Clinical Value of a One-Stop-Shop Low-Dose Lung Screening Combined with (18)F-FDG PET/CT for the Detection of Metastatic Lung Nodules from Colorectal Cancer.

Science.gov (United States)

Han, Yeon-Hee; Lim, Seok Tae; Jeong, Hwan-Jeong; Sohn, Myung-Hee

2016-06-01

The aim of this study was to evaluate the clinical usefulness of additional low-dose high-resolution lung computed tomography (LD-HRCT) combined with (18)F-fluoro-2-deoxyglucose positron emission tomography with CT ((18)F-FDG PET/CT) compared with conventional lung setting image of (18)F-FDG PET/CT for the detection of metastatic lung nodules from colorectal cancer. From January 2011 to September 2011, 649 patients with colorectal cancer underwent additional LD-HRCT at maximum inspiration combined with (18)F-FDG PET/CT. Forty-five patients were finally diagnosed to have lung metastasis based on histopathologic study or clinical follow-up. Twenty-five of the 45 patients had ≤5 metastatic lung nodules and the other 20 patients had >5 metastatic nodules. One hundred and twenty nodules in the 25 patients with ≤5 nodules were evaluated by conventional lung setting image of (18)F-FDG PET/CT and by additional LD-HRCT respectively. Sensitivities, specificities, diagnostic accuracies, positive predictive values (PPVs), and negative predictive values (NPVs) of conventional lung setting image of (18)F-FDG PET/CT and additional LD-HRCT were calculated using standard formulae. The McNemar test and receiver-operating characteristic (ROC) analysis were performed. Of the 120 nodules in the 25 patients with ≤5 metastatic lung nodules, 66 nodules were diagnosed as metastatic. Eleven of the 66 nodules were confirmed histopathologically and the others were diagnosed by clinical follow-up. Conventional lung setting image of (18)F-FDG PET/CT detected 40 of the 66 nodules and additional LD-HRCT detected 55 nodules. All 15 nodules missed by conventional lung setting imaging but detected by additional LD-HRCT were LD-HRCT. By ROC analysis, the area under the ROC curve (AUC) of conventional lung setting image and additional LD-HRCT were 0.712 and 0.827 respectively. Additional LD-HRCT with maximum inspiration was superior to conventional lung setting image of (18)F-FDG PET

Difficulties encountered managing nodules detected during a computed tomography lung cancer screening program.

Science.gov (United States)

Veronesi, Giulia; Bellomi, Massimo; Scanagatta, Paolo; Preda, Lorenzo; Rampinelli, Cristiano; Guarize, Juliana; Pelosi, Giuseppe; Maisonneuve, Patrick; Leo, Francesco; Solli, Piergiorgio; Masullo, Michele; Spaggiari, Lorenzo

2008-09-01

The main challenge of screening a healthy population with low-dose computed tomography is to balance the excessive use of diagnostic procedures with the risk of delayed cancer detection. We evaluated the pitfalls, difficulties, and sources of mistakes in the management of lung nodules detected in volunteers in the Cosmos single-center screening trial. A total of 5201 asymptomatic high-risk volunteers underwent screening with multidetector low-dose computed tomography. Nodules detected at baseline or new nodules at annual screening received repeat low-dose computed tomography at 1 year if less than 5 mm, repeat low-dose computed tomography 3 to 6 months later if between 5 and 8 mm, and fluorodeoxyglucose positron emission tomography if more than 8 mm. Growing nodules at the annual screening received low-dose computed tomography at 6 months and computed tomography-positron emission tomography or surgical biopsy according to doubling time, type, and size. During the first year of screening, 106 patients underwent lung biopsy and 91 lung cancers were identified (70% were stage I). Diagnosis was delayed (false-negative) in 6 patients (stage IIB in 1 patient, stage IIIA in 3 patients, and stage IV in 2 patients), including 2 small cell cancers and 1 central lesion. Surgical biopsy revealed benign disease (false-positives) in 15 cases (14%). Positron emission tomography sensitivity was 88% for prevalent cancers and 70% for cancers diagnosed after first annual screening. No needle biopsy procedures were performed in this cohort of patients. Low-dose computed tomography screening is effective for the early detection of lung cancers, but nodule management remains a challenge. Computed tomography-positron emission tomography is useful at baseline, but its sensitivity decreases significantly the subsequent year. Multidisciplinary management and experience are crucial for minimizing misdiagnoses.

Computer-aided detection of lung nodules on chest CT: issues to be solved before clinical use

International Nuclear Information System (INIS)

Goo, Jin Mo

2005-01-01

Given the increasing resolution of modern CT scanners, and the requirements for large-scale lung-screening examinations and diagnostic studies, there is an increased need for the accurate and reproducible analysis of the large number of images. Nodule detection is one of the main challenges of CT imaging, as they can be missed due to their small size, low relative contrast, or because they are located in an area with complex anatomy. Recent developments in computer-aided diagnosis (CAD) schemes are expected to aid radiologists in various tasks of chest imaging. In this era of multidetector row CT, the thoracic applications of greatest interest include the detection and volume measurement of lung nodules (1-7). Technology for CAD as applied to lung nodule detection on chest CT has been approved by the Food and Drug Administration and is currently commercially available. The article by Lee et al. (5) in this issue of the Korean Journal of Radiology is one of the few studies to examine the influence of a commercially available CAD system on the detection of lung nodules. In this study, some additional nodules were detected with the help of a CAD system, but at the expense of increased false positivity. The nodule detection rate of the CAD system in this study was lower than that achieved by radiologist, and the authors insist that the CAD system should be improved further. Compared to the use of CAD on mammograms, CAD evaluations of chest CTs remain limited to the laboratory setting. In this field, apart from the issues of detection rate and false positive detections, many obstacles must be overcome before CAD can be used in a true clinical reading environment. In this editorial, I will list some of these issues, but I emphasize now that I believe these issues will be solved by improved CAD versions in the near future

Clinical value of a one-stop-shop low-dose lung screening combined with 18F-FDG PET/CT for the detection of metastatic lung nodules from colorectal cancer

International Nuclear Information System (INIS)

Han, Yeon Hee; Lim, Seok Tae; Jeong, Hwan Jeong; Sohn, Myung Hee

2016-01-01

The aim of this study was to evaluate the clinical usefulness of additional low-dose high-resolution lung computed tomography (LD-HRCT) combined with 18F-fluoro-2-deoxyglucose positron emission tomography with CT (18F-FDG PET/CT) compared with conventional lung setting image of 18F-FDG PET/CT for the detection of metastatic lung nodules from colorectal cancer. From January 2011 to September 2011, 649 patients with colorectal cancer underwent additional LD-HRCT at maximum inspiration combined with 18F-FDG PET/CT. Forty-five patients were finally diagnosed to have lung metastasis based on histopathologic study or clinical follow-up. Twenty-five of the 45 patients had ≤5 metastatic lung nodules and the other 20 patients had  >5 metastatic nodules. One hundred and twenty nodules in the 25 patients with ≤5 nodules were evaluated by conventional lung setting image of 18F-FDG PET/CT and by additional LD-HRCT respectively. Sensitivities, specificities, diagnostic accuracies, positive predictive values (PPVs), and negative predictive values (NPVs) of conventional lung setting image of 18F-FDG PET/CT and additional LD-HRCT were calculated using standard formulae. The McNemar test and receiver-operating characteristic (ROC) analysis were performed. Of the 120 nodules in the 25 patients with ≤5 metastatic lung nodules, 66 nodules were diagnosed as metastatic. Eleven of the 66 nodules were confirmed histopathologically and the others were diagnosed by clinical follow-up. Conventional lung setting image of 18F-FDG PET/CT detected 40 of the 66 nodules and additional LD-HRCT detected 55 nodules. All 15 nodules missed by conventional lung setting imaging but detected by additional LD-HRCT were <1 cm in size. The sensitivity, specificity, and diagnostic accuracy of the modalities were 60.6 %, 85.2 %, and 71.1 % for conventional lung setting image and 83.3 %, 88.9 %, and 85.8 % for additional LD-HRCT. By ROC analysis, the area under the ROC curve (AUC) of conventional

Vasculature surrounding a nodule: A novel lung cancer biomarker.

Science.gov (United States)

Wang, Xiaohua; Leader, Joseph K; Wang, Renwei; Wilson, David; Herman, James; Yuan, Jian-Min; Pu, Jiantao

2017-12-01

To investigate whether the vessels surrounding a nodule depicted on non-contrast, low-dose computed tomography (LDCT) can discriminate benign and malignant screen detected nodules. We collected a dataset consisting of LDCT scans acquired on 100 subjects from the Pittsburgh Lung Screening study (PLuSS). Fifty subjects were diagnosed with lung cancer and 50 subjects had suspicious nodules later proven benign. For the lung cancer cases, the location of the malignant nodule in the LDCT scans was known; while for the benign cases, the largest nodule in the LDCT scan was used in the analysis. A computer algorithm was developed to identify surrounding vessels and quantify the number and volume of vessels that were connected or near the nodule. A nonparametric receiver operating characteristic (ROC) analysis was performed based on a single nodule per subject to assess the discriminability of the surrounding vessels to provide a lung cancer diagnosis. Odds ratio (OR) were computed to determine the probability of a nodule being lung cancer based on the vessel features. The areas under the ROC curves (AUCs) for vessel count and vessel volume were 0.722 (95% CI=0.616-0.811, plung cancer group 9.7 (±9.6) compared to the non-lung cancer group 4.0 (±4.3) CONCLUSION: Our preliminary results showed that malignant nodules are often surrounded by more vessels compared to benign nodules, suggesting that the surrounding vessel characteristics could serve as lung cancer biomarker for indeterminate nodules detected during LDCT lung cancer screening using only the information collected during the initial visit. Copyright © 2017 Elsevier B.V. All rights reserved.

Clinical value of a one-stop-shop low-dose lung screening combined with {sup 18}F-FDG PET/CT for the detection of metastatic lung nodules from colorectal cancer

Energy Technology Data Exchange (ETDEWEB)

Han, Yeon Hee; Lim, Seok Tae; Jeong, Hwan Jeong; Sohn, Myung Hee [Dept. of Nuclear Medicine, Research Institute of Clinical Medicine, Chonbuk National University-Biomedical Research Institute, Chonbuk National University Hospital, Cyclotron Research Center, Molecular Imaging and Therapeutic Medicine Research Center, Chonbuk National University Medical School and Hospital, Jeonju (Korea, Republic of)

2016-06-15

The aim of this study was to evaluate the clinical usefulness of additional low-dose high-resolution lung computed tomography (LD-HRCT) combined with 18F-fluoro-2-deoxyglucose positron emission tomography with CT (18F-FDG PET/CT) compared with conventional lung setting image of 18F-FDG PET/CT for the detection of metastatic lung nodules from colorectal cancer. From January 2011 to September 2011, 649 patients with colorectal cancer underwent additional LD-HRCT at maximum inspiration combined with 18F-FDG PET/CT. Forty-five patients were finally diagnosed to have lung metastasis based on histopathologic study or clinical follow-up. Twenty-five of the 45 patients had ≤5 metastatic lung nodules and the other 20 patients had  >5 metastatic nodules. One hundred and twenty nodules in the 25 patients with ≤5 nodules were evaluated by conventional lung setting image of 18F-FDG PET/CT and by additional LD-HRCT respectively. Sensitivities, specificities, diagnostic accuracies, positive predictive values (PPVs), and negative predictive values (NPVs) of conventional lung setting image of 18F-FDG PET/CT and additional LD-HRCT were calculated using standard formulae. The McNemar test and receiver-operating characteristic (ROC) analysis were performed. Of the 120 nodules in the 25 patients with ≤5 metastatic lung nodules, 66 nodules were diagnosed as metastatic. Eleven of the 66 nodules were confirmed histopathologically and the others were diagnosed by clinical follow-up. Conventional lung setting image of 18F-FDG PET/CT detected 40 of the 66 nodules and additional LD-HRCT detected 55 nodules. All 15 nodules missed by conventional lung setting imaging but detected by additional LD-HRCT were <1 cm in size. The sensitivity, specificity, and diagnostic accuracy of the modalities were 60.6 %, 85.2 %, and 71.1 % for conventional lung setting image and 83.3 %, 88.9 %, and 85.8 % for additional LD-HRCT. By ROC analysis, the area under the ROC curve (AUC) of conventional

Potential contribution of multiplanar reconstruction (MPR) to computer-aided detection of lung nodules on MDCT

International Nuclear Information System (INIS)

Matsumoto, Sumiaki; Ohno, Yoshiharu; Yamagata, Hitoshi; Nogami, Munenobu; Kono, Atsushi; Sugimura, Kazuro

2012-01-01

Purpose: To evaluate potential benefits of using multiplanar reconstruction (MPR) in computer-aided detection (CAD) of lung nodules on multidetector computed tomography (MDCT). Materials and methods: MDCT datasets of 60 patients with suspected lung nodules were retrospectively collected. Using “second-read” CAD, two radiologists (Readers 1 and 2) independently interpreted these datasets for the detection of non-calcified nodules (≥4 mm) with concomitant confidence rating. They did this task twice, first without MPR (using only axial images), and then 4 weeks later with MPR (using also coronal and sagittal MPR images), where the total reading time per dataset, including the time taken to assess the detection results of CAD software (CAD assessment time), was recorded. The total reading time and CAD assessment time without MPR and those with MPR were statistically compared for each reader. The radiologists’ performance for detecting nodules without MPR and the performance with MPR were compared using jackknife free-response receiver operating characteristic (JAFROC) analysis. Results: Compared to the CAD assessment time without MPR (mean, 69 s and 57 s for Readers 1 and 2), the CAD assessment time with MPR (mean, 46 s and 45 s for Readers 1 and 2) was significantly reduced (P < 0.001). For Reader 1, the total reading time was also significantly shorter in the case with MPR. There was no significant difference between the detection performances without MPR and with MPR. Conclusion: The use of MPR has the potential to improve the workflow in CAD of lung nodules on MDCT.

Lung nodule detection by microdose CT versus chest radiography (standard and dual-energy subtracted).

Science.gov (United States)

Ebner, Lukas; Bütikofer, Yanik; Ott, Daniel; Huber, Adrian; Landau, Julia; Roos, Justus E; Heverhagen, Johannes T; Christe, Andreas

2015-04-01

The purpose of this study was to investigate the feasibility of microdose CT using a comparable dose as for conventional chest radiographs in two planes including dual-energy subtraction for lung nodule assessment. We investigated 65 chest phantoms with 141 lung nodules, using an anthropomorphic chest phantom with artificial lung nodules. Microdose CT parameters were 80 kV and 6 mAs, with pitch of 2.2. Iterative reconstruction algorithms and an integrated circuit detector system (Stellar, Siemens Healthcare) were applied for maximum dose reduction. Maximum intensity projections (MIPs) were reconstructed. Chest radiographs were acquired in two projections with bone suppression. Four blinded radiologists interpreted the images in random order. A soft-tissue CT kernel (I30f) delivered better sensitivities in a pilot study than a hard kernel (I70f), with respective mean (SD) sensitivities of 91.1%±2.2% versus 85.6%±5.6% (p=0.041). Nodule size was measured accurately for all kernels. Mean clustered nodule sensitivity with chest radiography was 45.7%±8.1% (with bone suppression, 46.1%±8%; p=0.94); for microdose CT, nodule sensitivity was 83.6%±9% without MIP (with additional MIP, 92.5%±6%; pmicrodose CT for readers 1, 2, 3, and 4 were 84.3%, 90.7%, 68.6%, and 45.0%, respectively. Sensitivities with chest radiography for readers 1, 2, 3, and 4 were 42.9%, 58.6%, 36.4%, and 90.7%, respectively. In the per-phantom analysis, respective sensitivities of microdose CT versus chest radiography were 96.2% and 75% (pmicrodose CT, the applied dose was 0.1323 mSv. Microdose CT is better than the combination of chest radiography and dual-energy subtraction for the detection of solid nodules between 5 and 12 mm at a lower dose level of 0.13 mSv. Soft-tissue kernels allow better sensitivities. These preliminary results indicate that microdose CT has the potential to replace conventional chest radiography for lung nodule detection.

AUTOMATIC LUNG NODULE DETECTION BASED ON STATISTICAL REGION MERGING AND SUPPORT VECTOR MACHINES

Directory of Open Access Journals (Sweden)

Elaheh Aghabalaei Khordehchi

2017-06-01

Full Text Available Lung cancer is one of the most common diseases in the world that can be treated if the lung nodules are detected in their early stages of growth. This study develops a new framework for computer-aided detection of pulmonary nodules thorough a fully-automatic analysis of Computed Tomography (CT images. In the present work, the multi-layer CT data is fed into a pre-processing step that exploits an adaptive diffusion-based smoothing algorithm in which the parameters are automatically tuned using an adaptation technique. After multiple levels of morphological filtering, the Regions of Interest (ROIs are extracted from the smoothed images. The Statistical Region Merging (SRM algorithm is applied to the ROIs in order to segment each layer of the CT data. Extracted segments in consecutive layers are then analyzed in such a way that if they intersect at more than a predefined number of pixels, they are labeled with a similar index. The boundaries of the segments in adjacent layers which have the same indices are then connected together to form three-dimensional objects as the nodule candidates. After extracting four spectral, one morphological, and one textural feature from all candidates, they are finally classified into nodules and non-nodules using the Support Vector Machine (SVM classifier. The proposed framework has been applied to two sets of lung CT images and its performance has been compared to that of nine other competing state-of-the-art methods. The considerable efficiency of the proposed approach has been proved quantitatively and validated by clinical experts as well.

Radiological and pathological analysis of LDCT screen detected and surgically resected sub-centimetre lung nodules in 44 asymptomatic patients

International Nuclear Information System (INIS)

Hu, Xing; Zhao, Jiangmin; Qian, Haishan; Du, Guangyan; Kelly, Margaret; Yang, Hua

2016-01-01

Once lung cancer is detected due to clinical symptoms or by being visible on chest X-ray, it is usually high stage and non-operable. In order to improve mortality rates in lung cancer, low-dose CT (LDCT) screening of “high risk” individuals is gaining popularity. However, the rate of malignancy in LDCT detected sub-centimetre lung nodules is not clear. We aimed to analyze surgically resected specimens in this patient group to explore cost effectiveness and recommendations for clinical management of these nodules. Our hospital pathology database was searched for sub-centimeter lung nodules detected by LDCT screening which were resected. The patient demographics were collected and the radiologic and pathologic characteristics of those nodules were analyzed. From the records, 44 patients with 46 resected subcentimetre nodules were identified. Patients were selected for surgery based on an irregular shape, growth in size during follow up, family history of lung cancer or personal history of cancer of other sites, previous lung disease, smoking and personal anxiety. Of the 44 patients, 33 were women and the ages ranged from 43 to 76 years (56.75 ± 8.44). All nodules were equal to, or less than 10 mm with a mean diameter of 7.81 ± 1.80 mm (SD). Out of 46 nodules, the pathological diagnoses were: invasive adenocarcinoma (ACa) in 4 (8.7%); adenocarcinoma in situ (AIS) or atypical adenomatous hyperplasia (AAH) in 29 (63%); benign fibrosis/fibrotic scar with inflammation or calcification in 12 (26.1%); an intrapulmonary benign lymph node in 1 (2.2%). Of the ACa, AIS and AAH groups (a total of 31 patients), 77% were women (24 vs. 7). The cancer or pre-cancer nodules (ACa, AIS and AAH) tended to be larger than benign fibrotic scars (P = 0.039). Amongst all characteristics, significant statistical differences were found when the following radiological features were considered: reconstructed nodule shape (P = 0.011), margin (P = 0.003) and ground glass pattern (P = 0

Incidentally detected lung nodules: clinical predictors of adherence to fleischner society surveillance guidelines.

LENUS (Irish Health Repository)

Ridge, Carole A

2014-02-28

The objective of this study was to determine adherence to incidentally detected lung nodule computed tomographic (CT) surveillance recommendations and identify demographic and clinical factors that increase the likelihood of CT surveillance.

Lung nodule detection in pediatric chest CT: quantitative relationship between image quality and radiologist performance.

Science.gov (United States)

Li, Xiang; Samei, Ehsan; Barnhart, Huiman X; Gaca, Ana Maria; Hollingsworth, Caroline L; Maxfield, Charles M; Carrico, Caroline W T; Colsher, James G; Frush, Donald P

2011-05-01

To determine the quantitative relationship between image quality and radiologist performance in detecting small lung nodules in pediatric CT. The study included clinical chest CT images of 30 pediatric patients (0-16 years) scanned at tube currents of 55-180 mA. Calibrated noise addition software was used to simulate cases at three nominal mA settings: 70, 35, and 17.5 mA, resulting in quantum noise of 7-32 Hounsfield Unit (HU). Using a validated nodule simulation technique, lung nodules with diameters of 3-5 mm and peak contrasts of 200-500 HU were inserted into the cases, which were then randomized and rated independently by four experienced pediatric radiologists for nodule presence on a continuous scale from 0 (definitely absent) to 100 (definitely present). The receiver operating characteristic (ROC) data were analyzed to quantify the relationship between diagnostic accuracy (area under the ROC curve, AUC) and image quality (the product of nodule peak contrast and displayed diameter to noise ratio, CDNR display). AUC increased rapidly from 0.70 to 0.87 when CDNR display increased from 60 to 130 mm, followed by a slow increase to 0.94 when CDNR display further increased to 257 mm. For the average nodule diameter (4 mm) and contrast (350 HU), AUC decreased from 0.93 to 0.71 with noise increased from 7 to 28 HU. We quantified the relationship between image quality and the performance of radiologists in detecting lung nodules in pediatric CT. The relationship can guide CT protocol design to achieve the desired diagnostic performance at the lowest radiation dose.

Pulmonary Nodule Management in Lung Cancer Screening: A Pictorial Review of Lung-RADS Version 1.0.

Science.gov (United States)

Godoy, Myrna C B; Odisio, Erika G L C; Truong, Mylene T; de Groot, Patricia M; Shroff, Girish S; Erasmus, Jeremy J

2018-05-01

The number of screening-detected lung nodules is expected to increase as low-dose computed tomography screening is implemented nationally. Standardized guidelines for image acquisition, interpretation, and screen-detected nodule workup are essential to ensure a high standard of medical care and that lung cancer screening is implemented safely and cost effectively. In this article, we review the current guidelines for pulmonary nodule management in the lung cancer screening setting. Copyright © 2018 Elsevier Inc. All rights reserved.

Can Lung Nodules Be Cancerous?

Science.gov (United States)

... lung nodules be cancerous? Answers from Eric J. Olson, M.D. Yes, lung nodules can be cancerous, ... to determine if it's cancerous. With Eric J. Olson, M.D. AskMayoExpert. Pulmonary nodules. Rochester, Minn.: Mayo ...

Computer-aided detection of lung nodules via 3D fast radial transform, scale space representation, and Zernike MIP classification.

Science.gov (United States)

Riccardi, Alessandro; Petkov, Todor Sergueev; Ferri, Gianluca; Masotti, Matteo; Campanini, Renato

2011-04-01

The authors presented a novel system for automated nodule detection in lung CT exams. The approach is based on (1) a lung tissue segmentation preprocessing step, composed of histogram thresholding, seeded region growing, and mathematical morphology; (2) a filtering step, whose aim is the preliminary detection of candidate nodules (via 3D fast radial filtering) and estimation of their geometrical features (via scale space analysis); and (3) a false positive reduction (FPR) step, comprising a heuristic FPR, which applies thresholds based on geometrical features, and a supervised FPR, which is based on support vector machines classification, which in turn, is enhanced by a feature extraction algorithm based on maximum intensity projection processing and Zernike moments. The system was validated on 154 chest axial CT exams provided by the lung image database consortium public database. The authors obtained correct detection of 71% of nodules marked by all radiologists, with a false positive rate of 6.5 false positives per patient (FP/patient). A higher specificity of 2.5 FP/patient was reached with a sensitivity of 60%. An independent test on the ANODE09 competition database obtained an overall score of 0.310. The system shows a novel approach to the problem of lung nodule detection in CT scans: It relies on filtering techniques, image transforms, and descriptors rather than region growing and nodule segmentation, and the results are comparable to those of other recent systems in literature and show little dependency on the different types of nodules, which is a good sign of robustness.

3D pulmonary nodules detection using fast marching segmentation ...

African Journals Online (AJOL)

This paper proposes an automated computer aided diagnosis system for detection of pulmonary nodules based on three dimensional (3D) structures. Lung ... The proposed detection methodology can give the accuracy of 92%. Keywords: lung cancer; pulmonary nodule; fast marching; 3D features; random forest classifier.

Performance of computer-aided detection of pulmonary nodules in low-dose CT: comparison with double reading by nodule volume

Energy Technology Data Exchange (ETDEWEB)

Zhao, Yingru; Vliegenthart, Rozemarijn; Wang, Ying; Ooijen, Peter M.A. van; Oudkerk, Matthijs [University of Groningen/University Medical Center Groningen, Center for Medical Imaging - North East Netherlands, Department of Radiology, P.O. Box 30.001, Groningen (Netherlands); Bock, Geertruida H. de [University of Groningen/University Medical Center Groningen, Department of Epidemiology, P.O. Box 30.001, Groningen (Netherlands); Klaveren, Rob J. van [Lievensberg Hospital, Department of Pulmonology, P.O. Box 135, Bergen op Zoom (Netherlands); Bogoni, Luca [CAD Group, Siemens Medical Solutions USA, Inc., Malvern, PA (United States); Jong, Pim A. de; Mali, Willem P. [University of Utrecht, Department of Radiology, University Medical Center Utrecht, P.O. Box 85500, Utrecht (Netherlands)

2012-10-15

To evaluate performance of computer-aided detection (CAD) beyond double reading for pulmonary nodules on low-dose computed tomography (CT) by nodule volume. A total of 400 low-dose chest CT examinations were randomly selected from the NELSON lung cancer screening trial. CTs were evaluated by two independent readers and processed by CAD. A total of 1,667 findings marked by readers and/or CAD were evaluated by a consensus panel of expert chest radiologists. Performance was evaluated by calculating sensitivity of pulmonary nodule detection and number of false positives, by nodule characteristics and volume. According to the screening protocol, 90.9 % of the findings could be excluded from further evaluation, 49.2 % being small nodules (less than 50 mm{sup 3}). Excluding small nodules reduced false-positive detections by CAD from 3.7 to 1.9 per examination. Of 151 findings that needed further evaluation, 33 (21.9 %) were detected by CAD only, one of them being diagnosed as lung cancer the following year. The sensitivity of nodule detection was 78.1 % for double reading and 96.7 % for CAD. A total of 69.7 % of nodules undetected by readers were attached nodules of which 78.3 % were vessel-attached. CAD is valuable in lung cancer screening to improve sensitivity of pulmonary nodule detection beyond double reading, at a low false-positive rate when excluding small nodules. circle Computer-aided detection (CAD) has known advantages for computed tomography (CT). (orig.)

Performance of computer-aided detection of pulmonary nodules in low-dose CT: comparison with double reading by nodule volume

International Nuclear Information System (INIS)

Zhao, Yingru; Vliegenthart, Rozemarijn; Wang, Ying; Ooijen, Peter M.A. van; Oudkerk, Matthijs; Bock, Geertruida H. de; Klaveren, Rob J. van; Bogoni, Luca; Jong, Pim A. de; Mali, Willem P.

2012-01-01

To evaluate performance of computer-aided detection (CAD) beyond double reading for pulmonary nodules on low-dose computed tomography (CT) by nodule volume. A total of 400 low-dose chest CT examinations were randomly selected from the NELSON lung cancer screening trial. CTs were evaluated by two independent readers and processed by CAD. A total of 1,667 findings marked by readers and/or CAD were evaluated by a consensus panel of expert chest radiologists. Performance was evaluated by calculating sensitivity of pulmonary nodule detection and number of false positives, by nodule characteristics and volume. According to the screening protocol, 90.9 % of the findings could be excluded from further evaluation, 49.2 % being small nodules (less than 50 mm 3 ). Excluding small nodules reduced false-positive detections by CAD from 3.7 to 1.9 per examination. Of 151 findings that needed further evaluation, 33 (21.9 %) were detected by CAD only, one of them being diagnosed as lung cancer the following year. The sensitivity of nodule detection was 78.1 % for double reading and 96.7 % for CAD. A total of 69.7 % of nodules undetected by readers were attached nodules of which 78.3 % were vessel-attached. CAD is valuable in lung cancer screening to improve sensitivity of pulmonary nodule detection beyond double reading, at a low false-positive rate when excluding small nodules. circle Computer-aided detection (CAD) has known advantages for computed tomography (CT). (orig.)

TH-AB-207A-09: Tailoring TCM Schemes to a Task: Evaluating the Impact of Customized TCM Profiles On Detection of Lung Nodules in Simulated CT Lung Cancer Screening

Energy Technology Data Exchange (ETDEWEB)

Hoffman, J; McNitt-Gray, M [Departments of Biomedical Physics and Radiology, David Geffen School of Medicine at UCLA, Los Angeles, CA (United States); Noo, F [University of Utah, Salt Lake City, UT (United States); Young, S [Department of Radiology, UCLA, Los Angeles, CA (United States)

2016-06-15

Purpose: Recent work has shown that current TCM profile designs boost detection of low-contrast lung lesions in the lung apices, but yield reduced detection performance in the mid and lower lung regions relative to fixed tube current cases. This observed imbalance suggests that the TCM scheme might be tailored in new ways to maximize nodule detection throughout the entire lung. In this work, we begin a preliminary investigation into custom TCM profiles in an attempt to achieve uniform lesion detection throughout the extent of the lung. Methods: Low-contrast (25HU), 6mm nodules representing ground glass opacities were simulated at 1mm intervals over the length the lungs in a voxelized model of the XCAT phantom, one nodule per lung, per simulated scan. Voxel values represented attenuation values at 80keV. CT projection data was created by simulating a finite focal spot and using Joseph’s method for forward projection; scanner geometry was that of the Siemens Sensation 64 and the X-ray source was simulated as an 80keV monochromatic beam. Noise realizations were created using Poisson statistics, a realistic bowtie filter and varying tube current. 500 noise realizations were created for the custom TCM designs. All reconstruction was done with FreeCT-wFBP. An SKE/BKE task was used in conjunction with a 2D Hotelling Observer to calculate area-under-the-curve (AUC) as a proxy for “detectability.” AUC was plotted as a function of nodule Z-location to create a “detectability map.” The detectability map for the custom TCM curve was qualitatively assessed relative to previous results for the fixed TC and clinical TCM cases for uniformity. Results: Detection uniformity was improved throughout the mid and lower lungs, however detection remained disproportionately high in the upper lung region. Conclusion: Detection uniformity was improved with a custom TC profile. Future work will incorporate an analytic, task-specific approach to optimize the TC scheme for nodule

TH-AB-207A-09: Tailoring TCM Schemes to a Task: Evaluating the Impact of Customized TCM Profiles On Detection of Lung Nodules in Simulated CT Lung Cancer Screening

International Nuclear Information System (INIS)

Hoffman, J; McNitt-Gray, M; Noo, F; Young, S

2016-01-01

Purpose: Recent work has shown that current TCM profile designs boost detection of low-contrast lung lesions in the lung apices, but yield reduced detection performance in the mid and lower lung regions relative to fixed tube current cases. This observed imbalance suggests that the TCM scheme might be tailored in new ways to maximize nodule detection throughout the entire lung. In this work, we begin a preliminary investigation into custom TCM profiles in an attempt to achieve uniform lesion detection throughout the extent of the lung. Methods: Low-contrast (25HU), 6mm nodules representing ground glass opacities were simulated at 1mm intervals over the length the lungs in a voxelized model of the XCAT phantom, one nodule per lung, per simulated scan. Voxel values represented attenuation values at 80keV. CT projection data was created by simulating a finite focal spot and using Joseph’s method for forward projection; scanner geometry was that of the Siemens Sensation 64 and the X-ray source was simulated as an 80keV monochromatic beam. Noise realizations were created using Poisson statistics, a realistic bowtie filter and varying tube current. 500 noise realizations were created for the custom TCM designs. All reconstruction was done with FreeCT_wFBP. An SKE/BKE task was used in conjunction with a 2D Hotelling Observer to calculate area-under-the-curve (AUC) as a proxy for “detectability.” AUC was plotted as a function of nodule Z-location to create a “detectability map.” The detectability map for the custom TCM curve was qualitatively assessed relative to previous results for the fixed TC and clinical TCM cases for uniformity. Results: Detection uniformity was improved throughout the mid and lower lungs, however detection remained disproportionately high in the upper lung region. Conclusion: Detection uniformity was improved with a custom TC profile. Future work will incorporate an analytic, task-specific approach to optimize the TC scheme for nodule

Ant Colony Optimization Approaches to Clustering of Lung Nodules from CT Images

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Ravichandran C. Gopalakrishnan

2014-01-01

Full Text Available Lung cancer is becoming a threat to mankind. Applying machine learning algorithms for detection and segmentation of irregular shaped lung nodules remains a remarkable milestone in CT scan image analysis research. In this paper, we apply ACO algorithm for lung nodule detection. We have compared the performance against three other algorithms, namely, Otsu algorithm, watershed algorithm, and global region based segmentation. In addition, we suggest a novel approach which involves variations of ACO, namely, refined ACO, logical ACO, and variant ACO. Variant ACO shows better reduction in false positives. In addition we propose black circular neighborhood approach to detect nodule centers from the edge detected image. Genetic algorithm based clustering is performed to cluster the nodules based on intensity, shape, and size. The performance of the overall approach is compared with hierarchical clustering to establish the improvisation in the proposed approach.

Computer-aided detection and automated CT volumetry of pulmonary nodules

International Nuclear Information System (INIS)

Marten, Katharina; Engelke, Christoph

2007-01-01

With use of multislice computed tomography (MSCT), small pulmonary nodules are being detected in vast numbers, constituting the majority of all noncalcified lung nodules. Although the prevalence of lung cancers among such lesions in lung cancer screening populations is low, their isolation may contribute to increased patient survival. Computer-aided diagnosis (CAD) has emerged as a diverse set of diagnostic tools to handle the large number of images in MSCT datasets and most importantly, includes automated detection and volumetry of pulmonary nodules. Current CAD systems can significantly enhance experienced radiologists' performance and outweigh human limitations in identifying small lesions and manually measuring their diameters, augment observer consistency in the interpretation of such examinations and may thus help to detect significantly higher rates of early malignomas and give more precise estimates on chemotherapy response than can radiologists alone. In this review, we give an overview of current CAD in lung nodule detection and volumetry and discuss their relative merits and limitations. (orig.)

Nodule Detection in a Lung Region that's Segmented with Using Genetic Cellular Neural Networks and 3D Template Matching with Fuzzy Rule Based Thresholding

International Nuclear Information System (INIS)

Ozekes, Serhat; Osman, Onur; Ucan, N.

2008-01-01

The purpose of this study was to develop a new method for automated lung nodule detection in serial section CT images with using the characteristics of the 3D appearance of the nodules that distinguish themselves from the vessels. Lung nodules were detected in four steps. First, to reduce the number of region of interests (ROIs) and the computation time, the lung regions of the CTs were segmented using Genetic Cellular Neural Networks (G-CNN). Then, for each lung region, ROIs were specified with using the 8 directional search; +1 or -1 values were assigned to each voxel. The 3D ROI image was obtained by combining all the 2-Dimensional (2D) ROI images. A 3D template was created to find the nodule-like structures on the 3D ROI image. Convolution of the 3D ROI image with the proposed template strengthens the shapes that are similar to those of the template and it weakens the other ones. Finally, fuzzy rule based thresholding was applied and the ROI's were found. To test the system's efficiency, we used 16 cases with a total of 425 slices, which were taken from the Lung Image Database Consortium (LIDC) dataset. The computer aided diagnosis (CAD) system achieved 100% sensitivity with 13.375 FPs per case when the nodule thickness was greater than or equal to 5.625 mm. Our results indicate that the detection performance of our algorithm is satisfactory, and this may well improve the performance of computer aided detection of lung nodules

Intelligent Recognition of Lung Nodule Combining Rule-based and C-SVM Classifiers

Directory of Open Access Journals (Sweden)

Bin Li

2012-02-01

Full Text Available Computer-aided detection(CAD system for lung nodules plays the important role in the diagnosis of lung cancer. In this paper, an improved intelligent recognition method of lung nodule in HRCT combing rule-based and cost-sensitive support vector machine(C-SVM classifiers is proposed for detecting both solid nodules and ground-glass opacity(GGO nodules(part solid and nonsolid. This method consists of several steps. Firstly, segmentation of regions of interest(ROIs, including pulmonary parenchyma and lung nodule candidates, is a difficult task. On one side, the presence of noise lowers the visibility of low-contrast objects. On the other side, different types of nodules, including small nodules, nodules connecting to vasculature or other structures, part-solid or nonsolid nodules, are complex, noisy, weak edge or difficult to define the boundary. In order to overcome the difficulties of obvious boundary-leak and slow evolvement speed problem in segmentatioin of weak edge, an overall segmentation method is proposed, they are: the lung parenchyma is extracted based on threshold and morphologic segmentation method; the image denoising and enhancing is realized by nonlinear anisotropic diffusion filtering(NADF method; candidate pulmonary nodules are segmented by the improved C-V level set method, in which the segmentation result of EM-based fuzzy threshold method is used as the initial contour of active contour model and a constrained energy term is added into the PDE of level set function. Then, lung nodules are classified by using the intelligent classifiers combining rules and C-SVM. Rule-based classification is first used to remove easily dismissible nonnodule objects, then C-SVM classification are used to further classify nodule candidates and reduce the number of false positive(FP objects. In order to increase the efficiency of SVM, an improved training method is used to train SVM, which uses the grid search method to search the optimal

Intelligent Recognition of Lung Nodule Combining Rule-based and C-SVM Classifiers

Directory of Open Access Journals (Sweden)

Bin Li

2011-10-01

Full Text Available Computer-aided detection(CAD system for lung nodules plays the important role in the diagnosis of lung cancer. In this paper, an improved intelligent recognition method of lung nodule in HRCT combing rule-based and costsensitive support vector machine(C-SVM classifiers is proposed for detecting both solid nodules and ground-glass opacity(GGO nodules(part solid and nonsolid. This method consists of several steps. Firstly, segmentation of regions of interest(ROIs, including pulmonary parenchyma and lung nodule candidates, is a difficult task. On one side, the presence of noise lowers the visibility of low-contrast objects. On the other side, different types of nodules, including small nodules, nodules connecting to vasculature or other structures, part-solid or nonsolid nodules, are complex, noisy, weak edge or difficult to define the boundary. In order to overcome the difficulties of obvious boundary-leak and slow evolvement speed problem in segmentatioin of weak edge, an overall segmentation method is proposed, they are: the lung parenchyma is extracted based on threshold and morphologic segmentation method; the image denoising and enhancing is realized by nonlinear anisotropic diffusion filtering(NADF method;candidate pulmonary nodules are segmented by the improved C-V level set method, in which the segmentation result of EM-based fuzzy threshold method is used as the initial contour of active contour model and a constrained energy term is added into the PDE of level set function. Then, lung nodules are classified by using the intelligent classifiers combining rules and C-SVM. Rule-based classification is first used to remove easily dismissible nonnodule objects, then C-SVM classification are used to further classify nodule candidates and reduce the number of false positive(FP objects. In order to increase the efficiency of SVM, an improved training method is used to train SVM, which uses the grid search method to search the optimal parameters

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.

Use of morphologic filters in the computerized detection of lung nodules in digital chest images

International Nuclear Information System (INIS)

Yoshimura, H.; Giger, M.L.; Doi, K.; Ahn, N.; MacMahon, H.

1989-01-01

The authors have previously described a computerized scheme for the detection of lung nodules based on a difference-image approach, which had a detection accuracy of 70% with 7--8 false positives per image. Currently, they are investigating morphologic filters for the further enhancement/suppression of nodule-signals and the removal of false-positives. Gray-level morphologic filtering is performed on clinical chest radiographs digitized with an optical drum scanner. Various shapes and sequences of erosion and dilation filters (i.e., determination of the minimum and maximum gray levels, respectively) were examined for signal enhancement and suppression for sue in the difference- image approach

Computer-aided detection of lung nodules on multidetector CT in concurrent-reader and second-reader modes: A comparative study

International Nuclear Information System (INIS)

Matsumoto, Sumiaki; Ohno, Yoshiharu; Aoki, Takatoshi; Yamagata, Hitoshi; Nogami, Munenobu; Matsumoto, Keiko; Yamashita, Yoshiko; Sugimura, Kazuro

2013-01-01

Purpose: To compare the reading times and detection performances of radiologists in concurrent-reader and second-reader modes of computer-aided detection (CAD) for lung nodules on multidetector computed tomography (CT). Materials and Methods: Fifty clinical multidetector CT datasets containing nodules up to 20 mm in diameter were retrospectively collected. For the detection and rating of non-calcified nodules larger than 4 mm in diameter, 6 radiologists (3 experienced radiologists and 3 resident radiologists) independently interpreted these datasets twice, once with concurrent-reader CAD and once with second-reader CAD. The reference standard of nodules in the datasets was determined by the consensus of two experienced chest radiologists. The reading times and detection performances in the two modes of CAD were statistically compared, where jackknife free-response receiver operating characteristic (JAFROC) analysis was used for the comparison of detection performances. Results: Two hundreds and seven nodules constituted the reference standard. Reading time was significantly shorter in the concurrent-reader mode than in the second-reader mode, with the mean reading time for the 6 radiologists being 132 s with concurrent-reader CAD and 210 s with second-reader CAD (p < 0.01). JAFROC analysis revealed no significant difference between the detection performances in the two modes, with the average figure-of-merit value for the 6 radiologists being 0.70 with concurrent-reader CAD and 0.72 with second-reader CAD (p = 0.35). Conclusion: In CAD for lung nodules on multidetector CT, the concurrent-reader mode is more time-efficient than the second-reader mode, and there can be no significant difference between the two modes in terms of detection performance of radiologists

Nodule detection in digital chest radiography: Introduction to the radius chest trial

International Nuclear Information System (INIS)

Baath, M.; Haakansson, M.; Boerjesson, S.; Kheddache, S.; Grahn, A.; Ruschin, M.; Tingberg, A.; Mattsson, S.; Maansson, L. G.

2005-01-01

Most digital radiographic systems of today have wide latitude and are hence able to provide images with a small constraint on dose level. This opens up for an unprejudiced dose optimisation. However, in order to succeed in the optimisation task, good knowledge of the imaging and detection processes is needed. As a part of the European-wide research project 'unification of physical and clinical requirements for medical X-ray imaging - governed by the Radiological Imaging Unification Strategies (RADIUS) Group - a major image quality trial was conducted by members of the group. The RADIUS chest trial was focused on the detection of lung nodules in digital chest radiography with the aims of determining to what extent (1) the detection of a nodule is dependent on its location, (2) the system noise disturbs the detection of lung nodules, (3) the anatomical noise disturbs the detection of lung nodules and (4) the image background and anatomical background act as pure noise for the detection of lung nodules. The purpose of the present paper is to give an introduction to the trial and describe the framework and set-up of the investigation. (authors)

Ground-Glass Opacity Lung Nodules in the Era of Lung Cancer CT Screening

DEFF Research Database (Denmark)

Pedersen, Jesper Holst; Saghir, Zaigham; Wille, Mathilde Marie Winkler

2016-01-01

The advent of computed tomography screening for lung cancer will increase the incidence of ground-glass opacity (GGO) nodules detected and referred for diagnostic evaluation and management. GGO nodules remain a diagnostic challenge; therefore, a more systematic approach is necessary to ensure...... that will yield improvements in both diagnosis and treatment. The standard-of-care surgical treatment of early lung cancer is still minimally invasive lobectomy with systematic lymph node dissection. However, recent research has shown that some GGO lesions may be treated with sublobar resections; these findings......, the National Comprehensive Cancer Network, and the British Thoracic Society. In addition, we discuss the management and follow-up of GGO nodules in the light of experience from screening trials. Minimally invasive tissue biopsies and the marking of GGO nodules for surgery are new and rapidly developing fields...

Nodule detection methods using autocorrelation features on 3D chest CT scans

International Nuclear Information System (INIS)

Hara, T.; Zhou, X.; Okura, S.; Fujita, H.; Kiryu, T.; Hoshi, H.

2007-01-01

Lung cancer screening using low dose X-ray CT scan has been an acceptable examination to detect cancers at early stage. We have been developing an automated detection scheme for lung nodules on CT scan by using second-order autocorrelation features and the initial performance for small nodules (< 10 mm) shows a high true-positive rate with less than four false-positive marks per case. In this study, an open database of lung images, LIDC (Lung Image Database Consortium), was employed to evaluate our detection scheme as an consistency test. The detection performance for solid and solitary nodules in LIDC, included in the first data set opened by the consortium, was 83% (10/12) true-positive rate with 3.3 false-positive marks per case. (orig.)

Optimal dose levels in screening chest CT for unimpaired detection and volumetry of lung nodules, with and without computer assisted detection at minimal patient radiation.

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Andreas Christe

Full Text Available OBJECTIVES: The aim of this phantom study was to minimize the radiation dose by finding the best combination of low tube current and low voltage that would result in accurate volume measurements when compared to standard CT imaging without significantly decreasing the sensitivity of detecting lung nodules both with and without the assistance of CAD. METHODS: An anthropomorphic chest phantom containing artificial solid and ground glass nodules (GGNs, 5-12 mm was examined with a 64-row multi-detector CT scanner with three tube currents of 100, 50 and 25 mAs in combination with three tube voltages of 120, 100 and 80 kVp. This resulted in eight different protocols that were then compared to standard CT sensitivity (100 mAs/120 kVp. For each protocol, at least 127 different nodules were scanned in 21-25 phantoms. The nodules were analyzed in two separate sessions by three independent, blinded radiologists and computer-aided detection (CAD software. RESULTS: The mean sensitivity of the radiologists for identifying solid lung nodules on a standard CT was 89.7% ± 4.9%. The sensitivity was not significantly impaired when the tube and current voltage were lowered at the same time, except at the lowest exposure level of 25 mAs/80 kVp [80.6% ± 4.3% (p = 0.031]. Compared to the standard CT, the sensitivity for detecting GGNs was significantly lower at all dose levels when the voltage was 80 kVp; this result was independent of the tube current. The CAD significantly increased the radiologists' sensitivity for detecting solid nodules at all dose levels (5-11%. No significant volume measurement errors (VMEs were documented for the radiologists or the CAD software at any dose level. CONCLUSIONS: Our results suggest a CT protocol with 25 mAs and 100 kVp is optimal for detecting solid and ground glass nodules in lung cancer screening. The use of CAD software is highly recommended at all dose levels.

Application of a kernel-based online learning algorithm to the classification of nodule candidates in computer-aided detection of CT lung nodules

International Nuclear Information System (INIS)

Matsumoto, S.; Ohno, Y.; Takenaka, D.; Sugimura, K.; Yamagata, H.

2007-01-01

Classification of the nodule candidates in computer-aided detection (CAD) of lung nodules in CT images was addressed by constructing a nonlinear discriminant function using a kernel-based learning algorithm called the kernel recursive least-squares (KRLS) algorithm. Using the nodule candidates derived from the processing by a CAD scheme of 100 CT datasets containing 253 non-calcified nodules or 3 mm or larger as determined by the consensus of two thoracic radiologists, the following trial were carried out 100 times: by randomly selecting 50 datasets for training, a nonlinear discriminant function was obtained using the nodule candidates in the training datasets and tested with the remaining candidates; for comparison, a rule-based classification was tested in a similar manner. At the number of false positives per case of about 5, the nonlinear classification method showed an improved sensitivity of 80% (mean over the 100 trials) compared with 74% of the rule-based method. (orig.)

Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: Localized search method based on anatomical classification

International Nuclear Information System (INIS)

Shiraishi, Junji; Li Qiang; Suzuki, Kenji; Engelmann, Roger; Doi, Kunio

2006-01-01

We developed an advanced computer-aided diagnostic (CAD) scheme for the detection of various types of lung nodules on chest radiographs intended for implementation in clinical situations. We used 924 digitized chest images (992 noncalcified nodules) which had a 500x500 matrix size with a 1024 gray scale. The images were divided randomly into two sets which were used for training and testing of the computerized scheme. In this scheme, the lung field was first segmented by use of a ribcage detection technique, and then a large search area (448x448 matrix size) within the chest image was automatically determined by taking into account the locations of a midline and a top edge of the segmented ribcage. In order to detect lung nodule candidates based on a localized search method, we divided the entire search area into 7x7 regions of interest (ROIs: 64x64 matrix size). In the next step, each ROI was classified anatomically into apical, peripheral, hilar, and diaphragm/heart regions by use of its image features. Identification of lung nodule candidates and extraction of image features were applied for each localized region (128x128 matrix size), each having its central part (64x64 matrix size) located at a position corresponding to a ROI that was classified anatomically in the previous step. Initial candidates were identified by use of the nodule-enhanced image obtained with the average radial-gradient filtering technique, in which the filter size was varied adaptively depending on the location and the anatomical classification of the ROI. We extracted 57 image features from the original and nodule-enhanced images based on geometric, gray-level, background structure, and edge-gradient features. In addition, 14 image features were obtained from the corresponding locations in the contralateral subtraction image. A total of 71 image features were employed for three sequential artificial neural networks (ANNs) in order to reduce the number of false-positive candidates. All

Usefulness of computerized method for lung nodule detection on digital chest radiographs using similar subtraction images from different patients

International Nuclear Information System (INIS)

Aoki, Takatoshi; Oda, Nobuhiro; Yamashita, Yoshiko; Yamamoto, Keiji; Korogi, Yukunori

2012-01-01

Purpose: The purpose of this study is to evaluate the usefulness of a novel computerized method to select automatically the similar chest radiograph for image subtraction in the patients who have no previous chest radiographs and to assist the radiologists’ interpretation by presenting the “similar subtraction image” from different patients. Materials and methods: Institutional review board approval was obtained, and the requirement for informed patient consent was waived. A large database of approximately 15,000 normal chest radiographs was used for searching similar images of different patients. One hundred images of candidates were selected according to two clinical parameters and similarity of the lung field in the target image. We used the correlation value of chest region in the 100 images for searching the most similar image. The similar subtraction images were obtained by subtracting the similar image selected from the target image. Thirty cases with lung nodules and 30 cases without lung nodules were used for an observer performance test. Four attending radiologists and four radiology residents participated in this observer performance test. Results: The AUC for all radiologists increased significantly from 0.925 to 0.974 with the CAD (P = .004). When the computer output images were available, the average AUC for the residents was more improved (0.960 vs. 0.890) than for the attending radiologists (0.987 vs. 0.960). Conclusion: The novel computerized method for lung nodule detection using similar subtraction images from different patients would be useful to detect lung nodules on digital chest radiographs, especially for less experienced readers.

The probability of malignancy in small pulmonary nodules coexisting with potentially operable lung cancer detected by CT

International Nuclear Information System (INIS)

Yuan, Yue; Matsumoto, Tsuneo; Hiyama, Atsuto; Miura, Goji; Tanaka, Nobuyuki; Emoto, Takuya; Kawamura, Takeo; Matsunaga, Naofumi

2003-01-01

The aim of this study was to assess the probability of malignancy in one or two small nodules 1 cm or less coexisting with potentially operable lung cancer (coexisting small nodules). The preoperative helical CT scans of 223 patients with lung cancer were retrospectively reviewed. The probability of malignancy of coexisting small nodules was evaluated based on nodule size, location, and clinical stage of the primary lung cancers. Seventy-one coexisting small nodules were found on conventional CT in 58 (26%) of 223 patients, and 14 (6%) patients had malignant nodules. Eighteen (25%) of such nodules were malignant. The probability of malignancy was not significantly different between two groups of nodules larger and smaller than 0.5 cm (p=0.1). The probability of malignancy of such nodules within primary tumor lobe was significantly higher than that in the other lobes (p<0.01). Metastatic nodules were significantly fewer in clinical stage-IA patients than in the patients with the other stage (p<0.01); however, four (57%) of seven synchronous lung cancers were located in the non-primary tumor lobes in the clinical stage-I patients. Malignant coexisting small nodules are not infrequent, and such nodules in the non-primary tumor lobes should be carefully diagnosed. (orig.)

Paediatric CT: the effects of increasing image noise on pulmonary nodule detection

International Nuclear Information System (INIS)

Punwani, Shonit; Davies, Warren; Greenhalgh, Rebecca; Humphries, Paul; Zhang, Jie

2008-01-01

A radiation dose of any magnitude can produce a detrimental effect manifesting as an increased risk of cancer. Cancer development may be delayed for many years following radiation exposure. Minimizing radiation dose in children is particularly important. However, reducing the dose can reduce image quality and may, therefore, hinder lesion detection. We investigated the effects of reducing the image signal-to-noise ratio (SNR) on CT lung nodule detection for a range of nodule sizes. A simulated nodule was placed at the periphery of the lung on an axial CT slice using image editing software. Multiple copies of the manipulated image were saved with various levels of superimposed noise. The image creation process was repeated for a range of nodule sizes. For a given nodule size, output images were read independently by four Fellows of The Royal College of Radiologists. The overall sensitivities in detecting nodules for the SNR ranges 0.8-0.99, 1-1.49, and 1.5-2.35 were 40.5%, 77.3% and 90.3%, respectively, and the specificities were 47.9%, 73.3% and 75%, respectively. The sensitivity for detecting lung nodules increased with nodule size and increasing SNR. There was 100% sensitivity for the detection of nodules of 4-10 mm in diameter at SNRs greater than 1.5. Reducing medical radiation doses in children is of paramount importance. For chest CT examinations this may be counterbalanced by reduced sensitivity and specificity combined with an increased uncertainty of pulmonary nodule detection. This study demonstrates that pulmonary nodules of 4 mm and greater in diameter can be detected with 100% sensitivity provided that the perceived image SNR is greater than 1.5. (orig.)

Localized thin-section CT with radiomics feature extraction and machine learning to classify early-detected pulmonary nodules from lung cancer screening

Science.gov (United States)

Tu, Shu-Ju; Wang, Chih-Wei; Pan, Kuang-Tse; Wu, Yi-Cheng; Wu, Chen-Te

2018-03-01

Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clinical trials of lung cancer screening have shown that the false-positive rate is high and positive predictive value is low. To address these problems, a technical approach is greatly needed for accurate malignancy differentiation among these early-detected nodules. We studied the clinical feasibility of an additional protocol of localized thin-section CT for further assessment on recalled patients from lung cancer screening tests. Our approach of localized thin-section CT was integrated with radiomics features extraction and machine learning classification which was supervised by pathological diagnosis. Localized thin-section CT images of 122 nodules were retrospectively reviewed and 374 radiomics features were extracted. In this study, 48 nodules were benign and 74 malignant. There were nine patients with multiple nodules and four with synchronous multiple malignant nodules. Different machine learning classifiers with a stratified ten-fold cross-validation were used and repeated 100 times to evaluate classification accuracy. Of the image features extracted from the thin-section CT images, 238 (64%) were useful in differentiating between benign and malignant nodules. These useful features include CT density (p  =  0.002 518), sigma (p  =  0.002 781), uniformity (p  =  0.032 41), and entropy (p  =  0.006 685). The highest classification accuracy was 79% by the logistic classifier. The performance metrics of this logistic classification model was 0.80 for the positive predictive value, 0.36 for the false-positive rate, and 0.80 for the area under the receiver operating characteristic curve. Our approach of direct risk classification supervised by the pathological diagnosis with localized thin-section CT and radiomics feature extraction may support clinical physicians in determining

Detection of pulmonary nodules. Improvement by new screen-film systems?

International Nuclear Information System (INIS)

Lehmann, K.J.; Himmighoefer, U.

1994-01-01

In addition to digital radiography and AMBER, the development of asymmetric screen-film systems is another attempt to optimize chest radiography. Due to reduced contrast in the parenchyma, the former asymmetric screen-film systems did not show sufficient image quality. Three new asymmetric systems with completely different composition are available now. In-Sight VHC (Kodak), High Light GUV (3M) and Opthos D (Agfa) were compared to standard chest films using densitometric curves, a chest phantom for high and low contrast detectability, a nodule detection phantom and patient studies. The sensitivity of nodule detection in the mediastinum has been 41-48% for L-films and 58-65% for the asymmetric screen-film systems. No differences could be demonstrated for nodule detection in the lung field. Contrast in the parenchyma is equivalent to L-films. There is no loss of diagnostic information in the lung field. Differences between the asymmetric systems concern speed, dynamic range and granularity. If AMBER and digital radiography are not available, new asymmetric screen-film systems can improve nodule detection without further investment costs. (orig.) [de

Benefit of computer-aided detection analysis for the detection of subsolid and solid lung nodules on thin- and thick-section CT.

Science.gov (United States)

Godoy, Myrna C B; Kim, Tae Jung; White, Charles S; Bogoni, Luca; de Groot, Patricia; Florin, Charles; Obuchowski, Nancy; Babb, James S; Salganicoff, Marcos; Naidich, David P; Anand, Vikram; Park, Sangmin; Vlahos, Ioannis; Ko, Jane P

2013-01-01

The objective of our study was to evaluate the impact of computer-aided detection (CAD) on the identification of subsolid and solid lung nodules on thin- and thick-section CT. For 46 chest CT examinations with ground-glass opacity (GGO) nodules, CAD marks computed using thin data were evaluated in two phases. First, four chest radiologists reviewed thin sections (reader(thin)) for nodules and subsequently CAD marks (reader(thin) + CAD(thin)). After 4 months, the same cases were reviewed on thick sections (reader(thick)) and subsequently with CAD marks (reader(thick) + CAD(thick)). Sensitivities were evaluated. Additionally, reader(thick) sensitivity with assessment of CAD marks on thin sections was estimated (reader(thick) + CAD(thin)). For 155 nodules (mean, 5.5 mm; range, 4.0-27.5 mm)-74 solid nodules, 22 part-solid (part-solid nodules), and 59 GGO nodules-CAD stand-alone sensitivity was 80%, 95%, and 71%, respectively, with three false-positives on average (0-12) per CT study. Reader(thin) + CAD(thin) sensitivities were higher than reader(thin) for solid nodules (82% vs 57%, p thick), reader(thick) + CAD(thick), reader(thick) + CAD(thin) were 40%, 58% (p thick); false-positive rates were 1.17, 1.19, and 1.26 per case for reader(thick), reader(thick) + CAD(thick), and reader(thick) + CAD(thin), respectively. Detection of GGO nodules and solid nodules is significantly improved with CAD. When interpretation is performed on thick sections, the benefit is greater when CAD marks are reviewed on thin rather than thick sections.

Radiomic features analysis in computed tomography images of lung nodule classification.

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Chia-Hung Chen

Full Text Available Radiomics, which extract large amount of quantification image features from diagnostic medical images had been widely used for prognostication, treatment response prediction and cancer detection. The treatment options for lung nodules depend on their diagnosis, benign or malignant. Conventionally, lung nodule diagnosis is based on invasive biopsy. Recently, radiomics features, a non-invasive method based on clinical images, have shown high potential in lesion classification, treatment outcome prediction.Lung nodule classification using radiomics based on Computed Tomography (CT image data was investigated and a 4-feature signature was introduced for lung nodule classification. Retrospectively, 72 patients with 75 pulmonary nodules were collected. Radiomics feature extraction was performed on non-enhanced CT images with contours which were delineated by an experienced radiation oncologist.Among the 750 image features in each case, 76 features were found to have significant differences between benign and malignant lesions. A radiomics signature was composed of the best 4 features which included Laws_LSL_min, Laws_SLL_energy, Laws_SSL_skewness and Laws_EEL_uniformity. The accuracy using the signature in benign or malignant classification was 84% with the sensitivity of 92.85% and the specificity of 72.73%.The classification signature based on radiomics features demonstrated very good accuracy and high potential in clinical application.

Computerized detection of lung nodules by means of "virtual dual-energy" radiography.

Science.gov (United States)

Chen, Sheng; Suzuki, Kenji

2013-02-01

Major challenges in current computer-aided detection (CADe) schemes for nodule detection in chest radiographs (CXRs) are to detect nodules that overlap with ribs and/or clavicles and to reduce the frequent false positives (FPs) caused by ribs. Detection of such nodules by a CADe scheme is very important, because radiologists are likely to miss such subtle nodules. Our purpose in this study was to develop a CADe scheme with improved sensitivity and specificity by use of "virtual dual-energy" (VDE) CXRs where ribs and clavicles are suppressed with massive-training artificial neural networks (MTANNs). To reduce rib-induced FPs and detect nodules overlapping with ribs, we incorporated the VDE technology in our CADe scheme. The VDE technology suppressed rib and clavicle opacities in CXRs while maintaining soft-tissue opacity by use of the MTANN technique that had been trained with real dual-energy imaging. Our scheme detected nodule candidates on VDE images by use of a morphologic filtering technique. Sixty morphologic and gray-level-based features were extracted from each candidate from both original and VDE CXRs. A nonlinear support vector classifier was employed for classification of the nodule candidates. A publicly available database containing 140 nodules in 140 CXRs and 93 normal CXRs was used for testing our CADe scheme. All nodules were confirmed by computed tomography examinations, and the average size of the nodules was 17.8 mm. Thirty percent (42/140) of the nodules were rated "extremely subtle" or "very subtle" by a radiologist. The original scheme without VDE technology achieved a sensitivity of 78.6% (110/140) with 5 (1165/233) FPs per image. By use of the VDE technology, more nodules overlapping with ribs or clavicles were detected and the sensitivity was improved substantially to 85.0% (119/140) at the same FP rate in a leave-one-out cross-validation test, whereas the FP rate was reduced to 2.5 (583/233) per image at the same sensitivity level as the

Automated detection of lung nodules in multidetector CT: influence of different reconstruction protocols on performance of a software prototype

International Nuclear Information System (INIS)

Gurung, J.; Maataoui, A.; Khan, M.; Wetter, A.; Harth, M.; Jacobi, V.; Vogl, T.J.

2006-01-01

Purpose: To evaluate the accuracy of software for computer-aided detection (CAD) of lung nodules using different reconstruction slice thickness protocols in multidetector CT. Materials and Methods: Raw image data sets for 15 patients who had undergone 16-row multidetector CT (MDCT) for known pulmonary nodules were reconstructed at a reconstruction thickness of 5.0, 2.0 and 1.0 mm with a reconstruction increment of 1.5, 1.0 and 0.5 mm, respectively. The ''Nodule Enhanced Viewing'' (NEV) tool of LungCare for computer-aided detection of lung nodules was applied to the reconstructed images. The reconstructed images were also blinded and then evaluated by 2 radiologists (A and B). Data from the evaluating radiologists and CAD was then compared to an independent reference standard established using the consensus of 2 independent experienced chest radiologists. The eligible nodules were grouped according to their size (diameter >10, 5 - 10, <5 mm) for assessment. Statistical analysis was performed using the receiver operating characteristic (ROC) curve analysis, t-test and two-rater Cohen's Kappa co-efficient. Results: A total of 103 nodules were included in the reference standard by the consensus panel. The performance of CAD was marginally lower than that of readers at a 5.0-mm reconstruction thickness (AUC = 0.522, 0.517 and 0.497 for A, B and CAD, respectively). In the case of 2.0-mm reconstruction slices, the performance of CAD was better than that of the readers (AUC = 0.524, 0.524 and 0.614 for A, B and CAD, respectively). CAD was found to be significantly superior to radiologists in the case of 1.0-mm reconstruction slices (AUC = 0.537, 0.531 and 0.675 for A, B and CAD, respectively). The sensitivity at a reconstruction thickness of 1.0 mm was determined to be 66.99%, 68.93% and 80.58% for A, B and CAD, respectively. The time required for detection was shortest for CAD at reconstruction slices of 1.0 mm (mean t = 4 min). The performance of radiologists was greatly

Subtle pulmonary nodules: detection and identification with storage phosphor radiographs and conventional chest films

International Nuclear Information System (INIS)

Scheck, R.J.; Schaetzl, M.; Kandziora, C.; Panzer, M.; Rienmueller, R.

1994-01-01

To determine the value of digital storagephosphor radiography (SR) on the detection and identification of subtle lung nodules, postero-anterior (PA) and lateral (LAT) film-screen (FR) chest radiographs were compared with isodose SR images of 45 patients with metastatic malignancies. The SR postprocessing was done with a particular mode previously optimized for routine chest radiography. Pulmonary metastases were found in 34 patients and were proved or excluded by CT (n=28) or longterm follow-up FR (n=17). Chest images were divided into four regions for evaluation of image quality, number of lung nodules per region and marked pulmonary structures by receiver-operating characteristics (ROC) analysis (45 patients; 125 nodules; 2810 observations; five readers). Of the nodules selected for an ROC study 82% were 0.5-1.0 cm in diameter. Overall image quality was rated better for FR concerning lung fields (PA) and mediastinum/hilum (LAT). More lung-field nodules were detected on FR than on SR chest images. Use of FR was superior to SR in the general identification of nodules (PA chest), especially concerning intermediate and subtle abnormalities, whereas there was no significant difference for LAT chest images. Our results show, that currently FR still has advantages over SR in the detection and identification of subtle lung nodules in routine clinical radiography. (orig.)

Preliminary evaluation of lung care software of 16-slice helical CT in the study of pulmonary nodules

International Nuclear Information System (INIS)

Song Wei; Jin Zhengyu; Yan Hongzhen; Wang Yun; Zhang Yunqing; Wang Linhui; Zhu Haifeng; Liang Jixiang; Qi Bing

2005-01-01

Objective: To evaluate the auxiliary diagnostic ability and applicability of the Lung Care software for the study of the pulmonary nodules. Methods: Fifty-six patients underwent low-dose CT scan with 1.5 mm collimation, 4 mm reconstruction interval, and 4 mm reconstruction slice in group A, and with 1.5 mm collimation, 2 mm reconstruction interval, and 2 mm reconstruction slice in group B. 12 patients underwent low-dose CT with 0.75 mm collimation, 0.75 mm reconstruction interval, and 0.75 mm reconstruction slice in group C. The nodules detected in groups A, B, and C were analyzed by r-MPR or VOI of the Lung Care software to distinguish the true pulmonary nodules from the vessels. The volume and density distribution of the true pulmonary nodules in groups A, B, and C were measured with the Lung Care software. Results: It was difficult to observe the diffuse pulmonary nodules by r-MPR or VOI of the Lung Care software. The images of each patient in group C were too many to be applied in the clinic. There was statistically consistent in the observation of pulmonary nodules between r-MPR and VOI, but the coincidence was not good (Kappa=0.369, P=0.002). There was statistically significant difference in showing faint nodules between r-MPR and VOI (P=0.001), r-MPR was better than VOI. There was statistically significant difference between group A and B in showing = 3.886, P=0.045), but no statistically significant difference in showing 5-10 mm nodules (χ 2 =0.170, P=0.680). The volume and density distribution of most 5 - ≤20 mm nodules were successfully measured with the Lung Care software, whereas those of most 2 =5.811, P=0.016) and 5-10 mm nodules (χ 2 =13.500, P 10 - ≤20 mm nodules (χ 2 =0.000, P=1.000). Conclusion: For distinguishing the true pulmonary nodules from others, the Lung Care software is suitable for the well-edged pulmonary nodules and most faint nodules, but not suitable for the nodules such as ground-glass opacity. For measuring the volume and

Designing a new CAD system for pulmonary nodule detection in High Resolution Computed Tomography (HRCT images

Directory of Open Access Journals (Sweden)

Parsa Hosseini M

2012-07-01

Conclusion: Considering the complexity and different shapes of lung nodules and large number of CT images to evaluate, finding lung nodules are difficult and time consuming for physicians and include human error. Experimental results showed the accuracy of the proposed method to be appropriate (P<0.05 for lung nodule detection.

Clinical evaluation of a software for automated localization of lung nodules at follow-up CT examinations

International Nuclear Information System (INIS)

Beyer, F.; Wormanns, D.; Heindel, W.; Kohl, G.

2004-01-01

Purpose: To evaluate a software algorithm for automated localization of pulmonary nodules at follow-up CT examinations of the chest and to determine factors influencing the rate of correctly matched nodules. Materials and Methods: The 'real-time automatic matching' (RAM) algorithm (Siemens LungCare TM software) was applied to 22 follow-up multirow-detector CT (MDCT) examinations in 11 patients (Siemens Somatom VolumeZoom, tube voltage 120 kVp; effective tube current 20 mAs (n=18) or 100 mAs (n=4); 4 x 1 mm detector configuration, 1.25 mm slice thickness; 0.8 mm reconstruction increment; standard lung kernel B50f) with a total of 190 lung nodules (mean diameter 6.7±3.5 mm, range 2-17 mm). The following nodule features were recorded: diameter, edge definition (well- or ill-defined), location (upper, middle or lower third; central or peripheral; right of left lung) and inspiration level (considered identical if the difference of diaphragm-apex distance between baseline and follow-up examination was 2 -test was used to describe influence of nodule features on detection rate. Influence of nodule size was assessed using Mann-Whitney-U-Test. Results: RAM correctly located 164 of 190 of all lung nodules (86.3%). Detection rate did not depend on nodule location (left vs. right lung: p=0.48; upper vs. middle vs. lower third: p=0.96; peripheral vs. central: p=0.47) or diameter (p=0.30). Influence of inspiration level was highly significant (p [de

A Computer-Aided Diagnosis for Evaluating Lung Nodules on Chest CT: the Current Status and Perspective

Energy Technology Data Exchange (ETDEWEB)

Goo, Jin Mo [Seoul National University Medical Research Center, Seoul (Korea, Republic of)

2011-04-15

As the detection and characterization of lung nodules are of paramount importance in thoracic radiology, various tools for making a computer-aided diagnosis (CAD) have been developed to improve the diagnostic performance of radiologists in clinical practice. Numerous studies over the years have shown that the CAD system can effectively help readers identify more nodules. Moreover, nodule malignancy and the response of malignant lung tumors to treatment can also be assessed using nodule volumetry. CAD also has the potential to objectively analyze the morphology of nodules and enhance the work flow during the assessment of follow-up studies. Therefore, understanding the current status and limitations of CAD for evaluating lung nodules is essential to effectively apply CAD in clinical practice

Detection of small pulmonary nodules in high-field MR at 3 T: evaluation of different pulse sequences using porcine lung explants

International Nuclear Information System (INIS)

Regier, M.; Kaul, M.G.; Ittrich, H.; Bansmann, P.M.; Kemper, J.; Nolte-Ernsting, C.; Adam, G.; Kandel, S.; Hoffmann, B.; Heller, M.; Biederer, J.

2007-01-01

To evaluate two MR imaging sequences for the detection of artificial pulmonary nodules inside porcine lung explants. 67 agarose nodules ranging 3-20 mm were injected into ten porcine lungs within a dedicated chest phantom. The signal on T1-weighted images and radiopacity were adjusted by adding 0.125 mmol/l Gd-DTPA and 1.5 g/l of iodine. A T1-weighted three-dimensional gradient-echo (T1-3D-GRE; TR/TE:3.3/1.1 ms, slice:8 mm, flip-angle:10 ) and a T2-weighted half-Fourier fast-spin echo sequence (T2-HF-FSE; TR/TE:2000/66 ms, slice:7 mm, flip-angle:90 ) were applied in axial orientation using a 3-T system (Intera, Philips Medical Systems, Best, The Netherlands), followed by CT (16 x 0.5 mm) as reference. Nodule sizes and locations were assessed by three blinded observers. In nodules of >10 mm, sensitivity was 100% using 3D-GRE-MRI and 94% using the HF-FSE sequence. For nodules 6-10 mm, the sensitivity of MRI was lower than with CT (3D-GRE:92%; T2-HF-FSE:83%). In lesions smaller than 5 mm, the sensitivity declined to 80% (3D-GRE) and 53% (HF-FSE). Small lesion diameters were overestimated with both sequences, particularly with HF-FSE. This study confirms the feasibility of 3 T-MRI for lung nodule detection. In lesions greater than 5 mm, the sensitivity of the 3D-GRE sequence approximated CT (>90%), while sensitivity and PPV with the HF-FSE sequence were slightly inferior. (orig.)

Adaptive Statistical Iterative Reconstruction-Applied Ultra-Low-Dose CT with Radiography-Comparable Radiation Dose: Usefulness for Lung Nodule Detection.

Science.gov (United States)

Yoon, Hyun Jung; Chung, Myung Jin; Hwang, Hye Sun; Moon, Jung Won; Lee, Kyung Soo

2015-01-01

To assess the performance of adaptive statistical iterative reconstruction (ASIR)-applied ultra-low-dose CT (ULDCT) in detecting small lung nodules. Thirty patients underwent both ULDCT and standard dose CT (SCT). After determining the reference standard nodules, five observers, blinded to the reference standard reading results, independently evaluated SCT and both subsets of ASIR- and filtered back projection (FBP)-driven ULDCT images. Data assessed by observers were compared statistically. Converted effective doses in SCT and ULDCT were 2.81 ± 0.92 and 0.17 ± 0.02 mSv, respectively. A total of 114 lung nodules were detected on SCT as a standard reference. There was no statistically significant difference in sensitivity between ASIR-driven ULDCT and SCT for three out of the five observers (p = 0.678, 0.735, ASIR-driven ULDCT in three out of the five observers (p ASIR-driven ULDCT, and SCT were 0.682, 0.772, and 0.821, respectively, and there were no significant differences in FOM values between ASIR-driven ULDCT and SCT (p = 0.11), but the FOM value of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT and SCT (p = 0.01 and 0.00). Adaptive statistical iterative reconstruction-driven ULDCT delivering a radiation dose of only 0.17 mSv offers acceptable sensitivity in nodule detection compared with SCT and has better performance than FBP-driven ULDCT.

Fate of pulmonary nodules detected by computer-aided diagnosis and physician review on the computed tomography simulation images for hepatocellular carcinoma

International Nuclear Information System (INIS)

Park, Hyo Jung; Kim, Jin Sung; Park, Hee Chul; Oh, Dong Ryul

2014-01-01

To investigate the frequency and clinical significance of detected incidental lung nodules found on computed tomography (CT) simulation images for hepatocellular carcinoma (HCC) using computer-aided diagnosis (CAD) and a physician review. Sixty-seven treatment-naive HCC patients treated with transcatheter arterial chemoembolization and radiotherapy (RT) were included for the study. Portal phase of simulation CT images was used for CAD analysis and a physician review for lung nodule detection. For automated nodule detection, a commercially available CAD system was used. To assess the performance of lung nodule detection for lung metastasis, the sensitivity, negative predictive value (NPV), and positive predictive value (PPV) were calculated. Forty-six patients had incidental nodules detected by CAD with a total of 109 nodules. Only 20 (18.3%) nodules were considered to be significant nodules by a physician review. The number of significant nodules detected by both of CAD or a physician review was 24 in 9 patients. Lung metastases developed in 11 of 46 patients who had any type of nodule. The sensitivities were 58.3% and 100% based on patient number and on the number of nodules, respectively. The NPVs were 91.4% and 100%, respectively. And the PPVs were 77.8% and 91.7%, respectively. Incidental detection of metastatic nodules was not an uncommon event. From our study, CAD could be applied to CT simulation images allowing for an increase in detection of metastatic nodules.

Whole lung computed tomography for detection of pulmonary metastasis of osteosarcoma confirmed at thoracotomy

International Nuclear Information System (INIS)

Ishida, Itsuro; Fukuma, Seigo; Sawada, Kinya; Seki, Yasuo; Tanaka, Fumitaka

1980-01-01

Whole lung computed tomography (CT) was performed in patients with osteosarcoma of bone to evaluate its diagnostic efficacy in comparison to that in conventional chest radiography and in whole lung tomography to detect metastatic nodules in the lung. In 11 of the 12 patients with osteosarcoma, CT detected pulmonary nodules and in 6 of the 11 patients pulmonary nodules were detected by CT, conventional chest radiography and whole lung tomography, respectively, and 22 pulmonary nodules were resected at thoracotomy and proved to be metastatic lesions. Nineteen nodules of the 22 nodules resected were detected by CT and nine of the 22 nodules were discovered only by CT, while only 10 of 22 nodules were recognized by the conventional chest radiography and the whole lung tomography. Two pulmonary nodules, measuring 1 mm and 2 mm in diameter, respectively, were not detected by any of these three methods. In three nodules that showed to be false positive in CT in the two patients, two nodules were histologically suture granulomas induced by the previous operation, and a deformed protuberance of the chest wall was erroneously interpreted to be a subpleural and intrapulmonary nodule in the remaining. We conclude that CT is the most efficient method to detect pulmonary nodules in the patients with osteosarcoma, but that the minimal size of the detectable nodule by CT is 3 mm in diameter. But a smaller nodule having a tendency to ossify can be detected by CT. (author)

Lung nodule volumetry: segmentation algorithms within the same software package cannot be used interchangeably

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Ashraf, H.; Bach, K.S.; Hansen, H. [Copenhagen University, Department of Radiology, Gentofte Hospital, Hellerup (Denmark); Hoop, B. de [University Medical Centre Utrecht, Department of Radiology, Utrecht (Netherlands); Shaker, S.B.; Dirksen, A. [Copenhagen University, Department of Respiratory Medicine, Gentofte Hospital, Hellerup (Denmark); Prokop, M. [University Medical Centre Utrecht, Department of Radiology, Utrecht (Netherlands); Radboud University Nijmegen, Department of Radiology, Nijmegen (Netherlands); Pedersen, J.H. [Copenhagen University, Department of Cardiothoracic Surgery RT, Rigshospitalet, Copenhagen (Denmark)

2010-08-15

We examined the reproducibility of lung nodule volumetry software that offers three different volumetry algorithms. In a lung cancer screening trial, 188 baseline nodules >5 mm were identified. Including follow-ups, these nodules formed a study-set of 545 nodules. Nodules were independently double read by two readers using commercially available volumetry software. The software offers readers three different analysing algorithms. We compared the inter-observer variability of nodule volumetry when the readers used the same and different algorithms. Both readers were able to correctly segment and measure 72% of nodules. In 80% of these cases, the readers chose the same algorithm. When readers used the same algorithm, exactly the same volume was measured in 50% of readings and a difference of >25% was observed in 4%. When the readers used different algorithms, 83% of measurements showed a difference of >25%. Modern volumetric software failed to correctly segment a high number of screen detected nodules. While choosing a different algorithm can yield better segmentation of a lung nodule, reproducibility of volumetric measurements deteriorates substantially when different algorithms were used. It is crucial even in the same software package to choose identical parameters for follow-up. (orig.)

Lung nodule volumetry: segmentation algorithms within the same software package cannot be used interchangeably

International Nuclear Information System (INIS)

Ashraf, H.; Bach, K.S.; Hansen, H.; Hoop, B. de; Shaker, S.B.; Dirksen, A.; Prokop, M.; Pedersen, J.H.

2010-01-01

We examined the reproducibility of lung nodule volumetry software that offers three different volumetry algorithms. In a lung cancer screening trial, 188 baseline nodules >5 mm were identified. Including follow-ups, these nodules formed a study-set of 545 nodules. Nodules were independently double read by two readers using commercially available volumetry software. The software offers readers three different analysing algorithms. We compared the inter-observer variability of nodule volumetry when the readers used the same and different algorithms. Both readers were able to correctly segment and measure 72% of nodules. In 80% of these cases, the readers chose the same algorithm. When readers used the same algorithm, exactly the same volume was measured in 50% of readings and a difference of >25% was observed in 4%. When the readers used different algorithms, 83% of measurements showed a difference of >25%. Modern volumetric software failed to correctly segment a high number of screen detected nodules. While choosing a different algorithm can yield better segmentation of a lung nodule, reproducibility of volumetric measurements deteriorates substantially when different algorithms were used. It is crucial even in the same software package to choose identical parameters for follow-up. (orig.)

[Role of MRI for detection and characterization of pulmonary nodules].

Science.gov (United States)

Sommer, G; Koenigkam-Santos, M; Biederer, J; Puderbach, M

2014-05-01

Due to physical and technical limitations, magnetic resonance imaging (MRI) has hitherto played only a minor role in image-based diagnostics of the lungs. However, as a consequence of important methodological developments during recent years, MRI has developed into a technically mature and clinically well-proven method for specific pulmonary questions. The purpose of this article is to provide an overview on the currently available sequences and techniques for assessment of pulmonary nodules and analyzes the clinical significance according to the current literature. The main focus is on the detection of lung metastases, the detection of primary pulmonary malignancies in high-risk individuals and the differentiation between pulmonary nodules of benign and malignant character. The MRI technique has a sensitivity of approximately 80 % for detection of malignant pulmonary nodules compared to the reference standard low-dose computed tomography (CT) and is thus somewhat inferior to CT. Advantages of MRI on the other hand are a higher specificity in differentiating malignant and benign pulmonary nodules and the absence of ionizing radiation exposure. A systematic use of MRI as a primary tool for detection and characterization of pulmonary nodules is currently not recommended due to insufficient data. The diagnostic potential of MRI for early detection and staging of malignant pulmonary diseases, however, seems promising. Therefore, further evaluation of MRI as a secondary imaging modality in clinical trials is highly warranted.

Improved pulmonary nodule classification utilizing quantitative lung parenchyma features.

Science.gov (United States)

Dilger, Samantha K N; Uthoff, Johanna; Judisch, Alexandra; Hammond, Emily; Mott, Sarah L; Smith, Brian J; Newell, John D; Hoffman, Eric A; Sieren, Jessica C

2015-10-01

Current computer-aided diagnosis (CAD) models for determining pulmonary nodule malignancy characterize nodule shape, density, and border in computed tomography (CT) data. Analyzing the lung parenchyma surrounding the nodule has been minimally explored. We hypothesize that improved nodule classification is achievable by including features quantified from the surrounding lung tissue. To explore this hypothesis, we have developed expanded quantitative CT feature extraction techniques, including volumetric Laws texture energy measures for the parenchyma and nodule, border descriptors using ray-casting and rubber-band straightening, histogram features characterizing densities, and global lung measurements. Using stepwise forward selection and leave-one-case-out cross-validation, a neural network was used for classification. When applied to 50 nodules (22 malignant and 28 benign) from high-resolution CT scans, 52 features (8 nodule, 39 parenchymal, and 5 global) were statistically significant. Nodule-only features yielded an area under the ROC curve of 0.918 (including nodule size) and 0.872 (excluding nodule size). Performance was improved through inclusion of parenchymal (0.938) and global features (0.932). These results show a trend toward increased performance when the parenchyma is included, coupled with the large number of significant parenchymal features that support our hypothesis: the pulmonary parenchyma is influenced differentially by malignant versus benign nodules, assisting CAD-based nodule characterizations.

Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography

International Nuclear Information System (INIS)

Suzuki, Kenji; Armato, Samuel G. III; Li, Feng; Sone, Shusuke; Doi, Kunio

2003-01-01

In this study, we investigated a pattern-recognition technique based on an artificial neural network (ANN), which is called a massive training artificial neural network (MTANN), for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography (CT) images. The MTANN consists of a modified multilayer ANN, which is capable of operating on image data directly. The MTANN is trained by use of a large number of subregions extracted from input images together with the teacher images containing the distribution for the 'likelihood of being a nodule'. The output image is obtained by scanning an input image with the MTANN. The distinction between a nodule and a non-nodule is made by use of a score which is defined from the output image of the trained MTANN. In order to eliminate various types of non-nodules, we extended the capability of a single MTANN, and developed a multiple MTANN (Multi-MTANN). The Multi-MTANN consists of plural MTANNs that are arranged in parallel. Each MTANN is trained by using the same nodules, but with a different type of non-nodule. Each MTANN acts as an expert for a specific type of non-nodule, e.g., five different MTANNs were trained to distinguish nodules from various-sized vessels; four other MTANNs were applied to eliminate some other opacities. The outputs of the MTANNs were combined by using the logical AND operation such that each of the trained MTANNs eliminated none of the nodules, but removed the specific type of non-nodule with which the MTANN was trained, and thus removed various types of non-nodules. The Multi-MTANN consisting of nine MTANNs was trained with 10 typical nodules and 10 non-nodules representing each of nine different non-nodule types (90 training non-nodules overall) in a training set. The trained Multi-MTANN was applied to the reduction of false positives reported by our current computerized scheme for lung nodule detection based on a database of 63 low-dose CT scans (1765

Use of Volumetry for Lung Nodule Management: Theory and Practice

NARCIS (Netherlands)

Devaraj, A.; Ginneken, B. van; Nair, A.; Baldwin, D.

2017-01-01

A consistent feature of many lung nodule management guidelines is the recommendation to evaluate nodule size by using diameter measurements and electronic calipers. Traditionally, the use of nodule volumetry applications has primarily been reserved for certain lung cancer screening trials rather

Use of Volumetry for Lung Nodule Management: Theory and Practice.

Science.gov (United States)

Devaraj, Anand; van Ginneken, Bram; Nair, Arjun; Baldwin, David

2017-09-01

A consistent feature of many lung nodule management guidelines is the recommendation to evaluate nodule size by using diameter measurements and electronic calipers. Traditionally, the use of nodule volumetry applications has primarily been reserved for certain lung cancer screening trials rather than clinical practice. However, even before the first nodule management guidelines were published more than a decade ago, research has been ongoing into the use of nodule volumetry as a means of measuring nodule size, and this research has accelerated in recent years. This article aims to provide radiologists with an up-to-date review of the most recent literature on volumetry and volume doubling times in lung nodule management, outlining their benefits and drawbacks. A brief technical review of typical volumetry applications is also provided. © RSNA, 2017.

Computerized Detection of Lung Nodules by Means of “Virtual Dual-Energy” Radiography

Science.gov (United States)

Chen, Sheng; Suzuki, Kenji

2014-01-01

Major challenges in current computer-aided detection (CADe) schemes for nodule detection in chest radiographs (CXRs) are to detect nodules that overlap with ribs and/or clavicles and to reduce the frequent false positives (FPs) caused by ribs. Detection of such nodules by a CADe scheme is very important, because radiologists are likely to miss such subtle nodules. Our purpose in this study was to develop a CADe scheme with improved sensitivity and specificity by use of “virtual dual-energy” (VDE) CXRs where ribs and clavicles are suppressed with massive-training artificial neural networks (MTANNs). To reduce rib-induced FPs and detect nodules overlapping with ribs, we incorporated the VDE technology in our CADe scheme. The VDE technology suppressed rib and clavicle opacities in CXRs while maintaining soft-tissue opacity by use of the MTANN technique that had been trained with real dual-energy imaging. Our scheme detected nodule candidates on VDE images by use of a morphologic filtering technique. Sixty morphologic and gray-level-based features were extracted from each candidate from both original and VDE CXRs. A nonlinear support vector classifier was employed for classification of the nodule candidates. A publicly available database containing 140 nodules in 140 CXRs and 93 normal CXRs was used for testing our CADe scheme. All nodules were confirmed by computed tomography examinations, and the average size of the nodules was 17.8 mm. Thirty percent (42/140) of the nodules were rated “extremely subtle” or “very subtle” by a radiologist. The original scheme without VDE technology achieved a sensitivity of 78.6% (110/140) with 5 (1165/233) FPs per image. By use of the VDE technology, more nodules overlapping with ribs or clavicles were detected and the sensitivity was improved substantially to 85.0% (119/140) at the same FP rate in a leave-one-out cross-validation test, whereas the FP rate was reduced to 2.5 (583/233) per image at the same sensitivity

Automatic detection of pulmonary nodules at spiral CT: clinical application of a computer-aided diagnosis system

International Nuclear Information System (INIS)

Wormanns, Dag; Fiebich, Martin; Saidi, Mustafa; Diederich, Stefan; Heindel, Walter

2002-01-01

The aim of this study was to evaluate a computer-aided diagnosis (CAD) workstation with automatic detection of pulmonary nodules at low-dose spiral CT in a clinical setting for early detection of lung cancer. Eighty-eight consecutive spiral-CT examinations were reported by two radiologists in consensus. All examinations were reviewed using a CAD workstation with a self-developed algorithm for automatic detection of pulmonary nodules. The algorithm is designed to detect nodules with diameters of at least 5 mm. A total of 153 nodules were detected with at least one modality (radiologists in consensus, CAD, 85 nodules with diameter <5 mm, 68 with diameter ≥5 mm). The results of automatic nodule detection were compared to nodules detected with any modality as gold standard. Computer-aided diagnosis correctly identified 26 of 59 (38%) nodules with diameters ≥5 mm detected by visual assessment by the radiologists; of these, CAD detected 44% (24 of 54) nodules without pleural contact. In addition, 12 nodules ≥5 mm were detected which were not mentioned in the radiologist's report but represented real nodules. Sensitivity for detection of nodules ≥5 mm was 85% (58 of 68) for radiologists and 38% (26 of 68) for CAD. There were 5.8±3.6 false-positive results of CAD per CT study. Computer-aided diagnosis improves detection of pulmonary nodules at spiral CT and is a valuable second opinion in a clinical setting for lung cancer screening despite of its still limited sensitivity. (orig.)

Dynamic Gd-DTPA enhanced breath-hold 1.5 t MRI of normal lungs and patients with interstitial lung disease and pulmonary nodules: preliminary results

International Nuclear Information System (INIS)

Semelka, R.C.; Maycher, B.; Shoenut, J.P.; Kroeker, R.; Griffin, P.; Lertzman, M.

1992-01-01

A FLASH technique was used, which encompassed the entire thorax in the transverse plane, before and after dynamic intravenous injection of godalinium DTPA (Gd-DTPA) to study 7 patients with normal lungs, 12 patients with interstitial lung disease (ILD), and 11 patients with pulmonary nodules. Comparative CT studies were obtained within 2 weeks of the MRI study in the patients with lung disease. Quantitative signal intensity (SI) measurements were performed. Qualitative evaluation of lung parenchyma was determined in a prospective blinded fashion, and in the normal group comparison was made with the CT images. In normal patients, SI of lung parenchyma increased by 7.7±1.3%. On precontrast images, second-order pulmonary branchings were visible while post-contrast, fifth- to sixth-order branches were apparent. In patients with ILD, interstitial changes enhanced to a variable extent, increases in SI ranging from minimal (49.9%) to substantial (308.4%). Detection of pulmonary nodules improved following contrast injection. The minimum lesion size detectable decreased from 8 mm precontrast to 5 mm post-contrast. Percentage contrast enhancement was greater for malignant nodules (124.2±79.7%) than benign nodules (5.8±4.7%) (p<0.01). (orig.)

Computer aided detection system for lung cancer using computer tomography scans

Science.gov (United States)

Mahesh, Shanthi; Rakesh, Spoorthi; Patil, Vidya C.

2018-04-01

Lung Cancer is a disease can be defined as uncontrolled cell growth in tissues of the lung. If we detect the Lung Cancer in its early stage, then that could be the key of its cure. In this work the non-invasive methods are studied for assisting in nodule detection. It supplies a Computer Aided Diagnosis System (CAD) for early detection of lung cancer nodules from the Computer Tomography (CT) images. CAD system is the one which helps to improve the diagnostic performance of radiologists in their image interpretations. The main aim of this technique is to develop a CAD system for finding the lung cancer using the lung CT images and classify the nodule as Benign or Malignant. For classifying cancer cells, SVM classifier is used. Here, image processing techniques have been used to de-noise, to enhance, for segmentation and edge detection of an image is used to extract the area, perimeter and shape of nodule. The core factors of this research are Image quality and accuracy.

Computer-aided detection of pulmonary nodules: influence of nodule characteristics on detection performance

International Nuclear Information System (INIS)

Marten, K.; Engelke, C.; Seyfarth, T.; Grillhoesl, A.; Obenauer, S.; Rummeny, E.J.

2005-01-01

AIM: To evaluate prospectively the influence of pulmonary nodule characteristics on detection performances of a computer-aided diagnosis (CAD) tool and experienced chest radiologists using multislice CT (MSCT). MATERIALS AND METHODS: MSCT scans of 20 consecutive patients were evaluated by a CAD system and two independent chest radiologists for presence of pulmonary nodules. Nodule size, position, margin, matrix characteristics, vascular and pleural attachments and reader confidence were recorded and data compared with an independent standard of reference. Statistical analysis for predictors influencing nodule detection or reader performance included chi-squared, retrograde stepwise conditional logistic regression with odds ratios and nodule detection proportion estimates (DPE), and ROC analysis. RESULTS: For 135 nodules, detection rates for CAD and readers were 76.3, 52.6 and 52.6%, respectively; false-positive rates were 0.55, 0.25 and 0.15 per examination, respectively. In consensus with CAD the reader detection rate increased to 93.3%, and the false-positive rate dropped to 0.1/scan. DPEs for nodules ≤5 mm were significantly higher for ICAD than for the readers (p<0.05). Absence of vascular attachment was the only significant predictor of nodule detection by CAD (p=0.0006-0.008). There were no predictors of nodule detection for reader consensus with CAD. In contrast, vascular attachment predicted nodule detection by the readers (p=0.0001-0.003). Reader sensitivity was higher for nodules with vascular attachment than for unattached nodules (sensitivities 0.768 and 0.369; 95% confidence intervals=0.651-0.861 and 0.253-0.498, respectively). CONCLUSION: CAD increases nodule detection rates, decreases false-positive rates and compensates for deficient reader performance in detection of smallest lesions and of nodules without vascular attachment

TU-G-204-09: The Effects of Reduced- Dose Lung Cancer Screening CT On Lung Nodule Detection Using a CAD Algorithm

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Young, S; Lo, P; Kim, G; Hsu, W; Hoffman, J; Brown, M; McNitt-Gray, M [UCLA School of Medicine, Los Angeles, CA (United States)

2015-06-15

Purpose: While Lung Cancer Screening CT is being performed at low doses, the purpose of this study was to investigate the effects of further reducing dose on the performance of a CAD nodule-detection algorithm. Methods: We selected 50 cases from our local database of National Lung Screening Trial (NLST) patients for which we had both the image series and the raw CT data from the original scans. All scans were acquired with fixed mAs (25 for standard-sized patients, 40 for large patients) on a 64-slice scanner (Sensation 64, Siemens Healthcare). All images were reconstructed with 1-mm slice thickness, B50 kernel. 10 of the cases had at least one nodule reported on the NLST reader forms. Based on a previously-published technique, we added noise to the raw data to simulate reduced-dose versions of each case at 50% and 25% of the original NLST dose (i.e. approximately 1.0 and 0.5 mGy CTDIvol). For each case at each dose level, the CAD detection algorithm was run and nodules greater than 4 mm in diameter were reported. These CAD results were compared to “truth”, defined as the approximate nodule centroids from the NLST reports. Subject-level mean sensitivities and false-positive rates were calculated for each dose level. Results: The mean sensitivities of the CAD algorithm were 35% at the original dose, 20% at 50% dose, and 42.5% at 25% dose. The false-positive rates, in decreasing-dose order, were 3.7, 2.9, and 10 per case. In certain cases, particularly in larger patients, there were severe photon-starvation artifacts, especially in the apical region due to the high-attenuating shoulders. Conclusion: The detection task was challenging for the CAD algorithm at all dose levels, including the original NLST dose. However, the false-positive rate at 25% dose approximately tripled, suggesting a loss of CAD robustness somewhere between 0.5 and 1.0 mGy. NCI grant U01 CA181156 (Quantitative Imaging Network); Tobacco Related Disease Research Project grant 22RT-0131.

TU-G-204-09: The Effects of Reduced- Dose Lung Cancer Screening CT On Lung Nodule Detection Using a CAD Algorithm

International Nuclear Information System (INIS)

Young, S; Lo, P; Kim, G; Hsu, W; Hoffman, J; Brown, M; McNitt-Gray, M

2015-01-01

Purpose: While Lung Cancer Screening CT is being performed at low doses, the purpose of this study was to investigate the effects of further reducing dose on the performance of a CAD nodule-detection algorithm. Methods: We selected 50 cases from our local database of National Lung Screening Trial (NLST) patients for which we had both the image series and the raw CT data from the original scans. All scans were acquired with fixed mAs (25 for standard-sized patients, 40 for large patients) on a 64-slice scanner (Sensation 64, Siemens Healthcare). All images were reconstructed with 1-mm slice thickness, B50 kernel. 10 of the cases had at least one nodule reported on the NLST reader forms. Based on a previously-published technique, we added noise to the raw data to simulate reduced-dose versions of each case at 50% and 25% of the original NLST dose (i.e. approximately 1.0 and 0.5 mGy CTDIvol). For each case at each dose level, the CAD detection algorithm was run and nodules greater than 4 mm in diameter were reported. These CAD results were compared to “truth”, defined as the approximate nodule centroids from the NLST reports. Subject-level mean sensitivities and false-positive rates were calculated for each dose level. Results: The mean sensitivities of the CAD algorithm were 35% at the original dose, 20% at 50% dose, and 42.5% at 25% dose. The false-positive rates, in decreasing-dose order, were 3.7, 2.9, and 10 per case. In certain cases, particularly in larger patients, there were severe photon-starvation artifacts, especially in the apical region due to the high-attenuating shoulders. Conclusion: The detection task was challenging for the CAD algorithm at all dose levels, including the original NLST dose. However, the false-positive rate at 25% dose approximately tripled, suggesting a loss of CAD robustness somewhere between 0.5 and 1.0 mGy. NCI grant U01 CA181156 (Quantitative Imaging Network); Tobacco Related Disease Research Project grant 22RT-0131

Approaches to juxta-pleural nodule detection in CT images within the MAGIC-5 Collaboration

Energy Technology Data Exchange (ETDEWEB)

De Nunzio, G., E-mail: giorgio.denunzio@unisalento.it [University of Salento, Materials Science Department and Istituto Nazionale di Fisica Nucleare (INFN), Lecce (Italy); Massafra, A. [University of Salento, Physics Department and Istituto Nazionale di Fisica Nucleare (INFN), Lecce (Italy); Cataldo, R. [University of Salento, Materials Science Department and Istituto Nazionale di Fisica Nucleare (INFN), Lecce (Italy); De Mitri, I.; Peccarisi, M. [University of Salento, Physics Department and Istituto Nazionale di Fisica Nucleare (INFN), Lecce (Italy); Fantacci, M.E. [University of Pisa, Physics Department and Istituto Nazionale di Fisica Nucleare (INFN), Pisa (Italy); Gargano, G. [University of Bari, Physics Department and Istituto Nazionale di Fisica Nucleare (INFN), Bari (Italy); Lopez Torres, E. [CEADEN, Havana (Cuba)

2011-08-21

This work is a part of the MAGIC-5 (Medical Applications on a Grid Infrastructure Connection) experiment of the Italian INFN (Istituto Nazionale di Fisica Nucleare). A simple CAD (Computer-Assisted Detection) system for juxta-pleural lung nodules in CT images is presented, with the purpose of comparing different 2D concavity-patching techniques and assessing the respective efficiency in locating nodules. After a short introduction on the motivation, and a review of some CAD systems for lung nodules already published by the MAGIC-5 Collaboration, the paper describes the main lines of this particular approach, giving preliminary results and comments. In our procedure, candidate nodules are identified by patching lung border concavities in a hierarchical multiscale framework. Once located, they are fed to an artificial neural network for false positive reduction. The system has a modular structure that easily allows the insertion of arbitrary border-smoothing functions for concavity detection and nodule searching. In this paper the {alpha}-hull and morphological closing are compared, proving the higher sensitivity of the former, which also appears computationally less heavy.

Radiographic test phantom for computed tomographic lung nodule analysis

International Nuclear Information System (INIS)

Zerhouni, E.A.

1987-01-01

This patent describes a method for evaluating a computed tomograph scan of a nodule in a lung of a human or non-human animal. The method comprises generating a computer tomograph of a transverse section of the animal containing lung and nodule tissue, and generating a second computer tomograph of a test phantom comprising a device which simulates the transverse section of the animal. The tissue simulating portions of the device are constructed of materials having radiographic densities substantially identical to those of the corresponding tissue in the simulated transverse section of the animal and have voids therein which simulate, in size and shape, the lung cavities in the transverse section and which contain a test reference nodule constructed of a material of predetermined radiographic density which simulates in size, shape and position within a lung cavity void of the test phantom the nodule in the transverse section of the animal and comparing the respective tomographs

Automated system for lung nodules classification based on wavelet feature descriptor and support vector machine.

Science.gov (United States)

Madero Orozco, Hiram; Vergara Villegas, Osslan Osiris; Cruz Sánchez, Vianey Guadalupe; Ochoa Domínguez, Humberto de Jesús; Nandayapa Alfaro, Manuel de Jesús

2015-02-12

Lung cancer is a leading cause of death worldwide; it refers to the uncontrolled growth of abnormal cells in the lung. A computed tomography (CT) scan of the thorax is the most sensitive method for detecting cancerous lung nodules. A lung nodule is a round lesion which can be either non-cancerous or cancerous. In the CT, the lung cancer is observed as round white shadow nodules. The possibility to obtain a manually accurate interpretation from CT scans demands a big effort by the radiologist and might be a fatiguing process. Therefore, the design of a computer-aided diagnosis (CADx) system would be helpful as a second opinion tool. The stages of the proposed CADx are: a supervised extraction of the region of interest to eliminate the shape differences among CT images. The Daubechies db1, db2, and db4 wavelet transforms are computed with one and two levels of decomposition. After that, 19 features are computed from each wavelet sub-band. Then, the sub-band and attribute selection is performed. As a result, 11 features are selected and combined in pairs as inputs to the support vector machine (SVM), which is used to distinguish CT images containing cancerous nodules from those not containing nodules. The clinical data set used for experiments consists of 45 CT scans from ELCAP and LIDC. For the training stage 61 CT images were used (36 with cancerous lung nodules and 25 without lung nodules). The system performance was tested with 45 CT scans (23 CT scans with lung nodules and 22 without nodules), different from that used for training. The results obtained show that the methodology successfully classifies cancerous nodules with a diameter from 2 mm to 30 mm. The total preciseness obtained was 82%; the sensitivity was 90.90%, whereas the specificity was 73.91%. The CADx system presented is competitive with other literature systems in terms of sensitivity. The system reduces the complexity of classification by not performing the typical segmentation stage of most CADx

Adaptive statistical iterative reconstruction-applied ultra-low-dose CT with radiography- comparable radiation dose: Usefulness for lung nodule detection

International Nuclear Information System (INIS)

Yoon, Hyun Jung; Chung, Myung Jin; Hwang, Hye Sun; Lee, Kyung Soo; Moon, Jung Won

2015-01-01

To assess the performance of adaptive statistical iterative reconstruction (ASIR)-applied ultra-low-dose CT (ULDCT) in detecting small lung nodules. Thirty patients underwent both ULDCT and standard dose CT (SCT). After determining the reference standard nodules, five observers, blinded to the reference standard reading results, independently evaluated SCT and both subsets of ASIR- and filtered back projection (FBP)-driven ULDCT images. Data assessed by observers were compared statistically. Converted effective doses in SCT and ULDCT were 2.81 ± 0.92 and 0.17 ± 0.02 mSv, respectively. A total of 114 lung nodules were detected on SCT as a standard reference. There was no statistically significant difference in sensitivity between ASIR-driven ULDCT and SCT for three out of the five observers (p = 0.678, 0.735, < 0.01, 0.038, and < 0.868 for observers 1, 2, 3, 4, and 5, respectively). The sensitivity of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT in three out of the five observers (p < 0.01 for three observers, and p = 0.064 and 0.146 for two observers). In jackknife alternative free-response receiver operating characteristic analysis, the mean values of figure-of-merit (FOM) for FBP, ASIR-driven ULDCT, and SCT were 0.682, 0.772, and 0.821, respectively, and there were no significant differences in FOM values between ASIR-driven ULDCT and SCT (p = 0.11), but the FOM value of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT and SCT (p = 0.01 and 0.00). Adaptive statistical iterative reconstruction-driven ULDCT delivering a radiation dose of only 0.17 mSv offers acceptable sensitivity in nodule detection compared with SCT and has better performance than FBP-driven ULDCT

Adaptive statistical iterative reconstruction-applied ultra-low-dose CT with radiography- comparable radiation dose: Usefulness for lung nodule detection

Energy Technology Data Exchange (ETDEWEB)

Yoon, Hyun Jung; Chung, Myung Jin; Hwang, Hye Sun; Lee, Kyung Soo [Dept. of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of); Moon, Jung Won [Dept. of Radiology, Kangbuk Samsung Hospital, Seoul (Korea, Republic of)

2015-10-15

To assess the performance of adaptive statistical iterative reconstruction (ASIR)-applied ultra-low-dose CT (ULDCT) in detecting small lung nodules. Thirty patients underwent both ULDCT and standard dose CT (SCT). After determining the reference standard nodules, five observers, blinded to the reference standard reading results, independently evaluated SCT and both subsets of ASIR- and filtered back projection (FBP)-driven ULDCT images. Data assessed by observers were compared statistically. Converted effective doses in SCT and ULDCT were 2.81 ± 0.92 and 0.17 ± 0.02 mSv, respectively. A total of 114 lung nodules were detected on SCT as a standard reference. There was no statistically significant difference in sensitivity between ASIR-driven ULDCT and SCT for three out of the five observers (p = 0.678, 0.735, < 0.01, 0.038, and < 0.868 for observers 1, 2, 3, 4, and 5, respectively). The sensitivity of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT in three out of the five observers (p < 0.01 for three observers, and p = 0.064 and 0.146 for two observers). In jackknife alternative free-response receiver operating characteristic analysis, the mean values of figure-of-merit (FOM) for FBP, ASIR-driven ULDCT, and SCT were 0.682, 0.772, and 0.821, respectively, and there were no significant differences in FOM values between ASIR-driven ULDCT and SCT (p = 0.11), but the FOM value of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT and SCT (p = 0.01 and 0.00). Adaptive statistical iterative reconstruction-driven ULDCT delivering a radiation dose of only 0.17 mSv offers acceptable sensitivity in nodule detection compared with SCT and has better performance than FBP-driven ULDCT.

Computer-aided detection of artificial pulmonary nodules using an ex vivo lung phantom: influence of exposure parameters and iterative reconstruction.

Science.gov (United States)

Wielpütz, Mark O; Wroblewski, Jacek; Lederlin, Mathieu; Dinkel, Julien; Eichinger, Monika; Koenigkam-Santos, M; Biederer, Jürgen; Kauczor, Hans-Ulrich; Puderbach, Michael U; Jobst, Bertram J

2015-05-01

To evaluate the influence of exposure parameters and raw-data based iterative reconstruction (IR) on the performance of computer-aided detection (CAD) of pulmonary nodules on chest multidetector computed tomography (MDCT). Seven porcine lung explants were inflated in a dedicated ex vivo phantom shell and prepared with n=162 artificial nodules of a clinically relevant volume and maximum diameter (46-1063 μl, and 6.2-21.5 mm). n=118 nodules were solid and n=44 part-solid. MDCT was performed with different combinations of 120 and 80 kV with 120, 60, 30 and 12 mA*s, and reconstructed with both filtered back projection (FBP) and IR. Subsequently, 16 datasets per lung were subjected to dedicated CAD software. The rate of true positive, false negative and false positive CAD marks was measured for each reconstruction. The rate of true positive findings ranged between 88.9-91.4% for FBP and 88.3-90.1% for IR (n.s.) with most exposure settings, but was significantly lower with the combination of 80 kV and 12 mA*s (80.9% and 81.5%, respectively, pvolumes 300 μl (p<0.05). Similarly, it was significantly lower for diameters <12 mm compared to ≥12 mm (p<0.05). The rate of true positives for solid and part-solid nodules was similar. Nodule CAD on chest MDCT is robust over a wide range of exposure settings. Noise reduction by IR is not detrimental for CAD, and may be used to improve image quality in the setting of low-dose MDCT for lung cancer screening. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Evaluation of an improved method of simulating lung nodules in chest tomosynthesis

International Nuclear Information System (INIS)

Svalkvist, Angelica; Allansdotter Johnsson, Aase; Vikgren, Jenny

2012-01-01

Background Simulated pathology is a valuable complement to clinical images in studies aiming at evaluating an imaging technique. In order for a study using simulated pathology to be valid, it is important that the simulated pathology in a realistic way reflect the characteristics of real pathology. Purpose To perform a thorough evaluation of a nodule simulation method for chest tomosynthesis, comparing the detection rate and appearance of the artificial nodules with those of real nodules in an observer performance experiment. Material and Methods A cohort consisting of 64 patients, 38 patients with a total of 129 identified pulmonary nodules and 26 patients without identified pulmonary nodules, was used in the study. Simulated nodules, matching the real clinically found pulmonary nodules by size, attenuation, and location, were created and randomly inserted into the tomosynthesis section images of the patients. Three thoracic radiologists and one radiology resident reviewed the images in an observer performance study divided into two parts. The first part included nodule detection and the second part included rating of the visual appearance of the nodules. The results were evaluated using a modified receiver-operating characteristic (ROC) analysis. Results The sensitivities for real and simulated nodules were comparable, as the area under the modified ROC curve (AUC) was close to 0.5 for all observers (range, 0.43-0.55). Even though the ratings of visual appearance for real and simulated nodules overlapped considerably, the statistical analysis revealed that the observers to were able to separate simulated nodules from real nodules (AUC values range 0.70-0.74). Conclusion The simulation method can be used to create artificial lung nodules that have similar detectability as real nodules in chest tomosynthesis, although experienced thoracic radiologists may be able to distinguish them from real nodules

The MAGIC-5 CAD for nodule detection in low dose and thin slice lung CTs

International Nuclear Information System (INIS)

Cerello, Piergiorgio

2010-01-01

Lung cancer is the leading cause of cancer-related mortality in developed countries. Only 10-15% of all men and women diagnosed with lung cancer live 5 years after the diagnosis. However, the 5-year survival rate for patients diagnosed in the early asymptomatic stage of the disease can reach 70%. Early-stage lung cancers can be diagnosed by detecting non-calcified small pulmonary nodules with computed tomography (CT). Computer-aided detection (CAD) could support radiologists in the analysis of the large amount of noisy images generated in screening programs, where low-dose and thin-slice settings are used. The MAGIC-5 project, funded by the Istituto Nazionale di Fisica Nucleare (INFN, Italy) and Ministero dell'Universita e della Ricerca (MUR, Italy), developed a multi-method approach based on three CAD algorithms to be used in parallel with a merging of their results: the Channeler Ant Model (CAM), based on Virtual Ant Colonies, the Dot-Enhancement/Pleura Surface Normals/VBNA (DE-PSN-VBNA), and the Region Growing Volume Plateau (RGVP). Preliminary results show quite good performances, to be improved with the refining of the single algorithm and the added value of the results merging.

Clinical impact of abnormal FDG uptake in pulmonary nodules detected by CT in patients with only history of non-lung cancers

International Nuclear Information System (INIS)

Wong, C.O.; Nunez, R.; Welsh, R.J.; Chmielewski, G.W.; Hill, E.A.; Hill, J.C.; Ravikrishnan, K.P.; Darlene Fink-Bennett; Dworkin, H.J.

2001-01-01

Objective: The aim is to assess the clinical impact of positive FDG uptake in single (SPN) or multiple (MPN) pulmonary nodules detected by CT in patients with known past history of non-lung cancers (but no known lung cancers). Materials and Methods: Twenty-eight sequential patients with non-lung cancers (15 breast, 8 colon, 5 prostate) referred for evaluation of SPN or MPN by PET over a period of two years were included. F-18 FDG PET images, covering chest and upper abdomen, were interpreted blindly and then correlated with CT findings for the precise location of abnormal FDG uptake in the chest. Results: There was a significant number of abnormal FDG uptake in both SPN or MPN. Positive abnormal uptake suggestive of malignancy was found in 25% of patients in the form of SPN and 39% of patients in the form of MPN (p<0.03). Positive cases in the pattern of multiple foci of pulmonary uptake were attributed to metastatic disease. Otherwise positive cases were followed by tissue diagnosis and/or surgical attention. The negative cases were followed clinically. Of the 11 positive cases of MPN, 2 patients (18%) showed only abnormal FDG uptake in just one of the nodules, which was later confirmed at surgery to be a primary cancer of lung in both patients. Conclusion: These results suggest that PET scan would be just as useful in patients with SPN and known non-lung cancers as other patients with no history of any cancers. Not all patients with non-lung cancer and MPN have pulmonary metastasis by PET criteria. PET may single out a primary lung malignancy in patients with non-lung cancer and MPN. PET has thus great clinical impact in these patients with pulmonary nodules and known non-lung cancers as the management would otherwise be completely different in situations revealed by the study

Development and evaluation of a computer-aided diagnostic scheme for lung nodule detection in chest radiographs by means of two-stage nodule enhancement with support vector classification

International Nuclear Information System (INIS)

Chen Sheng; Suzuki, Kenji; MacMahon, Heber

2011-01-01

Purpose: To develop a computer-aided detection (CADe) scheme for nodules in chest radiographs (CXRs) with a high sensitivity and a low false-positive (FP) rate. Methods: The authors developed a CADe scheme consisting of five major steps, which were developed for improving the overall performance of CADe schemes. First, to segment the lung fields accurately, the authors developed a multisegment active shape model. Then, a two-stage nodule-enhancement technique was developed for improving the conspicuity of nodules. Initial nodule candidates were detected and segmented by using the clustering watershed algorithm. Thirty-one shape-, gray-level-, surface-, and gradient-based features were extracted from each segmented candidate for determining the feature space, including one of the new features based on the Canny edge detector to eliminate a major FP source caused by rib crossings. Finally, a nonlinear support vector machine (SVM) with a Gaussian kernel was employed for classification of the nodule candidates. Results: To evaluate and compare the scheme to other published CADe schemes, the authors used a publicly available database containing 140 nodules in 140 CXRs and 93 normal CXRs. The CADe scheme based on the SVM classifier achieved sensitivities of 78.6% (110/140) and 71.4% (100/140) with averages of 5.0 (1165/233) FPs/image and 2.0 (466/233) FPs/image, respectively, in a leave-one-out cross-validation test, whereas the CADe scheme based on a linear discriminant analysis classifier had a sensitivity of 60.7% (85/140) at an FP rate of 5.0 FPs/image. For nodules classified as ''very subtle'' and ''extremely subtle,'' a sensitivity of 57.1% (24/42) was achieved at an FP rate of 5.0 FPs/image. When the authors used a database developed at the University of Chicago, the sensitivities was 83.3% (40/48) and 77.1% (37/48) at an FP rate of 5.0 (240/48) FPs/image and 2.0 (96/48) FPs /image, respectively. Conclusions: These results compare favorably to those described for

Lung nodule volumetry: segmentation algorithms within the same software package cannot be used interchangeably.

NARCIS (Netherlands)

Ashraf, H.; Hoop, B.J. de; Shaker, S.B.; Dirksen, A.; Bach, K.S.; Hansen, H.; Prokop, M.; Pedersen, J.H.

2010-01-01

OBJECTIVE: We examined the reproducibility of lung nodule volumetry software that offers three different volumetry algorithms. METHODS: In a lung cancer screening trial, 188 baseline nodules >5 mm were identified. Including follow-ups, these nodules formed a study-set of 545 nodules. Nodules were

Characteristic CT Findings After Percutaneous Cryoablation Treatment of Malignant Lung Nodules.

Science.gov (United States)

Chaudhry, Ammar; Grechushkin, Vadim; Hoshmand, Mahsa; Kim, Choo Won; Pena, Andres; Huston, Brett; Chaya, Yair; Bilfinger, Thomas; Moore, William

2015-10-01

Assess computed tomography (CT) imaging characteristics after percutaneous cryotherapy for lung cancer.A retrospective IRB-approved analysis of 40 patients who underwent nonsurgical treatment for primary stage 1 lung cancer performed from January 2007 to March 2011 was included in this study. All procedures were performed using general anesthesia and CT guidance. Follow-up imaging with CT of the chest was obtained at 1 month, 3 months, 6 months, and 12 months postprocedure to evaluate the ablated lung nodule. Nodule surface area, density (in Hounsfield units), and presence or absence of cavitations were recorded. In addition, the degree of nodule enhancement was also recorded. Patients who were unable to obtain the aforementioned follow-up were excluded from the study.Thirty-six patients underwent percutaneous cryoablation with men to women ratio of 75% with mean age for men 74.6 and mean age for women 74.3 years of age. The average nodule surface area preablation and postcryoablation at 1-, 3-, 6-, and 12-month follow-ups were 2.99, 7.86, 3.89, 3.18 and 3.07[REPLACEMENT CHARACTER]cm, respectively. The average precontrast nodule density before cryoablation was 8.9 and average precontrast nodule density postprocedure at 1, 3, 6, and 12 months follow-ups were 8.5, -5.9, -9.4, and -3.8 HU, respectively. There is increased attenuation of lung nodules over time with an average postcontrast enhancement of 11.4, 18.5, 16.1, and 25.7 HU at the aforementioned time intervals. Cavitations occurred in the cryoablation zone in 53% (19/36) of patients. 80.6% (29/36) of the cavitations in the cryoablation zone resolved within 12 months. Four patients (11%) had recurrence of tumor at the site of cryoablation and none of the patients had satellite or distant metastasis.Our study shows that patients who underwent cryotherapy for lung nodules treatment had characteristic changes on follow-up CT including. The surface area of the nodule increases at the 1-month follow-up with

Cloud-Based NoSQL Open Database of Pulmonary Nodules for Computer-Aided Lung Cancer Diagnosis and Reproducible Research.

Science.gov (United States)

Ferreira Junior, José Raniery; Oliveira, Marcelo Costa; de Azevedo-Marques, Paulo Mazzoncini

2016-12-01

Lung cancer is the leading cause of cancer-related deaths in the world, and its main manifestation is pulmonary nodules. Detection and classification of pulmonary nodules are challenging tasks that must be done by qualified specialists, but image interpretation errors make those tasks difficult. In order to aid radiologists on those hard tasks, it is important to integrate the computer-based tools with the lesion detection, pathology diagnosis, and image interpretation processes. However, computer-aided diagnosis research faces the problem of not having enough shared medical reference data for the development, testing, and evaluation of computational methods for diagnosis. In order to minimize this problem, this paper presents a public nonrelational document-oriented cloud-based database of pulmonary nodules characterized by 3D texture attributes, identified by experienced radiologists and classified in nine different subjective characteristics by the same specialists. Our goal with the development of this database is to improve computer-aided lung cancer diagnosis and pulmonary nodule detection and classification research through the deployment of this database in a cloud Database as a Service framework. Pulmonary nodule data was provided by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), image descriptors were acquired by a volumetric texture analysis, and database schema was developed using a document-oriented Not only Structured Query Language (NoSQL) approach. The proposed database is now with 379 exams, 838 nodules, and 8237 images, 4029 of them are CT scans and 4208 manually segmented nodules, and it is allocated in a MongoDB instance on a cloud infrastructure.

A comparison of six software packages for evaluation of solid lung nodules using semi-automated volumetry: What is the minimum increase in size to detect growth in repeated CT examinations

International Nuclear Information System (INIS)

Hoop, Bartjan de; Gietema, Hester; Prokop, Mathias; Ginneken, Bram van; Zanen, Pieter; Groenewegen, Gerard

2009-01-01

We compared interexamination variability of CT lung nodule volumetry with six currently available semi-automated software packages to determine the minimum change needed to detect the growth of solid lung nodules. We had ethics committee approval. To simulate a follow-up examination with zero growth, we performed two low-dose unenhanced CT scans in 20 patients referred for pulmonary metastases. Between examinations, patients got off and on the table. Volumes of all pulmonary nodules were determined on both examinations using six nodule evaluation software packages. Variability (upper limit of the 95% confidence interval of the Bland-Altman plot) was calculated for nodules for which segmentation was visually rated as adequate. We evaluated 214 nodules (mean diameter 10.9 mm, range 3.3 mm-30.0 mm). Software packages provided adequate segmentation in 71% to 86% of nodules (p < 0.001). In case of adequate segmentation, variability in volumetry between scans ranged from 16.4% to 22.3% for the various software packages. Variability with five to six software packages was significantly less for nodules ≥8 mm in diameter (range 12.9%-17.1%) than for nodules <8 mm (range 18.5%-25.6%). Segmented volumes of each package were compared to each of the other packages. Systematic volume differences were detected in 11/15 comparisons. This hampers comparison of nodule volumes between software packages. (orig.)

Nodule detection in digital chest radiography: Summary of the radius chest trial

International Nuclear Information System (INIS)

Haakansson, M.; Baath, M.; Boerjesson, S.; Kheddache, S.; Grahn, A.; Ruschin, M.; Tingberg, A.; Mattson, S.; Maansson, L. G.

2005-01-01

As a part of the Europe-wide research project 'Unification of physical and clinical requirements for medical X-ray imaging' - governed by the Radiological Imaging Unification Strategies (RADIUS) Group - a major image quality trial was conducted by members of the group. The RADIUS chest trial aimed at thoroughly examining various aspects of nodule detection in digital chest radiography, such as the effects of nodule location, system noise, anatomical noise, and anatomical background. The main findings of the RADIUS chest trial concerning the detection of a lung nodule with a size in the order of 10 mm can be summarised as: (1) the detectability of the nodule is largely dependent on its location in the chest, (2) the system noise has a minor impact on the detectability at the dose levels used today, (3) the disturbance of the anatomical noise is larger than that of the system noise but smaller than that of the anatomical background and (4) the anatomical background acts as noise to a large extent and is the major image component affecting the detectability of the nodule. (authors)

Computer-aided detection of small pulmonary nodules in multidetector spiral computed tomography (MSCT) in children

International Nuclear Information System (INIS)

Honnef, D.; Behrendt, F.F.; Hohl, C.; Mahnken, A.H.; Guenther, R.W.; Das, M.; Mertens, R.; Stanzel, S.

2008-01-01

Purpose: Retrospective evaluation of computer-aided detection software (CAD) for automated detection (LungCAD, Siemens Medical solutions, Forchheim, Germany) and volumetry (LungCARE) of pulmonary nodules in dose-reduced pediatric MDCT. Materials and Methods: 30 scans of 24 children (10.4±5.9 years, 13 girls, 11 boys, 39.7±29.3 kg body weight) were performed on a 16-MDCT for tumor staging (n=18), inflammation (n=9), other indications (n=3). Tube voltage 120 kVp and effective mAs were adapted to body weight. Slice thickness 2 mm, increment 1 mm. A pediatric radiologist (U1), a CAD expert (U2) and an inexperienced radiologist (U3) independently analyzed the lung window images without and with the CAD as a second reader. In a consensus decision U1 and U2 were the reference standard. Results: Five examinations had to be excluded from the study due to other underlying lung disease. A total of 24 pulmonary nodules were found in all data sets with a minimal diameter of 0.35 mm to 3.81 mm (mean 1.7±0.85 mm). The sensitivities were as follows: U1 95.8% and 100% with CAD; U2 91.7% U3 66.7%. U2 and U3 did not detect further nodules with CAD. The sensitivity of CAD alone was 41.7% with 0.32 false-positive findings per examination. Interobserver agreement between U1/U2 regarding nodule detection with CAD was good (k=0.6500) and without CAD very good (k=0.8727). For the rest (U1/U3; U2/U3 with and without CAD), it was weak (k=0.0667-0.1884). Depending on the measured value (axial measurement, volume), there is a significant correlation (p=0.0026-0.0432) between nodule size and CAD detection. Undetected pulmonary nodules (mean 1.35 mm; range 0.35-2.61 mm) were smaller than the detected ones (mean 2.19 mm; range 1.35-3.81 mm). No significant correlation was found between CAD findings and patient age (p=0.9263) and body weight (p=0.9271) as well as nodule location (subpleural, intraparenchymal; p=1.0) and noise/SNR. (orig.)

Towards automatic pulmonary nodule management in lung cancer screening with deep learning.

Science.gov (United States)

Ciompi, Francesco; Chung, Kaman; van Riel, Sarah J; Setio, Arnaud Arindra Adiyoso; Gerke, Paul K; Jacobs, Colin; Scholten, Ernst Th; Schaefer-Prokop, Cornelia; Wille, Mathilde M W; Marchianò, Alfonso; Pastorino, Ugo; Prokop, Mathias; van Ginneken, Bram

2017-04-19

The introduction of lung cancer screening programs will produce an unprecedented amount of chest CT scans in the near future, which radiologists will have to read in order to decide on a patient follow-up strategy. According to the current guidelines, the workup of screen-detected nodules strongly relies on nodule size and nodule type. In this paper, we present a deep learning system based on multi-stream multi-scale convolutional networks, which automatically classifies all nodule types relevant for nodule workup. The system processes raw CT data containing a nodule without the need for any additional information such as nodule segmentation or nodule size and learns a representation of 3D data by analyzing an arbitrary number of 2D views of a given nodule. The deep learning system was trained with data from the Italian MILD screening trial and validated on an independent set of data from the Danish DLCST screening trial. We analyze the advantage of processing nodules at multiple scales with a multi-stream convolutional network architecture, and we show that the proposed deep learning system achieves performance at classifying nodule type that surpasses the one of classical machine learning approaches and is within the inter-observer variability among four experienced human observers.

Towards automatic pulmonary nodule management in lung cancer screening with deep learning

NARCIS (Netherlands)

Ciompi, F.; Chung, K; Riel, S.J. van; Setio, A.A.A.; Gerke, P.K.; Jacobs, C.; Scholten, E.T.; Schaefer-Prokop, C.M.; Wille, M.M.W.; Marchiano, A.; Pastorino, U.; Prokop, M.; Ginneken, B. van

2017-01-01

The introduction of lung cancer screening programs will produce an unprecedented amount of chest CT scans in the near future, which radiologists will have to read in order to decide on a patient follow-up strategy. According to the current guidelines, the workup of screen-detected nodules strongly

Automated lung module detection at low-dose CT: preliminary experience

International Nuclear Information System (INIS)

Goo, Jin-Mo; Lee, Jeong-Won; Lee, Hyun-Ju; Kim, Seung-Wan; Kim, Jong-Hyo; Im, Jung-Gi

2003-01-01

To determine the usefulness of a computer-aided diagnosis (CAD) system for the automated detection of lung nodules at low-dose CT. A CAD system developed for detecting lung nodules was used to process the data provided by 50 consecutive low-dose CT scans. The results of an initial report, a second look review by two chest radiologists, and those obtained by the CAD system were compared, and by reviewing all of these, a gold standard was established. By applying the gold standard, a total of 52 nodules were identified (26 with a diameter ≤ 5 mm; 26 with a diameter > 5 mm). Compared to an initial report, four additional nodules were detected by the CAD system. Three of these, identified only at CAD, formed part of the data used to derive the gold standard. For the detection of nodules > 5 mm in diameter, sensitivity was 77% for the initial report, for the second look review, and 88% for the second look review,and 65% for the CAD system. There were 8.0 ± 5.2 false-positive CAD results per CT study. These preliminary results indicate that a CAD system may improve the detection of pulmonary nodules at low-dose CT

Whether and under what conditions FDG-PET might be cost-effective in evaluating solitary pulmonary nodules depicted on lung cancer screening in Japan

International Nuclear Information System (INIS)

Tsushima, Yoshito; Aoki, Jun; Endo, Keigo

2003-01-01

The purpose of this study was to determine whether and under what conditions fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET) may be cost-effective in evaluating solitary pulmonary nodules depicted on lung cancer screening in Japan. Three decision models for differentiating lung cancer from benign nodules were compared: CT alone, PET alone, and CT plus PET. The various paths of each strategy were dependent on variables determined from a review of the medical literature. Costs were based on Japanese health insurance. The prevalence of lung cancer among solitary pulmonary nodules detected on lung cancer screening was less than 10%. For this prevalence, the CT-plus-PET model was the cost-effective alternative to the CT-alone model (cost savings were 64,000 yen per patient) and provided greater accuracy (0.90 vs. 0.84). Both of these effects were the result of reducing the number of candidates who undergo unnecessary CT-guided or bronchofiberscopic biopsies or thoracotomy for a benign pulmonary nodule. The CT-plus-PET strategy is accurate and cost-effective for the characterization of solitary pulmonary nodules detected on lung cancer screening in Japan. (author)

Ultralow dose CT for pulmonary nodule detection with chest X-ray equivalent dose - a prospective intra-individual comparative study

Energy Technology Data Exchange (ETDEWEB)

Messerli, Michael [University Zurich, Department of Nuclear Medicine, University Hospital Zurich, Zurich (Switzerland); Cantonal Hospital St. Gallen, Division of Radiology and Nuclear Medicine, St. Gallen (Switzerland); Kluckert, Thomas; Knitel, Meinhard; Desbiolles, Lotus; Bauer, Ralf W.; Wildermuth, Simon [Cantonal Hospital St. Gallen, Division of Radiology and Nuclear Medicine, St. Gallen (Switzerland); Waelti, Stephan [Cantonal Hospital St. Gallen, Division of Radiology and Nuclear Medicine, St. Gallen (Switzerland); University of Montreal, Department of Radiology, CHU Sainte-Justine, Montreal, Quebec (Canada); Rengier, Fabian [University Hospital Heidelberg, Department of Diagnostic and Interventional Radiology, Heidelberg (Germany); Warschkow, Rene [Cantonal Hospital St. Gallen, Department of Surgery, St. Gallen (Switzerland); Alkadhi, Hatem [University Zurich, Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich (Switzerland); Leschka, Sebastian [Cantonal Hospital St. Gallen, Division of Radiology and Nuclear Medicine, St. Gallen (Switzerland); University Zurich, Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich (Switzerland)

2017-08-15

To prospectively evaluate the accuracy of ultralow radiation dose CT of the chest with tin filtration at 100 kV for pulmonary nodule detection. 202 consecutive patients undergoing clinically indicated chest CT (standard dose, 1.8 ± 0.7 mSv) were prospectively included and additionally scanned with an ultralow dose protocol (0.13 ± 0.01 mSv). Standard dose CT was read in consensus by two board-certified radiologists to determine the presence of lung nodules and served as standard of reference (SOR). Two radiologists assessed the presence of lung nodules and their locations on ultralow dose CT. Sensitivity and specificity of the ultralow dose protocol was compared against the SOR, including subgroup analyses of different nodule sizes and types. A mixed effects logistic regression was used to test for independent predictors for sensitivity of pulmonary nodule detection. 425 nodules (mean diameter 3.7 ± 2.9 mm) were found on SOR. Overall sensitivity for nodule detection by ultralow dose CT was 91%. In multivariate analysis, nodule type, size and patients BMI were independent predictors for sensitivity (p < 0.001). Ultralow dose chest CT at 100 kV with spectral shaping enables a high sensitivity for the detection of pulmonary nodules at exposure levels comparable to plain film chest X-ray. (orig.)

The experimental study and clinical application on the detection of pulmonary nodules with low-dose multislice spiral CT

International Nuclear Information System (INIS)

Wu Xiaohua; Ma Daqing; Zhang Zhongjia; Ji Jingling; Zhang Yansong

2004-01-01

Objective: To investigate the detection rate of pulmonary nodules ,especially nodules ≤5 mm, in variable low-doses, and to evaluate the imaging quality of low-dose MSCT. Methods: Six postmortem specimens of patients with pneumoconiosis after necropsy were fixed at end-inspiratory volume. The fixed specimens were examined by using MSCT with standard dose (130 mA) and low-dose (50, 30, 10 mA, respectively). Low-dose MSCT scans of 40 asymptomatic volunteers and 60 patients with pulmonary metastasis were also examined with 30 mA. The numbers of pulmonary nodules less than 5 mm at standard-dose and different low-dose were recorded. Nodules were assessed by diagnostic confidence ('definite nodule', 'questionable nodule', and 'definite not nodule'). The number of images with artifact in specimens and in 40 volunteers and 60 patients with pulmonary metastasis were recorded. Results: In specimen's study, the Kappa values of groups of low-dose (50, 30, 10 mA) were 0.515, 0.242, and 0.154, respectively. The group of 50 mA had a good coincidence with standard-dose group by U test. The sensitivity of group 50, 30, 10 mA was 88.0%, 78.4%, and 75.0%, respectively. The positive predictive values of which were 98%, 94%, and 93%, respectively. The correction rates of which were 85%, 73%, and 69%, respectively. In specimens' images, subtle linear artifact was showed only in paravertebral lung field in 21 images of 31 at the group of 10 mA. Linear artifacts that affected small nodule detection were showed in lung apexes in 3 of 100 subjects. Conclusion: Low-dose MSCT is expected to improve early detection of lung cancer. Pulmonary nodules less than 5 mm could be reliably detected at 50 mA tube current in specimens. Low-dose CT (30 mA) showed satisfactory imaging quality in our study. Low-dose CT screening for lung cancer may be applied if situation permits. (authors)

Digital tomosynthesis for evaluating metastatic lung nodules: nodule visibility, learning curves, and reading times.

Science.gov (United States)

Lee, Kyung Hee; Goo, Jin Mo; Lee, Sang Min; Park, Chang Min; Bahn, Young Eun; Kim, Hyungjin; Song, Yong Sub; Hwang, Eui Jin

2015-01-01

To evaluate nodule visibility, learning curves, and reading times for digital tomosynthesis (DT). We included 80 patients who underwent computed tomography (CT) and DT before pulmonary metastasectomy. One experienced chest radiologist annotated all visible nodules on thin-section CT scans using computer-aided detection software. Two radiologists used CT as the reference standard and retrospectively graded the visibility of nodules on DT. Nodule detection performance was evaluated in four sessions of 20 cases each by six readers. After each session, readers were unblinded to the DT images by revealing the true-positive markings and were instructed to self-analyze their own misreads. Receiver-operating-characteristic curves were determined. Among 414 nodules on CT, 53.3% (221/414) were visible on DT. The main reason for not seeing a nodule on DT was small size (93.3%, ≤ 5 mm). DT revealed a substantial number of malignant nodules (84.1%, 143/170). The proportion of malignant nodules among visible nodules on DT was significantly higher (64.7%, 143/221) than that on CT (41.1%, 170/414) (p 0.8, and the average detection rate for malignant nodules was 85% (210/246). The inter-session analysis of the AUC showed no significant differences among the readers, and the detection rate for malignant nodules did not differ across sessions. A slight improvement in reading times was observed. Most malignant nodules > 5 mm were visible on DT. As nodule detection performance was high from the initial session, DT may be readily applicable for radiology residents and board-certified radiologists.

Phased searching with NEAT in a time-scaled framework: experiments on a computer-aided detection system for lung nodules.

Science.gov (United States)

Tan, Maxine; Deklerck, Rudi; Cornelis, Jan; Jansen, Bart

2013-11-01

In the field of computer-aided detection (CAD) systems for lung nodules in computed tomography (CT) scans, many image features are presented and many artificial neural network (ANN) classifiers with various structural topologies are analyzed; frequently, the classifier topologies are selected by trial-and-error experiments. To avoid these trial and error approaches, we present a novel classifier that evolves ANNs using genetic algorithms, called "Phased Searching with NEAT in a Time or Generation-Scaled Framework", integrating feature selection with the classification task. We analyzed our method's performance on 360 CT scans from the public Lung Image Database Consortium database. We compare our method's performance with other more-established classifiers, namely regular NEAT, Feature-Deselective NEAT (FD-NEAT), fixed-topology ANNs, and support vector machines (SVMs) using ten-fold cross-validation experiments of all 360 scans. The results show that the proposed "Phased Searching" method performs better and faster than regular NEAT, better than FD-NEAT, and achieves sensitivities at 3 and 4 false positives (FP) per scan that are comparable with the fixed-topology ANN and SVM classifiers, but with fewer input features. It achieves a detection sensitivity of 83.0±9.7% with an average of 4FP/scan, for nodules with a diameter greater than or equal to 3mm. It also evolves networks with shorter evolution times and with lower complexities than regular NEAT (p=0.026 and pNEAT and by our approach shows that our approach searches for good solutions in lower dimensional search spaces, and evolves networks without superfluous structure. We have presented a novel approach that combines feature selection with the evolution of ANN topology and weights. Compared with the original threshold-based Phased Searching method of Green, our method requires fewer parameters and converges to the optimal network complexity required for the classification task at hand. The results of the

Accuracy of lung nodule volumetry in low-dose CT with iterative reconstruction: an anthropomorphic thoracic phantom study.

Science.gov (United States)

Doo, K W; Kang, E-Y; Yong, H S; Woo, O H; Lee, K Y; Oh, Y-W

2014-09-01

The purpose of this study was to assess accuracy of lung nodule volumetry in low-dose CT with application of iterative reconstruction (IR) according to nodule size, nodule density and CT tube currents, using artificial lung nodules within an anthropomorphic thoracic phantom. Eight artificial nodules (four diameters: 5, 8, 10 and 12 mm; two CT densities: -630 HU that represents ground-glass nodule and +100 HU that represents solid nodule) were randomly placed inside a thoracic phantom. Scans were performed with tube current-time product to 10, 20, 30 and 50 mAs. Images were reconstructed with IR and filtered back projection (FBP). We compared volume estimates to a reference standard and calculated the absolute percentage error (APE). The APE of all nodules was significantly lower when IR was used than with FBP (7.5 ± 4.7% compared with 9.0 ±6.9%; p volumetry in low-dose CT by application of IR showed reliable accuracy in a phantom study. Lung nodule volumetry can be reliably applicable to all lung nodules including small, ground-glass nodules even in ultra-low-dose CT with application of IR. IR significantly improved the accuracy of lung nodule volumetry compared with FBP particularly for ground-glass (-630 HU) nodules. Volumetry in low-dose CT can be utilized in patient with lung nodule work-up, and IR has benefit for small, ground-glass lung nodules in low-dose CT.

Local pulmonary structure classification for computer-aided nodule detection

Science.gov (United States)

Bahlmann, Claus; Li, Xianlin; Okada, Kazunori

2006-03-01

We propose a new method of classifying the local structure types, such as nodules, vessels, and junctions, in thoracic CT scans. This classification is important in the context of computer aided detection (CAD) of lung nodules. The proposed method can be used as a post-process component of any lung CAD system. In such a scenario, the classification results provide an effective means of removing false positives caused by vessels and junctions thus improving overall performance. As main advantage, the proposed solution transforms the complex problem of classifying various 3D topological structures into much simpler 2D data clustering problem, to which more generic and flexible solutions are available in literature, and which is better suited for visualization. Given a nodule candidate, first, our solution robustly fits an anisotropic Gaussian to the data. The resulting Gaussian center and spread parameters are used to affine-normalize the data domain so as to warp the fitted anisotropic ellipsoid into a fixed-size isotropic sphere. We propose an automatic method to extract a 3D spherical manifold, containing the appropriate bounding surface of the target structure. Scale selection is performed by a data driven entropy minimization approach. The manifold is analyzed for high intensity clusters, corresponding to protruding structures. Techniques involve EMclustering with automatic mode number estimation, directional statistics, and hierarchical clustering with a modified Bhattacharyya distance. The estimated number of high intensity clusters explicitly determines the type of pulmonary structures: nodule (0), attached nodule (1), vessel (2), junction (>3). We show accurate classification results for selected examples in thoracic CT scans. This local procedure is more flexible and efficient than current state of the art and will help to improve the accuracy of general lung CAD systems.

Digital tomosynthesis for evaluating metastatic lung nodules: Nodule visibility, learning curves, and reading times

International Nuclear Information System (INIS)

Lee, Kyung Hee; Goo, Jin Mo; Lee, Sang Min; Park, Chang Min; Bahn, Young Eun; Kim, Hyung Jin; Song, Yong Sub; Hwang, Eui Jin

2015-01-01

To evaluate nodule visibility, learning curves, and reading times for digital tomosynthesis (DT). We included 80 patients who underwent computed tomography (CT) and DT before pulmonary metastasectomy. One experienced chest radiologist annotated all visible nodules on thin-section CT scans using computer-aided detection software. Two radiologists used CT as the reference standard and retrospectively graded the visibility of nodules on DT. Nodule detection performance was evaluated in four sessions of 20 cases each by six readers. After each session, readers were unblinded to the DT images by revealing the true-positive markings and were instructed to self-analyze their own misreads. Receiver-operating-characteristic curves were determined. Among 414 nodules on CT, 53.3% (221/414) were visible on DT. The main reason for not seeing a nodule on DT was small size (93.3%, < or = 5 mm). DT revealed a substantial number of malignant nodules (84.1%, 143/170). The proportion of malignant nodules among visible nodules on DT was significantly higher (64.7%, 143/221) than that on CT (41.1%, 170/414) (p < 0.001). Area under the curve (AUC) values at the initial session were > 0.8, and the average detection rate for malignant nodules was 85% (210/246). The inter-session analysis of the AUC showed no significant differences among the readers, and the detection rate for malignant nodules did not differ across sessions. A slight improvement in reading times was observed. Most malignant nodules > 5 mm were visible on DT. As nodule detection performance was high from the initial session, DT may be readily applicable for radiology residents and board-certified radiologists.

Digital tomosynthesis for evaluating metastatic lung nodules: Nodule visibility, learning curves, and reading times

Energy Technology Data Exchange (ETDEWEB)

Lee, Kyung Hee; Goo, Jin Mo; Lee, Sang Min; Park, Chang Min; Bahn, Young Eun; Kim, Hyung Jin; Song, Yong Sub; Hwang, Eui Jin [Dept. of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul (Korea, Republic of)

2015-04-15

To evaluate nodule visibility, learning curves, and reading times for digital tomosynthesis (DT). We included 80 patients who underwent computed tomography (CT) and DT before pulmonary metastasectomy. One experienced chest radiologist annotated all visible nodules on thin-section CT scans using computer-aided detection software. Two radiologists used CT as the reference standard and retrospectively graded the visibility of nodules on DT. Nodule detection performance was evaluated in four sessions of 20 cases each by six readers. After each session, readers were unblinded to the DT images by revealing the true-positive markings and were instructed to self-analyze their own misreads. Receiver-operating-characteristic curves were determined. Among 414 nodules on CT, 53.3% (221/414) were visible on DT. The main reason for not seeing a nodule on DT was small size (93.3%, < or = 5 mm). DT revealed a substantial number of malignant nodules (84.1%, 143/170). The proportion of malignant nodules among visible nodules on DT was significantly higher (64.7%, 143/221) than that on CT (41.1%, 170/414) (p < 0.001). Area under the curve (AUC) values at the initial session were > 0.8, and the average detection rate for malignant nodules was 85% (210/246). The inter-session analysis of the AUC showed no significant differences among the readers, and the detection rate for malignant nodules did not differ across sessions. A slight improvement in reading times was observed. Most malignant nodules > 5 mm were visible on DT. As nodule detection performance was high from the initial session, DT may be readily applicable for radiology residents and board-certified radiologists.

Malignancy risk estimation of screen-detected nodules at baseline CT: comparison of the PanCan model, Lung-RADS and NCCN guidelines

Energy Technology Data Exchange (ETDEWEB)

Riel, Sarah J. van; Ciompi, Francesco; Jacobs, Colin; Scholten, Ernst T.; Prokop, Mathias; Ginneken, Bram van [Radboud University Nijmegen Medical Center, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands); Winkler Wille, Mathilde M.; Naqibullah, Matiullah [University of Copenhagen, Department of Pulmonology Gentofte Hospital, Hellerup (Denmark); Lam, Stephen [British Columbia Cancer Agency, Department of Integrative Oncology, Vancouver, British Columbia (Canada); Schaefer-Prokop, Cornelia [Radboud University Nijmegen Medical Center, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands); Meander Medical Center, Department of Radiology, Amersfoort (Netherlands)

2017-10-15

To compare the PanCan model, Lung-RADS and the 1.2016 National Comprehensive Cancer Network (NCCN) guidelines for discriminating malignant from benign pulmonary nodules on baseline screening CT scans and the impact diameter measurement methods have on performances. From the Danish Lung Cancer Screening Trial database, 64 CTs with malignant nodules and 549 baseline CTs with benign nodules were included. Performance of the systems was evaluated applying the system's original diameter definitions: D{sup longest-C} (PanCan), D{sup meanAxial} (NCCN), both obtained from axial sections, and D{sup mean3D} (Lung-RADS). Subsequently all diameter definitions were applied uniformly to all systems. Areas under the ROC curves (AUC) were used to evaluate risk discrimination. PanCan performed superiorly to Lung-RADS and NCCN (AUC 0.874 vs. 0.813, p = 0.003; 0.874 vs. 0.836, p = 0.010), using the original diameter specifications. When uniformly applying D{sup longest-C}, D{sup mean3D} and D{sup meanAxial}, PanCan remained superior to Lung-RADS (p < 0.001 - p = 0.001) and NCCN (p < 0.001 - p = 0.016). Diameter definition significantly influenced NCCN's performance with D{sup longest-C} being the worst (D{sup longest-C} vs. D{sup mean3D}, p = 0.005; D{sup longest-C} vs. D{sup meanAxial}, p = 0.016). Without follow-up information, the PanCan model performs significantly superiorly to Lung-RADS and the 1.2016 NCCN guidelines for discriminating benign from malignant nodules. The NCCN guidelines are most sensitive to nodule size definition. (orig.)

SPECT/CT of lung nodules using 111In-DOTA-c(RGDfK) in a mouse lung carcinogenesis model.

Science.gov (United States)

Hayakawa, Takuya; Mutoh, Michihiro; Imai, Toshio; Tsuta, Koji; Yanaka, Akinori; Fujii, Hirofumi; Yoshimoto, Mitsuyoshi

2013-08-01

Lung cancer is one of the leading causes of cancer-related deaths worldwide, including Japan. Although computed tomography (CT) can detect small lung lesions such as those appearing as ground glass opacity, it cannot differentiate between malignant and non-malignant lesions. Previously, we have shown that single photon emission computed tomography (SPECT) imaging using (111)In-1,4,7,10-tetraazacyclododecane-N,N',N'',N'''-tetraacetic acid-cyclo-(Arg-Gly-Asp-D-Phe-Lys) (DOTA-c(RGDfK)), an imaging probe of αvβ3 integrin, is useful for the early detection of pancreatic cancer in a hamster pancreatic carcinogenesis model. In this study, we aimed to assess the usefulness of SPECT/CT with (111)In-DOTA-c(RGDfK) for the evaluation of the malignancy of lung cancer. Lung tumors were induced by a single intraperitoneal injection (250 mg/kg) of urethane in male A/J mice. Twenty-six weeks after the urethane treatment, SPECT was performed an hour after injection of (111)In-DOTA-c(RGDfK). Following this, the radioactivity ratios of tumor to normal lung tissue were measured by autoradiography (ARG) in the excised lung samples. We also examined the expression of αvβ3 integrin in mouse and human lung samples. Urethane treatment induced 5 hyperplasias, 41 adenomas and 12 adenocarcinomas in the lungs of 8 A/J mice. SPECT with (111)In-DOTA-c(RGDfK) could clearly visualize lung nodules, though we failed to detect small lung nodules like adenoma and hyperplasias (adenocarcinoma: 66.7%, adenoma: 33.6%, hyperplasia: 0.0%). ARG analysis revealed significant uptake of (111)In-DOTA-c(RGDfK) in all the lesions. Moreover, tumor to normal lung tissue ratios increased along with the progression of carcinogenesis. Histopathological examination using human lung tissue samples revealed clear up-regulation of αvβ3 integrin in well-differentiated adenocarcinoma (Noguchi type B and C) rather than atypical adenomatous hyperplasia. Although there are some limitations in evaluating the malignancy of

Distress and patient-centered communication among veterans with incidental (not screen-detected) pulmonary nodules. A cohort study.

Science.gov (United States)

Slatore, Christopher G; Golden, Sara E; Ganzini, Linda; Wiener, Renda Soylemez; Au, David H

2015-02-01

Incidental pulmonary nodule detection is postulated to cause distress, but the frequency and magnitude of that distress have not been reported. The quality of patient-clinician communication and the perceived risk of lung cancer may influence distress Objectives: To evaluate the association of communication processes with distress and the perceived risk of lung cancer using validated instruments. We conducted a prospective cohort study of patients with incidentally detected nodules who received care at one Department of Veterans Affairs Medical Center. We measured distress with the Impact of Event Scale and patient-centered communication with the Consultation Care Measure, both validated instruments. Risk of lung cancer was self-reported by participants. We used multivariable adjusted logistic regression to measure the association of communication quality with distress. Among 122 Veterans with incidental nodules, 23%, 12%, and 4% reported experiencing mild, moderate, and severe distress, respectively, at the time they were informed of the pulmonary nodule. Participant-reported risk of lung cancer was not associated with distress. In the adjusted model, high-quality communication was associated with decreased distress (odds ratio [OR] = 0.28, 95% confidence interval [CI] = 0.08-1.00, P = 0.05). Among participants who reported a risk of malignancy of 30% or less, high-quality communication was associated with decreased distress (OR = 0.15, 95% CI = 0.02-0.92, P = 0.04), but was not associated with distress for those who reported a risk greater than 30% (OR = 0.12 (95% CI = 0.00-3.97, P = 0.24), although the P value for interaction was not significant. Veterans with incidental pulmonary nodules frequently reported inadequate information exchange regarding their nodule. Many patients experience distress after they are informed that they have a pulmonary nodule, and high-quality patient-clinician communication is associated with

Clinical application of low-dose CT combined with computer-aided detection in lung cancer screening

International Nuclear Information System (INIS)

Xu Zushan; Hou Hongjun; Xu Yan; Ma Daqing

2010-01-01

Objective: To investigate the clinical value of chest low-dose CT (LDCT) combined with computer-aided detection (CAD) system for lung cancer screening in high risk population. Methods: Two hundred and nineteen healthy candidates underwent 64-slice LDCT scan. All images were reviewed in consensus by two radiologists with 15 years of thoracic CT diagnosis experience. Then the image data were analyzed with CAD alone. Finally images were reviewed by two radiologists with 5 years of CT diagnosis experience with and without CT Viewer software. The sensitivity, false positive rate of CAD for pulmonary nodule detection were calculated. SPSS 11.5 software and Chi-square test were used for the statistics. Results: Of 219 candidates ,104(47.5% ) were detected with lung nodules. There were 366 true nodules confirmed by the senior radiologists. The CAD system detected 271 (74.0%) true nodules and 424 false-positive nodules. The false-positive rate was 1.94/per case. The two junior radiologists indentifid 292 (79.8%), 286(78.1%) nodules without CAD and 336 (91.8%), 333 (91.0%) nodules with CAD respectively. There were significant differences for radiologists in indentifying nodules with or without CAD system (P<0.01). Conclusions: CAD is more sensitive than radiologists for indentifying the nodules in the central area or in the hilar region of the lung. While radiologists are more sensitive for the peripheral and sub-pleural nodules,or ground glass opacity nodules, or nodules smaller than 4 mm. CAD can not be used alone. The detection rate can be improved with the combination of radiologist and CAD in LDCT screen. (authors)

Lung nodule volumetry: segmentation algorithms within the same software package cannot be used interchangeably

DEFF Research Database (Denmark)

Ashraf, Haseem; de Hoop, B; Shaker, S B

2010-01-01

We examined the reproducibility of lung nodule volumetry software that offers three different volumetry algorithms.......We examined the reproducibility of lung nodule volumetry software that offers three different volumetry algorithms....

Novel high-resolution computed tomography-based radiomic classifier for screen-identified pulmonary nodules in the National Lung Screening Trial.

Science.gov (United States)

Peikert, Tobias; Duan, Fenghai; Rajagopalan, Srinivasan; Karwoski, Ronald A; Clay, Ryan; Robb, Richard A; Qin, Ziling; Sicks, JoRean; Bartholmai, Brian J; Maldonado, Fabien

2018-01-01

Optimization of the clinical management of screen-detected lung nodules is needed to avoid unnecessary diagnostic interventions. Herein we demonstrate the potential value of a novel radiomics-based approach for the classification of screen-detected indeterminate nodules. Independent quantitative variables assessing various radiologic nodule features such as sphericity, flatness, elongation, spiculation, lobulation and curvature were developed from the NLST dataset using 726 indeterminate nodules (all ≥ 7 mm, benign, n = 318 and malignant, n = 408). Multivariate analysis was performed using least absolute shrinkage and selection operator (LASSO) method for variable selection and regularization in order to enhance the prediction accuracy and interpretability of the multivariate model. The bootstrapping method was then applied for the internal validation and the optimism-corrected AUC was reported for the final model. Eight of the originally considered 57 quantitative radiologic features were selected by LASSO multivariate modeling. These 8 features include variables capturing Location: vertical location (Offset carina centroid z), Size: volume estimate (Minimum enclosing brick), Shape: flatness, Density: texture analysis (Score Indicative of Lesion/Lung Aggression/Abnormality (SILA) texture), and surface characteristics: surface complexity (Maximum shape index and Average shape index), and estimates of surface curvature (Average positive mean curvature and Minimum mean curvature), all with Pscreen-detected nodule characterization appears extremely promising however independent external validation is needed.

Optimization of a tomosynthesis system for the detection of lung nodules

International Nuclear Information System (INIS)

Pineda, Angel R.; Yoon, Sungwon; Paik, David S.; Fahrig, Rebecca

2006-01-01

Mathematical observers that track human performance can be used to reduce the number of human observer studies needed to optimize imaging systems. The performance of human observers for the detection of a 3.6 mm lung nodule in anatomical backgrounds was measured as a function of varying tomosynthetic angle and compared with mathematical observers. The human observer results showed a dramatic increase in the percent of correct responses, from 80% in the projection images to 96% in the projection images with a tomosynthetic angle of just 3 degrees. This result suggests the potential usefulness of the scanned beam digital x-ray system for this application. Given the small number of images (40) used per tomosynthetic angle and the highly nonstationary statistical nature of the backgrounds, the nonprewhitening eye observer achieved a higher performance than the channelized Hotelling observer using a Laguerre-Gauss basis. The channelized Hotelling observer with internal noise and the eye filter matched to the projection data were shown to track human performance as the tomosynthetic angle changed. The validation of these mathematical observers extends their applicability to the optimization of tomosynthesis systems

Volumetry of Artificial Pulmonary Nodules in Ex Vivo Porcine Lungs: Comparison of Semi-automated Volumetry and Radiologists' Performance

International Nuclear Information System (INIS)

Jeong, Ju Hyeon; Kim, Jin Hwan; Kim, Song Soo; Jeon, Ho Sang; Lee, Hyun Ju; Park, Noh Hyuck; Cho, Gyu Seong

2010-01-01

With the advent of MSCT, the detection rate of small pulmonary nodules is markedly greater. However, there is no definite diagnostic clue to differentiate between malignant and benign nodules, except for the interval growth in small nodule less than 1 cm in diameter. We evaluated the accuracy of computer aided volumetry (CAV) and compared it with 4 radiologists' measurement. Fifteen artificial nodules that were embedded in the ex vivo porcine lung were scanned by MSCT. The diameters and volumes of nodules were independently measured three times, at 5-day intervals, and by four radiologists as well as by CAV. We evaluated the accuracy of the measurements on the basis of the true diameter and volume of the nodules. Using a paired t-test and a Bland-Altman plot, we evaluated whether there was a statistically significant difference between the radiologists' measurements and the CAV. The accuracy of the manual measurements by radiologists revealed a statistically significant difference from the true diameter and volume of the artificial nodules (p 0.01) The results of this study suggest that CAV is an accurate and useful tool to evaluate the volume of pulmonary nodules and can eventually be used to differentiate malignant and benign nodules as well as evaluate the therapeutic response of lung cancer

Detectability of pulmonary nodules with electronic collimation and conventional antiscatter grid

International Nuclear Information System (INIS)

Plenkovich, D.; Plavsic, B.; Robinson, A.E.; Lichtenstein, R.L.

1989-01-01

Electronic collimation is a method for rejection of scattered radiation and veiling glare in digital radiography. Digital images of a frozen, unembalmed, human chest phantom with simulated pulmonary nodules were obtained with use of the electronic collimation technique and a conventional 10:1 antiscatter grid. Observers were asked to locate multiple nodules and to record one of three levels of confidence. For each criterion, the total number of correct responses was divided by the total number of nodules to obtain the ordinate of a point. The total number of false-positive answers generated was divided by the number of images to obtain the abscissa of the point. The analysis was repeated for each scatter rejection method and for either the lungs or the mediastinum. The electronic collimation technique has improved the detectability of nodules projected over the mediastinum

Malignancy estimation of Lung-RADS criteria for subsolid nodules on CT. Accuracy of low and high risk spectrum when using NLST nodules

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Chung, Kaman; Jacobs, Colin; Scholten, Ernst T.; Dekker, Irma; Prokop, Mathias; Ginneken, Bram van [Radboud University Medical Centre, Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands); Mets, Onno M. [University Medical Center Utrecht, Department of Radiology, Utrecht (Netherlands); Schaefer-Prokop, Cornelia M. [Radboud University Medical Centre, Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands); Meander Medical Center, Department of Radiology, Amersfoort (Netherlands)

2017-11-15

Lung-RADS proposes malignancy probabilities for categories 2 (<1%) and 4B (>15%). The purpose of this study was to quantify and compare malignancy rates for Lung-RADS 2 and 4B subsolid nodules (SSNs) on a nodule base. We identified all baseline SSNs eligible for Lung-RADS 2 and 4B in the National Lung Screening Trial (NLST) database. Solid cores and nodule locations were annotated using in-house software. Malignant SSNs were identified by an experienced radiologist using NLST information. Malignancy rates and percentages of persistence were calculated. Of the Lung-RADS 2SSNs, 94.3% (1790/1897) could be located on chest CTs. Likewise, 95.1% (331/348) of part-solid nodules ≥6 mm in diameter could be located. Of these, 120 had a solid core ≥8 mm, corresponding to category 4B. Category 2 SSNs showed a malignancy rate of 2.5%, exceeding slightly the proposed rate of <1%. Category 4B SSNs showed a malignancy rate of 23.9%. In both categories one third of benign lesions were transient. Malignancy probabilities for Lung-RADS 2 and 4B generally match malignancy rates in SSNs. An option to include also category 2 SSNs for upgrade to 4X designed for suspicious nodules might be useful in the future. Integration of short-term follow-up to confirm persistence would prevent unnecessary invasive work-up in 4B SSNs. (orig.)

Clinical, pathological, and radiological characteristics of solitary ground-glass opacity lung nodules on high-resolution computed tomography

Directory of Open Access Journals (Sweden)

Qiu ZX

2016-09-01

Full Text Available Zhi-Xin Qiu,1 Yue Cheng,1 Dan Liu,1 Wei-Ya Wang,2 Xia Wu,2 Wei-Lu Wu,2 Wei-Min Li1,2 1Department of Respiratory Medicine, 2Department of Pathology, West China Hospital, Sichuan University, Chengdu, People’s Republic of China Background: Lung nodules are being detected at an increasing rate year by year with high-resolution computed tomography (HRCT being widely used. Ground-glass opacity nodule is one of the special types of pulmonary nodules that is confirmed to be closely associated with early stage of lung cancer. Very little is known about solitary ground-glass opacity nodules (SGGNs. In this study, we analyzed the clinical, pathological, and radiological characteristics of SGGNs on HRCT.Methods: A total of 95 resected SGGNs were evaluated with HRCT scan. The clinical, pathological, and radiological characteristics of these cases were analyzed.Results: Eighty-one adenocarcinoma and 14 benign nodules were observed. The nodules included 12 (15% adenocarcinoma in situ (AIS, 14 (17% minimally invasive adenocarcinoma (MIA, and 55 (68% invasive adenocarcinoma (IA. No patients with recurrence till date have been identified. The positive expression rates of anaplastic lymphoma kinase and ROS-1 (proto-oncogene tyrosine-protein kinase ROS were only 2.5% and 8.6%, respectively. The specificity and accuracy of HRCT of invasive lung adenocarcinoma were 85.2% and 87.4%. The standard uptake values of only two patients determined by 18F-FDG positron emission tomography/computed tomography (PET/CT were above 2.5. The size, density, shape, and pleural tag of nodules were significant factors that differentiated IA from AIS and MIA. Moreover, the size, shape, margin, pleural tag, vascular cluster, bubble-like sign, and air bronchogram of nodules were significant determinants for mixed ground-glass opacity nodules (all P<0.05.Conclusion: We analyzed the clinical, pathological, and radiological characteristics of SGGNs on HRCT and found that the size, density

Pulmonary nodules and masses in lung transplant recipients: clinical and CT findings

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Morla, Olivier; Liberge, Renan; Arrigoni, Pierre Paul; Frampas, Eric [Service de Radiologie Centrale, C.H.U. Hotel Dieu, Nantes (France)

2014-09-15

The purpose of this study was to review the clinical and CT findings of pulmonary nodules and masses in lung transplant recipients and to determine distinguishing features among the various aetiologies. This retrospective study included 106 lung transplant recipients who had a chest CT performed over a 7-year period in a single institution. Twenty-four cases of pulmonary nodules and masses were observed on CT. Among the single lesions, three (50 %) were due to infections, one (17 %) to organizing pneumonia, and two (33 %) remained of undetermined origin. Among the multiple lesions, 14 (78 %) were due to infection, three to post-transplant lymphoproliferative disorder (17 %), and one to bronchogenic carcinoma (5 %). The two main microorganisms were P. aeruginosa and Aspergillus spp. Among 12 solid nodules > 1 cm, four (33 %) were due to malignancy: three post-transplant lymphoproliferative disorders (25 %), and one bronchogenic carcinoma (8 %). Among five cavitary nodules four (80 %) were due to aspergillosis. Infection is the most frequent aetiology of pulmonary nodules and masses in lung transplant recipients, but other causes such as post-transplant lymphoproliferative disorder, bronchogenic carcinoma, or organizing pneumonia should be considered. (orig.)

Detection of pulmonary nodules

International Nuclear Information System (INIS)

Vanzulli, A.; Zanello, A.; DelMaschio, M.; Paesano, P.; Panizza, P.; DelMaschio, A.

1989-01-01

The authors have prospectively studied 203 pulmonary nodules in 91 patients, selected by CT (gold standard), with both subtraction digital radiography (SDR) and conventional plain film. Subtracted images were obtained by using copper filter inserted between two photostimulable imaging plates. Five radiologists randomly analyzed all conventional and subtracted images. The authors calculated sensitivity, specificity, and positive and negative predictive values for both conventional radiography and SDR. Receiver operating characteristics (ROC) curves were calculated by plotting the number of nodules detected with different degrees of confidence. SDR detected 12% more nodules than conventional radiography. ROC curves demonstrated that the level of confidence was better for SDR (P <.05)

Eye-tracking of nodule detection in lung CT volumetric data

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Diaz, Ivan; Verdun, Francis R.; Bochud, François O., E-mail: francois.bochud@chuv.ch [Institute of Radiation Physics, Lausanne University Hospital, Lausanne 1004 (Switzerland); Schmidt, Sabine [Department of Radiology, Lausanne University Hospital, Lausanne 1004 (Switzerland)

2015-06-15

Purpose: Signal detection on 3D medical images depends on many factors, such as foveal and peripheral vision, the type of signal, and background complexity, and the speed at which the frames are displayed. In this paper, the authors focus on the speed with which radiologists and naïve observers search through medical images. Prior to the study, the authors asked the radiologists to estimate the speed at which they scrolled through CT sets. They gave a subjective estimate of 5 frames per second (fps). The aim of this paper is to measure and analyze the speed with which humans scroll through image stacks, showing a method to visually display the behavior of observers as the search is made as well as measuring the accuracy of the decisions. This information will be useful in the development of model observers, mathematical algorithms that can be used to evaluate diagnostic imaging systems. Methods: The authors performed a series of 3D 4-alternative forced-choice lung nodule detection tasks on volumetric stacks of chest CT images iteratively reconstructed in lung algorithm. The strategy used by three radiologists and three naïve observers was assessed using an eye-tracker in order to establish where their gaze was fixed during the experiment and to verify that when a decision was made, a correct answer was not due only to chance. In a first set of experiments, the observers were restricted to read the images at three fixed speeds of image scrolling and were allowed to see each alternative once. In the second set of experiments, the subjects were allowed to scroll through the image stacks at will with no time or gaze limits. In both static-speed and free-scrolling conditions, the four image stacks were displayed simultaneously. All trials were shown at two different image contrasts. Results: The authors were able to determine a histogram of scrolling speeds in frames per second. The scrolling speed of the naïve observers and the radiologists at the moment the signal

Surveillance of the remaining nodules after resection of the dominant lung adenocarcinoma is an appropriate follow-up strategy

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Massimo eCastiglioni

2015-01-01

Full Text Available IntroductionAdenocarcinomas, commonly present as a dominant lesion (DL with additional nodules in the ipsilateral or contralateral lung. We sought to determine the fate and management of the secondary nodules and to assess the risk of these nodules using the Lung CT Screening Reporting and Data System (Lung-RADS criteria and the National Comprehensive Cancer Network (NCCN guidelines to determine if surveillance is an appropriate strategy.MethodsWe retrospectively evaluated patients with lepidic growth pattern adenocarcinoma and secondary nodules from 2000 to 2013. Risk assessment of the additional lesions was completed with a simplified model of Lung-RADS and NCCN-Guidelines. ResultsEighty-seven patients underwent resection of 87 DLs (Group 1 concurrently with 60 additional pulmonary nodules (Group 2 while 157 non-DLs were radiologically surveyed over a median follow-up time of 3.2 years (Group 3. Malignancy was found in 29/60 (48% nodules in Group 2. Whereas, only 9/157 (6% of the lesions in Group 3 enlarged, 4 of which (2.5% of total were found to be malignant, and then treated, while the remaining nodules continued surveillance. After applying the Lung-RADS and NCCN simplified models, nodules in Group 2 were at higher risk for lung cancer than those in Group 3. ConclusionsIn patients with lepidic growth pattern adenocarcinoma associated with multiple secondary nodules, surveillance of the remaining nodules, after resection of the DL, is a reasonable strategy since these nodules exhibited a slow rate of growth and minimal malignancy. In contrast, nodules resected from the ipsilateral lung at the time of the DL, harbor malignancy in 48%. Risk assessment models may provide a useful and standardized tool for clinical assessment of pulmonary nodules.

Clinical significance of pulmonary nodules detected on abdominal CT in pediatric patients

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Breen, Micheal; Lee, Edward Y.; Zurakowski, David

2015-01-01

The clinical significance of a pulmonary nodule that is detected incidentally on CT studies in children is unknown. In addition, there is limited information regarding the management of incidentally detected pulmonary nodules discovered on abdominal CT studies in children. The purpose of this study was to investigate the clinical significance of incidental pulmonary nodules detected on abdominal CT studies in children. This was a retrospective study performed following institutional review board approval. Abdominal CT reports in patients younger than 18 years of age from July 2004 to June 2011 were reviewed for the terms ''nodule,'' ''nodular'' or ''mass'' in reference to the lung bases. The study population included those pediatric patients in whom pulmonary nodules were initially detected on abdominal CT studies. The largest pulmonary nodules detected on CT studies were evaluated for their features (size, shape, margin, attenuation, location, and presence of calcification and cavitation). Follow-up CT studies and clinical records were reviewed for demographic information, history of underlying malignancies and the clinical outcome of the incidental pulmonary nodules. Comparison of malignant versus benign pulmonary nodules was performed with respect to the size of the nodule, imaging features on CT, and patient history of malignancy using the Student's t-test and Fisher exact test. Youden J-index in receiver operating characteristic (ROC) analysis was used to determine the optimal cut-off size for suggesting a high risk of malignancy of incidentally detected pulmonary nodules. Pulmonary nodules meeting inclusion criteria were detected in 62 (1.2%) of 5,234 patients. The mean age of patients with nodules was 11.2 years (range: 5 months-18 years). Thirty-one patients (50%) had follow-up CT studies and two of these patients (6%) were subsequently found to have malignant pulmonary nodules. Both of these

Clinical significance of pulmonary nodules detected on abdominal CT in pediatric patients

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Breen, Micheal; Lee, Edward Y. [Boston Children' s Hospital and Harvard Medical School, Department of Radiology, Boston, MA (United States); Zurakowski, David [Boston Children' s Hospital and Harvard Medical School, Departments of Anesthesiology and Surgery, Boston, MA (United States)

2015-11-15

The clinical significance of a pulmonary nodule that is detected incidentally on CT studies in children is unknown. In addition, there is limited information regarding the management of incidentally detected pulmonary nodules discovered on abdominal CT studies in children. The purpose of this study was to investigate the clinical significance of incidental pulmonary nodules detected on abdominal CT studies in children. This was a retrospective study performed following institutional review board approval. Abdominal CT reports in patients younger than 18 years of age from July 2004 to June 2011 were reviewed for the terms ''nodule,'' ''nodular'' or ''mass'' in reference to the lung bases. The study population included those pediatric patients in whom pulmonary nodules were initially detected on abdominal CT studies. The largest pulmonary nodules detected on CT studies were evaluated for their features (size, shape, margin, attenuation, location, and presence of calcification and cavitation). Follow-up CT studies and clinical records were reviewed for demographic information, history of underlying malignancies and the clinical outcome of the incidental pulmonary nodules. Comparison of malignant versus benign pulmonary nodules was performed with respect to the size of the nodule, imaging features on CT, and patient history of malignancy using the Student's t-test and Fisher exact test. Youden J-index in receiver operating characteristic (ROC) analysis was used to determine the optimal cut-off size for suggesting a high risk of malignancy of incidentally detected pulmonary nodules. Pulmonary nodules meeting inclusion criteria were detected in 62 (1.2%) of 5,234 patients. The mean age of patients with nodules was 11.2 years (range: 5 months-18 years). Thirty-one patients (50%) had follow-up CT studies and two of these patients (6%) were subsequently found to have malignant pulmonary nodules. Both of these

Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation.

Science.gov (United States)

Wang, Shuo; Zhou, Mu; Liu, Zaiyi; Liu, Zhenyu; Gu, Dongsheng; Zang, Yali; Dong, Di; Gevaert, Olivier; Tian, Jie

2017-08-01

Accurate lung nodule segmentation from computed tomography (CT) images is of great importance for image-driven lung cancer analysis. However, the heterogeneity of lung nodules and the presence of similar visual characteristics between nodules and their surroundings make it difficult for robust nodule segmentation. In this study, we propose a data-driven model, termed the Central Focused Convolutional Neural Networks (CF-CNN), to segment lung nodules from heterogeneous CT images. Our approach combines two key insights: 1) the proposed model captures a diverse set of nodule-sensitive features from both 3-D and 2-D CT images simultaneously; 2) when classifying an image voxel, the effects of its neighbor voxels can vary according to their spatial locations. We describe this phenomenon by proposing a novel central pooling layer retaining much information on voxel patch center, followed by a multi-scale patch learning strategy. Moreover, we design a weighted sampling to facilitate the model training, where training samples are selected according to their degree of segmentation difficulty. The proposed method has been extensively evaluated on the public LIDC dataset including 893 nodules and an independent dataset with 74 nodules from Guangdong General Hospital (GDGH). We showed that CF-CNN achieved superior segmentation performance with average dice scores of 82.15% and 80.02% for the two datasets respectively. Moreover, we compared our results with the inter-radiologists consistency on LIDC dataset, showing a difference in average dice score of only 1.98%. Copyright © 2017. Published by Elsevier B.V.

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans

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NONE

2011-02-15

Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (''nodule{>=}3 mm,''''nodule<3 mm,'' and ''non-nodule{>=}3 mm''). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results: The Database contains 7371 lesions marked ''nodule'' by at least one radiologist. 2669 of these lesions were marked ''nodule

Multilevel Contextual 3-D CNNs for False Positive Reduction in Pulmonary Nodule Detection.

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Dou, Qi; Chen, Hao; Yu, Lequan; Qin, Jing; Heng, Pheng-Ann

2017-07-01

False positive reduction is one of the most crucial components in an automated pulmonary nodule detection system, which plays an important role in lung cancer diagnosis and early treatment. The objective of this paper is to effectively address the challenges in this task and therefore to accurately discriminate the true nodules from a large number of candidates. We propose a novel method employing three-dimensional (3-D) convolutional neural networks (CNNs) for false positive reduction in automated pulmonary nodule detection from volumetric computed tomography (CT) scans. Compared with its 2-D counterparts, the 3-D CNNs can encode richer spatial information and extract more representative features via their hierarchical architecture trained with 3-D samples. More importantly, we further propose a simple yet effective strategy to encode multilevel contextual information to meet the challenges coming with the large variations and hard mimics of pulmonary nodules. The proposed framework has been extensively validated in the LUNA16 challenge held in conjunction with ISBI 2016, where we achieved the highest competition performance metric (CPM) score in the false positive reduction track. Experimental results demonstrated the importance and effectiveness of integrating multilevel contextual information into 3-D CNN framework for automated pulmonary nodule detection in volumetric CT data. While our method is tailored for pulmonary nodule detection, the proposed framework is general and can be easily extended to many other 3-D object detection tasks from volumetric medical images, where the targeting objects have large variations and are accompanied by a number of hard mimics.

Incidental perifissural nodules on routine chest computed tomography. Lung cancer or not?

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Mets, Onno M.; Veldhuis, Wouter B.; Jong, Pim A. de [University Medical Center Utrecht, Department of Radiology, Utrecht (Netherlands); Chung, Kaman; Scholten, Ernst T.; Ginneken, Bram van [Radboud University Nijmegen Medical Centre, Diagnostic Image Analysis Group, Nijmegen (Netherlands); Prokop, M. [Radboud University Nijmegen Medical Centre, Department of Radiology, Nijmegen (Netherlands); Schaefer-Prokop, Cornelia M. [Radboud University Nijmegen Medical Centre, Diagnostic Image Analysis Group, Nijmegen (Netherlands); Meander Medical Center, Department of Radiology, Amersfoort (Netherlands)

2018-03-15

Perifissural nodules (PFNs) are a common finding on chest CT, and are thought to represent non-malignant lesions. However, data outside a lung cancer-screening setting are currently lacking. In a nested case-control design, out of a total cohort of 16,850 patients ≥ 40 years of age who underwent routine chest CT (2004-2012), 186 eligible subjects with incident lung cancer and 511 controls without were investigated. All non-calcified nodules ≥ 4 mm were semi-automatically annotated. Lung cancer location and subject characteristics were recorded. Cases (56 % male) had a median age of 64 years (IQR 59-70). Controls (60 % male) were slightly younger (p<0.01), median age of 61 years (IQR 51-70). A total of 262/1,278 (21 %) unique non-calcified nodules represented a PFN. None of these were traced to a lung malignancy over a median follow-up of around 4.5 years. PFNs were most often located in the lower lung zones (72 %, p<0.001). Median diameter was 4.6 mm (range: 4.0-8.1), volume 51 mm{sup 3} (range: 32-278). Some showed growth rates < 400 days. Our data show that incidental PFNs do not represent lung cancer in a routine care, heterogeneous population. This confirms prior screening-based results. (orig.)

Deep-learning derived features for lung nodule classification with limited datasets

Science.gov (United States)

Thammasorn, P.; Wu, W.; Pierce, L. A.; Pipavath, S. N.; Lampe, P. D.; Houghton, A. M.; Haynor, D. R.; Chaovalitwongse, W. A.; Kinahan, P. E.

2018-02-01

Only a few percent of indeterminate nodules found in lung CT images are cancer. However, enabling earlier diagnosis is important to avoid invasive procedures or long-time surveillance to those benign nodules. We are evaluating a classification framework using radiomics features derived with a machine learning approach from a small data set of indeterminate CT lung nodule images. We used a retrospective analysis of 194 cases with pulmonary nodules in the CT images with or without contrast enhancement from lung cancer screening clinics. The nodules were contoured by a radiologist and texture features of the lesion were calculated. In addition, sematic features describing shape were categorized. We also explored a Multiband network, a feature derivation path that uses a modified convolutional neural network (CNN) with a Triplet Network. This was trained to create discriminative feature representations useful for variable-sized nodule classification. The diagnostic accuracy was evaluated for multiple machine learning algorithms using texture, shape, and CNN features. In the CT contrast-enhanced group, the texture or semantic shape features yielded an overall diagnostic accuracy of 80%. Use of a standard deep learning network in the framework for feature derivation yielded features that substantially underperformed compared to texture and/or semantic features. However, the proposed Multiband approach of feature derivation produced results similar in diagnostic accuracy to the texture and semantic features. While the Multiband feature derivation approach did not outperform the texture and/or semantic features, its equivalent performance indicates promise for future improvements to increase diagnostic accuracy. Importantly, the Multiband approach adapts readily to different size lesions without interpolation, and performed well with relatively small amount of training data.

Computer-aided pulmonary nodule detection. Performance of two CAD systems at different CT dose levels

International Nuclear Information System (INIS)

Hein, Patrick Alexander; Rogalla, P.; Klessen, C.; Lembcke, A.; Romano, V.C.

2009-01-01

Purpose: To evaluate the impact of dose reduction on the performance of computer-aided lung nodule detection systems (CAD) of two manufacturers by comparing respective CAD results on ultra-low-dose computed tomography (ULD-CT) and standard dose CT (SD-CT). Materials and Methods: Multi-slice computed tomography (MSCT) data sets of 26 patients (13 male and 13 female, patients 31 - 74 years old) were retrospectively selected for CAD analysis. Indication for CT examination was staging of a known primary malignancy or suspected pulmonary malignancy. CT images were consecutively acquired at 5 mAs (ULD-CT) and 75 mAs (SD-CT) with 120kV tube voltage (1 mm slice thickness). The standard of reference was determined by three experienced readers in consensus. CAD reading algorithms (pre-commercial CAD system, Philips, Netherlands: CAD-1; LungCARE, Siemens, Germany: CAD-2) were applied to the CT data sets. Results: Consensus reading identified 253 nodules on SD-CT and ULD-CT. Nodules ranged in diameter between 2 and 41 mm (mean diameter 4.8 mm). Detection rates were recorded with 72% and 62% (CAD-1 vs. CAD-2) for SD-CT and with 73% and 56% for ULD-CT. Median also positive rates per patient were calculated with 6 and 5 (CAD-1 vs. CAD-2) for SD-CT and with 8 and 3 for ULD-CT. After separate statistical analysis of nodules with diameters of 5 mm and greater, the detection rates increased to 83% and 61% for SD-CT and to 89% and 67% for ULD-CT (CAD-1 vs. CAD-2). For both CAD systems there were no significant differences between the detection rates for standard and ultra-low-dose data sets (p>0.05). Conclusion: Dose reduction of the underlying CT scan did not significantly influence nodule detection performance of the tested CAD systems. (orig.)

Lung cancer detection with digital chest tomosynthesis: first round results from the SOS observational study.

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Bertolaccini, Luca; Viti, Andrea; Tavella, Chiara; Priotto, Roberto; Ghirardo, Donatella; Grosso, Maurizio; Terzi, Alberto

2015-04-01

Baseline results of the Studio OSservazionale (SOS), observational study, a single-arm observational study of digital chest tomosynthesis for lung cancer detection in an at-risk population demonstrated a detection rate of lung cancer comparable to that of studies that used low dose CT scan (LDCT). We present the results of the first round. Totally 1,703 out of 1,843 (92%) subjects who had a baseline digital chest tomosynthesis underwent a first round reevaluation after 1 year. At first round chest digital tomosynthesis, 13 (0.7%) subjects had an indeterminate nodule larger than 5 mm and underwent low-dose CT scan for nodule confirmation. PET/CT study was obtained in 10 (0.5%) subjects and 2 subjects had a low-dose CT follow up. Surgery, either video-assisted thoracoscopic or open surgery for indeterminate pulmonary nodules was performed in 10 (0.2%) subjects. A lung cancer was diagnosed and resected in five patients. The lung cancer detection rate at first round was 0.3% (5/1,703). The detection rate of lung cancer at first round for tomosynthesis is comparable to rates reported for CT. In addition, results of first round digital chest tomosynthesis confirm chest tomosynthesis as a possible first-line lung cancer-screening tool.

Application of CT-PSF-based computer-simulated lung nodules for evaluating the accuracy of computer-aided volumetry.

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Funaki, Ayumu; Ohkubo, Masaki; Wada, Shinichi; Murao, Kohei; Matsumoto, Toru; Niizuma, Shinji

2012-07-01

With the wide dissemination of computed tomography (CT) screening for lung cancer, measuring the nodule volume accurately with computer-aided volumetry software is increasingly important. Many studies for determining the accuracy of volumetry software have been performed using a phantom with artificial nodules. These phantom studies are limited, however, in their ability to reproduce the nodules both accurately and in the variety of sizes and densities required. Therefore, we propose a new approach of using computer-simulated nodules based on the point spread function measured in a CT system. The validity of the proposed method was confirmed by the excellent agreement obtained between computer-simulated nodules and phantom nodules regarding the volume measurements. A practical clinical evaluation of the accuracy of volumetry software was achieved by adding simulated nodules onto clinical lung images, including noise and artifacts. The tested volumetry software was revealed to be accurate within an error of 20 % for nodules >5 mm and with the difference between nodule density and background (lung) (CT value) being 400-600 HU. Such a detailed analysis can provide clinically useful information on the use of volumetry software in CT screening for lung cancer. We concluded that the proposed method is effective for evaluating the performance of computer-aided volumetry software.

Accuracy of lung nodule density on HRCT: analysis by PSF-based image simulation.

Science.gov (United States)

Ohno, Ken; Ohkubo, Masaki; Marasinghe, Janaka C; Murao, Kohei; Matsumoto, Toru; Wada, Shinichi

2012-11-08

A computed tomography (CT) image simulation technique based on the point spread function (PSF) was applied to analyze the accuracy of CT-based clinical evaluations of lung nodule density. The PSF of the CT system was measured and used to perform the lung nodule image simulation. Then, the simulated image was resampled at intervals equal to the pixel size and the slice interval found in clinical high-resolution CT (HRCT) images. On those images, the nodule density was measured by placing a region of interest (ROI) commonly used for routine clinical practice, and comparing the measured value with the true value (a known density of object function used in the image simulation). It was quantitatively determined that the measured nodule density depended on the nodule diameter and the image reconstruction parameters (kernel and slice thickness). In addition, the measured density fluctuated, depending on the offset between the nodule center and the image voxel center. This fluctuation was reduced by decreasing the slice interval (i.e., with the use of overlapping reconstruction), leading to a stable density evaluation. Our proposed method of PSF-based image simulation accompanied with resampling enables a quantitative analysis of the accuracy of CT-based evaluations of lung nodule density. These results could potentially reveal clinical misreadings in diagnosis, and lead to more accurate and precise density evaluations. They would also be of value for determining the optimum scan and reconstruction parameters, such as image reconstruction kernels and slice thicknesses/intervals.

Volumetry of Artificial Pulmonary Nodules in Ex Vivo Porcine Lungs: Comparison of Semi-automated Volumetry and Radiologists' Performance

Energy Technology Data Exchange (ETDEWEB)

Jeong, Ju Hyeon; Kim, Jin Hwan; Kim, Song Soo [Chungnam National University Hospital, Daejeon (Korea, Republic of); Jeon, Ho Sang [Pusan National University Yangsan Hospital, Yangsan (Korea, Republic of); Lee, Hyun Ju [Seoul National University Hospital, Seoul (Korea, Republic of); Park, Noh Hyuck [Kwandong University College of Medicine, Myungji Hospital, Goyang (Korea, Republic of); Cho, Gyu Seong [KAIST, Daejeon (Korea, Republic of)

2010-10-15

With the advent of MSCT, the detection rate of small pulmonary nodules is markedly greater. However, there is no definite diagnostic clue to differentiate between malignant and benign nodules, except for the interval growth in small nodule less than 1 cm in diameter. We evaluated the accuracy of computer aided volumetry (CAV) and compared it with 4 radiologists' measurement. Fifteen artificial nodules that were embedded in the ex vivo porcine lung were scanned by MSCT. The diameters and volumes of nodules were independently measured three times, at 5-day intervals, and by four radiologists as well as by CAV. We evaluated the accuracy of the measurements on the basis of the true diameter and volume of the nodules. Using a paired t-test and a Bland-Altman plot, we evaluated whether there was a statistically significant difference between the radiologists' measurements and the CAV. The accuracy of the manual measurements by radiologists revealed a statistically significant difference from the true diameter and volume of the artificial nodules (p<0.01). Conversely, the accuracy of CAV did not show a statistically significant difference with the true nodule diameter and volume (p>0.01) The results of this study suggest that CAV is an accurate and useful tool to evaluate the volume of pulmonary nodules and can eventually be used to differentiate malignant and benign nodules as well as evaluate the therapeutic response of lung cancer.

Assessing the use of digital radiography and a real-time interactive pulmonary nodule analysis system for large population lung cancer screening

International Nuclear Information System (INIS)

Xu Yan; Ma Daqing; He Wen

2012-01-01

Rationale and objectives: To assess the use of chest digital radiograph (DR) assisted with a real-time interactive pulmonary nodule analysis system in large population lung cancer screening. Materials and methods: 346 DR/CR patient studies with corresponding CT images were selected from 12,500 patients screened for lung cancer from year 2007 to 2009. Two expert chest radiologists established CT-confirmed Gold Standard of nodules on DR/CR images with consensus. These cases were read by eight other chest radiologists (participating radiologists) first without using a real-time interactive pulmonary nodule analysis system and then re-read using the system. Performances of participating radiologists and the computer system were analyzed. Results: The computer system achieved similar performance on DR and CR images, with a detection rate of 76% and an average FPs of 2.0 per image. Before and after using the computer-aided detection system, the nodule detection sensitivities of the participating radiologists were 62.3% and 77.3% respectively, and the A z values increased from 0.794 to 0.831. Statistical analysis demonstrated statically significant improvement for the participating radiologists after using the computer analysis system with a P-value 0.05. Conclusion: The computer system could help radiologists identify more lesions, especially small ones that are more likely to be overlooked on chest DR/CR images, and could help reduce inter-observer diagnostic variations, while its FPs were easy to recognize and dismiss. It is suggested that DR/CR assisted by the real-time interactive pulmonary nodule analysis system may be an effective means to screen large populations for lung cancer.

Correlation of emphysema score with perceived malignancy of pulmonary nodules: a multi-observer study using the LIDC-IDRI CT lung database

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Wiemker, Rafael; Bülow, Thomas; Blaffert, Thomas; Dharaiya, Ekta

2009-02-01

Presence of emphysema is recognized to be one of the single most significant risk factors in risk models for the prediction of lung cancer. Therefore, an automatically computed emphysema score would be a prime candidate as an additional numerical feature for computer aided diagnosis (CADx) for indeterminate pulmonary nodules. We have applied several histogram-based emphysema scores to 460 thoracic CT scans from the IDRI CT lung image database, and analyzed the emphysema scores in conjunction with 3000 nodule malignancy ratings of 1232 pulmonary nodules made by expert observers. Despite the emphysema being a known risk factor, we have not found any impact on the readers' malignancy rating of nodules found in a patient with higher emphysema score. We have also not found any correlation between the number of expert-detected nodules in a patient and his emphysema score, or the relative craniocaudal location of the nodules and their malignancy rating. The inter-observer agreement of the expert ratings was excellent on nodule diameter (as derived from manual delineations), good for calcification, and only modest for malignancy and shape descriptions such as spiculation, lobulation, margin, etc.

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans

International Nuclear Information System (INIS)

2011-01-01

Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (''nodule≥3 mm,''''nodule<3 mm,'' and ''non-nodule≥3 mm''). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results: The Database contains 7371 lesions marked ''nodule'' by at least one radiologist. 2669 of these lesions were marked ''nodule≥3 mm'' by at least one radiologist, of which 928 (34.7%) received such marks from all

Role of Computer Aided Diagnosis (CAD in the detection of pulmonary nodules on 64 row multi detector computed tomography

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K Prakashini

2016-01-01

Full Text Available Aims and Objectives: To determine the overall performance of an existing CAD algorithm with thin-section computed tomography (CT in the detection of pulmonary nodules and to evaluate detection sensitivity at a varying range of nodule density, size, and location. Materials and Methods: A cross-sectional prospective study was conducted on 20 patients with 322 suspected nodules who underwent diagnostic chest imaging using 64-row multi-detector CT. The examinations were evaluated on reconstructed images of 1.4 mm thickness and 0.7 mm interval. Detection of pulmonary nodules, initially by a radiologist of 2 years experience (RAD and later by CAD lung nodule software was assessed. Then, CAD nodule candidates were accepted or rejected accordingly. Detected nodules were classified based on their size, density, and location. The performance of the RAD and CAD system was compared with the gold standard that is true nodules confirmed by consensus of senior RAD and CAD together. The overall sensitivity and false-positive (FP rate of CAD software was calculated. Observations and Results: Of the 322 suspected nodules, 221 were classified as true nodules on the consensus of senior RAD and CAD together. Of the true nodules, the RAD detected 206 (93.2% and 202 (91.4% by the CAD. CAD and RAD together picked up more number of nodules than either CAD or RAD alone. Overall sensitivity for nodule detection with the CAD program was 91.4%, and FP detection per patient was 5.5%. The CAD showed comparatively higher sensitivity for nodules of size 4-10 mm (93.4% and nodules in hilar (100% and central (96.5% location when compared to RAD′s performance. Conclusion: CAD performance was high in detecting pulmonary nodules including the small size and low-density nodules. CAD even with relatively high FP rate, assists and improves RAD′s performance as a second reader, especially for nodules located in the central and hilar region and for small nodules by saving RADs time.

Role of Computer Aided Diagnosis (CAD) in the detection of pulmonary nodules on 64 row multi detector computed tomography.

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Prakashini, K; Babu, Satish; Rajgopal, K V; Kokila, K Raja

2016-01-01

To determine the overall performance of an existing CAD algorithm with thin-section computed tomography (CT) in the detection of pulmonary nodules and to evaluate detection sensitivity at a varying range of nodule density, size, and location. A cross-sectional prospective study was conducted on 20 patients with 322 suspected nodules who underwent diagnostic chest imaging using 64-row multi-detector CT. The examinations were evaluated on reconstructed images of 1.4 mm thickness and 0.7 mm interval. Detection of pulmonary nodules, initially by a radiologist of 2 years experience (RAD) and later by CAD lung nodule software was assessed. Then, CAD nodule candidates were accepted or rejected accordingly. Detected nodules were classified based on their size, density, and location. The performance of the RAD and CAD system was compared with the gold standard that is true nodules confirmed by consensus of senior RAD and CAD together. The overall sensitivity and false-positive (FP) rate of CAD software was calculated. Of the 322 suspected nodules, 221 were classified as true nodules on the consensus of senior RAD and CAD together. Of the true nodules, the RAD detected 206 (93.2%) and 202 (91.4%) by the CAD. CAD and RAD together picked up more number of nodules than either CAD or RAD alone. Overall sensitivity for nodule detection with the CAD program was 91.4%, and FP detection per patient was 5.5%. The CAD showed comparatively higher sensitivity for nodules of size 4-10 mm (93.4%) and nodules in hilar (100%) and central (96.5%) location when compared to RAD's performance. CAD performance was high in detecting pulmonary nodules including the small size and low-density nodules. CAD even with relatively high FP rate, assists and improves RAD's performance as a second reader, especially for nodules located in the central and hilar region and for small nodules by saving RADs time.

What to Do with All of These Lung Nodules?

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Dmitry Rozenberg

2014-01-01

Full Text Available Caplan syndrome is a rare entity that is specific to rheumatoid arthritis and presents with multiple, well-defined necrotic nodules in patients with occupational dust exposure. The present report describes a case of Caplan syndrome involving a 71-year-old man with a known diagnosis of seropositive rheumatoid arthritis who presented to the authors’ centre with a five-year history of multiple, bilateral cavitary lung nodules with mild dyspnea on exertion. He was an ex-smoker (30 pack-years and had previously worked with silica. The case highlights the clinical, radiological and pathological features of this syndrome and outlines the importance of considering a broad differential in the management of pulmonary nodules, especially in patients with rheumatoid arthritis.

The methods for detecting multiple small nodules from 3D chest X-ray CT images

International Nuclear Information System (INIS)

Hayase, Yosuke; Mekada, Yoshito; Mori, Kensaku; Toriwaki, Jun-ichiro; Natori, Hiroshi

2004-01-01

This paper describes a method for detecting small nodules, whose CT values and diameters are more than -600 Hounsfield unit (H.U.) and 2 mm, from three-dimensional chest X-ray CT images. The proposed method roughly consists of two submodules: initial detection of nodule candidates by discriminating between nodule regions and other regions such as blood vessels or bronchi using a shape feature computed from distance values inside the regions and reduction of false positive (FP) regions by using a minimum directional difference filter called minimum directional difference filter (Min-DD) changing its radius suit to the size of the initial candidates. The performance of the proposed method was evaluated by using seven cases of chest X-ray CT images including six abnormal cases where multiple lung cancers are observed. The experimental results for nodules (361 regions in total) showed that sensitivity and FP regions are 71% and 7.4 regions in average per case. (author)

Nodule detection by chest X-ray and evaluation of computer-aided detection (CAD) software using an originally developed phantom for instructional purposes

International Nuclear Information System (INIS)

Nitta, Norihisa; Takahashi, Masashi; Takazakura, Ryutaro

2006-01-01

Chest X-ray and computed tomography (CT) are indispensable modalities for lung cancer examinations. CT technologies have dramatically improved and small nodules and obscure shadows have been detected more frequently. The new generation of radiologists feels that chest X-rays are not as useful as chest CT. Experiments using a newly-developed chest phantom were conducted to reconfirm blind spots in chest X-rays. Recent technological advances and high-definition capability have made chest X-rays more useful than ever. Even though development of multi-detector CT (MDCT) has facilitated detection of nodules, it has conversely incurred a problem of increasing data for analysis, taking tremendous time and effort. Here, employing a chest phantom and clinical samples, we evaluated the utility of two kinds of computer-aided detection (CAD) software (Image Checker CT and LungCARE NEV) as well as GGO CAD software that we have developed. More development of chest CT diagnostic software is urgently needed. (author)

Differentiating early malignant lung tumors from inflammatory nodules to minimize the use of video-assisted thoracoscopic surgery or open biopsy to establish a diagnosis

International Nuclear Information System (INIS)

Nomori, Hiroaki; Horio, Hirotoshi; Suemasu, Keiichi

2001-01-01

To decrease the frequency of video-assisted thoracoscopic surgery (VATS) biopsy being used to diagnose inflammatory nodules, we studied the clinicopathological findings of lung cancers and inflammatory nodules diagnosed by VATS or open-lung biopsy. We studied 46 lung cancers and 47 inflammatory nodules smaller than 30 mm in diameter diagnosed by VATS or open-lung biopsy. While the computed tomography (CT) findings were not significantly different between lung cancers and inflammatory nodules, N1 or N2 lung cancers more frequently showed distinct malignant features on CT than T1N0M0 lung cancers (P<0.05). A review of previous chest X-ray films revealed that those of inflammatory nodules showed new nodules more frequently and nodular enlargement less frequently than those of lung cancer (P<0.01). Of 13 lung cancers that showed nodular enlargement during a mean 15-month period, 12 were T1N0M0. Nondiagnosable small lung nodules, which had few malignant features on CT and had newly appeared on a chest X-ray film, were more likely to be inflammatory nodules than lung cancers; and even if they were lung cancers, the tumor stage was usually T1N0M0. Thus, to decrease the incidence of VATS biopsy being performed for inflammatory nodules, intensive follow-up by CT until slight nodular enlargement becomes evident could be a means of revealing nondiagnosable small lung nodules without distinct malignant findings, except for nodules found to be enlarging on a review of retrospective films. (author)

A deep 3D residual CNN for false-positive reduction in pulmonary nodule detection.

Science.gov (United States)

Jin, Hongsheng; Li, Zongyao; Tong, Ruofeng; Lin, Lanfen

2018-05-01

The automatic detection of pulmonary nodules using CT scans improves the efficiency of lung cancer diagnosis, and false-positive reduction plays a significant role in the detection. In this paper, we focus on the false-positive reduction task and propose an effective method for this task. We construct a deep 3D residual CNN (convolution neural network) to reduce false-positive nodules from candidate nodules. The proposed network is much deeper than the traditional 3D CNNs used in medical image processing. Specifically, in the network, we design a spatial pooling and cropping (SPC) layer to extract multilevel contextual information of CT data. Moreover, we employ an online hard sample selection strategy in the training process to make the network better fit hard samples (e.g., nodules with irregular shapes). Our method is evaluated on 888 CT scans from the dataset of the LUNA16 Challenge. The free-response receiver operating characteristic (FROC) curve shows that the proposed method achieves a high detection performance. Our experiments confirm that our method is robust and that the SPC layer helps increase the prediction accuracy. Additionally, the proposed method can easily be extended to other 3D object detection tasks in medical image processing. © 2018 American Association of Physicists in Medicine.

Diagnosis and management of solitary pulmonary nodules.

Science.gov (United States)

Jeong, Yeon Joo; Lee, Kyung Soo; Kwon, O Jung

2008-12-01

The advent of computed tomography (CT) screening with or without the help of computer-aided detection systems has increased the detection rate of solitary pulmonary nodules (SPNs), including that of early peripheral lung cancer. Helical dynamic (HD)CT, providing the information on morphologic and hemodynamic characteristics with high specificity and reasonably high accuracy, can be used for the initial assessment of SPNs. (18)F-fluorodeoxyglucose PET/CT is more sensitive at detecting malignancy than HDCT. Therefore, PET/CT may be selectively performed to characterize SPNs when HDCT gives an inconclusive diagnosis. Serial volume measurements are currently the most reliable methods for the tissue characterization of subcentimeter nodules. When malignant nodule is highly suspected for subcentimeter nodules, video-assisted thoracoscopic surgery nodule removal after nodule localization using the pulmonary nodule-marker system may be performed for diagnosis and treatment.

Role of high-resolution CT in the diagnosis of small pulmonary nodules coexisting with potentially operable lung cancer

International Nuclear Information System (INIS)

Yuan, Yue; Matsumoto, Tsuneo; Hiyama, Atsuto; Miura, Goji; Tanaka, Nobuyuki; Matsunaga, Naofumi

2002-01-01

The purpose of this study was to evaluate whether high-resolution CT (HRCT) could facilitate the preoperative diagnosis of one or two small nodules of 1 cm or less coexisting with a lung cancer, i.e., coexisting small nodule. This study included 27 coexisting small nodules in 24 potentially operable lung cancer patients. An observer study was performed by five radiologists. The observer performances in differentiating malignant from benign coexisting small nodules were evaluated on conventional CT and HRCT using receiver operating characteristic (ROC) analysis. The area under the ROC curve of five observers was 0.731 on HRCT and 0.578 on conventional CT in the differential diagnosis of coexisting small nodules. A significant diagnostic improvement was found on HRCT (p=0.031). This was especially evident for nodules of ground-glass attenuation (p=0.005). HRCT plays an important role in determining the treatment of potentially operable lung cancer patients with coexisting small nodules. (author)

Subsolid pulmonary nodules: imaging evaluation and strategic management.

Science.gov (United States)

Godoy, Myrna C B; Sabloff, Bradley; Naidich, David P

2012-07-01

Given the higher rate of malignancy of subsolid pulmonary nodules and the considerably lower growth rate of ground-glass nodules (GGNs), dedicated standardized guidelines for management of these nodules have been proposed, including long-term low-dose computed tomography (CT) follow-up (≥3 years). Physicians must be familiar with the strategic management of subsolid pulmonary nodules, and should be able to identify imaging features that suggest invasive adenocarcinoma requiring a more aggressive management. Low-dose CT screening studies for early detection of lung cancer have increased our knowledge of pulmonary nodules, and in particular our understanding of the strong although imperfect correlation of the subsolid pulmonary nodules, including pure GGNs and part-solid nodules, with the spectrum of preinvasive to invasive lung adenocarcinoma. Serial CT imaging has shown stepwise progression in a subset of these nodules, characterized by increase in size and density of pure GGNs and development of a solid component, the latter usually indicating invasive adenocarcinoma. There is close correlation between the CT features of subsolid nodules (SSNs) and the spectrum of lung adenocarcinoma. Standardized guidelines are suggested for management of SSNs.

Computer-aided detection (CAD) of lung nodules in CT scans: radiologist performance and reading time with incremental CAD assistance

International Nuclear Information System (INIS)

Roos, Justus E.; Paik, David; Olsen, David; Liu, Emily G.; Leung, Ann N.; Mindelzun, Robert; Choudhury, Kingshuk R.; Napel, Sandy; Rubin, Geoffrey D.; Chow, Lawrence C.; Naidich, David P.

2010-01-01

The diagnostic performance of radiologists using incremental CAD assistance for lung nodule detection on CT and their temporal variation in performance during CAD evaluation was assessed. CAD was applied to 20 chest multidetector-row computed tomography (MDCT) scans containing 190 non-calcified ≥3-mm nodules. After free search, three radiologists independently evaluated a maximum of up to 50 CAD detections/patient. Multiple free-response ROC curves were generated for free search and successive CAD evaluation, by incrementally adding CAD detections one at a time to the radiologists' performance. The sensitivity for free search was 53% (range, 44%-59%) at 1.15 false positives (FP)/patient and increased with CAD to 69% (range, 59-82%) at 1.45 FP/patient. CAD evaluation initially resulted in a sharp rise in sensitivity of 14% with a minimal increase in FP over a time period of 100 s, followed by flattening of the sensitivity increase to only 2%. This transition resulted from a greater prevalence of true positive (TP) versus FP detections at early CAD evaluation and not by a temporal change in readers' performance. The time spent for TP (9.5 s ± 4.5 s) and false negative (FN) (8.4 s ± 6.7 s) detections was similar; FP decisions took two- to three-times longer (14.4 s ± 8.7 s) than true negative (TN) decisions (4.7 s ± 1.3 s). When CAD output is ordered by CAD score, an initial period of rapid performance improvement slows significantly over time because of non-uniformity in the distribution of TP CAD output and not to a changing reader performance over time. (orig.)

Computer-aided detection of pulmonary nodules: a comparative study using the public LIDC/IDRI database

International Nuclear Information System (INIS)

Jacobs, Colin; Prokop, Mathias; Rikxoort, Eva M. van; Ginneken, Bram van; Murphy, Keelin; Schaefer-Prokop, Cornelia M.

2016-01-01

To benchmark the performance of state-of-the-art computer-aided detection (CAD) of pulmonary nodules using the largest publicly available annotated CT database (LIDC/IDRI), and to show that CAD finds lesions not identified by the LIDC's four-fold double reading process. The LIDC/IDRI database contains 888 thoracic CT scans with a section thickness of 2.5 mm or lower. We report performance of two commercial and one academic CAD system. The influence of presence of contrast, section thickness, and reconstruction kernel on CAD performance was assessed. Four radiologists independently analyzed the false positive CAD marks of the best CAD system. The updated commercial CAD system showed the best performance with a sensitivity of 82 % at an average of 3.1 false positive detections per scan. Forty-five false positive CAD marks were scored as nodules by all four radiologists in our study. On the largest publicly available reference database for lung nodule detection in chest CT, the updated commercial CAD system locates the vast majority of pulmonary nodules at a low false positive rate. Potential for CAD is substantiated by the fact that it identifies pulmonary nodules that were not marked during the extensive four-fold LIDC annotation process. (orig.)

A mixed reality approach for stereo-tomographic quantification of lung nodules.

Science.gov (United States)

Chen, Mianyi; Kalra, Mannudeep K; Yun, Wenbing; Cong, Wenxiang; Yang, Qingsong; Nguyen, Terry; Wei, Biao; Wang, Ge

2016-05-25

To reduce the radiation dose and the equipment cost associated with lung CT screening, in this paper we propose a mixed reality based nodule measurement method with an active shutter stereo imaging system. Without involving hundreds of projection views and subsequent image reconstruction, we generated two projections of an iteratively placed ellipsoidal volume in the field of view and merging these synthetic projections with two original CT projections. We then demonstrated the feasibility of measuring the position and size of a nodule by observing whether projections of an ellipsoidal volume and the nodule are overlapped from a human observer's visual perception through the active shutter 3D vision glasses. The average errors of measured nodule parameters are less than 1 mm in the simulated experiment with 8 viewers. Hence, it could measure real nodules accurately in the experiments with physically measured projections.

AUTOMATIC LUNG NODULE SEGMENTATION USING AUTOSEED REGION GROWING WITH MORPHOLOGICAL MASKING (ARGMM AND FEATURE EX-TRACTION THROUGH COMPLETE LOCAL BINARY PATTERN AND MICROSCOPIC INFORMATION PATTERN

Directory of Open Access Journals (Sweden)

Senthil Kumar

2015-04-01

Full Text Available An efficient Autoseed Region Growing with Morphological Masking(ARGMM is imple-mented in this paper on the Lung CT Slice to segment the 'Lung Nodules',which may be the potential indicator for the Lung Cancer. The segmentation of lung nodules car-ried out in this paper through Multi-Thresholding, ARGMM and Level Set Evolution. ARGMM takes twice the time compared to Level Set, but still the number of suspected segmented nodules are doubled, which make sure that no potential cancerous nodules go unnoticed at the earlier stages of diagnosis. It is very important not to panic the patient by finding the presence of nodules from Lung CT scan. Only 40 percent of nod-ules can be cancerous. Hence, in this paper an efficient Shape and Texture analysis is computed to quantitatively describe the segmented lung nodules. The Frequency spectrum of the lung nodules is developed and its frequency domain features are com-puted. The Complete Local binary pattern of lung nodules is computed in this paper by constructing the combine histogram of Sign and Magnitude Local Binary Patterns. Lo-cal Configuration Pattern is also determined in this work for lung nodules to numeri-cally model the microscopic information of nodules pattern.

Automatic detection of spiculation of pulmonary nodules in computed tomography images

DEFF Research Database (Denmark)

Ciompi, F; Jacobs, C; Scholten, E.T.

2015-01-01

to classify spiculated nodules via supervised learning. We tested our approach on a set of nodules from the Danish Lung Cancer Screening Trial (DLCST) dataset. Our results show that the proposed method outperforms other 3-D descriptors of morphology in the automatic assessment of spiculation. © (2015......-up procedure. For this reason, lung cancer screening scenario would benefit from the presence of a fully automatic system for the assessment of spiculation. The presented framework relies on the fact that spiculated nodules mainly differ from non-spiculated ones in their morphology. In order to discriminate....... A library of spectra is created by clustering data via unsupervised learning. The centroids of the clusters are used to label back each spectrum in the sampling pattern. A compact descriptor encoding the nodule morphology is obtained as the histogram of labels along all the spherical surfaces and used...

3D multi-view convolutional neural networks for lung nodule classification

Science.gov (United States)

Kang, Guixia; Hou, Beibei; Zhang, Ningbo

2017-01-01

The 3D convolutional neural network (CNN) is able to make full use of the spatial 3D context information of lung nodules, and the multi-view strategy has been shown to be useful for improving the performance of 2D CNN in classifying lung nodules. In this paper, we explore the classification of lung nodules using the 3D multi-view convolutional neural networks (MV-CNN) with both chain architecture and directed acyclic graph architecture, including 3D Inception and 3D Inception-ResNet. All networks employ the multi-view-one-network strategy. We conduct a binary classification (benign and malignant) and a ternary classification (benign, primary malignant and metastatic malignant) on Computed Tomography (CT) images from Lung Image Database Consortium and Image Database Resource Initiative database (LIDC-IDRI). All results are obtained via 10-fold cross validation. As regards the MV-CNN with chain architecture, results show that the performance of 3D MV-CNN surpasses that of 2D MV-CNN by a significant margin. Finally, a 3D Inception network achieved an error rate of 4.59% for the binary classification and 7.70% for the ternary classification, both of which represent superior results for the corresponding task. We compare the multi-view-one-network strategy with the one-view-one-network strategy. The results reveal that the multi-view-one-network strategy can achieve a lower error rate than the one-view-one-network strategy. PMID:29145492

Importance of scatter compensation algorithm in heterogeneous tissue for the radiation dose calculation of small lung nodules. A clinical study

International Nuclear Information System (INIS)

Baba, Yuji; Murakami, Ryuji; Mizukami, Naohisa; Morishita, Shoji; Yamashita, Yasuyuki; Araki, Fujio; Moribe, Nobuyuki; Hirata, Yukinori

2004-01-01

The purpose of this study was to compare radiation doses of small lung nodules calculated with beam scattering compensation and those without compensation in heterogeneous tissues. Computed tomography (CT) data of 34 small (1-2 cm: 12 nodules, 2-3 cm 11 nodules, 3-4 cm 11 nodules) lung nodules were used in the radiation dose measurements. Radiation planning for lung nodule was performed with a commercially available unit using two different radiation dose calculation methods: the superposition method (with scatter compensation in heterogeneous tissues), and the Clarkson method (without scatter compensation in heterogeneous tissues). The energy of the linac photon used in this study was 10 MV and 4 MV. Monitor unit (MU) to deliver 10 Gy at the center of the radiation field (center of the nodule) calculated with the two methods were compared. In 1-2 cm nodules, MU calculated by Clarkson method (MUc) was 90.0±1.1% (4 MV photon) and 80.5±2.7% (10 MV photon) compared to MU calculated by superposion method (MUs), in 2-3 cm nodules, MUc was 92.9±1.1% (4 MV photon) and 86.6±2.8% (10 MV photon) compared to MUs, and in 3-4 cm nodules, MUc was 90.5±2.0% (4 MV photon) and 90.1±1.7% (10 MV photon) compared to MUs. In 1-2 cm nodules, MU calculated without lung compensation (MUn) was 120.6±8.3% (4 MV photon) and 95.1±4.1% (10 MV photon) compared to MU calculated by superposion method (MUs), in 2-3 cm nodules, MUc was 120.3±11.5% (4 MV photon) and 100.5±4.6% (10 MV photon) compared to MUs, and in 3-4 cm nodules, MUc was 105.3±9.0% (4 MV photon) and 103.4±4.9% (10 MV photon) compared to MUs. The MU calculated without lung compensation was not significantly different from the MU calculated by superposition method in 2-3 cm nodules. We found that the conventional dose calculation algorithm without scatter compensation in heterogeneous tissues substantially overestimated the radiation dose of small nodules in the lung field. In the calculation of dose distribution of small

Automatic Approach for Lung Segmentation with Juxta-Pleural Nodules from Thoracic CT Based on Contour Tracing and Correction

Directory of Open Access Journals (Sweden)

Jinke Wang

2016-01-01

Full Text Available This paper presents a fully automatic framework for lung segmentation, in which juxta-pleural nodule problem is brought into strong focus. The proposed scheme consists of three phases: skin boundary detection, rough segmentation of lung contour, and pulmonary parenchyma refinement. Firstly, chest skin boundary is extracted through image aligning, morphology operation, and connective region analysis. Secondly, diagonal-based border tracing is implemented for lung contour segmentation, with maximum cost path algorithm used for separating the left and right lungs. Finally, by arc-based border smoothing and concave-based border correction, the refined pulmonary parenchyma is obtained. The proposed scheme is evaluated on 45 volumes of chest scans, with volume difference (VD 11.15±69.63 cm3, volume overlap error (VOE 3.5057±1.3719%, average surface distance (ASD 0.7917±0.2741 mm, root mean square distance (RMSD 1.6957±0.6568 mm, maximum symmetric absolute surface distance (MSD 21.3430±8.1743 mm, and average time-cost 2 seconds per image. The preliminary results on accuracy and complexity prove that our scheme is a promising tool for lung segmentation with juxta-pleural nodules.

Lung cancer risk and cancer-specific mortality in subjects undergoing routine imaging test when stratified with and without identified lung nodule on imaging study

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Gomez-Saez, Noemi [Miguel Hernandez University, Public Health, History of Science and Ginecology Department, Alicante (Spain); Hernandez-Aguado, Ildefonso; Pastor Valero, Maria; Parker, Lucy Anne; Lumbreras, Blanca [Miguel Hernandez University, Public Health, History of Science and Ginecology Department, Alicante (Spain); CIBER en Epidemiologia y Salud Publica, Madrid (Spain); Vilar, Jose; Domingo, Maria Luisa [Peset Hospital, Radiodiagnostic Department, Valencia (Spain); Gonzalez-Alvarez, Isabel; Lorente, Maria Fermina [San Juan Hospital, Radiodiagnostic Department, San Juan de Alicante (Spain)

2015-12-15

To assess the risk of lung cancer and specific mortality rate in patients with and without solitary pulmonary nodules (SPN) on chest radiograph and CT. This prospective study included 16,078 patients ≥35 years old (893 of them had an SPN detected with either chest radiograph or CT) and 15,185 without SPN. Patients were followed up for 18 months or until being diagnosed with lung cancer. Risk and mortality lung cancer were calculated in both groups with Poisson regression. In patients with SPN, incidence of lung cancer was 8.3 % (95 % CI 6.0-11.2) on radiograph and 12.4 % (95 % CI 9.3-15.9) on CT. A chronic obstructive pulmonary disease in patients with radiographs (odds ratio 2.62; 95 % CI 1.03, 6.67) and smoking habit (odds ratio 20.63; 95 % CI 3.84, 110.77) in patients with CT were associated with a higher probability of lung cancer. Large nodule size and spiculated edge were associated with lung cancer on both CT and radiograph. Lung cancer-specific mortality was lower in patients with SPN than in those without SPN (1.73/1000 person-years, 95 % CI 1.08-2.88 vs. 2.15/1000 person-years, 95 % CI 1.25-3.96). The risk of lung cancer for patients with SPN is higher in clinical populations than in screening studies. Moreover, patients with SPN showed lower mortality than those without SPN. (orig.)

Lung cancer risk and cancer-specific mortality in subjects undergoing routine imaging test when stratified with and without identified lung nodule on imaging study

International Nuclear Information System (INIS)

Gomez-Saez, Noemi; Hernandez-Aguado, Ildefonso; Pastor Valero, Maria; Parker, Lucy Anne; Lumbreras, Blanca; Vilar, Jose; Domingo, Maria Luisa; Gonzalez-Alvarez, Isabel; Lorente, Maria Fermina

2015-01-01

To assess the risk of lung cancer and specific mortality rate in patients with and without solitary pulmonary nodules (SPN) on chest radiograph and CT. This prospective study included 16,078 patients ≥35 years old (893 of them had an SPN detected with either chest radiograph or CT) and 15,185 without SPN. Patients were followed up for 18 months or until being diagnosed with lung cancer. Risk and mortality lung cancer were calculated in both groups with Poisson regression. In patients with SPN, incidence of lung cancer was 8.3 % (95 % CI 6.0-11.2) on radiograph and 12.4 % (95 % CI 9.3-15.9) on CT. A chronic obstructive pulmonary disease in patients with radiographs (odds ratio 2.62; 95 % CI 1.03, 6.67) and smoking habit (odds ratio 20.63; 95 % CI 3.84, 110.77) in patients with CT were associated with a higher probability of lung cancer. Large nodule size and spiculated edge were associated with lung cancer on both CT and radiograph. Lung cancer-specific mortality was lower in patients with SPN than in those without SPN (1.73/1000 person-years, 95 % CI 1.08-2.88 vs. 2.15/1000 person-years, 95 % CI 1.25-3.96). The risk of lung cancer for patients with SPN is higher in clinical populations than in screening studies. Moreover, patients with SPN showed lower mortality than those without SPN. (orig.)

Incidental detection of prostate-specific antigen-negative metastatic prostate cancer initially presented with solitary pulmonary nodule on fluorodeoxyglucose positron emission tomography/computed tomography

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Erdogan, Ezgi Basak; Buyukpinarbasili, Nur; Ziyade, Sedat; Akman, Tolga; Turk, Haci Mehmet; Aydin, Mehmet

2005-01-01

A 71-year-old male patient with solitary pulmonary nodule underwent fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) showing slightly increased FDG uptake in this nodule. In addition, PET/CT detected hypermetabolic sclerotic bone lesions in the right second rib and 7 th thoracic vertebrae, which were interpreted as possible metastases, and mildly increased FDG uptake in the prostate gland highly suspicious of malignancy. The patient's prostate-specific antigen (PSA) level was within normal range (3.8 ng/dL). The histopathological examination of the lung nodule and right second rib lesion proved metastases from prostate cancer, then the prostate biopsy-confirmed prostate adenocarcinoma. The unique feature of this case is to emphasize the importance of performing PET/CT for solitary pulmonary nodule in detecting PSA-negative metastatic prostate cancer. This case indicated that it should be kept in mind that, even if the PSA is negative, a lung metastasis of prostate cancer may be an underlying cause in patients evaluated for solitary pulmonary nodule by FDG PET/CT

Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier.

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Mao, Keming; Deng, Zhuofu

2016-01-01

This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP) is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier.

Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier

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Keming Mao

2016-01-01

Full Text Available This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier.

Outcomes of Stereotactic Body Radiotherapy (SBRT) treatment of multiple synchronous and recurrent lung nodules

International Nuclear Information System (INIS)

Owen, Dawn; Olivier, Kenneth R; Mayo, Charles S; Miller, Robert C; Nelson, Kathryn; Bauer, Heather; Brown, Paul D; Park, Sean S; Ma, Daniel J; Garces, Yolanda I

2015-01-01

Stereotactic body radiotherapy (SBRT) is evolving into a standard of care for unresectable lung nodules. Local control has been shown to be in excess of 90% at 3 years. However, some patients present with synchronous lung nodules in the ipsilateral or contralateral lobe or metasynchronous disease. In these cases, patients may receive multiple courses of lung SBRT or a single course for synchronous nodules. The toxicity of such treatment is currently unknown. Between 2006 and 2012, 63 subjects with 128 metasynchronous and synchronous lung nodules were treated at the Mayo Clinic with SBRT. Demographic patient data and dosimetric data regarding SBRT treatments were collected. Acute toxicity (defined as toxicity < 90 days) and late toxicity (defined as toxicity > = 90 days) were reported and graded as per standardized CTCAE 4.0 criteria. Local control, progression free survival and overall survival were also described. The median age of patients treated was 73 years. Sixty five percent were primary or recurrent lung cancers with the remainder metastatic lung nodules of varying histologies. Of 63 patients, 18 had prior high dose external beam radiation to the mediastinum or chest. Dose and fractionation varied but the most common prescriptions were 48 Gy/4 fractions, 54 Gy/3 fractions, and 50 Gy/5 fractions. Only 6 patients demonstrated local recurrence. With a median follow up of 12.6 months, median SBRT specific overall survival and progression free survival were 35.7 months and 10.7 months respectively. Fifty one percent (32/63 patients) experienced acute toxicity, predominantly grade 1 and 2 fatigue. One patient developed acute grade 3 radiation pneumonitis at 75 days. Forty six percent (29/63 patients) developed late effects. Most were grade 1 dyspnea. There was one patient with grade 5 pneumonitis. Multiple courses of SBRT and SBRT delivery after external beam radiotherapy appear to be feasible and safe. Most toxicity was grade 1 and 2 but the risk was

Detection of pulmonary nodules on lung X-ray images. Studies on multi-resolutional filter and energy subtraction images

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Sawada, Akira; Sato, Yoshinobu; Kido, Shoji; Tamura, Shinichi

1999-01-01

The purpose of this work is to prove the effectiveness of an energy subtraction image for the detection of pulmonary nodules and the effectiveness of multi-resolutional filter on an energy subtraction image to detect pulmonary nodules. Also we study influential factors to the accuracy of detection of pulmonary nodules from viewpoints of types of images, types of digital filters and types of evaluation methods. As one type of images, we select an energy subtraction image, which removes bones such as ribs from the conventional X-ray image by utilizing the difference of X-ray absorption ratios at different energy between bones and soft tissue. Ribs and vessels are major causes of CAD errors in detection of pulmonary nodules and many researches have tried to solve this problem. So we select conventional X-ray images and energy subtraction X-ray images as types of images, and at the same time select ∇ 2 G (Laplacian of Guassian) filter, Min-DD (Minimum Directional Difference) filter and our multi-resolutional filter as types of digital filters. Also we select two evaluation methods and prove the effectiveness of an energy subtraction image, the effectiveness of Min-DD filter on a conventional X-ray image and the effectiveness of multi-resolutional filter on an energy subtraction image. (author)

The incidental pulmonary nodule in a child. Part 2: Commentary and suggestions for clinical management, risk communication and prevention

International Nuclear Information System (INIS)

Westra, Sjirk J.; Thacker, Paul G.; Podberesky, Daniel J.; Lee, Edward Y.; Iyer, Ramesh S.; Hegde, Shilpa V.; Guillerman, R.P.; Mahani, Maryam Ghadimi

2015-01-01

The incidental detection of small lung nodules in children is a vexing consequence of an increased reliance on CT. We present an algorithm for the management of lung nodules detected on CT in children, based on the presence or absence of symptoms, the presence or absence of elements in the clinical history that might explain these nodules, and the imaging characteristics of the nodules (such as attenuation measurements within the nodule). We provide suggestions on how to perform a thoughtfully directed and focused search for clinically occult extrathoracic disease processes (including malignant disease) that may present as an incidentally detected lung nodule on CT. This algorithm emphasizes that because of the lack of definitive information on the natural history of small solid nodules that are truly detected incidentally, their clinical management is highly dependent on the caregivers' individual risk tolerance. In addition, we present strategies to reduce the prevalence of these incidental findings, by preventing unnecessary chest CT scans or inadvertent inclusion of portions of the lungs in scans of adjacent body parts. Application of these guidelines provides pediatric radiologists with an important opportunity to practice patient-centered and evidence-based medicine. (orig.)

Initial application of digital tomosynthesis for detection of pulmonary nodules

International Nuclear Information System (INIS)

Sun Zhiyuan; Su Hong; Zhao Yane; Ju Bing; Chang Shuanghui; Hu Qiuju; Lu Guangming

2010-01-01

Objective: To discuss the value of digital tomosynthesis for detection of pulmonary nodules. Methods: Thirty patients suspected of having pulmonary nodules underwent chest radiography, digital tomosynthesis and CT examination. Above image data were transferred to postprocessing work station and were reviewed by 2 radiologists with 3 years of chest-radiology diagnosis experience in a double-blind method. The number, location and size of nodules were recorded. Then, 2 radiologists reviewed the all images once more, and discuss in consensus. The sensitivities of chest radiography and digital tomosynthesis for detection of pulmonary nodules were respectively calculated according to the CT results. Chi-square test was used for radiography, digital tomosynthesis and CT examination. Results: Of 30 patients, 21 were detected having pulmonary nodules by X-ray radiography and 9 were negative, the total number of 40 nodules was detected, while 89 nodules in 26 patients were detected by digital tomosynthesis, and only 4 patients were negative. CT demonstrated 102 nodules in 27 patients, and 3 patients were negative. Taking CT as 'gold standard', the sensitivities of X-ray radiography and digital tomosynthesis were 27.4%(28/102)and 87.2%(89/102), X 2 =4.35, P<0.05, respectively. Conclusion: Digital tomosynthesis has a high sensitivity for detection of pulmonary nodules compared with X-ray radiography, and could be an excellent and necessary supplementary technique of X-ray radiography. (authors)

An Unusual Radiologic Manifestation of Pulmonary Tuberculosis with Bilateral Multiple Lung Nodules and Diffuse Alveolar Hemorrhage: A Case Report

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Jeong, Seo In; Seon, Hyun Ju; Kim, Yun Hyeon [Dept. of Radiology, Chunnam National University Hospital, Gwangju (Korea, Republic of); Choi, Sung [Dept. of Radiology, Chunnam National University Hwasun Hospital, Hwasun(Korea, Republic of)

2011-12-15

Pulmonary tuberculosis presenting as bilateral multiple lung nodules or diffuse alveolar hemorrhage is very rare. Here, we report a case of pulmonary tuberculosis presenting as bilateral multiple lung nodules and diffuse alveolar hemorrhage mimicking granulomatous vasculitis, such as Wegener's granulomatosis.

Radiofrequency thermal ablation of a metastatic lung nodule

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Highland, Adrian M. [Department of Clinical Radiology, Hull Royal Infirmary, Anlaby Road, Hull, HU3 2JZ (United Kingdom); Mack, Paul [Diana Princess of Wales Hospital, Scartho Road, Grimsby, DN33 2BA (United Kingdom); Breen, David J. [Department of Radiology, Southampton University Hospitals, Tremona Road, Southampton, SO16 6YD (United Kingdom)

2002-07-01

Pulmonary metastases are a common finding in patients with colonic adenocarcinoma. We report the treatment of a metastatic lung nodule with radiofrequency (RF) ablation under CT guidance. This case illustrates the use of RF ablation in a patient in whom surgical resection was no longer possible and where chemotherapy was unlikely to produce benefit. This technique may offer a viable method of cytoreduction when other treatments have not succeeded. (orig.)

Radiofrequency thermal ablation of a metastatic lung nodule

International Nuclear Information System (INIS)

Highland, Adrian M.; Mack, Paul; Breen, David J.

2002-01-01

Pulmonary metastases are a common finding in patients with colonic adenocarcinoma. We report the treatment of a metastatic lung nodule with radiofrequency (RF) ablation under CT guidance. This case illustrates the use of RF ablation in a patient in whom surgical resection was no longer possible and where chemotherapy was unlikely to produce benefit. This technique may offer a viable method of cytoreduction when other treatments have not succeeded. (orig.)

Cryptogenic Organizing Pneumonia With Lung Nodules Secondary to Pulmonary Manifestation of Crohn Disease

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Taufiq Zaman

2017-05-01

Full Text Available Crohn disease is an immune-mediated inflammatory condition with gastrointestinal and extraintestinal manifestations in patients. Pulmonary involvement of Crohn disease is one manifestation. There have been case reports which have shown Crohn disease and lung nodules which were noted to be histopathological as cryptogenic organizing pneumonia (COP. In our case, a 22-year-old woman with Crohn disease was seen with complaints of chest pain and cough. Computed tomographic scan of chest showed multiple bilateral lung nodules, for which biopsy was done, which showed COP. The case study is followed by a deeper discussion of COP and the extraintestinal manifestation seen in inflammatory bowel disease.

Differential diagnosis and cancer staging of a unique case with multiple nodules in the lung - lung adenocarcinoma, metastasis of colon adenocarcinoma, and colon adenocarcinoma metastasizing to lung adenocarcinoma.

Science.gov (United States)

Bai, Yun; Qiu, Jianxing; Shang, Xueqian; Liu, Ping; Zhang, Ying; Wang, Ying; Xiong, Yan; Li, Ting

2015-05-01

Lung cancer is the most common cancer in the world. Despite this, there have been few cases of simultaneous primary and metastatic cancers in the lung reported, let alone coexisting with tumor-to-tumor metastasis. Herein, we describe an extremely unusual case. A 61-year-old man with a history of colon adenocarcinoma was revealed as having three nodules in the lung 11 months after colectomy. The nodule in the left upper lobe was primary lung adenocarcinoma, the larger one in the right upper lobe was a metastasis of colon adenocarcinoma, and the smaller one in the right upper lobe was colon adenocarcinoma metastasizing to lung adenocarcinoma. Our paper focused on the differential diagnosis and cancer staging of this unique case, and discussed the uncommon phenomenon of the lung acting as a recipient in tumor-to-tumor metastasis.

Development and validation of a prediction model for measurement variability of lung nodule volumetry in patients with pulmonary metastases.

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Hwang, Eui Jin; Goo, Jin Mo; Kim, Jihye; Park, Sang Joon; Ahn, Soyeon; Park, Chang Min; Shin, Yeong-Gil

2017-08-01

To develop a prediction model for the variability range of lung nodule volumetry and validate the model in detecting nodule growth. For model development, 50 patients with metastatic nodules were prospectively included. Two consecutive CT scans were performed to assess volumetry for 1,586 nodules. Nodule volume, surface voxel proportion (SVP), attachment proportion (AP) and absolute percentage error (APE) were calculated for each nodule and quantile regression analyses were performed to model the 95% percentile of APE. For validation, 41 patients who underwent metastasectomy were included. After volumetry of resected nodules, sensitivity and specificity for diagnosis of metastatic nodules were compared between two different thresholds of nodule growth determination: uniform 25% volume change threshold and individualized threshold calculated from the model (estimated 95% percentile APE). SVP and AP were included in the final model: Estimated 95% percentile APE = 37.82 · SVP + 48.60 · AP-10.87. In the validation session, the individualized threshold showed significantly higher sensitivity for diagnosis of metastatic nodules than the uniform 25% threshold (75.0% vs. 66.0%, P = 0.004) CONCLUSION: Estimated 95% percentile APE as an individualized threshold of nodule growth showed greater sensitivity in diagnosing metastatic nodules than a global 25% threshold. • The 95 % percentile APE of a particular nodule can be predicted. • Estimated 95 % percentile APE can be utilized as an individualized threshold. • More sensitive diagnosis of metastasis can be made with an individualized threshold. • Tailored nodule management can be provided during nodule growth follow-up.

Diffusion-weighted MR-imaging for the detection of pulmonary nodules at 1.5 Tesla: intraindividual comparison with multidetector computed tomography

International Nuclear Information System (INIS)

Regier, Marc; Schwarz, Dorothee; Henes, Frank Oliver; Groth, Michael; Begemann, Philipp G.C.; Adam, Gerhard; Kooijman, Hendrik

2011-01-01

To investigate the feasibility of diffusion-weighted imaging (DWI) MRI for detecting pulmonary nodules at 1.5 Tesla in comparison with standard multidetector computed tomography (MDCT). Twenty patients with disseminated cancer disease in which MDCT had assured the presence of at least one pulmonary nodule were examined using a respiratory-gated DWI MR-sequence. Grey scale inverted source images and coronal maximum intensity projection (MIP) images were consensually analysed by two experienced radiologists. Size and location of any nodule detected were assessed. Additionally, the readers evaluated each hemithorax for the presence of at least one nodule and applied a four-point conspicuity scale (1-hemithorax definitely affected; 4-hemithorax definitely not affected). MDCT data served as reference. At MDCT, a total of 71 pulmonary noduIes was found (size 3–5 mm, n = 16; 6–9 mm, n = 22; ≥10 mm, n = 33). For the DWI MR-sequence, a sensitivity of 86.4% was calculated for nodules ranging 6–9 mm and 97% for nodules ≥10 mm. In contrast, only 43.8% of lesions ≤5 mm was detected. The separate analysis of each hemithorax for the presence of at least one pulmonary nodule revealed a specificity rate, PPV and NPV of DWI-MR of 92.3%, 96% and 80%, respectively. The presented study is the first to confirm the diagnostic potential of DWI-MR in the detection of solid lung nodules. This technique allows for the detection of nodules ≥6 mm with reasonably high sensitivity rates (>86%). The observation of false positive findings decreases the accuracy of this approach compared with MDCT.

Automated detection of pulmonary nodules in CT images with support vector machines

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Liu, Lu; Liu, Wanyu; Sun, Xiaoming

2008-10-01

Many methods have been proposed to avoid radiologists fail to diagnose small pulmonary nodules. Recently, support vector machines (SVMs) had received an increasing attention for pattern recognition. In this paper, we present a computerized system aimed at pulmonary nodules detection; it identifies the lung field, extracts a set of candidate regions with a high sensitivity ratio and then classifies candidates by the use of SVMs. The Computer Aided Diagnosis (CAD) system presented in this paper supports the diagnosis of pulmonary nodules from Computed Tomography (CT) images as inflammation, tuberculoma, granuloma..sclerosing hemangioma, and malignant tumor. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of SVMs classifiers. The achieved classification performance was 100%, 92.75% and 90.23% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

TU-FG-209-11: Validation of a Channelized Hotelling Observer to Optimize Chest Radiography Image Processing for Nodule Detection: A Human Observer Study

International Nuclear Information System (INIS)

Sanchez, A; Little, K; Chung, J; Lu, ZF; MacMahon, H; Reiser, I

2016-01-01

Purpose: To validate the use of a Channelized Hotelling Observer (CHO) model for guiding image processing parameter selection and enable improved nodule detection in digital chest radiography. Methods: In a previous study, an anthropomorphic chest phantom was imaged with and without PMMA simulated nodules using a GE Discovery XR656 digital radiography system. The impact of image processing parameters was then explored using a CHO with 10 Laguerre-Gauss channels. In this work, we validate the CHO’s trend in nodule detectability as a function of two processing parameters by conducting a signal-known-exactly, multi-reader-multi-case (MRMC) ROC observer study. Five naive readers scored confidence of nodule visualization in 384 images with 50% nodule prevalence. The image backgrounds were regions-of-interest extracted from 6 normal patient scans, and the digitally inserted simulated nodules were obtained from phantom data in previous work. Each patient image was processed with both a near-optimal and a worst-case parameter combination, as determined by the CHO for nodule detection. The same 192 ROIs were used for each image processing method, with 32 randomly selected lung ROIs per patient image. Finally, the MRMC data was analyzed using the freely available iMRMC software of Gallas et al. Results: The image processing parameters which were optimized for the CHO led to a statistically significant improvement (p=0.049) in human observer AUC from 0.78 to 0.86, relative to the image processing implementation which produced the lowest CHO performance. Conclusion: Differences in user-selectable image processing methods on a commercially available digital radiography system were shown to have a marked impact on performance of human observers in the task of lung nodule detection. Further, the effect of processing on humans was similar to the effect on CHO performance. Future work will expand this study to include a wider range of detection/classification tasks and more

Fusobacterium necrophorum presenting as isolated lung nodules

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Rajiv Sonti

2015-01-01

Full Text Available Fusobacterium necrophorum causes Lemierre's syndrome - a dramatic and distinct condition beginning with pharyngitis before proceeding to internal jugular vein septic thrombophlebitis and respiratory tract infection in otherwise healthy individuals. It is rare, but by far the most common pathway to parenchymal lung disease with this organism. Here we describe we a 34 year old healthy lady who was nontoxic without any antecedent illness who presented with lung nodules due to fusobacterium necrophorum as the sole manifestation of disease. Leading diagnostic consideration prior to culture data was pulmonary vasculitis. Identifying her disease process was a somewhat chance occurrence, and it began to resolve prior to antibiotic therapy. Though it would be difficult to recommend keen awareness of this organism given its rarity, it is important to consider that its scope may be broader than traditionally considered.

Hard-copy versus soft-copy with and without simple image manipulation for detection of pulmonary nodules and masses

International Nuclear Information System (INIS)

Kosuda, S.; Kaji, T.; Iwasaki, Y.; Kusano, S.; Kobayashi, H.; Watanabe, M.

2000-01-01

To compare interpretation performance on soft-copy presentations, with and without simple image manipulation, and on unmodified hard-copy presentations with regard to detection of pulmonary nodules and masses. Material and Methods: Fifty chest digital radiograph combinations of patients with a total of 60 nodules, 32 of which were 2.0 cm in diameter, were selected for the study. Three readers evaluated three separate image formats: unmodified hard- and soft-copies, and soft-copies with simple image manipulation of lung and mediastinum window settings, and zooming. The screen display was 1600x1200 pixels with 8 bits/pixel. Results: The sensitivity, accuracy, detectability, and Az value of the soft-copy systems were clearly inferior to hard-copy evaluation. The mean Az values were 0.921 for unmodified hard-copy, 0.820 for image-manipulated soft-copy, and 0.781 for unmodified soft-copy. Conclusion: Soft-copy interpretations were not as sensitive in detecting pulmonary nodules and masses as hard-copy evaluation

Noninvasive Computed Tomography-based Risk Stratification of Lung Adenocarcinomas in the National Lung Screening Trial.

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Maldonado, Fabien; Duan, Fenghai; Raghunath, Sushravya M; Rajagopalan, Srinivasan; Karwoski, Ronald A; Garg, Kavita; Greco, Erin; Nath, Hrudaya; Robb, Richard A; Bartholmai, Brian J; Peikert, Tobias

2015-09-15

Screening for lung cancer using low-dose computed tomography (CT) reduces lung cancer mortality. However, in addition to a high rate of benign nodules, lung cancer screening detects a large number of indolent cancers that generally belong to the adenocarcinoma spectrum. Individualized management of screen-detected adenocarcinomas would be facilitated by noninvasive risk stratification. To validate that Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel image analysis software, successfully risk stratifies screen-detected lung adenocarcinomas based on clinical disease outcomes. We identified retrospective 294 eligible patients diagnosed with lung adenocarcinoma spectrum lesions in the low-dose CT arm of the National Lung Screening Trial. The last low-dose CT scan before the diagnosis of lung adenocarcinoma was analyzed using CANARY blinded to clinical data. Based on their parametric CANARY signatures, all the lung adenocarcinoma nodules were risk stratified into three groups. CANARY risk groups were compared using survival analysis for progression-free survival. A total of 294 patients were included in the analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into the Good, Intermediate, and Poor CANARY risk groups yielded distinct progression-free survival curves (P < 0.0001). This observation was confirmed in the unadjusted and adjusted (age, sex, race, and smoking status) progression-free survival analysis of all stage I cases. CANARY allows the noninvasive risk stratification of lung adenocarcinomas into three groups with distinct post-treatment progression-free survival. Our results suggest that CANARY could ultimately facilitate individualized management of incidentally or screen-detected lung adenocarcinomas.

Toxocariasis masquerading as liver and lung metastatic nodules in patents with gastrointestinal cancer: clinicopathologic study of five cases.

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Park, Sanghui; Kim, Yun Soo; Kim, Yu Jin; Kyung, Sun Young; Park, Jeong-Woong; Jeong, Sung Hwan; Lee, Sang Pyo

2012-01-01

There are sporadic reports in the literature in which radiologic liver and lung lesions found incidentally during follow-up metastatic surveillance were shown to be caused by toxocariasis. The objective of the work discussed in this report was to identify common clinical and histopathological features of toxocariasis resembling metastatic nodules in five patients with gastrointestinal cancer. We retrospectively analyzed clinical features of five gastrointestinal cancer patients with liver or lung nodules mimicking metastasis. Serologic tests for parasitic infestations and pathologic examinations were performed. All five patients were males and three patients had gastric cancer and two had colorectal cancer. All the cases of toxocariasis were confirmed serologically. On follow-up imaging, the lesions improved or resolved, suggestive of the phenomenon of visceral larva migrans. In two patients, liver biopsy was performed and showed eosinophilic abscess. Serologic tests and liver or lung biopsy should be performed aggressively to exclude toxocariasis when patients with underlying gastrointestinal cancer present with hepatic or pulmonary nodules associated with eosinophilia, particularly if the patients have a clinical history of raw animal liver ingestion. Curative surgical intervention should not be excluded just because of multiple nodules in the liver or the lungs.

Diagnostic work-up of pulmonary nodules. Management of pulmonary nodules detected with low-dose CT screening; Abklaerung von Lungenrundherden. Management durch Frueherkennungsuntersuchungen detektierter pulmonaler Rundherde

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Wormanns, D. [Evangelische Lungenklinik Berlin, Berlin (Germany)

2016-09-15

Pulmonary nodules are the most frequent pathological finding in low-dose computed tomography (CT) scanning for early detection of lung cancer. Early stages of lung cancer are often manifested as pulmonary nodules; however, the very commonly occurring small nodules are predominantly benign. These benign nodules are responsible for the high percentage of false positive test results in screening studies. Appropriate diagnostic algorithms are necessary to reduce false positive screening results and to improve the specificity of lung cancer screening. Such algorithms are based on some of the basic principles comprehensively described in this article. Firstly, the diameter of nodules allows a differentiation between large (>8 mm) probably malignant and small (<8 mm) probably benign nodules. Secondly, some morphological features of pulmonary nodules in CT can prove their benign nature. Thirdly, growth of small nodules is the best non-invasive predictor of malignancy and is utilized as a trigger for further diagnostic work-up. Non-invasive testing using positron emission tomography (PET) and contrast enhancement as well as invasive diagnostic tests (e.g. various procedures for cytological and histological diagnostics) are briefly described in this article. Different nodule morphology using CT (e.g. solid and semisolid nodules) is associated with different biological behavior and different algorithms for follow-up are required. Currently, no obligatory algorithm is available in German-speaking countries for the management of pulmonary nodules, which reflects the current state of knowledge. The main features of some international and American recommendations are briefly presented in this article from which conclusions for the daily clinical use are derived. (orig.) [German] Lungenrundherde sind die haeufigsten pathologischen Befunde bei Untersuchungen mit der Niedrigdosis-CT zur Lungenkrebsfrueherkennung. Fruehstadien des Lungenkarzinoms manifestieren sich meist als Rundherd

Aquamous cell carcinomas of the lung which presented as numerous polypoid nodules in the tracheobronchial tree: A case report

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Lee, Hyun Gyu; Choi, Yo Won; Yoon, Hyun Jung; Paik, Seung Sam [Hanyang University Hospital, Hanyang University College of Medicine, Seoul (Korea, Republic of)

2017-03-15

We report a case of squamous cell carcinomas of the lung, which presented as numerous polypoid nodules in the tracheobronchial tree. They occurred at two years and 7 months after resection of squamous cell carcinoma, which presented as a lung nodule in the left lower lobe, and at 7 months after resection of tracheal squamous cell carcinoma.

Aquamous cell carcinomas of the lung which presented as numerous polypoid nodules in the tracheobronchial tree: A case report

International Nuclear Information System (INIS)

Lee, Hyun Gyu; Choi, Yo Won; Yoon, Hyun Jung; Paik, Seung Sam

2017-01-01

We report a case of squamous cell carcinomas of the lung, which presented as numerous polypoid nodules in the tracheobronchial tree. They occurred at two years and 7 months after resection of squamous cell carcinoma, which presented as a lung nodule in the left lower lobe, and at 7 months after resection of tracheal squamous cell carcinoma

Usefulness of the CAD System for Detecting Pulmonary Nodule in Real Clinical Practice

International Nuclear Information System (INIS)

Song, Kyoung Doo; Chung, Myung Jin; Kim, Hee Cheol; Lee, Kyung Soo; Jeong, Sun Young

2011-01-01

We wanted to evaluate the usefulness of the computer-aided detection (CAD) system for detecting pulmonary nodules in real clinical practice by using the CT images. Our Institutional Review Board approved our retrospective study with a waiver of informed consent. This study included 166 CT examinations that were performed for the evaluation of pulmonary metastasis in 166 patients with colorectal cancer. All the CT examinations were interpreted by radiologists and they were also evaluated by the CAD system. All the nodules detected by the CAD system were evaluated with regard to whether or not they were true nodules, and they were classified into micro nodules (MN, diameter < 4 mm) and significant nodules (SN, 4 ≤ diameter ≤ 10 mm). The radiologic reports and CAD results were compared. The CAD system helped detect 426 nodules: 115 (27%) of the 426 nodules were classified as true nodules and 35 (30%) of the 115 nodules were SNs, and 83 (72%) of the 115 were not mentioned in the radiologists' reports and three (4%) of the 83 nodules were non-calcified SNs. One of three non-calcified SNs was confirmed as a metastatic nodule. According to the radiologists' reports, 60 true nodules were detected, and 28 of the 60 were not detected by the CAD system. Although the CAD system missed many SNs that are detected by radiologists, it helps detect additional nodules that are missed by the radiologists in real clinical practice. Therefore, the CAD system can be useful to support a radiologist's detection performance

Noninvasive Computed Tomography–based Risk Stratification of Lung Adenocarcinomas in the National Lung Screening Trial

Science.gov (United States)

Maldonado, Fabien; Duan, Fenghai; Raghunath, Sushravya M.; Rajagopalan, Srinivasan; Karwoski, Ronald A.; Garg, Kavita; Greco, Erin; Nath, Hrudaya; Robb, Richard A.; Bartholmai, Brian J.

2015-01-01

Rationale: Screening for lung cancer using low-dose computed tomography (CT) reduces lung cancer mortality. However, in addition to a high rate of benign nodules, lung cancer screening detects a large number of indolent cancers that generally belong to the adenocarcinoma spectrum. Individualized management of screen-detected adenocarcinomas would be facilitated by noninvasive risk stratification. Objectives: To validate that Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel image analysis software, successfully risk stratifies screen-detected lung adenocarcinomas based on clinical disease outcomes. Methods: We identified retrospective 294 eligible patients diagnosed with lung adenocarcinoma spectrum lesions in the low-dose CT arm of the National Lung Screening Trial. The last low-dose CT scan before the diagnosis of lung adenocarcinoma was analyzed using CANARY blinded to clinical data. Based on their parametric CANARY signatures, all the lung adenocarcinoma nodules were risk stratified into three groups. CANARY risk groups were compared using survival analysis for progression-free survival. Measurements and Main Results: A total of 294 patients were included in the analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into the Good, Intermediate, and Poor CANARY risk groups yielded distinct progression-free survival curves (P < 0.0001). This observation was confirmed in the unadjusted and adjusted (age, sex, race, and smoking status) progression-free survival analysis of all stage I cases. Conclusions: CANARY allows the noninvasive risk stratification of lung adenocarcinomas into three groups with distinct post-treatment progression-free survival. Our results suggest that CANARY could ultimately facilitate individualized management of incidentally or screen-detected lung adenocarcinomas. PMID:26052977

Pulmonary cavitary mass containing a mural nodule: differential diagnosis between intracavitary aspergilloma and cavitating lung cancer on contrast-enhanced computed tomography

International Nuclear Information System (INIS)

Park, Y.; Kim, T.S.; Yi, C.A.; Cho, E.Y.; Kim, H.; Choi, Y.S.

2007-01-01

Aim: The objective of this study was to identify whether there were any significant differences in the computed tomography (CT) findings of an intracavitary aspergilloma and a cavitating lung cancer containing a mural nodule. Materials and methods: The CT and histopathological findings of 12 patients (male:female ratio 3:9; aged 51-76 years) with cavitating lung cancer containing a mural nodule and 26 patients (male:female ratio 14:12; aged 29-72 years) with intracavitary aspergilloma were retrospectively reviewed. Results: The mural nodules within cavitating lung cancer were more enhanced (p < 0.001) and showed a nondependent location more frequently (p = 0.012) than those of intracavitary aspergillomas. The cavitary walls were thicker in cavitating lung cancer (mean 5.8 mm thick) than those in intracavitary aspergillomas (mean 2.6 mm thick; p = 0.035). Adjacent bronchiectasis and volume decrease of the involved lobe were observed more frequently in intracavitary aspergillomas than in cavitating lung cancers (p < 0.001 and p = 0.008, respectively). Conclusion: Whether a mural nodule within a cavitary lesion is contrast-enhanced or not is one of the most important features in making a differential diagnosis between an intracavitary aspergilloma and a cavitating lung cancer. Assessment of dependent location of a mural nodule within the cavity and wall thickness of the cavity itself can also be helpful for differentiation

Pulmonary cavitary mass containing a mural nodule: differential diagnosis between intracavitary aspergilloma and cavitating lung cancer on contrast-enhanced computed tomography

Energy Technology Data Exchange (ETDEWEB)

Park, Y. [Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Kim, T.S. [Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of)]. E-mail: tskim.kim@samsung.com; Yi, C.A. [Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Cho, E.Y. [Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Kim, H. [Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Choi, Y.S. [Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of)

2007-03-15

Aim: The objective of this study was to identify whether there were any significant differences in the computed tomography (CT) findings of an intracavitary aspergilloma and a cavitating lung cancer containing a mural nodule. Materials and methods: The CT and histopathological findings of 12 patients (male:female ratio 3:9; aged 51-76 years) with cavitating lung cancer containing a mural nodule and 26 patients (male:female ratio 14:12; aged 29-72 years) with intracavitary aspergilloma were retrospectively reviewed. Results: The mural nodules within cavitating lung cancer were more enhanced (p < 0.001) and showed a nondependent location more frequently (p = 0.012) than those of intracavitary aspergillomas. The cavitary walls were thicker in cavitating lung cancer (mean 5.8 mm thick) than those in intracavitary aspergillomas (mean 2.6 mm thick; p = 0.035). Adjacent bronchiectasis and volume decrease of the involved lobe were observed more frequently in intracavitary aspergillomas than in cavitating lung cancers (p < 0.001 and p = 0.008, respectively). Conclusion: Whether a mural nodule within a cavitary lesion is contrast-enhanced or not is one of the most important features in making a differential diagnosis between an intracavitary aspergilloma and a cavitating lung cancer. Assessment of dependent location of a mural nodule within the cavity and wall thickness of the cavity itself can also be helpful for differentiation.

Discriminative Localization in CNNs for Weakly-Supervised Segmentation of Pulmonary Nodules.

Science.gov (United States)

Feng, Xinyang; Yang, Jie; Laine, Andrew F; Angelini, Elsa D

2017-09-01

Automated detection and segmentation of pulmonary nodules on lung computed tomography (CT) scans can facilitate early lung cancer diagnosis. Existing supervised approaches for automated nodule segmentation on CT scans require voxel-based annotations for training, which are labor- and time-consuming to obtain. In this work, we propose a weakly-supervised method that generates accurate voxel-level nodule segmentation trained with image-level labels only. By adapting a convolutional neural network (CNN) trained for image classification, our proposed method learns discriminative regions from the activation maps of convolution units at different scales, and identifies the true nodule location with a novel candidate-screening framework. Experimental results on the public LIDC-IDRI dataset demonstrate that, our weakly-supervised nodule segmentation framework achieves competitive performance compared to a fully-supervised CNN-based segmentation method.

Convolution neural-network-based detection of lung structures

Science.gov (United States)

Hasegawa, Akira; Lo, Shih-Chung B.; Freedman, Matthew T.; Mun, Seong K.

1994-05-01

Chest radiography is one of the most primary and widely used techniques in diagnostic imaging. Nowadays with the advent of digital radiology, the digital medical image processing techniques for digital chest radiographs have attracted considerable attention, and several studies on the computer-aided diagnosis (CADx) as well as on the conventional image processing techniques for chest radiographs have been reported. In the automatic diagnostic process for chest radiographs, it is important to outline the areas of the lungs, the heart, and the diaphragm. This is because the original chest radiograph is composed of important anatomic structures and, without knowing exact positions of the organs, the automatic diagnosis may result in unexpected detections. The automatic extraction of an anatomical structure from digital chest radiographs can be a useful tool for (1) the evaluation of heart size, (2) automatic detection of interstitial lung diseases, (3) automatic detection of lung nodules, and (4) data compression, etc. Based on the clearly defined boundaries of heart area, rib spaces, rib positions, and rib cage extracted, one should be able to use this information to facilitate the tasks of the CADx on chest radiographs. In this paper, we present an automatic scheme for the detection of lung field from chest radiographs by using a shift-invariant convolution neural network. A novel algorithm for smoothing boundaries of lungs is also presented.

The usefulness of F-18 FDG PET to discriminate between malignant and benign nodule in idiopathic pulmonary fibrosis

International Nuclear Information System (INIS)

Kim, Bom Sahn; Kang, Won Jun; Lee, Dong Soo; Chung, June Key; Lee, Myung Chul

2006-01-01

Incidence of lung cancer in patients with idiopathic pulmonary fibrosis (IPF) is known to be higher than that in general population. However, it is difficult to discriminate pulmonary nodule in patients with IPF, because underlying IPF can be expressed as lung nodules. We evaluated the diagnostic performance of FDG PET in discriminating lung nodule in patients with IPF. We retrospectively reviewed 28 lung nodules in 16 subjects (age; 67.53 ± 9.83, M:F = 14:2). Two patients had previous history of malignant cancer (small cell lung cancer and subglottic cancer). The diagnostic criteria on chest CT were size, morphology and serial changes of size. FDG PET was visually interpreted, and maximal SUV was calculated for quantitative analysis. From 28 nodules, 18 nodules were interpreted as benign nodules, 10 nodules as malignant nodules by histopathology or follow-up chest CT. The sensitivity and specificity of FDG PET were 100% and 94.4%, while those of CT were 70.0% and 44.4% respectively. Malignant nodule was higher maxSUV than that of benign lung nodules (7.68 ± 3.96 vs 1.22 ± 0.65, p < 0.001). Inflammatory lesion in underlying IPF was significantly lower masSUV than that of malignant nodules (1.80 ± 0.43, p < 0.001). The size of malignant and benign nodule were 23.95 ± 10.15 mm and 10.83 ± 5.23 mm p < 0.01) FDG PET showed superior diagnostic performance to chest CT in differentiating lung nodules in patients with underlying IPF. FDG PET could be used to evaluate suspicious malignant nodule detected by chest in patients with IPF

The usefulness of F-18 FDG PET to discriminate between malignant and benign nodule in idiopathic pulmonary fibrosis

Energy Technology Data Exchange (ETDEWEB)

Kim, Bom Sahn; Kang, Won Jun; Lee, Dong Soo; Chung, June Key; Lee, Myung Chul [Seoul National University College of Medicine, Seoul (Korea, Republic of)

2006-06-15

Incidence of lung cancer in patients with idiopathic pulmonary fibrosis (IPF) is known to be higher than that in general population. However, it is difficult to discriminate pulmonary nodule in patients with IPF, because underlying IPF can be expressed as lung nodules. We evaluated the diagnostic performance of FDG PET in discriminating lung nodule in patients with IPF. We retrospectively reviewed 28 lung nodules in 16 subjects (age; 67.53 {+-} 9.83, M:F = 14:2). Two patients had previous history of malignant cancer (small cell lung cancer and subglottic cancer). The diagnostic criteria on chest CT were size, morphology and serial changes of size. FDG PET was visually interpreted, and maximal SUV was calculated for quantitative analysis. From 28 nodules, 18 nodules were interpreted as benign nodules, 10 nodules as malignant nodules by histopathology or follow-up chest CT. The sensitivity and specificity of FDG PET were 100% and 94.4%, while those of CT were 70.0% and 44.4% respectively. Malignant nodule was higher maxSUV than that of benign lung nodules (7.68 {+-} 3.96 vs 1.22 {+-} 0.65, p < 0.001). Inflammatory lesion in underlying IPF was significantly lower masSUV than that of malignant nodules (1.80 {+-} 0.43, p < 0.001). The size of malignant and benign nodule were 23.95 {+-} 10.15 mm and 10.83 {+-} 5.23 mm p < 0.01) FDG PET showed superior diagnostic performance to chest CT in differentiating lung nodules in patients with underlying IPF. FDG PET could be used to evaluate suspicious malignant nodule detected by chest in patients with IPF.

A approach for differential diagnosis of primary lung cancer and breast cancer relapse presenting as a solitary pulmonary nodule in patients after breast surgery

International Nuclear Information System (INIS)

Fujita, Takashi; Iwata, Hiroharu; Yatabe, Yasushi

2009-01-01

The differential diagnosis of primary lung cancer from metastatic breast cancer is crucial in patients presenting with a solitary pulmonary nodule after breast surgery. However definitive diagnosis of these nodules is often difficult due to similar radiological and pathological features in primary lung and metastatic breast cancer nodules. We assessed the feasibility of our diagnostic approach for these nodules by morphopathological and immunohistochemical examination (thyroid transcription factor-1 (TTF-1), surfactant pro-protein B (SPPB), estrogen receptor (ER), mammaglobin-1 (MGB1)), and estimated the frequency of primary lung cancer occurrence in 23 breast cancer patients. Biopsy specimens were obtained using CT-guided needle biopsy (NB) and transbronchial lung biopsy (TBLB) in 21 patients (91.3%). Surgical resection was performed for diagnosis and treatment in two patients. Differential diagnosis was obtained by morphopathological methods alone in 17 patients (73.9%, primary lung cancer: 6 cases, metastatic breast cancer: 11 cases) and by immunohistochemical examination in the remaining 6 (26.1%, primary lung cancer: 1 case, metastatic breast cancer: 5 cases). Our results show the clinical feasibility of our approach to the differential diagnosis of breast cancer relapse and primary lung cancer presenting as a solitary nodule in breast cancer patients. (author)

Variability in CT lung-nodule volumetry: Effects of dose reduction and reconstruction methods.

Science.gov (United States)

Young, Stefano; Kim, Hyun J Grace; Ko, Moe Moe; Ko, War War; Flores, Carlos; McNitt-Gray, Michael F

2015-05-01

Measuring the size of nodules on chest CT is important for lung cancer staging and measuring therapy response. 3D volumetry has been proposed as a more robust alternative to 1D and 2D sizing methods. There have also been substantial advances in methods to reduce radiation dose in CT. The purpose of this work was to investigate the effect of dose reduction and reconstruction methods on variability in 3D lung-nodule volumetry. Reduced-dose CT scans were simulated by applying a noise-addition tool to the raw (sinogram) data from clinically indicated patient scans acquired on a multidetector-row CT scanner (Definition Flash, Siemens Healthcare). Scans were simulated at 25%, 10%, and 3% of the dose of their clinical protocol (CTDIvol of 20.9 mGy), corresponding to CTDIvol values of 5.2, 2.1, and 0.6 mGy. Simulated reduced-dose data were reconstructed with both conventional filtered backprojection (B45 kernel) and iterative reconstruction methods (SAFIRE: I44 strength 3 and I50 strength 3). Three lab technologist readers contoured "measurable" nodules in 33 patients under each of the different acquisition/reconstruction conditions in a blinded study design. Of the 33 measurable nodules, 17 were used to estimate repeatability with their clinical reference protocol, as well as interdose and inter-reconstruction-method reproducibilities. The authors compared the resulting distributions of proportional differences across dose and reconstruction methods by analyzing their means, standard deviations (SDs), and t-test and F-test results. The clinical-dose repeatability experiment yielded a mean proportional difference of 1.1% and SD of 5.5%. The interdose reproducibility experiments gave mean differences ranging from -5.6% to -1.7% and SDs ranging from 6.3% to 9.9%. The inter-reconstruction-method reproducibility experiments gave mean differences of 2.0% (I44 strength 3) and -0.3% (I50 strength 3), and SDs were identical at 7.3%. For the subset of repeatability cases, inter

Nodule detection in digital chest radiography: Effect of anatomical noise

International Nuclear Information System (INIS)

Baath, M.; Haakansson, M.; Boerjesson, S.; Hoeschen, C.; Tischenko, O.; Kheddache, S.; Vikgren, J.; Maansson, L. G.

2005-01-01

The image background resulting from imaged anatomy can be divided into those components that are meaningful to the observers, in the sense that they are recognised as separate structures, and those that are not. These latter components (referred to as anatomical noise) can be removed using a method developed within the RADIUS group. The aim of the present study was to investigate whether the removal of the anatomical noise results in images where lung nodules with lower contrast can be detected. A receiver operating characteristic (ROC) study was therefore conducted using two types of images: clinical chest images and chest images in which the anatomical noise had been removed. Simulated designer nodules with a full-width-at-fifth-maximum of 10 mm but with varying contrast were added to the images. The contrast needed to obtain an area under the ROC curve of 0.80, C0.8, was used as a measure of detectability (a low value of C0.8 represents a high delectability). Five regions of the chest X ray were investigated and it was found that in all regions the removal of anatomical noise led to images with lower C0.8 than the original images. On average, C0.8 was 20% higher in the original images, ranging from 7% (the lateral pulmonary regions) to 41% (the upper mediastinal regions). (authors)

Systematic Error in Lung Nodule Volumetry : Effect of Iterative Reconstruction Versus Filtered Back Projection at Different CT Parameters

NARCIS (Netherlands)

Willemink, Martin J.; Leiner, Tim; Budde, Ricardo P. J.; de Kort, Freek P. L.; Vliegenthart, Rozemarijn; van Ooijen, Peter M. A.; Oudkerk, Matthijs; de Jong, Pim A.

2012-01-01

OBJECTIVE. Iterative reconstruction potentially can reduce radiation dose compared with filtered back projection (FBP) for chest CT. This is especially important for repeated CT scanning, as is the case in patients with indeterminate lung nodules. It is currently unknown whether absolute nodule

68Ga-DOTATATE PET/CT imaging of indeterminate pulmonary nodules and lung cancer.

Directory of Open Access Journals (Sweden)

Ronald Walker

Full Text Available 18F-FDG PET/CT is widely used to evaluate indeterminate pulmonary nodules (IPNs. False positive results occur, especially from active granulomatous nodules. A PET-based imaging agent with superior specificity to 18F-FDG for IPNs, is badly needed, especially in areas of endemic granulomatous nodules. Somatostatin receptors (SSTR are expressed in many malignant cells including small cell and non-small cell lung cancers (NSCLCs. 68Ga-DOTATATE, a positron emitter labeled somatostatin analog, combined with PET/CT imaging, may improve the diagnosis of IPNs over 18F-FDG by reducing false positives. Our study purpose was to test this hypothesis in our region with high endemic granulomatous IPNs.We prospectively performed 68Ga-DOTATATE PET/CT and 18F-FDG PET/CT scans in the same 30 patients with newly diagnosed, treatment-naïve lung cancer (N = 14 or IPNs (N = 15 and one metastatic nodule. 68Ga-DOTATATE SUVmax levels at or above 1.5 were considered likely malignant. We analyzed the scan results, correlating with ultimate diagnosis via biopsy or 2-year chest CT follow-up. We also correlated 68Ga-DOTATATE uptake with immunohistochemical (IHC staining for SSTR subtype 2A (SSTR2A in pathological specimens.We analyzed 31 lesions in 30 individuals, with 14 (45% being non-neuroendocrine lung cancers and 1 (3% being metastatic disease. McNemar's result comparing the two radiopharmaceuticals (p = 0.65 indicates that their accuracy of diagnosis in this indication are equivalent. 68Ga-DOTATATE was more specific (94% compared to 81% and less sensitive 73% compared to 93% than 18F-FDG. 68Ga-DOTATATE uptake correlated with SSTR2A expression in tumor stroma determined by immunohistochemical (IHC staining in 5 of 9 (55% NSCLCs.68Ga-DOTATATE and 18F-FDG PET/CT had equivalent accuracy in the diagnosis of non-neuroendocrine lung cancer and 68Ga-DOTATATE was more specific than 18F-FDG for the diagnosis of IPNs. IHC staining for SSTR2A receptor expression correlated with

Roles of computed tomography and [18F]fluorodeoxyglucose-positron emission tomography/computed tomography in the characterization of multiple solitary solid lung nodules

OpenAIRE

Travaini, LL; Trifirò, G; Vigna, PD; Veronesi, G; De Pas, TM; Spaggiari, L; Paganelli, G; Bellomi, M

2012-01-01

The purpose of this study is to compare the performance of multidetector computed tomography (CT) and positron emission tomography/CT (PET/CT) with [18F]fluorodeoxyglucose in the diagnosis of multiple solitary lung nodules in 14 consecutive patients with suspicious lung cancer. CT and PET/CT findings were reviewed by a radiologist and nuclear medicine physician, respectively, blinded to the pathological diagnoses of lung cancer, considering nodule size, shape, and location (CT) and maximum st...

Prognostic importance of pleural attachment status measured by pretreatment CT images in patients with stage IA lung adenocarcinoma: measurement of the ratio of the interface between nodule and neighboring pleura to nodule surface area

Science.gov (United States)

Kawata, Y.; Niki, N.; Kusumoto, M.; Ohmatsu, H.; Aokage, K.; Ishii, G.; Matsumoto, Y.; Tsuchida, T.; Eguchi, K.; Kaneko, M.

2018-02-01

Screening for lung cancer with low-dose computed tomography (CT) has led to increased recognition of small lung cancers and is expected to increase the rate of detection of early-stage lung cancer. Major concerns in the implementation of the CT screening of large populations include determining the appropriate management of pulmonary nodules found on a scan. The identification of patients with early-stage lung cancer who have a higher risk for relapse and who require more aggressive surveillance has been a target of intense investigation. This study was performed to investigate whether image features of internal intensity in combination with surrounding structure characteristics are associated with an increased risk of relapse in patients with stage IA lung adenocarcinoma. We focused on pleural attachment status which is one of morphological characteristics associated with prognosis in three-dimensional thoracic CT images.

VATS intraoperative tattooing to facilitate solitary pulmonary nodule resection

Directory of Open Access Journals (Sweden)

Boutros Cherif

2008-03-01

Full Text Available Abstract Introduction Video-assisted thoracic surgery (VATS has become routine and widely accepted for the removal of solitary pulmonary nodules of unknown etiology. Thoracosopic techniques continue to evolve with better instruments, robotic applications, and increased patient acceptance and awareness. Several techniques have been described to localize peripheral pulmonary nodules, including pre-operative CT-guided tattooing with methylene blue, CT scan guided spiral/hook wire placement, and transthoracic ultrasound. As pulmonary surgeons well know, the lung and visceral pleura may appear featureless on top of a pulmonary nodule. Case description This paper presents a rapid, direct and inexpensive approach to peripheral lung lesion resection by marking the lung parenchyma on top of the nodule using direct methylene blue injection. Methods In two patients with peripherally located lung nodules (n = 3 scheduled for VATS, we used direct methylene blue injection for intraoperative localization of the pulmonary nodule. Our technique was the following: After finger palpation of the lung, a spinal 25 gauge needle was inserted through an existing port and 0.1 ml of methylene blue was used to tattoo the pleura perpendicular to the localized nodule. The methylene blue tattoo immediately marks the lung surface over the nodule. The surgeon avoids repeated finger palpation, while lining up stapler, graspers and camera, because of the visible tattoo. Our technique eliminates regrasping and repalpating the lung once again to identify a non marked lesion. Results Three lung nodules were resected in two patients. Once each lesion was palpated it was marked, and the area was resected with security of accurate localization. All lung nodules were resected in totality with normal lung parenchymal margins. Our technique added about one minute to the operative time. The two patients were discharged home on the second postoperative day, with no morbidity. Conclusion

Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR).

Science.gov (United States)

Chen, Baiyu; Barnhart, Huiman; Richard, Samuel; Robins, Marthony; Colsher, James; Samei, Ehsan

2013-11-01

Volume quantifications of lung nodules with multidetector computed tomography (CT) images provide useful information for monitoring nodule developments. The accuracy and precision of the volume quantification, however, can be impacted by imaging and reconstruction parameters. This study aimed to investigate the impact of iterative reconstruction algorithms on the accuracy and precision of volume quantification with dose and slice thickness as additional variables. Repeated CT images were acquired from an anthropomorphic chest phantom with synthetic nodules (9.5 and 4.8 mm) at six dose levels, and reconstructed with three reconstruction algorithms [filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASiR), and model based iterative reconstruction (MBIR)] into three slice thicknesses. The nodule volumes were measured with two clinical software (A: Lung VCAR, B: iNtuition), and analyzed for accuracy and precision. Precision was found to be generally comparable between FBP and iterative reconstruction with no statistically significant difference noted for different dose levels, slice thickness, and segmentation software. Accuracy was found to be more variable. For large nodules, the accuracy was significantly different between ASiR and FBP for all slice thicknesses with both software, and significantly different between MBIR and FBP for 0.625 mm slice thickness with Software A and for all slice thicknesses with Software B. For small nodules, the accuracy was more similar between FBP and iterative reconstruction, with the exception of ASIR vs FBP at 1.25 mm with Software A and MBIR vs FBP at 0.625 mm with Software A. The systematic difference between the accuracy of FBP and iterative reconstructions highlights the importance of extending current segmentation software to accommodate the image characteristics of iterative reconstructions. In addition, a calibration process may help reduce the dependency of accuracy on reconstruction algorithms

Noninvasive Characterization of Indeterminate Pulmonary Nodules Detected on Chest High-Resolution Computed Tomography

Science.gov (United States)

2016-10-01

Current Status ANALYZE Nodule Segmentation CANARY -PLUS ANALYZE AVW Surface Extraction In-house monolithic software ADMesh Surface Repair MATLAB...a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE October 2016 2. REPORT TYPE Annual 3...we are currently developing a multivariate radiologic prediction model (radiologic model) using a population of benign and malignant lung nodules

Soft computing approach to 3D lung nodule segmentation in CT.

Science.gov (United States)

Badura, P; Pietka, E

2014-10-01

This paper presents a novel, multilevel approach to the segmentation of various types of pulmonary nodules in computed tomography studies. It is based on two branches of computational intelligence: the fuzzy connectedness (FC) and the evolutionary computation. First, the image and auxiliary data are prepared for the 3D FC analysis during the first stage of an algorithm - the masks generation. Its main goal is to process some specific types of nodules connected to the pleura or vessels. It consists of some basic image processing operations as well as dedicated routines for the specific cases of nodules. The evolutionary computation is performed on the image and seed points in order to shorten the FC analysis and improve its accuracy. After the FC application, the remaining vessels are removed during the postprocessing stage. The method has been validated using the first dataset of studies acquired and described by the Lung Image Database Consortium (LIDC) and by its latest release - the LIDC-IDRI (Image Database Resource Initiative) database. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development of a multivariate model to predict the likelihood of carcinoma in patients with indeterminate peripheral lung nodules after a nondiagnostic bronchoscopic evaluation.

Science.gov (United States)

Voss, Jesse S; Iqbal, Seher; Jenkins, Sarah M; Henry, Michael R; Clayton, Amy C; Jett, James R; Kipp, Benjamin R; Halling, Kevin C; Maldonado, Fabien

2014-01-01

Studies have shown that fluorescence in situ hybridization (FISH) testing increases lung cancer detection on cytology specimens in peripheral nodules. The goal of this study was to determine whether a predictive model using clinical features and routine cytology with FISH results could predict lung malignancy after a nondiagnostic bronchoscopic evaluation. Patients with an indeterminate peripheral lung nodule that had a nondiagnostic bronchoscopic evaluation were included in this study (N = 220). FISH was performed on residual bronchial brushing cytology specimens diagnosed as negative (n = 195), atypical (n = 16), or suspicious (n = 9). FISH results included hypertetrasomy (n = 30) and negative (n = 190). Primary study end points included lung cancer status along with time to diagnosis of lung cancer or date of last clinical follow-up. Hazard ratios (HRs) were calculated using Cox proportional hazards regression model analyses, and P values < .05 were considered statistically significant. The mean age of the 220 patients was 66.7 years (range, 35-91), and most (58%) were men. Most patients (79%) were current or former smokers with a mean pack year history of 43.2 years (median, 40; range, 1-200). After multivariate analysis, hypertetrasomy FISH (HR = 2.96, P < .001), pack years (HR = 1.03 per pack year up to 50, P = .001), age (HR = 1.04 per year, P = .02), atypical or suspicious cytology (HR = 2.02, P = .04), and nodule spiculation (HR = 2.36, P = .003) were independent predictors of malignancy over time and were used to create a prediction model (C-statistic = 0.78). These results suggest that this multivariate model including test results and clinical features may be useful following a nondiagnostic bronchoscopic examination. © 2013.

Additional value of integrated PET-CT in the detection and characterization of lung metastases: correlation with CT alone and PET alone

International Nuclear Information System (INIS)

Wever, W. de; Meylaerts, L.; Verschakelen, J.A.; Ceuninck, L. de; Stroobants, S.

2007-01-01

The purpose was evaluating retrospectively the additional value of integrated positron emission tomography (PET) and computed tomography (CT) in the detection of pulmonary metastases in comparison with CT and PET alone. Fifty-six lung nodules, divided into three groups according their size, detected in 24 consecutive patients with a known primary tumor were retrospectively evaluated with integrated PET-CT, CT and PET. The nature of these nodules was determined by either histopathology or a follow-up of at least 6 months. The CT and PET images of the integrated PET-CT were evaluated separately by a radiologist and a nuclear medicine physician, the integrated PET-CT images were evaluated by a chest radiologist and nuclear medicine physician in consensus. The investigators were asked to search lung nodules and to determine whether these nodules were metastases or not. Sensitivity and accuracy for CT, PET and integrated PET-CT for characterization of all pulmonary nodules were, respectively: 100%, 90%, 100% and 57%, 55%, 55%. There was no significant difference in the characterization of pulmonary nodules between integrated PET-CT and CT alone (P=1.000) and PET alone (P=0.1306). An accurate evaluation is only possible for lesions larger than 1 cm. (orig.)

Direct detection of radicals in intact soybean nodules

DEFF Research Database (Denmark)

Mathieu, C; Moreau, S; Frendo, P

1998-01-01

Electron paramagnetic resonance spectroscopy has been employed to examine the nature of the metal ions and radicals present in intact root nodules of soybean plants grown in the absence of nitrate. The spectra obtained from nodules of different ages using this non-invasive technique show dramatic...... differences, suggesting that there are both qualitative and quantitative changes in the metal ion and radical species present. A major component of the spectra obtained from young nodules is assigned to a complex (Lb-NO) of nitric oxide (NO.) with the heme protein leghemoglobin (Lb). This Lb-NO species, which...... has not been previously detected in intact root nodules of plants grown in the absence of nitrate, is thought to be formed by reaction of nitric oxide with iron(II) leghemoglobin. The nitric oxide may be generated from arginine via a nitric oxide synthase-like activity present in the nodules...

Multi-Institutional Evaluation of Digital Tomosynthesis, Dual-Energy Radiography, and Conventional Chest Radiography for the Detection and Management of Pulmonary Nodules.

Science.gov (United States)

Dobbins, James T; McAdams, H Page; Sabol, John M; Chakraborty, Dev P; Kazerooni, Ella A; Reddy, Gautham P; Vikgren, Jenny; Båth, Magnus

2017-01-01

Purpose To conduct a multi-institutional, multireader study to compare the performance of digital tomosynthesis, dual-energy (DE) imaging, and conventional chest radiography for pulmonary nodule detection and management. Materials and Methods In this binational, institutional review board-approved, HIPAA-compliant prospective study, 158 subjects (43 subjects with normal findings) were enrolled at four institutions. Informed consent was obtained prior to enrollment. Subjects underwent chest computed tomography (CT) and imaging with conventional chest radiography (posteroanterior and lateral), DE imaging, and tomosynthesis with a flat-panel imaging device. Three experienced thoracic radiologists identified true locations of nodules (n = 516, 3-20-mm diameters) with CT and recommended case management by using Fleischner Society guidelines. Five other radiologists marked nodules and indicated case management by using images from conventional chest radiography, conventional chest radiography plus DE imaging, tomosynthesis, and tomosynthesis plus DE imaging. Sensitivity, specificity, and overall accuracy were measured by using the free-response receiver operating characteristic method and the receiver operating characteristic method for nodule detection and case management, respectively. Results were further analyzed according to nodule diameter categories (3-4 mm, >4 mm to 6 mm, >6 mm to 8 mm, and >8 mm to 20 mm). Results Maximum lesion localization fraction was higher for tomosynthesis than for conventional chest radiography in all nodule size categories (3.55-fold for all nodules, P chest radiography for all nodules (1.49-fold, P chest radiography, as given by the area under the receiver operating characteristic curve (1.23-fold, P chest radiography or tomosynthesis. Conclusion Tomosynthesis outperformed conventional chest radiography for lung nodule detection and determination of case management; DE imaging did not show significant differences over conventional chest

Nodule detection in digital chest radiography: Part of image background acting as pure noise

International Nuclear Information System (INIS)

Baath, M.; Haakansson, M.; Boerjesson, S.; Kheddache, S.; Grahn, A.; Bochud, F. O.; Verdun, F. R.; Maansson, L. G.

2005-01-01

There are several factors that influence the radiologist's ability to detect a specific structure/lesion in a radiograph. Three factors that are commonly known to be of major importance are the signal itself, the system noise and the projected anatomy. The aim of this study was to determine to what extent the image background acts as pure noise for the detection of subtle lung nodules in five different regions of the chest. A receiver operating characteristic (ROC) study with five observers was conducted on two different sets of images, clinical chest X-ray images and images with a similar power spectrum as the clinical images but with a random phase spectrum, resulting in an image background containing pure noise. Simulated designer nodules with a full-width-at-fifth-maximum of 10 mm but with varying contrasts were added to the images. As a measure of the part of the image background that acts as pure noise, the ratio between the contrast needed to obtain an area under the ROC curve of 0.80 in the clinical images to that in the random-phase images was used. The ratio ranged from 0.40 (in the lateral pulmonary regions) to 0.83 (in the hilar regions) indicating that there was a large difference between different regions regarding to what extent the image background acted as pure noise; and that in the hilar regions the image background almost completely acted as pure noise for the detection of 10 mm nodules. (authors)

Quantitative assessment of the influence of anatomic noise on the detection of subtle lung nodule in digital chest radiography using fractal-feature distance

International Nuclear Information System (INIS)

Imai, Kuniharu; Ikeda, Mitsuru; Enchi, Yukihiro; Niimi, Takanaga

2008-01-01

Purpose: To confirm whether or not the influence of anatomic noise on the detection of nodules in digital chest radiography can be evaluated by the fractal-feature distance. Materials and methods: We used the square images with and without a simulated nodule which were generated in our previous observer performance study; the simulated nodule was located on the upper margin of a rib, the inside of a rib, the lower margin of a rib, or the central region between two adjoining ribs. For the square chest images, fractal analysis was conducted using the virtual volume method. The fractal-feature distances between the considered and the reference images were calculated using the pseudo-fractal dimension and complexity, and the square images without the simulated nodule were employed as the reference images. We compared the fractal-feature distances with the observer's confidence level regarding the presence of a nodule in plain chest radiograph. Results: For all square chest images, the relationships between the length of the square boxes and the mean of the virtual volumes were linear on a log-log scale. For all types of the simulated nodules, the fractal-feature distance was the highest for the simulated nodules located on the central region between two adjoining ribs and was the lowest for those located in the inside of a rib. The fractal-feature distance showed a linear relation to an observer's confidence level. Conclusion: The fractal-feature distance would be useful for evaluating the influence of anatomic noise on the detection of nodules in digital chest radiography

Toward clinically usable CAD for lung cancer screening with computed tomography

International Nuclear Information System (INIS)

Brown, Matthew S.; Lo, Pechin; Goldin, Jonathan G.; Barnoy, Eran; Kim, Grace Hyun J.; McNitt-Gray, Michael F.; Aberle, Denise R.

2014-01-01

The purpose of this study was to define clinically appropriate, computer-aided lung nodule detection (CAD) requirements and protocols based on recent screening trials. In the following paper, we describe a CAD evaluation methodology based on a publically available, annotated computed tomography (CT) image data set, and demonstrate the evaluation of a new CAD system with the functionality and performance required for adoption in clinical practice. A new automated lung nodule detection and measurement system was developed that incorporates intensity thresholding, a Euclidean Distance Transformation, and segmentation based on watersheds. System performance was evaluated against the Lung Imaging Database Consortium (LIDC) CT reference data set. The test set comprised thin-section CT scans from 108 LIDC subjects. The median (±IQR) sensitivity per subject was 100 (±37.5) for nodules ≥ 4 mm and 100 (±8.33) for nodules ≥ 8 mm. The corresponding false positive rates were 0 (±2.0) and 0 (±1.0), respectively. The concordance correlation coefficient between the CAD nodule diameter and the LIDC reference was 0.91, and for volume it was 0.90. The new CAD system shows high nodule sensitivity with a low false positive rate. Automated volume measurements have strong agreement with the reference standard. Thus, it provides comprehensive, clinically-usable lung nodule detection and assessment functionality. (orig.)

Toward clinically usable CAD for lung cancer screening with computed tomography

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Brown, Matthew S.; Lo, Pechin; Goldin, Jonathan G.; Barnoy, Eran; Kim, Grace Hyun J.; McNitt-Gray, Michael F.; Aberle, Denise R. [David Geffen School of Medicine at UCLA, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, Los Angeles, CA (United States)

2014-11-15

The purpose of this study was to define clinically appropriate, computer-aided lung nodule detection (CAD) requirements and protocols based on recent screening trials. In the following paper, we describe a CAD evaluation methodology based on a publically available, annotated computed tomography (CT) image data set, and demonstrate the evaluation of a new CAD system with the functionality and performance required for adoption in clinical practice. A new automated lung nodule detection and measurement system was developed that incorporates intensity thresholding, a Euclidean Distance Transformation, and segmentation based on watersheds. System performance was evaluated against the Lung Imaging Database Consortium (LIDC) CT reference data set. The test set comprised thin-section CT scans from 108 LIDC subjects. The median (±IQR) sensitivity per subject was 100 (±37.5) for nodules ≥ 4 mm and 100 (±8.33) for nodules ≥ 8 mm. The corresponding false positive rates were 0 (±2.0) and 0 (±1.0), respectively. The concordance correlation coefficient between the CAD nodule diameter and the LIDC reference was 0.91, and for volume it was 0.90. The new CAD system shows high nodule sensitivity with a low false positive rate. Automated volume measurements have strong agreement with the reference standard. Thus, it provides comprehensive, clinically-usable lung nodule detection and assessment functionality. (orig.)

Computer-aided classification of lung nodules on computed tomography images via deep learning technique

Directory of Open Access Journals (Sweden)

Hua KL

2015-08-01

Full Text Available Kai-Lung Hua,1 Che-Hao Hsu,1 Shintami Chusnul Hidayati,1 Wen-Huang Cheng,2 Yu-Jen Chen3 1Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, 2Research Center for Information Technology Innovation, Academia Sinica, 3Department of Radiation Oncology, MacKay Memorial Hospital, Taipei, Taiwan Abstract: Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD scheme requires several image processing and pattern recognition steps to accomplish a quantitative tumor differentiation result. In such an ad hoc image analysis pipeline, every step depends heavily on the performance of the previous step. Accordingly, tuning of classification performance in a conventional CAD scheme is very complicated and arduous. Deep learning techniques, on the other hand, have the intrinsic advantage of an automatic exploitation feature and tuning of performance in a seamless fashion. In this study, we attempted to simplify the image analysis pipeline of conventional CAD with deep learning techniques. Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography images. Two baseline methods with feature computing steps were implemented for comparison. The experimental results suggest that deep learning methods could achieve better discriminative results and hold promise in the CAD application domain. Keywords: nodule classification, deep learning, deep belief network, convolutional neural network

Diagnostic feasibility and safety of CT-guided core biopsy for lung nodules less than or equal to 8 mm. A single-institution experience

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Chang, Ying-Yueh [Taipei Veterans General Hospital, Department of Radiology, Taipei (China); Chen, Chun-Ku [Taipei Veterans General Hospital, Department of Radiology, Taipei (China); National Yang-Ming University, School of Medicine, Taipei (China); National Yang-Ming University, Institute of Clinical Medicine, Taipei (China); Yeh, Yi-Chen [National Yang-Ming University, School of Medicine, Taipei (China); Taipei Veterans General Hospital, Department of Pathology and Laboratory Medicine, Taipei (China); Wu, Mei-Han [Taipei Veterans General Hospital, Department of Radiology, Taipei (China); National Yang-Ming University, School of Medicine, Taipei (China)

2018-02-15

This retrospective study evaluated the diagnostic yield and safety of CT-guided core biopsy of pulmonary nodules ≤8 mm. We determined the diagnostic yield and safety profile of CT-guided lung biopsies for 125 pulmonary nodules ≤8 mm. Pathological diagnoses were made by a combination of histopathological examination and imprint cytology. Results were compared with biopsy results for 134 pulmonary nodules >8 and ≤10 mm. Final diagnoses were established in 94 nodules ≤8 mm. The sensitivity, specificity and diagnostic accuracy of CT-guided core biopsy for nodules ≤8 mm were 87.1 % (61/70 nodules), 100 % (24/24) and 90.4 % (85/94), respectively. Diagnostic failure rates were comparable for nodules ≤8 mm and nodules >8 mm and ≤10 mm (9/94, 9.6 % and 7/111, 6.3 %, respectively, P=0.385). The rate of tube thoracostomy for nodules ≤8 mm was comparable to that for nodules >8 and ≤10 mm (1.6 % vs. 0.7 %, P=0.611). Nodules ≤6 mm had a higher non-diagnostic result rate of 15.4 % (6/39) than did nodules >8 and ≤10 mm (3.7 %, 5/134, P=0.017). CT-guided pulmonary biopsy is feasible for lung nodules ≤8 mm, especially those >6 mm, and has an acceptable diagnostic yield and safety profile. (orig.)

Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR)

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Chen, Baiyu [Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 and Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, North Carolina 27705 (United States); Barnhart, Huiman [Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina 27705 (United States); Richard, Samuel [Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, North Carolina 27705 and Department of Radiology, Duke University, Durham, North Carolina 27705 (United States); Robins, Marthony [Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 (United States); Colsher, James [Department of Radiology, Duke University, Durham, North Carolina 27705 (United States); Samei, Ehsan [Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 (United States); Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, North Carolina 27705 (United States); Department of Radiology, Duke University, Durham, North Carolina 27705 (United States); Department of Physics, Department of Biomedical Engineering, and Department of Electronic and Computer Engineering, Duke University, Durham, North Carolina 27705 (United States)

2013-11-15

Purpose: Volume quantifications of lung nodules with multidetector computed tomography (CT) images provide useful information for monitoring nodule developments. The accuracy and precision of the volume quantification, however, can be impacted by imaging and reconstruction parameters. This study aimed to investigate the impact of iterative reconstruction algorithms on the accuracy and precision of volume quantification with dose and slice thickness as additional variables.Methods: Repeated CT images were acquired from an anthropomorphic chest phantom with synthetic nodules (9.5 and 4.8 mm) at six dose levels, and reconstructed with three reconstruction algorithms [filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASiR), and model based iterative reconstruction (MBIR)] into three slice thicknesses. The nodule volumes were measured with two clinical software (A: Lung VCAR, B: iNtuition), and analyzed for accuracy and precision.Results: Precision was found to be generally comparable between FBP and iterative reconstruction with no statistically significant difference noted for different dose levels, slice thickness, and segmentation software. Accuracy was found to be more variable. For large nodules, the accuracy was significantly different between ASiR and FBP for all slice thicknesses with both software, and significantly different between MBIR and FBP for 0.625 mm slice thickness with Software A and for all slice thicknesses with Software B. For small nodules, the accuracy was more similar between FBP and iterative reconstruction, with the exception of ASIR vs FBP at 1.25 mm with Software A and MBIR vs FBP at 0.625 mm with Software A.Conclusions: The systematic difference between the accuracy of FBP and iterative reconstructions highlights the importance of extending current segmentation software to accommodate the image characteristics of iterative reconstructions. In addition, a calibration process may help reduce the dependency of

Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR)

International Nuclear Information System (INIS)

Chen, Baiyu; Barnhart, Huiman; Richard, Samuel; Robins, Marthony; Colsher, James; Samei, Ehsan

2013-01-01

Purpose: Volume quantifications of lung nodules with multidetector computed tomography (CT) images provide useful information for monitoring nodule developments. The accuracy and precision of the volume quantification, however, can be impacted by imaging and reconstruction parameters. This study aimed to investigate the impact of iterative reconstruction algorithms on the accuracy and precision of volume quantification with dose and slice thickness as additional variables.Methods: Repeated CT images were acquired from an anthropomorphic chest phantom with synthetic nodules (9.5 and 4.8 mm) at six dose levels, and reconstructed with three reconstruction algorithms [filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASiR), and model based iterative reconstruction (MBIR)] into three slice thicknesses. The nodule volumes were measured with two clinical software (A: Lung VCAR, B: iNtuition), and analyzed for accuracy and precision.Results: Precision was found to be generally comparable between FBP and iterative reconstruction with no statistically significant difference noted for different dose levels, slice thickness, and segmentation software. Accuracy was found to be more variable. For large nodules, the accuracy was significantly different between ASiR and FBP for all slice thicknesses with both software, and significantly different between MBIR and FBP for 0.625 mm slice thickness with Software A and for all slice thicknesses with Software B. For small nodules, the accuracy was more similar between FBP and iterative reconstruction, with the exception of ASIR vs FBP at 1.25 mm with Software A and MBIR vs FBP at 0.625 mm with Software A.Conclusions: The systematic difference between the accuracy of FBP and iterative reconstructions highlights the importance of extending current segmentation software to accommodate the image characteristics of iterative reconstructions. In addition, a calibration process may help reduce the dependency of

Subcentimeter Pulmonary Nodules Detected in Patients with Sarcoma

Directory of Open Access Journals (Sweden)

Michelle S. Ginsberg

2000-01-01

Full Text Available Background. Subcentimeter pulmonary nodules are being detected with increasing frequency in patients with sarcoma due to the greater use of chest CT, the advent of helical (spiral CT scanning and multidetector scanners, and the attendant decrease in image section thickness.Assessing the clinical significance of these pulmonary nodules is of particular importance in sarcoma patients, due to the frequent occurrence of pulmonary metastasis from sarcomas.

An Innocent Appearing Subcutaneous Nodule Diagnoses a Small Cell Lung Cancer in a Never-Smoker Female

Directory of Open Access Journals (Sweden)

Nupur Sinha

2014-01-01

Full Text Available Lung cancer among never-smokers is recognized as the 7th most common cause of cancer death globally. Adenocarcinoma is the most commonly reported histology. Small cell lung cancer (SCLC has the strongest association with smoking and is rarely reported in never-smokers. Although lung cancer in never-smokers is more common in women, the overall incidence of SCLC in female never-smokers still remains low. Soft tissue metastases from any cancer are rare with an overall prevalence of 1.8%. Soft tissue metastases from lung primary are uncommon, mostly from adenocarcinoma, and portend a poor prognosis. Cutaneous metastases from SCLC are exceptionally rare with reported incidence of 0.3% to 0.8%. We believe ours is the first reported case of SCLC presenting as subcutaneous nodule, in a never-smoker, otherwise asymptomatic female. The diagnosis of SCLC was made incidentally by the excisional biopsy of the subcutaneous nodule. Subsequent CT chest and PET scan revealed a hypermetabolic right lower lobe spiculated lung mass with adrenal and liver involvement. Platinum and etoposide chemotherapy with prophylactic cranial irradiation was initiated for advanced SCLC, and she required further irinotecan and taxol for subsequent pancreatic and adrenal metastases. With continued deterioration, she died approximately 36 months from diagnosis, while under hospice care.

The calcified lung nodule: What does it mean?

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Khan Ali

2010-01-01

Full Text Available The aim of this review is to present a pictorial essay emphasizing the various patterns of calcification in pulmonary nodules (PN to aid diagnosis and to discuss the differential diagnosis and the pathogenesis where it is known. The imaging evaluation of PN is based on clinical history, size, distribution and the gross appearance of the nodule as well as feasibility of obtaining a tissue diagnosis. Imaging is instrumental in the management of PN and one should strive not only to identify small malignant tumors with high survival rates but to spare patients with benign PN from undergoing unnecessary surgery. The review emphasizes how to achieve these goals. One of the most reliable imaging features of a benign lesion is a benign pattern of calcification and periodic follow-up with computed tomography showing no growth for 2 years. Calcification in PN is generally considered as a pointer toward a possible benign disease. However, as we show here, calcification in PN as a criterion to determine benign nature is fallacious and can be misleading. The differential considerations of a calcified lesion include calcified granuloma, hamartoma, carcinoid, osteosarcoma, chondrosarcoma and lung metastases or a primary bronchogenic carcinoma among others. We describe and illustrate different patterns of calcification as seen in PN on imaging.

Computer-aided detection systems to improve lung cancer early diagnosis: state-of-the-art and challenges

International Nuclear Information System (INIS)

Traverso, A; Lopez Torres, E; Cerello, P; Fantacci, M E

2017-01-01

Lung cancer is one of the most lethal types of cancer, because its early diagnosis is not good enough. In fact, the detection of pulmonary nodule, potential lung cancers, in Computed Tomography scans is a very challenging and time-consuming task for radiologists. To support radiologists, researchers have developed Computer-Aided Diagnosis (CAD) systems for the automated detection of pulmonary nodules in chest Computed Tomography scans. Despite the high level of technological developments and the proved benefits on the overall detection performance, the usage of Computer-Aided Diagnosis in clinical practice is far from being a common procedure. In this paper we investigate the causes underlying this discrepancy and present a solution to tackle it: the M5L WEB- and Cloud-based on-demand Computer-Aided Diagnosis. In addition, we prove how the combination of traditional imaging processing techniques with state-of-art advanced classification algorithms allows to build a system whose performance could be much larger than any Computer-Aided Diagnosis developed so far. This outcome opens the possibility to use the CAD as clinical decision support for radiologists. (paper)

Computer-aided detection systems to improve lung cancer early diagnosis: state-of-the-art and challenges

Science.gov (United States)

Traverso, A.; Lopez Torres, E.; Fantacci, M. E.; Cerello, P.

2017-05-01

Lung cancer is one of the most lethal types of cancer, because its early diagnosis is not good enough. In fact, the detection of pulmonary nodule, potential lung cancers, in Computed Tomography scans is a very challenging and time-consuming task for radiologists. To support radiologists, researchers have developed Computer-Aided Diagnosis (CAD) systems for the automated detection of pulmonary nodules in chest Computed Tomography scans. Despite the high level of technological developments and the proved benefits on the overall detection performance, the usage of Computer-Aided Diagnosis in clinical practice is far from being a common procedure. In this paper we investigate the causes underlying this discrepancy and present a solution to tackle it: the M5L WEB- and Cloud-based on-demand Computer-Aided Diagnosis. In addition, we prove how the combination of traditional imaging processing techniques with state-of-art advanced classification algorithms allows to build a system whose performance could be much larger than any Computer-Aided Diagnosis developed so far. This outcome opens the possibility to use the CAD as clinical decision support for radiologists.

Correlation coefficient based supervised locally linear embedding for pulmonary nodule recognition.

Science.gov (United States)

Wu, Panpan; Xia, Kewen; Yu, Hengyong

2016-11-01

Dimensionality reduction techniques are developed to suppress the negative effects of high dimensional feature space of lung CT images on classification performance in computer aided detection (CAD) systems for pulmonary nodule detection. An improved supervised locally linear embedding (SLLE) algorithm is proposed based on the concept of correlation coefficient. The Spearman's rank correlation coefficient is introduced to adjust the distance metric in the SLLE algorithm to ensure that more suitable neighborhood points could be identified, and thus to enhance the discriminating power of embedded data. The proposed Spearman's rank correlation coefficient based SLLE (SC(2)SLLE) is implemented and validated in our pilot CAD system using a clinical dataset collected from the publicly available lung image database consortium and image database resource initiative (LICD-IDRI). Particularly, a representative CAD system for solitary pulmonary nodule detection is designed and implemented. After a sequential medical image processing steps, 64 nodules and 140 non-nodules are extracted, and 34 representative features are calculated. The SC(2)SLLE, as well as SLLE and LLE algorithm, are applied to reduce the dimensionality. Several quantitative measurements are also used to evaluate and compare the performances. Using a 5-fold cross-validation methodology, the proposed algorithm achieves 87.65% accuracy, 79.23% sensitivity, 91.43% specificity, and 8.57% false positive rate, on average. Experimental results indicate that the proposed algorithm outperforms the original locally linear embedding and SLLE coupled with the support vector machine (SVM) classifier. Based on the preliminary results from a limited number of nodules in our dataset, this study demonstrates the great potential to improve the performance of a CAD system for nodule detection using the proposed SC(2)SLLE. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Low dose CT in early lung cancer diagnosis: prevalence data

International Nuclear Information System (INIS)

Cardinale, Luciano; Cortese, Giancarlo; Ferraris, Fabrizio; Perotto, Fabio; Fava, Cesare; Borasio, Piero; Dogliotti, Luigi; Novello, Silvia; Scagliotti, Giorgio

2005-01-01

Purpose. Lung cancer has a high mortality rate and its prognosis largely depends on early detection. We report the prevalence data of the study on early detection of lung cancer with low-dose spiral CT underway at our hospital. Materials and methods. Since the beginning of 2001, 519 asymptomatic volunteers have undergone annual blood tests, sputum tests, urinalyses and low-dose spiral CT. The inclusion criteria were age (55 years old), a history of cigarette smoking and a negative history for previous neoplastic disease. The diagnostic workup varied depending on the size and CT features of the nodules detected. Results. At baseline, the CT scan detected nodules> 5 mm in 22% of subjects; the nodules were single in 42 and multiple in 71. In 53% of cases the findings were completely negative, while in 122 (23.4%) nodules with a diameter [it

Additional effects of FDG-PET to thin-section CT for the differential diagnosis of lung nodules. A Japanese multicenter clinical study

International Nuclear Information System (INIS)

Kubota, Kazuo; Murakami, Koji; Inoue, Tomio; Saga, Tsuneo; Shiomi, Susumu

2011-01-01

This study was a controlled multicenter clinical study on patients with peripheral lung nodules to verify the improvement in the diagnostic ability of fluorodeoxyglucose-positron emission tomography (FDG-PET) when used in combination with thin-section CT (TS-CT). Patients with peripheral lung nodules (long maximal diameter: 10-30 mm) detected using CT were examined using TS-CT and FDG-PET for the differential diagnosis of benign or malignant lesions. The primary endpoint was the specificity of the results using a combination of TS-CT and FDG-PET, compared with the results for TS-CT alone. Images were interpreted by investigators at each institution. Blind readings were also performed by an independent image interpretation committee. The gold standard was a pathological diagnosis determined using a surgical or biopsy specimen obtained after PET; and the patients in whom a pathological diagnosis could not be obtained were diagnosed based on a follow-up TS-CT performed more than 6 months later. Adverse reactions to FDG were also evaluated. The blind reading results for 82 lesions in 81 subjects eligible for analysis among the 90 subjects included in the study showed a specificity of 91.2% (31/34) (95% confidence interval (CI): 76.3-98.1) for TS-CT + PET, compared with a specificity of 67.6% (23/34) (95% CI: 49.5-82.6) for TS-CT alone. The specificity was significantly improved by the addition of the PET findings (p<0.05). The sensitivity improved from 89.6% (43/48) for TS-CT to 91.7% (44/48) for TS-CT + PET; the addition of PET increased the level of confidence in the diagnosis, but the difference was not significant. The results reported by the institutional investigators were not significantly different. No serious adverse reactions occurred, although two of the 90 subjects exhibited mild adverse reactions. The addition of FDG-PET to TS-CT for the differential diagnosis of benign or malignant peripheral lung nodules resulted in a significant improvement in

CT detection of daughter nodules in hepatocellular carcinoma after lipiodol infusion via the hepatic artery

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Ohishi, Hajime; Ohgami, Syoichi; Katsuragi, Masami

1985-02-01

The detectability of daughter nodules in 80 hepatocellular carcinomas was compared between CT assisted by Lipiodol Ultra Fluid (Lipiodol) infused via the hepatic artery and IHA (Infusion hepatic angiography). Lipiodol infused via the hepatic artery was selectively accumulated in the tumor vessels and the tumors and small daughter nodules appeared as markedly high density areas by CT. 18 cases in which the daughter nodules were detected were identified only by CT. Furthermore, in 38 cases CT demonstrated superior detectability of the daughthr nodules than IHA. In 15 cases the daughter nodules were newly detected in areas other than the invaded area where the primary tumor existed. This method is very effective in the diagnosis of daughter nodules of hepatocellular carcinoma. (author).

Automatic segmentation of tumor-laden lung volumes from the LIDC database

Science.gov (United States)

O'Dell, Walter G.

2012-03-01

The segmentation of the lung parenchyma is often a critical pre-processing step prior to application of computer-aided detection of lung nodules. Segmentation of the lung volume can dramatically decrease computation time and reduce the number of false positive detections by excluding from consideration extra-pulmonary tissue. However, while many algorithms are capable of adequately segmenting the healthy lung, none have been demonstrated to work reliably well on tumor-laden lungs. Of particular challenge is to preserve tumorous masses attached to the chest wall, mediastinum or major vessels. In this role, lung volume segmentation comprises an important computational step that can adversely affect the performance of the overall CAD algorithm. An automated lung volume segmentation algorithm has been developed with the goals to maximally exclude extra-pulmonary tissue while retaining all true nodules. The algorithm comprises a series of tasks including intensity thresholding, 2-D and 3-D morphological operations, 2-D and 3-D floodfilling, and snake-based clipping of nodules attached to the chest wall. It features the ability to (1) exclude trachea and bowels, (2) snip large attached nodules using snakes, (3) snip small attached nodules using dilation, (4) preserve large masses fully internal to lung volume, (5) account for basal aspects of the lung where in a 2-D slice the lower sections appear to be disconnected from main lung, and (6) achieve separation of the right and left hemi-lungs. The algorithm was developed and trained to on the first 100 datasets of the LIDC image database.

Volumetric measurements of pulmonary nodules at multi-row detector CT: in vivo reproducibility

International Nuclear Information System (INIS)

Wormanns, Dag; Marheine, Anke; Beyer, Florian; Heindel, Walter; Diederich, Stefan; Kohl, Gerhard; Klotz, Ernst

2004-01-01

The aim of this study was to assess the in vivo measurement precision of a software tool for volumetric analysis of pulmonary nodules from two consecutive low-dose multi-row detector CT scans. A total of 151 pulmonary nodules (diameter 2.2-20.5 mm, mean diameter 7.4±4.5 mm) in ten subjects with pulmonary metastases were examined with low-dose four-detector-row CT (120 kVp, 20 mAs (effective), collimation 4 x 1 mm, normalized pitch 1.75, slice thickness 1.25 mm, reconstruction increment 0.8 mm; Somatom VolumeZoom, Siemens). Two consecutive low-dose scans covering the whole lung were performed within 10 min. Nodule volume was determined for all pulmonary nodules visually detected in both scans using the volumetry tool included in the Siemens LungCare software. The 95% limits of agreement between nodule volume measurements on different scans were calculated using the Bland and Altman method for assessing measurement agreement. Intra- and interobserver agreement of volume measurement were determined using repetitive measurements of 50 randomly selected nodules at the same scan by the same and different observers. Taking into account all 151 nodules, 95% limits of agreement were -20.4 to 21.9% (standard error 1.5%); they were -19.3 to 20.4% (standard error 1.7%) for 105 nodules <10 mm. Limits of agreement were -3.9 to 5.7% for intraobserver and -5.5 to 6.6% for interobserver agreement. Precision of in vivo volumetric analysis of nodules with an automatic volumetry software tool was sufficiently high to allow for detection of clinically relevant growth in small pulmonary nodules. (orig.)

Pulmonary nodules in workers exposed to urban stressor

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Sancini, A. [University of Rome ' Sapienza' , Department of Occupational Medicine, Viale Regina Elena 336, 00161 Rome (Italy); Fioravanti, M. [University of Rome ' Sapienza' , Department of Psychiatric Science and Psychological Medicine, Piazzale Aldo Moro 5, 00185 Rome (Italy); Ciarrocca, M.; Palermo, P.; Fiaschetti, M.; Schifano, M.P. [University of Rome ' Sapienza' , Department of Occupational Medicine, Viale Regina Elena 336, 00161 Rome (Italy); Tomei, G. [University of Rome ' Sapienza' , Department of Psychiatric Science and Psychological Medicine, Piazzale Aldo Moro 5, 00185 Rome (Italy); Tomei, F., E-mail: francesco.tomei@uniroma1.it [University of Rome ' Sapienza' , Department of Occupational Medicine, Viale Regina Elena 336, 00161 Rome (Italy)

2010-07-15

By multilayer spiral low-dose computed tomography (LD-CT) of the chest this study assesses the early detection of lung lesions on a sample of 100 traffic policemen of a big Italian city professionally exposed to urban pollutants and 100 controls non-occupationally exposed to urban pollutants matched by sex, age, length of service and cigarette smoking habit. Exposure to urban pollutants in traffic policemen was characterized using the annual average concentrations of PM{sub 10}, NO{sub 2} and benzene in the period 1998-2008 measured by fixed monitoring stations located in different areas of the city. A significant and increasing number of suspicious lung nodules with diameters between 5 and 10 mm was observed: in traffic policemen (including smokers and non-smokers) vs. controls (including smokers and non-smokers); in total smokers (including traffic policemen and controls) vs. total non-smokers (traffic policemen and controls); in smoker traffic policemen vs. smoker controls and vs. non-smoker traffic policemen; in non-smoker traffic policemen vs. non-smoker controls. The RR of finding cases with at least one lung nodule with diameters between 5 and 10 mm in traffic policemen (including smokers and non-smokers) compared to controls (including smokers and non-smokers) is 1.94 (CI 1.13-3.31); in total smokers vs. non-smokers the RR is 1.96 (CI 1.20-3.19). The comparison between the interaction exposure and smoking shows an increase in smoker traffic policemen than in smoker controls (RR=2.14; CI 1.02-4.52). The RR for smoker traffic policemen was higher than in non-smoker traffic policemen (RR=2.09; CI 1.19-3.66). The results of our study show that: (1) while smoker workers have a higher risk for developing solid suspicious lung nodules, the simple routinely exposure to urban pollutants is unable to produce the same kind of increased risk; (2) the interaction of smoking and exposure to urban pollutants greatly increases the risk for the development of solid

Pulmonary nodules in workers exposed to urban stressor

International Nuclear Information System (INIS)

Sancini, A.; Fioravanti, M.; Ciarrocca, M.; Palermo, P.; Fiaschetti, M.; Schifano, M.P.; Tomei, G.; Tomei, F.

2010-01-01

By multilayer spiral low-dose computed tomography (LD-CT) of the chest this study assesses the early detection of lung lesions on a sample of 100 traffic policemen of a big Italian city professionally exposed to urban pollutants and 100 controls non-occupationally exposed to urban pollutants matched by sex, age, length of service and cigarette smoking habit. Exposure to urban pollutants in traffic policemen was characterized using the annual average concentrations of PM 10 , NO 2 and benzene in the period 1998-2008 measured by fixed monitoring stations located in different areas of the city. A significant and increasing number of suspicious lung nodules with diameters between 5 and 10 mm was observed: in traffic policemen (including smokers and non-smokers) vs. controls (including smokers and non-smokers); in total smokers (including traffic policemen and controls) vs. total non-smokers (traffic policemen and controls); in smoker traffic policemen vs. smoker controls and vs. non-smoker traffic policemen; in non-smoker traffic policemen vs. non-smoker controls. The RR of finding cases with at least one lung nodule with diameters between 5 and 10 mm in traffic policemen (including smokers and non-smokers) compared to controls (including smokers and non-smokers) is 1.94 (CI 1.13-3.31); in total smokers vs. non-smokers the RR is 1.96 (CI 1.20-3.19). The comparison between the interaction exposure and smoking shows an increase in smoker traffic policemen than in smoker controls (RR=2.14; CI 1.02-4.52). The RR for smoker traffic policemen was higher than in non-smoker traffic policemen (RR=2.09; CI 1.19-3.66). The results of our study show that: (1) while smoker workers have a higher risk for developing solid suspicious lung nodules, the simple routinely exposure to urban pollutants is unable to produce the same kind of increased risk; (2) the interaction of smoking and exposure to urban pollutants greatly increases the risk for the development of solid suspicious lung

Comparison of sensitivity and reading time for the use of computer-aided detection (CAD) of pulmonary nodules at MDCT as concurrent or second reader

International Nuclear Information System (INIS)

Beyer, F.; Zierott, L.; Juergens, K.U.; Heindel, W.; Fallenberg, E.M.; Stoeckel, J.; Wormanns, D.

2007-01-01

The purpose of this study was to compare sensitivity for detection of pulmonary nodules in MDCT scans and reading time of radiologists when using CAD as the second reader (SR) respectively concurrent reader (CR). Four radiologists analyzed 50 chest MDCT scans chosen from clinical routine two times and marked all detected pulmonary nodules: first with CAD as CR (display of CAD results immediately in the reading session) and later (median 14 weeks) with CAD as SR (display of CAD markers after completion of first reading without CAD). A Siemens LungCAD prototype was used. Sensitivities for detection of nodules and reading times were recorded. Sensitivity of reading with CAD as SR was significantly higher than reading without CAD (p < 0.001) and CAD as CR (p < 0.001). For nodule size of 1.75 mm or above no significant sensitivity difference between CAD as CR and reading without CAD was observed; e.g., for nodules above 4 mm sensitivity was 68% without CAD, 68% with CAD as CR (p 0.45) and 75% with CAD as SR (p < 0.001). Reading time was significantly shorter for CR (274 s) compared to reading without CAD (294 s; p = 0.04) and SR (337 s; p < 0.001). In our study CAD could either speed up reading of chest CT cases for pulmonary nodules without relevant loss of sensitivity when used as CR, or it increased sensitivity at the cost of longer reading times when used as SR. (orig.)

Observer training for computer-aided detection of pulmonary nodules in chest radiography

NARCIS (Netherlands)

de Boo, Diederick W.; van Hoorn, François; van Schuppen, Joost; Schijf, Laura; Scheerder, Maeke J.; Freling, Nicole J.; Mets, Onno; Weber, Michael; Schaefer-Prokop, Cornelia M.

2012-01-01

To assess whether short-term feedback helps readers to increase their performance using computer-aided detection (CAD) for nodule detection in chest radiography. The 140 CXRs (56 with a solitary CT-proven nodules and 84 negative controls) were divided into four subsets of 35; each were read in a

Detection of pulmonary metastatic nodules: usefulness of low-dose multidetector CT in comparison with chest radiograph

International Nuclear Information System (INIS)

Kim, Ki Nam; Lee, Ki Nam; Yang, Doo Kyung; Lee, Soo Keol

2006-01-01

We wanted to evaluate the usefulness of low-dose multidetector CT for the detection and follow-up of pulmonary metastatic nodules in patients suffering with malignancy. We retrospectively reviewed the conventional chest radiographs and low-dose multidetector CT (low-dose CT) scans of 81 patients who had been under the diagnosis of malignancy. We reviewed the detection of pulmonary nodules and we counted the number of nodules detected by each method. The nodules were confirmed by surgical operation and by the radiologic criteria. The accuracy, sensitivity, specificity and positive and negative predictive values of each method for detecting metastatic nodules were compared with χ 2 tests. Low-dose CT depicted more nodules than did chest radiograph, and the indeterminate nodules seen on chest radiograph may be clearly benign on low-dose CT (eg. calcified granulomas or bony lesions). The accuracy of low-dose CT (75.3%) was significantly higher than that of chest radiograph (49.4%) for the detection for metastatic nodules (ρ < 0.05). Low-dose CT may provide better information than does chest radiograph for diagnosing pulmonary metastasis

Lung cancer screening with low-dose helical CT in Korea: experiences at the Samsung Medical Center.

Science.gov (United States)

Chong, Semin; Lee, Kyung Soo; Chung, Myung Jin; Kim, Tae Sung; Kim, Hojoong; Kwon, O Jung; Choi, Yoon-Ho; Rhee, Chong H

2005-06-01

To determine overall detection rates of lung cancer by low-dose CT (LDCT) screening and to compare histopathologic and imaging differences of detected cancers between high- and low-risk groups, this study included 6,406 asymptomatic Korean adults with >or=45 yr of age who underwent LDCT for lung cancer screening. All were classified into high- (>or=20 pack-year smoking; 3,353) and low-risk (3,053; <20 pack-yr smoking and non-smokers) groups. We compared CT findings of detected cancers and detection rates between high- and low-risk. At initial CT, 35% (2,255 of 6,406) had at least one or more non-calcified nodule. Lung cancer detection rates were 0.36% (23 of 6,406). Twenty-one non-small cell lung cancers appeared as solid (n=14) or ground-glass opacity (GGO) (n=7) nodules. Cancer likelihood was higher in GGO nodules than in solid nodules (p<0.01). Fifteen of 23 cancers occurred in high-risk group and 8 in low-risk group (p=0.215). Therefore, LDCT screening help detect early stage of lung cancer in asymptomatic Korean population with detection rate of 0.36% on a population basis and may be useful for discovering early lung cancer in low-risk group as well as in high-risk group.

Data-driven decision support for radiologists: re-using the National Lung Screening Trial dataset for pulmonary nodule management.

Science.gov (United States)

Morrison, James J; Hostetter, Jason; Wang, Kenneth; Siegel, Eliot L

2015-02-01

Real-time mining of large research trial datasets enables development of case-based clinical decision support tools. Several applicable research datasets exist including the National Lung Screening Trial (NLST), a dataset unparalleled in size and scope for studying population-based lung cancer screening. Using these data, a clinical decision support tool was developed which matches patient demographics and lung nodule characteristics to a cohort of similar patients. The NLST dataset was converted into Structured Query Language (SQL) tables hosted on a web server, and a web-based JavaScript application was developed which performs real-time queries. JavaScript is used for both the server-side and client-side language, allowing for rapid development of a robust client interface and server-side data layer. Real-time data mining of user-specified patient cohorts achieved a rapid return of cohort cancer statistics and lung nodule distribution information. This system demonstrates the potential of individualized real-time data mining using large high-quality clinical trial datasets to drive evidence-based clinical decision-making.

Computer-assisted solid lung nodule 3D volumetry on CT : influence of scan mode and iterative reconstruction: a CT phantom study

NARCIS (Netherlands)

Coenen, Adriaan; Honda, Osamu; van der Jagt, Eric J.; Tomiyama, Noriyuki

2013-01-01

To evaluate the effect of high-resolution scan mode and iterative reconstruction on lung nodule 3D volumetry. Solid nodules with various sizes (5, 8, 10 and 12 mm) were placed inside a chest phantom. CT images were obtained with various tube currents, scan modes (conventional mode, high-resolution

Techniques for virtual lung nodule insertion: volumetric and morphometric comparison of projection-based and image-based methods for quantitative CT

Science.gov (United States)

Robins, Marthony; Solomon, Justin; Sahbaee, Pooyan; Sedlmair, Martin; Choudhury, Kingshuk Roy; Pezeshk, Aria; Sahiner, Berkman; Samei, Ehsan

2017-09-01

Virtual nodule insertion paves the way towards the development of standardized databases of hybrid CT images with known lesions. The purpose of this study was to assess three methods (an established and two newly developed techniques) for inserting virtual lung nodules into CT images. Assessment was done by comparing virtual nodule volume and shape to the CT-derived volume and shape of synthetic nodules. 24 synthetic nodules (three sizes, four morphologies, two repeats) were physically inserted into the lung cavity of an anthropomorphic chest phantom (KYOTO KAGAKU). The phantom was imaged with and without nodules on a commercial CT scanner (SOMATOM Definition Flash, Siemens) using a standard thoracic CT protocol at two dose levels (1.4 and 22 mGy CTDIvol). Raw projection data were saved and reconstructed with filtered back-projection and sinogram affirmed iterative reconstruction (SAFIRE, strength 5) at 0.6 mm slice thickness. Corresponding 3D idealized, virtual nodule models were co-registered with the CT images to determine each nodule’s location and orientation. Virtual nodules were voxelized, partial volume corrected, and inserted into nodule-free CT data (accounting for system imaging physics) using two methods: projection-based Technique A, and image-based Technique B. Also a third Technique C based on cropping a region of interest from the acquired image of the real nodule and blending it into the nodule-free image was tested. Nodule volumes were measured using a commercial segmentation tool (iNtuition, TeraRecon, Inc.) and deformation was assessed using the Hausdorff distance. Nodule volumes and deformations were compared between the idealized, CT-derived and virtual nodules using a linear mixed effects regression model which utilized the mean, standard deviation, and coefficient of variation (Mea{{n}RHD} , ST{{D}RHD} and C{{V}RHD}{) }~ of the regional Hausdorff distance. Overall, there was a close concordance between the volumes of the CT-derived and

Data-Driven Decision Support for Radiologists: Re-using the National Lung Screening Trial Dataset for Pulmonary Nodule Management

OpenAIRE

Morrison, James J.; Hostetter, Jason; Wang, Kenneth; Siegel, Eliot L.

2014-01-01

Real-time mining of large research trial datasets enables development of case-based clinical decision support tools. Several applicable research datasets exist including the National Lung Screening Trial (NLST), a dataset unparalleled in size and scope for studying population-based lung cancer screening. Using these data, a clinical decision support tool was developed which matches patient demographics and lung nodule characteristics to a cohort of similar patients. The NLST dataset was conve...

Significance and management of computed tomography detected pulmonary nodules: a report from the National Wilms Tumor Study Group

International Nuclear Information System (INIS)

Meisel, Jay A.; Guthrie, Katherine A.; Breslow, Norman E.; Donaldson, Sarah S.; Green, Daniel M.

1999-01-01

Purpose: To define the optimal treatment for children with Wilms tumor who have pulmonary nodules identified on chest computed tomography (CT) scan, but have a negative chest radiograph, we evaluated the outcome of all such patients randomized or followed on National Wilms Tumor Study (NWTS)-3 and -4. Patients and Methods: We estimated the event-free and overall survival percentages of 53 patients with favorable histology tumors and pulmonary densities identified only by CT scan (CT-only) who were treated as Stage IV with intensive doxorubicin-containing chemotherapy and whole-lung irradiation, and compared these to the event-free and overall survival percentages of 37 CT-only patients who were treated less aggressively based on the extent of locoregional disease with 2 or 3 drugs, and without whole-lung irradiation. Results: The 4-year event-free and overall survival percentages of the 53 patients with CT-only nodules and favorable histology Wilms tumor who were treated as Stage IV were 89% and 91%, respectively. The 4-year event-free and overall survival percentages for the 37 patients with CT-only nodules and favorable histology who were treated according to the extent of locoregional disease were 80% and 85%, respectively. The differences observed between the 2 groups were not statistically significant. Among the patients who received whole-lung irradiation, there were fewer pulmonary relapses, but more deaths attributable to lung toxicity. Conclusions: The current data raise the possibility that children with Wilms tumor and CT-only pulmonary nodules who receive whole lung irradiation have fewer pulmonary relapses, but a greater number of deaths due to treatment toxicity. The role of whole lung irradiation in the treatment of this group of patients cannot be definitively determined based on the present data. Prolonged follow-up of this group of patients is necessary to accurately estimate the frequency of late, treatment-related mortality

Small nodule detectability evaluation using a generalized scan-statistic model

International Nuclear Information System (INIS)

Popescu, Lucretiu M; Lewitt, Robert M

2006-01-01

In this paper is investigated the use of the scan statistic for evaluating the detectability of small nodules in medical images. The scan-statistic method is often used in applications in which random fields must be searched for abnormal local features. Several results of the detection with localization theory are reviewed and a generalization is presented using the noise nodule distribution obtained by scanning arbitrary areas. One benefit of the noise nodule model is that it enables determination of the scan-statistic distribution by using only a few image samples in a way suitable both for simulation and experimental setups. Also, based on the noise nodule model, the case of multiple targets per image is addressed and an image abnormality test using the likelihood ratio and an alternative test using multiple decision thresholds are derived. The results obtained reveal that in the case of low contrast nodules or multiple nodules the usual test strategy based on a single decision threshold underperforms compared with the alternative tests. That is a consequence of the fact that not only the contrast or the size, but also the number of suspicious nodules is a clue indicating the image abnormality. In the case of the likelihood ratio test, the multiple clues are unified in a single decision variable. Other tests that process multiple clues differently do not necessarily produce a unique ROC curve, as shown in examples using a test involving two decision thresholds. We present examples with two-dimensional time-of-flight (TOF) and non-TOF PET image sets analysed using the scan statistic for different search areas, as well as the fixed position observer

Advances in intelligent diagnosis methods for pulmonary ground-glass opacity nodules.

Science.gov (United States)

Yang, Jing; Wang, Hailin; Geng, Chen; Dai, Yakang; Ji, Jiansong

2018-02-07

Pulmonary nodule is one of the important lesions of lung cancer, mainly divided into two categories of solid nodules and ground glass nodules. The improvement of diagnosis of lung cancer has significant clinical significance, which could be realized by machine learning techniques. At present, there have been a lot of researches focusing on solid nodules. But the research on ground glass nodules started late, and lacked research results. This paper summarizes the research progress of the method of intelligent diagnosis for pulmonary nodules since 2014. It is described in details from four aspects: nodular signs, data analysis methods, prediction models and system evaluation. This paper aims to provide the research material for researchers of the clinical diagnosis and intelligent analysis of lung cancer, and further improve the precision of pulmonary ground glass nodule diagnosis.

Role of digital tomosynthesis and dual energy subtraction digital radiography in detecting pulmonary nodules

Energy Technology Data Exchange (ETDEWEB)

Kumar, Sarvana G. [Department of Radiodiagnosis and Imaging, Postgraduate Institute of Medical Education and Research (PGIMER), Sector 12, Chandigarh 160012 (India); Garg, Mandeep Kumar, E-mail: gargmandeep01@gmail.com [Department of Radiodiagnosis and Imaging, Postgraduate Institute of Medical Education and Research (PGIMER), Sector 12, Chandigarh 160012 (India); Khandelwal, Niranjan; Gupta, Pankaj [Department of Radiodiagnosis and Imaging, Postgraduate Institute of Medical Education and Research (PGIMER), Sector 12, Chandigarh 160012 (India); Gupta, Dheeraj; Aggarwal, Ashutosh Nath [Department of Pulmonary Medicine, Postgraduate Institute of Medical Education and Research (PGIMER), Sector 12, Chandigarh 160012 (India); Bansal, Subash Chand [Department of Radiodiagnosis and Imaging, Postgraduate Institute of Medical Education and Research (PGIMER), Sector 12, Chandigarh 160012 (India)

2015-07-15

Highlights: • Accuracy of digital tomosynthesis for nodule detection is substantially higher. • Improvement in diagnostic accuracy is most pronounced for nodules <10 mm. • There is five times increase in radiation dose compared to DR. - Abstract: Objective: Digital tomosynthesis (DT) and dual-energy subtraction digital radiography (DES-DR) are known to perform better than conventional radiography in the detection of pulmonary nodules. Yet the comparative diagnostic performances of DT, DES-DR and digital radiography (DR) is not known. The present study compares the diagnostic performances of DT, DES-DR and DR in detecting pulmonary nodules. Subjects and methods: The institutional Review Board approved the study and informed written consent was obtained. Fifty-five patients (30 with pulmonary nodules, 25 with non-nodular focal chest pathology) were included in the study. DT and DES-DR were performed within14 days of MDCT. Composite images acquired at high kVp as part of DES-DR were used as DR images. Images were analyzed for presence of nodules and calcification in nodules. Interpretations were assigned confidence levels from 1 to 5 according to Five-Point rating scale. Areas under the receiver operating characteristic curves were compared using Z test. Results: A total of 110 (88 non-calcified, 22 calcified) nodules were identified on MDCT. For detection of nodules, DR showed cumulative sensitivity and specificity of 25.45% and 67.97%, respectively. DT showed a cumulative sensitivity and specificity of 60.9% and 85.07%, respectively. The performance was significantly better than DR (p < 0.003). DES-DR showed sensitivity and specificity of 27.75% and 82.64%, not statistically different from those of DR (p—0.92). In detection of calcification, there was no statistically significant difference between DT, DES-DR and DR. Conclusions: DT performs significantly better than DES-DR and DR at the cost of moderate increase in radiation dose.

Spatial frequency characteristics at image decision-point locations for observers with different radiological backgrounds in lung nodule detection

Science.gov (United States)

Pietrzyk, Mariusz W.; Manning, David J.; Dix, Alan; Donovan, Tim

2009-02-01

Aim: The goal of the study is to determine the spatial frequency characteristics at locations in the image of overt and covert observers' decisions and find out if there are any similarities in different observers' groups: the same radiological experience group or the same accuracy scored level. Background: The radiological task is described as a visual searching decision making procedure involving visual perception and cognitive processing. Humans perceive the world through a number of spatial frequency channels, each sensitive to visual information carried by different spatial frequency ranges and orientations. Recent studies have shown that particular physical properties of local and global image-based elements are correlated with the performance and the level of experience of human observers in breast cancer and lung nodule detections. Neurological findings in visual perception were an inspiration for wavelet applications in vision research because the methodology tries to mimic the brain processing algorithms. Methods: The wavelet approach to the set of postero-anterior chest radiographs analysis has been used to characterize perceptual preferences observers with different levels of experience in the radiological task. Psychophysical methodology has been applied to track eye movements over the image, where particular ROIs related to the observers' fixation clusters has been analysed in the spaces frame by Daubechies functions. Results: Significance differences have been found between the spatial frequency characteristics at the location of different decisions.

Lung nodule detection performance in five observers on computed tomography (CT) with adaptive iterative dose reduction using three-dimensional processing (AIDR 3D) in a Japanese multicenter study: Comparison between ultra-low-dose CT and low-dose CT by receiver-operating characteristic analysis.

Science.gov (United States)

Nagatani, Yukihiro; Takahashi, Masashi; Murata, Kiyoshi; Ikeda, Mitsuru; Yamashiro, Tsuneo; Miyara, Tetsuhiro; Koyama, Hisanobu; Koyama, Mitsuhiro; Sato, Yukihisa; Moriya, Hiroshi; Noma, Satoshi; Tomiyama, Noriyuki; Ohno, Yoshiharu; Murayama, Sadayuki

2015-07-01

To compare lung nodule detection performance (LNDP) in computed tomography (CT) with adaptive iterative dose reduction using three dimensional processing (AIDR3D) between ultra-low dose CT (ULDCT) and low dose CT (LDCT). This was part of the Area-detector Computed Tomography for the Investigation of Thoracic Diseases (ACTIve) Study, a multicenter research project being conducted in Japan. Institutional Review Board approved this study and informed consent was obtained. Eighty-three subjects (body mass index, 23.3 ± 3.2) underwent chest CT at 6 institutions using identical scanners and protocols. In a single visit, each subject was scanned using different tube currents: 240, 120 and 20 mA (3.52, 1.74 and 0.29 mSv, respectively). Axial CT images with 2-mm thickness/increment were reconstructed using AIDR3D. Standard of reference (SOR) was determined based on CT images at 240 mA by consensus reading of 2 board-certificated radiologists as to the presence of lung nodules with the longest diameter (LD) of more than 3mm. Another 5 radiologists independently assessed and recorded presence/absence of lung nodules and their locations by continuously-distributed rating in CT images at 20 mA (ULDCT) and 120 mA (LDCT). Receiver-operating characteristic (ROC) analysis was used to evaluate LNDP of both methods in total and also in subgroups classified by LD (>4, 6 and 8 mm) and nodular characteristics (solid and ground glass nodules). For SOR, 161 solid and 60 ground glass nodules were identified. No significant difference in LNDP for entire solid nodules was demonstrated between both methods, as area under ROC curve (AUC) was 0.844 ± 0.017 in ULDCT and 0.876 ± 0.026 in LDCT (p=0.057). For ground glass nodules with LD 8mm or more, LNDP was similar between both methods, as AUC 0.899 ± 0.038 in ULDCT and 0.941 ± 0.030 in LDCT. (p=0.144). ULDCT using AIDR3D with an equivalent radiation dose to chest x-ray could have comparable LNDP to LDCT with AIDR3D except for smaller ground

Parametric features of image textures in 18F-FDG PET/CT evaluation of lung nodules

International Nuclear Information System (INIS)

Wang Changmei; Guan Yihui; Zhang Wenqiang; Zuo Chuantao; Hua Fengchun

2013-01-01

Objective: To evaluate the parametric features of image textures on 18 F-FDG PET/CT for the differentiation between malignant and benign pulmonary nodules and compare the diagnostic performance of these parameters with SUV max . Methods: 18 F-FDG PET/CT images of 170 patients (102 males, 68 females, age range: 29-81 (mean 59) years) with pulmonary nodules were retrospectively evaluated. Eighty-nine pulmonary nodules (230 slices) were malignant and 81 (193 slices) were benign. The pulmonary nodules were contoured on CT images and mapped to the co-registered PET images. Thirteen parameters of textural features were extracted and SUV max was measured. Logistic regression analysis was used to identify the significant texture parameters and create a regression model. The efficacy of the textural features and SUV max to distinguish between malignant and benign pulmonary nodules was evaluated by ROC curve analysis. The textural features of squamous cell carcinoma and adenocarcinoma were compared via the Mann-Whitney u test. The sensitivity and specificity of the textural features and SUV max for the differential diagnosis were compared with χ 2 test. Results: Logistic regression model identified 4 textural features (skewness (β=1.7058), kurtosis (β=-1.0989), angular second moment (ASM, 3=-4.4140) and strength (β=0.5626); all P<0.05) to have significant correlation with the malignancy of lung nodules. The AUC of ROC curve was 0.775 (95% CI 0.732-0.819; P<0.001) with the sensitivity of 89.6% (206/230) and specificity of 50.8% (98/193). ASM and strength had statistically significant differences between squamous cell carcinoma and adenocarcinoma [ASM: 0.0303 (95% CI 0.0392-0.0724) vs 0.0594 (95% CI 0.0721-0.0947); strength: 2.4714 (95% CI 2.4632-4.1050) vs 1.5945 (95% CI 1.9003-2.4652); u=3082.0 and 3115.0, both P<0.01]. The AUC of SUV max -based diagnosis was 0.757 (95% CI 0.711-0.802; P<0.001) with the sensitivity of 80.9% (186/230) and specificity of 50.3% (97/193) at

Improvement in visibility of simulated lung nodules on computed radiography (CR) chest images by use of temporal subtraction technique

International Nuclear Information System (INIS)

Oda, Nobuhiro; Fujimoto, Keiji; Murakami, Seiichi; Katsuragawa, Shigehiko; Doi, Kunio; Nakata, Hajime

1999-01-01

A temporal subtraction image obtained by subtraction of a previous image from a current one can enhance interval change on chest images. In this study, we compared the visibility of simulated lung nodules on CR images with and without temporal subtraction. Chest phantom images without and with simulated nodules were obtained as previous and current images, respectively, by a CR system. Then, subtraction images were produced with an iterative image warping technique. Twelve simulated nodules were attached on various locations of the chest phantom. The diameter of nodules having a CT number of 47 ranged from 3 mm to 10 mm. Seven radiologists subjectively evaluated the visibility of simulated nodules on CR images with and without temporal subtraction using a three-point rating scale (0: invisible, +1: questionable, +2:visible). The minimum diameter of simulated nodules visible at a frequency greater than 50% was 4 mm on the CR images with temporal subtraction and 6 mm on those without. Our results indicated that the subtraction images clearly improved the visibility of simulated nodules. (author)

Diagnosing lung nodules on oncologic MR/PET imaging: Comparison of fast T1-weighted sequences and influence of image acquisition in inspiration and expiration breath-hold

Energy Technology Data Exchange (ETDEWEB)

Schwenzer, Nina F.; Seith, Ferdinand; Gatidis, Sergios; Brendle, Cornelia; Schmidt, Holger; Pfannenberg, Christina A; LaFougère, Christian; Nikolaou, Konstantin; Schraml, Christina [University Hospital of Tuebingen, Tuebingen (Germany)

2016-09-15

First, to investigate the diagnostic performance of fast T1-weighted sequences for lung nodule evaluation in oncologic magnetic resonance (MR)/positron emission tomography (PET). Second, to evaluate the influence of image acquisition in inspiration and expiration breath-hold on diagnostic performance. The study was approved by the local Institutional Review Board. PET/CT and MR/PET of 44 cancer patients were evaluated by 2 readers. PET/CT included lung computed tomography (CT) scans in inspiration and expiration (CTin, CTex). MR/PET included Dixon sequence for attenuation correction and fast T1-weighted volumetric interpolated breath-hold examination (VIBE) sequences (volume interpolated breath-hold examination acquired in inspiration [VIBEin], volume interpolated breath-hold examination acquired in expiration [VIBEex]). Diagnostic performance was analyzed for lesion-, lobe-, and size-dependence. Diagnostic confidence was evaluated (4-point Likert-scale; 1 = high). Jackknife alternative free-response receiver-operating characteristic (JAFROC) analysis was performed. Seventy-six pulmonary lesions were evaluated. Lesion-based detection rates were: CTex, 77.6%; VIBEin, 53.3%; VIBEex, 51.3%; and Dixon, 22.4%. Lobe-based detection rates were: CTex, 89.6%; VIBEin, 58.3%; VIBEex, 60.4%; and Dixon, 31.3%. In contrast to CT, inspiration versus expiration did not alter diagnostic performance in VIBE sequences. Diagnostic confidence was best for VIBEin and CTex and decreased in VIBEex and Dixon (1.2 ± 0.6; 1.2 ± 0.7; 1.5 ± 0.9; 1.7 ± 1.1, respectively). The JAFROC figure-of-merit of Dixon was significantly lower. All patients with malignant lesions were identified by CTex, VIBEin, and VIBEex, while 3 patients were false-negative in Dixon. Fast T1-weighted VIBE sequences allow for identification of patients with malignant pulmonary lesions. The Dixon sequence is not recommended for lung nodule evaluation in oncologic MR/PET patients. In contrast to CT, inspiration versus

Diagnosing Lung Nodules on Oncologic MR/PET Imaging: Comparison of Fast T1-Weighted Sequences and Influence of Image Acquisition in Inspiration and Expiration Breath-Hold

Energy Technology Data Exchange (ETDEWEB)

Schwenzer, Nina F.; Seith, Ferdinand; Gatidis, Sergios [Department of Diagnostic and Interventional Radiology, University Hospital of Tuebingen, Tuebingen 72076 (Germany); Brendle, Cornelia [Department of Diagnostic and Interventional Radiology, University Hospital of Tuebingen, Tuebingen 72076 (Germany); Department of Diagnostic and Interventional Neuroradiology, University Hospital of Tuebingen, Tuebingen 72076 (Germany); Schmidt, Holger; Pfannenberg, Christina A. [Department of Diagnostic and Interventional Radiology, University Hospital of Tuebingen, Tuebingen 72076 (Germany); Fougère, Christian la [Department of Nuclear Medicine, University Hospital of Tuebingen, Tuebingen 72076 (Germany); Nikolaou, Konstantin; Schraml, Christina [Department of Diagnostic and Interventional Radiology, University Hospital of Tuebingen, Tuebingen 72076 (Germany)

2016-11-01

First, to investigate the diagnostic performance of fast T1-weighted sequences for lung nodule evaluation in oncologic magnetic resonance (MR)/positron emission tomography (PET). Second, to evaluate the influence of image acquisition in inspiration and expiration breath-hold on diagnostic performance. The study was approved by the local Institutional Review Board. PET/CT and MR/PET of 44 cancer patients were evaluated by 2 readers. PET/CT included lung computed tomography (CT) scans in inspiration and expiration (CTin, CTex). MR/PET included Dixon sequence for attenuation correction and fast T1-weighted volumetric interpolated breath-hold examination (VIBE) sequences (volume interpolated breath-hold examination acquired in inspiration [VIBEin], volume interpolated breath-hold examination acquired in expiration [VIBEex]). Diagnostic performance was analyzed for lesion-, lobe-, and size-dependence. Diagnostic confidence was evaluated (4-point Likert-scale; 1 = high). Jackknife alternative free-response receiver-operating characteristic (JAFROC) analysis was performed. Seventy-six pulmonary lesions were evaluated. Lesion-based detection rates were: CTex, 77.6%; VIBEin, 53.3%; VIBEex, 51.3%; and Dixon, 22.4%. Lobe-based detection rates were: CTex, 89.6%; VIBEin, 58.3%; VIBEex, 60.4%; and Dixon, 31.3%. In contrast to CT, inspiration versus expiration did not alter diagnostic performance in VIBE sequences. Diagnostic confidence was best for VIBEin and CTex and decreased in VIBEex and Dixon (1.2 ± 0.6; 1.2 ± 0.7; 1.5 ± 0.9; 1.7 ± 1.1, respectively). The JAFROC figure-of-merit of Dixon was significantly lower. All patients with malignant lesions were identified by CTex, VIBEin, and VIBEex, while 3 patients were false-negative in Dixon. Fast T1-weighted VIBE sequences allow for identification of patients with malignant pulmonary lesions. The Dixon sequence is not recommended for lung nodule evaluation in oncologic MR/PET patients. In contrast to CT, inspiration versus

Lung nodule detection performance in five observers on computed tomography (CT) with adaptive iterative dose reduction using three-dimensional processing (AIDR 3D) in a Japanese multicenter study: Comparison between ultra-low-dose CT and low-dose CT by receiver-operating characteristic analysis

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Nagatani, Yukihiro, E-mail: yatsushi@belle.shiga-med.ac.jp [Department of Radiology, Shiga University of Medical Science, Otsu 520-2192, Shiga (Japan); Takahashi, Masashi; Murata, Kiyoshi [Department of Radiology, Shiga University of Medical Science, Otsu 520-2192, Shiga (Japan); Ikeda, Mitsuru [Department of Radiological and Medical Laboratory Science, Nagoya University Graduate School of Medicine, Nagoya 461-8673, Aichi (Japan); Yamashiro, Tsuneo [Department of Radiology, Graduate School of Medical Science, University of the Ryukyus, Nishihara 903-0215, Okinawa (Japan); Miyara, Tetsuhiro [Department of Radiology, Graduate School of Medical Science, University of the Ryukyus, Nishihara 903-0215, Okinawa (Japan); Department of Radiology, Okinawa Prefectural Yaeyama Hospital, Ishigaki 907-0022, Okinawa (Japan); Koyama, Hisanobu [Department of Radiology, Kobe University Graduate School of Medicine, Kobe 650-0017, Hyogo (Japan); Koyama, Mitsuhiro [Department of Radiology, Osaka Medical College, Takatsuki 569-8686, Osaka (Japan); Sato, Yukihisa [Department of Radiology, Osaka University Graduate School of Medicine, Suita 565-0871, Osaka (Japan); Department of Radiology, Osaka Medical Center of Cancer and Cardiovascular Diseases, Osaka 537-8511, Osaka (Japan); Moriya, Hiroshi [Department of Radiology, Ohara General Hospital, Fukushima 960-8611 (Japan); Noma, Satoshi [Department of Radiology, Tenri Hospital, Tenri 632-8552, Nara (Japan); Tomiyama, Noriyuki [Department of Radiology, Osaka University Graduate School of Medicine, Suita 565-0871, Osaka (Japan); Ohno, Yoshiharu [Department of Radiology, Kobe University Graduate School of Medicine, Kobe 650-0017, Hyogo (Japan); Murayama, Sadayuki [Department of Radiology, Graduate School of Medical Science, University of the Ryukyus, Nishihara 903-0215, Okinawa (Japan)

2015-07-15

Highlights: • Using AIDR 3D, ULDCT showed comparable LND of solid nodules to LDCT. • Using AIDR 3D, LND of smaller GGN in ULDCT was inferior to that in LDCT. • Effective dose in ULDCT was about only twice of that in chest X-ray. • BMI values in study population were mostly in the normal range body habitus. - Abstract: Purpose: To compare lung nodule detection performance (LNDP) in computed tomography (CT) with adaptive iterative dose reduction using three dimensional processing (AIDR3D) between ultra-low dose CT (ULDCT) and low dose CT (LDCT). Materials and methods: This was part of the Area-detector Computed Tomography for the Investigation of Thoracic Diseases (ACTIve) Study, a multicenter research project being conducted in Japan. Institutional Review Board approved this study and informed consent was obtained. Eighty-three subjects (body mass index, 23.3 ± 3.2) underwent chest CT at 6 institutions using identical scanners and protocols. In a single visit, each subject was scanned using different tube currents: 240, 120 and 20 mA (3.52, 1.74 and 0.29 mSv, respectively). Axial CT images with 2-mm thickness/increment were reconstructed using AIDR3D. Standard of reference (SOR) was determined based on CT images at 240 mA by consensus reading of 2 board-certificated radiologists as to the presence of lung nodules with the longest diameter (LD) of more than 3 mm. Another 5 radiologists independently assessed and recorded presence/absence of lung nodules and their locations by continuously-distributed rating in CT images at 20 mA (ULDCT) and 120 mA (LDCT). Receiver-operating characteristic (ROC) analysis was used to evaluate LNDP of both methods in total and also in subgroups classified by LD (>4, 6 and 8 mm) and nodular characteristics (solid and ground glass nodules). Results: For SOR, 161 solid and 60 ground glass nodules were identified. No significant difference in LNDP for entire solid nodules was demonstrated between both methods, as area under ROC

The incidental pulmonary nodule in a child. Part 1: recommendations from the SPR Thoracic Imaging Committee regarding characterization, significance and follow-up

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Westra, Sjirk J. [Massachusetts General Hospital, Division of Pediatric Radiology, Boston, MA (United States); Brody, Alan S. [Cincinnati Children' s Hospital Medical Center, Department of Radiology (CH-1), Cincinnati, OH (United States); Mahani, Maryam Ghadimi [University of Michigan Health System, Section of Pediatric Radiology, C. S. Mott Children' s Hospital Department of Radiology, Ann Arbor, MI (United States); Guillerman, R.P. [Texas Children' s Hospital, Department of Radiology, Houston, TX (United States); Hegde, Shilpa V. [Arkansas Children' s Hospital, Department of Radiology, Little Rock, AR (United States); Iyer, Ramesh S. [Seattle Children' s Hospital, Department of Radiology, Seattle, WA (United States); Lee, Edward Y. [Boston Children' s Hospital, Department of Pediatric Radiology, Boston, MA (United States); Newman, Beverley [Lucile Packard Children' s Hospital at Stanford University, Department of Radiology, Stanford, CA (United States); Podberesky, Daniel J. [Nemours Children' s Hospital, Department of Radiology, Orlando, FL (United States); Thacker, Paul G. [Medical University of South Carolina, Department of Radiology, Charleston, SC (United States)

2015-05-01

No guidelines are in place for the follow-up and management of pulmonary nodules that are incidentally detected on CT in the pediatric population. The Fleischner guidelines, which were developed for the older adult population, do not apply to children. This review summarizes the evidence collected by the Society for Pediatric Radiology (SPR) Thoracic Imaging Committee in its attempt to develop pediatric-specific guidelines. Small pulmonary opacities can be characterized as linear or as ground-glass or solid nodules. Linear opacities and ground-glass nodules are extremely unlikely to represent an early primary or metastatic malignancy in a child. In our review, we found a virtual absence of reported cases of a primary pulmonary malignancy presenting as an incidentally detected small lung nodule on CT in a healthy immune-competent child. Because of the lack of definitive information on the clinical significance of small lung nodules that are incidentally detected on CT in children, the management of those that do not have the typical characteristics of an intrapulmonary lymph node should be dictated by the clinical history as to possible exposure to infectious agents, the presence of an occult immunodeficiency, the much higher likelihood that the nodule represents a metastasis than a primary lung tumor, and ultimately the individual preference of the child's caregiver. Nodules appearing in children with a history of immune deficiency, malignancy or congenital pulmonary airway malformation should not be considered incidental, and their workup should be dictated by the natural history of these underlying conditions. (orig.)

The influence of inspiratory effort and emphysema on pulmonary nodule volumetry reproducibility.

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Moser, J B; Mak, S M; McNulty, W H; Padley, S; Nair, A; Shah, P L; Devaraj, A

2017-11-01

To evaluate the impact of inspiratory effort and emphysema on reproducibility of pulmonary nodule volumetry. Eighty-eight nodules in 24 patients with emphysema were studied retrospectively. All patients had undergone volumetric inspiratory and end-expiratory thoracic computed tomography (CT) for consideration of bronchoscopic lung volume reduction. Inspiratory and expiratory nodule volumes were measured using commercially available software. Local emphysema extent was established by analysing a segmentation area extended circumferentially around each nodule (quantified as percent of lung with density of -950 HU or less). Lung volumes were established using the same software. Differences in inspiratory and expiratory nodule volumes were illustrated using the Bland-Altman test. The influences of percentage reduction in lung volume at expiration, local emphysema extent, and nodule size on nodule volume variability were tested with multiple linear regression. The majority of nodules (59/88 [67%]) showed an increased volume at expiration. Mean difference in nodule volume between expiration and inspiration was +7.5% (95% confidence interval: -24.1, 39.1%). No relationships were demonstrated between nodule volume variability and emphysema extent, degree of expiration, or nodule size. Expiration causes a modest increase in volumetry-derived nodule volumes; however, the effect is unpredictable. Local emphysema extent had no significant effect on volume variability in the present cohort. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Seven-microRNA panel for lung adenocarcinoma early diagnosis in patients presenting with ground-glass nodules

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He Y

2017-12-01

Full Text Available Yayi He,1,2,* Yang Yang,3,* Peng Kuang,1 Shengxiang Ren,1 Leslie Rozeboom,2 Christopher J Rivard,2 Xuefei Li,4 Caicun Zhou,1 Fred R Hirsch2 1Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, People’s Republic of China; 2Division of Medical Oncology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; 3Department of Surgery, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, 4Department of Lung Cancer and Immunology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, People’s Republic of China *These authors contributed equally to this work Background: MicroRNA (miRNA expression is correlated with tumor histology, differentiation, invasiveness and treatment outcome. We aimed to identify miRNAs whose differential expression might enable early diagnosis of lung adenocarcinoma in patients presenting with ground-glass nodules (GGNs.Methods: To identify potential miRNAs of interest, we analyzed the miRNA expression profile of tumor and adjacent non-para-tumor tissue in three participants by next-generation sequencing (NGS. We then assessed the expression levels of the miRNAs of interest in 73 lung adenocarcinomas presenting with GGNs with matched adjacent non-tumor tissue by quantitative real-time polymerase chain reaction (qRT-PCR. We also detected the miRNA panel in 66 lung benign diseases and 66 lung adenocarcinomas presenting with GGN lesion tissues by qRT-PCR. Target genes of our selected miRNA panel were predicted using Miranda with default parameters.Results: Twenty-three miRNAs showed differential expression between tumor and adjacent non-tumor tissue by NGS. Five miRNAs exhibited higher expression in tumor tissue compared to adjacent non-tumor tissue (P

Quantitative CT: technique dependence of volume estimation on pulmonary nodules

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Chen, Baiyu; Barnhart, Huiman; Richard, Samuel; Colsher, James; Amurao, Maxwell; Samei, Ehsan

2012-03-01

Current estimation of lung nodule size typically relies on uni- or bi-dimensional techniques. While new three-dimensional volume estimation techniques using MDCT have improved size estimation of nodules with irregular shapes, the effect of acquisition and reconstruction parameters on accuracy (bias) and precision (variance) of the new techniques has not been fully investigated. To characterize the volume estimation performance dependence on these parameters, an anthropomorphic chest phantom containing synthetic nodules was scanned and reconstructed with protocols across various acquisition and reconstruction parameters. Nodule volumes were estimated by a clinical lung analysis software package, LungVCAR. Precision and accuracy of the volume assessment were calculated across the nodules and compared between protocols via a generalized estimating equation analysis. Results showed that the precision and accuracy of nodule volume quantifications were dependent on slice thickness, with different dependences for different nodule characteristics. Other parameters including kVp, pitch, and reconstruction kernel had lower impact. Determining these technique dependences enables better volume quantification via protocol optimization and highlights the importance of consistent imaging parameters in sequential examinations.

Detectability of T1a lung cancer on digital chest radiographs: an observer-performance comparison among 2-megapixel general-purpose, 2-megapixel medical-purpose, and 3-megapixel medical-purpose liquid-crystal display (LCD) monitors.

Science.gov (United States)

Yabuuchi, Hidetake; Matsuo, Yoshio; Kamitani, Takeshi; Jinnnouchi, Mikako; Yonezawa, Masato; Yamasaki, Yuzo; Nagao, Michinobu; Kawanami, Satoshi; Okamoto, Tatsuro; Sasaki, Masayuki; Honda, Hiroshi

2015-08-01

There has been no comparison of detectability of small lung cancer between general and medical LCD monitors or no comparison of detectability of small lung cancer between solid and part-solid nodules. To compare the detectabilities of T1a lung cancer on chest radiographs on three LCD monitor types: 2-megapixel (MP) for general purpose (General), 2-MP for medical purpose (Medical), and 3-MP-Medical. Radiographs from forty patients with T1aN0M0 primary lung cancer (27 solid nodules, 13 part-solid nodules) and 60 patients with no abnormalities on both chest X-ray and computed tomography (CT) were consecutively collected. Five readers assessed 100 cases for each monitor. The observations were analyzed using receiver operating characteristic (ROC) analysis. A jackknife method was used for statistical analysis. A P value of General, 2-MP-Medical, and 3-MP-Medical LCD monitors were 0.86, 0.89, and 0.89, respectively; there were no significant differences among them. The average AUC for part-solid nodule detection using a 2-MP-General, 2-MP-Medical, and 3-MP-Medical LCD monitors were 0.77, 0.86, and 0.89, respectively. There were significant differences between the 2-MP-General and 2-MP-Medical LCD monitors (P = 0.043) and between the 2-MP-General and 3-MP-Medical LCD monitors (P = 0.027). There was no significant difference between the 2-MP-Medical and 3-MP-Medical LCD monitors. The average AUC for solid nodule detection using a 2-MP-General, 2-MP-Medical, and 3-MP-Medical LCD monitors were 0.90, 0.90, and 0.88, respectively; there were no significant differences among them. The mean AUC values for all and part-solid nodules of the low-experienced readers were significantly lower than those of the high-experienced readers with the 2 M-GP color LCD monitor (P general-purpose LCD monitor was significantly lower than those using medical-purpose LCD monitors. © The Foundation Acta Radiologica 2014.

Computed tomography of pulmonary nodules

International Nuclear Information System (INIS)

Nakata, Hajime; Honda, Hiroshi; Nakayama, Chikashi; Kimoto, Tatsuya; Nakayama, Takashi

1983-01-01

We have evaluated the value of computed tomography (CT) in distinguishing benign and malignant pulmonary nodules. CT was performed on 30 cases of solitary pulmonary nodules consisting of 17 primary lung cancers, 3 metastatic tumors and 10 benign nodules. The CT number was calculated for each lesion. Three benign nodules showed CT numbers well above the range of malignant nodules, and only in one of them was calcification visible on conventional tomography. In 6 benign nodules, the CT numbers overlapped those of malignant lesion and could not be differentiated. Thus the measurement of CT number can be useful to confirm the benign nature of certain nodules when calcification is unclear or not visible on conventional tomography. As for the morphological observation of the nodule, CT was not superior to conventional tomography and its value seems to be limited. (author)

Low-dose CT: new tool for screening lung cancer?

International Nuclear Information System (INIS)

Diederich, S.; Wormanns, D.; Heindel, W.

2001-01-01

Lung cancer is the leading cause of death from malignant tumours as it is very common and has a poor prognosis at advanced tumour stages. Prognosis could be improved by treatment at early stages. As these stages are usually asymptomatic, a diagnostic test that would allow detection of early tumour stages in a population at risk could potentially reduce mortality from lung cancer. Previous approaches using chest radiography and sputum cytology in smokers have been disappointing. Fluorescent bronchoscopy and molecular markers are not yet applicable in clinical routine. Because of its high sensitivity for small pulmonary nodules, which are the most common manifestation of early lung cancer, CT appears suitable as a screening test. Low-dose examination parameters can and should be used for this purpose. From clinical practice it is well known that chest CT often demonstrates small pulmonary nodules, which do not represent lung cancer. Therefore, non-invasive diagnostic algorithms are required to avoid unnecessary biopsies in benign lesions. In preliminary studies of low-dose CT using algorithms based on size and density of detected nodules a large proportion of asymptomatic lung cancers and a large proportion of early, resectable tumour stages were found with a small proportion of invasive procedures for benign nodules. Before this technology can be recommended for broad application, however, further information is required regarding appropriate inclusion criteria (smoking habits, age groups) and screening intervals. Most importantly, further data are required to clarify whether lung cancer screening using low-dose CT can actually reduce mortality from lung cancer. (orig.)

iPads and LCDs show similar performance in the detection of pulmonary nodules

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McEntee, Mark F.; Lowe, Joanna; Butler, Marie Louise; Pietrzyk, Mariusz; Evanoff, Michael G.; Ryan, John; Brennan, Patrick C.; Rainford, Louise A.

2012-02-01

In February 2011 the University of Chicago Medical School distributed iPads to its trainee doctors for use when reviewing clinical information and images on the ward or clinics. The use of tablet computing devices is becoming widespread in medicine with Apple™ heralding them as "revolutionary" in medicine. The question arises, just because it is technical achievable to use iPads for clinical evaluation of images, should we do so? The current work assesses the diagnostic efficacy of iPads when compared with LCD secondary display monitors for identifying lung nodules on chest x-rays. Eight examining radiologists of the American Board of Radiology were involved in the assessment, reading chest images on both the iPad and the an off-the-shelf LCD monitor. Thirty chest images were shown to each observer, of which 15 had one or more lung nodules. Radiologists were asked to locate the nodules and score how confident they were with their decision on a scale of 1-5. An ROC and JAFROC analysis was performed and modalities were compared using DBM MRMC. The results demonstrate no significant differences in performance between the iPad and the LCD for the ROC AUC (p<0.075) or JAFROC FOM (p<0.059) for random readers and random cases. Sample size estimation showed that this result is significant at a power of 0.8 and an effect size of 0.05 for ROC and 0.07 for JAFROC. This work demonstrates that for the task of identifying pulmonary nodules, the use of the iPad does not significantly change performance compared to an off-the-shelf LCD.

Effect of Clinical Experience of Chest Tomosynthesis on Detection of Pulmonary Nodules

International Nuclear Information System (INIS)

Zachrisson, S.; Svalkvist, A.; Maansson, L.G.; Baath, M.; Vikgren, J.; Johnsson, Aa.A.; Boijsen, M.; Flinck, A.; Kheddache, S.

2009-01-01

Background: The new technique chest tomosynthesis refers to the principle of collecting low-dose projections of the chest at different angles and using these projections to reconstruct section images of the chest at a radiation dose comparable to that of chest radiography. Purpose: To investigate if, for experienced thoracic radiologists, the detectability of pulmonary nodules obtained after only a short initial learning period of chest tomosynthesis improves with additional clinical experience of the new technique. Material and Methods: Two readings of the same clinical chest tomosynthesis cases, the first performed after 6 months of clinical experience and the second after an additional period of 1 year, were conducted. Three senior thoracic radiologists, with more than 20 years of experience of chest radiography, acted as observers, with the task of detecting pulmonary nodules in a jackknife free-response receiver operating characteristics (JAFROC1) study. The image material consisted of 42 patients with and 47 patients without pulmonary nodules examined with chest tomosynthesis. Multidetector computed tomography (MDCT) was used as a reference. The total number of nodules was 131. The JAFROC1 figure of merit (FOM) was used as the principal measure of detectability. Results: The difference in the observer-averaged JAFROC1 FOM of the two readings was 0.004 (95% confidence interval: -0.11, 0.12; F-statistic: 0.01 on 1 and 2.65 df; P=0.91). Thus, no significant improvement in detectability was found after the additional clinical experience of tomosynthesis. Conclusion: The study indicates that experienced thoracic radiologists already within the first months of clinical use of chest tomosynthesis are able to take advantage of the new technique in the task of detecting pulmonary nodules

Multi-scale analysis of lung computed tomography images

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Gori, I; Fantacci, M E; Preite Martinez, A; Retico, A; De Mitri, I; Donadio, S; Fulcheri, C

2007-01-01

A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.

Computer-assisted lung nodule volumetry from multi-detector row CT: Influence of image reconstruction parameters

International Nuclear Information System (INIS)

Honda, Osamu; Sumikawa, Hiromitsu; Johkoh, Takeshi; Tomiyama, Noriyuki; Mihara, Naoki; Inoue, Atsuo; Tsubamoto, Mitsuko; Natsag, Javzandulam; Hamada, Seiki; Nakamura, Hironobu

2007-01-01

Purpose: To investigate differences in volumetric measurement of pulmonary nodules caused by changing the reconstruction parameters for multi-detector row CT. Materials and methods: Thirty-nine pulmonary nodules less than 2 cm in diameter were examined by multi-slice CT. All nodules were solid, and located in the peripheral part of the lungs. The resultant 48 parameters images were reconstructed by changing slice thickness (1.25, 2.5, 3.75, or 5 mm), field of view (FOV: 10, 20, or 30 cm), algorithm (high-spatial frequency algorithm or low-spatial frequency algorithm) and reconstruction interval (reconstruction with 50% overlapping of the reconstructed slices or non-overlapping reconstruction). Volumetric measurements were calculated using commercially available software. The differences between nodule volumes were analyzed by the Kruskal-Wallis test and the Wilcoxon Signed-Ranks test. Results: The diameter of the nodules was 8.7 ± 2.7 mm on average, ranging from 4.3 to 16.4 mm. Pulmonary nodule volume did not change significantly with changes in slice thickness or FOV (p > 0.05), but was significantly larger with the high-spatial frequency algorithm than the low-spatial frequency algorithm (p < 0.05), except for one reconstruction parameter. The volumes determined by non-overlapping reconstruction were significantly larger than those of overlapping reconstruction (p < 0.05), except for a 1.25 mm thickness with 10 cm FOV with the high-spatial frequency algorithm, and 5 mm thickness. The maximum difference in measured volume was 16% on average between the 1.25 mm slice thickness/10 cm FOV/high-spatial frequency algorithm parameters and overlapping reconstruction. Conclusion: Volumetric measurements of pulmonary nodules differ with changes in the reconstruction parameters, with a tendency toward larger volumes in high-spatial frequency algorithm and non-overlapping reconstruction compared to the low-spatial frequency algorithm and overlapping reconstruction

Chromogenic in situ hybridization to detect EGFR gene copy number in cell blocks from fine-needle aspirates of non small cell lung carcinomas and lung metastases from colo-rectal cancer

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Terrenato Irene

2010-09-01

Full Text Available Abstract Background Several studies demonstrated that epidermal growth factor receptor (EGFR gene copy number (GCN correlates to the response to tyrosine kinase inhibitors in non small cell lung cancer (NSCLC and to anti-EGFR monoclonal antibodies (MoAbs in metastatic colorectal cancer (CRC. In the presence of lung nodules, cytology is often the only possible diagnostic approach. Chromogenic in situ hybridization (CISH is an alternative technique to fluorescence in situ hybridization (FISH, but its feasibility in detecting EGFR GCN in cell blocks from fine-needle aspiration cytology (FNAC of lung nodules has not yet been established. Methods We evaluated the feasibility of CISH on 33 FNAC from 20 primary NSCLC (5 squamous carcinomas, 8 large cell carcinomas and 7 adenocarcinomas and 13 lung metastases from CRC. Results Of the 33 FNAC analyzed by CISH, 27 (82% presented a balanced increase in EGFR gene and chromosome 7 number: 10 cases (30% showed a low polysomy, 15 (45% a high polysomy and 2 (6% NSCLC were amplified. No significant differences between NSCLC and CRC lung metastases were found in relation to disomic or polysomic status. In addition, no correlation between EGFR GCN and EGFR immunohistochemical overexpression was found. Furthermore, we compared CISH results with those obtained by FISH on the same samples and we found 97% overall agreement between the two assays (k = 0.78, p Conclusions Our study shows that CISH is a valid method to detect EGFR GCN in cell blocks from FNAC of primary NSCLC or metastatic CRC to the lung.

Early detection of lung cancer using ultra-low-dose computed tomography in coronary CT angiography scans among patients with suspected coronary heart disease.

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Zanon, Matheus; Pacini, Gabriel Sartori; de Souza, Vinicius Valério Silveiro; Marchiori, Edson; Meirelles, Gustavo Souza Portes; Szarf, Gilberto; Torres, Felipe Soares; Hochhegger, Bruno

2017-12-01

To assess whether an additional chest ultra-low-dose CT scan to the coronary CT angiography protocol can be used for lung cancer screening among patients with suspected coronary artery disease. 175 patients underwent coronary CT angiography for assessment of coronary artery disease, additionally undergoing ultra-low-dose CT screening to early diagnosis of lung cancer in the same scanner (80kVp and 15mAs). Patients presenting pulmonary nodules were followed-up for two years, repeating low-dose CTs in intervals of 3, 6, or 12 months based on nodule size and growth rate in accordance with National Comprehensive Cancer Network guidelines. Ultra-low-dose CT identified 71 patients with solitary pulmonary nodules (41%), with a mean diameter of 5.50±4.00mm. Twenty-eight were >6mm, and in 79% (n=22) of these cases they were false positive findings, further confirmed by follow-up (n=20), resection (n=1), or biopsy (n=1). Lung cancer was detected in six patients due to CT screening (diagnostic yield: 3%). Among these, four cases could not be detected in the cardiac field of view. Most patients were in early stages of the disease. Two patients diagnosed at advanced stages died due to cancer complications. The addition of the ultra-low-dose CT scan represented a radiation dose increment of 1.22±0.53% (effective dose, 0.11±0.03mSv). Lung cancer might be detected using additional ultra-low-dose protocols in coronary CT angiography scans among patients with suspected coronary artery disease. Copyright © 2017 Elsevier B.V. All rights reserved.

[Computed tomography with computer-assisted detection of pulmonary nodules in dogs and cats].

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Niesterok, C; Piesnack, S; Köhler, C; Ludewig, E; Alef, M; Kiefer, I

2015-01-01

The aim of this study was to assess the potential benefit of computer-assisted detection (CAD) of pulmonary nodules in veterinary medicine. Therefore, the CAD rate was compared to the detection rates of two individual examiners in terms of its sensitivity and false-positive findings. We included 51 dogs and 16 cats with pulmonary nodules previously diagnosed by computed tomography. First, the number of nodules ≥ 3 mm was recorded for each patient by two independent examiners. Subsequently, each examiner used the CAD software for automated nodule detection. With the knowledge of the CAD results, a final consensus decision on the number of nodules was achieved. The software used was a commercially available CAD program. The sensitivity of examiner 1 was 89.2%, while that of examiner 2 reached 87.4%. CAD had a sensitivity of 69.4%. With CAD, the sensitivity of examiner 1 increased to 94.7% and that of examiner 2 to 90.8%. The CAD-system, which we used in our study, had a moderate sensitivity of 69.4%. Despite its severe limitations, with a high level of false-positive and false-negative results, CAD increased the examiners' sensitivity. Therefore, its supportive role in diagnostics appears to be evident.

Pulmonary nodule characterization, including computer analysis and quantitative features.

Science.gov (United States)

Bartholmai, Brian J; Koo, Chi Wan; Johnson, Geoffrey B; White, Darin B; Raghunath, Sushravya M; Rajagopalan, Srinivasan; Moynagh, Michael R; Lindell, Rebecca M; Hartman, Thomas E

2015-03-01

Pulmonary nodules are commonly detected in computed tomography (CT) chest screening of a high-risk population. The specific visual or quantitative features on CT or other modalities can be used to characterize the likelihood that a nodule is benign or malignant. Visual features on CT such as size, attenuation, location, morphology, edge characteristics, and other distinctive "signs" can be highly suggestive of a specific diagnosis and, in general, be used to determine the probability that a specific nodule is benign or malignant. Change in size, attenuation, and morphology on serial follow-up CT, or features on other modalities such as nuclear medicine studies or MRI, can also contribute to the characterization of lung nodules. Imaging analytics can objectively and reproducibly quantify nodule features on CT, nuclear medicine, and magnetic resonance imaging. Some quantitative techniques show great promise in helping to differentiate benign from malignant lesions or to stratify the risk of aggressive versus indolent neoplasm. In this article, we (1) summarize the visual characteristics, descriptors, and signs that may be helpful in management of nodules identified on screening CT, (2) discuss current quantitative and multimodality techniques that aid in the differentiation of nodules, and (3) highlight the power, pitfalls, and limitations of these various techniques.

CT diagnosis of pleural dissemination without pleural effusion in primary lung cancer

International Nuclear Information System (INIS)

Murayama, Sadayuki; Murakami, Junji; Yoshimitsu, Kengo; Torii, Yoshikuni; Masuda, Kouji; Ishida, Teruyoshi.

1996-01-01

We retrospectively reviewed the CT scans of 25 primary lung cancers with disseminated pleural nodules or minimal malignant pleural effusion that were not recognized preparatively. Special attention was devoted to abutting interlobar fissures, thick major fissures, and disseminated nodules on the chest wall, the diaphragm, and in the interlobar fissures. Among 10 primary tumors abutting interlobar fissures, nine (90%) had at least one of these findings. Among 15 primary lung tumors which did not abut interlobar fissures, four (27%) had at least one of these findings. We conclude that CT is a useful modality for detecting the pleural dissemination of primary lung cancers when primary lung cancers abut interlobar fissures even if no pleural effusion is detectable on CT. (author)

Effects of Different Reconstruction Parameters on CT Volumetric Measurement 
of Pulmonary Nodules

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Rongrong YANG

2012-02-01

Full Text Available Background and objective It has been proven that volumetric measurements could detect subtle changes in small pulmonary nodules in serial CT scans, and thus may play an important role in the follow-up of indeterminate pulmonary nodules and in differentiating malignant nodules from benign nodules. The current study aims to evaluate the effects of different reconstruction parameters on the volumetric measurements of pulmonary nodules in chest CT scans. Methods Thirty subjects who underwent chest CT scan because of indeterminate pulmonary nodules in General Hospital of Tianjin Medical University from December 2009 to August 2011 were retrospectively analyzed. A total of 52 pulmonary nodules were included, and all CT data were reconstructed using three reconstruction algorithms and three slice thicknesses. The volumetric measurements of the nodules were performed using the advanced lung analysis (ALA software. The effects of the reconstruction algorithms, slice thicknesses, and nodule diameters on the volumetric measurements were assessed using the multivariate analysis of variance for repeated measures, the correlation analysis, and the Bland-Altman method. Results The reconstruction algorithms (F=13.6, P<0.001 and slice thicknesses (F=4.4, P=0.02 had significant effects on the measured volume of pulmonary nodules. In addition, the coefficients of variation of nine measurements were inversely related with nodule diameter (r=-0.814, P<0.001. The volume measured at the 2.5 mm slice thickness had poor agreement with the volumes measured at 1.25 mm and 0.625 mm, respectively. Moreover, the best agreement was achieved between the slice thicknesses of 1.25 mm and 0.625 mm using the bone algorithm. Conclusion Reconstruction algorithms and slice thicknesses have significant impacts on the volumetric measurements of lung nodules, especially for the small nodules. Therefore, the reconstruction setting in serial CT scans should be consistent in the follow

Detection and quantification of the solid component in pulmonary subsolid nodules by semiautomatic segmentation

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Scholten, Ernst T. [University Medical Center, Department of Radiology, Utrecht (Netherlands); Kennemer Gasthuis, Department of Radiology, Haarlem (Netherlands); Jacobs, Colin; Riel, Sarah van [Radboud University Medical Center, Diagnostic Image Analysis Group, Nijmegen (Netherlands); Ginneken, Bram van [Radboud University Medical Center, Diagnostic Image Analysis Group, Nijmegen (Netherlands); Fraunhofer MEVIS, Bremen (Germany); Vliegenthart, Rozemarijn [University of Groningen, University Medical Center Groningen, Department of Radiology, Groningen (Netherlands); University of Groningen, University Medical Centre Groningen, Center for Medical Imaging-North East Netherlands, Groningen (Netherlands); Oudkerk, Matthijs [University of Groningen, University Medical Centre Groningen, Center for Medical Imaging-North East Netherlands, Groningen (Netherlands); Koning, Harry J. de [Erasmus Medical Center, Department of Public Health, Rotterdam (Netherlands); Horeweg, Nanda [Erasmus Medical Center, Department of Public Health, Rotterdam (Netherlands); Erasmus Medical Center, Department of Pulmonology, Rotterdam (Netherlands); Prokop, Mathias [Radboud University Medical Center, Department of Radiology, Nijmegen (Netherlands); Gietema, Hester A.; Mali, Willem P.T.M.; Jong, Pim A. de [University Medical Center, Department of Radiology, Utrecht (Netherlands)

2014-10-07

To determine whether semiautomatic volumetric software can differentiate part-solid from nonsolid pulmonary nodules and aid quantification of the solid component. As per reference standard, 115 nodules were differentiated into nonsolid and part-solid by two radiologists; disagreements were adjudicated by a third radiologist. The diameters of solid components were measured manually. Semiautomatic volumetric measurements were used to identify and quantify a possible solid component, using different Hounsfield unit (HU) thresholds. The measurements were compared with the reference standard and manual measurements. The reference standard detected a solid component in 86 nodules. Diagnosis of a solid component by semiautomatic software depended on the threshold chosen. A threshold of -300 HU resulted in the detection of a solid component in 75 nodules with good sensitivity (90 %) and specificity (88 %). At a threshold of -130 HU, semiautomatic measurements of the diameter of the solid component (mean 2.4 mm, SD 2.7 mm) were comparable to manual measurements at the mediastinal window setting (mean 2.3 mm, SD 2.5 mm [p = 0.63]). Semiautomatic segmentation of subsolid nodules could diagnose part-solid nodules and quantify the solid component similar to human observers. Performance depends on the attenuation segmentation thresholds. This method may prove useful in managing subsolid nodules. (orig.)

Solitary pulmonary nodule and 18F-FDG PET/CT. Part 1: epidemiology, morphological evaluation and cancer probability

Directory of Open Access Journals (Sweden)

Marcos Pretto Mosmann

2016-02-01

Full Text Available Abstract Solitary pulmonary nodule corresponds to a common radiographic finding, which is frequently detected incidentally. The investigation of this entity remains complex, since characteristics of benign and malignant processes overlap in the differential diagnosis. Currently, many strategies are available to evaluate solitary pulmonary nodules with the main objective of characterizing benign lesions as best as possible, while avoiding to expose patients to the risks inherent to invasive methods, besides correctly detecting cases of lung cancer so as the potential curative treatment is not delayed. This first part of the study focuses on the epidemiology, the morfological evaluation and the methods to determine the likelihood of cancer in cases of indeterminate solitary pulmonary nodule.

Comparative reading support system for lung cancer CT screening

International Nuclear Information System (INIS)

Kubo, Mitsuru; Saita, Shinsuke; Kawata, Yoshiki; Niki, Noboru; Suzuki, Hidenobu; Ohmatsu, Hironobu; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki

2010-01-01

The comparative reading is performed using current and past images of the same case obtained from lung cancer CT screening. The result of this is useful for the early detection of lung cancer. Our paper describes the efficiency improvement of comparative reading using 10 mm slice thickness CT images by developing the system consists of slice registration method, pulmonary nodule registration method, and quantitative evaluation method of pulmonary nodule's degree of change. The proposed system is applied to CT images scanned for 1107 times of 85 cases with 198 pulmonary nodules and is evaluated by comparing it with the reading result of the doctors. We show the effectiveness of the system. (author)

Simple pulmonary eosinophilia detected at low-dose CT for lung cancer screening

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Jeon, Kyung Nyeo; Bae, Kyung Soo; Kim, Ho Cheol [Gyeongsang National University Hospital, Jinju (Korea, Republic of)] (and others)

2006-05-15

The aim of this study was to evaluate the frequency, radiologic findings and clinical significance of the simple pulmonary eosinophilia (SPE) that was diagnosed among the asymptomatic patients who underwent low-dose CT scans for the early detection of lung cancer. From June 2003 to May 2005, 1,239 asymptomatic patients (1,275 examinations) who visited the health promotion center in our hospital and who underwent low-dose CT were enrolled in this study. SPE was defined as the presence of > 500 eosinophils per microliter of peripheral blood and the presence of abnormal parenchymal lesions such as nodules, airspace consolidation or areas of ground-glass attenuation (GGA) on CT, and there was spontaneous resolution or migration of the lesions on the follow-up examination. We analyzed the CT findings of SPE and we investigated the relationship between the occurrence of SPE and the season, smoking and the presence of parasite infestation. 36 patients were finally diagnosed as having SPE; this was 24% of the 153 patients who were diagnosed with parasite infestation and 2.8% of the total low-dose CT scans. These 36 patients consisted of 31 men and 5 women with a mean age 45.7 years. There was no significant relationship between SPE and the presence of parasite infestation, smoking or gender. Among the patients with peripheral blood eosinophilia, the eosinophil count was significantly higher in the patients with SPE than that in the patients without pulmonary infiltration ({rho} < 0.05). SPE more frequently occurred in winter and spring than in summer and autumn ({rho} < 0.05). The CT findings were single or multiple nodules in 18 patients, nodules and focal GGA in 9 patients and GGA only in 9 patients. Most of the nodules were less than 10 mm (88%, 49/56) in diameter and they showed an ill-defined margin (82%, n = 46); 30% of the nodules (n = 17) showed a halo around them. Simple pulmonary eosinophilia can be suggested as the cause if single or multiple ill-defined nodules

Simple pulmonary eosinophilia detected at low-dose CT for lung cancer screening

International Nuclear Information System (INIS)

Jeon, Kyung Nyeo; Bae, Kyung Soo; Kim, Ho Cheol

2006-01-01

The aim of this study was to evaluate the frequency, radiologic findings and clinical significance of the simple pulmonary eosinophilia (SPE) that was diagnosed among the asymptomatic patients who underwent low-dose CT scans for the early detection of lung cancer. From June 2003 to May 2005, 1,239 asymptomatic patients (1,275 examinations) who visited the health promotion center in our hospital and who underwent low-dose CT were enrolled in this study. SPE was defined as the presence of > 500 eosinophils per microliter of peripheral blood and the presence of abnormal parenchymal lesions such as nodules, airspace consolidation or areas of ground-glass attenuation (GGA) on CT, and there was spontaneous resolution or migration of the lesions on the follow-up examination. We analyzed the CT findings of SPE and we investigated the relationship between the occurrence of SPE and the season, smoking and the presence of parasite infestation. 36 patients were finally diagnosed as having SPE; this was 24% of the 153 patients who were diagnosed with parasite infestation and 2.8% of the total low-dose CT scans. These 36 patients consisted of 31 men and 5 women with a mean age 45.7 years. There was no significant relationship between SPE and the presence of parasite infestation, smoking or gender. Among the patients with peripheral blood eosinophilia, the eosinophil count was significantly higher in the patients with SPE than that in the patients without pulmonary infiltration (ρ < 0.05). SPE more frequently occurred in winter and spring than in summer and autumn (ρ < 0.05). The CT findings were single or multiple nodules in 18 patients, nodules and focal GGA in 9 patients and GGA only in 9 patients. Most of the nodules were less than 10 mm (88%, 49/56) in diameter and they showed an ill-defined margin (82%, n = 46); 30% of the nodules (n = 17) showed a halo around them. Simple pulmonary eosinophilia can be suggested as the cause if single or multiple ill-defined nodules or

Surgical resection of highly suspicious pulmonary nodules without a tissue diagnosis

International Nuclear Information System (INIS)

Heo, Eun-Young; Lee, Kyung-Won; Jheon, Sanghoon; Lee, Jae-Ho; Lee, Choon-Taek; Yoon, Ho-II

2011-01-01

The safety and efficacy of surgical resection of lung nodule without tissue diagnosis is controversial. We evaluated direct surgical resection of highly suspicious pulmonary nodules and the clinical and radiological predictors of malignancy. Retrospective analyses were performed on 113 patients who underwent surgical resection without prior tissue diagnosis for highly suspicious pulmonary nodules. Clinical and radiological characteristics were compared between histologically proven benign and malignant nodules after resection. Total costs, length of hospitalization and waiting time to surgery were compared with those of patients who had tissue diagnosis prior to surgery. Among 280 patients with pulmonary nodules suspicious for lung cancer, 113 (40.4%) underwent operation without prior tissue diagnosis. Lung nodules were diagnosed as malignant in 96 (85%) of the 113 patients. Except for forced expiratory volume in 1 s, clinical characteristics were not significantly different according to the pathologic results. Forty-five (90%) of 50 patients with ground-glass opacity nodules had a malignancy. Mixed ground-glass opacity, bubble lucency, irregular margin and larger size correlated with malignancy in ground-glass opacity nodules (P<0.05). Fifty-one (81%) of 67 patients with solid nodules had a malignancy. Spiculation, pre-contrast attenuation and contrast enhancement significantly correlated with malignancy in solid nodules (P<0.05). Surgical resection without tissue diagnosis significantly decreased total costs, hospital stay and waiting time (P<0.05). Direct surgical resection of highly suspicious pulmonary nodules can be a valid procedure. However, careful patient selection and further investigations are required to justify direct surgical resection. (author)

Computer Vision Tool and Technician as First Reader of Lung Cancer Screening CT Scans.

Science.gov (United States)

Ritchie, Alexander J; Sanghera, Calvin; Jacobs, Colin; Zhang, Wei; Mayo, John; Schmidt, Heidi; Gingras, Michel; Pasian, Sergio; Stewart, Lori; Tsai, Scott; Manos, Daria; Seely, Jean M; Burrowes, Paul; Bhatia, Rick; Atkar-Khattra, Sukhinder; van Ginneken, Bram; Tammemagi, Martin; Tsao, Ming Sound; Lam, Stephen

2016-05-01

To implement a cost-effective low-dose computed tomography (LDCT) lung cancer screening program at the population level, accurate and efficient interpretation of a large volume of LDCT scans is needed. The objective of this study was to evaluate a workflow strategy to identify abnormal LDCT scans in which a technician assisted by computer vision (CV) software acts as a first reader with the aim to improve speed, consistency, and quality of scan interpretation. Without knowledge of the diagnosis, a technician reviewed 828 randomly batched scans (136 with lung cancers, 556 with benign nodules, and 136 without nodules) from the baseline Pan-Canadian Early Detection of Lung Cancer Study that had been annotated by the CV software CIRRUS Lung Screening (Diagnostic Image Analysis Group, Nijmegen, The Netherlands). The scans were classified as either normal (no nodules ≥1 mm or benign nodules) or abnormal (nodules or other abnormality). The results were compared with the diagnostic interpretation by Pan-Canadian Early Detection of Lung Cancer Study radiologists. The overall sensitivity and specificity of the technician in identifying an abnormal scan were 97.8% (95% confidence interval: 96.4-98.8) and 98.0% (95% confidence interval: 89.5-99.7), respectively. Of the 112 prevalent nodules that were found to be malignant in follow-up, 92.9% were correctly identified by the technician plus CV compared with 84.8% by the study radiologists. The average time taken by the technician to review a scan after CV processing was 208 ± 120 seconds. Prescreening CV software and a technician as first reader is a promising strategy for improving the consistency and quality of screening interpretation of LDCT scans. Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Follow-up for hepatic nodules detected only by angio-CT in noncancerous regions of the liver with hepatocellular carcinoma

International Nuclear Information System (INIS)

Shuto, Taichi; Mikami, Shinichi; Hirohashi, Kazuhiro; Kubo, Shoji; Tanaka, Hiromu; Yamamoto, Takatsugu; Nakamura, Kenji; Kinoshita, Hiroaki

1998-01-01

As of March 1997, we routinely performed angio-CT or computed tomography during arterial portography (CTAP) and computed tomography during arteriography (CTA) before hepatic resection in 103 cases of hepatocellular carcinoma. Nine cases (9%) had ten nodules those were detected only by angio-CT before surgery, but were not found by palpation and intraoperative ultrasonography during surgery. The mean diameter of these nodules was 1 cm in angio-CT. These were not detected by other imaging tests, such as conventional CT, ultrasonography, or angiography. None of these nodules were the main tumor. All were hyperattenuated nodules according to CTA findings. After hepatic resection for the main tumors, these patients were followed in our outpatient clinic. Five patients suffered recurrence as of March 1998. Two of these nodules (20%) were preexisting nodules that were not detected during surgery. Moreover, these were located near the center of the liver in these patients. We found that at least 20% of the nodules detected only by angio-CT are true-positives, especially when they are located at the center of the liver. (author)

Positron emission tomography of incidentally detected small pulmonary nodules

DEFF Research Database (Denmark)

Fischer, B M; Mortensen, J; Dirksen, A

2004-01-01

The aim of this study was to assess the value of fluorodeoxyglucose positron emission tomography (FDG PET) imaging of small pulmonary nodules incidentally detected by spiral computed tomography (CT) in a high-risk population. Ten patients (five females, five males, aged 54-72 years) were recruited...

Solitary pulmonary nodule and {sup 18}F-FDG PET/CT. Part 1: epidemiology, morphological evaluation and cancer probability

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Mosmann, Marcos Pretto; Borba, Marcelle Alves; Macedo, Francisco Pires Negromonte; Liguori, Adriano de Araujo Lima; Villarim Neto, Arthur, E-mail: mosmann@gmail.com [Liga Norte Riograndense Contra o Cancer, Natal, RN (Brazil); Lima, Kenio Costa de [Universidade Federal do Rio Grande do Norte (UFRN), Natal, RN (Brazil). Programa de Pos-Graduacao em Saude Coletiva

2016-01-15

Solitary pulmonary nodule corresponds to a common radiographic finding, which is frequently detected incidentally. The investigation of this entity remains complex, since characteristics of benign and malignant processes overlap in the differential diagnosis. Currently, many strategies are available to evaluate solitary pulmonary nodules with the main objective of characterizing benign lesions as best as possible, while avoiding to expose patients to the risks inherent to invasive methods, besides correctly detecting cases of lung cancer so as the potential curative treatment is not delayed. This first part of the study focuses on the epidemiology, the morphological evaluation and the methods to determine the likelihood of cancer in cases of indeterminate solitary pulmonary nodule. (author)

Management of an incidentally discovered pulmonary nodule

International Nuclear Information System (INIS)

Beigelman-Aubry, Catherine; Hill, Catherine; Grenier, Philippe A.

2007-01-01

The incidental finding of a pulmonary nodule on computed tomography (CT) is becoming an increasingly frequent event. The discovery of such a nodule should evoke the possibility of a small bronchogenic carcinoma, for which excision is indicated without delay. However, invasive diagnostic procedures should be avoided in the case of a benign lesion. The objectives of this review article are: (1) to analyze the CT criteria defining benign nodules, nodules of high suspicion of malignancy and indeterminate nodules, (2) to analyze the diagnostic performances and limitations of complementary investigations requested to characterize indeterminate lung nodules, (3) to review the criteria permitting to assess the probability of malignancy of indeterminate nodules and (4) to report on the new guidelines provided by the Fleischner Society for the management of small indeterminate pulmonary nodules, according to their prior probability of malignancy. (orig.)

Napsin A levels in epithelial lining fluid as a diagnostic biomarker of primary lung adenocarcinoma.

Science.gov (United States)

Uchida, Akifumi; Samukawa, Takuya; Kumamoto, Tomohiro; Ohshige, Masahiro; Hatanaka, Kazuhito; Nakamura, Yoshihiro; Mizuno, Keiko; Higashimoto, Ikkou; Sato, Masami; Inoue, Hiromasa

2017-12-12

It is crucial to develop novel diagnostic approaches for determining if peripheral lung nodules are malignant, as such nodules are frequently detected due to the increased use of chest computed tomography scans. To this end, we evaluated levels of napsin A in epithelial lining fluid (ELF), since napsin A has been reported to be an immunohistochemical biomarker for histological diagnosis of primary lung adenocarcinoma. In consecutive patients with indeterminate peripheral lung nodules, ELF samples were obtained using a bronchoscopic microsampling (BMS) technique. The levels of napsin A and carcinoembryonic antigen (CEA) in ELF at the nodule site were compared with those at the contralateral site. A final diagnosis of primary lung adenocarcinoma was established by surgical resection. We performed BMS in 43 consecutive patients. Among patients with primary lung adenocarcinoma, the napsin A levels in ELF at the nodule site were markedly higher than those at the contralateral site, while there were no significant differences in CEA levels. Furthermore, in 18 patients who were undiagnosed by bronchoscopy and finally diagnosed by surgery, the napsin A levels in ELF at the nodule site were identically significantly higher than those at the contralateral site. In patients with non-adenocarcinoma, there were no differences in napsin A levels in ELF. The area under the receiver operator characteristic curve for identifying primary lung adenocarcinoma was 0.840 for napsin A and 0.542 for CEA. Evaluation of napsin A levels in ELF may be useful for distinguishing primary lung adenocarcinoma.

On the computed tomographic diagnosis of pulmonary nodules

International Nuclear Information System (INIS)

Higashi, Yuuichirou

1988-01-01

Computed tomography (CT) was used to examine 53 pulmonary nodules which were considered not definitely calcified on plain radiographs or conventional tomograms. An average CT number was calculate for each lesion. For the primary lung cancers, the average CT number was 36 HU with a standard deviation of 6.6 HU, while the benign lesions had the mean CT number of 69 HU, with a standard deviation of 42.8 HU. The mean CT number separating lung malignancies from benign lesions was 78.8 HU. To evaluate the attenuation values within each nodule, iso-CT value map was obtained by using Siemens therapy planning system, MEVAPLAN. Nodules were classified into five categories, Type I to V. All of three nodules classified as Type IV were benign. Iso-CT value map was effective in establishing the benignancy of nodules. The quantitative computed tomographic analysis of pulmonary nodules was evaluated by dual-energy CT. Dual-energy CT has the potential to eliminate the effect of spectral hardening by use of monoenergic images derived from dual-kV data and to separate high CT numbers due to calcium from those due to high density organic material. (author)

Automatic Lung-RADS™ classification with a natural language processing system.

Science.gov (United States)

Beyer, Sebastian E; McKee, Brady J; Regis, Shawn M; McKee, Andrea B; Flacke, Sebastian; El Saadawi, Gilan; Wald, Christoph

2017-09-01

Our aim was to train a natural language processing (NLP) algorithm to capture imaging characteristics of lung nodules reported in a structured CT report and suggest the applicable Lung-RADS™ (LR) category. Our study included structured, clinical reports of consecutive CT lung screening (CTLS) exams performed from 08/2014 to 08/2015 at an ACR accredited Lung Cancer Screening Center. All patients screened were at high-risk for lung cancer according to the NCCN Guidelines ® . All exams were interpreted by one of three radiologists credentialed to read CTLS exams using LR using a standard reporting template. Training and test sets consisted of consecutive exams. Lung screening exams were divided into two groups: three training sets (500, 120, and 383 reports each) and one final evaluation set (498 reports). NLP algorithm results were compared with the gold standard of LR category assigned by the radiologist. The sensitivity/specificity of the NLP algorithm to correctly assign LR categories for suspicious nodules (LR 4) and positive nodules (LR 3/4) were 74.1%/98.6% and 75.0%/98.8% respectively. The majority of mismatches occurred in cases where pulmonary findings were present not currently addressed by LR. Misclassifications also resulted from the failure to identify exams as follow-up and the failure to completely characterize part-solid nodules. In a sub-group analysis among structured reports with standardized language, the sensitivity and specificity to detect LR 4 nodules were 87.0% and 99.5%, respectively. An NLP system can accurately suggest the appropriate LR category from CTLS exam findings when standardized reporting is used.

Generation of realistic virtual nodules based on three-dimensional spatial resolution in lung computed tomography: A pilot phantom study.

Science.gov (United States)

Narita, Akihiro; Ohkubo, Masaki; Murao, Kohei; Matsumoto, Toru; Wada, Shinichi

2017-10-01

The aim of this feasibility study using phantoms was to propose a novel method for obtaining computer-generated realistic virtual nodules in lung computed tomography (CT). In the proposed methodology, pulmonary nodule images obtained with a CT scanner are deconvolved with the point spread function (PSF) in the scan plane and slice sensitivity profile (SSP) measured for the scanner; the resultant images are referred to as nodule-like object functions. Next, by convolving the nodule-like object function with the PSF and SSP of another (target) scanner, the virtual nodule can be generated so that it has the characteristics of the spatial resolution of the target scanner. To validate the methodology, the authors applied physical nodules of 5-, 7- and 10-mm-diameter (uniform spheres) included in a commercial CT test phantom. The nodule-like object functions were calculated from the sphere images obtained with two scanners (Scanner A and Scanner B); these functions were referred to as nodule-like object functions A and B, respectively. From these, virtual nodules were generated based on the spatial resolution of another scanner (Scanner C). By investigating the agreement of the virtual nodules generated from the nodule-like object functions A and B, the equivalence of the nodule-like object functions obtained from different scanners could be assessed. In addition, these virtual nodules were compared with the real (true) sphere images obtained with Scanner C. As a practical validation, five types of laboratory-made physical nodules with various complicated shapes and heterogeneous densities, similar to real lesions, were used. The nodule-like object functions were calculated from the images of these laboratory-made nodules obtained with Scanner A. From them, virtual nodules were generated based on the spatial resolution of Scanner C and compared with the real images of laboratory-made nodules obtained with Scanner C. Good agreement of the virtual nodules generated from

Lung nodules after whole lung radiation

International Nuclear Information System (INIS)

Cohen, M.D.; Mirkin, D.L.; Provisor, A.; Hornback, N.B.; Smith, J.A.; Slabaugh, R.D.

1983-01-01

It is essential to recognize radiation pneumonitis after whole lung irradiation, or nodular changes in response to chemotherapy, so that such conditions are not mistaken for tumor metastases, causing grave error in patient management and the possibility of further lung damage

Emphysema and soluble CD14 are associated with pulmonary nodules in HIV-infected patients: implications for lung cancer screening.

Science.gov (United States)

Triplette, Matthew; Sigel, Keith M; Morris, Alison; Shahrir, Shahida; Wisnivesky, Juan P; Kong, Chung Y; Diaz, Phillip T; Petraglia, Alycia; Crothers, Kristina

2017-07-31

Lung cancer screening may benefit HIV-infected (HIV) smokers because of an elevated risk of lung cancer, but may have unique harms because of HIV-specific risk factors for false-positive screens. This study seeks to understand whether inflammatory biomarkers and markers of chronic lung disease are associated with noncalcified nodules at least 4 mm (NCN) in HIV compared with uninfected patients. This is a cohort study of Examinations of HIV-Associated Lung Emphysema (EXHALE), including 158 HIV and 133 HIV-uninfected participants. Participants underwent a laboratory assessment [including measurement of D-dimer, interleukin 6, and soluble CD14 (sCD14)], chest computed tomography (CT), and pulmonary function testing. We created multivariable logistic regression models to determine predictors of NCN in the participants stratified by HIV status, with attention to semiqualitative scoring of radiographic emphysema, markers of pulmonary function, and inflammatory biomarkers. Of the 291 participants, 69 had NCN on chest CT. As previously reported, there was no difference in prevalence of these nodules by HIV status. Emphysema and elevated sCD14 demonstrated an association with NCN in HIV participants independent of smoking status, CD4 cell count, HIV viral load, and pulmonary function. Emphysema and sCD14, a marker of immune activation, was associated with a higher prevalence of NCN on chest CT in HIV participants. Patients with chronic immune activation and emphysema may be at higher risk for both false-positive findings and incident lung cancer, thus screening in this group requires further study to understand the balance of benefits and harms.

Preliminary study of diagnostic workstation with different matrix size for detection of small pulmonary nodules

International Nuclear Information System (INIS)

Wu Jie; Wang Xuejian; Wang Bo; Tong Juan; Wei Yuqing; Shen Guiquan; Wang Limei; Cao Jun; Sui He

2004-01-01

Objective: To assess the influence in detecting small pulmonary nodules (SPNs) on soft-copy images displayed with different matrix sizes. Methods: Seventy-six chest compute radiographs were selected for the study. Of the 76 test images, 36 pulmonary nodules smaller than 20 mm in diameter were proven by CT, which were further divided into two groups: 1.0-2.0 cm and Z values and standard error of three kinds of view system for individual observers. Results: For 1.0-2.0 cm group, the mean A Z values were 0.7936 for DRCS with 2-fold magnification and window technique, 0.8225 for 1 K monitor with 2-fold magnification and window technique, and 0.8367 for 2 K monitor without magnification; for Z values increased slightly as the display matrix size improved, but there were no significant differences among the three sets in the detection of SPNs in the ROC analyses. Conclusion: It is acceptable to detect small pulmonary nodules of 1.0-2.0 cm in diameter on 1 K monitor and DRCS with magnification. High resolution diagnostic workstation is recommended for detecting small pulmonary nodules <1.0 cm in diameter. Reasonable equipment for the detection of subtle abnormality may result in better cost-efficacy and diagnostic accuracy

Atypical adenomatous hyperplasia of the lung: correlation between high-resolution CT findings and histopathologic features

International Nuclear Information System (INIS)

Kawakami, S.; Takashima, S.; Li, F.; Yang, Z.G.; Maruyama, Y.; Hasegawa, M.; Wang, J.C.; Sone, S.; Honda, T.

2001-01-01

We describe herein the CT features of atypical adenomatous hyperplasia (AAH) of the lung and its histopathological characteristics. Among 17,919 individuals screened for lung cancer by CT scanning, ten AAH nodules were detected in nine asymptomatic subjects. On high-resolution CT, the lesions measured from 6 x 6 mm to 15 x 17 mm and their CT number ranged from -500 to -760 HU. The AAHs appeared as round nodules with smooth and distinct borders and showed a ground-glass opacity. Plain chest radiographs failed to identify all lesions. Histopathologically, AAH lesions showed atypical epithelial cell proliferation along slightly thickened alveolar septa. Whereas it is often easy to differentiate these nodules from inflammatory and benign lung lesions, histopathological examination remains at present the only method to differentiate AAH from lung cancers. (orig.)

Atypical adenomatous hyperplasia of the lung: correlation between high-resolution CT findings and histopathologic features

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Kawakami, S.; Takashima, S.; Li, F.; Yang, Z.G.; Maruyama, Y.; Hasegawa, M.; Wang, J.C. [Dept. of Radiology, Shinshu University School of Medicine, Matsumoto (Japan); Sone, S. [Dept. of Radiology, Shinshu University School of Medicine, Matsumoto (Japan); Azumi General Hospital, Ikeda, Nagano (Japan); Honda, T. [Dept. of Laboratory Medicine, Shinshu University School of Medicine, Matsumoto (Japan)

2001-05-01

We describe herein the CT features of atypical adenomatous hyperplasia (AAH) of the lung and its histopathological characteristics. Among 17,919 individuals screened for lung cancer by CT scanning, ten AAH nodules were detected in nine asymptomatic subjects. On high-resolution CT, the lesions measured from 6 x 6 mm to 15 x 17 mm and their CT number ranged from -500 to -760 HU. The AAHs appeared as round nodules with smooth and distinct borders and showed a ground-glass opacity. Plain chest radiographs failed to identify all lesions. Histopathologically, AAH lesions showed atypical epithelial cell proliferation along slightly thickened alveolar septa. Whereas it is often easy to differentiate these nodules from inflammatory and benign lung lesions, histopathological examination remains at present the only method to differentiate AAH from lung cancers. (orig.)

Lung nodule assessment in computed tomography. Precision of attenuation measurement based on computer-aided volumetry

International Nuclear Information System (INIS)

Knoess, Naomi; Hoffmann, B.; Fabel, M.; Wiese, C.; Bolte, H.; Heller, M.; Biederer, J.; Jochens, A.

2009-01-01

Purpose: to compare the reproducibility (r) of CT value measurement of pulmonary nodules using volumetry software (LungCare, LC) and manual ROIs (mROI). Materials and methods: 54 artificial nodules in a chest phantom were scanned three times with CT. CT values were measured with LC and mROI. The intrascan-r was assessed with three measurements in the first scan, and the interscan-r with measurements in three consecutive scans (one observer). Intrascan-r und interobserver-r (two obs.) were assessed in the first scan and in contrast-enhanced CT of 51 nodules from 15 patients (kernels b50f and b80f). Intrascan-r and interscan-r were described as the mean range and interobserver-r as the mean difference of CT values. The significance of differences was tested using t-test and sign test. Results: reproducibility was significantly higher for volumetry-based measurements in both artificial and patient nodules (range 0.11 vs. 6.16 HU for intrascan-r, 2.22 vs. 7.03 HU for interscan-r, difference 0.11 vs. 18.42 HU for interobserver-r; patients: 1.78 vs. 13.19 HU (b50f-Kernel) and 1.88 vs. 27.4 HU (b80f-Kernel) for intrascan-r, 3.71 vs. 22.43 HU for interobserver-r). Absolute CT values differed significantly between convolution kernels (pat./mROI: 29.3 [b50f] and 151.9 HU [b80f] pat./LC: 5 [b50f] and 147 HU [b80f]). Conclusion: the reproducibility of volumetry-based measurements of CT values in pulmonary nodules is significantly higher and should therefore be recommended, e.g. in dynamic chest CT protocols. Reproducibility does not depend on absolute CT values. (orig.)

CT-guided marking of pulmonary nodules with a special lung marking wire before video-assisted thoracoscopic surgery. Review of 184 cases; CT-gestuetzte Drahtmarkierung vor videoassistierter thorakoskopischer OP von pulmonalen Rundherden. Eine Auswertung von 184 Faellen

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Schulze, M.K.; Eichfeld, U.; Kahn, T.; Stumpp, P. [Universitaetsklinikum Leipzig AoeR (Germany). Klinik und Poliklinik fuer Diagnostische und Interventionelle Radiologie

2012-06-15

Purpose: Minimally invasive techniques like video-assisted thoracoscopic surgery (VATS) are currently the method of choice for the resection of small pulmonary nodules, when they are located in the periphery of the lungs. To guarantee quick and safe intraoperative identification of the nodule, preoperative marking is necessary and sensible. We report about our experiences in 184 markings with a special lung marking wire, which is placed in or around the pulmonary nodule using CT guidance. Materials and Methods: In 184 patients (97 m, 87f, mean age: 58.1 {+-} 13.7 years) with pulmonary nodules, scheduled for resection with VATS, a special lung marking wire was placed preoperatively under CT guidance. We evaluated the technical success, safety, necessity of conversion to thoracotomy and histology in all patients. Results: The marking wire could be positioned successfully in 181 cases (98.4 %). There was one major complication (uncontrollable pneumothorax). Minor adverse events like small pneumothorax (53.3 %) or a perifocal bleeding (30.4 %) did not necessitate treatment. Complete resection of the marked nodule was successful in 98.4 % of the patients. Conversion to thoracotomy was necessary in 29 patients (15.9 %) due to bleeding, adhesions, malignancy or wire dislocation. Histology revealed a benign nodule in 96 cases (54.4 %) and a malignant lesion in 78 cases (45.6 %), of which only 21 nodules (11.5 %) turned out to present a primary pulmonary carcinoma. Conclusion: CT-guided marking of pulmonary nodules using a special marking wire followed by thoracoscopic resection is an efficient and safe method for diagnosing suspicious nodules in the periphery of the lung. (orig.)

Differential diagnosis of a solitary pulmonary nodule of the lung on the grounds of selected laboratory tests and radiological examination

International Nuclear Information System (INIS)

Szlachcinska, A.; Kozak, J.

2011-01-01

Objective: To present in detail the diagnosis of solitary pulmonary nodule and especially evaluation of: clinical data, analysis of radiological images, selected laboratory tests. Material and methods: There were 50 patients - 31 men and 19 women at the mean age 58.7 ± 11.4 years old who underwent surgical treatment because of a solitary pulmonary nodule. Interview, physical examination, computed tomography, bronchoscopy, spirometry, and laboratory tests needed for the operation were performed in all these patients. Additionally LDH, fibrinogen, ESR, and the tumour markers CEA, Ca 15-3, Ca 19-9, NSE, SCC, and Cyfra 21-1 were measured from the blood sample collected during admission. Results: Malignant tumour was diagnosed in 24 patients, benign in 26. There is a significant difference between patients with malignant and nonmalignant tumours in age (54.46 years vs. 63.33 years), size of the tumour in the lung scan of chest CT (1.53 cm vs. 1.91 cm) and location (lower right lobe vs. upper right lobe). There is no significant difference between type of tumour and sex, clinical symptoms and laboratory tests. Conclusions: 1. The risk factors of malignancy in patient with solitary pulmonary nodule are: age ≥ 56.5 years, size of the tumour in the lung scan of chest CT ≥ 1.45 cm, location in upper right lobe. 2. LDH, fibrinogen, ESR, and the tumour markers CEA, Ca 15-3, Ca 19-9, NSE, SCC, and Cyfra 21-1 are not useful in differential diagnosis of solitary pulmonary nodule. (authors)

The impact of faceplate surface characteristics on detection of pulmonary nodules

Science.gov (United States)

Toomey, R. J.; Ryan, J. T.; McEntee, M. F.; McNulty, J.; Evanoff, M. G.; Cuffe, F.; Yoneda, T.; Stowe, J.; Brennan, P. C.

2009-02-01

Introduction In order to prevent specular reflections, many monitor faceplates have features such as tiny dimples on their surface to diffuse ambient light incident on the monitor, however, this "anti-glare" surface may also diffuse the image itself. The purpose of the study was to determine whether the surface characteristics of monitor faceplates influence the detection of pulmonary nodules under low and high ambient lighting conditions. Methods and Materials Separate observer performance studies were conducted at each of two light levels (250 lux). Twelve examining radiologists with the American Board of Radiology participated in the darker condition and eleven in the brighter condition. All observers read on both smooth "glare" and dimpled "anti-glare" faceplates in a single lighting condition. A counterbalanced methodology was utilized to minimise memory effects. In each reading, observers were presented with thirty chest images in random order, of which half contained a single simulated pulmonary nodule. They were asked to give their confidence that each image did or did not contain a nodule and to mark the suspicious location. ROC analysis was applied to resultant data. Results No statistically significant differences were seen in the trapezoidal area under the ROC curve (AUC), sensitivity, specificity or average time per case at either light level for chest specialists or radiologists from other specialities. Conclusion The characteristics of the faceplate surfaces do not appear to affect detection of pulmonary nodules. Further work into other image types is being conducted.

Radio-guided thoracoscopic surgery (RGTS) of small pulmonary nodules.

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Ambrogi, Marcello Carlo; Melfi, Franca; Zirafa, Carmelina; Lucchi, Marco; De Liperi, Annalisa; Mariani, Giuliano; Fanucchi, Olivia; Mussi, Alfredo

2012-04-01

The demand for adequate tissue sampling to determine individual tumor behavior is increasing the number of lung nodule resections, even when the diagnosis is already recognized. Video-assisted thoracic surgery (VATS) is the procedure of choice for diagnosis and treatment of small pulmonary nodules. Difficulties in localizing smaller and deeper nodules have been approached with different techniques. Herein we report our 13-years' experience with radio-guided thoracoscopic resection. Patients with pulmonary nodules smaller than 1 cm and/or deeper than 1 cm, below the visceral pleura, underwent computed tomography (CT)-guided injection of a solution, composed of 0.2 ml (99)Tc-labeled human serum albumin microspheres and 0.1 ml nonionic contrast, into the nodule. During the VATS procedure, an 11-mm-diameter collimated probe connected to a gamma ray detector was introduced to scan the lung surface. The area of major radioactivity, which matched with the area of the nodule, was resected. From 1997 to 2009, 573 patients underwent thoracoscopic resection of small pulmonary nodules, 211 with the radio-guided technique. There were 159 men and 52 women, with an average age of 60.6 years (range = 12-83). The mean duration of the surgical procedure was 41 min (range = 20-100). The procedure was successful in 208/211 cases. Three patients (0.5%) required conversion to a minithoracotomy. The mean length of pleural drainage and hospital stay was 2.3 and 3.7 days, respectively. Histological examination showed 98 benign lesions and 113 malignant lesions (61 metastases and 52 primary lung cancers). This study confirms that radio-guided localization of small pulmonary nodules is a feasible, safe, and quick procedure, with a high rate of success. The spread of the sentinel lymph node technique has increased the availability of technology required for RGTS.

Telomerase in lung cancer diagnostics

International Nuclear Information System (INIS)

Kovkarova, E.; Stefanovski, T.; Dimov, A.; Naumovski, J.

2003-01-01

Background. Telomerase is a ribonucleoprotein that looks after the telomeric cap of the linear chromosomes maintaining its length. It is over expressed in tumour tissues, but not in normal somatic cells. Therefore the aim of this study was to determine the telomerase activity in lung cancer patients as novel marker for lung cancer detection evaluating the influence of tissue/cell obtaining technique. Material and methods. Using the TRAP (telomeric repeat amplification protocol), telomerase activity was determined in material obtained from bronchobiopsy (60 lung cancer patients compared with 20 controls) and washings from transthoracic fine needle aspiration biopsy performed in 10 patients with peripheral lung tumours. Results. Telomerase activity was detected in 75% of the lung cancer bronchobyopsies, and in 100% in transthoracic needle washings. Conclusions. Measurement of telomerase activity can contribute in fulfilling the diagnosis of lung masses and nodules suspected for lung cancer. (author)

Incidentally detection of non-palpable testicular nodules at scrotal ultrasound: What is new?

Directory of Open Access Journals (Sweden)

Massimo Valentino

2014-12-01

Full Text Available The increased use of ultrasound in patients with urological and andrological symptoms has given an higher detection of intra-testicular nodules. Most of these lesions are hypoechoic and their interpretation is often equivocal. Recently, new ultrasound techniques have been developed alongside of B-mode and color-Doppler ultrasound. Although not completely standardized, contrast-enhanced ultrasound (CEUS and tissue elastography (TE, added to traditional ultrasonography, can provide useful information about the correct interpretation of incidentally detected non-palpable testicular nodules. The purpose of this review article is to illustrate these new techniques in the patient management.

Spatial resolution and chest nodule detection: an interesting incidental finding

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Toomey, R. J.; McEntee, M. F.; Ryan, J. T.; Evanoff, M. G.; Hayes, A.; Brennan, P. C.

2010-02-01

This study reports an incidental finding from a larger work. It examines the relationship between spatial resolution and nodule detection for chest radiographs. Twelve examining radiologists with the American Board of Radiology read thirty chest radiographs in two conditions - full (1500 × 1500 pixel) resolution, and 300 × 300 pixel resolution linearly interpolated to 1500 × 1500 pixels. All images were surrounded by a 10-pixel sharp grey border to aid in focussing the observer's eye when viewing the comparatively unsharp interpolated images. Fifteen of the images contained a single simulated pulmonary nodule. Observers were asked to rate their confidence that a nodule was present on each radiograph on a scale of 1 (least confidence, certain no lesion is present) to 6 (most confidence, certain a lesion was present). All other abnormalities were to be ignored. No windowing, levelling or magnification of the images was permitted and viewing distance was constrained to approximately 70cm. Images were displayed on a 3 megapixel greyscale monitor. Receiver operating characteristic (ROC) analysis was applied to the results of the readings using the Dorfman-Berbaum-Metz multiplereader, multiple-case method. No statistically significant differences were found with either readers and cases treated as random or with cases treated as fixed. Low spatial frequency information appears to be sufficient for the detection of chest lesion of the type used in this study.

Development of a world wide web-based interactive education program to improve detectability of pulmonary nodules on chest radiographs

International Nuclear Information System (INIS)

Ohm, Joon Young; Kim, Jin Hwan; Kim, Sung Soo; Han, Ki Tae; Ahn, Young Seob; Shin, Byung Seok; Bae, Kyongtae T.

2007-01-01

To design and develop a World Wide Web-based education program that will allow trainees to interactively learn and improve the diagnostic capability of detecting pulmonary nodules on chest radiographs. Chest radiographs with known diagnosis were retrieved and selected from our institutional clinical archives. A database was constructed by sorting radiographs into three groups: normal, nodule, and false positive (i.e., nodule-like focal opacity). Each nodule was assigned with the degree of detectability: easy, intermediate, difficult, and likely missed. Nodules were characterized by their morphology (well-defined, ill-defined, irregular, faint) and by other associated pathologies or potentially obscuring structures. The Web site was organized into four sections: study, test, record and information. The Web site allowed a user interactively to undergo the training section appropriate to the user's diagnostic capability. The training was enhanced by means of clinical and other pertinent radiological findings included in the database. The outcome of the training was tested with clinical test radiographs that presented nodules or false positives with varying diagnostic difficulties. A World Wide Web-based education program is a promising technique that would allow trainees to interactively learn and improve the diagnostic capability of detecting and characterizing pulmonary nodules

Sublobar resection is equivalent to lobectomy for clinical stage 1A lung cancer in solid nodules.

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Altorki, Nasser K; Yip, Rowena; Hanaoka, Takaomi; Bauer, Thomas; Aye, Ralph; Kohman, Leslie; Sheppard, Barry; Thurer, Richard; Andaz, Shahriyour; Smith, Michael; Mayfield, William; Grannis, Fred; Korst, Robert; Pass, Harvey; Straznicka, Michaela; Flores, Raja; Henschke, Claudia I

2014-02-01

A single randomized trial established lobectomy as the standard of care for the surgical treatment of early-stage non-small cell lung cancer. Recent advances in imaging/staging modalities and detection of smaller tumors have once again rekindled interest in sublobar resection for early-stage disease. The objective of this study was to compare lung cancer survival in patients with non-small cell lung cancer with a diameter of 30 mm or less with clinical stage 1 disease who underwent lobectomy or sublobar resection. We identified 347 patients diagnosed with lung cancer who underwent lobectomy (n = 294) or sublobar resection (n = 53) for non-small cell lung cancer manifesting as a solid nodule in the International Early Lung Cancer Action Program from 1993 to 2011. Differences in the distribution of the presurgical covariates between sublobar resection and lobectomy were assessed using unadjusted P values determined by logistic regression analysis. Propensity scoring was performed using the same covariates. Differences in the distribution of the same covariates between sublobar resection and lobectomy were assessed using adjusted P values determined by logistic regression analysis with adjustment for the propensity scores. Lung cancer-specific survival was determined by the Kaplan-Meier method. Cox survival regression analysis was used to compare sublobar resection with lobectomy, adjusted for the propensity scores, surgical, and pathology findings, when adjusted and stratified by propensity quintiles. Among 347 patients, 10-year Kaplan-Meier for 53 patients treated by sublobar resection compared with 294 patients treated by lobectomy was 85% (95% confidence interval, 80-91) versus 86% (confidence interval, 75-96) (P = .86). Cox survival analysis showed no significant difference between sublobar resection and lobectomy when adjusted for propensity scores or when using propensity quintiles (P = .62 and P = .79, respectively). For those with cancers 20 mm or less in

TH-CD-207B-10: Effect of CT Reconstruction Filter On Measured Hounsfield Values in Lung Nodules

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Little, K; Reiser, I; Sanchez, A; Chung, J; MacMahon, H; Lu, Z [The University of Chicago, Chicago, IL (United States)

2016-06-15

Purpose: Measured Hounsfield numbers in CT are used by radiologists to determine the presence of calcium or fat in lung nodules, either of which suggests a benign diagnosis. However, substantial variations in Hounsfield number may arise due to the use of different reconstruction parameters such as the filter/kernel, leading to measurement inaccuracies. This quality improvement project was developed to demonstrate measurement pitfalls and to identify acceptable conditions for incorporating Hounsfield values as a factor in lung nodule diagnosis. Methods: 12 mm-diameter spheres of polyurethane and urethane foam were placed into an anthropomorphic chest phantom, and 10 mm-diameter tubes with varying iodine concentrations were placed into a 16 cm PMMA cylindrical phantom. Additionally, 11 mm-diameter PMMA and HDPE spheres were placed in a 10 cm PMMA cylindrical phantom. Phantoms were scanned at 120 kVp using a Siemens Biograph mCT and on a Philips iCT and reconstructed using various reconstruction filters. Results: For the Siemens system, both sharp kernels and smooth kernels altered the Hounsfield numbers. Hounsfield numbers varied within a range of 8.9 HU for urethane foam and varied within 58.7 HU for polyurethane. The iodine measurements varied up to 37.9 HU for the lowest concentration. For the Philips system, Hounsfield numbers were relatively consistent but were higher for the “Detail” and “Lung Enhanced” filters, varying by 36.9 HU for PMMA and 15.9 HU for HDPE. Conclusion: Reconstruction filters can change the measured Hounsfield numbers of nodular objects, especially with detail-enhancing (sharpening) filters commonly used in lung imaging. Measured values should only be used for diagnostic decision support with filters that have demonstrated accuracy and consistency. While filter accuracy statements are available from manufacturers, radiologists are likely not aware of the extent of potential variations that can occur in a clinical setting.

Benign metastasizing leiomyoma presenting as multiple cystic pulmonary nodules: a case report.

Science.gov (United States)

Choe, Yeong Hun; Jeon, So Yeon; Lee, Yoon Chae; Chung, Myung Ja; Park, Seung Yong; Lee, Yong Chul; Kim, So Ri

2017-09-12

Benign metastatic leiomyoma (BML) is an extremely rare disease. Although uterine leiomyomas are benign histologically, they can metastasize to distant sites. While the incidence is very low, the lung is the organ most frequently affected by BML. Pulmonary BML usually presents as numerous well-defined nodules of various sizes, while the cavitary or cystic features in the nodules are rarely observed on radiologic images. A 52-year-old woman complained of cough and dyspnea for one month. She had been previously diagnosed with uterine leiomyoma and had undergone total hysterectomy about 14 years prior. High-resolution computed tomography (CT) images showed that there were multiple cystic nodules of various sizes in both lungs. Pathologic examination revealed that the pulmonary nodule had complex branching glandular structures lined by a single layer of simple cuboidal to columnar epithelium that was surrounded by abundant spindle cells. Additional immunohistochemistry data suggested that pulmonary nodule diagnosis was BML-associated uterine leiomyoma. In this report, we introduce an interesting case of pulmonary BML that presented as a combination of various kinds of nodules including simple round nodules, simple cysts, and cysts with a solid portion, which are very rare radiologic features of BML in lung. In addition, when the patient is a woman of reproductive age, physicians should meticulously review the gynecological history and suspect BML when there are various cystic pulmonary lesions.

Computerized comprehensive data analysis of Lung Imaging Database Consortium (LIDC)

International Nuclear Information System (INIS)

Tan Jun; Pu Jiantao; Zheng Bin; Wang Xingwei; Leader, Joseph K.

2010-01-01

Purpose: Lung Image Database Consortium (LIDC) is the largest public CT image database of lung nodules. In this study, the authors present a comprehensive and the most updated analysis of this dynamically growing database under the help of a computerized tool, aiming to assist researchers to optimally use this database for lung cancer related investigations. Methods: The authors developed a computer scheme to automatically match the nodule outlines marked manually by radiologists on CT images. A large variety of characteristics regarding the annotated nodules in the database including volume, spiculation level, elongation, interobserver variability, as well as the intersection of delineated nodule voxels and overlapping ratio between the same nodules marked by different radiologists are automatically calculated and summarized. The scheme was applied to analyze all 157 examinations with complete annotation data currently available in LIDC dataset. Results: The scheme summarizes the statistical distributions of the abovementioned geometric and diagnosis features. Among the 391 nodules, (1) 365 (93.35%) have principal axis length ≤20 mm; (2) 120, 75, 76, and 120 were marked by one, two, three, and four radiologists, respectively; and (3) 122 (32.48%) have the maximum volume overlapping ratios ≥80% for the delineations of two radiologists, while 198 (50.64%) have the maximum volume overlapping ratios <60%. The results also showed that 72.89% of the nodules were assessed with malignancy score between 2 and 4, and only 7.93% of these nodules were considered as severely malignant (malignancy ≥4). Conclusions: This study demonstrates that LIDC contains examinations covering a diverse distribution of nodule characteristics and it can be a useful resource to assess the performance of the nodule detection and/or segmentation schemes.

3D Convolutional Neural Network for Automatic Detection of Lung Nodules in Chest CT.

Science.gov (United States)

Hamidian, Sardar; Sahiner, Berkman; Petrick, Nicholas; Pezeshk, Aria

2017-01-01

Deep convolutional neural networks (CNNs) form the backbone of many state-of-the-art computer vision systems for classification and segmentation of 2D images. The same principles and architectures can be extended to three dimensions to obtain 3D CNNs that are suitable for volumetric data such as CT scans. In this work, we train a 3D CNN for automatic detection of pulmonary nodules in chest CT images using volumes of interest extracted from the LIDC dataset. We then convert the 3D CNN which has a fixed field of view to a 3D fully convolutional network (FCN) which can generate the score map for the entire volume efficiently in a single pass. Compared to the sliding window approach for applying a CNN across the entire input volume, the FCN leads to a nearly 800-fold speed-up, and thereby fast generation of output scores for a single case. This screening FCN is used to generate difficult negative examples that are used to train a new discriminant CNN. The overall system consists of the screening FCN for fast generation of candidate regions of interest, followed by the discrimination CNN.

Solitary pulmonary nodule and {sup 18}F-FDG PET/CT. Part 2: accuracy, cost-effectiveness, and current recommendations

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Mosmann, Marcos Pretto; Borba, Marcelle Alves; Macedo, Francisco Pires Negromonte de; Liguori, Adriano de Araujo Lima; Villarim Neto, Arthur [Liga Norte-Riograndense Contra o Cancer, Natal, RN (Brazil); Lima, Kenio Costa de, E-mail: mosmann@gmail.com [Universidade Federal do Rio Grande do Norte (UFRN), Natal, RN (Brazil). Programa de Pos-Graduacao em Saude Coletiva

2016-03-15

A solitary pulmonary nodule is a common, often incidental, radiographic finding. The investigation and differential diagnosis of solitary pulmonary nodules remain complex, because there are overlaps between the characteristics of benign and malignant processes. There are currently many strategies for evaluating solitary pulmonary nodules. The main objective is to identify benign lesions, in order to avoid exposing patients to the risks of invasive methods, and to detect cases of lung cancer accurately, in order to avoid delaying potentially curative treatment. The focus of this study was to review the evaluation of solitary pulmonary nodules, to discuss the current role of {sup 18}F fluorodeoxyglucose positron-emission tomography, addressing its accuracy and cost-effectiveness, and to detail the current recommendations for the examination in this scenario. (author)

Robust semi-automatic segmentation of pulmonary subsolid nodules in chest computed tomography scans

International Nuclear Information System (INIS)

Lassen, B C; Kuhnigk, J-M; Van Ginneken, B; Van Rikxoort, E M; Jacobs, C

2015-01-01

The malignancy of lung nodules is most often detected by analyzing changes of the nodule diameter in follow-up scans. A recent study showed that comparing the volume or the mass of a nodule over time is much more significant than comparing the diameter. Since the survival rate is higher when the disease is still in an early stage it is important to detect the growth rate as soon as possible. However manual segmentation of a volume is time-consuming. Whereas there are several well evaluated methods for the segmentation of solid nodules, less work is done on subsolid nodules which actually show a higher malignancy rate than solid nodules. In this work we present a fast, semi-automatic method for segmentation of subsolid nodules. As minimal user interaction the method expects a user-drawn stroke on the largest diameter of the nodule. First, a threshold-based region growing is performed based on intensity analysis of the nodule region and surrounding parenchyma. In the next step the chest wall is removed by a combination of a connected component analyses and convex hull calculation. Finally, attached vessels are detached by morphological operations. The method was evaluated on all nodules of the publicly available LIDC/IDRI database that were manually segmented and rated as non-solid or part-solid by four radiologists (Dataset 1) and three radiologists (Dataset 2). For these 59 nodules the Jaccard index for the agreement of the proposed method with the manual reference segmentations was 0.52/0.50 (Dataset 1/Dataset 2) compared to an inter-observer agreement of the manual segmentations of 0.54/0.58 (Dataset 1/Dataset 2). Furthermore, the inter-observer agreement using the proposed method (i.e. different input strokes) was analyzed and gave a Jaccard index of 0.74/0.74 (Dataset 1/Dataset 2). The presented method provides satisfactory segmentation results with minimal observer effort in minimal time and can reduce the inter-observer variability for segmentation of

Robust semi-automatic segmentation of pulmonary subsolid nodules in chest computed tomography scans

Science.gov (United States)

Lassen, B. C.; Jacobs, C.; Kuhnigk, J.-M.; van Ginneken, B.; van Rikxoort, E. M.

2015-02-01

The malignancy of lung nodules is most often detected by analyzing changes of the nodule diameter in follow-up scans. A recent study showed that comparing the volume or the mass of a nodule over time is much more significant than comparing the diameter. Since the survival rate is higher when the disease is still in an early stage it is important to detect the growth rate as soon as possible. However manual segmentation of a volume is time-consuming. Whereas there are several well evaluated methods for the segmentation of solid nodules, less work is done on subsolid nodules which actually show a higher malignancy rate than solid nodules. In this work we present a fast, semi-automatic method for segmentation of subsolid nodules. As minimal user interaction the method expects a user-drawn stroke on the largest diameter of the nodule. First, a threshold-based region growing is performed based on intensity analysis of the nodule region and surrounding parenchyma. In the next step the chest wall is removed by a combination of a connected component analyses and convex hull calculation. Finally, attached vessels are detached by morphological operations. The method was evaluated on all nodules of the publicly available LIDC/IDRI database that were manually segmented and rated as non-solid or part-solid by four radiologists (Dataset 1) and three radiologists (Dataset 2). For these 59 nodules the Jaccard index for the agreement of the proposed method with the manual reference segmentations was 0.52/0.50 (Dataset 1/Dataset 2) compared to an inter-observer agreement of the manual segmentations of 0.54/0.58 (Dataset 1/Dataset 2). Furthermore, the inter-observer agreement using the proposed method (i.e. different input strokes) was analyzed and gave a Jaccard index of 0.74/0.74 (Dataset 1/Dataset 2). The presented method provides satisfactory segmentation results with minimal observer effort in minimal time and can reduce the inter-observer variability for segmentation of

Computer-assisted solid lung nodule 3D volumetry on CT. Influence of scan mode and iterative reconstruction. A CT phantom study

International Nuclear Information System (INIS)

Coenen, Adriaan; Honda, Osamu; Tomiyama, Noriyuki; Jagt, Eric J. van der

2013-01-01

The objective of this study was to evaluate the effect of high-resolution scan mode and iterative reconstruction on lung nodule 3D volumetry. Solid nodules with various sizes (5, 8, 10 and 12 mm) were placed inside a chest phantom. CT images were obtained with various tube currents, scan modes (conventional mode, high-resolution mode) and iterative reconstructions [0, 50 and 100% blending of adaptive statistical iterative reconstruction (ASiR) and filtered back projection]. The nodule volumes were calculated using semiautomatic software and compared with the assumed volume from the nodules. The mean absolute and relative percentage error improved when using iterative reconstruction especially when using the conventional scan mode; however, this effect was not significant. Significant reduction in volume overestimation was observed when using high-resolution scan mode (P=0.011). The high-resolution mode significantly reduces the volume overestimation of 3D volumetry. Iterative reconstruction shows a reduction in volume overestimation and error margin especially with the conventional scan mode; however, this effect was not significant. (author)

[Lung abscess which needed to be distinguished from lung cancer; report of a case].

Science.gov (United States)

Kamiya, Kazunori; Yoshizu, Akira; Misumi, Yuki; Hida, Naoya; Okamoto, Hiroaki; Yoshida, Sachiko

2011-12-01

Differential diagnosis of lung abscess from lung cancer is sometimes difficult. In February 2009, a 57-year-old man consulted our hospital complaining of bloody sputum. Chest computed tomography (CT) demonstrated a 2.5 cm nodule with pleural indentation, spicula and vascular involvement in the right S(3). Bronchofiberscope could not establish a definitive diagnosis. Blood test showed no abnormality. Three months later, progression of the nodule to the adjacent middle lobe was demonstrated by follow-up CT, and F-18 fluorodeoxyglucose positron emission tomography (FDG-PET) showed isotope accumulation in the nodule and hilar lymph node. A diagnosis of lung cancer was suspected and surgery was performed. The diagnosis of possible lung cancer was made by needle biopsy, and the patient underwent right upper lobectomy and partial resection of middle lobe with standard nodal dissection. The final pathological diagnosis was lung abscess. Lung abscess must be kept in mind as a possible differential diagnosis when abnormal shadow suspected of lung cancer is observed.

A Comparison of Two Commercial Volumetry Software Programs in the Analysis of Pulmonary Ground-Glass Nodules: Segmentation Capability and Measurement Accuracy

Science.gov (United States)

Kim, Hyungjin; Lee, Sang Min; Lee, Hyun-Ju; Goo, Jin Mo

2013-01-01

Objective To compare the segmentation capability of the 2 currently available commercial volumetry software programs with specific segmentation algorithms for pulmonary ground-glass nodules (GGNs) and to assess their measurement accuracy. Materials and Methods In this study, 55 patients with 66 GGNs underwent unenhanced low-dose CT. GGN segmentation was performed by using 2 volumetry software programs (LungCARE, Siemens Healthcare; LungVCAR, GE Healthcare). Successful nodule segmentation was assessed visually and morphologic features of GGNs were evaluated to determine factors affecting segmentation by both types of software. In addition, the measurement accuracy of the software programs was investigated by using an anthropomorphic chest phantom containing simulated GGNs. Results The successful nodule segmentation rate was significantly higher in LungCARE (90.9%) than in LungVCAR (72.7%) (p = 0.012). Vascular attachment was a negatively influencing morphologic feature of nodule segmentation for both software programs. As for measurement accuracy, mean relative volume measurement errors in nodules ≥ 10 mm were 14.89% with LungCARE and 19.96% with LungVCAR. The mean relative attenuation measurement errors in nodules ≥ 10 mm were 3.03% with LungCARE and 5.12% with LungVCAR. Conclusion LungCARE shows significantly higher segmentation success rates than LungVCAR. Measurement accuracy of volume and attenuation of GGNs is acceptable in GGNs ≥ 10 mm by both software programs. PMID:23901328

A comparison of two commercial volumetry software programs in the analysis of pulmonary ground-glass nodules: Segmentation capability and measurement accuracy

International Nuclear Information System (INIS)

Kim, Hyung Jin; Park, Chang Min; Lee, Sang Min; Lee, Hyun Joo; Goo, Jin Mo

2013-01-01

To compare the segmentation capability of the 2 currently available commercial volumetry software programs with specific segmentation algorithms for pulmonary ground-glass nodules (GGNs) and to assess their measurement accuracy. In this study, 55 patients with 66 GGNs underwent unenhanced low-dose CT. GGN segmentation was performed by using 2 volumetry software programs (LungCARE, Siemens Healthcare; LungVCAR, GE Healthcare). Successful nodule segmentation was assessed visually and morphologic features of GGNs were evaluated to determine factors affecting segmentation by both types of software. In addition, the measurement accuracy of the software programs was investigated by using an anthropomorphic chest phantom containing simulated GGNs. The successful nodule segmentation rate was significantly higher in LungCARE (90.9%) than in LungVCAR (72.7%) (p = 0.012). Vascular attachment was a negatively influencing morphologic feature of nodule segmentation for both software programs. As for measurement accuracy, mean relative volume measurement errors in nodules ≥ 10 mm were 14.89% with LungCARE and 19.96% with LungVCAR. The mean relative attenuation measurement errors in nodules ≥ 10 mm were 3.03% with LungCARE and 5.12% with LungVCAR. LungCARE shows significantly higher segmentation success rates than LungVCAR. Measurement accuracy of volume and attenuation of GGNs is acceptable in GGNs ≥ 10 mm by both software programs.

A comparison of two commercial volumetry software programs in the analysis of pulmonary ground-glass nodules: Segmentation capability and measurement accuracy

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Kim, Hyung Jin; Park, Chang Min; Lee, Sang Min; Lee, Hyun Joo; Goo, Jin Mo [Dept. of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul (Korea, Republic of)

2013-08-15

To compare the segmentation capability of the 2 currently available commercial volumetry software programs with specific segmentation algorithms for pulmonary ground-glass nodules (GGNs) and to assess their measurement accuracy. In this study, 55 patients with 66 GGNs underwent unenhanced low-dose CT. GGN segmentation was performed by using 2 volumetry software programs (LungCARE, Siemens Healthcare; LungVCAR, GE Healthcare). Successful nodule segmentation was assessed visually and morphologic features of GGNs were evaluated to determine factors affecting segmentation by both types of software. In addition, the measurement accuracy of the software programs was investigated by using an anthropomorphic chest phantom containing simulated GGNs. The successful nodule segmentation rate was significantly higher in LungCARE (90.9%) than in LungVCAR (72.7%) (p = 0.012). Vascular attachment was a negatively influencing morphologic feature of nodule segmentation for both software programs. As for measurement accuracy, mean relative volume measurement errors in nodules ≥ 10 mm were 14.89% with LungCARE and 19.96% with LungVCAR. The mean relative attenuation measurement errors in nodules ≥ 10 mm were 3.03% with LungCARE and 5.12% with LungVCAR. LungCARE shows significantly higher segmentation success rates than LungVCAR. Measurement accuracy of volume and attenuation of GGNs is acceptable in GGNs ≥ 10 mm by both software programs.

TH-AB-207A-12: CT Lung Cancer Screening and the Effects of Further Dose Reduction On CAD Performance

International Nuclear Information System (INIS)

Young, S; Lo, P; Hoffman, J; Kim, H; Hsu, W; Flores, C; Lee, G; Brown, M; McNitt-Gray, M

2016-01-01

Purpose: CT lung screening is already performed at low doses. In this study, we investigated the effects of further dose reduction on a lung-nodule CAD detection algorithm. Methods: The original raw CT data and images from 348 patients were obtained from our local database of National Lung Screening Trial (NLST) cases. 61 patients (17.5%) had at least one nodule reported on the NLST reader forms. All scans were acquired with fixed mAs (25 for standard-sized patients, 40 for large patients) on a 64-slice scanner (Sensation 64, Siemens Healthcare). All images were reconstructed with 1-mm slice thickness, B50 kernel. Based on a previously-published technique, we added noise to the raw data to simulate reduced-dose versions of each case at 50% and 25% of the original NLST dose (i.e. approximately 1.0 and 0.5 mGy CTDIvol). For each case at each dose level, a CAD detection algorithm was run and nodules greater than 4 mm in diameter were reported. These CAD results were compared to “truth”, defined as the approximate nodule centroids from the NLST forms. Sensitivities and false-positive rates (FPR) were calculated for each dose level, with a sub-analysis by nodule LungRADS category. Results: For larger category 4 nodules, median sensitivities were 100% at all three dose levels, and mean sensitivity decreased with dose. For the more challenging category 2 and 3 nodules, the dose dependence was less obvious. Overall, mean subject-level sensitivity varied from 38.5% at 100% dose to 40.4% at 50% dose, a difference of only 1.9%. However, median FPR quadrupled from 1 per case at 100% dose to 4 per case at 25% dose. Conclusions: Dose reduction affected nodule detectability differently depending on the LungRADS category, and FPR was very sensitive at sub-screening levels. Care should be taken to adapt CAD for the very challenging noise characteristics of screening. Funding support: NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens

TH-AB-207A-12: CT Lung Cancer Screening and the Effects of Further Dose Reduction On CAD Performance

Energy Technology Data Exchange (ETDEWEB)

Young, S; Lo, P; Hoffman, J; Kim, H; Hsu, W; Flores, C; Lee, G; Brown, M; McNitt-Gray, M [UCLA School of Medicine, Los Angeles, CA (United States)

2016-06-15

Purpose: CT lung screening is already performed at low doses. In this study, we investigated the effects of further dose reduction on a lung-nodule CAD detection algorithm. Methods: The original raw CT data and images from 348 patients were obtained from our local database of National Lung Screening Trial (NLST) cases. 61 patients (17.5%) had at least one nodule reported on the NLST reader forms. All scans were acquired with fixed mAs (25 for standard-sized patients, 40 for large patients) on a 64-slice scanner (Sensation 64, Siemens Healthcare). All images were reconstructed with 1-mm slice thickness, B50 kernel. Based on a previously-published technique, we added noise to the raw data to simulate reduced-dose versions of each case at 50% and 25% of the original NLST dose (i.e. approximately 1.0 and 0.5 mGy CTDIvol). For each case at each dose level, a CAD detection algorithm was run and nodules greater than 4 mm in diameter were reported. These CAD results were compared to “truth”, defined as the approximate nodule centroids from the NLST forms. Sensitivities and false-positive rates (FPR) were calculated for each dose level, with a sub-analysis by nodule LungRADS category. Results: For larger category 4 nodules, median sensitivities were 100% at all three dose levels, and mean sensitivity decreased with dose. For the more challenging category 2 and 3 nodules, the dose dependence was less obvious. Overall, mean subject-level sensitivity varied from 38.5% at 100% dose to 40.4% at 50% dose, a difference of only 1.9%. However, median FPR quadrupled from 1 per case at 100% dose to 4 per case at 25% dose. Conclusions: Dose reduction affected nodule detectability differently depending on the LungRADS category, and FPR was very sensitive at sub-screening levels. Care should be taken to adapt CAD for the very challenging noise characteristics of screening. Funding support: NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens

Artificial life models in lung CTS

International Nuclear Information System (INIS)

Sorin, Cheran

2006-01-01

A new method for the analysis of 3D medical images is introduced. The algorithm is based on Biological Models of ants known as Artificial Life models. Test images (lung Computed Tomographies) undergo a 3D region growing procedure for the identification of the ribs cage. Active Contour Models (snakes) are used in order to build a confined area where ants are deployed. The ant-based approach, in which steps are allowed in any direction with different probabilities, allows a kind of tunneling effect for the successful identification of small 3D structures that are not clearly connected to the rest of the tree. The best approach is based on a gradient rule for the release of pheromone. A possible application, as part of a Computer Assisted Detection system for the identification of lung nodules, is the removal of the bronchial and vascular tree from lung CTs thus reducing the number of false positives a Nodule Hunter might report. (Full Text)

Solitary pulmonary nodule by pulmonary hematoma under warfarin therapy

International Nuclear Information System (INIS)

Scheppach, W.; Kulke, H.; Liebau, G.; Braun, H.; Wuerzburg Univ.

1983-01-01

Pulmonary hematoma is a rare cause of a pulmonary nodule. Mostly it results from penetrating or blunt chest injuries. The case of a patient is reported, whose chest X-ray showed a pulmonary nodule suspected of malignancy. This patient was maintained permanently on anticoagulants (warfarin derivates) after cardiac valve replacement with a prosthesis. A definite diagnosis could not be established by non-invasive methods. A needle biopsy of the lung was impracticable because of the location of the pulmonary lesion; an exploratory thoracotomy could not be carried out due to a general indication of nonoperability. Control examinations showed that the pulmonary nodule had vanished completely within four months. In consideration of the patient's clinical situation it can be concluded that the pulmonary lesion was caused by a hematoma of the lung. (orig.) [de

Solitary pulmonary nodule by pulmonary hematoma under warfarin therapy

Energy Technology Data Exchange (ETDEWEB)

Scheppach, W.; Kulke, H.; Liebau, G.; Braun, H.

1983-06-01

Pulmonary hematoma is a rare cause of a pulmonary nodule. Mostly it results from penetrating or blunt chest injuries. The case of a patient is reported, whose chest X-ray showed a pulmonary nodule suspected of malignancy. This patient was maintained permanently on anticoagulants (warfarin derivates) after cardiac valve replacement with a prosthesis. A definite diagnosis could not be established by non-invasive methods. A needle biopsy of the lung was impracticable because of the location of the pulmonary lesion; an exploratory thoracotomy could not be carried out due to a general indication of nonoperability. Control examinations showed that the pulmonary nodule had vanished completely within four months. In consideration of the patient's clinical situation it can be concluded that the pulmonary lesion was caused by a hematoma of the lung.

X-ray Digital Linear Tomosynthesis Imaging for Artificial Pulmonary Nodule Detection

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Tsutomu Gomi

2011-01-01

Full Text Available The purpose of this paper is to identify indications for volumetric X-ray digital linear tomosynthesis (DLT with single- and dual-energy subtraction techniques for artificial pulmonary nodule detection and compare X-ray DLT, X-ray digital radiography, and computed tomography.

Observer training for computer-aided detection of pulmonary nodules in chest radiography.

Science.gov (United States)

De Boo, Diederick W; van Hoorn, François; van Schuppen, Joost; Schijf, Laura; Scheerder, Maeke J; Freling, Nicole J; Mets, Onno; Weber, Michael; Schaefer-Prokop, Cornelia M

2012-08-01

To assess whether short-term feedback helps readers to increase their performance using computer-aided detection (CAD) for nodule detection in chest radiography. The 140 CXRs (56 with a solitary CT-proven nodules and 84 negative controls) were divided into four subsets of 35; each were read in a different order by six readers. Lesion presence, location and diagnostic confidence were scored without and with CAD (IQQA-Chest, EDDA Technology) as second reader. Readers received individual feedback after each subset. Sensitivity, specificity and area under the receiver-operating characteristics curve (AUC) were calculated for readings with and without CAD with respect to change over time and impact of CAD. CAD stand-alone sensitivity was 59 % with 1.9 false-positives per image. Mean AUC slightly increased over time with and without CAD (0.78 vs. 0.84 with and 0.76 vs. 0.82 without CAD) but differences did not reach significance. The sensitivity increased (65 % vs. 70 % and 66 % vs. 70 %) and specificity decreased over time (79 % vs. 74 % and 80 % vs. 77 %) but no significant impact of CAD was found. Short-term feedback does not increase the ability of readers to differentiate true- from false-positive candidate lesions and to use CAD more effectively. • Computer-aided detection (CAD) is increasingly used as an adjunct for many radiological techniques. • Short-term feedback does not improve reader performance with CAD in chest radiography. • Differentiation between true- and false-positive CAD for low conspicious possible lesions proves difficult. • CAD can potentially increase reader performance for nodule detection in chest radiography.

Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique

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Teramoto, Atsushi, E-mail: teramoto@fujita-hu.ac.jp [Faculty of Radiological Technology, School of Health Sciences, Fujita Health University, 1-98 Dengakugakubo, Kutsukake, Toyoake, Aichi 470-1192 (Japan); Fujita, Hiroshi [Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University, 1-1 Yanagido, Gifu 501-1194 (Japan); Yamamuro, Osamu; Tamaki, Tsuneo [East Nagoya Imaging Diagnosis Center, 3-4-26 Jiyugaoka, Chikusa-ku, Nagoya, Aichi 464-0044 (Japan)

2016-06-15

Purpose: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; however, it is difficult to detect nodules in contact with normal organs, and additional efforts are needed so that the number of false positives (FPs) can be further reduced. In this paper, the authors propose an improved FP-reduction method for the detection of pulmonary nodules in PET/CT images by means of convolutional neural networks (CNNs). Methods: The overall scheme detects pulmonary nodules using both CT and PET images. In the CT images, a massive region is first detected using an active contour filter, which is a type of contrast enhancement filter that has a deformable kernel shape. Subsequently, high-uptake regions detected by the PET images are merged with the regions detected by the CT images. FP candidates are eliminated using an ensemble method; it consists of two feature extractions, one by shape/metabolic feature analysis and the other by a CNN, followed by a two-step classifier, one step being rule based and the other being based on support vector machines. Results: The authors evaluated the detection performance using 104 PET/CT images collected by a cancer-screening program. The sensitivity in detecting candidates at an initial stage was 97.2%, with 72.8 FPs/case. After performing the proposed FP-reduction method, the sensitivity of detection was 90.1%, with 4.9 FPs/case; the proposed method eliminated approximately half the FPs existing in the previous study. Conclusions: An improved FP-reduction scheme using CNN technique has been developed for the detection of pulmonary nodules in PET/CT images. The authors’ ensemble FP-reduction method eliminated 93% of the FPs; their proposed method using CNN technique eliminates approximately half the FPs existing in the previous study. These results indicate that their method may be useful in the computer-aided detection of pulmonary nodules

Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique

International Nuclear Information System (INIS)

Teramoto, Atsushi; Fujita, Hiroshi; Yamamuro, Osamu; Tamaki, Tsuneo

2016-01-01

Purpose: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; however, it is difficult to detect nodules in contact with normal organs, and additional efforts are needed so that the number of false positives (FPs) can be further reduced. In this paper, the authors propose an improved FP-reduction method for the detection of pulmonary nodules in PET/CT images by means of convolutional neural networks (CNNs). Methods: The overall scheme detects pulmonary nodules using both CT and PET images. In the CT images, a massive region is first detected using an active contour filter, which is a type of contrast enhancement filter that has a deformable kernel shape. Subsequently, high-uptake regions detected by the PET images are merged with the regions detected by the CT images. FP candidates are eliminated using an ensemble method; it consists of two feature extractions, one by shape/metabolic feature analysis and the other by a CNN, followed by a two-step classifier, one step being rule based and the other being based on support vector machines. Results: The authors evaluated the detection performance using 104 PET/CT images collected by a cancer-screening program. The sensitivity in detecting candidates at an initial stage was 97.2%, with 72.8 FPs/case. After performing the proposed FP-reduction method, the sensitivity of detection was 90.1%, with 4.9 FPs/case; the proposed method eliminated approximately half the FPs existing in the previous study. Conclusions: An improved FP-reduction scheme using CNN technique has been developed for the detection of pulmonary nodules in PET/CT images. The authors’ ensemble FP-reduction method eliminated 93% of the FPs; their proposed method using CNN technique eliminates approximately half the FPs existing in the previous study. These results indicate that their method may be useful in the computer-aided detection of pulmonary nodules

Non-invasive Characterization of the Histopathologic Features of Pulmonary Nodules of the Lung Adenocarcinoma Spectrum using Computer Aided Nodule Assessment and Risk Yield (CANARY) – a Pilot Study

Science.gov (United States)

Maldonado, Fabien; Boland, Jennifer M.; Raghunath, Sushravya; Aubry, Marie Christine; Bartholmai, Brian J.; deAndrade, Mariza; Hartman, Thomas E.; Karwoski, Ronald A.; Rajagopalan, Srinivasan; Sykes, Anne-Marie; Yang, Ping; Yi, Eunhee S.; Robb, Richard A.; Peikert, Tobias

2013-01-01

Introduction Pulmonary nodules of the adenocarcinoma spectrum are characterized by distinctive morphological and radiological features and variable prognosis. Non-invasive high-resolution computed-tomography (HRCT)-based risk stratification tools are needed to individualize their management. Methods Radiological measurements of histopathologic tissue invasion were developed in a training set of 54 pulmonary nodules of the adenocarcinoma spectrum and validated in 86 consecutively resected nodules. Nodules were isolated and characterized by computer-aided analysis and data were analyzed by Spearman correlation, sensitivity, specificity as well as the positive and negative predictive values. Results Computer Aided Nodule Assessment and Risk Yield (CANARY) can non-invasively characterize pulmonary nodules of the adenocarcinoma spectrum. Unsupervised clustering analysis of HRCT data identified 9 unique exemplars representing the basic radiologic building blocks of these lesions. The exemplar distribution within each nodule correlated well with the proportion of histologic tissue invasion, Spearman R=0.87,p < 0.0001 and 0.89,p < 0.0001 for the training and the validation set, respectively. Clustering of the exemplars in three-dimensional space corresponding to tissue invasion and lepidic growth was used to develop a CANARY decision algorithm, which successfully categorized these pulmonary nodules as “aggressive” (invasive adenocarcinoma) or “indolent” (adenocarcinoma in situ and minimally invasive adenocarcinoma). Sensitivity, specificity, positive predictive value and negative predictive value of this approach for the detection of “aggressive” lesions were 95.4%, 96.8%, 95.4% and 96.8%, respectively in the training set and 98.7%, 63.6%, 94.9% and 87.5%, respectively in the validation set. Conclusion CANARY represents a promising tool to non-invasively risk stratify pulmonary nodules of the adenocarcinoma spectrum. PMID:23486265

Shape based automated detection of pulmonary nodules with surface feature based false positive reduction

International Nuclear Information System (INIS)

Nomura, Y.; Itoh, H.; Masutani, Y.; Ohtomo, K.; Maeda, E.; Yoshikawa, T.; Hayashi, N.

2007-01-01

We proposed a shape based automated detection of pulmonary nodules with surface feature based false positive (FP) reduction. In the proposed system, the FP existing in internal of vessel bifurcation is removed using extracted surface of vessels and nodules. From the validation with 16 chest CT scans, we find that the proposed CAD system achieves 18.7 FPs/scan at 90% sensitivity, and 7.8 FPs/scan at 80% sensitivity. (orig.)

Evaluation of effectiveness of a computer system (CAD) in the identification of lung nodules with low-dose MSCT: scanning technique and preliminary results

International Nuclear Information System (INIS)

Fraioli, Francesco; Catalano, Carlo; Almberger, Maria; Bertoletti, Linda; Cantisani, Vito; Danti, Massimiliano; Pediconi, Federica; Passariello, Roberto

2005-01-01

Purpose: Evaluation of the effectiveness of a computer-aided diagnosis (CAD) in the identification of pulmonary nodules. Materials and methods: Two observers (A1, A2) with different levels of experience independently evaluated 20 chest MSCT studies with and without the aid of a CAD system (LungCheck, R2 Technology, Inc.). The study parameters were as follows: 140 kVs, 40 mAs, collimation 4x1 mm, slice thickness 1.25 mm, reconstruction interval 1.0 mm. The observers analysed the images with and without CAD and evaluated: 1) nodule size (longer axis); 2) number and location of nodules; 3) reading time for each observer. The gold standard was represented by the evaluation of both readers in consensus with the aid of the CAD system. Results: Without CAD support the two readers identified 77 (A1) and 79 (A2) nodules and with CAD 81 (A1) and 82 (A2) nodules. Working in consensus the two observers identified 81 nodules without the aid of CAD and 84 nodules with the aid of CAD. Total number of nodules identified by CAD was 104, 25 of which were false positive and 5 false negative. The average reading time with the aid of CAD decreased by as much as 40% for both the observers. Conclusions: The preliminary results of our study suggest that the CAD technique is an accurate automatic support tool in the identification of pulmonary nodules. It reduces reading time and automatically supplies the size, volume, density and number of nodules, thus being useful both in screening programmes and in the follow-up of cancer patients, in whom comparison of the images is particularly difficult [it

Value of a Computer-aided Detection System Based on Chest Tomosynthesis Imaging for the Detection of Pulmonary Nodules.

Science.gov (United States)

Yamada, Yoshitake; Shiomi, Eisuke; Hashimoto, Masahiro; Abe, Takayuki; Matsusako, Masaki; Saida, Yukihisa; Ogawa, Kenji

2018-04-01

Purpose To assess the value of a computer-aided detection (CAD) system for the detection of pulmonary nodules on chest tomosynthesis images. Materials and Methods Fifty patients with and 50 without pulmonary nodules underwent both chest tomosynthesis and multidetector computed tomography (CT) on the same day. Fifteen observers (five interns and residents, five chest radiologists, and five abdominal radiologists) independently evaluated tomosynthesis images of 100 patients for the presence of pulmonary nodules in a blinded and randomized manner, first without CAD, then with the inclusion of CAD marks. Multidetector CT images served as the reference standard. Free-response receiver operating characteristic analysis was used for the statistical analysis. Results The pooled diagnostic performance of 15 observers was significantly better with CAD than without CAD (figure of merit [FOM], 0.74 vs 0.71, respectively; P = .02). The average true-positive fraction and false-positive rate per all cases with CAD were 0.56 and 0.26, respectively, whereas those without CAD were 0.47 and 0.20, respectively. Subanalysis showed that the diagnostic performance of interns and residents was significantly better with CAD than without CAD (FOM, 0.70 vs 0.62, respectively; P = .001), whereas for chest radiologists and abdominal radiologists, the FOM with CAD values were greater but not significantly: 0.80 versus 0.78 (P = .38) and 0.74 versus 0.73 (P = .65), respectively. Conclusion CAD significantly improved diagnostic performance in the detection of pulmonary nodules on chest tomosynthesis images for interns and residents, but provided minimal benefit for chest radiologists and abdominal radiologists. © RSNA, 2017 Online supplemental material is available for this article.

The UK Lung Cancer Screening Trial: a pilot randomised controlled trial of low-dose computed tomography screening for the early detection of lung cancer.

Science.gov (United States)

Field, John K; Duffy, Stephen W; Baldwin, David R; Brain, Kate E; Devaraj, Anand; Eisen, Tim; Green, Beverley A; Holemans, John A; Kavanagh, Terry; Kerr, Keith M; Ledson, Martin; Lifford, Kate J; McRonald, Fiona E; Nair, Arjun; Page, Richard D; Parmar, Mahesh Kb; Rintoul, Robert C; Screaton, Nicholas; Wald, Nicholas J; Weller, David; Whynes, David K; Williamson, Paula R; Yadegarfar, Ghasem; Hansell, David M

2016-05-01

Lung cancer kills more people than any other cancer in the UK (5-year survival high-risk UK population, determine optimum recruitment, screening, reading and care pathway strategies; and (2) assess the psychological consequences and the health-economic implications of screening. A pilot randomised controlled trial comparing intervention with usual care. A population-based risk questionnaire identified individuals who were at high risk of developing lung cancer (≥ 5% over 5 years). Thoracic centres with expertise in lung cancer imaging, respiratory medicine, pathology and surgery: Liverpool Heart & Chest Hospital, Merseyside, and Papworth Hospital, Cambridgeshire. Individuals aged 50-75 years, at high risk of lung cancer, in the primary care trusts adjacent to the centres. A thoracic LDCT scan. Follow-up computed tomography (CT) scans as per protocol. Referral to multidisciplinary team clinics was determined by nodule size criteria. Population-based recruitment based on risk stratification; management of the trial through web-based database; optimal characteristics of CT scan readers (radiologists vs. radiographers); characterisation of CT-detected nodules utilising volumetric analysis; prevalence of lung cancer at baseline; sociodemographic factors affecting participation; psychosocial measures (cancer distress, anxiety, depression, decision satisfaction); and cost-effectiveness modelling. A total of 247,354 individuals were approached to take part in the trial; 30.7% responded positively to the screening invitation. Recruitment of participants resulted in 2028 in the CT arm and 2027 in the control arm. A total of 1994 participants underwent CT scanning: 42 participants (2.1%) were diagnosed with lung cancer; 36 out of 42 (85.7%) of the screen-detected cancers were identified as stage 1 or 2, and 35 (83.3%) underwent surgical resection as their primary treatment. Lung cancer was more common in the lowest socioeconomic group. Short-term adverse psychosocial