respondents/953 eligible). Compared with non-responders, participants were on average 2 years younger and more likely non-Hispanic white, resided in educationally non-deprived areas, and had KP membership through a group. The mCOH-QOL-O, SF-12, and FSSQ were found to be highly reliable for RC survivors. In the ostomy group, BFI Urgency/Soilage and Dietary subscales were found to be reliable, but Frequency was not. Factor analysis supported the construct of Urgency/Soilage and Dietary subscales in the ostomy group, although one item had a moderate correlation with all three factors. The BFI also demonstrated good concurrent validity with other instruments in the ostomy group. With possible exception of the BFI Frequency subscale in populations with ostomies, components of our survey can be used for the entire population of RC survivors, no matter whether they received anastomosis or ostomy.

  10. Insights into the classification of small GTPases

    Directory of Open Access Journals (Sweden)

    Dominik Heider

    2010-05-01

    Full Text Available Dominik Heider1, Sascha Hauke3, Martin Pyka4, Daniel Kessler21Department of Bioinformatics, Center for Medical Biotechnology, 2Institute of Cell Biology (Cancer Research, University of Duisburg-Essen, Essen, Germany; 3Institute of Computer Science, University of Münster, Münster, Germany; 4Interdisciplinary Center for Clinical Research, University Hospital of Münster, Münster, GermanyAbstract: In this study we used a Random Forest-based approach for an assignment of small guanosine triphosphate proteins (GTPases to specific subgroups. Small GTPases represent an important functional group of proteins that serve as molecular switches in a wide range of fundamental cellular processes, including intracellular transport, movement and signaling events. These proteins have further gained a special emphasis in cancer research, because within the last decades a huge variety of small GTPases from different subgroups could be related to the development of all types of tumors. Using a random forest approach, we were able to identify the most important amino acid positions for the classification process within the small GTPases superfamily and its subgroups. These positions are in line with the results of earlier studies and have been shown to be the essential elements for the different functionalities of the GTPase families. Furthermore, we provide an accurate and reliable software tool (GTPasePred to identify potential novel GTPases and demonstrate its application to genome sequences.Keywords: cancer, machine learning, classification, Random Forests, proteins

  11. CLASSIFICATION OF SEVERAL SKIN CANCER TYPES BASED ON AUTOFLUORESCENCE INTENSITY OF VISIBLE LIGHT TO NEAR INFRARED RATIO

    Directory of Open Access Journals (Sweden)

    Aryo Tedjo

    2009-12-01

    Full Text Available Skin cancer is a malignant growth on the skin caused by many factors. The most common skin cancers are Basal Cell Cancer (BCC and Squamous Cell Cancer (SCC. This research uses a discriminant analysis to classify some tissues of skin cancer based on criterion number of independent variables. An independent variable is variation of excitation light sources (LED lamp, filters, and sensors to measure Autofluorescence Intensity (IAF of visible light to near infrared (VIS/NIR ratio of paraffin embedded tissue biopsy from BCC, SCC, and Lipoma. From the result of discriminant analysis, it is known that the discriminant function is determined by 4 (four independent variables i.e., Blue LED-Red Filter, Blue LED-Yellow Filter, UV LED-Blue Filter, and UV LED-Yellow Filter. The accuracy of discriminant in classifying the analysis of three skin cancer tissues is 100 %.

  12. Evaluation of the Reliability of Electronic Medical Record Data in Identifying Comorbid Conditions among Patients with Advanced Non-Small Cell Lung Cancer

    International Nuclear Information System (INIS)

    Muehlenbein, C. E.; Lawson, A.; Pohl, G.; Hoverman, R.; Gruschkus, S. K.; Forsyth, M.; Chen, C.; Lopez, W.; Hartnett, H. J.

    2011-01-01

    Traditional methods for identifying co morbidity data in EMRs have relied primarily on costly and time-consuming manual chart review. The purpose of this study was to validate a strategy of electronically searching EMR data to identify co morbidities among cancer patients. Methods. Advanced stage NSCLC patients ( N = 2,513) who received chemotherapy from 7/1/2006 to 6/30/2008 were identified using iKnowMed, US Oncology's proprietary oncology-specific EMR system. EMR data were searched for documentation of co morbidities common to advanced stage cancer patients. The search was conducted by a series of programmatic queries on standardized information including concomitant illnesses, patient history, review of systems, and diagnoses other than cancer. The validity of the co morbidity information that we derived from the EMR search was compared to the chart review gold standard in a random sample of 450 patients for whom the EMR search yielded no indication of co morbidities. Negative predictive values were calculated. Results. The overall prevalence of co morbidities of 22%. Overall negative predictive value was 0.92 in the 450 patients randomly sampled patients (36 of 450 were found to have evidence of co morbidities on chart review). Conclusion. Results of this study suggest that efficient queries/text searches of EMR data may provide reliable data on co morbid conditions among cancer patients.

  13. Feasibility, reliability, and validity of the Pediatric Quality of Life Inventory ™ generic core scales, cancer module, and multidimensional fatigue scale in long-term adult survivors of pediatric cancer.

    Science.gov (United States)

    Robert, Rhonda S; Paxton, Raheem J; Palla, Shana L; Yang, Grace; Askins, Martha A; Joy, Shaini E; Ater, Joann L

    2012-10-01

    Most health-related quality of life assessments are designed for either children or adults and have not been evaluated for adolescent and young adult survivors of pediatric cancer. The objective of this study was to examine the feasibility, reliability, and validity of the Pediatric Quality of Life Inventory (PedsQL ™ Generic Core Scales, Cancer Module, and Multidimensional Fatigue Scale in adult survivors of pediatric cancer. Adult survivors (n = 64; Mean age 35 year old; >2 years after treatment) completed the PedsQL™ Generic Core Scales, Cancer Module, and Multidimensional Fatigue Scale. Feasibility was examined with floor and ceiling effects; and internal consistency was determined by Cronbach's coefficient alpha calculations. Inter-factor correlations were also assessed. Significant ceiling effects were observed for the scales of social function, nausea, procedural anxiety, treatment anxiety, and communication. Internal consistency for all subscales was within the recommended ranges (α ≥ 0.70). Moderate to strong correlations between most Cancer Module and Generic Core Scales (r = 0.25 to r = 0.76) and between the Multidimensional Fatigue Scale and Generic Core Scales (r = 0.37 to r = 0.73). The PedsQL™ Generic Core Scales, Cancer Module, and Multidimensional Fatigue Scale appear to be feasible for an older population of pediatric cancer survivors; however, some of the Cancer Module Scales (nausea, procedural/treatment anxiety, and communication) were deemed not relevant for long-term survivors. More information is needed to determine whether the issues addressed by these modules are meaningful to long-term adult survivors of pediatric cancers. Copyright © 2012 Wiley Periodicals, Inc.

  14. Tumor Size Evaluation according to the T Component of the Seventh Edition of the International Association for the Study of Lung Cancer's TNM Classification: Interobserver Agreement between Radiologists and Computer-Aided Diagnosis System in Patients with Lung Cancer

    International Nuclear Information System (INIS)

    Kim, Jin Kyoung; Chong, Se Min; Seo, Jae Seung; Lee, Sun Jin; Han, Heon

    2011-01-01

    To assess the interobserver agreement for tumor size evaluation between radiologists and the computer-aided diagnosis (CAD) system based on the 7th edition of the TNM classification by the International Association for the Study of Lung Cancer in patients with lung cancer. We evaluated 20 patients who underwent a lobectomy or pneumonectomy for primary lung cancer. The maximum diameter of each primary tumor was measured by two radiologists and a CAD system on CT, and was staged based on the 7th edition of the TNM classification. The CT size and T-staging of the primary tumors was compared with the pathologic size and staging and the variability in the sizes and T stages of primary tumors was statistically analyzed between each radiologist's measurement or CAD estimation and the pathologic results. There was no statistically significant interobserver difference for the CT size among the two radiologists, between pathologic and CT size estimated by the radiologists, and between pathologic and CT staging by the radiologists and CAD system. However, there was a statistically significant interobserver difference between pathologic size and the CT size estimated by the CAD system (p = 0.003). No significant differences were found in the measurement of tumor size among radiologists or in the assessment of T-staging by radiologists and the CAD system.

  15. Locus-Specific Databases and Recommendations to Strengthen Their Contribution to the Classification of Variants in Cancer Susceptibility Genes

    NARCIS (Netherlands)

    Greenblatt, Marc S.; Brody, Lawrence C.; Foulkes, William D.; Genuardi, Maurizio; Hofstra, Robert M. W.; Olivier, Magali; Plon, Sharon E.; Sijmons, Rolf H.; Sinilnikova, Olga; Spurdle, Amanda B.

    2008-01-01

    Locus-specific databases (LSDBs) are curated collections of sequence variants in genes associated with disease. LSDBs of cancer-related genes often serve as a critical resource to researchers, diagnostic laboratories, clinicians, and others in the cancer genetics community. LSDBs are poised to play

  16. Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer

    NARCIS (Netherlands)

    Hoadley, Katherine A.; Yau, Christina; Hinoue, Toshinori; Wolf, Denise M.; Lazar, Alexander J.; Drill, Esther; Shen, Ronglai; Taylor, Alison M.; Cherniack, Andrew D.; Thorsson, Vésteinn; Akbani, Rehan; Bowlby, Reanne; Wong, Christopher K.; Wiznerowicz, Maciej; Sanchez-Vega, Francisco; Robertson, A. Gordon; Schneider, Barbara G.; Lawrence, Michael S.; Noushmehr, Houtan; Malta, Tathiane M.; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher C.; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Parker, Joel S.; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. Jeffrey; Martin, Julie; Baudin, Eric; Bubley, Glenn; Bueno, Raphael; De Rienzo, Assunta; Richards, William G.; Kalkanis, Steven; Mikkelsen, Tom; Noushmehr, Houtan; Scarpace, Lisa; Girard, Nicolas; Aymerich, Marta; Campo, Elias; Giné, Eva; Guillermo, Armando López; Van Bang, Nguyen; Hanh, Phan Thi; Phu, Bui Duc; Tang, Yufang; Colman, Howard; Evason, Kimberley; Dottino, Peter R.; Martignetti, John A.; Gabra, Hani; Juhl, Hartmut; Akeredolu, Teniola; Stepa, Serghei; Hoon, Dave; Ahn, Keunsoo; Kang, Koo Jeong; Beuschlein, Felix; Breggia, Anne; Birrer, Michael; Bell, Debra; Borad, Mitesh; Bryce, Alan H.; Castle, Erik; Chandan, Vishal; Cheville, John; Copland, John A.; Farnell, Michael; Flotte, Thomas; Giama, Nasra; Ho, Thai; Kendrick, Michael; Kocher, Jean Pierre; Kopp, Karla; Moser, Catherine; Nagorney, David; O'Brien, Daniel; O'Neill, Brian Patrick; Patel, Tushar; Petersen, Gloria; Que, Florencia; Rivera, Michael; Roberts, Lewis; Smallridge, Robert; Smyrk, Thomas; Stanton, Melissa; Thompson, R. Houston; Torbenson, Michael; Yang, Ju Dong; Zhang, Lizhi; Brimo, Fadi; Ajani, Jaffer A.; Gonzalez, Ana Maria Angulo; Behrens, Carmen; Bondaruk, olanta; Broaddus, Russell; Czerniak, Bogdan; Esmaeli, Bita; Fujimoto, Junya; Gershenwald, Jeffrey; Guo, Charles; Lazar, Alexander J.; Logothetis, Christopher; Meric-Bernstam, Funda; Moran, Cesar; Ramondetta, Lois; Rice, David; Sood, Anil; Tamboli, Pheroze; Thompson, Timothy; Troncoso, Patricia; Tsao, Anne; Wistuba, Ignacio; Carter, Candace; Haydu, Lauren; Hersey, Peter; Jakrot, Valerie; Kakavand, Hojabr; Kefford, Richard; Lee, Kenneth; Long, Georgina; Mann, Graham; Quinn, Michael; Saw, Robyn; Scolyer, Richard; Shannon, Kerwin; Spillane, Andrew; Stretch, Jonathan; Synott, Maria; Thompson, John; Wilmott, James; Al-Ahmadie, Hikmat; Chan, Timothy A.; Ghossein, Ronald; Gopalan, Anuradha; Levine, Douglas A.; Reuter, Victor; Singer, Samuel; Singh, Bhuvanesh; Tien, Nguyen Viet; Broudy, Thomas; Mirsaidi, Cyrus; Nair, Praveen; Drwiega, Paul; Miller, Judy; Smith, Jennifer; Zaren, Howard; Park, Joong Won; Hung, Nguyen Phi; Kebebew, Electron; Linehan, W. Marston; Metwalli, Adam R.; Pacak, Karel; Pinto, Peter A.; Schiffman, Mark; Schmidt, Laura S.; Vocke, Cathy D.; Wentzensen, Nicolas; Worrell, Robert; Yang, Hannah; Moncrieff, Marc; Goparaju, Chandra; Melamed, Jonathan; Pass, Harvey; Botnariuc, Natalia; Caraman, Irina; Cernat, Mircea; Chemencedji, Inga; Clipca, Adrian; Doruc, Serghei; Gorincioi, Ghenadie; Mura, Sergiu; Pirtac, Maria; Stancul, Irina; Tcaciuc, Diana; Albert, Monique; Alexopoulou, Iakovina; Arnaout, Angel; Bartlett, John; Engel, Jay; Gilbert, Sebastien; Parfitt, Jeremy; Sekhon, Harman; Thomas, George; Rassl, Doris M.; Rintoul, Robert C.; Bifulco, Carlo; Tamakawa, Raina; Urba, Walter; Hayward, Nicholas; Timmers, Henri; Antenucci, Anna; Facciolo, Francesco; Grazi, Gianluca; Marino, Mirella; Merola, Roberta; de Krijger, Ronald; Gimenez-Roqueplo, Anne Paule; Piché, Alain; Chevalier, Simone; McKercher, Ginette; Birsoy, Kivanc; Barnett, Gene; Brewer, Cathy; Farver, Carol; Naska, Theresa; Pennell, Nathan A.; Raymond, Daniel; Schilero, Cathy; Smolenski, Kathy; Williams, Felicia; Morrison, Carl; Borgia, Jeffrey A.; Liptay, Michael J.; Pool, Mark; Seder, Christopher W.; Junker, Kerstin; Omberg, Larsson; Dinkin, Mikhail; Manikhas, George; Alvaro, Domenico; Bragazzi, Maria Consiglia; Cardinale, Vincenzo; Carpino, Guido; Gaudio, Eugenio; Chesla, David; Cottingham, Sandra; Dubina, Michael; Moiseenko, Fedor; Dhanasekaran, Renumathy; Becker, Karl Friedrich; Janssen, Klaus Peter; Slotta-Huspenina, Julia; Abdel-Rahman, Mohamed H.; Aziz, Dina; Bell, Sue; Cebulla, Colleen M.; Davis, Amy; Duell, Rebecca; Elder, J. Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Pinero, Edna M.Mora; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz; Stuart, Joshua M.; Benz, Christopher C.; Laird, Peter W.

    2018-01-01

    We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA

  17. Discovering a Reliable Heat-Shock Factor-1 Inhibitor to Treat Human Cancers: Potential Opportunity for Phytochemists

    Directory of Open Access Journals (Sweden)

    Murugesan Velayutham

    2018-04-01

    Full Text Available Heat-shock factor-1 (HSF-1 is an important transcription factor that regulates pathogenesis of many human diseases through its extensive transcriptional regulation. Especially, it shows pleiotropic effects in human cancer, and hence it has recently received increased attention of cancer researchers. After myriad investigations on HSF-1, the field has advanced to the phase where there is consensus that finding a potent and selective pharmacological inhibitor for this transcription factor will be a major break-through in the treatment of various human cancers. Presently, all reported inhibitors have their limitations, made evident at different stages of clinical trials. This brief account summarizes the advances with tested natural products as HSF-1 inhibitors and highlights the necessity of phytochemistry in this endeavor of discovering a potent pharmacological HSF-1 inhibitor.

  18. Development of a Korean version of the Cancer Therapy Satisfaction Questionnaire (CTSQ): cross-cultural adaptation, reliability, and validity.

    Science.gov (United States)

    Park, So Jeong; An, Soo Min; Kim, Se Hyun

    2013-03-01

    (1) To translate original English Cancer Therapy Satisfaction Questionnaire (CTSQ) into Korean and perform validation, (2) to compare CTSQ domains of expectations of therapy (ET), feelings about side effects (FSE), and satisfaction with therapy (SWT) by cancer therapy type. Cross-cultural adaptation was performed according to guidelines: translation, back translation, focus-group, and field test. We performed validation with internal consistency by Cronbach's alpha and construct validity by exploratory factor analysis (EFA) with varimax rotation method. We compared each CTSQ domain between traditional Korean Medicine (TKM) and integrative cancer therapy (ICT) of combining western and TKM by two-sample t test. Cross-cultural adaptation produced no major modifications in the items and domains. A total of 102 outpatients were participated. Mean age was 51.9 ± 12.4. Most were stage 4 (74.4 %) cancer. Mean scores of ET, FSE, and SWT were 81.2 ± 15.7, 79.5 ± 22.9, and 75.7 ± 14.8, respectively. Cronbach's alpha of ET, FSE, and SWT were 0.86, 0.78, and 0.74, respectively. EFA loaded items on the three domains, which is very close to that of the original CTSQ. ET and SWT was similar, but FSE was significantly higher in TKM than ICT (87.5 ± 19.3 vs. 74.9 ± 23.5; p = 0.0054). Cross-cultural adaptation was successful, and the adapted Korean CTSQ demonstrated good internal consistency and construct validity. Similar expectation and satisfaction was shown between the two types of therapy, but patient's reported feelings about side effects was significantly lower in patients receiving TKM than receiving ICT. Korean version of CTSQ can be used to evaluate Korean cancer patient's experiences receiving various cancer therapy types.

  19. Reliability and validity of the Malay Version of the Breast- Impact of Treatment Scale (MVBITS) in breast cancer women undergoing chemotherapy.

    Science.gov (United States)

    Zainal, Nor Zuraida; Shuib, Norley; Bustam, Anita Zarina; Sabki, Zuraida Ahmad; Guan, Ng Chong

    2013-01-01

    Body image dissatisfaction among breast cancer survivors has been associated with psychological stress resultant from breast cancer and resultant surgery. This study aimed to examine the psychometric properties of the Malay Version of the Breast-Impact of Treatment Scale (MVBITS) and to investigate the associations of retained factors with the Hospital Anxiety and Depression Scale (HADS) and the Rosenberg Self-Esteem Scale (RSES). The MVBITS was 'forward-backward' translated from English to Malay and then administered to 70 female breast cancer patients who came to the Oncology Clinic of University Malaya Medical Centre, Kuala Lumpur, Malaysia to undergo chemotherapy. Principal component analysis (PCA) with varimax rotation was performed to explore the factor structure of the MVBITS. Associations of retained factors were estimated with reference to Spearman correlation coefficients. The internal consistency reliability of MVBITS was good (Cronbach's alpha 0.945) and showed temporal stability over a 3-week period. Principal component analysis suggested two factors termed as 'Intrusion' and 'Avoidance' domains. These factors explained 70.3% of the variance. Factor 1 comprised the effects of breast cancer treatment on the emotion and thought, while Factor 2 informed attempts to limit exposure of the body to self or others. The Factor 1 of MVBITS was positively correlated with total, depression and anxiety sub-scores of HADS. Factor 2 was positively correlated with total and anxiety sub-scores of HADS. MVBITS was also positively correlated with the RSES scores. The results showed that the Malay Version of Breast-Impact of Treatment Scale possesses satisfactory psychometric properties suggesting that this instrument is appropriate for assessment of body change stress among female breast cancer patients in Malaysia.

  20. Validity and reliability testing of two instruments to measure breast cancer patients' concerns and information needs relating to radiation therapy

    International Nuclear Information System (INIS)

    Halkett, Georgia KB; Kristjanson, Linda J

    2007-01-01

    It is difficult to determine the most effective approach to patient education or tailor education interventions for patients in radiotherapy without tools that assess patients' specific radiation therapy information needs and concerns. Therefore, the aim of this study was to develop psychometrically sound tools to adequately determine the concerns and information needs of cancer patients during radiation therapy. Two tools were developed to (1) determine patients concerns about radiation therapy (RT Concerns Scale) and (2) ascertain patient's information needs at different time point during their radiation therapy (RT Information Needs Scale). Tools were based on previous research by the authors, published literature on breast cancer and radiation therapy and information behaviour research. Thirty-one breast cancer patients completed the questionnaire on one occasion and thirty participants completed the questionnaire on a second occasion to facilitate test-retest reliability. One participant's responses were removed from the analysis. Results were analysed for content validity, internal consistency and stability over time. Both tools demonstrated high internal consistency and adequate stability over time. The nine items in the RT Concerns Scale were retained because they met all pre-set psychometric criteria. Two items were deleted from the RT Information Needs Scale because they did not meet content validity criteria and did not achieve pre-specified criteria for internal consistency. This tool now contains 22 items. This paper provides preliminary data suggesting that the two tools presented are reliable and valid and would be suitable for use in trials or in the clinical setting

  1. Software reliability

    CERN Document Server

    Bendell, A

    1986-01-01

    Software Reliability reviews some fundamental issues of software reliability as well as the techniques, models, and metrics used to predict the reliability of software. Topics covered include fault avoidance, fault removal, and fault tolerance, along with statistical methods for the objective assessment of predictive accuracy. Development cost models and life-cycle cost models are also discussed. This book is divided into eight sections and begins with a chapter on adaptive modeling used to predict software reliability, followed by a discussion on failure rate in software reliability growth mo

  2. Mammogram classification scheme using 2D-discrete wavelet and local binary pattern for detection of breast cancer

    Science.gov (United States)

    Adi Putra, Januar

    2018-04-01

    In this paper, we propose a new mammogram classification scheme to classify the breast tissues as normal or abnormal. Feature matrix is generated using Local Binary Pattern to all the detailed coefficients from 2D-DWT of the region of interest (ROI) of a mammogram. Feature selection is done by selecting the relevant features that affect the classification. Feature selection is used to reduce the dimensionality of data and features that are not relevant, in this paper the F-test and Ttest will be performed to the results of the feature extraction dataset to reduce and select the relevant feature. The best features are used in a Neural Network classifier for classification. In this research we use MIAS and DDSM database. In addition to the suggested scheme, the competent schemes are also simulated for comparative analysis. It is observed that the proposed scheme has a better say with respect to accuracy, specificity and sensitivity. Based on experiments, the performance of the proposed scheme can produce high accuracy that is 92.71%, while the lowest accuracy obtained is 77.08%.

  3. Reliability and Validity of the Medical Outcomes Study Short Form-12 Version 2 (SF-12v2 in Adults with Non-Cancer Pain

    Directory of Open Access Journals (Sweden)

    Corey J. Hayes

    2017-04-01

    Full Text Available Limited evidence exists on how non-cancer pain (NCP affects an individual’s health-related quality of life (HRQoL. This study aimed to validate the Medical Outcomes Study Short Form-12 Version 2 (SF-12v2, a generic measure of HRQoL, in a NCP cohort using the Medical Expenditure Panel Survey Longitudinal Files. The SF Mental Component Summary (MCS12 and SF Physical Component Summary (PCS12 were tested for reliability (internal consistency and test-retest reliability and validity (construct: convergent and discriminant; criterion: concurrent and predictive. A total of 15,716 patients with NCP were included in the final analysis. The MCS12 and PCS12 demonstrated high internal consistency (Cronbach’s alpha and Mosier’s alpha > 0.8, and moderate and high test-retest reliability, respectively (MCS12 intraclass correlation coefficient (ICC: 0.64; PCS12 ICC: 0.73. Both scales were significantly associated with a number of chronic conditions (p < 0.05. The PCS12 was strongly correlated with perceived health (r = 0.52 but weakly correlated with perceived mental health (r = 0.25. The MCS12 was moderately correlated with perceived mental health (r = 0.42 and perceived health (r = 0.33. Increasing PCS12 and MCS12 scores were significantly associated with lower odds of reporting future physical and cognitive limitations (PCS12: OR = 0.90 95%CI: 0.89–0.90, MCS12: OR = 0.94 95%CI: 0.93–0.94. In summary, the SF-12v2 is a reliable and valid measure of HRQoL for patients with NCP.

  4. Evaluating sequelae after head and neck cancer from the patient perspective with the help of the International Classification of Functioning, Disability and Health.

    Science.gov (United States)

    Tschiesner, Uta; Linseisen, Elisabeth; Coenen, Michaela; Rogers, Simon; Harreus, Ulrich; Berghaus, Alexander; Cieza, Alarcos

    2009-03-01

    Functioning is recognized increasingly as an important study outcome with head and neck cancer (HNC). The International Classification of Functioning, Disability and Health, as adopted by the World Health Organization in 2001, is based on a comprehensive bio-psycho-social view. The objective of this study was to evaluate functioning from the patient perspective and to classify the results using the comprehensive view of the ICF. Patients with HNC were interviewed on their problems in daily life using qualitative methodology. Sampling of patients followed the maximum variation strategy. Sample size was determined by saturation. All individual interviews were digitally recorded and transcribed verbatim. Interview texts were divided into meaning units and the concepts contained in the meaning units were linked to the ICF according to established linking rules. The transcribed data were analyzed and linked by a second health professional and the degree of consensus was calculated using kappa statistics. Concordance of identified ICF categories among different tumor locations was also measured with kappa statistics. Until saturation was reached, 18 patients were interviewed: seven patients with oral cancer, five with hypopharyngeal cancer and six with laryngeal cancer. Thousand four hundred and sixty-two (1,462) different concepts were translated into the ICF using 104 different, second-level ICF categories. These ICF categories are presented in detail. From the patient perspective, the ICF components (a) Body functions, (b) Activities and participation and (c) contextual Environmental factors are equally represented, while (d) Body structures show by far the least number of categories. The concordance between different tumor locations rages between 0.53 and 0.58 (confidence interval 0.42-0.70). The degree of consensus in the linking process was 0.58 (confidence interval 0.45-0.73). The ICF classification can display problems with functioning following HNC sufficiently

  5. Rural-Urban Differences in Late-Stage Breast Cancer: Do Associations Differ by Rural-Urban Classification System?

    Science.gov (United States)

    Pruitt, Sandi L; Eberth, Jan M; Morris, E Scott; Grinsfelder, David B; Cuate, Erica L

    2016-01-01

    Introduction Rural residence is associated with later stage of breast cancer diagnosis in some but not all prior studies. The lack of a standardized definition of rural residence may contribute to these mixed findings. We characterize and compare multiple definitions of rural vs. non-rural residence to provide guidance regarding choice of measures and to further elucidate rural disparities in breast cancer stage at diagnosis. Methods We used Texas Cancer Registry data of 120,738 female breast cancer patients ≥50 years old diagnosed between 1995–2009. We defined rural vs. non-rural residence using 7 different measures and examined their agreement using Kappa statistics. Measures were defined at various geographic levels: county, ZIP code, census tract, and census block group. Late-stage was defined as regional or distant disease. For each measure, we tested the association of rural residence and late-stage cancer with unadjusted and adjusted logistic regression. Covariates included: age; patient race/ethnicity; diagnosis year; census block group-level mammography capacity; and census tract-level percent poverty, percent Hispanic, and percent Black. Results We found moderate to high levels of agreement between measures of rural vs. non-rural residence. For 72.9% of all patients, all 7 definitions agreed as to rural vs. non-rural residence. Overall, 6 of 7 definitions demonstrated an adverse association between rural residence and late-stage disease in unadjusted and adjusted models (Adjusted OR Range = 1.09–1.14). Discussion Our results document a clear rural disadvantage in late-stage breast cancer. We contribute to the heterogeneous literature by comparing varied measures of rural residence. We recommend use of the census tract-level Rural Urban Commuting Area Codes in future cancer outcomes research where small area data are available. PMID:27158685

  6. Usefulness and reliability of available epidemiological study results in assessments of radiation-related risks of cancer. Pt. 4

    International Nuclear Information System (INIS)

    Martignoni, K.; Elsasser, U.

    1990-05-01

    Carcinomas occurring in the thyroid gland as a result of radiation generally affect the papillary and, to a slightly lesser extent, follicular parts of this organ, while the available body of evidence hardly gives any indications of anaplastic and medullary neoplasms. Radiation has, however, mostly been associated with multicentric tumours. Among the survivors of the nuclear assaults on Hiroshima and Nagasaki, there are no known cases of anaplastic carcinomas of the thyroid. The papillary carcinoma, which is the prevailing type of neoplasm after radiation exposure, has less malignant potential than the follicular one and is encountered in all age groups. Malignant carcinomas of the thyroid are predominantly found in the middle and high age groups. It was calculated that high Gy doses and dose efficiencies are associated in children with a risk coefficient of 2.5 in 10 4 person-years. This rate is only half as high for adults. Studies performed on relevant cohorts point to latency periods of at least five years. Individuals exposed to radiation are believed to be at a forty-year or even life-long risk of developing cancer. The cancer risk can best be described on the basis of a linear dose-effect relationship. The mortality rate calculated for cancer of the thyroid amounts to approx. 10% of the morbidity rate. The carcinogenic potential of iodine-131 in the thyroid is only one-third as great as that associated with external radiation of high dose efficiency. (orig./MG) [de

  7. Reliability Calculations

    DEFF Research Database (Denmark)

    Petersen, Kurt Erling

    1986-01-01

    Risk and reliability analysis is increasingly being used in evaluations of plant safety and plant reliability. The analysis can be performed either during the design process or during the operation time, with the purpose to improve the safety or the reliability. Due to plant complexity and safety...... and availability requirements, sophisticated tools, which are flexible and efficient, are needed. Such tools have been developed in the last 20 years and they have to be continuously refined to meet the growing requirements. Two different areas of application were analysed. In structural reliability probabilistic...... approaches have been introduced in some cases for the calculation of the reliability of structures or components. A new computer program has been developed based upon numerical integration in several variables. In systems reliability Monte Carlo simulation programs are used especially in analysis of very...

  8. Reporting combined outcomes with Trifecta and survival, continence, and potency (SCP) classification in 337 patients with prostate cancer treated with image-guided hypofractionated radiotherapy.

    Science.gov (United States)

    Jereczek-Fossa, Barbara A; Zerini, Dario; Fodor, Cristiana; Santoro, Luigi; Maucieri, Andrea; Gerardi, Marianna A; Vischioni, Barbara; Cambria, Raffaella; Garibaldi, Cristina; Cattani, Federica; Vavassori, Andrea; Matei, Deliu V; Musi, Gennaro; De Cobelli, Ottavio; Orecchia, Roberto

    2014-12-01

    To report the image-guided hypofractionated radiotherapy (hypo-IGRT) outcome for patients with localised prostate cancer according to the new outcome models Trifecta (cancer control, urinary continence, and sexual potency) and SCP (failure-free survival, continence and potency). Between August 2006 and January 2011, 337 patients with cT1-T2N0M0 prostate cancer (median age 73 years) were eligible for a prospective longitudinal study on hypo-IGRT (70.2 Gy/26 fractions) in our Department. Patients completed four questionnaires before treatment, and during follow-up: the International Index of Erectile Function-5 (IIEF-5), the International Prostate Symptom Score (IPSS), and the European Organization for Research and Treatment of Cancer prostate-cancer-specific Quality of Life Questionnaires (QLQ) QLQ-PR25 and QLQ-C30. Baseline and follow-up patient data were analysed according to the Trifecta and SCP outcome models. Cancer control, continence and potency were defined respectively as no evidence of disease, score 1 or 2 for item 36 of the QLQ-PR25 questionnaire, and total score of >16 on the IIEF-5 questionnaire. Patients receiving androgen-deprivation therapy (ADT) at any time were excluded. Trifecta criteria at baseline were met in 72 patients (42% of all ADT-free patients with completed questionnaires). Both at 12 and 24 months after hypo-IGRT, 57% of the Trifecta patients at baseline were still meeting the Trifecta criteria (both oncological and functional success according to the SCP model). The main reason for failing the Trifecta criteria during follow-up was erectile dysfunction: in 18 patients after 6 months follow-up, in 12 patients after 12 months follow-up, and in eight patients after 24 months. Actuarial 2-year Trifecta failure-free survival rate was 44% (95% confidence interval 27-60%). In multivariate analysis no predictors of Trifecta failure were identified. Missing questionnaires was the main limitation of the study. The Trifecta and SCP

  9. Reliability analysis of the Chinese version of the Functional Assessment of Cancer Therapy - Leukemia (FACT-Leu) scale based on multivariate generalizability theory.

    Science.gov (United States)

    Meng, Qiong; Yang, Zheng; Wu, Yang; Xiao, Yuanyuan; Gu, Xuezhong; Zhang, Meixia; Wan, Chonghua; Li, Xiaosong

    2017-05-04

    The Functional Assessment of Cancer Therapy-Leukemia (FACT-Leu) scale, a leukemia-specific instrument for determining the health-related quality of life (HRQOL) in patients with leukemia, had been developed and validated, but there have been no reports on the development of a simplified Chinese version of this scale. This is a new exploration to analyze the reliability of the HRQOL measurement using multivariate generalizability theory (MGT). This study aimed to develop a Chinese version of the FACT-Leu scale and evaluate its reliability using MGT to provide evidence to support the revision and improvement of this scale. The Chinese version of the FACT-Leu scale was developed by four steps: forward translation, backward translation, cultural adaptation and pilot-testing. The HRQOL was measured for eligible inpatients with leukemia using this scale to provide data. A single-facet multivariate Generalizability Study (G-study) design was demonstrated to estimate the variance-covariance components and then several Decision Studies (D-studies) with varying numbers of items were analyzed to obtain reliability coefficients and to understand how much the measurement reliability could be vary as the number of items in MGT changes. One-hundred and one eligible inpatients diagnosed with leukemia were recruited and completed the HRQOL measurement at the time of admission to the hospital. In the G-study, the variation component of the patient-item interaction was largest while the variation component of the item was the smallest for the four of five domains, except for the leukemia-specific (LEUS) domain. In the D-study, at the level of domain, the generalizability coefficients (G) and the indexes of dependability (Ф) for four of the five domains were approximately equal to or greater than 0.80 except for the Emotional Well-being (EWB) domain (>0.70 but number of items were obtained: one is a 37-item version while the other is a 45-item version. The Chinese version of the FACT

  10. Tolerance to missing data using a likelihood ratio based classifier for computer-aided classification of breast cancer

    International Nuclear Information System (INIS)

    Bilska-Wolak, Anna O; Floyd, Carey E Jr

    2004-01-01

    While mammography is a highly sensitive method for detecting breast tumours, its ability to differentiate between malignant and benign lesions is low, which may result in as many as 70% of unnecessary biopsies. The purpose of this study was to develop a highly specific computer-aided diagnosis algorithm to improve classification of mammographic masses. A classifier based on the likelihood ratio was developed to accommodate cases with missing data. Data for development included 671 biopsy cases (245 malignant), with biopsy-proved outcome. Sixteen features based on the BI-RADS TM lexicon and patient history had been recorded for the cases, with 1.3 ± 1.1 missing feature values per case. Classifier evaluation methods included receiver operating characteristic and leave-one-out bootstrap sampling. The classifier achieved 32% specificity at 100% sensitivity on the 671 cases with 16 features that had missing values. Utilizing just the seven features present for all cases resulted in decreased performance at 100% sensitivity with average 19% specificity. No cases and no feature data were omitted during classifier development, showing that it is more beneficial to utilize cases with missing values than to discard incomplete cases that cannot be handled by many algorithms. Classification of mammographic masses was commendable at high sensitivity levels, indicating that benign cases could be potentially spared from biopsy

  11. Diagnosis of breast cancer using diffuse optical spectroscopy from 500 to 1600 nm: comparison of classification methods

    Science.gov (United States)

    Nachabé, Rami; Evers, Daniel J.; Hendriks, Benno H. W.; Lucassen, Gerald W.; van der Voort, Marjolein; Rutgers, Emiel J.; Peeters, Marie-Jeanne Vrancken; van der Hage, Jos A.; Oldenburg, Hester S.; Wesseling, Jelle; Ruers, Theo J. M.

    2011-08-01

    We report on the use of diffuse optical spectroscopy analysis of breast spectra acquired in the wavelength range from 500 to 1600 nm with a fiber optic probe. A total of 102 ex vivo samples of five different breast tissue types, namely adipose, glandular, fibroadenoma, invasive carcinoma, and ductal carcinoma in situ from 52 patients were measured. A model deriving from the diffusion theory was applied to the measured spectra in order to extract clinically relevant parameters such as blood, water, lipid, and collagen volume fractions, β-carotene concentration, average vessels radius, reduced scattering amplitude, Mie slope, and Mie-to-total scattering fraction. Based on a classification and regression tree algorithm applied to the derived parameters, a sensitivity-specificity of 98%-99%, 84%-95%, 81%-98%, 91%-95%, and 83%-99% were obtained for discrimination of adipose, glandular, fibroadenoma, invasive carcinoma, and ductal carcinoma in situ, respectively; and a multiple classes overall diagnostic performance of 94%. Sensitivity-specificity values obtained for discriminating malignant from nonmalignant tissue were compared to existing reported studies by applying the different classification methods that were used in each of these studies. Furthermore, in these reported studies, either lipid or β-carotene was considered as adipose tissue precursors. We estimate both chromophore concentrations and demonstrate that lipid is a better discriminator for adipose tissue than β-carotene.

  12. The classification of secondary colorectal liver cancer in human biopsy samples using angular dispersive x-ray diffraction and multivariate analysis

    International Nuclear Information System (INIS)

    Theodorakou, Chrysoula; Farquharson, Michael J

    2009-01-01

    The motivation behind this study is to assess whether angular dispersive x-ray diffraction (ADXRD) data, processed using multivariate analysis techniques, can be used for classifying secondary colorectal liver cancer tissue and normal surrounding liver tissue in human liver biopsy samples. The ADXRD profiles from a total of 60 samples of normal liver tissue and colorectal liver metastases were measured using a synchrotron radiation source. The data were analysed for 56 samples using nonlinear peak-fitting software. Four peaks were fitted to all of the ADXRD profiles, and the amplitude, area, amplitude and area ratios for three of the four peaks were calculated and used for the statistical and multivariate analysis. The statistical analysis showed that there are significant differences between all the peak-fitting parameters and ratios between the normal and the diseased tissue groups. The technique of soft independent modelling of class analogy (SIMCA) was used to classify normal liver tissue and colorectal liver metastases resulting in 67% of the normal tissue samples and 60% of the secondary colorectal liver tissue samples being classified correctly. This study has shown that the ADXRD data of normal and secondary colorectal liver cancer are statistically different and x-ray diffraction data analysed using multivariate analysis have the potential to be used as a method of tissue classification.

  13. A multifactorial likelihood model for MMR gene variant classification incorporating probabilities based on sequence bioinformatics and tumor characteristics: a report from the Colon Cancer Family Registry.

    Science.gov (United States)

    Thompson, Bryony A; Goldgar, David E; Paterson, Carol; Clendenning, Mark; Walters, Rhiannon; Arnold, Sven; Parsons, Michael T; Michael D, Walsh; Gallinger, Steven; Haile, Robert W; Hopper, John L; Jenkins, Mark A; Lemarchand, Loic; Lindor, Noralane M; Newcomb, Polly A; Thibodeau, Stephen N; Young, Joanne P; Buchanan, Daniel D; Tavtigian, Sean V; Spurdle, Amanda B

    2013-01-01

    Mismatch repair (MMR) gene sequence variants of uncertain clinical significance are often identified in suspected Lynch syndrome families, and this constitutes a challenge for both researchers and clinicians. Multifactorial likelihood model approaches provide a quantitative measure of MMR variant pathogenicity, but first require input of likelihood ratios (LRs) for different MMR variation-associated characteristics from appropriate, well-characterized reference datasets. Microsatellite instability (MSI) and somatic BRAF tumor data for unselected colorectal cancer probands of known pathogenic variant status were used to derive LRs for tumor characteristics using the Colon Cancer Family Registry (CFR) resource. These tumor LRs were combined with variant segregation within families, and estimates of prior probability of pathogenicity based on sequence conservation and position, to analyze 44 unclassified variants identified initially in Australasian Colon CFR families. In addition, in vitro splicing analyses were conducted on the subset of variants based on bioinformatic splicing predictions. The LR in favor of pathogenicity was estimated to be ~12-fold for a colorectal tumor with a BRAF mutation-negative MSI-H phenotype. For 31 of the 44 variants, the posterior probabilities of pathogenicity were such that altered clinical management would be indicated. Our findings provide a working multifactorial likelihood model for classification that carefully considers mode of ascertainment for gene testing. © 2012 Wiley Periodicals, Inc.

  14. Classification of molecular structure images by using ANN, RF, LBP, HOG, and size reduction methods for early stomach cancer detection

    Science.gov (United States)

    Aytaç Korkmaz, Sevcan; Binol, Hamidullah

    2018-03-01

    Patients who die from stomach cancer are still present. Early diagnosis is crucial in reducing the mortality rate of cancer patients. Therefore, computer aided methods have been developed for early detection in this article. Stomach cancer images were obtained from Fırat University Medical Faculty Pathology Department. The Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) features of these images are calculated. At the same time, Sammon mapping, Stochastic Neighbor Embedding (SNE), Isomap, Classical multidimensional scaling (MDS), Local Linear Embedding (LLE), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Laplacian Eigenmaps methods are used for dimensional the reduction of the features. The high dimension of these features has been reduced to lower dimensions using dimensional reduction methods. Artificial neural networks (ANN) and Random Forest (RF) classifiers were used to classify stomach cancer images with these new lower feature sizes. New medical systems have developed to measure the effects of these dimensions by obtaining features in different dimensional with dimensional reduction methods. When all the methods developed are compared, it has been found that the best accuracy results are obtained with LBP_MDS_ANN and LBP_LLE_ANN methods.

  15. Translational database selection and multiplexed sequence capture for up front filtering of reliable breast cancer biomarker candidates.

    Directory of Open Access Journals (Sweden)

    Patrik L Ståhl

    Full Text Available Biomarker identification is of utmost importance for the development of novel diagnostics and therapeutics. Here we make use of a translational database selection strategy, utilizing data from the Human Protein Atlas (HPA on differentially expressed protein patterns in healthy and breast cancer tissues as a means to filter out potential biomarkers for underlying genetic causatives of the disease. DNA was isolated from ten breast cancer biopsies, and the protein coding and flanking non-coding genomic regions corresponding to the selected proteins were extracted in a multiplexed format from the samples using a single DNA sequence capture array. Deep sequencing revealed an even enrichment of the multiplexed samples and a great variation of genetic alterations in the tumors of the sampled individuals. Benefiting from the upstream filtering method, the final set of biomarker candidates could be completely verified through bidirectional Sanger sequencing, revealing a 40 percent false positive rate despite high read coverage. Of the variants encountered in translated regions, nine novel non-synonymous variations were identified and verified, two of which were present in more than one of the ten tumor samples.

  16. MALDI Imaging Mass Spectrometry (MALDI-IMS―Application of Spatial Proteomics for Ovarian Cancer Classification and Diagnosis

    Directory of Open Access Journals (Sweden)

    Johan O. R. Gustafsson

    2011-01-01

    Full Text Available MALDI imaging mass spectrometry (MALDI-IMS allows acquisition of mass data for metabolites, lipids, peptides and proteins directly from tissue sections. IMS is typically performed either as a multiple spot profiling experiment to generate tissue specific mass profiles, or a high resolution imaging experiment where relative spatial abundance for potentially hundreds of analytes across virtually any tissue section can be measured. Crucially, imaging can be achieved without prior knowledge of tissue composition and without the use of antibodies. In effect MALDI-IMS allows generation of molecular data which complement and expand upon the information provided by histology including immuno-histochemistry, making its application valuable to both cancer biomarker research and diagnostics. The current state of MALDI-IMS, key biological applications to ovarian cancer research and practical considerations for analysis of peptides and proteins on ovarian tissue are presented in this review.

  17. Classification of 27 Tumor-Associated Antigens by Histochemical Analysis of 36 Freshly Resected Lung Cancer Tissues

    Directory of Open Access Journals (Sweden)

    Gene Kurosawa

    2016-11-01

    Full Text Available In previous studies, we identified 29 tumor-associated antigens (TAAs and isolated 488 human monoclonal antibodies (mAbs that specifically bind to one of the 29 TAAs. In the present study, we performed histochemical analysis of 36 freshly resected lung cancer tissues by using 60 mAbs against 27 TAAs. Comparison of the staining patterns of tumor cells, bronchial epithelial cells, and normal pulmonary alveolus cells and interalveolar septum allowed us to determine the type and location of cells that express target molecules, as well as the degree of expression. The patterns were classified into 7 categories. While multiple Abs were used against certain TAAs, the differences observed among them should be derived from differences in the binding activity and/or the epitope. Thus, such data indicate the versatility of respective clones as anti-cancer drugs. Although the information obtained was limited to the lung and bronchial tube, bronchial epithelial cells represent normal growing cells, and therefore, the data are informative. The results indicate that 9 of the 27 TAAs are suitable targets for therapeutic Abs. These 9 Ags include EGFR, HER2, TfR, and integrin α6β4. Based on our findings, a pharmaceutical company has started to develop anti-cancer drugs by using Abs to TfR and integrin α6β4. HGFR, PTP-LAR, CD147, CDCP1, and integrin αvβ3 are also appropriate targets for therapeutic purposes.

  18. Reliability Engineering

    CERN Document Server

    Lazzaroni, Massimo

    2012-01-01

    This book gives a practical guide for designers and users in Information and Communication Technology context. In particular, in the first Section, the definition of the fundamental terms according to the international standards are given. Then, some theoretical concepts and reliability models are presented in Chapters 2 and 3: the aim is to evaluate performance for components and systems and reliability growth. Chapter 4, by introducing the laboratory tests, puts in evidence the reliability concept from the experimental point of view. In ICT context, the failure rate for a given system can be

  19. Reliability training

    Science.gov (United States)

    Lalli, Vincent R. (Editor); Malec, Henry A. (Editor); Dillard, Richard B.; Wong, Kam L.; Barber, Frank J.; Barina, Frank J.

    1992-01-01

    Discussed here is failure physics, the study of how products, hardware, software, and systems fail and what can be done about it. The intent is to impart useful information, to extend the limits of production capability, and to assist in achieving low cost reliable products. A review of reliability for the years 1940 to 2000 is given. Next, a review of mathematics is given as well as a description of what elements contribute to product failures. Basic reliability theory and the disciplines that allow us to control and eliminate failures are elucidated.

  20. Reliability studies of diagnostic methods in Indian traditional Ayurveda medicine

    DEFF Research Database (Denmark)

    Kurande, Vrinda Hitendra; Waagepetersen, Rasmus; Toft, Egon

    2013-01-01

    as prakriti classification), method development (pulse diagnosis), quality assurance for diagnosis and treatment and in the conduct of clinical studies. Several reliability studies are conducted in western medicine. The investigation of the reliability of traditional Chinese, Japanese and Sasang medicine...

  1. Gender, Race, and Survival: A Study in Non-Small-Cell Lung Cancer Brain Metastases Patients Utilizing the Radiation Therapy Oncology Group Recursive Partitioning Analysis Classification

    International Nuclear Information System (INIS)

    Videtic, Gregory M.M.; Reddy, Chandana A.; Chao, Samuel T.; Rice, Thomas W.; Adelstein, David J.; Barnett, Gene H.; Mekhail, Tarek M.; Vogelbaum, Michael A.; Suh, John H.

    2009-01-01

    Purpose: To explore whether gender and race influence survival in non-small-cell lung cancer (NSCLC) in patients with brain metastases, using our large single-institution brain tumor database and the Radiation Therapy Oncology Group recursive partitioning analysis (RPA) brain metastases classification. Methods and materials: A retrospective review of a single-institution brain metastasis database for the interval January 1982 to September 2004 yielded 835 NSCLC patients with brain metastases for analysis. Patient subsets based on combinations of gender, race, and RPA class were then analyzed for survival differences. Results: Median follow-up was 5.4 months (range, 0-122.9 months). There were 485 male patients (M) (58.4%) and 346 female patients (F) (41.6%). Of the 828 evaluable patients (99%), 143 (17%) were black/African American (B) and 685 (83%) were white/Caucasian (W). Median survival time (MST) from time of brain metastasis diagnosis for all patients was 5.8 months. Median survival time by gender (F vs. M) and race (W vs. B) was 6.3 months vs. 5.5 months (p = 0.013) and 6.0 months vs. 5.2 months (p = 0.08), respectively. For patients stratified by RPA class, gender, and race, MST significantly favored BFs over BMs in Class II: 11.2 months vs. 4.6 months (p = 0.021). On multivariable analysis, significant variables were gender (p = 0.041, relative risk [RR] 0.83) and RPA class (p < 0.0001, RR 0.28 for I vs. III; p < 0.0001, RR 0.51 for II vs. III) but not race. Conclusions: Gender significantly influences NSCLC brain metastasis survival. Race trended to significance in overall survival but was not significant on multivariable analysis. Multivariable analysis identified gender and RPA classification as significant variables with respect to survival.

  2. The newly proposed clinical and post-neoadjuvant treatment staging classifications for gastric adenocarcinoma for the American Joint Committee on Cancer (AJCC) staging.

    Science.gov (United States)

    In, Haejin; Ravetch, Ethan; Langdon-Embry, Marisa; Palis, Bryan; Ajani, Jaffer A; Hofstetter, Wayne L; Kelsen, David P; Sano, Takeshi

    2018-01-01

    New stage grouping classifications for clinical (cStage) and post-neoadjuvant treatment (ypStage) stage for gastric adenocarcinoma have been proposed for the eighth edition of the AJCC manual. This article summarizes the analysis for these stages. Gastric adenocarcinoma patients diagnosed in 2004-2009 were identified from the National Cancer Database (NCDB). The cStage cohort included both surgical and nonsurgical cases, and the ypStage cohort included only patients who had chemotherapy or radiation therapy before surgery. Survival differences between the stage groups were determined by the log-rank test and prognostic accuracy was assessed by concordance index. Analysis was performed using SAS 9.4 (SAS, Cary, NC, USA). Five strata for cStage and four strata for ypStage were developed. The 5-year survival rates for cStages were 56.77%, 47.39%, 33.1%, 25.9%, and 5.0% for stages I, IIa, IIb, III, and IV, respectively, and the rates for ypStage were 74.2%, 46.3%, 19.2%, and 11.6% for stages I, II, III, and IV, respectively. The log-rank test showed that survival differences were well stratified and stage groupings were ordered and distinct (p < 0.0001). The proposed cStage and ypStage classification was sensitive and specific and had high prognostic accuracy (cStage: c index = 0.81, 95% CI, 0.79-0.83; ypStage: c index = 0.80, 95% CI, 0.73-0.87). The proposed eighth edition establishes two new staging schemata that provide essential prognostic data for patients before treatment and for patients who have undergone surgery following neoadjuvant therapy. These additions are a significant advance to the AJCC staging manual and will provide critical guidance to clinicians in making informed decisions throughout the treatment course.

  3. An improved behavioural assay demonstrates that ultrasound vocalizations constitute a reliable indicator of chronic cancer pain and neuropathic pain

    Directory of Open Access Journals (Sweden)

    Selvaraj Deepitha

    2010-03-01

    Full Text Available Abstract Background On-going pain is one of the most debilitating symptoms associated with a variety of chronic pain disorders. An understanding of mechanisms underlying on-going pain, i.e. stimulus-independent pain has been hampered so far by a lack of behavioural parameters which enable studying it in experimental animals. Ultrasound vocalizations (USVs have been proposed to correlate with pain evoked by an acute activation of nociceptors. However, literature on the utility of USVs as an indicator of chronic pain is very controversial. A majority of these inconsistencies arise from parameters confounding behavioural experiments, which include novelty, fear and stress due to restrain, amongst others. Results We have developed an improved assay which overcomes these confounding factors and enables studying USVs in freely moving mice repetitively over several weeks. Using this improved assay, we report here that USVs increase significantly in mice with bone metastases-induced cancer pain or neuropathic pain for several weeks, in comparison to sham-treated mice. Importantly, analgesic drugs which are known to alleviate tumour pain or neuropathic pain in human patients significantly reduce USVs as well as mechanical allodynia in corresponding mouse models. Conclusions We show that studying USVs and mechanical allodynia in the same cohort of mice enables comparing the temporal progression of on-going pain (i.e. stimulus-independent pain and stimulus-evoked pain in these clinically highly-relevant forms of chronic pain.

  4. Reliability calculations

    International Nuclear Information System (INIS)

    Petersen, K.E.

    1986-03-01

    Risk and reliability analysis is increasingly being used in evaluations of plant safety and plant reliability. The analysis can be performed either during the design process or during the operation time, with the purpose to improve the safety or the reliability. Due to plant complexity and safety and availability requirements, sophisticated tools, which are flexible and efficient, are needed. Such tools have been developed in the last 20 years and they have to be continuously refined to meet the growing requirements. Two different areas of application were analysed. In structural reliability probabilistic approaches have been introduced in some cases for the calculation of the reliability of structures or components. A new computer program has been developed based upon numerical integration in several variables. In systems reliability Monte Carlo simulation programs are used especially in analysis of very complex systems. In order to increase the applicability of the programs variance reduction techniques can be applied to speed up the calculation process. Variance reduction techniques have been studied and procedures for implementation of importance sampling are suggested. (author)

  5. Detection and classification of focal liver lesions in patients with colorectal cancer: Retrospective comparison of diffusion-weighted MR imaging and multi-slice CT

    International Nuclear Information System (INIS)

    Eiber, Matthias; Fingerle, Alexander A.; Brügel, Melanie; Gaa, Jochen; Rummeny, Ernst J.; Holzapfel, Konstantin

    2012-01-01

    Objectives: To compare the diagnostic performance of diffusion-weighted MR imaging (DWI) with multi-slice CT (MS-CT) in the detection and classification of focal liver lesions in patients with colorectal cancer. Methods: In a retrospective study 68 patients who underwent DWI at 1.5 T (b-values of 50, 300 and 600 s/mm 2 ) and contrast-enhanced MS-CT were analysed by two radiologists blinded to the clinical results. Imaging results were correlated with intraoperative surgical and ultrasound findings (n = 24), imaging follow-up or PET (n = 44). Sensitivity of DWI and MS-CT in detection of focal liver lesions was compared on a per-lesion and a per-segment basis. Receiver operator-characteristic (ROC) curves to determine the diagnostic performance and the sensitivities of correctly identifying liver metastases on a segmental base were calculated. Results: For lesion detection, DWI was significantly superior to MS-CT both on a per-lesion (difference in sensitivities for reader 1 and 2 22.65% and 19.06%, p < 0.0001) and a per-segment basis (16.86% and 11.76%, p < 0.0001). Especially lesions smaller than 10 mm were better detected with DWI compared to MS-CT (difference 41.10% and 29.45%, p < 0.0001). ROC-analysis showed superiority for lesions classification (p < 0.0001) of DWI (AUC: 0.949 and 0.951) as compared to MS-CT (AUC: 0.879 and 0.892, p < 0.0001 and p = 0.005). DWI was able to filter out metastatic segments with a higher sensitivity (88.2 and 86.5%) compared to MS-CT (68.0 and 67.4%, p < 0.0001 and p = 0.005, respectively). Conclusion: Compared to MS-CT DWI is both more sensitive in the detection of liver lesions and more accurate in determining the extent of metastatic disease in patients with colorectal cancer and therefore might help to optimize therapeutic management in those patients.

  6. Evaluation of the reliability of clinical staging of T2 N0 esophageal cancer: a review of the Society of Thoracic Surgeons database.

    Science.gov (United States)

    Crabtree, Traves D; Kosinski, Andrzej S; Puri, Varun; Burfeind, William; Bharat, Ankit; Patterson, G Alexander; Hofstetter, Wayne; Meyers, Bryan F

    2013-08-01

    Clinical staging of esophageal cancer has improved with positron-emission tomography/computed tomography and endoscopic ultrasound imaging. Despite such progress, small single-center studies have questioned the reliability of clinical staging of T2 N0 esophageal cancer. This study broadly examines the adequacy of clinical staging of T2 N0 disease using The Society of Thoracic Surgeons database. We retrospectively studied 810 clinical stage T2 N0 patients from 2002 to 2011, with 58 excluded because of incomplete pathologic staging data. Clinical stage, pathologic stage, and preoperative characteristics were recorded. Logistic regression analysis was used to identify factors associated with upstaging at the time of surgical intervention. Among 752 clinical stage T2 N0 patients, 270 (35.9%) received induction therapy before the operation. Of 482 patients who went directly to surgical intervention, 132 (27.4%) were confirmed as pathologic T2 N0, 125 (25.9%) were downstaged (ie, T0-1 N0), and 225 (46.7%) were upstaged at the operation (T3-4 N0 or Tany N1-3). Exclusive tumor upstaging (ie, pathologic T3-4 N0) accounted for 41 patients (18.2%), whereas exclusive nodal upstaging (ie, pathological T1-2 N1-3) accounted for 100 (44.5%). Combined tumor and nodal upstaging (ie, pathological T3-4 N1-3) accounted for 84 patients (37.3%). Among patients who received induction therapy, 103 (38.1%) were upstaged vs 225 (46.7%) without induction therapy (p = 0.026). Comparing the induction therapy group and the primary surgical group, postoperative 30-day mortality (3.7% vs 3.7%, p > 0.99) and morbidity (46.3% vs 45%, p = 0.76) were similar. Despite advances in staging techniques, clinical staging of T2 N0 esophageal cancer remains unreliable. Recognizing T2 N0 as a threshold for induction therapy in esophageal cancer, many surgeons have opted to treat T2 N0 disease with induction therapy, even though one-quarter of these patients will be pathologic T1 N0. Although this study

  7. Systems reliability/structural reliability

    International Nuclear Information System (INIS)

    Green, A.E.

    1980-01-01

    The question of reliability technology using quantified techniques is considered for systems and structures. Systems reliability analysis has progressed to a viable and proven methodology whereas this has yet to be fully achieved for large scale structures. Structural loading variants over the half-time of the plant are considered to be more difficult to analyse than for systems, even though a relatively crude model may be a necessary starting point. Various reliability characteristics and environmental conditions are considered which enter this problem. The rare event situation is briefly mentioned together with aspects of proof testing and normal and upset loading conditions. (orig.)

  8. Classification of Non-Small Cell Lung Cancer Using Significance Analysis of Microarray-Gene Set Reduction Algorithm

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2016-01-01

    Full Text Available Among non-small cell lung cancer (NSCLC, adenocarcinoma (AC, and squamous cell carcinoma (SCC are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR, can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed.

  9. Classifier Fusion With Contextual Reliability Evaluation.

    Science.gov (United States)

    Liu, Zhunga; Pan, Quan; Dezert, Jean; Han, Jun-Wei; He, You

    2018-05-01

    Classifier fusion is an efficient strategy to improve the classification performance for the complex pattern recognition problem. In practice, the multiple classifiers to combine can have different reliabilities and the proper reliability evaluation plays an important role in the fusion process for getting the best classification performance. We propose a new method for classifier fusion with contextual reliability evaluation (CF-CRE) based on inner reliability and relative reliability concepts. The inner reliability, represented by a matrix, characterizes the probability of the object belonging to one class when it is classified to another class. The elements of this matrix are estimated from the -nearest neighbors of the object. A cautious discounting rule is developed under belief functions framework to revise the classification result according to the inner reliability. The relative reliability is evaluated based on a new incompatibility measure which allows to reduce the level of conflict between the classifiers by applying the classical evidence discounting rule to each classifier before their combination. The inner reliability and relative reliability capture different aspects of the classification reliability. The discounted classification results are combined with Dempster-Shafer's rule for the final class decision making support. The performance of CF-CRE have been evaluated and compared with those of main classical fusion methods using real data sets. The experimental results show that CF-CRE can produce substantially higher accuracy than other fusion methods in general. Moreover, CF-CRE is robust to the changes of the number of nearest neighbors chosen for estimating the reliability matrix, which is appealing for the applications.

  10. Profiling cancer

    DEFF Research Database (Denmark)

    Ciro, Marco; Bracken, Adrian P; Helin, Kristian

    2003-01-01

    In the past couple of years, several very exciting studies have demonstrated the enormous power of gene-expression profiling for cancer classification and prediction of patient survival. In addition to promising a more accurate classification of cancer and therefore better treatment of patients......, gene-expression profiling can result in the identification of novel potential targets for cancer therapy and a better understanding of the molecular mechanisms leading to cancer....

  11. [Guideline development for rehabilitation of breast cancer patients - phase 2: findings from the classification of therapeutic procedures, KTL-data-analysis].

    Science.gov (United States)

    Domann, U; Brüggemann, S; Klosterhuis, H; Weis, J

    2007-08-01

    Aim of this project is the development of an evidence based guideline for the rehabilitation of breast cancer patients, funded by the German Pension Insurance scheme. The project consists of four phases. This paper is focused on the 2nd phase, i.e., analysis of procedures in rehabilitation based on evidence based therapeutic modules. As a result of a systematic literature review 14 therapeutic modules were defined. From a total of 840 possible KTL Codes (Klassifikation Therapeutischer Leistungen, Classification of therapeutic procedures), 229 could be assigned to these modules. These analyses are based on 24685 patients in 57 rehabilitation clinics, who had been treated in 2003. For these modules the number of patients having received those interventions as well as the duration of the modules were calculated. The data were analysed with respect to the influence of age and comorbidity. Moreover, differences between rehabilitation clinics were investigated according to the category of interventions. Our findings show great variability in the use of the therapeutic modules. Therapeutic modules like Physiotherapy (91.6%), Training Therapy (85.2%) and Information (97.8%) are provided to most of the patients. Younger patients receive more treatments than older patients, and patients with higher comorbidity receive more Physiotherapie, Lymphoedema Therapy and Psychological Interventions than patients without comorbidities. Data analysis shows wide interindividual variability with regard to the therapeutic modules. This variability is related to age and comorbidity of the patients. Furthermore, great differences were found between the rehabilitation clinics concerning the use of the various interventions. This variability supports the necessity of developing and implementing an evidence based guideline for the rehabilitation of breast cancer patients. The next step will be discussing these findings with experts from science and clinical practice.

  12. Unsupervised Analysis of Array Comparative Genomic Hybridization Data from Early-Onset Colorectal Cancer Reveals Equivalence with Molecular Classification and Phenotypes

    Directory of Open Access Journals (Sweden)

    María Arriba

    2017-01-01

    Full Text Available AIM: To investigate whether chromosomal instability (CIN is associated with tumor phenotypes and/or with global genomic status based on MSI (microsatellite instability and CIMP (CpG island methylator phenotype in early-onset colorectal cancer (EOCRC. METHODS: Taking as a starting point our previous work in which tumors from 60 EOCRC cases (≤45 years at the time of diagnosis were analyzed by array comparative genomic hybridization (aCGH, in the present study we performed an unsupervised hierarchical clustering analysis of those aCGH data in order to unveil possible associations between the CIN profile and the clinical features of the tumors. In addition, we evaluated the MSI and the CIMP statuses of the samples with the aim of investigating a possible relationship between copy number alterations (CNAs and the MSI/CIMP condition in EOCRC. RESULTS: Based on the similarity of the CNAs detected, the unsupervised analysis stratified samples into two main clusters (A, B and four secondary clusters (A1, A2, B3, B4. The different subgroups showed a certain correspondence with the molecular classification of colorectal cancer (CRC, which enabled us to outline an algorithm to categorize tumors according to their CIMP status. Interestingly, each subcluster showed some distinctive clinicopathological features. But more interestingly, the CIN of each subcluster mainly affected particular chromosomes, allowing us to define chromosomal regions more specifically affected depending on the CIMP/MSI status of the samples. CONCLUSIONS: Our findings may provide a basis for a new form of classifying EOCRC according to the genomic status of the tumors.

  13. Human reliability

    International Nuclear Information System (INIS)

    Bubb, H.

    1992-01-01

    This book resulted from the activity of Task Force 4.2 - 'Human Reliability'. This group was established on February 27th, 1986, at the plenary meeting of the Technical Reliability Committee of VDI, within the framework of the joint committee of VDI on industrial systems technology - GIS. It is composed of representatives of industry, representatives of research institutes, of technical control boards and universities, whose job it is to study how man fits into the technical side of the world of work and to optimize this interaction. In a total of 17 sessions, information from the part of ergonomy dealing with human reliability in using technical systems at work was exchanged, and different methods for its evaluation were examined and analyzed. The outcome of this work was systematized and compiled in this book. (orig.) [de

  14. Microelectronics Reliability

    Science.gov (United States)

    2017-01-17

    inverters  connected in a chain. ................................................. 5  Figure 3  Typical graph showing frequency versus square root of...developing an experimental  reliability estimating methodology that could both illuminate the  lifetime  reliability of advanced devices,  circuits and...or  FIT of the device. In other words an accurate estimate of the device  lifetime  was found and thus the  reliability  that  can  be  conveniently

  15. Application of the International Classification of Functioning, Disability and Health (ICF) to people with dysphagia following non-surgical head and neck cancer management.

    Science.gov (United States)

    Nund, Rebecca L; Scarinci, Nerina A; Cartmill, Bena; Ward, Elizabeth C; Kuipers, Pim; Porceddu, Sandro V

    2014-12-01

    The International Classification of Functioning, Disability, and Health (ICF) is an internationally recognized framework which allows its user to describe the consequences of a health condition on an individual in the context of their environment. With growing recognition that dysphagia can have broad ranging physical and psychosocial impacts, the aim of this paper was to identify the ICF domains and categories that describe the full functional impact of dysphagia following non-surgical head and neck cancer (HNC) management, from the perspective of the person with dysphagia. A secondary analysis was conducted on previously published qualitative study data which explored the lived experiences of dysphagia of 24 individuals with self-reported swallowing difficulties following HNC management. Categories and sub-categories identified by the qualitative analysis were subsequently mapped to the ICF using the established linking rules to develop a set of ICF codes relevant to the impact of dysphagia following HNC management. The 69 categories and sub-categories that had emerged from the qualitative analysis were successfully linked to 52 ICF codes. The distribution of these codes across the ICF framework revealed that the components of Body Functions, Activities and Participation, and Environmental Factors were almost equally represented. The findings confirm that the ICF is a valuable framework for representing the complexity and multifaceted impact of dysphagia following HNC. This list of ICF codes, which reflect the diverse impact of dysphagia associated with HNC on the individual, can be used to guide more holistic assessment and management for this population.

  16. Network-Based Logistic Classification with an Enhanced L1/2 Solver Reveals Biomarker and Subnetwork Signatures for Diagnosing Lung Cancer

    Directory of Open Access Journals (Sweden)

    Hai-Hui Huang

    2015-01-01

    Full Text Available Identifying biomarker and signaling pathway is a critical step in genomic studies, in which the regularization method is a widely used feature extraction approach. However, most of the regularizers are based on L1-norm and their results are not good enough for sparsity and interpretation and are asymptotically biased, especially in genomic research. Recently, we gained a large amount of molecular interaction information about the disease-related biological processes and gathered them through various databases, which focused on many aspects of biological systems. In this paper, we use an enhanced L1/2 penalized solver to penalize network-constrained logistic regression model called an enhanced L1/2 net, where the predictors are based on gene-expression data with biologic network knowledge. Extensive simulation studies showed that our proposed approach outperforms L1 regularization, the old L1/2 penalized solver, and the Elastic net approaches in terms of classification accuracy and stability. Furthermore, we applied our method for lung cancer data analysis and found that our method achieves higher predictive accuracy than L1 regularization, the old L1/2 penalized solver, and the Elastic net approaches, while fewer but informative biomarkers and pathways are selected.

  17. AOSpine subaxial cervical spine injury classification system

    NARCIS (Netherlands)

    Vaccaro, Alexander R.; Koerner, John D.; Radcliff, Kris E.; Oner, F. Cumhur; Reinhold, Maximilian; Schnake, Klaus J.; Kandziora, Frank; Fehlings, Michael G.; Dvorak, Marcel F.; Aarabi, Bizhan; Rajasekaran, Shanmuganathan; Schroeder, Gregory D.; Kepler, Christopher K.; Vialle, Luiz R.

    2016-01-01

    Purpose: This project describes a morphology-based subaxial cervical spine traumatic injury classification system. Using the same approach as the thoracolumbar system, the goal was to develop a comprehensive yet simple classification system with high intra- and interobserver reliability to be used

  18. Tissue Classification

    DEFF Research Database (Denmark)

    Van Leemput, Koen; Puonti, Oula

    2015-01-01

    Computational methods for automatically segmenting magnetic resonance images of the brain have seen tremendous advances in recent years. So-called tissue classification techniques, aimed at extracting the three main brain tissue classes (white matter, gray matter, and cerebrospinal fluid), are now...... well established. In their simplest form, these methods classify voxels independently based on their intensity alone, although much more sophisticated models are typically used in practice. This article aims to give an overview of often-used computational techniques for brain tissue classification...

  19. Using a thermoluminescent dosimeter to evaluate the location reliability of the highest–skin dose area detected by treatment planning in radiotherapy for breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Li-Min, E-mail: limin.sun@yahoo.com [Department of Radiation Oncology, Zuoying Branch of Kaohsiung Armed Forces General Hospital, Kaohsiung City, Taiwan (China); Huang, Chih-Jen [Department of Radiation Oncology, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohs