Implementation of several mathematical algorithms to breast tissue density classification

International Nuclear Information System (INIS)

Quintana, C.; Redondo, M.; Tirao, G.

2014-01-01

The accuracy of mammographic abnormality detection methods is strongly dependent on breast tissue characteristics, where a dense breast tissue can hide lesions causing cancer to be detected at later stages. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. This paper presents the implementation and the performance of different mathematical algorithms designed to standardize the categorization of mammographic images, according to the American College of Radiology classifications. These mathematical techniques are based on intrinsic properties calculations and on comparison with an ideal homogeneous image (joint entropy, mutual information, normalized cross correlation and index Q) as categorization parameters. The algorithms evaluation was performed on 100 cases of the mammographic data sets provided by the Ministerio de Salud de la Provincia de Córdoba, Argentina—Programa de Prevención del Cáncer de Mama (Department of Public Health, Córdoba, Argentina, Breast Cancer Prevention Program). The obtained breast classifications were compared with the expert medical diagnostics, showing a good performance. The implemented algorithms revealed a high potentiality to classify breasts into tissue density categories. - Highlights: • Breast density classification can be obtained by suitable mathematical algorithms. • Mathematical processing help radiologists to obtain the BI-RADS classification. • The entropy and joint entropy show high performance for density classification

Classification of breast cancer cytological specimen using convolutional neural network

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

2017-01-01

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

Novelty detection for breast cancer image classification

Science.gov (United States)

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

2016-09-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-06-15

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-04-15

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

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

Directory of Open Access Journals (Sweden)

Mark Burton

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

Meenakshi M. Pawar

2016-09-01

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

Analysis of framelets for breast cancer diagnosis.

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Thivya, K S; Sakthivel, P; Venkata Sai, P M

2016-01-01

Breast cancer is the second threatening tumor among the women. The effective way of reducing breast cancer is its early detection which helps to improve the diagnosing process. Digital mammography plays a significant role in mammogram screening at earlier stage of breast carcinoma. Even though, it is very difficult to find accurate abnormality in prevalent screening by radiologists. But the possibility of precise breast cancer screening is encouraged by predicting the accurate type of abnormality through Computer Aided Diagnosis (CAD) systems. The two most important indicators of breast malignancy are microcalcifications and masses. In this study, framelet transform, a multiresolutional analysis is investigated for the classification of the above mentioned two indicators. The statistical and co-occurrence features are extracted from the framelet decomposed mammograms with different resolution levels and support vector machine is employed for classification with k-fold cross validation. This system achieves 94.82% and 100% accuracy in normal/abnormal classification (stage I) and benign/malignant classification (stage II) of mass classification system and 98.57% and 100% for microcalcification system when using the MIAS database.

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

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

2013-10-01

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

Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations.

Science.gov (United States)

Wang, Dong-Yu; Done, Susan J; Mc Cready, David R; Leong, Wey L

2014-07-04

Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts. An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147). The original training cohort reached a statistically significant difference (p value of the triad classification was reproduced in the second independent internal cohort and the new external validation cohort. CMTC achieved even higher prognostic significance when all available patients were analyzed (n = 4,851). Oncogenic pathways Myc, E2F1, Ras and β-catenin were again implicated in the high-risk groups. Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments.

Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations

Science.gov (United States)

2014-01-01

Introduction Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts. Methods An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147). Results The original training cohort reached a statistically significant difference (p risk groups. Conclusions Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments. PMID:24996446

Early diagnosis of breast cancer

International Nuclear Information System (INIS)

Semiglazov, V.F.

1989-01-01

Modern data are presentd on epidemology etiopathogensis and statistics of breast cancer. Home and international clinical and histological classifications is given. Much attention is paid to the methods for early diagnosis of pretumor diseases and breast cancer: clinical roentgenomammography, thrmography and computerized tomomammography. The role of self-examination in cancer early detection has been analyzed. Special attention is paid to system of detection of minimal and unpalpable form of breast cancer, screening of these tumors. 113 refs.; 60 figs.; 6 tabs

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

International Nuclear Information System (INIS)

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

2010-01-01

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

Automated detection of breast cancer in resected specimens with fluorescence lifetime imaging

Science.gov (United States)

Phipps, Jennifer E.; Gorpas, Dimitris; Unger, Jakob; Darrow, Morgan; Bold, Richard J.; Marcu, Laura

2018-01-01

Re-excision rates for breast cancer lumpectomy procedures are currently nearly 25% due to surgeons relying on inaccurate or incomplete methods of evaluating specimen margins. The objective of this study was to determine if cancer could be automatically detected in breast specimens from mastectomy and lumpectomy procedures by a classification algorithm that incorporated parameters derived from fluorescence lifetime imaging (FLIm). This study generated a database of co-registered histologic sections and FLIm data from breast cancer specimens (N  =  20) and a support vector machine (SVM) classification algorithm able to automatically detect cancerous, fibrous, and adipose breast tissue. Classification accuracies were greater than 97% for automated detection of cancerous, fibrous, and adipose tissue from breast cancer specimens. The classification worked equally well for specimens scanned by hand or with a mechanical stage, demonstrating that the system could be used during surgery or on excised specimens. The ability of this technique to simply discriminate between cancerous and normal breast tissue, in particular to distinguish fibrous breast tissue from tumor, which is notoriously challenging for optical techniques, leads to the conclusion that FLIm has great potential to assess breast cancer margins. Identification of positive margins before waiting for complete histologic analysis could significantly reduce breast cancer re-excision rates.

Clinical application of a microfluidic chip for immunocapture and quantification of circulating exosomes to assist breast cancer diagnosis and molecular classification.

Science.gov (United States)

Fang, Shimeng; Tian, Hongzhu; Li, Xiancheng; Jin, Dong; Li, Xiaojie; Kong, Jing; Yang, Chun; Yang, Xuesong; Lu, Yao; Luo, Yong; Lin, Bingcheng; Niu, Weidong; Liu, Tingjiao

2017-01-01

Increasing attention has been attracted by exosomes in blood-based diagnosis because cancer cells release more exosomes in serum than normal cells and these exosomes overexpress a certain number of cancer-related biomarkers. However, capture and biomarker analysis of exosomes for clinical application are technically challenging. In this study, we developed a microfluidic chip for immunocapture and quantification of circulating exosomes from small sample volume and applied this device in clinical study. Circulating EpCAM-positive exosomes were measured in 6 cases breast cancer patients and 3 healthy controls to assist diagnosis. A significant increase in the EpCAM-positive exosome level in these patients was detected, compared to healthy controls. Furthermore, we quantified circulating HER2-positive exosomes in 19 cases of breast cancer patients for molecular classification. We demonstrated that the exosomal HER2 expression levels were almost consistent with that in tumor tissues assessed by immunohistochemical staining. The microfluidic chip might provide a new platform to assist breast cancer diagnosis and molecular classification.

Implementation of several mathematical algorithms to breast tissue density classification

Science.gov (United States)

Quintana, C.; Redondo, M.; Tirao, G.

2014-02-01

The accuracy of mammographic abnormality detection methods is strongly dependent on breast tissue characteristics, where a dense breast tissue can hide lesions causing cancer to be detected at later stages. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. This paper presents the implementation and the performance of different mathematical algorithms designed to standardize the categorization of mammographic images, according to the American College of Radiology classifications. These mathematical techniques are based on intrinsic properties calculations and on comparison with an ideal homogeneous image (joint entropy, mutual information, normalized cross correlation and index Q) as categorization parameters. The algorithms evaluation was performed on 100 cases of the mammographic data sets provided by the Ministerio de Salud de la Provincia de Córdoba, Argentina—Programa de Prevención del Cáncer de Mama (Department of Public Health, Córdoba, Argentina, Breast Cancer Prevention Program). The obtained breast classifications were compared with the expert medical diagnostics, showing a good performance. The implemented algorithms revealed a high potentiality to classify breasts into tissue density categories.

Summer Student Breast Cancer Research Training Program

Science.gov (United States)

2006-05-01

kinase inhibition on ERK activity in breast cancer cells, the role of the calpain proteolytic pathway in breast cancer-induced cachexia , and the...research training; breast cancer; fatty acids and prevention; nutrition and prevention; alternative prevention 16. SECURITY CLASSIFICATION OF...growth. In in vivo experiments, mice were fed diets that were rich in either omega-3 (fish oil) or omega-6 (corn oil) fatty acids. Three weeks after

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

International Nuclear Information System (INIS)

Parise, C. A.; Caggiano, V.

2014-01-01

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

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

Directory of Open Access Journals (Sweden)

Carol A. Parise

2014-01-01

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

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

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

2018-01-01

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

Can-CSC-GBE: Developing Cost-sensitive Classifier with Gentleboost Ensemble for breast cancer classification using protein amino acids and imbalanced data.

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Ali, Safdar; Majid, Abdul; Javed, Syed Gibran; Sattar, Mohsin

2016-06-01

Early prediction of breast cancer is important for effective treatment and survival. We developed an effective Cost-Sensitive Classifier with GentleBoost Ensemble (Can-CSC-GBE) for the classification of breast cancer using protein amino acid features. In this work, first, discriminant information of the protein sequences related to breast tissue is extracted. Then, the physicochemical properties hydrophobicity and hydrophilicity of amino acids are employed to generate molecule descriptors in different feature spaces. For comparison, we obtained results by combining Cost-Sensitive learning with conventional ensemble of AdaBoostM1 and Bagging. The proposed Can-CSC-GBE system has effectively reduced the misclassification costs and thereby improved the overall classification performance. Our novel approach has highlighted promising results as compared to the state-of-the-art ensemble approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

Hereditary breast cancer

DEFF Research Database (Denmark)

Larsen, Martin J; Thomassen, Mads; Gerdes, Anne-Marie

2014-01-01

Pathogenic mutations in BRCA1 or BRCA2 are only detected in 25% of families with a strong history of breast cancer, though hereditary factors are expected to be involved in the remaining families with no recognized mutation. Molecular characterization is expected to provide new insight...... into the tumor biology to guide the search of new high-risk alleles and provide better classification of the growing number of BRCA1/2 variants of unknown significance (VUS). In this review, we provide an overview of hereditary breast cancer, its genetic background, and clinical implications, before focusing...... on the pathologically and molecular features associated with the disease. Recent transcriptome and genome profiling studies of tumor series from BRCA1/2 mutation carriers as well as familial non-BRCA1/2 will be discussed. Special attention is paid to its association with molecular breast cancer subtypes as well...

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

Science.gov (United States)

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

2018-05-01

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

Classification System for Identifying Women at Risk for Altered Partial Breast Irradiation Recommendations After Breast Magnetic Resonance Imaging

International Nuclear Information System (INIS)

Kowalchik, Kristin V.; Vallow, Laura A.; McDonough, Michelle; Thomas, Colleen S.; Heckman, Michael G.; Peterson, Jennifer L.; Adkisson, Cameron D.; Serago, Christopher; McLaughlin, Sarah A.

2013-01-01

Purpose: To study the utility of preoperative breast MRI for partial breast irradiation (PBI) patient selection, using multivariable analysis of significant risk factors to create a classification rule. Methods and Materials: Between 2002 and 2009, 712 women with newly diagnosed breast cancer underwent preoperative bilateral breast MRI at Mayo Clinic Florida. Of this cohort, 566 were retrospectively deemed eligible for PBI according to the National Surgical Adjuvant Breast and Bowel Project Protocol B-39 inclusion criteria using physical examination, mammogram, and/or ultrasound. Magnetic resonance images were then reviewed to determine their impact on patient eligibility. The patient and tumor characteristics were evaluated to determine risk factors for altered PBI eligibility after MRI and to create a classification rule. Results: Of the 566 patients initially eligible for PBI, 141 (25%) were found ineligible because of pathologically proven MRI findings. Magnetic resonance imaging detected additional ipsilateral breast cancer in 118 (21%). Of these, 62 (11%) had more extensive disease than originally noted before MRI, and 64 (11%) had multicentric disease. Contralateral breast cancer was detected in 28 (5%). Four characteristics were found to be significantly associated with PBI ineligibility after MRI on multivariable analysis: premenopausal status (P=.021), detection by palpation (P<.001), first-degree relative with a history of breast cancer (P=.033), and lobular histology (P=.002). Risk factors were assigned a score of 0-2. The risk of altered PBI eligibility from MRI based on number of risk factors was 0:18%; 1:22%; 2:42%; 3:65%. Conclusions: Preoperative bilateral breast MRI altered the PBI recommendations for 25% of women. Women who may undergo PBI should be considered for breast MRI, especially those with lobular histology or with 2 or more of the following risk factors: premenopausal, detection by palpation, and first-degree relative with a history of

Aided diagnosis methods of breast cancer based on machine learning

Science.gov (United States)

Zhao, Yue; Wang, Nian; Cui, Xiaoyu

2017-08-01

In the field of medicine, quickly and accurately determining whether the patient is malignant or benign is the key to treatment. In this paper, K-Nearest Neighbor, Linear Discriminant Analysis, Logistic Regression were applied to predict the classification of thyroid,Her-2,PR,ER,Ki67,metastasis and lymph nodes in breast cancer, in order to recognize the benign and malignant breast tumors and achieve the purpose of aided diagnosis of breast cancer. The results showed that the highest classification accuracy of LDA was 88.56%, while the classification effect of KNN and Logistic Regression were better than that of LDA, the best accuracy reached 96.30%.

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

Science.gov (United States)

Fernández, Angel; Reigosa, Aldo

2013-12-01

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

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

Science.gov (United States)

Ali, Safdar; Majid, Abdul; Khan, Asifullah

2014-04-01

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

Carcinoma de mama: novos conceitos na classificação Breast cancer: new concepts in classification

Directory of Open Access Journals (Sweden)

Daniella Serafin Couto Vieira

2008-01-01

and the basis for and improved breast cancer molecular taxonomy. Another important implication is that genetic profiling may lead to the identification of new target for therapy and better predictive markers are needed to guide difficult treatment decisions. Additionally, the current pathology classification system is suboptimal, since patients with identical tumor types and stage of disease present different responses to therapy and different overall outcomes. Basal breast tumor represents one of the most intriguing subtypes and is frequently associated with poor prognosis and absence of putative therapeutic targets. Then, the purpose of this review was to resume the most recent knowledge about the breast carcinoma classification and characterization.

Proteomic maps of breast cancer subtypes

DEFF Research Database (Denmark)

Tyanova, Stefka; Albrechtsen, Reidar; Kronqvist, Pauliina

2016-01-01

Systems-wide profiling of breast cancer has almost always entailed RNA and DNA analysis by microarray and sequencing techniques. Marked developments in proteomic technologies now enable very deep profiling of clinical samples, with high identification and quantification accuracy. We analysed 40...... oestrogen receptor positive (luminal), Her2 positive and triple negative breast tumours and reached a quantitative depth of >10,000 proteins. These proteomic profiles identified functional differences between breast cancer subtypes, related to energy metabolism, cell growth, mRNA translation and cell......-cell communication. Furthermore, we derived a signature of 19 proteins, which differ between the breast cancer subtypes, through support vector machine (SVM)-based classification and feature selection. Remarkably, only three proteins of the signature were associated with gene copy number variations and eleven were...

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-11-15

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

Breast cancer tumor classification using LASSO method selection approach

International Nuclear Information System (INIS)

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

2016-10-01

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

Breast cancer tumor classification using LASSO method selection approach

Energy Technology Data Exchange (ETDEWEB)

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

2016-10-15

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

AN ADABOOST OPTIMIZED CCFIS BASED CLASSIFICATION MODEL FOR BREAST CANCER DETECTION

Directory of Open Access Journals (Sweden)

CHANDRASEKAR RAVI

2017-06-01

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

An iterated Laplacian based semi-supervised dimensionality reduction for classification of breast cancer on ultrasound images.

Science.gov (United States)

Liu, Xiao; Shi, Jun; Zhou, Shichong; Lu, Minhua

2014-01-01

The dimensionality reduction is an important step in ultrasound image based computer-aided diagnosis (CAD) for breast cancer. A newly proposed l2,1 regularized correntropy algorithm for robust feature selection (CRFS) has achieved good performance for noise corrupted data. Therefore, it has the potential to reduce the dimensions of ultrasound image features. However, in clinical practice, the collection of labeled instances is usually expensive and time costing, while it is relatively easy to acquire the unlabeled or undetermined instances. Therefore, the semi-supervised learning is very suitable for clinical CAD. The iterated Laplacian regularization (Iter-LR) is a new regularization method, which has been proved to outperform the traditional graph Laplacian regularization in semi-supervised classification and ranking. In this study, to augment the classification accuracy of the breast ultrasound CAD based on texture feature, we propose an Iter-LR-based semi-supervised CRFS (Iter-LR-CRFS) algorithm, and then apply it to reduce the feature dimensions of ultrasound images for breast CAD. We compared the Iter-LR-CRFS with LR-CRFS, original supervised CRFS, and principal component analysis. The experimental results indicate that the proposed Iter-LR-CRFS significantly outperforms all other algorithms.

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

Directory of Open Access Journals (Sweden)

Pelin GORGEL

2013-01-01

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

Design ensemble machine learning model for breast cancer diagnosis.

Science.gov (United States)

Hsieh, Sheau-Ling; Hsieh, Sung-Huai; Cheng, Po-Hsun; Chen, Chi-Huang; Hsu, Kai-Ping; Lee, I-Shun; Wang, Zhenyu; Lai, Feipei

2012-10-01

In this paper, we classify the breast cancer of medical diagnostic data. Information gain has been adapted for feature selections. Neural fuzzy (NF), k-nearest neighbor (KNN), quadratic classifier (QC), each single model scheme as well as their associated, ensemble ones have been developed for classifications. In addition, a combined ensemble model with these three schemes has been constructed for further validations. The experimental results indicate that the ensemble learning performs better than individual single ones. Moreover, the combined ensemble model illustrates the highest accuracy of classifications for the breast cancer among all models.

Hybrid analysis for indicating patients with breast cancer using temperature time series.

Science.gov (United States)

Silva, Lincoln F; Santos, Alair Augusto S M D; Bravo, Renato S; Silva, Aristófanes C; Muchaluat-Saade, Débora C; Conci, Aura

2016-07-01

Breast cancer is the most common cancer among women worldwide. Diagnosis and treatment in early stages increase cure chances. The temperature of cancerous tissue is generally higher than that of healthy surrounding tissues, making thermography an option to be considered in screening strategies of this cancer type. This paper proposes a hybrid methodology for analyzing dynamic infrared thermography in order to indicate patients with risk of breast cancer, using unsupervised and supervised machine learning techniques, which characterizes the methodology as hybrid. The dynamic infrared thermography monitors or quantitatively measures temperature changes on the examined surface, after a thermal stress. In the dynamic infrared thermography execution, a sequence of breast thermograms is generated. In the proposed methodology, this sequence is processed and analyzed by several techniques. First, the region of the breasts is segmented and the thermograms of the sequence are registered. Then, temperature time series are built and the k-means algorithm is applied on these series using various values of k. Clustering formed by k-means algorithm, for each k value, is evaluated using clustering validation indices, generating values treated as features in the classification model construction step. A data mining tool was used to solve the combined algorithm selection and hyperparameter optimization (CASH) problem in classification tasks. Besides the classification algorithm recommended by the data mining tool, classifiers based on Bayesian networks, neural networks, decision rules and decision tree were executed on the data set used for evaluation. Test results support that the proposed analysis methodology is able to indicate patients with breast cancer. Among 39 tested classification algorithms, K-Star and Bayes Net presented 100% classification accuracy. Furthermore, among the Bayes Net, multi-layer perceptron, decision table and random forest classification algorithms, an

Pulsed terahertz imaging of breast cancer in freshly excised murine tumors

Science.gov (United States)

Bowman, Tyler; Chavez, Tanny; Khan, Kamrul; Wu, Jingxian; Chakraborty, Avishek; Rajaram, Narasimhan; Bailey, Keith; El-Shenawee, Magda

2018-02-01

This paper investigates terahertz (THz) imaging and classification of freshly excised murine xenograft breast cancer tumors. These tumors are grown via injection of E0771 breast adenocarcinoma cells into the flank of mice maintained on high-fat diet. Within 1 h of excision, the tumor and adjacent tissues are imaged using a pulsed THz system in the reflection mode. The THz images are classified using a statistical Bayesian mixture model with unsupervised and supervised approaches. Correlation with digitized pathology images is conducted using classification images assigned by a modal class decision rule. The corresponding receiver operating characteristic curves are obtained based on the classification results. A total of 13 tumor samples obtained from 9 tumors are investigated. The results show good correlation of THz images with pathology results in all samples of cancer and fat tissues. For tumor samples of cancer, fat, and muscle tissues, THz images show reasonable correlation with pathology where the primary challenge lies in the overlapping dielectric properties of cancer and muscle tissues. The use of a supervised regression approach shows improvement in the classification images although not consistently in all tissue regions. Advancing THz imaging of breast tumors from mice and the development of accurate statistical models will ultimately progress the technique for the assessment of human breast tumor margins.

RRHGE: A Novel Approach to Classify the Estrogen Receptor Based Breast Cancer Subtypes

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Ashish Saini

2014-01-01

Full Text Available Background. Breast cancer is the most common type of cancer among females with a high mortality rate. It is essential to classify the estrogen receptor based breast cancer subtypes into correct subclasses, so that the right treatments can be applied to lower the mortality rate. Using gene signatures derived from gene interaction networks to classify breast cancers has proven to be more reproducible and can achieve higher classification performance. However, the interactions in the gene interaction network usually contain many false-positive interactions that do not have any biological meanings. Therefore, it is a challenge to incorporate the reliability assessment of interactions when deriving gene signatures from gene interaction networks. How to effectively extract gene signatures from available resources is critical to the success of cancer classification. Methods. We propose a novel method to measure and extract the reliable (biologically true or valid interactions from gene interaction networks and incorporate the extracted reliable gene interactions into our proposed RRHGE algorithm to identify significant gene signatures from microarray gene expression data for classifying ER+ and ER− breast cancer samples. Results. The evaluation on real breast cancer samples showed that our RRHGE algorithm achieved higher classification accuracy than the existing approaches.

DDT Exposure in Utero and Breast Cancer.

Science.gov (United States)

Cohn, Barbara A; La Merrill, Michele; Krigbaum, Nickilou Y; Yeh, Gregory; Park, June-Soo; Zimmermann, Lauren; Cirillo, Piera M

2015-08-01

Currently no direct evidence links in utero dichlorodiphenyltrichloroethane (DDT) exposure to human breast cancer. However, in utero exposure to another xenoestrogen, diethylstilbestrol, predicts an increased breast cancer risk. If this finding extends to DDT, it could have far-reaching consequences. Many women were heavily exposed in utero during widespread DDT use in the 1960s. They are now reaching the age of heightened breast cancer risk. DDT exposure persists and use continues in Africa and Asia without clear knowledge of the consequences for the next generation. In utero exposure to DDT is associated with an increased risk of breast cancer. This was a case-control study nested in a prospective 54-year follow-up of 9300 daughters in the Child Health and Development Studies pregnancy cohort (n = 118 breast cancer cases, diagnosed by age 52 y and 354 controls matched on birth year). Kaiser Foundation Health Plan members who received obstetric care in Alameda County, California, from 1959 to 1967, and their adult daughters participated in the study. Daughters' breast cancer diagnosed by age 52 years as of 2012 was measured. Maternal o,p'-DDT predicted daughters' breast cancer (odds ratio fourth quartile vs first = 3.7, 95% confidence interval 1.5-9.0). Mothers' lipids, weight, race, age, and breast cancer history did not explain the findings. This prospective human study links measured DDT exposure in utero to risk of breast cancer. Experimental studies are essential to confirm results and discover causal mechanisms. Findings support classification of DDT as an endocrine disruptor, a predictor of breast cancer, and a marker of high risk.

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

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

2015-01-01

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

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

Science.gov (United States)

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

2018-05-15

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

Diagnosis and prognosis of primary breast cancer

International Nuclear Information System (INIS)

Robertson, J. F. R.; Evans, A. J.

1997-01-01

The diagnosis of breast cancer should be made in the context of a multidisciplinary team: preoperative diagnosis can be made in over 90 % of patients with symptomatic and screen-detected cancers. A preoperative diagnosis allows patients the opportunity to come to terms with the diagnosis of breast cancer and to consider their treatment options before progressing to therapeutic surgery. Surgery remains the primary therapeutic treatment for operable breast cancer with radiotherapy and systemic therapies as adjuvant treatments. Surgery in addition provides pathological specimens from which important prognostic information may be obtained. The traditional TNM classification in itself is no longer sufficient although there is still c considerable prognostic information to be gained in staging patients. Markers of tumour biology provide prognostic data independent of TNM staging. Both need to be considered in any overall assessment of patient prognosis

Breast cancer in the 21st century: from early detection to new therapies.

Science.gov (United States)

Merino Bonilla, J A; Torres Tabanera, M; Ros Mendoza, L H

The analysis of the causes that have given rise to a change in tendency in the incidence and mortality rates of breast cancer in the last few decades generates important revelations regarding the role of breast screening, the regular application of adjuvant therapies and the change of risk factors. The benefits of early detection have been accompanied by certain adverse effects, even in terms of an excessive number of prophylactic mastectomies. Recently, several updates have been published on the recommendations in breast cancer screening at an international level. On the other hand, the advances in genomics have made it possible to establish a new molecular classification of breast cancer. Our aim is to present an updated overview of the epidemiological situation of breast cancer, as well as some relevant issues from the point of view of diagnosis, such as molecular classification and different strategies for both population-based and opportunistic screening. Copyright © 2017 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

Classification of breast tissue for protocols development in mammography exam;Classificacao dos tecidos mamarios para elaboracao de protocolos em exames de mamografia

Energy Technology Data Exchange (ETDEWEB)

Teixeira, M. Ines; Caldas, Linda V.E. [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Chohfi, Adriana C.S.; Figueiredo, Zenaide A. [Universidade Nove de Julho (UNINOVE), Sao Paulo, SP (Brazil). Dept. da Saude. Radiologia Medica

2009-07-01

For accomplishment of a mammogram should be considered several factors such as equipment used and the classification of breast cancer patients. The density of the breast is different of patient to patient, thus making it difficult many precocious diagnostic of breast cancer. There is a significant variation in the breast to be radiographed, depending on several factors presented in the breast tissue of breast prosthesis with or without breasts or with implants. This work had as objective main to make a survey of the factors that influence in the classification of mammary fabrics. With this survey and classification it can be better adjusted the protocols which will be more efficient in the mammography exam, preventing excess of radiation dose, stress for the patient, economy of raw material, control of the quality and rapidity in the process of image attainment. (author)

Impact of Preexisting Mental Illness on All-Cause and Breast Cancer-Specific Mortality in Elderly Patients With Breast Cancer.

Science.gov (United States)

Iglay, Kristy; Santorelli, Melissa L; Hirshfield, Kim M; Williams, Jill M; Rhoads, George G; Lin, Yong; Demissie, Kitaw

2017-12-20

Purpose Limited data are available on the survival of patients with breast cancer with preexisting mental illness, and elderly women are of special interest because they experience the highest incidence of breast cancer. Therefore, we compared all-cause and breast cancer-specific mortality for elderly patients with breast cancer with and without mental illness. Methods A retrospective cohort study was conducted by using SEER-Medicare data, including 19,028 women ≥ 68 years of age who were diagnosed with stage I to IIIa breast cancer in the United States from 2005 to 2007. Patients were classified as having severe mental illness if an International Classification of Diseases, Ninth Edition, Clinical Modification code for bipolar disorder, schizophrenia, or other psychotic disorder was recorded on at least one inpatient or two outpatient claims during the 3 years before breast cancer diagnosis. Patients were followed for up to 5 years after breast cancer diagnosis to assess survival outcomes, which were then compared with those of patients without mental illness. Results Nearly 3% of patients had preexisting severe mental illness. We observed a two-fold increase in the all-cause mortality hazard between patients with severe mental illness compared with those without mental illness after adjusting for age, income, race, ethnicity, geographic location, and marital status (adjusted hazard ratio, 2.19; 95% CI, 1.84 to 2.60). A 20% increase in breast cancer-specific mortality hazard was observed, but the association was not significant (adjusted hazard ratio, 1.20; 95% CI, 0.82 to 1.74). Patients with severe mental illness were more likely to be diagnosed with advanced breast cancer and aggressive tumor characteristics. They also had increased tobacco use and more comorbidities. Conclusion Patients with severe mental illness may need assistance with coordinating medical services.

Breast cancer statistics and prediction methodology: a systematic review and analysis.

Science.gov (United States)

Dubey, Ashutosh Kumar; Gupta, Umesh; Jain, Sonal

2015-01-01

Breast cancer is a menacing cancer, primarily affecting women. Continuous research is going on for detecting breast cancer in the early stage as the possibility of cure in early stages is bright. There are two main objectives of this current study, first establish statistics for breast cancer and second to find methodologies which can be helpful in the early stage detection of the breast cancer based on previous studies. The breast cancer statistics for incidence and mortality of the UK, US, India and Egypt were considered for this study. The finding of this study proved that the overall mortality rates of the UK and US have been improved because of awareness, improved medical technology and screening, but in case of India and Egypt the condition is less positive because of lack of awareness. The methodological findings of this study suggest a combined framework based on data mining and evolutionary algorithms. It provides a strong bridge in improving the classification and detection accuracy of breast cancer data.

Breast cancer staging: the role of the radiologist

International Nuclear Information System (INIS)

Trop, I.; David, J.; Lalonde, L.

2005-01-01

The role of the breast radiologist has evolved over the past years, with an increasing involvement in patient care. Improvements in diagnostic technology and surgical techniques allow for better preoperative staging and surgeries with decreased morbidity. This article reviews the elements of investigation that are important to the surgeon and oncologist in optimizing care for the newly diagnosed breast cancer patient, with the 6th edition of the TNM classification of the American Joint Committee on Cancer used as a reference. (author)

Molecular Classification of Lobular Carcinoma of the Breast

Science.gov (United States)

Fu, Denggang; Zuo, Qi; Huang, Qi; Su, Li; Ring, Huijun Z.; Ring, Brian Z.

2017-01-01

The morphology of breast tumors is complicated and diagnosis can be difficult. We present here a novel diagnostic model which we validate on both array-based and RNA sequencing platforms which reliably distinguishes this tumor type across multiple cohorts. We also examine how this molecular classification predicts sensitivity to common chemotherapeutics in cell-line based assays. A total of 1845 invasive breast cancer cases in six cohorts were collected, split into discovery and validation cohorts, and a classifier was created and compared to pathological diagnosis, grade and survival. In the validation cohorts the concordance of predicted diagnosis with a pathological diagnosis was 92%, and 97% when inconclusively classified cases were excluded. Tumor-derived cell lines were classified with the model as having predominantly ductal or lobular-like molecular physiologies, and sensitivity of these lines to relevant compounds was analyzed. A diagnostic tool can be created that reliably distinguishes lobular from ductal carcinoma and allows the classification of cell lines on the basis of molecular profiles associated with these tumor types. This tool may assist in improved diagnosis and aid in explorations of the response of lobular type breast tumor models to different compounds. PMID:28303886

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification

Directory of Open Access Journals (Sweden)

Lu Bing

2017-01-01

Full Text Available We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL. After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM. Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification.

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Bing, Lu; Wang, Wei

2017-01-01

We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL). After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM). Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Breast Cancer Prevention

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... of Breast & Gynecologic Cancers Breast Cancer Screening Research Breast Cancer Prevention (PDQ®)–Patient Version What is prevention? Go ... from starting. Risk-reducing surgery . General Information About Breast Cancer Key Points Breast cancer is a disease in ...

Breast Cancer Treatment

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... of Breast & Gynecologic Cancers Breast Cancer Screening Research Breast Cancer Treatment (PDQ®)–Patient Version General Information About Breast Cancer Go to Health Professional Version Key Points Breast ...

Molecular Imaging in Breast Cancer: From Whole-Body PET/CT to Dedicated Breast PET

Directory of Open Access Journals (Sweden)

B. B. Koolen

2012-01-01

Full Text Available Positron emission tomography (PET, with or without integrated computed tomography (CT, using 18F-fluorodeoxyglucose (FDG is based on the principle of elevated glucose metabolism in malignant tumors, and its use in breast cancer patients is frequently being investigated. It has been shown useful for classification, staging, and response monitoring, both in primary and recurrent disease. However, because of the partial volume effect and limited resolution of most whole-body PET scanners, sensitivity for the visualization of small tumors is generally low. To improve the detection and quantification of primary breast tumors with FDG PET, several dedicated breast PET devices have been developed. In this nonsystematic review, we shortly summarize the value of whole-body PET/CT in breast cancer and provide an overview of currently available dedicated breast PETs.

Study design requirements for RNA sequencing-based breast cancer diagnostics.

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Mer, Arvind Singh; Klevebring, Daniel; Grönberg, Henrik; Rantalainen, Mattias

2016-02-01

Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care. Clinical translation is dependent on subtype prediction models providing high sensitivity and specificity. In this study we evaluate sample size and RNA-sequencing read requirements for breast cancer subtyping to facilitate rational design of translational studies. We applied subsampling to ascertain the effect of training sample size and the number of RNA sequencing reads on classification accuracy of molecular subtype and routine biomarker prediction models (unsupervised and supervised). Subtype classification accuracy improved with increasing sample size up to N = 750 (accuracy = 0.93), although with a modest improvement beyond N = 350 (accuracy = 0.92). Prediction of routine biomarkers achieved accuracy of 0.94 (ER) and 0.92 (Her2) at N = 200. Subtype classification improved with RNA-sequencing library size up to 5 million reads. Development of molecular subtyping models for cancer diagnostics requires well-designed studies. Sample size and the number of RNA sequencing reads directly influence accuracy of molecular subtyping. Results in this study provide key information for rational design of translational studies aiming to bring sequencing-based diagnostics to the clinic.

Classification of breast masses in ultrasonic B scans using Nakagami and K distributions

International Nuclear Information System (INIS)

Shankar, P M; Dumane, Vishruta A; George, Thomas; Piccoli, Catherine W; Reid, John M; Forsberg, Flemming; Goldberg, Barry B

2003-01-01

Classification of breast masses in greyscale ultrasound images is undertaken using a multiparameter approach. Five parameters reflecting the non-Rayleigh nature of the backscattered echo were used. These parameters, based mostly on the Nakagami and K distributions, were extracted from the envelope of the echoes at the site, boundary, spiculated region and shadow of the mass. They were combined to create a linear discriminant. The performance of this discriminant for the classification of breast masses was studied using a data set consisting of 70 benign and 29 malignant cases. The A z value for the discriminant was 0.96 ± 0.02, showing great promise in the classification of masses into benign and malignant ones. The discriminant was combined with the level of suspicion values of the radiologist leading to an A z value of 0.97 ± 0.014. The parameters used here can be calculated with minimal clinical intervention, so the method proposed here may therefore be easily implemented in an automated fashion. These results also support the recent reports suggesting that ultrasound may help as an adjunct to mammography in breast cancer diagnostics to enhance the classification of breast masses

Breast cancer screening

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Mammogram - breast cancer screening; Breast exam - breast cancer screening; MRI - breast cancer screening ... is performed to screen women to detect early breast cancer when it is more likely to be cured. ...

The Royal College of Radiologists Breast Group breast imaging classification

International Nuclear Information System (INIS)

Maxwell, A.J.; Ridley, N.T.; Rubin, G.; Wallis, M.G.; Gilbert, F.J.; Michell, M.J.

2009-01-01

Standardisation of the classification of breast imaging reports will improve communication between the referrer and the radiologist and avoid ambiguity, which may otherwise lead to mismanagement of patients. Following wide consultation, Royal College of Radiologists Breast Group has produced a scoring system for the classification of breast imaging. This will facilitate audit and the development of nationally agreed standards for the investigation of women with breast disease. This five-point system is as follows: 1, normal; 2, benign findings; 3, indeterminate/probably benign findings; 4, findings suspicious of malignancy; 5, findings highly suspicious of malignancy. It is recommended that this be used in the reporting of all breast imaging examinations in the UK.

Identification of immune cell infiltration in hematoxylin-eosin stained breast cancer samples: texture-based classification of tissue morphologies

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Turkki, Riku; Linder, Nina; Kovanen, Panu E.; Pellinen, Teijo; Lundin, Johan

2016-03-01

The characteristics of immune cells in the tumor microenvironment of breast cancer capture clinically important information. Despite the heterogeneity of tumor-infiltrating immune cells, it has been shown that the degree of infiltration assessed by visual evaluation of hematoxylin-eosin (H and E) stained samples has prognostic and possibly predictive value. However, quantification of the infiltration in H and E-stained tissue samples is currently dependent on visual scoring by an expert. Computer vision enables automated characterization of the components of the tumor microenvironment, and texture-based methods have successfully been used to discriminate between different tissue morphologies and cell phenotypes. In this study, we evaluate whether local binary pattern texture features with superpixel segmentation and classification with support vector machine can be utilized to identify immune cell infiltration in H and E-stained breast cancer samples. Guided with the pan-leukocyte CD45 marker, we annotated training and test sets from 20 primary breast cancer samples. In the training set of arbitrary sized image regions (n=1,116) a 3-fold cross-validation resulted in 98% accuracy and an area under the receiver-operating characteristic curve (AUC) of 0.98 to discriminate between immune cell -rich and - poor areas. In the test set (n=204), we achieved an accuracy of 96% and AUC of 0.99 to label cropped tissue regions correctly into immune cell -rich and -poor categories. The obtained results demonstrate strong discrimination between immune cell -rich and -poor tissue morphologies. The proposed method can provide a quantitative measurement of the degree of immune cell infiltration and applied to digitally scanned H and E-stained breast cancer samples for diagnostic purposes.

Breast Cancer Overview

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... are here Home > Types of Cancer > Breast Cancer Breast Cancer This is Cancer.Net’s Guide to Breast Cancer. Use the menu below to choose the Overview/ ... social workers, and patient advocates. Cancer.Net Guide Breast Cancer Introduction Statistics Medical Illustrations Risk Factors and Prevention ...

Breast Cancer -- Male

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... Home > Types of Cancer > Breast Cancer in Men Breast Cancer in Men This is Cancer.Net’s Guide to Breast Cancer in Men. Use the menu below to choose ... social workers, and patient advocates. Cancer.Net Guide Breast Cancer in Men Introduction Statistics Risk Factors and Prevention ...

Breast cancer Ki67 expression preoperative discrimination by DCE-MRI radiomics features

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Ma, Wenjuan; Ji, Yu; Qin, Zhuanping; Guo, Xinpeng; Jian, Xiqi; Liu, Peifang

2018-02-01

To investigate whether quantitative radiomics features extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are associated with Ki67 expression of breast cancer. In this institutional review board approved retrospective study, we collected 377 cases Chinese women who were diagnosed with invasive breast cancer in 2015. This cohort included 53 low-Ki67 expression (Ki67 proliferation index less than 14%) and 324 cases with high-Ki67 expression (Ki67 proliferation index more than 14%). A binary-classification of low- vs. high- Ki67 expression was performed. A set of 52 quantitative radiomics features, including morphological, gray scale statistic, and texture features, were extracted from the segmented lesion area. Three most common machine learning classification methods, including Naive Bayes, k-Nearest Neighbor and support vector machine with Gaussian kernel, were employed for the classification and the least absolute shrink age and selection operator (LASSO) method was used to select most predictive features set for the classifiers. Classification performance was evaluated by the area under receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity. The model that used Naive Bayes classification method achieved the best performance than the other two methods, yielding 0.773 AUC value, 0.757 accuracy, 0.777 sensitivity and 0.769 specificity. Our study showed that quantitative radiomics imaging features of breast tumor extracted from DCE-MRI are associated with breast cancer Ki67 expression. Future larger studies are needed in order to further evaluate the findings.

Immune Response Augmentation in Metastasized Breast Cancer by Localized Therapy Utilizing Biocompatible Magnetic Fluids

Science.gov (United States)

2008-08-01

SUBJECT TERMS Cancer therapy by localized immune response, Magneto -rehological Fluids 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT...Metastasized Breast Cancer by Localized Therapy utilizing Biocompatible Magnetic Fluids PRINCIPAL INVESTIGATOR: Cahit Evrensel...2008 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Immune Response Augmentation in Metastasized Breast Cancer by Localized Therapy utilizing

Thermogram breast cancer prediction approach based on Neutrosophic sets and fuzzy c-means algorithm.

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Gaber, Tarek; Ismail, Gehad; Anter, Ahmed; Soliman, Mona; Ali, Mona; Semary, Noura; Hassanien, Aboul Ella; Snasel, Vaclav

2015-08-01

The early detection of breast cancer makes many women survive. In this paper, a CAD system classifying breast cancer thermograms to normal and abnormal is proposed. This approach consists of two main phases: automatic segmentation and classification. For the former phase, an improved segmentation approach based on both Neutrosophic sets (NS) and optimized Fast Fuzzy c-mean (F-FCM) algorithm was proposed. Also, post-segmentation process was suggested to segment breast parenchyma (i.e. ROI) from thermogram images. For the classification, different kernel functions of the Support Vector Machine (SVM) were used to classify breast parenchyma into normal or abnormal cases. Using benchmark database, the proposed CAD system was evaluated based on precision, recall, and accuracy as well as a comparison with related work. The experimental results showed that our system would be a very promising step toward automatic diagnosis of breast cancer using thermograms as the accuracy reached 100%.

Breast Cancer Surgery

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FACTS FOR LIFE Breast Cancer Surgery The goal of breast cancer surgery is to remove the whole tumor from the breast. Some lymph nodes ... might still be in the body. Types of breast cancer surgery There are two types of breast cancer ...

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

Directory of Open Access Journals (Sweden)

Jessica Roelands

2018-02-01

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

[Fibrocystic breast disease--breast cancer sequence].

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Habor, V; Habor, A; Copotoiu, C; Panţîru, A

2010-01-01

Fibrocystic breast disease has developed a major issue: the breast cancer sequence. Its involvement regarding the increse of breast cancer risk has 2 aspects: it may be either the marker of a prone tissue or a premalignant hystological deffect. Difficult differential diagnosis of benign proliferative breast lession and carcinoma led to the idea of sequency between the two: cancer does not initiate on normal mammary epithelia; it takes several proliferative stages for it to occur. In our series we analized a number of 677 breast surgical procedures where the pathologic examination reveals 115 cases (17%) of coexistence between cancer and fibrocystic breast disease. This aspect has proved to be related to earlier debut of breast cancer, suggesting that epithelial hyperplasia is a risk factor for breast cancer.

Mutation analysis of breast cancer gene BRCA among breast cancer Jordanian females

International Nuclear Information System (INIS)

Atoum, Manar F.; Al-Kayed, Sameer A.

2004-01-01

To screen mutations of the tumor suppressor breast cancer susceptibility gene 1 (BRCA1) within 3 exons among Jordanian breast cancer females. A total of 135 Jordanian breast cancer females were genetically analyzed by denaturing gradient electrophoresis (DGGE) for mutation detection in 3 BRCA1 exons (2, 11 and 20) between 2000-2002 in Al-Basheer Hospital, Amman, Jordan. Of the studied patients 50 had a family history of breast cancer, 28 had a family history of cancer other than breast cancer, and 57 had no family history of any cancer. Five germline mutations were detected among breast cancer females with a family history of breast cancers (one in exon 2 and 4 mutations in exon 11). Another germline mutation (within exon 11) was detected among breast cancer females with family history of cancer other than breast cancer, and no mutation was detected among breast cancer females with no family history of any cancer or among normal control females. Screening mutations within exon 2, exon 11 and exon 20 showed that most screened mutations were within BRCA1 exon 11 among breast cancer Jordanian families with a family history of breast cancer. (author)

6 Common Cancers - Breast Cancer

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... Home Current Issue Past Issues 6 Common Cancers - Breast Cancer Past Issues / Spring 2007 Table of Contents For ... slow her down. Photo: AP Photo/Brett Flashnick Breast Cancer Breast cancer is a malignant (cancerous) growth that ...

Cancer classification in the genomic era: five contemporary problems.

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

2015-10-19

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

Machine learning models in breast cancer survival prediction.

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Montazeri, Mitra; Montazeri, Mohadeseh; Montazeri, Mahdieh; Beigzadeh, Amin

2016-01-01

Breast cancer is one of the most common cancers with a high mortality rate among women. With the early diagnosis of breast cancer survival will increase from 56% to more than 86%. Therefore, an accurate and reliable system is necessary for the early diagnosis of this cancer. The proposed model is the combination of rules and different machine learning techniques. Machine learning models can help physicians to reduce the number of false decisions. They try to exploit patterns and relationships among a large number of cases and predict the outcome of a disease using historical cases stored in datasets. The objective of this study is to propose a rule-based classification method with machine learning techniques for the prediction of different types of Breast cancer survival. We use a dataset with eight attributes that include the records of 900 patients in which 876 patients (97.3%) and 24 (2.7%) patients were females and males respectively. Naive Bayes (NB), Trees Random Forest (TRF), 1-Nearest Neighbor (1NN), AdaBoost (AD), Support Vector Machine (SVM), RBF Network (RBFN), and Multilayer Perceptron (MLP) machine learning techniques with 10-cross fold technique were used with the proposed model for the prediction of breast cancer survival. The performance of machine learning techniques were evaluated with accuracy, precision, sensitivity, specificity, and area under ROC curve. Out of 900 patients, 803 patients and 97 patients were alive and dead, respectively. In this study, Trees Random Forest (TRF) technique showed better results in comparison to other techniques (NB, 1NN, AD, SVM and RBFN, MLP). The accuracy, sensitivity and the area under ROC curve of TRF are 96%, 96%, 93%, respectively. However, 1NN machine learning technique provided poor performance (accuracy 91%, sensitivity 91% and area under ROC curve 78%). This study demonstrates that Trees Random Forest model (TRF) which is a rule-based classification model was the best model with the highest level of

Low expression of Mel-18 predicts poor prognosis in patients with breast cancer.

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Guo, B-H; Zhang, X; Zhang, H-Z; Lin, H-L; Feng, Y; Shao, J-Y; Huang, W-L; Kung, H-F; Zeng, M-S

2010-12-01

Our previous study suggested that melanoma nuclear protein 18 (Mel-18) acted as a tumor suppressor in human breast cancer. This study was designed to investigate the clinical and prognostic significance of Mel-18 in breast cancer patients. Mel-18 was detected by immunohistochemistry in paraffin-embedded tissues from 287 breast cancer patients, of which 287 were from primary cancer sites, 63 from matched adjacent noncancerous sites, and 35 from metastatic lymph nodes. Differences in Mel-18 expression and clinical characteristics were compared by χ² test. Prognostic outcomes correlated with Mel-18 were examined using Kaplan-Meier analysis and Cox proportional hazards model. The decreased Mel-18 expression is incremental depending upon the magnitude of cancer progression (P Mel-18 was conversely correlated with the pathological classifications (P Mel-18 showed prolonged overall survivals (P Mel-18 expression may be a risk factor for the patients' survival (P Mel-18 expression is correlated with advanced clinicopathologic classifications and a poor overall survival in breast cancer patients. These findings suggest that Mel-18 may serve as a useful marker in prognostic evaluation for patients.

NIM: A Node Influence Based Method for Cancer Classification

Directory of Open Access Journals (Sweden)

Yiwen Wang

2014-01-01

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

Breast cancer

International Nuclear Information System (INIS)

Tokunaga, Masayoshi

1992-01-01

More than 20-year follow-up of A-bomb survivors in Hiroshima and Nagasaki has a crucial role in determining the relationship of radiation to the occurrence of breast cancer. In 1967, Wanebo et al have first reported 27 cases of breast cancer during the period 1950-1966 among the Adult Health Study population of A-bomb survivors. Since then, follow-up surveys for breast cancer have been made using the Life Span Study (LSS) cohort, and the incidence of breast cancer has increased year by year; that is breast cancer was identified in 231 cases by the first LSS series (1950-1969), 360 cases by the second LSS series (1950-1974), 564 cases by the third LSS series (1950-1980), and 816 cases in the fourth LSS series (1950-1085). The third LSS series have revealed a high risk for radiation-induced breast cancer in women aged 10 or less at the time of exposure (ATE). Both relative and absolute risks are found to be decreased with increasing ages ATE. Based on the above-mentioned findings and other studies on persons exposed medical radiation, radiation-induced breast cancer is characterized by the following: (1) the incidence of breast cancer is linearly increased with increasing radiation doses; (2) both relative and absolute risks for breast cancer are high in younger persons ATE; (3) age distribution of breast cancer in proximally exposed A-bomb survivors is the same as that in both distally A-bomb survivors and non-exposed persons, and there is no difference in histology between the former and latter groups. Thus, immature mammary gland cells before the age of puberty are found to be most radiosensitive. (N.K.)

Mammographic features and subsequent risk of breast cancer: a comparison of qualitative and quantitative evaluations in the Guernsey prospective studies.

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Torres-Mejía, Gabriela; De Stavola, Bianca; Allen, Diane S; Pérez-Gavilán, Juan J; Ferreira, Jorge M; Fentiman, Ian S; Dos Santos Silva, Isabel

2005-05-01

Mammographic features are known to be associated with breast cancer but the magnitude of the effect differs markedly from study to study. Methods to assess mammographic features range from subjective qualitative classifications to computer-automated quantitative measures. We used data from the UK Guernsey prospective studies to examine the relative value of these methods in predicting breast cancer risk. In all, 3,211 women ages > or =35 years who had a mammogram taken in 1986 to 1989 were followed-up to the end of October 2003, with 111 developing breast cancer during this period. Mammograms were classified using the subjective qualitative Wolfe classification and several quantitative mammographic features measured using computer-based techniques. Breast cancer risk was positively associated with high-grade Wolfe classification, percent breast density and area of dense tissue, and negatively associated with area of lucent tissue, fractal dimension, and lacunarity. Inclusion of the quantitative measures in the same model identified area of dense tissue and lacunarity as the best predictors of breast cancer, with risk increasing by 59% [95% confidence interval (95% CI), 29-94%] per SD increase in total area of dense tissue but declining by 39% (95% CI, 53-22%) per SD increase in lacunarity, after adjusting for each other and for other confounders. Comparison of models that included both the qualitative Wolfe classification and these two quantitative measures to models that included either the qualitative or the two quantitative variables showed that they all made significant contributions to prediction of breast cancer risk. These findings indicate that breast cancer risk is affected not only by the amount of mammographic density but also by the degree of heterogeneity of the parenchymal pattern and, presumably, by other features captured by the Wolfe classification.

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

Science.gov (United States)

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

2013-02-01

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

Breast Cancer Immunotherapy

Institute of Scientific and Technical Information of China (English)

Juhua Zhou; Yin Zhong

2004-01-01

Breast cancer is a leading cause of cancer-related deaths in women worldwide. Although tumorectomy,radiotherapy, chemotherapy and hormone replacement therapy have been used for the treatment of breast cancer, there is no effective therapy for patients with invasive and metastatic breast cancer. Immunotherapy may be proved effective in treating patients with advanced breast cancer. Breast cancer immunotherapy includes antibody based immunotherapy, cancer vaccine immunotherapy, adoptive T cell transfer immunotherapy and T cell receptor gene transfer immunotherapy. Antibody based immunotherapy such as the monoclonal antibody against HER-2/neu (trastuzumab) is successfully used in the treatment of breast cancer patients with over-expressed HER-2/neu, however, HER-2/neu is over-expressed only in 25-30% of breast cancer patients. Cancer vaccine immunotherapy is a promising method to treat cancer patients. Cancer vaccines can be used to induce specific anti-tumor immunity in breast cancer patients, but cannot induce objective tumor regression. Adoptive T cell transfer immunotherapy is an effective method in the treatment of melanoma patients. Recent advances in anti-tumor T cell generation ex vivo and limited clinical trial data have made the feasibility of adoptive T cell transfer immunotherapy in the treatment of breast cancer patients. T cell receptor gene transfer can redirect the specificity of T cells. Chimeric receptor, scFv(anti-HER-2/neu)/zeta receptor, was successfully used to redirect cytotoxic T lymphocyte hybridoma cells to obtain anti-HER-2/neu positive tumor cells, suggesting the feasibility of treatment of breast cancer patients with T cell receptor gene transfer immunotherapy. Clinical trials will approve that immunotherapy is an effective method to cure breast cancer disease in the near future.

Breast Cancer Immunotherapy

Institute of Scientific and Technical Information of China (English)

JuhuaZhou; YinZhong

2004-01-01

Breast cancer is a leading cause of cancer-related deaths in women worldwide. Although tumorectomy, radiotherapy, chemotherapy and hormone replacement therapy have been used for the treatment of breast cancer, there is no effective therapy for patients with invasive and metastatic breast cancer. Immunotherapy may be proved effective in treating patients with advanced breast cancer. Breast cancer immunotherapy includes antibody based immunotherapy, cancer vaccine immunotherapy, adoptive T cell transfer immunotherapy and T cell receptor gene transfer immunotherapy. Antibody based immunotherapy such as the monoclonal antibody against HER-2/neu (trastuzumab) is successfully used in the treatment of breast cancer patients with over-expressed HER-2/neu, however, HER-2/neu is over-expressed only in 25-30% of breast cancer patients. Cancer vaccine immunotherapy is a promising method to treat cancer patients. Cancer vaccines can be used to induce specific anti-tumor immunity in breast cancer patients, but cannot induce objective tumor regression. Adoptive T cell transfer immunotherapy is an effective method in the treatment of melanoma patients. Recent advances in anti-tumor T cell generation ex vivo and limited clinical trial data have made the feasibility of adoptive T cell transfer immunotherapy in the treatment of breast cancer patients. T cell receptor gene transfer can redirect the specificity of T cells. Chimeric receptor, scFv(anti-HER-2/neu)/zeta receptor, was successfully used to redirect cytotoxic T lymphocyte hybridoma cells to obtain anti-HER-2/neu positive tumor cells, suggesting the feasibility of treatment of breast cancer patients with T cell receptor gene transfer immunotherapy. Clinical trials will approve that immunotherapy is an effective method to cure breast cancer disease in the near future. Cellular & Molecular Immunology.

Breast Cancer

Science.gov (United States)

Breast cancer affects one in eight women during their lives. No one knows why some women get breast cancer, but there are many risk factors. Risks that ... who have family members with breast or ovarian cancer may wish to be tested for the genes. ...

Recurrent neural networks for breast lesion classification based on DCE-MRIs

Science.gov (United States)

Antropova, Natasha; Huynh, Benjamin; Giger, Maryellen

2018-02-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays a significant role in breast cancer screening, cancer staging, and monitoring response to therapy. Recently, deep learning methods are being rapidly incorporated in image-based breast cancer diagnosis and prognosis. However, most of the current deep learning methods make clinical decisions based on 2-dimentional (2D) or 3D images and are not well suited for temporal image data. In this study, we develop a deep learning methodology that enables integration of clinically valuable temporal components of DCE-MRIs into deep learning-based lesion classification. Our work is performed on a database of 703 DCE-MRI cases for the task of distinguishing benign and malignant lesions, and uses the area under the ROC curve (AUC) as the performance metric in conducting that task. We train a recurrent neural network, specifically a long short-term memory network (LSTM), on sequences of image features extracted from the dynamic MRI sequences. These features are extracted with VGGNet, a convolutional neural network pre-trained on a large dataset of natural images ImageNet. The features are obtained from various levels of the network, to capture low-, mid-, and high-level information about the lesion. Compared to a classification method that takes as input only images at a single time-point (yielding an AUC = 0.81 (se = 0.04)), our LSTM method improves lesion classification with an AUC of 0.85 (se = 0.03).

Normed kernel function-based fuzzy possibilistic C-means (NKFPCM) algorithm for high-dimensional breast cancer database classification with feature selection is based on Laplacian Score

Science.gov (United States)

Lestari, A. W.; Rustam, Z.

2017-07-01

In the last decade, breast cancer has become the focus of world attention as this disease is one of the primary leading cause of death for women. Therefore, it is necessary to have the correct precautions and treatment. In previous studies, Fuzzy Kennel K-Medoid algorithm has been used for multi-class data. This paper proposes an algorithm to classify the high dimensional data of breast cancer using Fuzzy Possibilistic C-means (FPCM) and a new method based on clustering analysis using Normed Kernel Function-Based Fuzzy Possibilistic C-Means (NKFPCM). The objective of this paper is to obtain the best accuracy in classification of breast cancer data. In order to improve the accuracy of the two methods, the features candidates are evaluated using feature selection, where Laplacian Score is used. The results show the comparison accuracy and running time of FPCM and NKFPCM with and without feature selection.

Factors determining esthetic outcome after breast cancer conservative treatment

DEFF Research Database (Denmark)

Cardoso, Maria J; Cardoso, Jaime; Santos, Ana C

2007-01-01

with lower body mass index (BMI) and premenopausal status obtained better cosmetic results. In the group of tumor- and treatment-related factors, larger removed specimens, clearly visible scars, the use of chemotherapy and longer follow-up period were associated with less satisfactory results......The aim of this study was to evaluate the factors that determine esthetic outcome after breast cancer conservative treatment, based on a consensual classification obtained with an international consensus panel. Photographs were taken from 120 women submitted to conservative unilateral breast cancer...... surgery (with or without axillary surgery) and radiotherapy. The images were sent to a panel of observers from 13 different countries and consensus on the classification of esthetic result (recorded as excellent, good, fair or poor) was obtained in 113 cases by means of a Delphi method. For each patient...

Sex Hormone Receptor Repertoire in Breast Cancer

Directory of Open Access Journals (Sweden)

Gerald M. Higa

2013-01-01

Full Text Available Classification of breast cancer as endocrine sensitive, hormone dependent, or estrogen receptor (ER positive refers singularly to ERα. One of the oldest recognized tumor targets, disruption of ERα-mediated signaling, is believed to be the mechanistic mode of action for all hormonal interventions used in treating this disease. Whereas ERα is widely accepted as the single most important predictive factor (for response to endocrine therapy, the presence of the receptor in tumor cells is also of prognostic value. Even though the clinical relevance of the two other sex hormone receptors, namely, ERβ and the androgen receptor remains unclear, two discordant phenomena observed in hormone-dependent breast cancers could be causally related to ERβ-mediated effects and androgenic actions. Nonetheless, our understanding of regulatory molecules and resistance mechanisms remains incomplete, further compromising our ability to develop novel therapeutic strategies that could improve disease outcomes. This review focuses on the receptor-mediated actions of the sex hormones in breast cancer.

Decision support system for breast cancer detection using mammograms.

Science.gov (United States)

Ganesan, Karthikeyan; Acharya, Rajendra U; Chua, Chua K; Min, Lim C; Mathew, Betty; Thomas, Abraham K

2013-07-01

Mammograms are by far one of the most preferred methods of screening for breast cancer. Early detection of breast cancer can improve survival rates to a greater extent. Although the analysis and diagnosis of breast cancer are done by experienced radiologists, there is always the possibility of human error. Interobserver and intraobserver errors occur frequently in the analysis of medical images, given the high variability between every patient. Also, the sensitivity of mammographic screening varies with image quality and expertise of the radiologist. So, there is no golden standard for the screening process. To offset this variability and to standardize the diagnostic procedures, efforts are being made to develop automated techniques for diagnosis and grading of breast cancer images. This article presents a classification pipeline to improve the accuracy of differentiation between normal, benign, and malignant mammograms. Several features based on higher-order spectra, local binary pattern, Laws' texture energy, and discrete wavelet transform were extracted from mammograms. Feature selection techniques based on sequential forward, backward, plus-l-takeaway-r, individual, and branch-and-bound selections using the Mahalanobis distance criterion were used to rank the features and find classification accuracies for combination of several features based on the ranking. Six classifiers were used, namely, decision tree classifier, fisher classifier, linear discriminant classifier, nearest mean classifier, Parzen classifier, and support vector machine classifier. We evaluated our proposed methodology with 300 mammograms obtained from the Digital Database for Screening Mammography and 300 mammograms from the Singapore Anti-Tuberculosis Association CommHealth database. Sensitivity, specificity, and accuracy values were used to compare the performances of the classifiers. Our results show that the decision tree classifier demonstrated an excellent performance compared to

Stages of Breast Cancer

Science.gov (United States)

... of Breast & Gynecologic Cancers Breast Cancer Screening Research Breast Cancer Treatment (PDQ®)–Patient Version General Information About Breast Cancer Go to Health Professional Version Key Points Breast ...

Breast cancer

Science.gov (United States)

... can help you know how to prevent breast cancer. Breast implants, using antiperspirants, and wearing underwire bras do not increase the risk for breast cancer. There is also no evidence of a direct ...

Risk Factors for Breast Cancer, Including Occupational Exposures

Directory of Open Access Journals (Sweden)

Elisabete Weiderpass

2011-03-01

Full Text Available The knowledge on the etiology of breast cancer has advanced substantially in recent years, and several etiological factors are now firmly established. However, very few new discoveries have been made in relation to occupational risk factors. The International Agency for Research on Cancer has evaluated over 900 different exposures or agents to-date to determine whether they are carcinogenic to humans. These evaluations are published as a series of Monographs (www.iarc.fr. For breast cancer the following substances have been classified as “carcinogenic to humans” (Group 1: alcoholic beverages, exposure to diethylstilbestrol, estrogen-progestogen contraceptives, estrogen-progestogen hormone replacement therapy and exposure to X-radiation and gamma-radiation (in special populations such as atomic bomb survivors, medical patients, and in-utero exposure. Ethylene oxide is also classified as a Group 1 carcinogen, although the evidence for carcinogenicity in epidemiologic studies, and specifically for the human breast, is limited. The classification “probably carcinogenic to humans” (Group 2A includes estrogen hormone replacement therapy, tobacco smoking, and shift work involving circadian disruption, including work as a flight attendant. If the association between shift work and breast cancer, the most common female cancer, is confirmed, shift work could become the leading cause of occupational cancer in women.

Breast Cancer: Treatment Options

Science.gov (United States)

... Breast Cancer > Breast Cancer: Treatment Options Request Permissions Breast Cancer: Treatment Options Approved by the Cancer.Net Editorial ... can be addressed as quickly as possible. Recurrent breast cancer If the cancer does return after treatment for ...

Common breast cancer susceptibility loci are associated with triple negative breast cancer

Science.gov (United States)

Stevens, Kristen N.; Vachon, Celine M.; Lee, Adam M.; Slager, Susan; Lesnick, Timothy; Olswold, Curtis; Fasching, Peter A.; Miron, Penelope; Eccles, Diana; Carpenter, Jane E.; Godwin, Andrew K.; Ambrosone, Christine; Winqvist, Robert; Schmidt, Marjanka K.; Cox, Angela; Cross, Simon S.; Sawyer, Elinor; Hartmann, Arndt; Beckmann, Matthias W.; Schulz-Wendtland, Rüdiger; Ekici, Arif B.; Tapper, William J; Gerty, Susan M; Durcan, Lorraine; Graham, Nikki; Hein, Rebecca; Nickels, Stephan; Flesch-Janys, Dieter; Heinz, Judith; Sinn, Hans-Peter; Konstantopoulou, Irene; Fostira, Florentia; Pectasides, Dimitrios; Dimopoulos, Athanasios M.; Fountzilas, George; Clarke, Christine L.; Balleine, Rosemary; Olson, Janet E.; Fredericksen, Zachary; Diasio, Robert B.; Pathak, Harsh; Ross, Eric; Weaver, JoEllen; Rüdiger, Thomas; Försti, Asta; Dünnebier, Thomas; Ademuyiwa, Foluso; Kulkarni, Swati; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Ko, Yon-Dschun; Van Limbergen, Erik; Janssen, Hilde; Peto, Julian; Fletcher, Olivia; Giles, Graham G.; Baglietto, Laura; Verhoef, Senno; Tomlinson, Ian; Kosma, Veli-Matti; Beesley, Jonathan; Greco, Dario; Blomqvist, Carl; Irwanto, Astrid; Liu, Jianjun; Blows, Fiona M.; Dawson, Sarah-Jane; Margolin, Sara; Mannermaa, Arto; Martin, Nicholas G.; Montgomery, Grant W; Lambrechts, Diether; dos Santos Silva, Isabel; Severi, Gianluca; Hamann, Ute; Pharoah, Paul; Easton, Douglas F.; Chang-Claude, Jenny; Yannoukakos, Drakoulis; Nevanlinna, Heli; Wang, Xianshu; Couch, Fergus J.

2012-01-01

Triple negative breast cancers are an aggressive subtype of breast cancer with poor survival, but there remains little known about the etiological factors which promote its initiation and development. Commonly inherited breast cancer risk factors identified through genome wide association studies (GWAS) display heterogeneity of effect among breast cancer subtypes as defined by estrogen receptor (ER) and progesterone receptor (PR) status. In the Triple Negative Breast Cancer Consortium (TNBCC), 22 common breast cancer susceptibility variants were investigated in 2,980 Caucasian women with triple negative breast cancer and 4,978 healthy controls. We identified six single nucleotide polymorphisms (SNPs) significantly associated with risk of triple negative breast cancer, including rs2046210 (ESR1), rs12662670 (ESR1), rs3803662 (TOX3), rs999737 (RAD51L1), rs8170 (19p13.11) and rs8100241 (19p13.11). Together, our results provide convincing evidence of genetic susceptibility for triple negative breast cancer. PMID:21844186

Breast Cancer Screening

International Nuclear Information System (INIS)

Altaf, Fadwa J.

2004-01-01

Breast cancer is a very common health problem in Saudi females that can be reduced by early detection through introducing breast cancer screening. Literature review reveals significant reduction in breast cancer incidence and outcome after the beginning of breast cancer screening. The objectives of this article are to highlight the significance of breast cancer screening in different international societies and to write the major guidelines of breast cancer screening in relation to other departments involved with more emphasis on the Pathology Department guidelines in tissue handling, diagnostic criteria and significance of the diagnosis. This article summaries and acknowledges major work carried out before, and recommends similar modified work in order to meet the requirement for the Saudi society. (author)

Methylation of Breast Cancer Predisposition Genes in Early-Onset Breast Cancer: Australian Breast Cancer Family Registry.

Directory of Open Access Journals (Sweden)

Cameron M Scott

Full Text Available DNA methylation can mimic the effects of both germline and somatic mutations for cancer predisposition genes such as BRCA1 and p16INK4a. Constitutional DNA methylation of the BRCA1 promoter has been well described and is associated with an increased risk of early-onset breast cancers that have BRCA1-mutation associated histological features. The role of methylation in the context of other breast cancer predisposition genes has been less well studied and often with conflicting or ambiguous outcomes. We examined the role of methylation in known breast cancer susceptibility genes in breast cancer predisposition and tumor development. We applied the Infinium HumanMethylation450 Beadchip (HM450K array to blood and tumor-derived DNA from 43 women diagnosed with breast cancer before the age of 40 years and measured the methylation profiles across promoter regions of BRCA1, BRCA2, ATM, PALB2, CDH1, TP53, FANCM, CHEK2, MLH1, MSH2, MSH6 and PMS2. Prior genetic testing had demonstrated that these women did not carry a germline mutation in BRCA1, ATM, CHEK2, PALB2, TP53, BRCA2, CDH1 or FANCM. In addition to the BRCA1 promoter region, this work identified regions with variable methylation at multiple breast cancer susceptibility genes including PALB2 and MLH1. Methylation at the region of MLH1 in these breast cancers was not associated with microsatellite instability. This work informs future studies of the role of methylation in breast cancer susceptibility gene silencing.

Evaluation of sestamibi scanning as a predictor of risk of development of breast cancer and as a non-invasive biomarker for breast cancer chemoprevention trials

International Nuclear Information System (INIS)

Kimler, B.F.; Preston, D.; McMillin, C.H.; Dusing, R.; Zalles, C.M.; Fabian, C.J.

2003-01-01

Sestamibi scintimammography is becoming increasingly accepted as an adjunct to conventional breast imaging by mammography and ultrasound. We sought to determine whether it might serve to detect/quantify pre-cancerous breast lesions, specifically hyperplasia with atypia which, when detected by random periareolar fine needle aspiration (FNA), is known to be associated with increased risk for subsequent development of breast cancer. If a parameter derived from sestamibi scanning could be shown to correlate with and predict for atypia, then this could serve 1) to refine estimates of risk of development of breast cancer; and 2) as a surrogate endpoint biomarker in clinical breast cancer chemoprevention trials. To this end, we performed sestamibi scanning on both breasts of 65 women at high risk for development of breast cancer who also underwent FNA. Seventeen women (26%) exhibited non-proliferative cytology; 30 (46%) had hyperplasia; and 18 (28%) had hyperplasia with atypia in the FNA specimen. Since the fine needle aspiration specimens from both breasts are pooled to provide a single result, we likewise pooled the sestamibi results from both breasts so as to consider the most abnormal finding. Twenty-five women (39%) were characterized as having an abnormal sestamibi scan with heterogenous, focal, intense uptake. There was no correlation between an abnormal scan and cytologic evidence of hyperplasia with atypia. Neither was there a correlation between any of a variety of quantitative measures of the sestamibi scans and the cytological classification. At this time, there is no indication for the use of sestamibi scanning for the prediction of risk of subsequent development of breast cancer, or as a surrogate endpoint biomarker in clinical breast cancer chemoprevention trials

Positive psychology interventions in breast cancer. A systematic review.

Science.gov (United States)

Casellas-Grau, Anna; Font, Antoni; Vives, Jaume

2014-01-01

Positive psychology is an emerging area of empirical study, not only in clinical, but also in health psychology. The present systematic review aims to synthesize the evidence about the positive psychology interventions utilized in breast cancer. Relevant studies were identified via Pubmed, PsycINFO, Web of Science, Scopus, Cochrane, CINAHL, Wiley Online Library, TDX, and DIALNET databases (up to April 2013). Only those papers focused on interventions related to positive psychology and carried out on breast cancer patients were included. Of the 7266 articles found through databases, 16 studies were finally included in this review. Five groups of therapies were found: mindfulness-based approaches, expression of positive emotions, spiritual interventions, hope therapy, and meaning-making interventions. These specific interventions promoted positive changes in breast cancer participants, such as enhanced quality of life, well-being, hope, benefit finding, or optimism. However, the disparity of the interventions and some methodological issues limit the outcomes. Some studies provided relevant evidence about the clear development of positive aspects from the breast cancer experience. Positive interventions applied to patients and survivors of breast cancer were found to be able to promote positive aspects. A global consensus of a positive therapies classification is needed to take one more step in structuring positive psychology. Copyright © 2013 John Wiley & Sons, Ltd.

Inheritance of proliferative breast disease in breast cancer kindreds

International Nuclear Information System (INIS)

Skolnick, M.H.; Cannon-Albright, L.A.; Goldgar, D.E.; Ward, J.H.; Marshall, C.J.; Schumann, G.B.; Hogle, H.; McWhorter, W.P.; Wright, E.C.; Tran, T.D.; Bishop, D.T.; Kushner, J.P.; Eyre, H.J.

1990-01-01

Previous studies have emphasized that genetic susceptibility to breast cancer is rare and is expressed primarily as premenopausal breast cancer, bilateral breast cancer, or both. Proliferative breast disease (PBD) is a significant risk factor for the development of breast cancer and appears to be a precursor lesion. PBD and breast cancer were studied in 103 women from 20 kindreds that were selected for the presence of two first degree relatives with breast cancer and in 31 control women. Physical examination, screening mammography, and four-quadrant fine-needle breast aspirates were performed. Cytologic analysis of breast aspirates revealed PBD in 35% of clinically normal female first degree relatives of breast cancer cases and in 13% of controls. Genetic analysis suggests that genetic susceptibility causes both PBD and breast cancer in these kindreds. This study supports the hypothesis that this susceptibility is responsible for a considerable portion of breast cancer, including unilateral and postmenopausal breast cancer

Male Breast Cancer

Science.gov (United States)

... types of breast cancer that can occur in men include Paget's disease of the nipple and inflammatory breast cancer. Inherited genes that increase breast cancer risk Some men inherit abnormal (mutated) genes from their parents that ...

Inflammatory Breast Cancer

Science.gov (United States)

... Common Cancer Types Recurrent Cancer Common Cancer Types Bladder Cancer Breast Cancer Colorectal Cancer Kidney (Renal Cell) Cancer ... white women. Inflammatory breast tumors are frequently hormone receptor negative, which means they cannot be treated with ...

Male Breast Cancer

Science.gov (United States)

Although breast cancer is much more common in women, men can get it too. It happens most often to men between ... 60 and 70. Breast lumps usually aren't cancer. However, most men with breast cancer have lumps. ...

Expression of the breast cancer resistance protein in breast cancer

NARCIS (Netherlands)

Faneyte, Ian F.; Kristel, Petra M. P.; Maliepaard, Marc; Scheffer, George L.; Scheper, Rik J.; Schellens, Jan H. M.; van de Vijver, Marc J.

2002-01-01

PURPOSE: The breast cancer resistance protein (BCRP) is involved in in vitro multidrug resistance and was first identified in the breast cancer cell line MCF7/AdrVp. The aim of this study was to investigate the role of BCRP in resistance of breast cancer to anthracycline treatment. EXPERIMENTAL

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

Directory of Open Access Journals (Sweden)

Qingzhong Liu

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

Increasing Breast Cancer Surveillance among African American Breast Cancer Survivors

National Research Council Canada - National Science Library

Thompson, Hayley

2005-01-01

...; they also are at considerable risk for breast cancer recurrence. According to the American Society of Clinical Oncology, survivors should undergo careful breast cancer surveillance, including annual mammography and breast self-exam...

Breast asymmetry and predisposition to breast cancer

OpenAIRE

Scutt, Diane; Lancaster, Gillian A; Manning, John T

2006-01-01

INTRODUCTION: It has been shown in our previous work that breast asymmetry is related to several of the known risk factors for breast cancer, and that patients with diagnosed breast cancer have more breast volume asymmetry, as measured from mammograms, than age-matched healthy women. METHODS: In the present study, we compared the breast asymmetry of women who were free of breast disease at time of mammography, but who had subsequently developed breast cancer, with that of age-matched healthy ...

Relationship of Predicted Risk of Developing Invasive Breast Cancer, as Assessed with Three Models, and Breast Cancer Mortality among Breast Cancer Patients.

Directory of Open Access Journals (Sweden)

Mark E Sherman

Full Text Available Breast cancer risk prediction models are used to plan clinical trials and counsel women; however, relationships of predicted risks of breast cancer incidence and prognosis after breast cancer diagnosis are unknown.Using largely pre-diagnostic information from the Breast Cancer Surveillance Consortium (BCSC for 37,939 invasive breast cancers (1996-2007, we estimated 5-year breast cancer risk (<1%; 1-1.66%; ≥1.67% with three models: BCSC 1-year risk model (BCSC-1; adapted to 5-year predictions; Breast Cancer Risk Assessment Tool (BCRAT; and BCSC 5-year risk model (BCSC-5. Breast cancer-specific mortality post-diagnosis (range: 1-13 years; median: 5.4-5.6 years was related to predicted risk of developing breast cancer using unadjusted Cox proportional hazards models, and in age-stratified (35-44; 45-54; 55-69; 70-89 years models adjusted for continuous age, BCSC registry, calendar period, income, mode of presentation, stage and treatment. Mean age at diagnosis was 60 years.Of 6,021 deaths, 2,993 (49.7% were ascribed to breast cancer. In unadjusted case-only analyses, predicted breast cancer risk ≥1.67% versus <1.0% was associated with lower risk of breast cancer death; BCSC-1: hazard ratio (HR = 0.82 (95% CI = 0.75-0.90; BCRAT: HR = 0.72 (95% CI = 0.65-0.81 and BCSC-5: HR = 0.84 (95% CI = 0.75-0.94. Age-stratified, adjusted models showed similar, although mostly non-significant HRs. Among women ages 55-69 years, HRs approximated 1.0. Generally, higher predicted risk was inversely related to percentages of cancers with unfavorable prognostic characteristics, especially among women 35-44 years.Among cases assessed with three models, higher predicted risk of developing breast cancer was not associated with greater risk of breast cancer death; thus, these models would have limited utility in planning studies to evaluate breast cancer mortality reduction strategies. Further, when offering women counseling, it may be useful to note that high

The Effect of Breast Cancer Fatalism on Breast Cancer Awareness Among Turkish Women.

Science.gov (United States)

Altintas, Hulya Kulakci; Ayyildiz, Tulay Kuzlu; Veren, Funda; Topan, Aysel Kose

2017-10-01

The aim of this study was to evaluate the effect of breast cancer fatalism and other factors on breast cancer awareness among Turkish women. This cross-sectional and comparative descriptive study was conducted with 894 women. Data were collected by Personal Information Form, Powe Fatalism Inventory and Champion's Health Belief Model Scale. Seriousness, health motivation, BSE benefits and BSE self-efficacy perceptions of the women were moderate, and susceptibility and BSE barriers perceptions were low. It was determined that awareness of breast cancer of the women was affected by breast cancer fatalism, age, education level, employment status, marital status, family type, economic status, social assurance, menopause status, family history of cancer, family history of breast cancer, knowledge on BSE, source of information on BSE, performing of BSE, frequency of BSE performing, having a problem with breast, having a breast examination in hospital, feeling during breast examination by healthcare professional, sex of healthcare professional for breast examination and their health beliefs (p breast cancer of the women was affected by breast cancer fatalism. In providing breast cancer early diagnosis behaviors, it is recommended to evaluate fatalism perceptions and health beliefs of the women and to arrange educational programs for this purpose.

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

Science.gov (United States)

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

2013-09-01

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

Susceptibility to breast cancer Cuban families and intervention strategy proposal

International Nuclear Information System (INIS)

Robaina, Martha S.; Menendez, Ibis; Valdes, Zodilina; Diaz, Milania

2009-01-01

In breast cancer, as in most cancers, mutations usually occur in somatic cells, but sometimes occur in germ cells. The carriers of these mutations germ have up to 80% risk of having the disease course of their lives and pass it on to their offspring, they are called hereditary cancers. In this work studied 50 tested history relatives of this neoplasm from consulting advice genetic hereditary breast cancer. The tree was made pedigree of the family of each test and been classified risk using the criteria of Hampel et al. Other malignancies were identified through the analysis of pedigrees and performed syndromic classification of families. It develops an algorithm for the care of breast cancer families hereditary and plotted strategies identified by risk taking that each category implies a different intervention. It recommended to continue studying the value of marking lesions subclinical and train staff to perform this technique for its widespread use in the country. (Author)

Breast cancer in men

Science.gov (United States)

... in situ - male; Intraductal carcinoma - male; Inflammatory breast cancer - male; Paget disease of the nipple - male; Breast cancer - male ... The cause of breast cancer in men is not clear. But there are risk factors that make breast cancer more likely in men: Exposure to ...

Breast MRI in pregnancy-associated breast cancer

Energy Technology Data Exchange (ETDEWEB)

Kim, Shin Jung; Shin, Sang Soo [Dept. of of Radiology, Chonnam National University Hospital, Gwangju (Korea, Republic of); Lim, Hyo Soon; Baek, Jang Mi; Seon, Hyun Ju; Heo, Suk Hee; Kim, Jin Woong; Park, Min Ho [Chonnam National University Medical School, Chonnam National University Hwasun Hospital, Hwasun (Korea, Republic of)

2017-03-15

The purpose of this study was to evaluate the usefulness of MR imaging and to describe the MR imaging findings of pregnancy-associated breast cancer. From 2006 to 2013, MR images of 23 patients with pregnancy-associated breast cancer were retrospectively evaluated. MR images were reviewed to evaluate lesion detection and imaging findings of pregnancy-associated breast cancer. MR images were analyzed by using the Breast Imaging Reporting and Data System and an additional MR-detected lesion with no mammographic or sonographic abnormality was determined. MR imaging depicted breast cancer in all patients, even in marked background parenchymal enhancement. Pregnancy-associated breast cancer was seen as a mass in 20 patients and as non-mass enhancement with segmental distribution in 3 patients. The most common features of the masses were irregular shape (85%), non-circumscribed margin (85%), and heterogeneous enhancement (60%). An additional site of cancer was detected with MR imaging in 5 patients (21.7%) and the type of surgery was changed. Pregnancy-associated breast cancer was usually seen as an irregular mass with heterogeneous enhancement on MR images. Although these findings were not specific, MR imaging was useful in evaluating the disease extent of pregnancy-associated breast cancer.

Breast MRI in pregnancy-associated breast cancer

International Nuclear Information System (INIS)

Kim, Shin Jung; Shin, Sang Soo; Lim, Hyo Soon; Baek, Jang Mi; Seon, Hyun Ju; Heo, Suk Hee; Kim, Jin Woong; Park, Min Ho

2017-01-01

The purpose of this study was to evaluate the usefulness of MR imaging and to describe the MR imaging findings of pregnancy-associated breast cancer. From 2006 to 2013, MR images of 23 patients with pregnancy-associated breast cancer were retrospectively evaluated. MR images were reviewed to evaluate lesion detection and imaging findings of pregnancy-associated breast cancer. MR images were analyzed by using the Breast Imaging Reporting and Data System and an additional MR-detected lesion with no mammographic or sonographic abnormality was determined. MR imaging depicted breast cancer in all patients, even in marked background parenchymal enhancement. Pregnancy-associated breast cancer was seen as a mass in 20 patients and as non-mass enhancement with segmental distribution in 3 patients. The most common features of the masses were irregular shape (85%), non-circumscribed margin (85%), and heterogeneous enhancement (60%). An additional site of cancer was detected with MR imaging in 5 patients (21.7%) and the type of surgery was changed. Pregnancy-associated breast cancer was usually seen as an irregular mass with heterogeneous enhancement on MR images. Although these findings were not specific, MR imaging was useful in evaluating the disease extent of pregnancy-associated breast cancer

A case-oriented web-based training system for breast cancer diagnosis.

Science.gov (United States)

Huang, Qinghua; Huang, Xianhai; Liu, Longzhong; Lin, Yidi; Long, Xingzhang; Li, Xuelong

2018-03-01

Breast cancer is still considered as the most common form of cancer as well as the leading causes of cancer deaths among women all over the world. We aim to provide a web-based breast ultrasound database for online training inexperienced radiologists and giving computer-assisted diagnostic information for detection and classification of the breast tumor. We introduce a web database which stores breast ultrasound images from breast cancer patients as well as their diagnostic information. A web-based training system using a feature scoring scheme based on Breast Imaging Reporting and Data System (BI-RADS) US lexicon was designed. A computer-aided diagnosis (CAD) subsystem was developed to assist the radiologists to make scores on the BI-RADS features for an input case. The training system possesses 1669 scored cases, where 412 cases are benign and 1257 cases are malignant. It was tested by 31 users including 12 interns, 11 junior radiologists, and 8 experienced senior radiologists. This online training system automatically creates case-based exercises to train and guide the newly employed or resident radiologists for the diagnosis of breast cancer using breast ultrasound images based on the BI-RADS. After the trainings, the interns and junior radiologists show significant improvement in the diagnosis of the breast tumor with ultrasound imaging (p-value  .05). The online training system can improve the capabilities of early-career radiologists in distinguishing between the benign and malignant lesions and reduce the misdiagnosis of breast cancer in a quick, convenient and effective manner. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Breast cancer prevention.

Science.gov (United States)

Euhus, David M; Diaz, Jennifer

2015-01-01

Breast cancer is the most common cancer in women with 232,670 new cases estimated in the USA for 2014. Approaches for reducing breast cancer risk include lifestyle modification, chemoprevention, and prophylactic surgery. Lifestyle modification has a variety of health benefits with few associated risks and is appropriate for all women regardless of breast cancer risk. Chemoprevention options have expanded rapidly, but most are directed at estrogen receptor positive breast cancer and uptake is low. Prophylactic surgery introduces significant additional risks of its own and is generally reserved for the highest risk women. © 2014 Wiley Periodicals, Inc.

Polyphenols as Promising Drugs against Main Breast Cancer Signatures

Directory of Open Access Journals (Sweden)

María Losada-Echeberría

2017-11-01

Full Text Available Breast cancer is one of the most common neoplasms worldwide, and in spite of clinical and pharmacological advances, it is still a clinical problem, causing morbidity and mortality. On the one hand, breast cancer shares with other neoplasms some molecular signatures such as an imbalanced redox state, cell cycle alterations, increased proliferation and an inflammatory status. On the other hand, breast cancer shows differential molecular subtypes that determine its prognosis and treatment. These are characterized mainly by hormone receptors especially estrogen receptors (ERs and epidermal growth factor receptor 2 (HER2. Tumors with none of these receptors are classified as triple negative breast cancer (TNBC and are associated with a worse prognosis. The success of treatments partially depends on their specificity and the adequate molecular classification of tumors. New advances in anticancer drug discovery using natural compounds have been made in the last few decades, and polyphenols have emerged as promising molecules. They may act on various molecular targets because of their promiscuous behavior, presenting several physiological effects, some of which confer antitumor activity. This review analyzes the accumulated evidence of the antitumor effects of plant polyphenols on breast cancer, with special attention to their activity on ERs and HER2 targets and also covering different aspects such as redox balance, uncontrolled proliferation and chronic inflammation.

Polyphenols as Promising Drugs against Main Breast Cancer Signatures

Science.gov (United States)

Herranz-López, María; Micol, Vicente

2017-01-01

Breast cancer is one of the most common neoplasms worldwide, and in spite of clinical and pharmacological advances, it is still a clinical problem, causing morbidity and mortality. On the one hand, breast cancer shares with other neoplasms some molecular signatures such as an imbalanced redox state, cell cycle alterations, increased proliferation and an inflammatory status. On the other hand, breast cancer shows differential molecular subtypes that determine its prognosis and treatment. These are characterized mainly by hormone receptors especially estrogen receptors (ERs) and epidermal growth factor receptor 2 (HER2). Tumors with none of these receptors are classified as triple negative breast cancer (TNBC) and are associated with a worse prognosis. The success of treatments partially depends on their specificity and the adequate molecular classification of tumors. New advances in anticancer drug discovery using natural compounds have been made in the last few decades, and polyphenols have emerged as promising molecules. They may act on various molecular targets because of their promiscuous behavior, presenting several physiological effects, some of which confer antitumor activity. This review analyzes the accumulated evidence of the antitumor effects of plant polyphenols on breast cancer, with special attention to their activity on ERs and HER2 targets and also covering different aspects such as redox balance, uncontrolled proliferation and chronic inflammation. PMID:29112149

Prediction of metastasis from low-malignant breast cancer by gene expression profiling

DEFF Research Database (Denmark)

Thomassen, Mads; Tan, Qihua; Eiriksdottir, Freyja

2007-01-01

examined in these studies is the low-risk patients for whom outcome is very difficult to predict with currently used methods. These patients do not receive adjuvant treatment according to the guidelines of the Danish Breast Cancer Cooperative Group (DBCG). In this study, 26 tumors from low-risk patients...... with different characteristics and risk, expression-based classification specifically developed in low-risk patients have higher predictive power in this group.......Promising results for prediction of outcome in breast cancer have been obtained by genome wide gene expression profiling. Some studies have suggested that an extensive overtreatment of breast cancer patients might be reduced by risk assessment with gene expression profiling. A patient group hardly...

Recursive SVM biomarker selection for early detection of breast cancer in peripheral blood.

Science.gov (United States)

Zhang, Fan; Kaufman, Howard L; Deng, Youping; Drabier, Renee

2013-01-01

Breast cancer is worldwide the second most common type of cancer after lung cancer. Traditional mammography and Tissue Microarray has been studied for early cancer detection and cancer prediction. However, there is a need for more reliable diagnostic tools for early detection of breast cancer. This can be a challenge due to a number of factors and logistics. First, obtaining tissue biopsies can be difficult. Second, mammography may not detect small tumors, and is often unsatisfactory for younger women who typically have dense breast tissue. Lastly, breast cancer is not a single homogeneous disease but consists of multiple disease states, each arising from a distinct molecular mechanism and having a distinct clinical progression path which makes the disease difficult to detect and predict in early stages. In the paper, we present a Support Vector Machine based on Recursive Feature Elimination and Cross Validation (SVM-RFE-CV) algorithm for early detection of breast cancer in peripheral blood and show how to use SVM-RFE-CV to model the classification and prediction problem of early detection of breast cancer in peripheral blood.The training set which consists of 32 health and 33 cancer samples and the testing set consisting of 31 health and 34 cancer samples were randomly separated from a dataset of peripheral blood of breast cancer that is downloaded from Gene Express Omnibus. First, we identified the 42 differentially expressed biomarkers between "normal" and "cancer". Then, with the SVM-RFE-CV we extracted 15 biomarkers that yield zero cross validation score. Lastly, we compared the classification and prediction performance of SVM-RFE-CV with that of SVM and SVM Recursive Feature Elimination (SVM-RFE). We found that 1) the SVM-RFE-CV is suitable for analyzing noisy high-throughput microarray data, 2) it outperforms SVM-RFE in the robustness to noise and in the ability to recover informative features, and 3) it can improve the prediction performance (Area Under

Breast cancer

OpenAIRE

Gablerová, Pavlína

2010-01-01

In this work the topic of breast cancer treated more generally and mainly focused on risk factors for the development. The theoretical part describes the general knowledge about breast cancer as a stage or treatment. The practical part is to have clarified the risk factors that have some bearing on the diagnosis of breast cancer. What level are involved in the probability of occurrence? Can we eliminate them? As a comparison of risk factors examined in the Czech Republic, England, Australia a...

Metabolic profiles are principally different between cancers of the liver, pancreas and breast.

Science.gov (United States)

Budhu, Anuradha; Terunuma, Atsushi; Zhang, Geng; Hussain, S Perwez; Ambs, Stefan; Wang, Xin Wei

2014-01-01

Molecular profiling of primary tumors may facilitate the classification of patients with cancer into more homogenous biological groups to aid clinical management. Metabolomic profiling has been shown to be a powerful tool in characterizing the biological mechanisms underlying a disease but has not been evaluated for its ability to classify cancers by their tissue of origin. Thus, we assessed metabolomic profiling as a novel tool for multiclass cancer characterization. Global metabolic profiling was employed to identify metabolites in paired tumor and non-tumor liver (n=60), breast (n=130) and pancreatic (n=76) tissue specimens. Unsupervised principal component analysis showed that metabolites are principally unique to each tissue and cancer type. Such a difference can also be observed even among early stage cancers, suggesting a significant and unique alteration of global metabolic pathways associated with each cancer type. Our global high-throughput metabolomic profiling study shows that specific biochemical alterations distinguish liver, pancreatic and breast cancer and could be applied as cancer classification tools to differentiate tumors based on tissue of origin.

A resampling-based meta-analysis for detection of differential gene expression in breast cancer

International Nuclear Information System (INIS)

Gur-Dedeoglu, Bala; Konu, Ozlen; Kir, Serkan; Ozturk, Ahmet Rasit; Bozkurt, Betul; Ergul, Gulusan; Yulug, Isik G

2008-01-01

Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively). The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real-time qRT-PCR supported the meta-analysis results. The

A resampling-based meta-analysis for detection of differential gene expression in breast cancer

Directory of Open Access Journals (Sweden)

Ergul Gulusan

2008-12-01

Full Text Available Abstract Background Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. Methods A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC, and invasive lobular carcinoma (ILC samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. Results The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively. The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real

Prevention of breast cancer.

Science.gov (United States)

Olver, Ian N

2016-11-21

Modifiable lifestyle factors may reduce the risk of developing breast cancer. Obesity is associated particularly with post-menopausal breast cancer. Diet is important, and exercise equivalent to running for up to 8 hours each week reduces the risk of breast cancer, both in its own right and through reducing obesity. Alcohol consumption may be responsible for 5.8% of breast cancers in Australia and it is recommended to reduce this to two standard drinks per day. Drinking alcohol and smoking increases the risk for breast cancer and, therefore, it is important to quit tobacco smoking. Prolonged use of combined oestrogen and progesterone hormone replacement therapy and oral contraceptives may increase breast cancer risk and this must be factored into individual decisions about their use. Ionising radiation, either from diagnostic or therapeutic radiation or through occupational exposure, is associated with a high incidence of breast cancer and exposure may be reduced in some cases. Tamoxifen chemoprevention may reduce the incidence of oestrogen receptor positive cancer in 51% of women with high risk of breast cancer. Uncommon but serious side effects include thromboembolism and uterine cancer. Raloxifene, which can also reduce osteoporosis, can be used in post-menopausal women and is not associated with the development of uterine cancer. Surgical prophylaxis with bilateral mastectomy and salpingo-oophorectomy can reduce the risk of breast cancer in patients carrying BRCA1 or BRCA2 mutations. For preventive treatments, mammographic screening can identify other women at high risk.

Plasma membrane proteomics of human breast cancer cell lines identifies potential targets for breast cancer diagnosis and treatment.

Directory of Open Access Journals (Sweden)

Yvonne S Ziegler

Full Text Available The use of broad spectrum chemotherapeutic agents to treat breast cancer results in substantial and debilitating side effects, necessitating the development of targeted therapies to limit tumor proliferation and prevent metastasis. In recent years, the list of approved targeted therapies has expanded, and it includes both monoclonal antibodies and small molecule inhibitors that interfere with key proteins involved in the uncontrolled growth and migration of cancer cells. The targeting of plasma membrane proteins has been most successful to date, and this is reflected in the large representation of these proteins as targets of newer therapies. In view of these facts, experiments were designed to investigate the plasma membrane proteome of a variety of human breast cancer cell lines representing hormone-responsive, ErbB2 over-expressing and triple negative cell types, as well as a benign control. Plasma membranes were isolated by using an aqueous two-phase system, and the resulting proteins were subjected to mass spectrometry analysis. Overall, each of the cell lines expressed some unique proteins, and a number of proteins were expressed in multiple cell lines, but in patterns that did not always follow traditional clinical definitions of breast cancer type. From our data, it can be deduced that most cancer cells possess multiple strategies to promote uncontrolled growth, reflected in aberrant expression of tyrosine kinases, cellular adhesion molecules, and structural proteins. Our data set provides a very rich and complex picture of plasma membrane proteins present on breast cancer cells, and the sorting and categorizing of this data provides interesting insights into the biology, classification, and potential treatment of this prevalent and debilitating disease.

Stages of Male Breast Cancer

Science.gov (United States)

... Breast & Gynecologic Cancers Breast Cancer Screening Research Male Breast Cancer Treatment (PDQ®)–Patient Version General Information about Male Breast Cancer Go to Health Professional Version Key Points Male ...

Enhancing Breast Cancer Recurrence Algorithms Through Selective Use of Medical Record Data.

Science.gov (United States)

Kroenke, Candyce H; Chubak, Jessica; Johnson, Lisa; Castillo, Adrienne; Weltzien, Erin; Caan, Bette J

2016-03-01

The utility of data-based algorithms in research has been questioned because of errors in identification of cancer recurrences. We adapted previously published breast cancer recurrence algorithms, selectively using medical record (MR) data to improve classification. We evaluated second breast cancer event (SBCE) and recurrence-specific algorithms previously published by Chubak and colleagues in 1535 women from the Life After Cancer Epidemiology (LACE) and 225 women from the Women's Health Initiative cohorts and compared classification statistics to published values. We also sought to improve classification with minimal MR examination. We selected pairs of algorithms-one with high sensitivity/high positive predictive value (PPV) and another with high specificity/high PPV-using MR information to resolve discrepancies between algorithms, properly classifying events based on review; we called this "triangulation." Finally, in LACE, we compared associations between breast cancer survival risk factors and recurrence using MR data, single Chubak algorithms, and triangulation. The SBCE algorithms performed well in identifying SBCE and recurrences. Recurrence-specific algorithms performed more poorly than published except for the high-specificity/high-PPV algorithm, which performed well. The triangulation method (sensitivity = 81.3%, specificity = 99.7%, PPV = 98.1%, NPV = 96.5%) improved recurrence classification over two single algorithms (sensitivity = 57.1%, specificity = 95.5%, PPV = 71.3%, NPV = 91.9%; and sensitivity = 74.6%, specificity = 97.3%, PPV = 84.7%, NPV = 95.1%), with 10.6% MR review. Triangulation performed well in survival risk factor analyses vs analyses using MR-identified recurrences. Use of multiple recurrence algorithms in administrative data, in combination with selective examination of MR data, may improve recurrence data quality and reduce research costs. © The Author 2015. Published by Oxford University Press. All rights reserved. For

Breast imaging reporting and data system (BI-RADS) or French 'classification ACR'

International Nuclear Information System (INIS)

Dilhuydy, Marie Helene

2007-01-01

Summary: The American College of Radiology Task Force on Breast Cancer published in 2003 Fourth edition of BI-RADS for Mammography. It is a lexicon of mammography terms including illustrations of each feature described, followed by a reporting format with assessment categories according to the degree of concern. The aim is to reduce inconsistencies in mammography reports and recommendations for assessment, to facilitate outcome monitoring and to allow each radiologist to audit his own mammography practice. In France, the Societe Francaise de Radiologie acquired the rights to translate BI-RADS, word for word and without adaptation or influence. The last edition was published in 2004. Simultaneously, French Haute Autorite de Sante and National Committee for Breast Cancer Screening proposed to all community practice mammography facilities a classification of detected abnormalities stating more clearly than BI-RADS do which feature has to be included in such and such assessment category and how to manage it. This 'classification ACR' is adapted from BI-RADS but strongly influenced by the context of the French nationwide screening programme, and by European recommendations to limitate undesirable risks of screening such as false positive and overdiagnosis. The differences between the two systems are discussed

Breast cancer imaging

International Nuclear Information System (INIS)

Funke, M.; Villena, C.

2008-01-01

Advances in female breast imaging have substantially influenced the diagnosis, therapy, and prognosis of breast cancer in the past few years. Mammography using conventional or digital technique is considered the gold standard for the early detection of breast cancer. Other modalities such as breast ultrasound and contrast-enhanced magnetic resonance imaging of the breast play an important role in diagnostic imaging, staging, and follow-up of breast cancer. Percutaneous needle biopsy is a faster, less invasive, and more cost-effective method than surgical biopsy for verifying the histological diagnosis. New methods such as breast tomosynthesis, contrast-enhanced mammography, and positron emission tomography promise to further improve breast imaging. Further studies are mandatory to adapt these new methods to clinical needs and to evaluate their performance in clinical practice. (orig.) [de

Breast Cancer Disparities

Science.gov (United States)

... 2.65 MB] Read the MMWR Science Clips Breast Cancer Black Women Have Higher Death Rates from Breast ... of Page U.S. State Info Number of Additional Breast Cancer Deaths Among Black Women, By State SOURCE: National ...

Breast cancer

African Journals Online (AJOL)

A collaborative article gives an overview of breast cancer in LICs, ... approach to the problem; therefore they are published as two separate ... attached to the diagnosis of breast cancer. ... Their founding statement in its early form is included.

Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

DEFF Research Database (Denmark)

Huang, Sijia; Chong, Nicole; Lewis, Nathan

2016-01-01

diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. Results: The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under.......993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions: We have successfully developed a new type of pathway-based model to study...... metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease...

Hormonal Modulation of Breast Cancer Gene Expression: Implications for Intrinsic Subtyping in Premenopausal Women

OpenAIRE

Bernhardt, Sarah M.; Dasari, Pallave; Walsh, David; Townsend, Amanda R.; Price, Timothy J.; Ingman, Wendy V.

2016-01-01

Clinics are increasingly adopting gene-expression profiling to diagnose breast cancer subtype, providing an intrinsic, molecular portrait of the tumor. For example, the PAM50-based Prosigna test quantifies expression of 50 key genes to classify breast cancer subtype, and this method of classification has been demonstrated to be superior over traditional immunohistochemical methods that detect proteins, to predict risk of disease recurrence. However, these tests were largely developed and vali...

DIAGNOSIS OF MUCINOUS BREAST CANCER

Directory of Open Access Journals (Sweden)

E. К. Saribekyan

2014-01-01

Full Text Available The paper presents the diagnostic results of 27 patients with mucinous breast cancer, which is a rare type of invasive ductal breast cancer accounting for less than 2% of all breast cancers. The role of radiological, histological and cytological examination in the diagnosis of mucinous breast cancer is evaluated. In cases with large tumors, it was difficult to differentiate mucinous breast cancer from fibrocystic and other benign breast lesions.

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

Directory of Open Access Journals (Sweden)

Chen C

2014-02-01

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

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

Science.gov (United States)

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

1996-03-01

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

Exploring the breast cancer patient journey: do breast cancer survivors need menopause management support?

Science.gov (United States)

Tanna, Nuttan; Buijs, Helene; Pitkin, Joan

2011-12-01

Breast cancer survivors can be expected to suffer from menopause symptoms with estrogen deprivation due to cancer treatments, in addition to natural menopause-related estrogen loss. To gain an understanding of what support breast cancer patients have when they suffer from menopausal symptoms, and utilize findings to further inform National Health Service (NHS) care provision for breast cancer survivors. Qualitative study with focus group sessions targeting Caucasian and Asian women with breast cancer. Patient stories, with women describing their breast cancer journey and speaking about support received for any menopausal symptoms. Thematic data analysis of transcription. Breast cancer patients were not sure if they had menopausal symptoms or whether this was due to their breast cancer condition or treatment. Patients had an attitude of acceptance of menopausal symptoms and reported trying to cope with these by themselves. This research identifies a need for more information that is culturally sensitive on managing menopause symptoms, both as side-effects of breast cancer treatments as well as for affect on quality of life during the survivorship phase. Our work also gives insight into cultural remedies used for hot flushes by Asian patients, which they consider as 'cooling' foods. Breast cancer patients want to know whether side-effects of cancer treatment persist long term and how these can be managed. There is a need for improved patient support within any new NHS service models that are developed along breast cancer patient pathways, and inclusion of personalized advice for menopause symptoms.

The Effect of Simvastatin on Breast Cancer Cell Growth in Women With Stage I-II Breast Cancer

Science.gov (United States)

2018-03-02

Invasive Breast Carcinoma; Stage I Breast Cancer AJCC v7; Stage IA Breast Cancer AJCC v7; Stage IB Breast Cancer AJCC v7; Stage II Breast Cancer AJCC v6 and v7; Stage IIA Breast Cancer AJCC v6 and v7; Stage IIB Breast Cancer AJCC v6 and v7

Archives of Breast Cancer: An Academic Multidisciplinary Breast Cancer Forum

Directory of Open Access Journals (Sweden)

Ahmad Kaviani

2014-05-01

Full Text Available Welcome to Archives of Breast Cancer (ABC, a new journal with sole focus on breast diseases and especially breast cancer. Breast cancer is a devastating disease that impacts many women and threatens their health and wellbeing. A large number of health professionals from a wide spectrum of clinical disciplines, such as surgery, medical oncology, public health, pathology, radiation oncology, diagnostic radiology, and nuclear medicine, are involved in dealing with such a challenging and common disease.The concept of applying a multidisciplinary approach to clinical and non-clinical aspects of breast cancer has been found to be of vital importance to the understanding of this prevalent type of cancer. Such collaboration can also improve the quantity and quality of the research in this field. To this end, journals which choose to publish multidisciplinary articles as their primary focus can serve as the academic forum to share ideas from a variety of expertise. Archives of Breast Cancer can certainly add to the depth and quality of the research in the field. Articles on a single topic would be readily available to the readers from multiple disciplines and all in one journal. This would eventually lead to fruitful interaction among specialists seeking to investigate this disease, yet,from different perspectives. The benefits of this interaction in the process of devising appropriate strategies and approaches in dealing with the problem are crystal clear.The world of medical sciences has witnessed an abundant increase in the quality and quantity of breast-cancer-related research. In the past 20 years, the number of published articles indexed in PubMed from 1994 to 2014 is more than 5 times than the number published before 1993 (about 170,000 compared to 30,000. Meanwhile, the number of PubMed indexed medical journals dedicated to breast cancer research has also risen from 5 in 1993 to 17 in 2014. This increasing trend highlights an essential need for

Breast cancer statistics, 2011.

Science.gov (United States)

DeSantis, Carol; Siegel, Rebecca; Bandi, Priti; Jemal, Ahmedin

2011-01-01

In this article, the American Cancer Society provides an overview of female breast cancer statistics in the United States, including trends in incidence, mortality, survival, and screening. Approximately 230,480 new cases of invasive breast cancer and 39,520 breast cancer deaths are expected to occur among US women in 2011. Breast cancer incidence rates were stable among all racial/ethnic groups from 2004 to 2008. Breast cancer death rates have been declining since the early 1990s for all women except American Indians/Alaska Natives, among whom rates have remained stable. Disparities in breast cancer death rates are evident by state, socioeconomic status, and race/ethnicity. While significant declines in mortality rates were observed for 36 states and the District of Columbia over the past 10 years, rates for 14 states remained level. Analyses by county-level poverty rates showed that the decrease in mortality rates began later and was slower among women residing in poor areas. As a result, the highest breast cancer death rates shifted from the affluent areas to the poor areas in the early 1990s. Screening rates continue to be lower in poor women compared with non-poor women, despite much progress in increasing mammography utilization. In 2008, 51.4% of poor women had undergone a screening mammogram in the past 2 years compared with 72.8% of non-poor women. Encouraging patients aged 40 years and older to have annual mammography and a clinical breast examination is the single most important step that clinicians can take to reduce suffering and death from breast cancer. Clinicians should also ensure that patients at high risk of breast cancer are identified and offered appropriate screening and follow-up. Continued progress in the control of breast cancer will require sustained and increased efforts to provide high-quality screening, diagnosis, and treatment to all segments of the population. Copyright © 2011 American Cancer Society, Inc.

Breast Cancer (For Kids)

Science.gov (United States)

... Staying Safe Videos for Educators Search English Español Breast Cancer KidsHealth / For Kids / Breast Cancer What's in this ... for it when they are older. What Is Breast Cancer? The human body is made of tiny building ...

Who's talking about breast cancer? Analysis of daily breast cancer posts on the internet.

Science.gov (United States)

Quinn, Edel M; Corrigan, Mark A; McHugh, Seamus M; Murphy, David; O'Mullane, John; Hill, Arnold D; Redmond, Henry Paul

2013-02-01

Breast cancer is the cancer most commonly searched for on the internet. Our aim was to assess daily new breast cancer related posting on the internet. We analyzed numbers of new daily posts for common cancers for one month and subsequently analyzed content of 1426 breast cancer related posts. We also assessed use of online discussion forums for breast cancer related dialogue. Breast related topics had significantly more posts per day compared to others (mean 66.7, p Anonymous posts were common (55%) and less likely to be accurate (p internet has become a primary forum within which health information, particularly relating to breast cancer, is both sought and shared. Increasingly information is provided by patients themselves. Copyright © 2012 Elsevier Ltd. All rights reserved.

Breast Cancer Risk in American Women

Science.gov (United States)

... of Breast & Gynecologic Cancers Breast Cancer Screening Research Breast Cancer Risk in American Women On This Page What ... risk of developing the disease. Personal history of breast cancer : Women who have had breast cancer are more ...

Mammographic Breast Density in Malaysian Women with Breast Cancer

International Nuclear Information System (INIS)

Noriah Jamal; Humairah Samad Cheung

2016-01-01

The objective of this study was to examine the mammographic breast density of women with breast cancer detected on voluntary mammographic screening at two selected screening centers in Malaysia. This was a retrospective study of Full-Field Digital Mammography (FFDM) images of 150 Malaysian women with biopsy-proven breast cancer. The study population comprised 73 Malays (37.7 %), 59 Chinese (39.3 %) and 18 Indians (12.0 %). The Tabar breast density Patterns (I - V) were used to evaluate mammographic breast density. Data were analyzed using descriptive statistics. The results were compared with findings from a similar study on a group of 668 women who did not have breast cancer. The results showed that 44.7 % of the study population had dense breasts (Patterns IV and V), 14.7 % had predominantly fatty breasts (Patterns II and III) while 40.7 % had Pattern I. The proportion of study population with dense breasts decreased with age. In conclusion, the proportion of women with dense breasts decreased with age. Majority of the women with cancer (44.7 %) had dense breasts of Tabar Patterns IV and V, which has been associated with increased risk of breast cancer detected by voluntary mammographic screening. The results support the notion that increased breast density is a risk factor of breast cancer. (author)

Sentinel Lymph Node Biopsy and Isolated Tumor Cells in Invasive Lobular Versus Ductal Breast Cancer

NARCIS (Netherlands)

Truin, Wilfred; Roumen, Rudi M.; Siesling, Sabine; van der Heiden-van der Loo, Margriet; Lobbezoo, Dorien J.; Tjan-Heijnen, Vivianne C.G.; Voogd, Adri C.

2016-01-01

Background Sentinel lymph node (SLN) biopsy is the standard of care for axillary staging in invasive breast cancer. The introduction of SLN biopsy with an extensive pathology examination, in addition to the introduction of the 2002 TNM classification, led to different axillary classification

Breast tissue classification in digital breast tomosynthesis images using texture features: a feasibility study

Science.gov (United States)

Kontos, Despina; Berger, Rachelle; Bakic, Predrag R.; Maidment, Andrew D. A.

2009-02-01

Mammographic breast density is a known breast cancer risk factor. Studies have shown the potential to automate breast density estimation by using computerized texture-based segmentation of the dense tissue in mammograms. Digital breast tomosynthesis (DBT) is a tomographic x-ray breast imaging modality that could allow volumetric breast density estimation. We evaluated the feasibility of distinguishing between dense and fatty breast regions in DBT using computer-extracted texture features. Our long-term hypothesis is that DBT texture analysis can be used to develop 3D dense tissue segmentation algorithms for estimating volumetric breast density. DBT images from 40 women were analyzed. The dense tissue area was delineated within each central source projection (CSP) image using a thresholding technique (Cumulus, Univ. Toronto). Two (2.5cm)2 ROIs were manually selected: one within the dense tissue region and another within the fatty region. Corresponding (2.5cm)3 ROIs were placed within the reconstructed DBT images. Texture features, previously used for mammographic dense tissue segmentation, were computed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate feature classification performance. Different texture features appeared to perform best in the 3D reconstructed DBT compared to the 2D CSP images. Fractal dimension was superior in DBT (AUC=0.90), while contrast was best in CSP images (AUC=0.92). We attribute these differences to the effects of tissue superimposition in CSP and the volumetric visualization of the breast tissue in DBT. Our results suggest that novel approaches, different than those conventionally used in projection mammography, need to be investigated in order to develop DBT dense tissue segmentation algorithms for estimating volumetric breast density.

Breast cancer in systemic lupus

DEFF Research Database (Denmark)

Bernatsky, S.; Ramsey-Goldman, R.; Petri, M.

2017-01-01

Objective There is a decreased breast cancer risk in systemic lupus erythematosus (SLE) versus the general population. We assessed a large sample of SLE patients, evaluating demographic and clinical characteristics and breast cancer risk. Methods We performed case-cohort analyses within a multi......-center international SLE sample. We calculated the breast cancer hazard ratio (HR) in female SLE patients, relative to demographics, reproductive history, family history of breast cancer, and time-dependent measures of anti-dsDNA positivity, cumulative disease activity, and drugs, adjusted for SLE duration. Results...... There were 86 SLE breast cancers and 4498 female SLE cancer-free controls. Patients were followed on average for 7.6 years. Versus controls, SLE breast cancer cases tended to be white and older. Breast cancer cases were similar to controls regarding anti-dsDNA positivity, disease activity, and most drug...

Observed and Predicted Risk of Breast Cancer Death in Randomized Trials on Breast Cancer Screening.

Science.gov (United States)

Autier, Philippe; Boniol, Mathieu; Smans, Michel; Sullivan, Richard; Boyle, Peter

2016-01-01

The role of breast screening in breast cancer mortality declines is debated. Screening impacts cancer mortality through decreasing the number of advanced cancers with poor diagnosis, while cancer treatment works through decreasing the case-fatality rate. Hence, reductions in cancer death rates thanks to screening should directly reflect reductions in advanced cancer rates. We verified whether in breast screening trials, the observed reductions in the risk of breast cancer death could be predicted from reductions of advanced breast cancer rates. The Greater New York Health Insurance Plan trial (HIP) is the only breast screening trial that reported stage-specific cancer fatality for the screening and for the control group separately. The Swedish Two-County trial (TCT)) reported size-specific fatalities for cancer patients in both screening and control groups. We computed predicted numbers of breast cancer deaths, from which we calculated predicted relative risks (RR) and (95% confidence intervals). The Age trial in England performed its own calculations of predicted relative risk. The observed and predicted RR of breast cancer death were 0.72 (0.56-0.94) and 0.98 (0.77-1.24) in the HIP trial, and 0.79 (0.78-1.01) and 0.90 (0.80-1.01) in the Age trial. In the TCT, the observed RR was 0.73 (0.62-0.87), while the predicted RR was 0.89 (0.75-1.05) if overdiagnosis was assumed to be negligible and 0.83 (0.70-0.97) if extra cancers were excluded. In breast screening trials, factors other than screening have contributed to reductions in the risk of breast cancer death most probably by reducing the fatality of advanced cancers in screening groups. These factors were the better management of breast cancer patients and the underreporting of breast cancer as the underlying cause of death. Breast screening trials should publish stage-specific fatalities observed in each group.

Hormonal modulation of breast cancer gene expression: implications for intrinsic subtyping in pre-menopausal women

OpenAIRE

Sarah M Bernhardt; Pallave Dasari; David Walsh; Amanda R Townsend; Amanda R Townsend; Timothy J Price; Timothy J Price; Wendy V Ingman

2016-01-01

Clinics are increasingly adopting gene expression profiling to diagnose breast cancer subtype, providing an intrinsic, molecular portrait of the tumour. For example, the PAM50-based Prosigna test quantifies expression of 50 key genes to classify breast cancer subtype, and this method of classification has been demonstrated to be superior over traditional immunohistochemical methods that detect proteins, to predict risk of disease recurrence. However, these tests were largely developed and val...

Benign breast disease, mammographic breast density, and the risk of breast cancer.

Science.gov (United States)

Tice, Jeffrey A; O'Meara, Ellen S; Weaver, Donald L; Vachon, Celine; Ballard-Barbash, Rachel; Kerlikowske, Karla

2013-07-17

Benign breast disease and high breast density are prevalent, strong risk factors for breast cancer. Women with both risk factors may be at very high risk. We included 42818 women participating in the Breast Cancer Surveillance Consortium who had no prior diagnosis of breast cancer and had undergone at least one benign breast biopsy and mammogram; 1359 women developed incident breast cancer in 6.1 years of follow-up (78.1% invasive, 21.9% ductal carcinoma in situ). We calculated hazard ratios (HRs) using Cox regression analysis. The referent group was women with nonproliferative changes and average density. All P values are two-sided. Benign breast disease and breast density were independently associated with breast cancer. The combination of atypical hyperplasia and very high density was uncommon (0.6% of biopsies) but was associated with the highest risk for breast cancer (HR = 5.34; 95% confidence interval [CI] = 3.52 to 8.09, P < .001). Proliferative disease without atypia (25.6% of biopsies) was associated with elevated risk that varied little across levels of density: average (HR = 1.37; 95% CI = 1.11 to 1.69, P = .003), high (HR = 2.02; 95% CI = 1.68 to 2.44, P < .001), or very high (HR = 2.05; 95% CI = 1.54 to 2.72, P < .001). Low breast density (4.5% of biopsies) was associated with low risk (HRs <1) for all benign pathology diagnoses. Women with high breast density and proliferative benign breast disease are at very high risk for future breast cancer. Women with low breast density are at low risk, regardless of their benign pathologic diagnosis.

[Hormonotherapy for breast cancer prevention: What about women with genetic predisposition to breast cancer?].

Science.gov (United States)

Sénéchal, Claire; Reyal, Fabien; Callet, Nasrine; This, Pascale; Noguès, Catherine; Stoppa-Lyonnet, Dominique; Fourme, Emmanuelle

2016-03-01

In France, women carrying BRCA1/2 mutation, at an identified high risk of breast cancer are recommended to undergo breast MRI screening. That screening does not however prevent the risk of developing a breast cancer. The only alternative to breast cancer screening available in France is surgical prevention by prophylactic mastectomy. An interesting option for women who wish to reduce their breast cancer risk, but are unready for prophylactic mastectomy is a preventive hormonal treatment by aromatase inhibitors, or selective estrogens receptor modulators (SERMs). Reliable clinical trials show the efficiency of tamoxifen, raloxifen, exemestane, and anastrozole especially, in reducing breast cancer incidence by 33%, 34%, 65% and 53% respectively. This article tries to sum up the main published trials of breast cancer prevention with hormonal treatment, and presents the latest American and English clinical guidelines concerning hormonal prevention for women at high risk of breast cancer, and starts thinking about the possibilities of hormonoprevention, especially among women carrying a BRCA1/2 mutation in France. Copyright © 2016 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

Advances in the Molecular Analysis of Breast Cancer: Pathway Toward Personalized Medicine.

Science.gov (United States)

Rosa, Marilin

2015-04-01

Breast cancer is a heterogeneous disease that encompasses a wide range of clinical behaviors and histological and molecular variants. It is the most common type of cancer affecting women worldwide and is the second leading cause of cancer death. A comprehensive literature search was performed to explore the advances in molecular medicine related to the diagnosis and treatment of breast cancer. During the last few decades, advances in molecular medicine have changed the landscape of cancer treatment as new molecular tests complement and, in many instances, exceed traditional methods for determining patient prognosis and response to treatment options. Personalized medicine is becoming the standard of care around the world. Developments in molecular profiling, genomic analysis, and the discovery of targeted drug therapies have significantly improved patient survival rates and quality of life. This review highlights what pathologists need to know about current molecular tests for classification and prognostic/ predictive assessment of breast carcinoma as well as their role as part of the medical team.

Metabolic Syndrome and Breast Cancer Risk.

Science.gov (United States)

Wani, Burhan; Aziz, Shiekh Aejaz; Ganaie, Mohammad Ashraf; Mir, Mohammad Hussain

2017-01-01

The study was meant to estimate the prevalence of metabolic syndrome in patients with breast cancer and to establish its role as an independent risk factor on occurrence of breast cancer. Fifty women aged between 40 and 80 years with breast cancer and fifty controls of similar age were assessed for metabolic syndrome prevalence and breast cancer risk factors, including age at menarche, reproductive status, live births, breastfeeding, and family history of breast cancer, age at diagnosis of breast cancer, body mass index, and metabolic syndrome parameters. Metabolic syndrome prevalence was found in 40.0% of breast cancer patients, and 18.0% of those in control group ( P = 0.02). An independent and positive association was seen between metabolic syndrome and breast cancer risk (odds ratio = 3.037; 95% confidence interval 1.214-7.597). Metabolic syndrome is more prevalent in breast cancer patients and is an independent risk factor for breast cancer.

Improved detection of breast cancer on FDG-PET cancer screening using breast positioning device

International Nuclear Information System (INIS)

Kaida, Hayato; Ishibashi, Masatoshi; Fujii, Teruhiko; Kurata, Seiji; Ogo, Etsuyo; Hayabuchi, Naofumi; Tanaka, Maki

2008-01-01

The aim of this study was to investigate the detection rate of breast cancer by positron emission tomography cancer screening using a breast positioning device. Between January 2004 and January 2006, 1,498 healthy asymptomatic individuals underwent cancer screening by fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET) at our institution; 660 of 1498 asymptomatic healthy women underwent breast PET imaging in the prone position using the breast positioning device to examine the mammary glands in addition to whole-body PET imaging. All subjects that showed abnormal 18 F-FDG uptake in the mammary glands were referred for further examination or surgery at our institution or a local hospital. Our data were compared with the histopathological findings or findings of other imaging modalities in our institution and replies from the doctors at another hospital. Of the 660 participants, 7 (1.06%) were found to have breast cancers at a curable stage. All the seven cancers were detected by breast PET imaging, but only five of these were detected by whole-body PET imaging; the other two were detected by breast PET imaging using the breast positioning device. In cancer screening, prone breast imaging using a positioning device may help to improve the detection rate of breast cancer. However, overall cancer including mammography and ultrasonography screening should be performed to investigate the false-negative cases and reduce false-positive cases. The effectiveness of prone breast PET imaging in cancer screening should be investigated using a much larger number of cases in the near future. (author)

Early Diagnosis of Breast Cancer.

Science.gov (United States)

Wang, Lulu

2017-07-05

Early-stage cancer detection could reduce breast cancer death rates significantly in the long-term. The most critical point for best prognosis is to identify early-stage cancer cells. Investigators have studied many breast diagnostic approaches, including mammography, magnetic resonance imaging, ultrasound, computerized tomography, positron emission tomography and biopsy. However, these techniques have some limitations such as being expensive, time consuming and not suitable for young women. Developing a high-sensitive and rapid early-stage breast cancer diagnostic method is urgent. In recent years, investigators have paid their attention in the development of biosensors to detect breast cancer using different biomarkers. Apart from biosensors and biomarkers, microwave imaging techniques have also been intensely studied as a promising diagnostic tool for rapid and cost-effective early-stage breast cancer detection. This paper aims to provide an overview on recent important achievements in breast screening methods (particularly on microwave imaging) and breast biomarkers along with biosensors for rapidly diagnosing breast cancer.

Study on the plasma leptin level and leptin mRNA expression in cancerous breast tissue in patients with breast carcinoma complicated with obesity

International Nuclear Information System (INIS)

Li Chunrui; Liu Wenli; Sun Hanying; Zhou Jianfeng

2006-01-01

Objective: To study the plasma leptin level and leptin mRNA expression in cancerous breast tissue in patients with breast cancer complicated with obesity. Methods: Plasma leptin levels were measured with RIA in 48 breast cancer patients with obesity, 36 patients with various benign breast disorders and obesity and 40 controls (with simple obesity only). The leptin mRNA expression in the surgical specimens from the 84 patients with breast disease was also examined with RT-PCR, Results: The plasma leptin levels in the breast cancer patients (12.02 ± 1.23 μg/L) were significantly higher than those in patients with benign breast disorders (9.84 ± 0.98 μg/L) and controls (9.79 ± 1.16 μg/L) (both P<0.05). The expression levels of leptin mRNA in specimens from malignant breast disease (0.71 ± 0.32), were significantly higher than those in specimens from benign breast diseases (0.41 ± 0.26) (P<0.05), The plasma leptin levels and the tissue leptin mRNA expression levels were mutually positively correlated (r=0.4220 ,P 0.0180). These levels were not correlated with the presence of axillary metastasis, TMN stage, menstrual status, pathological classification and other parameters. Conclusion: Leptin might be a promotive factor in the development of breast cancer. (authors)

Opioids and breast cancer recurrence

DEFF Research Database (Denmark)

Cronin-Fenton, Deirdre P; Heide-Jørgensen, Uffe; Ahern, Thomas P

2015-01-01

BACKGROUND: Opioids may alter immune function, thereby potentially affecting cancer recurrence. The authors investigated the association between postdiagnosis opioid use and breast cancer recurrence. METHODS: Patients with incident, early stage breast cancer who were diagnosed during 1996 through...... 2008 in Denmark were identified from the Danish Breast Cancer Cooperative Group Registry. Opioid prescriptions were ascertained from the Danish National Prescription Registry. Follow-up began on the date of primary surgery for breast cancer and continued until breast cancer recurrence, death......, emigration, 10 years, or July 31, 2013, whichever occurred first. Cox regression models were used to compute hazard ratios and 95% confidence intervals associating breast cancer recurrence with opioid prescription use overall and by opioid type and strength, immunosuppressive effect, chronic use (≥6 months...

Breast cancer screening

International Nuclear Information System (INIS)

Vandenbroucke, A.

1987-01-01

Many studies have shown that breast cancer screening is able to reduce breast cancer mortality, including the HIP study, the Swedish Trial and the Netherlands studies. Mammography is considered as the most effective method for breast cancer screening but it might be unfeasible for some reasons: - the population acceptability of the method might be low. Indeed, most populations of the South of Europe are less compliant to mass screening than populations of the North of Europe; - the medical equipment and personnel - radiologists and pathologists - might be insufficient; - it might be too costly for the National Health Service, specially where the incidence rate of breast cancer is relatively low (i.e. Greece, Portugal). The validity of screening tests is judged by their sensitivity and their specificity

Breast cancer screening with digital breast tomosynthesis.

Science.gov (United States)

Skaane, Per

2017-01-01

To give an overview of studies comparing full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) in breast cancer screening. The implementation of tomosynthesis in breast imaging is rapidly increasing world-wide. Experimental clinical studies of relevance for DBT screening have shown that tomosynthesis might have a great potential in breast cancer screening, although most of these retrospective reading studies are based on small populations, so that final conclusions are difficult to draw from individual reports. Several retrospective studies and three prospective trials on tomosynthesis in breast cancer screening have been published so far, confirming the great potential of DBT in mammography screening. The main results of these screening studies are presented. The retrospective screening studies from USA have all shown a significant decrease in the recall rate using DBT as adjunct to mammography. Most of these studies have also shown an increase in the cancer detection rate, and the non-significant results in some studies might be explained by a lack of statistical power. All the three prospective European trials have shown a significant increase in the cancer detection rate. The retrospective and the prospective screening studies comparing FFDM and DBT have all demonstrated that tomosynthesis has a great potential for improving breast cancer screening. DBT should be regarded as a better mammogram that could improve or overcome limitations of the conventional mammography, and tomosynthesis might be considered as the new technique in the next future of breast cancer screening.

Magnetic resonance imaging in the detection of breast cancer

International Nuclear Information System (INIS)

Olcucuoglu, E.; Tuncbilek, I.; Oztekin, P.; Asal, N.; Yilmaz, O.; Kosar, U.

2012-01-01

Full text: Purpose: The aim of the study is to state breast Magnetic Resonance Imaging (MRI) diagnostic value of examination of MG (MG), ultrasonography (U.S.) by comparing with the results of a biopsy revealed, and emphasize the value of detecting breast cancer. Materials and methods: 327 patients were included in the breast MRI examination. MG breast MRI and U.S. were performed before the cases, respectively. All tests which are in fact planned no later than two months in between and evaluation were performed by two radiologists. BI-RADS classification was evaluated according to the investigations. As a result of MRI BIRADS 4 and 5 cases that were diagnosed in a biopsy was recommended. Following the recommended BI-RADS 3 biopsies diagnosed as those of the cases were due to the physical examination findings. MG with the results of a biopsy, U.S., and MRI results were compared. Results: The study recommended a biopsy of BIRADS 4 and 5 group, 36 out of 63 cases of breast cancer (32 invasive ductal carcinomas, 2 invasive lobular carcinoma, 1 lymphoma, 1 angiosarcoma) were diagnosed. 16% of patients with BI-RADS 4 group, 94% of BI-RADS 5 group of patients were diagnosed as breast cancer. BI-RADS is a group of breast cancer with axillary adenopathy in a patient with the diagnosis of MRI examination was no diagnostic. False-positive cases in our study were counted for the majority of cases as fibrocystic. Conclusion: MRI sensitivity, specificity, positive predictive value, negative predictive value and accuracy of tests with the highest rates, while the combination of MG and MRI, were found to be the best non-invasive examination methods

Breast Cancer Rates by State

Science.gov (United States)

... Associated Lung Ovarian Prostate Skin Uterine Cancer Home Breast Cancer Rates by State Language: English (US) Español (Spanish) ... from breast cancer each year. Rates of Getting Breast Cancer by State The number of people who get ...

CE-Magnetic Resonance mammography for the evaluation of the contralateral breast in patients with diagnosed breast cancer

International Nuclear Information System (INIS)

Pediconi, Federica; Venditti, Fiammetta; Padula, Simona; Roselli, Antonella; Moriconi, Enrica; Catalano, Carlo; Passariello, Roberto; Giacomelli, Laura

2005-01-01

Purpose. To evaluate the role of contrast-enhanced Magnetic Resonance Mammography (MRM) in the evaluation of the contralateral breast in patients with recently diagnosed breast cancer. Materials and methods. Fifty patients with proved unilateral breast cancer, with a negative contralateral breast at physical examination, ultrasound and mammography, were studied with a 1.5 T magnet (Siemens, Vision Plus, Germany). A bilateral breast surface coil was used. Dynamic 3D Flash T1-weighted sequences were acquired in the axial plane before and 0, 2, 4, 6 and 8 minutes after the administration of 0.1 mmol/kg of Gd-BOPTA at a flow rate of 2 ml/s followed by 10 ml of saline. The level of suspicion was reported on a scale from 0 to 5 following the BI-RADS classification, based on lesion morphology and kinetic features. The results were compared with the histological findings after biopsy or surgery. Results. Fourteen out of 50 patients (28%) had contralateral lesions identified on MRM. Biopsy was performed in four of them for suspicious lesions (BI-RADS 4) while 10 patients underwent surgery because of highly suggestive malignant lesions (BI-RADS 5). Histology diagnosed three fibroadenomas, 5 ductal carcinoma in situ, 2 lobular carcinomas in situ, 3 invasive ductal carcinomas and 1 invasive lobular carcinoma. Contrast enhanced MRM yielded no false negative and three false positives. Conclusions. Our results demonstrate a very good accuracy of Magnetic Resonance Mammography in the detection of synchronous contralateral cancer in patients with newly diagnosed breast cancer. Therefore, contrast-enhanced MRM could be introduced to screen patients with proven breast cancer before they under-go surgery [it

Propranolol and survival from breast cancer

DEFF Research Database (Denmark)

Cardwell, Chris R; Pottegård, Anton; Vaes, Evelien

2016-01-01

BACKGROUND: Preclinical studies have demonstrated that propranolol inhibits several pathways involved in breast cancer progression and metastasis. We investigated whether breast cancer patients who used propranolol, or other non-selective beta-blockers, had reduced breast cancer-specific or all......-cause mortality in eight European cohorts. METHODS: Incident breast cancer patients were identified from eight cancer registries and compiled through the European Cancer Pharmacoepidemiology Network. Propranolol and non-selective beta-blocker use was ascertained for each patient. Breast cancer-specific and all......-analysis techniques. Dose-response analyses by number of prescriptions were also performed. Analyses were repeated investigating propranolol use before cancer diagnosis. RESULTS: The combined study population included 55,252 and 133,251 breast cancer patients in the analysis of breast cancer-specific and all...

Comparison of Back propagation neural network and Back propagation neural network Based Particle Swarm intelligence in Diagnostic Breast Cancer

Directory of Open Access Journals (Sweden)

Farahnaz SADOUGHI

2014-03-01

Full Text Available Breast cancer is the most commonly diagnosed cancer and the most common cause of death in women all over the world. Use of computer technology supporting breast cancer diagnosing is now widespread and pervasive across a broad range of medical areas. Early diagnosis of this disease can greatly enhance the chances of long-term survival of breast cancer victims. Artificial Neural Networks (ANN as mainly method play important role in early diagnoses breast cancer. This paper studies Levenberg Marquardet Backpropagation (LMBP neural network and Levenberg Marquardet Backpropagation based Particle Swarm Optimization(LMBP-PSO for the diagnosis of breast cancer. The obtained results show that LMBP and LMBP based PSO system provides higher classification efficiency. But LMBP based PSO needs minimum training and testing time. It helps in developing Medical Decision System (MDS for breast cancer diagnosing. It can also be used as secondary observer in clinical decision making.

Early detection of breast cancer: benefits and risks of supplemental breast ultrasound in asymptomatic women with mammographically dense breast tissue. A systematic review

International Nuclear Information System (INIS)

Nothacker, Monika; Duda, Volker; Hahn, Markus; Warm, Mathias; Degenhardt, Friedrich; Madjar, Helmut; Weinbrenner, Susanne; Albert, Ute-Susann

2009-01-01

Mammographic screening alone will miss a certain fraction of malignancies, as evidenced by retrospective reviews of mammograms following a subsequent screening. Mammographic breast density is a marker for increased breast cancer risk and is associated with a higher risk of interval breast cancer, i.e. cancer detected between screening tests. The purpose of this review is to estimate risks and benefits of supplemental breast ultrasound in women with negative mammographic screening with dense breast tissue. A systematic search and review of studies involving mammography and breast ultrasound for screening of breast cancer was conducted. The search was performed for the period 1/2000-8/2008 within the data source of PubMed, DARE, and Cochrane databases. Inclusion and exclusion criteria were determined prospectively, and the Oxford evidence classification system for diagnostic studies was used for evidence level. The parameters biopsy rate, positive predictive value (PPV) for biopsy, cancer yield for breast ultrasound alone, and carcinoma detection rate by breast density were extracted or constructed. The systematic search identified no randomized controlled trials or systematic reviews, six cohort studies of intermediate level of evidence (3b) were found. Only two of the studies included adequate follow-up of subjects with negative or benign findings. Supplemental breast ultrasound after negative mammographic screening permitted diagnosis of primarily invasive carcinomas in 0.32% of women in breast density type categories 2-4 of the American College of Radiology (ACR); mean tumor size for those identified was 9.9 mm, 90% with negative lymph node status. Most detected cancers occurred in mammographically dense breast ACR types 3 and 4. Biopsy rates were in the range 2.3%-4.7%, with PPV of 8.4-13.7% for those biopsied due to positive ultrasound, or about one third of the PPV of biopsies due to mammography. Limitations: The study populations included wide age ranges, and

Breast carcinoma - diagnostics, therapy and resistance

International Nuclear Information System (INIS)

Kuzma-Richert, A.; Saczko, J.; Kulbacka, J.

2011-01-01

Breast cancer is a pathologically and clinically heterogeneous disease with a variable prognosis. This type of cancer is the most common female cancer in Poland. According to data collected up to 2004, approximately 12,000 new breast cancer cases per year were diagnosed in women in Poland, and approximately 5000 patients died yearly of breast cancer. The authors present the histopathology, diagnostics, classification and general types of systemic therapy of breast cancer. (authors)

SVM and SVM Ensembles in Breast Cancer Prediction.

Science.gov (United States)

Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong

2017-01-01

Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.

SVM and SVM Ensembles in Breast Cancer Prediction.

Directory of Open Access Journals (Sweden)

Min-Wei Huang

Full Text Available Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.

Breast Cancer in Men

Science.gov (United States)

... ultrasound or a breast MRI cannot rule out breast cancer then you will need a biopsy to confirm diagnosis. If diagnosed When first diagnosed with breast cancer, many men are in shock. After all, ...

A new intelligent classifier for breast cancer diagnosis based on a rough set and extreme learning machine: RS + ELM

OpenAIRE

KAYA, Yılmaz

2014-01-01

Breast cancer is one of the leading causes of death among women all around the world. Therefore, true and early diagnosis of breast cancer is an important problem. The rough set (RS) and extreme learning machine (ELM) methods were used collectively in this study for the diagnosis of breast cancer. The unnecessary attributes were discarded from the dataset by means of the RS approach. The classification process by means of ELM was performed using the remaining attributes. The Wisconsin B...

Risk of primary non-breast cancer after female breast cancer by age at diagnosis

DEFF Research Database (Denmark)

Mellemkjær, Lene; Christensen, Jane; Frederiksen, Kirsten Skovsgaard

2011-01-01

Women diagnosed with breast cancer at young age have been shown to be at higher risk of developing a new primary cancer than women diagnosed at older ages, but little is known about whether adjustment for calendar year of breast cancer diagnosis, length of follow-up, and/or breast cancer treatment...

Hierarchical clustering of breast cancer methylomes revealed differentially methylated and expressed breast cancer genes.

Directory of Open Access Journals (Sweden)

I-Hsuan Lin

Full Text Available Oncogenic transformation of normal cells often involves epigenetic alterations, including histone modification and DNA methylation. We conducted whole-genome bisulfite sequencing to determine the DNA methylomes of normal breast, fibroadenoma, invasive ductal carcinomas and MCF7. The emergence, disappearance, expansion and contraction of kilobase-sized hypomethylated regions (HMRs and the hypomethylation of the megabase-sized partially methylated domains (PMDs are the major forms of methylation changes observed in breast tumor samples. Hierarchical clustering of HMR revealed tumor-specific hypermethylated clusters and differential methylated enhancers specific to normal or breast cancer cell lines. Joint analysis of gene expression and DNA methylation data of normal breast and breast cancer cells identified differentially methylated and expressed genes associated with breast and/or ovarian cancers in cancer-specific HMR clusters. Furthermore, aberrant patterns of X-chromosome inactivation (XCI was found in breast cancer cell lines as well as breast tumor samples in the TCGA BRCA (breast invasive carcinoma dataset. They were characterized with differentially hypermethylated XIST promoter, reduced expression of XIST, and over-expression of hypomethylated X-linked genes. High expressions of these genes were significantly associated with lower survival rates in breast cancer patients. Comprehensive analysis of the normal and breast tumor methylomes suggests selective targeting of DNA methylation changes during breast cancer progression. The weak causal relationship between DNA methylation and gene expression observed in this study is evident of more complex role of DNA methylation in the regulation of gene expression in human epigenetics that deserves further investigation.

Mammographic density and breast cancer risk in breast screening assessment cases and women with a family history of breast cancer.

Science.gov (United States)

Duffy, Stephen W; Morrish, Oliver W E; Allgood, Prue C; Black, Richard; Gillan, Maureen G C; Willsher, Paula; Cooke, Julie; Duncan, Karen A; Michell, Michael J; Dobson, Hilary M; Maroni, Roberta; Lim, Yit Y; Purushothaman, Hema N; Suaris, Tamara; Astley, Susan M; Young, Kenneth C; Tucker, Lorraine; Gilbert, Fiona J

2018-01-01

Mammographic density has been shown to be a strong independent predictor of breast cancer and a causative factor in reducing the sensitivity of mammography. There remain questions as to the use of mammographic density information in the context of screening and risk management, and of the association with cancer in populations known to be at increased risk of breast cancer. To assess the association of breast density with presence of cancer by measuring mammographic density visually as a percentage, and with two automated volumetric methods, Quantra™ and VolparaDensity™. The TOMosynthesis with digital MammographY (TOMMY) study of digital breast tomosynthesis in the Breast Screening Programme of the National Health Service (NHS) of the United Kingdom (UK) included 6020 breast screening assessment cases (of whom 1158 had breast cancer) and 1040 screened women with a family history of breast cancer (of whom two had breast cancer). We assessed the association of each measure with breast cancer risk in these populations at enhanced risk, using logistic regression adjusted for age and total breast volume as a surrogate for body mass index (BMI). All density measures showed a positive association with presence of cancer and all declined with age. The strongest effect was seen with Volpara absolute density, with a significant 3% (95% CI 1-5%) increase in risk per 10 cm 3 of dense tissue. The effect of Volpara volumetric density on risk was stronger for large and grade 3 tumours. Automated absolute breast density is a predictor of breast cancer risk in populations at enhanced risk due to either positive mammographic findings or family history. In the screening context, density could be a trigger for more intensive imaging. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Contralateral breast cancer risk

International Nuclear Information System (INIS)

Unnithan, Jaya; Macklis, Roger M.

2001-01-01

The use of breast-conserving treatment approaches for breast cancer has now become a standard option for early stage disease. Numerous randomized studies have shown medical equivalence when mastectomy is compared to lumpectomy followed by radiotherapy for the local management of this common problem. With an increased emphasis on patient involvement in the therapeutic decision making process, it is important to identify and quantify any unforeseen risks of the conservation approach. One concern that has been raised is the question of radiation- related contralateral breast cancer after breast radiotherapy. Although most studies do not show statistically significant evidence that patients treated with breast radiotherapy are at increased risk of developing contralateral breast cancer when compared to control groups treated with mastectomy alone, there are clear data showing the amount of scattered radiation absorbed by the contralateral breast during a routine course of breast radiotherapy is considerable (several Gy) and is therefore within the range where one might be concerned about radiogenic contralateral tumors. While radiation related risks of contralateral breast cancer appear to be small enough to be statistically insignificant for the majority of patients, there may exist a smaller subset which, for genetic or environmental reasons, is at special risk for scatter related second tumors. If such a group could be predicted, it would seem appropriate to offer either special counselling or special prevention procedures aimed at mitigating this second tumor risk. The use of genetic testing, detailed analysis of breast cancer family history, and the identification of patients who acquired their first breast cancer at a very early age may all be candidate screening procedures useful in identifying such at- risk groups. Since some risk mitigation strategies are convenient and easy to utilize, it makes sense to follow the classic 'ALARA' (as low as reasonably

Radiologic aspects of breast cancers detected through a breast cancer screening program

International Nuclear Information System (INIS)

Azavedo, E.; Svane, G.

1991-01-01

Early detection in breast cancer and reduced mortality in women with this disease is today attributed to widespread use of mammography. High-quality performance is essential in all steps of breast cancer screening programs in order to avoid unnecessary anxiety and surgery in the women concerned. This report presents radiologic aspects of screening cancers. A total of 8370 asymptomatic women aged 50-69 years were screened with 2-view mammography, of which only 70 (0.84 percent) were selected for surgery after a thorough work-up. Cancers were verified histologically in 61 women and 9 showed non-malignant histology, giving a cancer detection rate of 7.3 cancers per thousand screened asymptomatic women. The benign/malignant ratio in the operated cases is thus approximately 1:7. The cancers detected showed all existing types of mammographic features where 77 percent (47 cases) showed rather typical findings, such as spiculated densities both with and without microcalcifications. The results indicate that surgery can be minimized without impairing the breast cancer detection rate. Radiologists in screening programs should be aware that a large proportion of non-palpable breast cancers present in rather unconventional forms. This point is important in order to maintain a high cancer detection rate and thereby justify the widespread use of mammography as a screening tool for breast cancer in asymptomatic women. (author). 20 refs.; 1 tab

The potential prognostic value of connexin 26 and 46 expression in neoadjuvant-treated breast cancer

Directory of Open Access Journals (Sweden)

Teleki Ivett

2013-02-01

Full Text Available Abstract Background Several classification systems are available to assess pathological response to neoadjuvant chemotherapy in breast cancer, but reliable biomarkers to predict the efficiency of primary systemic therapy (PST are still missing. Deregulation of gap junction channel forming connexins (Cx has been implicated in carcinogenesis and tumour progression through loss of cell cycle control. In this study we correlated Cx expression and cell proliferation with disease survival and pathological response to neoadjuvant chemotherapy in breast cancers using existing classification systems. Methods The expression of Cx26, Cx32, Cx43, Cx46 and Ki67 was evaluated in 96 breast cancer patients prior to and after neoadjuvant chemotherapy using duplicate cores in tissue microarrays (TMA. Cx plaques of Results In our cohort dominated by hormone receptor (ER/PR positive and HER2 negative cases, only the CPS-EG classification showed prognostic relevance: cases with scores 1–2 had significantly better overall survival (p=0.015 than cases with scores 3–5. Pre-chemotherapy Cx43 expression correlated positively with hormone receptor status both before and after chemotherapy and had a negative correlation with HER2 expression pre-chemotherapy. There was a positive correlation between Cx32 and HER2 expression pre-chemotherapy and between Cx32 and Ki67 expression post-chemotherapy. A negative correlation was found between post-chemotherapy Cx46 and Ki67 expression. Decreased post-chemotherapy Cx26 expression (20% pre- and post-chemotherapy correlated with significantly better survival in the intermediate prognostic subgroups of EWGBSP TR2b (ppre-chemo=0.006; Sataloff TB (ppre-chemo=0.005; ppost-chemo=0.029 and in Miller-Payne G3 (ppre-chemo=0.002; ppost-chemo=0.012 classifications. Pre-chemotherapy, Cx46 expression was the only marker that correlated with overall survival within these subgroups. Conclusion Our results suggest that Cx46 and Cx26 expression

Breast cancer staging

Science.gov (United States)

... this page: //medlineplus.gov/ency/patientinstructions/000911.htm Breast cancer staging To use the sharing features on this ... Once your health care team knows you have breast cancer , they will do more tests to stage it. ...

Early Diagnosis of Breast Cancer by Identifying Malignant Cells Within Neoplasias Histologically Classified as Benign

National Research Council Canada - National Science Library

Lelievre, Sophie A

2005-01-01

Current diagnostic tools permit the classification of breast neoplasias into categories that represent different relative risks of developing cancer, but they do not indicate which particular lesion...

Immunohistochemical Expression of Survivin in Breast Carcinoma: Relationship with Clinico pathological Parameters, Proliferation and Molecular Classification

International Nuclear Information System (INIS)

YOUSSEF, N.S.; HEWEDI, I.H.; ABD RABOH, N.M.

2008-01-01

Background and Objective: Survivin is a novel member of the inhibitor of apoptosis (IAP) gene family. It is associated with more aggressive behavior and parameters of poor prognosis in most human cancers including gastric, colorectal and bladder carcinomas. However, conflicting data exist on its prognostic effect in breast cancer. This current study is designed to assess survivin expression in breast carcinoma relating results with clinico pathological parameters, proliferation (MIB-1) and molecular classification. Material and Methods: Our retrospective study com- prised of 65 archived cases of breast carcinoma. Samples from the tumor and the adjacent normal breast tissue were immuno stained for survivin and MIB-1. Nuclear and cytoplasmic survivin expression was evaluated in normal breast tissue and carcinoma regarding both the intensity and the percentage of positive cells. ER, PR, HER2 were used as surrogate markers to classify the cases into four molecular subtypes. Results: Survivin expression was detected in 78.5% of breast carcinomas. The adjacent normal breast tissue was immuno negative. Survivin expression showed significant association with increased tumor size ( p <0.0001), high histologic grade ( p =0.04), lymph node metastases ( p <0.001), advanced tumor stage ( p <0.0001), MIB-1 expression ( p =0.02), negative estrogen receptor status ( p =0.01) and negative progesterone receptor status ( p <0.0001). The subcellular localization of survivin significantly related to histologic grade, stage and lymph node involvement. The percentage of TNP (triple negative phenotype) and HER2+/ER-PR- tumors expressing survivin were significantly higher compared to the Luminal subtypes ( p =0.01). Conclusion: Survivin expression was associated with parameters of poor prognosis in breast cancer. Moreover, the cancer-specific expression of survivin, coupled with its importance in inhibiting cell death and in regulating cell division, makes it a potential target for novel

A Developmental Approach to Characterizing the Tissue-Invasion Gene Program in Breast Cancer

Science.gov (United States)

2001-09-01

OF PAGES Breast Cancer 24 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF...induced host response. Am J. Pathol. 149:273-282, 1996. 4. Wolf, c., Rouyer, N., Lutz, Y., Adida , C., Loriot, M., Bellocq, J.P., Chambon, P., and Basset...following a 5 d incubation period. (upper left and right panels). In contrast, MT1-MMP-transfected cells perforated the BM in representative TEM and

Targeted Therapy for Breast Cancer Prevention

Science.gov (United States)

den Hollander, Petra; Savage, Michelle I.; Brown, Powel H.

2013-01-01

With a better understanding of the etiology of breast cancer, molecularly targeted drugs have been developed and are being testing for the treatment and prevention of breast cancer. Targeted drugs that inhibit the estrogen receptor (ER) or estrogen-activated pathways include the selective ER modulators (tamoxifen, raloxifene, and lasofoxifene) and aromatase inhibitors (AIs) (anastrozole, letrozole, and exemestane) have been tested in preclinical and clinical studies. Tamoxifen and raloxifene have been shown to reduce the risk of breast cancer and promising results of AIs in breast cancer trials, suggest that AIs might be even more effective in the prevention of ER-positive breast cancer. However, these agents only prevent ER-positive breast cancer. Therefore, current research is focused on identifying preventive therapies for other forms of breast cancer such as human epidermal growth factor receptor 2 (HER2)-positive and triple-negative breast cancer (TNBC, breast cancer that does express ER, progesterone receptor, or HER2). HER2-positive breast cancers are currently treated with anti-HER2 therapies including trastuzumab and lapatinib, and preclinical and clinical studies are now being conducted to test these drugs for the prevention of HER2-positive breast cancers. Several promising agents currently being tested in cancer prevention trials for the prevention of TNBC include poly(ADP-ribose) polymerase inhibitors, vitamin D, and rexinoids, both of which activate nuclear hormone receptors (the vitamin D and retinoid X receptors). This review discusses currently used breast cancer preventive drugs, and describes the progress of research striving to identify and develop more effective preventive agents for all forms of breast cancer. PMID:24069582

Hormone Therapy for Breast Cancer

Science.gov (United States)

... Common Cancer Types Recurrent Cancer Common Cancer Types Bladder Cancer Breast Cancer Colorectal Cancer Kidney (Renal Cell) Cancer ... sensitive breast cancer cells contain proteins called hormone receptors that become activated when hormones bind to them. ...

Ultrasound screening of contralateral breast after surgery for breast cancer

Energy Technology Data Exchange (ETDEWEB)

Kim, Seung Ja [Department of Radiology, Seoul Metropolitan Government Seoul National University, Boramae Medical Center (Korea, Republic of); Chung, Se-Yeong; Chang, Jung Min; Cho, Nariya [Department of Radiology, Seoul National University Hospital (Korea, Republic of); Han, Wonshik [Department of Surgery, Seoul National University Hospital (Korea, Republic of); Moon, Woo Kyung, E-mail: moonwk@snu.ac.kr [Department of Radiology, Seoul National University Hospital (Korea, Republic of)

2015-01-15

Highlights: • The addition of supplemental US to mammography depicted additional 5.0 cancers per 1000 postoperative women. • Positive biopsy rate of mammography-detected lesions was 66.7% (4 of 6) and that of US-detected lesions was 40.0% (6 of 15). • US can be helpful to detect mammographically occult breast cancer in the contralateral breast in women with previous history of cancer and dense breast. - Abstract: Objective: To determine whether supplemental screening ultrasound (US) to mammography could improve cancer detection rate of the contralateral breast in patients with a personal history of breast cancer and dense breasts. Materials and methods: During a one-year study period, 1314 screening patients with a personal history of breast cancer and dense breasts simultaneously underwent mammography and breast US. BI-RADS categories were given for mammography or US-detected lesions in the contralateral breast. The reference standard was histology and/or 1-year imaging follow-up, and the cancer rate according to BI-RADS categories and cancer detection rate and positive biopsy rate according to detection modality were analyzed. Results: Of 1314 patients, 84 patients (6.4%) were categorized as category 3 with one interval cancer and one cancer which was upgraded to category 4A after 6-month follow-up US (2.5% cancer rate, 95% CIs 1.5–9.1%). Fifteen patients (1.1%) had category 4A or 4B lesions in the contralateral breast. Four lesions were detected on mammography (two lesions were also visible on US) and 11 lesions were detected on US and 5 cancers were confirmed (33.3%, 95% CIs 15.0–58.5%). Six patients (0.5%) had category 4C lesions, 2 detected on mammography and 4 on US and 4 cancers were confirmed (66.7%, 95% CIs 29.6–90.8%). No lesions were categorized as category 5 in the contralateral breast. Cancer detection rate by mammography was 3.3 per 1000 patients and that by US was 5.0 per 1000 patients, therefore overall cancer detection rate by

Ultrasound screening of contralateral breast after surgery for breast cancer

International Nuclear Information System (INIS)

Kim, Seung Ja; Chung, Se-Yeong; Chang, Jung Min; Cho, Nariya; Han, Wonshik; Moon, Woo Kyung

2015-01-01

Highlights: • The addition of supplemental US to mammography depicted additional 5.0 cancers per 1000 postoperative women. • Positive biopsy rate of mammography-detected lesions was 66.7% (4 of 6) and that of US-detected lesions was 40.0% (6 of 15). • US can be helpful to detect mammographically occult breast cancer in the contralateral breast in women with previous history of cancer and dense breast. - Abstract: Objective: To determine whether supplemental screening ultrasound (US) to mammography could improve cancer detection rate of the contralateral breast in patients with a personal history of breast cancer and dense breasts. Materials and methods: During a one-year study period, 1314 screening patients with a personal history of breast cancer and dense breasts simultaneously underwent mammography and breast US. BI-RADS categories were given for mammography or US-detected lesions in the contralateral breast. The reference standard was histology and/or 1-year imaging follow-up, and the cancer rate according to BI-RADS categories and cancer detection rate and positive biopsy rate according to detection modality were analyzed. Results: Of 1314 patients, 84 patients (6.4%) were categorized as category 3 with one interval cancer and one cancer which was upgraded to category 4A after 6-month follow-up US (2.5% cancer rate, 95% CIs 1.5–9.1%). Fifteen patients (1.1%) had category 4A or 4B lesions in the contralateral breast. Four lesions were detected on mammography (two lesions were also visible on US) and 11 lesions were detected on US and 5 cancers were confirmed (33.3%, 95% CIs 15.0–58.5%). Six patients (0.5%) had category 4C lesions, 2 detected on mammography and 4 on US and 4 cancers were confirmed (66.7%, 95% CIs 29.6–90.8%). No lesions were categorized as category 5 in the contralateral breast. Cancer detection rate by mammography was 3.3 per 1000 patients and that by US was 5.0 per 1000 patients, therefore overall cancer detection rate by

Efficacy of breast conservation therapy in early stage bilateral breast cancer

International Nuclear Information System (INIS)

Lee, Misa M.; Chen, Luci M.; Heimann, Ruth; Powers, Claire; Weichselbaum, Ralph R.

1996-01-01

PURPOSE: To evaluate outcome of patients with bilateral breast cancer as compared to unilateral breast cancer treated with breast conservation therapy. This is a complex issue, however, we address this by comparing (1) synchronous bilateral breast cancer patients, (2) metachronous bilateral breast cancer patients from the time of diagnosis of the second breast primary, and (3) unilateral breast cancer patients. The authors recognize that there are inherent biases in these comparisons. MATERIALS AND METHODS: A total of 60 bilateral patients and 1080 unilateral patients treated with breast conservation therapy from 1977-1994 were analyzed for outcome. Of the 60 bilateral patients, 44 were metachronous bilateral breast cancer patients (MBBC) and 16 were synchronous breast cancer patients (SBBC). Patients with bilateral breast cancer had local-regional disease with the following tumor stages: DCIS=8%, T1=80%, T2=12%, pathologic N0=90%, pathologic N+=10%. Unilateral patients had the following tumor stages: DCIS=10%, T1=66%, T2=20%, T3=1.2%, Tx=2%, pathological N0=80%, pathological N+=19%, and NX=1%. The majority of patients received lumpectomy and axillary node dissection followed by radiation therapy. The median size of the lesions were 1.4cm and 1.5cm for bilateral and unilateral patients, respectively. Median total dose to the primary tumor was 60Gy for both unilateral and bilateral patients. Of the 44 metachronous bilateral breast cancer patients, 14 patients received breast conservation for both the first and second lesions while 30 patients had breast conservation for only the second metachronous breast lesion. Thus 58 lesions in the 44 patients were treated with breast conservation therapy in the patients with metachronous bilateral breast cancer. Of the synchronous bilateral breast cancer patients, 13 out of 16 patients had breast conserving therapy for both breasts, and 3 patients received mastectomy for the second synchronous breast tumor. The median follow

Radiation-induced breast cancer

International Nuclear Information System (INIS)

Finnerty, N.A.; Buzdar, A.U.; Blumenschein, G.R.

1984-01-01

Between 1975 and 1983, sixteen patients with a history of irradiation at an early age to the head, neck, or chest areas for a variety of conditions in whom breast cancer subsequently developed were seen at out institute. The median latent period between the irradiation and the development of breast cancer was 420 months. The distribution of patients by stage of the disease and the median age at diagnosis of this subgroup was similar to the breast cancer observed in the general population. The subsequent course of this disease was also similar to the breast cancer observed in the general population. A substantial number of women have been exposed to irradiation at a young age, and these women are at a higher risk of having breast cancer develop. These women should be closely observed to discover the disease in an early curable stage

Hereditary forms of breast cancer

International Nuclear Information System (INIS)

Bella, V.

2009-01-01

Breast cancer is the most common oncologic disease in the female population. Besides the sporadic occurrence it occurs in the familial and hereditary form. Persons with the occurrence of positive family anamnesis of breast cancer should be actively investigated. In the indicated cases it is necessary to send the woman to genetic examination. In case that the hereditary form of breast cancer is affirmed it is necessary to examine her family relatives. Women with the hereditary form of breast cancer occur in about 5 – 10 % portion from all women diagnosed with breast cancer. Nowadays we already know that 80 % of hereditary breast cancers are due to germ mutations in BRCA 1 and BRCA 2 gene. Persons with detected gene mutations must be dispensarized in the centres intended for it. (author)

Using Five Machine Learning for Breast Cancer Biopsy Predictions Based on Mammographic Diagnosis

OpenAIRE

Oyewola, David; Hakimi, Danladi; Adeboye, Kayode; Shehu, Musa Danjuma

2017-01-01

Breast cancer is one of thecauses of female death in the world. Mammography  is commonly  used for  distinguishing  malignant tumors  from benign  ones. In this research,  a mammographic  diagnostic method  is  presented for breast  cancer  biopsy outcome  predictions  using  fivemachine learning which includes: Logistic Regression(LR), Linear DiscriminantAnalysis(LDA), Quadratic Discriminant Analysis(QDA), Random Forest(RF) andSupport  Vector Machine(SVM)  classification.  The testing result...

Genetics Home Reference: breast cancer

Science.gov (United States)

... Email Facebook Twitter Home Health Conditions Breast cancer Breast cancer Printable PDF Open All Close All Enable Javascript to view the expand/collapse boxes. Description Breast cancer is a disease in which certain cells in ...

Awareness and current knowledge of breast cancer.

Science.gov (United States)

Akram, Muhammad; Iqbal, Mehwish; Daniyal, Muhammad; Khan, Asmat Ullah

2017-10-02

Breast cancer remains a worldwide public health dilemma and is currently the most common tumour in the globe. Awareness of breast cancer, public attentiveness, and advancement in breast imaging has made a positive impact on recognition and screening of breast cancer. Breast cancer is life-threatening disease in females and the leading cause of mortality among women population. For the previous two decades, studies related to the breast cancer has guided to astonishing advancement in our understanding of the breast cancer, resulting in further proficient treatments. Amongst all the malignant diseases, breast cancer is considered as one of the leading cause of death in post menopausal women accounting for 23% of all cancer deaths. It is a global issue now, but still it is diagnosed in their advanced stages due to the negligence of women regarding the self inspection and clinical examination of the breast. This review addresses anatomy of the breast, risk factors, epidemiology of breast cancer, pathogenesis of breast cancer, stages of breast cancer, diagnostic investigations and treatment including chemotherapy, surgery, targeted therapies, hormone replacement therapy, radiation therapy, complementary therapies, gene therapy and stem-cell therapy etc for breast cancer.

A comparative study of breast cancer diagnosis based on neural network ensemble via improved training algorithms.

Science.gov (United States)

Azami, Hamed; Escudero, Javier

2015-08-01

Breast cancer is one of the most common types of cancer in women all over the world. Early diagnosis of this kind of cancer can significantly increase the chances of long-term survival. Since diagnosis of breast cancer is a complex problem, neural network (NN) approaches have been used as a promising solution. Considering the low speed of the back-propagation (BP) algorithm to train a feed-forward NN, we consider a number of improved NN trainings for the Wisconsin breast cancer dataset: BP with momentum, BP with adaptive learning rate, BP with adaptive learning rate and momentum, Polak-Ribikre conjugate gradient algorithm (CGA), Fletcher-Reeves CGA, Powell-Beale CGA, scaled CGA, resilient BP (RBP), one-step secant and quasi-Newton methods. An NN ensemble, which is a learning paradigm to combine a number of NN outputs, is used to improve the accuracy of the classification task. Results demonstrate that NN ensemble-based classification methods have better performance than NN-based algorithms. The highest overall average accuracy is 97.68% obtained by NN ensemble trained by RBP for 50%-50% training-test evaluation method.

Breast cancer patterns and lifetime risk of developing breast cancer among Puerto Rican females.

Science.gov (United States)

Nazario, C M; Figueroa-Vallés, N; Rosario, R V

2000-03-01

The purpose of this study was to evaluate the epidemiologic patterns of breast cancer and to estimate the lifetime risk probability of developing breast cancer among Hispanic females using cancer data from Puerto Rico. The age-adjusted breast cancer incidence rate (per 100,000) in Puerto Rico increased from 15.3 in 1960-1964 to 43.3 in 1985-1989. The age-adjusted breast cancer mortality rate (per 100,000) increased from 5.7 to 10.6 comparing the same two time periods (1960-1964 vs 1985-1989). Nevertheless, in 1985-1989 breast cancer incidence rate was higher in US White females (110.8 per 100,000) compared to Puerto Rican females (51.4 per 100,000; age-adjusted to the 1970 US standard population). The breast cancer mortality rate was also higher in US White females (27.4 per 100,000) than in Puerto Rican females (15.1 per 100,000; age-adjusted to the 1970 US standard population) during 1985-1989. A multiple decrement life table was constructed applying age-specific incidence and mortality rates from cross-sectional data sets (1980-1984 and 1985-1989 data for Puerto Rican females and 1987-1989 SEER data sets for US White and Black females) to a hypothetical cohort of 10,000,000 women. The probability of developing invasive breast cancer was computed for the three groups using the long version of DEVCAN: Probability of DEVeloping CANcer software, version 3.3. The lifetime risk of developing breast cancer was 5.4% for Puerto Rican females, compared to 8.8% for US Black females and 13.0% for US White females. Lifetime risk for Puerto Rican females increased from 4.5% in 1980-1984 to 5.4% in 1985-1989. Lifetime risk of breast cancer appears to be increasing in Puerto Rico, but remains lower than the probability for US White females. Therefore, the application of lifetime probability of developing invasive breast cancer estimated for the US female population will overestimate the risk for the Puerto Rican female population.

Breast cancer epidemiology and risk factors

International Nuclear Information System (INIS)

Broeders, M. J. M.; Verbeek, A. L. M.

1997-01-01

Breast cancer is the most common malignancy among women in the Western society. Over the past decades it has become apparent that breast cancer incidence rates are increasing steadily, whereas the mortality rates for breast cancer have remained relatively constant. Information through the media on this rising number of cases has increased breast health awareness but has also introduced anxiety in the female population. This combination of factors has made the need for prevention of breast cancer an urgent matter. Breast cancer does not seem to be a single disease entity. A specific etiologic factor may therefore have more influence on one form may therefore have more influence on one form of breast cancer than another. So far though, as shown in their summary of current knowledge on established and dubious risk factors, no risk factors have been identified that can explain a major part of the incidence. Efforts to identify other ways for primary prevention have also been discouraging, even though breast cancer is one of the most investigated tumours world-wide. Thus, at this point i time, the most important strategy to reduce breast cancer mortality is early detection through individual counselling and organised breast screening programs. The recent isolation of breast cancer susceptibility genes may introduce new ways to reduce the risk of breast cancer in a small subset of women

Breast Cancer and Bone Loss

Science.gov (United States)

... Menopause Map Featured Resource Find an Endocrinologist Search Breast Cancer and Bone Loss July 2010 Download PDFs English ... G. Komen Foundation What is the link between breast cancer and bone loss? Certain treatments for breast cancer ...

Treatment Option Overview (Breast Cancer)

Science.gov (United States)

... Common Cancer Types Recurrent Cancer Common Cancer Types Bladder Cancer Breast Cancer Colorectal Cancer Kidney (Renal Cell) Cancer ... only hormone therapy after a hysterectomy . Selective estrogen receptor modulators (SERMs). Aromatase inhibitors . Less exposure of breast ...

Identifying Breast Cancer Oncogenes

Science.gov (United States)

2011-10-01

cells we observed that it promoted transformation of HMLE cells, suggesting a tumor suppressive role of Merlin in breast cancer (Figure 4B). A...08-1-0767 TITLE: Identifying Breast Cancer Oncogenes PRINCIPAL INVESTIGATOR: Yashaswi Shrestha...Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39.18 W81XWH-08-1-0767 Identifying Breast Cancer Oncogenes Yashaswi Shrestha Dana-Farber

Breast cancer literacy and health beliefs related to breast cancer screening among American Indian women.

Science.gov (United States)

Roh, Soonhee; Burnette, Catherine E; Lee, Yeon-Shim; Jun, Jung Sim; Lee, Hee Yun; Lee, Kyoung Hag

2018-08-01

The purpose of this article is to examine the health beliefs and literacy about breast cancer and their relationship with breast cancer screening among American Indian (AI) women. Using the Health Belief Model (HBM) and hierarchical logistic regression with data from a sample of 286 AI female adults residing in the Northern Plains, we found that greater awareness of breast cancer screening was linked to breast cancer screening practices. However, perceived barriers, one of the HBM constructs, prevented such screening practices. This study suggested that culturally relevant HBM factors should be targeted when developing culturally sensitive breast cancer prevention efforts.

Computed tomography of the breast cancer

International Nuclear Information System (INIS)

Chung, Soo Young; Lee, Yul; Bae, Sang Hoon; Yoon, Jong Sup; Lee, Ki Chu

1985-01-01

The indication of computed tomography for the breast lesion are 1) Unusually extensive or small breast caused technical difficulties in performing mammograms. 2) Questionable mammographic findings, especially in dense proliferative breast parenchyme. 3) Microcancer. 4) Suspicious regional lymph node enlargement or invasive of the chest wall by breast cancer. The diagnosis of breast CT in breast cancer is based on pathologic anatomic changes and characteristic increase of mean CT No. of lesion following contrast enhancement. Authors analysed CT of the 34 patients who were clinically suspected breast cancer, and compared with mammography. The results are as follows: 1. Pathological diagnosis of 34 cases were 27 cases of breast cancer, 4 cases of fibrocystic disease, 2 cases of fibroadenoma, and 1 case of intraductal papilloma. The diagnostic accuracy of CT in 27 breast cancer was 93% (25 cases) and mammography 71% (19 case). 2. Correct diagnosis of CT in 7 benign breast disease is in 5 cases and mammography in 5 cases. 3. The most important finding of CT in breast cancer is characteristic increase of CT No. of lesion following contrast enhancement (200 ml, 65%): over average 50 HU in 19 cases of 27 breast cancers, 30-50 HU in a 6 cases, 20-30 HU in 2 cases with tumor necrosis. 4. Computed with mammography, other more valuable CT findings of breast cancer are axillary lymph node enlargement and adjacentic pectoral muscle invasion. 5. In conclusion, breast CT is considered as valuable diagnostic tool in evaluation of breast cancer, but not of benign breast disease

Computed tomography of the breast cancer

Energy Technology Data Exchange (ETDEWEB)

Chung, Soo Young; Lee, Yul; Bae, Sang Hoon; Yoon, Jong Sup; Lee, Ki Chu [Hallym University Medical Center, Seoul (Korea, Republic of)

1985-12-15

The indication of computed tomography for the breast lesion are 1) Unusually extensive or small breast caused technical difficulties in performing mammograms. 2) Questionable mammographic findings, especially in dense proliferative breast parenchyme. 3) Microcancer. 4) Suspicious regional lymph node enlargement or invasive of the chest wall by breast cancer. The diagnosis of breast CT in breast cancer is based on pathologic anatomic changes and characteristic increase of mean CT No. of lesion following contrast enhancement. Authors analysed CT of the 34 patients who were clinically suspected breast cancer, and compared with mammography. The results are as follows: 1. Pathological diagnosis of 34 cases were 27 cases of breast cancer, 4 cases of fibrocystic disease, 2 cases of fibroadenoma, and 1 case of intraductal papilloma. The diagnostic accuracy of CT in 27 breast cancer was 93% (25 cases) and mammography 71% (19 case). 2. Correct diagnosis of CT in 7 benign breast disease is in 5 cases and mammography in 5 cases. 3. The most important finding of CT in breast cancer is characteristic increase of CT No. of lesion following contrast enhancement (200 ml, 65%): over average 50 HU in 19 cases of 27 breast cancers, 30-50 HU in a 6 cases, 20-30 HU in 2 cases with tumor necrosis. 4. Computed with mammography, other more valuable CT findings of breast cancer are axillary lymph node enlargement and adjacentic pectoral muscle invasion. 5. In conclusion, breast CT is considered as valuable diagnostic tool in evaluation of breast cancer, but not of benign breast disease.

Application of SVM classifier in thermographic image classification for early detection of breast cancer

Science.gov (United States)

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

2016-09-01

This article presents the application of machine learning algorithms for early detection of breast cancer on the basis of thermographic images. Supervised learning model: Support vector machine (SVM) and Sequential Minimal Optimization algorithm (SMO) for the training of SVM classifier were implemented. The SVM classifier was included in a client-server application which enables to create a training set of examinations and to apply classifiers (including SVM) for the diagnosis and early detection of the breast cancer. The sensitivity and specificity of SVM classifier were calculated based on the thermographic images from studies. Furthermore, the heuristic method for SVM's parameters tuning was proposed.

A minimum spanning forest based classification method for dedicated breast CT images

International Nuclear Information System (INIS)

Pike, Robert; Sechopoulos, Ioannis; Fei, Baowei

2015-01-01

Purpose: To develop and test an automated algorithm to classify different types of tissue in dedicated breast CT images. Methods: Images of a single breast of five different patients were acquired with a dedicated breast CT clinical prototype. The breast CT images were processed by a multiscale bilateral filter to reduce noise while keeping edge information and were corrected to overcome cupping artifacts. As skin and glandular tissue have similar CT values on breast CT images, morphologic processing is used to identify the skin based on its position information. A support vector machine (SVM) is trained and the resulting model used to create a pixelwise classification map of fat and glandular tissue. By combining the results of the skin mask with the SVM results, the breast tissue is classified as skin, fat, and glandular tissue. This map is then used to identify markers for a minimum spanning forest that is grown to segment the image using spatial and intensity information. To evaluate the authors’ classification method, they use DICE overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on five patient images. Results: Comparison between the automatic and the manual segmentation shows that the minimum spanning forest based classification method was able to successfully classify dedicated breast CT image with average DICE ratios of 96.9%, 89.8%, and 89.5% for fat, glandular, and skin tissue, respectively. Conclusions: A 2D minimum spanning forest based classification method was proposed and evaluated for classifying the fat, skin, and glandular tissue in dedicated breast CT images. The classification method can be used for dense breast tissue quantification, radiation dose assessment, and other applications in breast imaging

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

NARCIS (Netherlands)

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

2009-01-01

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

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

NARCIS (Netherlands)

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

2009-01-01

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

Male breast cancer

DEFF Research Database (Denmark)

Lautrup, Marianne D; Thorup, Signe S; Jensen, Vibeke

2018-01-01

OBJECTIVE: Describe prognostic parameters of Danish male breast cancer patients (MBCP) diagnosed from 1980-2009. Determine all-cause mortality compared to the general male population and analyze survival/mortality compared with Danish female breast cancer patients (FBCP) in the same period...

Unemployment among breast cancer survivors.

Science.gov (United States)

Carlsen, Kathrine; Ewertz, Marianne; Dalton, Susanne Oksbjerg; Badsberg, Jens Henrik; Osler, Merete

2014-05-01

Though about 20% of working age breast cancer survivors do not return to work after treatment, few studies have addressed risk factors for unemployment. The majority of studies on occupational consequences of breast cancer focus on non-employment, which is a mixture of sickness absence, unemployment, retirement pensions and other reasons for not working. Unemployment in combination with breast cancer may represent a particular challenge for these women. The aim of the present study is therefore to analyze the risk for unemployment in the years following diagnosis and treatment for breast cancer. This study included 14,750 women diagnosed with breast cancer in Denmark 2001-2009 identified through a population-based clinical database and linked with information from Danish administrative population based registers for information on labour market affiliation, socio-demography and co-morbid conditions. Multivariable analyses were performed by Cox's proportional hazard models. Two years after treatment, 81% of patients were still part of the work force, 10% of which were unemployed. Increasing duration of unemployment before breast cancer was associated with an adjusted HR = 4.37 (95% CI: 3.90-4.90) for unemployment after breast cancer. Other risk factors for unemployment included low socioeconomic status and demography, while adjuvant therapy did not increase the risk of unemployment. Duration of unemployment before breast cancer was the most important determinant of unemployment after breast cancer treatment. This allows identification of a particularly vulnerable group of patients in need of rehabilitation.

Breast Cancer Basics and You

Science.gov (United States)

... page please turn JavaScript on. Feature: Screening For Breast Cancer Breast Cancer Basics and You Past Issues / Summer 2014 Table ... more than 232,670 new cases of female breast cancer in the United States in 2014. More than ...

Retrospective observation on contribution and limitations of screening for breast cancer with mammography in Korea: detection rate of breast cancer and incidence rate of interval cancer of the breast.

Science.gov (United States)

Lee, Kunsei; Kim, Hyeongsu; Lee, Jung Hyun; Jeong, Hyoseon; Shin, Soon Ae; Han, Taehwa; Seo, Young Lan; Yoo, Youngbum; Nam, Sang Eun; Park, Jong Heon; Park, Yoo Mi

2016-11-18

The purpose of this study was to determine the benefits and limitations of screening for breast cancer using mammography. Descriptive design with follow-up was used in the study. Data from breast cancer screening and health insurance claim data were used. The study population consisted of all participants in breast cancer screening from 2009 to 2014. Crude detection rate, positive predictive value and sensitivity and specificity of breast cancer screening and, incidence rate of interval cancer of the breast were calculated. The crude detection rate of breast cancer screening per 100,000 participants increased from 126.3 in 2009 to 182.1 in 2014. The positive predictive value of breast cancer screening per 100,000 positives increased from 741.2 in 2009 to 1,367.9 in 2014. The incidence rate of interval cancer of the breast per 100,000 negatives increased from 51.7 in 2009 to 76.3 in 2014. The sensitivities of screening for breast cancer were 74.6% in 2009 and 75.1% in 2014 and the specificities were 83.1% in 2009 and 85.7% in 2014. To increase the detection rate of breast cancer by breast cancer screening using mammography, the participation rate should be higher and an environment where accurate mammography and reading can be performed and reinforcement of quality control are required. To reduce the incidence rate of interval cancer of the breast, it will be necessary to educate women after their 20s to perform self-examination of the breast once a month regardless of participation in screening for breast cancer.

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

Science.gov (United States)

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

2016-08-22

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

Diffusion-weighted imaging features of breast tumours and the surrounding stroma reflect intrinsic heterogeneous characteristics of molecular subtypes in breast cancer

KAUST Repository

Fan, Ming; He, Ting; Zhang, Peng; Cheng, Hu; Zhang, Juan; Gao, Xin; Li, Lihua

2017-01-01

Breast cancer heterogeneity is the main obstacle preventing the identification of patients with breast cancer with poor prognoses and treatment responses; however, such heterogeneity has not been well characterized. The purpose of this retrospective study was to reveal heterogeneous patterns in the apparent diffusion coefficient (ADC) signals in tumours and the surrounding stroma to predict molecular subtypes of breast cancer. A dataset of 126 patients with breast cancer, who underwent preoperative diffusion-weighted imaging (DWI) on a 3.0-T image system, was collected. Breast images were segmented into regions comprising the tumour and surrounding stromal shells in which features that reflect heterogeneous ADC signal distribution were extracted. For each region, imaging features were computed, including the mean, minimum, variance, interquartile range (IQR), range, skewness, kurtosis and entropy of ADC values. Univariate and stepwise multivariate logistic regression modelling was performed to identify the magnetic resonance imaging features that optimally discriminate luminal A, luminal B, human epidermal growth factor 2 (HER2)-enriched and basal-like molecular subtypes. The performance of the predictive models was evaluated using the area under the receiver operating characteristic curve (AUC). Univariate logistic regression analysis showed that the skewness in the tumour boundary achieved an AUC of 0.718 for discrimination between luminal A and non-luminal A tumours, whereas the IQR of the ADC value in the tumour boundary had an AUC of 0.703 for classification of the HER2-enriched subtype. Imaging features in the tumour boundary and the proximal peritumoral stroma corresponded to a higher overall prediction performance than those in other regions. A multivariate logistic regression model combining features in all the regions achieved an overall AUC of 0.800 for the classification of the four tumour subtypes. These findings suggest that features in the tumour

Diffusion-weighted imaging features of breast tumours and the surrounding stroma reflect intrinsic heterogeneous characteristics of molecular subtypes in breast cancer

KAUST Repository

Fan, Ming

2017-12-16

Breast cancer heterogeneity is the main obstacle preventing the identification of patients with breast cancer with poor prognoses and treatment responses; however, such heterogeneity has not been well characterized. The purpose of this retrospective study was to reveal heterogeneous patterns in the apparent diffusion coefficient (ADC) signals in tumours and the surrounding stroma to predict molecular subtypes of breast cancer. A dataset of 126 patients with breast cancer, who underwent preoperative diffusion-weighted imaging (DWI) on a 3.0-T image system, was collected. Breast images were segmented into regions comprising the tumour and surrounding stromal shells in which features that reflect heterogeneous ADC signal distribution were extracted. For each region, imaging features were computed, including the mean, minimum, variance, interquartile range (IQR), range, skewness, kurtosis and entropy of ADC values. Univariate and stepwise multivariate logistic regression modelling was performed to identify the magnetic resonance imaging features that optimally discriminate luminal A, luminal B, human epidermal growth factor 2 (HER2)-enriched and basal-like molecular subtypes. The performance of the predictive models was evaluated using the area under the receiver operating characteristic curve (AUC). Univariate logistic regression analysis showed that the skewness in the tumour boundary achieved an AUC of 0.718 for discrimination between luminal A and non-luminal A tumours, whereas the IQR of the ADC value in the tumour boundary had an AUC of 0.703 for classification of the HER2-enriched subtype. Imaging features in the tumour boundary and the proximal peritumoral stroma corresponded to a higher overall prediction performance than those in other regions. A multivariate logistic regression model combining features in all the regions achieved an overall AUC of 0.800 for the classification of the four tumour subtypes. These findings suggest that features in the tumour

Awareness of Breast Cancer and Breast Self Examination Among ...

African Journals Online (AJOL)

Background: Breast cancer is the commonest malignancy affecting women in Nigeria. Regular breast self examination reduces morbidity and mortality from this disease. Objective: To assess the knowledge of breast cancer, breast self examination and practice amongst secondary school teachers in Enugu , Nigeria.

Early breast cancer

International Nuclear Information System (INIS)

Dongen, J.A. van

1989-01-01

The therapy of early breast cancer has been changing during the last decennium. It requires a multi-disciplinary approach and in each of these disciplines improvements have been implemented. The result is that treatment schedules can now be adapted to specific subgroups. In this review early breast cancer is defined as operable disease, using the criteria set out by Haagensen. Emphasis is given to describing the new developments in prognostic criteria, since these form the basis for creating subgroups for specific treatment schedules. Distinction is made between the factors relating to growth rate and those relating to metastatic potential. Data on screening promises a beneficial effect of the implementation of screening in national health care programs. Important shifts are seen in treatment schedules; the place of postoperative radiotherapy after classic ablative treatment is being challenged, whereas it plays a major role in the new breast conserving therapy schedules. The data mentioned in the review suggest that a large proportion of 'operable' cases can be treated with breast conservation but details in the technique of breast conserving therapy are still under investigation. They form a major part of the coming prospective studies in breast cancer. Improvements in reconstruction techniques, creating better cosmetic results, make reconstruction more competitive with breast conserving therapy. The use of chemotherapy and endocrine manipulation in early breast cancer has now been clearly confirmed by the overview technique by the Peto-group, thanks to all efforts of individual trialists together. (orig.)

CHEK2*1100delC Heterozygosity in Women With Breast Cancer Associated With Early Death, Breast Cancer-Specific Death, and Increased Risk of a Second Breast Cancer

DEFF Research Database (Denmark)

Weischer, Maren; Nordestgaard, Børge G; Pharoah, Paul

2012-01-01

PURPOSE We tested the hypotheses that CHEK2*1100delC heterozygosity is associated with increased risk of early death, breast cancer-specific death, and risk of a second breast cancer in women with a first breast cancer. PATIENTS AND METHODS From 22 studies participating in the Breast Cancer Assoc...

Molecular characterization of breast cancer cell lines through multiple omic approaches.

Science.gov (United States)

Smith, Shari E; Mellor, Paul; Ward, Alison K; Kendall, Stephanie; McDonald, Megan; Vizeacoumar, Frederick S; Vizeacoumar, Franco J; Napper, Scott; Anderson, Deborah H

2017-06-05

Breast cancer cell lines are frequently used as model systems to study the cellular properties and biology of breast cancer. Our objective was to characterize a large, commonly employed panel of breast cancer cell lines obtained from the American Type Culture Collection (ATCC 30-4500 K) to enable researchers to make more informed decisions in selecting cell lines for specific studies. Information about these cell lines was obtained from a wide variety of sources. In addition, new information about cellular pathways that are activated within each cell line was generated. We determined key protein expression data using immunoblot analyses. In addition, two analyses on serum-starved cells were carried out to identify cellular proteins and pathways that are activated in these cells. These analyses were performed using a commercial PathScan array and a novel and more extensive phosphopeptide-based kinome analysis that queries 1290 phosphorylation events in major signaling pathways. Data about this panel of breast cancer cell lines was also accessed from several online sources, compiled and summarized for the following areas: molecular classification, mRNA expression, mutational status of key proteins and other possible cancer-associated mutations, and the tumorigenic and metastatic capacity in mouse xenograft models of breast cancer. The cell lines that were characterized included 10 estrogen receptor (ER)-positive, 12 human epidermal growth factor receptor 2 (HER2)-amplified and 18 triple negative breast cancer cell lines, in addition to 4 non-tumorigenic breast cell lines. Within each subtype, there was significant genetic heterogeneity that could impact both the selection of model cell lines and the interpretation of the results obtained. To capture the net activation of key signaling pathways as a result of these mutational combinations, profiled pathway activation status was examined. This provided further clarity for which cell lines were particularly deregulated

Cutaneous manifestations of breast cancer

OpenAIRE

Agnieszka B. Owczarczyk-Saczonek; Dawid Sigorski; Paweł Różanowski; Agnieszka Markiewicz; Waldemar J. Placek

2017-01-01

Breast cancer is the most common malignant neoplasm among women in Poland and in the European Union. According to most recent data of the Polish National Cancer Registry, in 2014 breast cancer was diagnosed in over 17,000 women. Based on the National Health Fund records, it is estimated that there are about 55,000–60,000 women in Poland who have a history of breast cancer diagnosis and are potentially at a risk of relapse. The most common sign of breast cancer is the presence of a nodule, how...

Breast cancer imaging: A perspective for the next decade

International Nuclear Information System (INIS)

Karellas, Andrew; Vedantham, Srinivasan

2008-01-01

Breast imaging is largely indicated for detection, diagnosis, and clinical management of breast cancer and for evaluation of the integrity of breast implants. In this work, a prospective view of techniques for breast cancer detection and diagnosis is provided based on an assessment of current trends. The potential role of emerging techniques that are under various stages of research and development is also addressed. It appears that the primary imaging tool for breast cancer screening in the next decade will be high-resolution, high-contrast, anatomical x-ray imaging with or without depth information. MRI and ultrasonography will have an increasingly important adjunctive role for imaging high-risk patients and women with dense breasts. Pilot studies with dedicated breast CT have demonstrated high-resolution three-dimensional imaging capabilities, but several technological barriers must be overcome before clinical adoption. Radionuclide based imaging techniques and x-ray imaging with intravenously injected contrast offer substantial potential as a diagnostic tools and for evaluation of suspicious lesions. Developing optical and electromagnetic imaging techniques hold significant potential for physiologic information and they are likely to be of most value when integrated with or adjunctively used with techniques that provide anatomic information. Experimental studies with breast specimens suggest that phase-sensitive x-ray imaging techniques can provide edge enhancement and contrast improvement but more research is needed to evaluate their potential role in clinical breast imaging. From the technological perspective, in addition to improvements within each modality, there is likely to be a trend towards multi-modality systems that combine anatomic with physiologic information. We are also likely to transition from a standardized screening, where all women undergo the same imaging exam (mammography), to selection of a screening modality or modalities based an

Breast cancer imaging: A perspective for the next decade

Energy Technology Data Exchange (ETDEWEB)

Karellas, Andrew; Vedantham, Srinivasan [Department of Radiology, University of Massachusetts Medical School, Worcester, MA 01655 (United States)

2008-11-15

Breast imaging is largely indicated for detection, diagnosis, and clinical management of breast cancer and for evaluation of the integrity of breast implants. In this work, a prospective view of techniques for breast cancer detection and diagnosis is provided based on an assessment of current trends. The potential role of emerging techniques that are under various stages of research and development is also addressed. It appears that the primary imaging tool for breast cancer screening in the next decade will be high-resolution, high-contrast, anatomical x-ray imaging with or without depth information. MRI and ultrasonography will have an increasingly important adjunctive role for imaging high-risk patients and women with dense breasts. Pilot studies with dedicated breast CT have demonstrated high-resolution three-dimensional imaging capabilities, but several technological barriers must be overcome before clinical adoption. Radionuclide based imaging techniques and x-ray imaging with intravenously injected contrast offer substantial potential as a diagnostic tools and for evaluation of suspicious lesions. Developing optical and electromagnetic imaging techniques hold significant potential for physiologic information and they are likely to be of most value when integrated with or adjunctively used with techniques that provide anatomic information. Experimental studies with breast specimens suggest that phase-sensitive x-ray imaging techniques can provide edge enhancement and contrast improvement but more research is needed to evaluate their potential role in clinical breast imaging. From the technological perspective, in addition to improvements within each modality, there is likely to be a trend towards multi-modality systems that combine anatomic with physiologic information. We are also likely to transition from a standardized screening, where all women undergo the same imaging exam (mammography), to selection of a screening modality or modalities based an

THE MAMMOGRAPHIC CALCIFICATIONS IN BREAST CANCER

Institute of Scientific and Technical Information of China (English)

Tang Ruiying; Liu Jingxian; Gaowen

1998-01-01

Objective: This study was performed to exam the relativeship between mammographic calcifications and breast cancer. Methods: All of the 184 patients with breast diseases underwent mammography before either an open biopsy or a mastectomy. The presence,morphology, and distribution of calcifications visualized on mammograms for breast cancer were compared with the controls who remained cancer free. Statistical comparisons were made by using the x2 test. Results:Of the 184 patients with breast diaeases, 93 malignant and 91 benign lesions were histologically confirmed.Calcifications were visualized on mammograms in 60(64%) of 93 breast cancers and 26 (28%) of 91 non breast cancers. The estimated odds ratio (OR) of breast cancer was 4.5 in women with calcifications seen on mammograms, compared with those having none (P＜0.01). Of the 60 breast carcinomas having mammographic calcifications, 28 (47%) were infiltrating ductal carcinomas.There were only 8 (24%) cases with infiltrating ductal cancers in the group of without calcifications seen on the mammograms (P＜0.05). Conclusion: Our finding suggests that mammographic calcification appears to be a risk factor for breast cancer. The granular and linear cast type calcification provide clues to the presence of breast cancer, especially when the carcinomas without associated masses were seen on mammograms.

Human papilloma viruses (HPV and breast cancer.

Directory of Open Access Journals (Sweden)

James Sutherland Lawson

2015-12-01

Full Text Available Purpose: Human papillomaviruses (HPV may have a role in some breast cancers. The purpose of this study is to fill important gaps in the evidence. These gaps are: (i confirmation of the presence of high risk for cancer HPVs in breast cancers, (ii evidence of HPV infections in benign breast tissues prior to the development of HPV positive breast cancer in the same patients, (iii evidence that HPVs are biologically active and not harmless passengers in breast cancer.Methods: RNA-seq data from The Cancer Genome Atlas (TCGA was used to identify HPV RNA sequences in breast cancers. We also conducted a retrospective cohort study based on polymerase chain reaction (PCR analyses to identify HPVs in archival specimens from Australian women with benign breast biopsies who later developed breast cancer. To assess whether HPVs in breast cancer were biologically active, the expression of the oncogenic protein HPV E7 was assessed by immunohistochemistry (IHC.Results: Thirty (3.5% low risk and 20 (2.3% high risk HPV types were identified in 855 breast cancers from the TCGA data base. The high risk types were HPV 18 (48%, HPV 113 (24%, HPV 16 (10%, HPV 52 (10%. Data from the PCR cohort study, indicated that HPV type 18 was the most common type identified in breast cancer specimens (55% of 40 breast cancer specimens followed by HPV 16 (13%. The same HPV type was identified in both the benign and subsequent breast cancer in 15 patients. HPV E7 proteins were identified in 72% of benign breast specimens and 59% of invasive breast cancer specimens.Conclusions: There were 4 observations of particular interest: (i confirmation by both NGS and PCR of the presence of high risk HPV gene sequences in breast cancers, (ii a correlation between high risk HPV in benign breast specimens and subsequent HPV positive breast cancer in the same patient, (iii HPVs in breast cancer are likely to be biologically active (as shown by transcription of HPV DNA to RNA plus the expression of

Risk of treatment-related esophageal cancer among breast cancer survivors

DEFF Research Database (Denmark)

Morton, L M; Gilbert, E S; Hall, P

2012-01-01

Radiotherapy for breast cancer may expose the esophagus to ionizing radiation, but no study has evaluated esophageal cancer risk after breast cancer associated with radiation dose or systemic therapy use.......Radiotherapy for breast cancer may expose the esophagus to ionizing radiation, but no study has evaluated esophageal cancer risk after breast cancer associated with radiation dose or systemic therapy use....

Evidence that breast tissue stiffness is associated with risk of breast cancer.

Science.gov (United States)

Boyd, Norman F; Li, Qing; Melnichouk, Olga; Huszti, Ella; Martin, Lisa J; Gunasekara, Anoma; Mawdsley, Gord; Yaffe, Martin J; Minkin, Salomon

2014-01-01

Evidence from animal models shows that tissue stiffness increases the invasion and progression of cancers, including mammary cancer. We here use measurements of the volume and the projected area of the compressed breast during mammography to derive estimates of breast tissue stiffness and examine the relationship of stiffness to risk of breast cancer. Mammograms were used to measure the volume and projected areas of total and radiologically dense breast tissue in the unaffected breasts of 362 women with newly diagnosed breast cancer (cases) and 656 women of the same age who did not have breast cancer (controls). Measures of breast tissue volume and the projected area of the compressed breast during mammography were used to calculate the deformation of the breast during compression and, with the recorded compression force, to estimate the stiffness of breast tissue. Stiffness was compared in cases and controls, and associations with breast cancer risk examined after adjustment for other risk factors. After adjustment for percent mammographic density by area measurements, and other risk factors, our estimate of breast tissue stiffness was significantly associated with breast cancer (odds ratio = 1.21, 95% confidence interval = 1.03, 1.43, p = 0.02) and improved breast cancer risk prediction in models with percent mammographic density, by both area and volume measurements. An estimate of breast tissue stiffness was associated with breast cancer risk and improved risk prediction based on mammographic measures and other risk factors. Stiffness may provide an additional mechanism by which breast tissue composition is associated with risk of breast cancer and merits examination using more direct methods of measurement.

Combining quantitative and qualitative breast density measures to assess breast cancer risk.

Science.gov (United States)

Kerlikowske, Karla; Ma, Lin; Scott, Christopher G; Mahmoudzadeh, Amir P; Jensen, Matthew R; Sprague, Brian L; Henderson, Louise M; Pankratz, V Shane; Cummings, Steven R; Miglioretti, Diana L; Vachon, Celine M; Shepherd, John A

2017-08-22

Accurately identifying women with dense breasts (Breast Imaging Reporting and Data System [BI-RADS] heterogeneously or extremely dense) who are at high breast cancer risk will facilitate discussions of supplemental imaging and primary prevention. We examined the independent contribution of dense breast volume and BI-RADS breast density to predict invasive breast cancer and whether dense breast volume combined with Breast Cancer Surveillance Consortium (BCSC) risk model factors (age, race/ethnicity, family history of breast cancer, history of breast biopsy, and BI-RADS breast density) improves identifying women with dense breasts at high breast cancer risk. We conducted a case-control study of 1720 women with invasive cancer and 3686 control subjects. We calculated ORs and 95% CIs for the effect of BI-RADS breast density and Volpara™ automated dense breast volume on invasive cancer risk, adjusting for other BCSC risk model factors plus body mass index (BMI), and we compared C-statistics between models. We calculated BCSC 5-year breast cancer risk, incorporating the adjusted ORs associated with dense breast volume. Compared with women with BI-RADS scattered fibroglandular densities and second-quartile dense breast volume, women with BI-RADS extremely dense breasts and third- or fourth-quartile dense breast volume (75% of women with extremely dense breasts) had high breast cancer risk (OR 2.87, 95% CI 1.84-4.47, and OR 2.56, 95% CI 1.87-3.52, respectively), whereas women with extremely dense breasts and first- or second-quartile dense breast volume were not at significantly increased breast cancer risk (OR 1.53, 95% CI 0.75-3.09, and OR 1.50, 95% CI 0.82-2.73, respectively). Adding continuous dense breast volume to a model with BCSC risk model factors and BMI increased discriminatory accuracy compared with a model with only BCSC risk model factors (C-statistic 0.639, 95% CI 0.623-0.654, vs. C-statistic 0.614, 95% CI 0.598-0.630, respectively; P breasts and fourth

DEGRO practical guidelines. Radiotherapy of breast cancer I. Radiotherapy following breast conserving therapy for invasive breast cancer

International Nuclear Information System (INIS)

Sedlmayer, F.

2013-01-01

Background and purpose: The aim of the present paper is to update the practical guidelines for postoperative adjuvant radiotherapy of breast cancer published in 2007 by the breast cancer expert panel of the German Society for Radiooncology (Deutsche Gesellschaft fuer Radioonkologie, DEGRO). The present recommendations are based on a revision of the German interdisciplinary S-3 guidelines published in July 2012. Methods: A comprehensive survey of the literature concerning radiotherapy following breast conserving therapy (BCT) was performed using the search terms 'breast cancer', 'radiotherapy', and 'breast conserving therapy'. Data from lately published meta-analyses, recent randomized trials, and guidelines of international breast cancer societies, yielding new aspects compared to 2007, provided the basis for defining recommendations according to the criteria of evidence-based medicine. In addition to the more general statements of the DKG (Deutsche Krebsgesellschaft), this paper addresses indications, target definition, dosage, and technique of radiotherapy of the breast after conservative surgery for invasive breast cancer. Results: Among numerous reports on the effect of radiotherapy during BCT published since the last recommendations, the recent EBCTCG report builds the largest meta-analysis so far available. In a 15 year follow-up on 10,801 patients, whole breast irradiation (WBI) halves the average annual rate of disease recurrence (RR 0.52, 0.48-0.56) and reduces the annual breast cancer death rate by about one sixth (RR 0.82, 0.75-0.90), with a similar proportional, but different absolute benefit in prognostic subgroups (EBCTCG 2011). Furthermore, there is growing evidence that risk-adapted dose augmentation strategies to the tumor bed as well as the implementation of high precision RT techniques (e.g., intraoperative radiotherapy) contribute substantially to a further reduction of local relapse rates. A main focus of ongoing research lies in partial breast

MicroRNA-139 suppresses proliferation in luminal type breast cancer cells by targeting Topoisomerase II alpha

Energy Technology Data Exchange (ETDEWEB)

Hua, Wei [Department of Obstetrics and Gynecology, Xijing Hospital, Fourth Military Medical University, Xi' an 710032 (China); State Key Laboratory of Cancer Biology, Department of Biochemistry and Molecular Biology, Fourth Military Medical University, 710032 Xi' an (China); Sa, Ke-Di; Zhang, Xiang; Jia, Lin-Tao; Zhao, Jing [State Key Laboratory of Cancer Biology, Department of Biochemistry and Molecular Biology, Fourth Military Medical University, 710032 Xi' an (China); Yang, An-Gang [State Key Laboratory of Cancer Biology, Department of Immunology, Fourth Military Medical University, 710032 Xi' an (China); Zhang, Rui, E-mail: ruizhang@fmmu.edu.cn [State Key Laboratory of Cancer Biology, Department of Biochemistry and Molecular Biology, Fourth Military Medical University, 710032 Xi' an (China); Fan, Jing, E-mail: jingfan@fmmu.edu.cn [Department of Vascular and Endocrine Surgery, Xijing Hospital, Fourth Military Medical University, Xi' an 710032 (China); Bian, Ka, E-mail: kakamax85@hotmail.com [State Key Laboratory of Cancer Biology, Department of Immunology, Fourth Military Medical University, 710032 Xi' an (China); Department of Otolaryngology, Tangdu Hospital, Fourth Military Medical University, Xi' an 710038 (China)

2015-08-07

The classification of molecular subtypes of breast cancer improves the prognostic accuracy and therapeutic benefits in clinic. However, because of the complexity of breast cancer, more biomarkers and functional molecules need to be explored. Here, analyzing the data in a huge cohort of breast cancer patients, we found that Topoisomerase II alpha (TOP2a), an important target of chemotherapy is a biomarker for prognosis in luminal type breast cancer patients, but not in basal like or HER2 positive breast cancer patients. We identified that miR-139, a previous reported anti-metastatic microRNA targets 3’-untranslated region (3′UTR) of TOP2a mRNA. Further more, we revealed that the forced expression of miR-139 reduces the TOP2a expression at both mRNA and protein levels. And our functional experiments showed that the ectopic expression of miR-139 remarkably inhibits proliferation in luminal type breast cancer cells, while exogenous TOP2a expression could rescue inhibition of cell proliferation mediated by miR-139. Collectively, our present study demonstrates the miR-139-TOP2a regulatory axis is important for proliferation in luminal type breast cancer cells. This functional link may help us to further understand the specificity of subtypes of breast cancer and optimize the strategy of cancer treatment. - Highlights: • High levels of TOP2a expression are closely associated with poor prognosis in luminal type breast cancer patients. • TOP2a is a novel target of miR-139. • Overexpression of miR-139 inhibits proliferation in luminal type breast cancer cells. • TOP2a is essential for miR-139-induced growth arrest in luminal type breast cancer cells.

MicroRNA-139 suppresses proliferation in luminal type breast cancer cells by targeting Topoisomerase II alpha

International Nuclear Information System (INIS)

Hua, Wei; Sa, Ke-Di; Zhang, Xiang; Jia, Lin-Tao; Zhao, Jing; Yang, An-Gang; Zhang, Rui; Fan, Jing; Bian, Ka

2015-01-01

The classification of molecular subtypes of breast cancer improves the prognostic accuracy and therapeutic benefits in clinic. However, because of the complexity of breast cancer, more biomarkers and functional molecules need to be explored. Here, analyzing the data in a huge cohort of breast cancer patients, we found that Topoisomerase II alpha (TOP2a), an important target of chemotherapy is a biomarker for prognosis in luminal type breast cancer patients, but not in basal like or HER2 positive breast cancer patients. We identified that miR-139, a previous reported anti-metastatic microRNA targets 3’-untranslated region (3′UTR) of TOP2a mRNA. Further more, we revealed that the forced expression of miR-139 reduces the TOP2a expression at both mRNA and protein levels. And our functional experiments showed that the ectopic expression of miR-139 remarkably inhibits proliferation in luminal type breast cancer cells, while exogenous TOP2a expression could rescue inhibition of cell proliferation mediated by miR-139. Collectively, our present study demonstrates the miR-139-TOP2a regulatory axis is important for proliferation in luminal type breast cancer cells. This functional link may help us to further understand the specificity of subtypes of breast cancer and optimize the strategy of cancer treatment. - Highlights: • High levels of TOP2a expression are closely associated with poor prognosis in luminal type breast cancer patients. • TOP2a is a novel target of miR-139. • Overexpression of miR-139 inhibits proliferation in luminal type breast cancer cells. • TOP2a is essential for miR-139-induced growth arrest in luminal type breast cancer cells

Awareness of Breast Cancer and Practice of Breast Self ...

African Journals Online (AJOL)

Background and Objective: Breast cancer is the commonest cancer among women in globally and in Nigeria. In Nigeria, cases of breast cancer cases have been prevalent for three decades and more than 90% of cases can be detected by women themselves through breast self – examination. The objective of this study ...

Obesity and Breast Cancer.

Science.gov (United States)

Fortner, Renée T; Katzke, Verena; Kühn, Tilman; Kaaks, Rudolf

The relationship between adiposity and breast cancer risk and prognosis is complex, with associations that differ depending on when body size is assessed (e.g., pre- vs. postmenopausal obesity) and when breast cancer is diagnosed (i.e., pre- vs. postmenopausal disease). Further, the impact of obesity on risk differs by tumor hormone receptor status (e.g., estrogen (ER) and progesterone (PR) receptor) and, among postmenopausal women, use of exogenous hormones (i.e., hormone replacement therapy (HRT)). In the context of these complexities, this review focuses on associations between childhood and adolescent adiposity, general adiposity, weight changes (i.e., loss and gain), abdominal adiposity, and breast cancer risk and survival. Finally, we discuss potential mechanisms linking adiposity to breast cancer.

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

Energy Technology Data Exchange (ETDEWEB)

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

2011-09-21

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

Automatic classification of tissue malignancy for breast carcinoma diagnosis.

Science.gov (United States)

Fondón, Irene; Sarmiento, Auxiliadora; García, Ana Isabel; Silvestre, María; Eloy, Catarina; Polónia, António; Aguiar, Paulo

2018-05-01

Breast cancer is the second leading cause of cancer death among women. Its early diagnosis is extremely important to prevent avoidable deaths. However, malignancy assessment of tissue biopsies is complex and dependent on observer subjectivity. Moreover, hematoxylin and eosin (H&E)-stained histological images exhibit a highly variable appearance, even within the same malignancy level. In this paper, we propose a computer-aided diagnosis (CAD) tool for automated malignancy assessment of breast tissue samples based on the processing of histological images. We provide four malignancy levels as the output of the system: normal, benign, in situ and invasive. The method is based on the calculation of three sets of features related to nuclei, colour regions and textures considering local characteristics and global image properties. By taking advantage of well-established image processing techniques, we build a feature vector for each image that serves as an input to an SVM (Support Vector Machine) classifier with a quadratic kernel. The method has been rigorously evaluated, first with a 5-fold cross-validation within an initial set of 120 images, second with an external set of 30 different images and third with images with artefacts included. Accuracy levels range from 75.8% when the 5-fold cross-validation was performed to 75% with the external set of new images and 61.11% when the extremely difficult images were added to the classification experiment. The experimental results indicate that the proposed method is capable of distinguishing between four malignancy levels with high accuracy. Our results are close to those obtained with recent deep learning-based methods. Moreover, it performs better than other state-of-the-art methods based on feature extraction, and it can help improve the CAD of breast cancer. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Management of breast cancer in a woman with breast implants].

Science.gov (United States)

Remacle, S; Lifrange, E; Nizet, J-L

2015-01-01

The incidence of breast cancer, currently one woman on eight, also concerns patients who underwent augmentation surgery. Breast implants have already been the subject of numerous publications concerning the risk of inducing breast cancer or of delaying its diagnosis; however, no significant causal relationship has been established. The purpose of this article is to assess the diagnostic and therapeutic consequences when breast cancer is identified in a patient with breast implants.

Levels of estrogen, carcinoembryonic antigen and cancer antigen of breast in breast cancer patients

International Nuclear Information System (INIS)

Abdelhadi, H. A.

2005-09-01

This study was conducted during the period from february 2004 to July 2004; with the objective of measuring the levels of estrogen (E2), carcinoembryonic antigen (CEA) and cancer antigen of breast (CA-15.3) so as to facilitate the early diagnosis of breast cancer and determine the involvement of these parameters as risk factors for breast cancer. Ninety blood samples were collected from Sudanese females, divided into two groups; control group and patient groups. The patients group was sixty Sudanese females visiting the Radio Isotope Center, Khartoum (RICK) and they were confirmed as breast cancer patient by histopathology. The levels of the above mentioned parameters were determined by using radioimmunoassay technique. The results showed that, no significant (p=0.05) difference between the levels of the estrogen in patients compared to the control, on the other hand there was non significant (p>0.05) elevation in CEA levels in the patients with breast cancer compared to the control. The level of CA15.3 was significantly (p<0.0001) higher in the breast cancer patients compared to the control.(Author)

Docosahexaenoic Acid in Preventing Recurrence in Breast Cancer Survivors

Science.gov (United States)

2016-06-20

Benign Breast Neoplasm; Ductal Breast Carcinoma In Situ; Invasive Breast Carcinoma; Lobular Breast Carcinoma In Situ; Paget Disease of the Breast; Stage IA Breast Cancer; Stage IB Breast Cancer; Stage IIA Breast Cancer; Stage IIB Breast Cancer; Stage IIIA Breast Cancer; Stage IIIB Breast Cancer; Stage IIIC Breast Cancer

Association between breast cancer, breast density, and body adiposity evaluated by MRI

International Nuclear Information System (INIS)

Zhu, Wenlian; Huang, Peng; Macura, Katarzyna J.; Artemov, Dmitri

2016-01-01

Despite the lack of reliable methods with which to measure breast density from 2D mammograms, numerous studies have demonstrated a positive association between breast cancer and breast density. The goal of this study was to study the association between breast cancer and body adiposity, as well as breast density quantitatively assessed from 3D MRI breast images. Breast density was calculated from 3D T1-weighted MRI images. The thickness of the upper abdominal adipose layer was used as a surrogate marker for body adiposity. We evaluated the correlation between breast density, age, body adiposity, and breast cancer. Breast density was calculated for 410 patients with unilateral invasive breast cancer, 73 patients with ductal carcinoma in situ (DCIS), and 361 controls without breast cancer. Breast density was inversely related to age and the thickness of the upper abdominal adipose layer. Breast cancer was only positively associated with body adiposity and age. Age and body adiposity are predictive of breast density. Breast cancer was not associated with breast density; however, it was associated with the thickness of the upper abdominal adipose layer, a surrogate marker for body adiposity. Our results based on a limited number of patients warrant further investigations. (orig.)

High resolution MRI of the breast at 3 T: which BI-RADS registered descriptors are most strongly associated with the diagnosis of breast cancer?

International Nuclear Information System (INIS)

Pinker-Domenig, K.; Helbich, T.H.; Bogner, W.; Gruber, S.; Bickel, H.; Duffy, S.; Schernthaner, M.; Dubsky, P.; Pluschnig, U.; Rudas, M.; Trattnig, S.

2012-01-01

To identify which breast lesion descriptors in the ACR BI-RADS registered MRI lexicon are most strongly associated with the diagnosis of breast cancer when performing breast MR imaging at 3 T. 150 patients underwent breast MR imaging at 3 T. Lesion size, morphology and enhancement kinetics were assessed according to the BI-RADS registered classification. Sensitivity, specificity and diagnostic accuracy were assessed. The effects of the BI-RADS registered descriptors on sensitivity and specificity were evaluated. Data were analysed using logistic regression. Histopathological diagnoses were used as the standard of reference. The sensitivity, specificity and diagnostic accuracy of breast MRI at 3 T was 99%, 81% and 93%, respectively. In univariate analysis, the final diagnosis of malignancy was positively associated with irregular shape (p registered breast lesion descriptors that are mostly strongly associated with breast cancer in breast MR imaging at 3 T are lesion shape, lesion margin, internal enhancement pattern and Type 3 enhancement kinetics. (orig.)

Getting free of breast cancer

DEFF Research Database (Denmark)

Halttunen, Arja; Hietanen, P; Jallinoja, P

1992-01-01

Twenty-two breast cancer patients who were relapse-free and had no need for cancer-related treatment were interviewed 8 years after mastectomy in order to evaluate their feelings of getting free of breast cancer and the meaning of breast cancer in their lives. The study is a part of an intervention...... and follow-up study of 57 breast cancer patients. Half of the 22 patients still had frequent or occasional thoughts of recurrence and over two-thirds still thought they had not been 'cured' of cancer. More than half of the patients admitted that going through breast cancer had made them more mature. Women...... who had less thoughts of recurrence belonged to a group that had gone through an eight-week group psychotherapy intervention, were less depressed and had more other illnesses. Women who felt 'cured' had less limitations and restrictions due to cancer and belonged more often to higher social classes...

Micropapillary Lung Cancer with Breast Metastasis Simulating Primary Breast Cancer due to Architectural Distortion on Images

Energy Technology Data Exchange (ETDEWEB)

Ko, Kyung Ran; Hong, Eun Kyung; Lee, See Yeon [Center for Breast Cancer, National Cancer Center, Goyang (Korea, Republic of); Ro, Jae Yoon [The Methodist Hospital, Weill Medical College of Cornell University, Houston (United States)

2012-03-15

A 47-year-old Korean woman with right middle lobe lung adenocarcinoma, malignant pleural effusion, and multiple lymph node and bone metastases, after three months of lung cancer diagnosis, presented with a palpable right breast mass. Images of the right breast demonstrated architectural distortion that strongly suggested primary breast cancer. Breast biopsy revealed metastatic lung cancer with a negative result for estrogen receptor (ER), progesterone receptor (PR) and mammaglobin, and a positive result for thyroid transcription factor-1 (TTF-1). We present a case of breast metastasis from a case of lung cancer with an extensive micropapillary component, which was initially misinterpreted as a primary breast cancer due to unusual image findings with architectural distortion.

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

International Nuclear Information System (INIS)

Mannello, Ferdinando; Ligi, Daniela

2013-01-01

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

A conceptual-practice model for occupational therapy to facilitate return to work in breast cancer patients.

Science.gov (United States)

Désiron, Huguette A M; Donceel, Peter; de Rijk, Angelique; Van Hoof, Elke

2013-12-01

Improved therapies and early detection have significantly increased the number of breast cancers survivors, leading to increasing needs regarding return to work (RTW). Occupational therapy (OT) interventions provide successful RTW assistance for other conditions, but are not validated in breast cancer. This paper aims to identify a theoretical framework for OT intervention by questioning how OT models can be used in OT interventions in RTW of breast cancer patients; criteria to be used to select these models and adaptations that would be necessary to match the OT model(s) to breast cancer patients' needs? Using research specific criteria derived from OT literature (conceptual OT-model, multidisciplinary, referring to the International Classification of functioning (ICF), RTW in breast cancer) a search in 9 electronic databases was conducted to select articles that describe conceptual OT models. A content analysis of those models complying to at least two of the selection criteria was realised. Checking for breast cancer specific issues, results were matched with literature of care-models regarding RTW in breast cancer. From the nine models initially identified, three [Canadian Model of Occupational Performance, Model of Human Occupation (MOHO), Person-Environment-Occupation-Performance model] were selected based on the selection criteria. The MOHO had the highest compliance rate with the criteria. To enhance usability in breast cancer, some adaptations are needed. No OT model to facilitate RTW in breast cancer could be identified, indicating a need to fill this gap. Individual and societal needs of breast cancer patients can be answered by using a MOHO-based OT model, extended with indications for better treatment, work-outcomes and longitudinal process factors.

Racial and Socioeconomic Disparities Are More Pronounced in Inflammatory Breast Cancer Than Other Breast Cancers

Directory of Open Access Journals (Sweden)

Ryan A. Denu

2017-01-01

Full Text Available Inflammatory breast cancer (IBC is a rare yet aggressive form of breast cancer. We examined differences in patient demographics and outcomes in IBC compared to locally advanced breast cancer (LABC and all other breast cancer patients from the Breast and Prostate Cancer Data Quality and Patterns of Care Study (POC-BP, containing information from cancer registries in seven states. Out of 7,624 cases of invasive carcinoma, IBC and LABC accounted for 2.2% (N=170 and 4.9% (N=375, respectively. IBC patients were more likely to have a higher number (P=0.03 and severity (P=0.01 of comorbidities than other breast cancer patients. Among IBC patients, a higher percentage of patients with metastatic disease versus nonmetastatic disease were black, on Medicaid, and from areas of higher poverty and more urban areas. Black and Hispanic IBC patients had worse overall and breast cancer-specific survival than white patients; moreover, IBC patients with Medicaid, patients from urban areas, and patients from areas of higher poverty and lower education had worse outcomes. These data highlight the effects of disparities in race and socioeconomic status on the incidence of IBC as well as IBC outcomes. Further work is needed to reveal the causes behind these disparities and methods to improve IBC outcomes.

Bilateral mammographic density asymmetry and breast cancer risk: A preliminary assessment

Energy Technology Data Exchange (ETDEWEB)

Zheng, Bin, E-mail: zhengb@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States); Sumkin, Jules H., E-mail: jsumkin@mail.magee.edu [Department of Radiology, Magee Womens Hospital, 300 Halket Street, Pittsburgh, PA 15213 (United States); Zuley, Margarita L., E-mail: zuleyml@upmc.edu [Department of Radiology, Magee Womens Hospital, 300 Halket Street, Pittsburgh, PA 15213 (United States); Wang, Xingwei, E-mail: wangx6@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States); Klym, Amy H., E-mail: klymah@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States); Gur, David, E-mail: gurd@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States)

2012-11-15

To improve efficacy of breast cancer screening and prevention programs, it requires a risk assessment model with high discriminatory power. This study aimed to assess classification performance of using computed bilateral mammographic density asymmetry to predict risk of individual women developing breast cancer in near-term. The database includes 451 cases with multiple screening mammography examinations. The first (baseline) examinations of all case were interpreted negative. In the next sequential examinations, 187 cases developed cancer or surgically excised high-risk lesions, 155 remained negative (not-recalled), and 109 were recalled benign cases. From each of two bilateral cranio-caudal view images acquired from the baseline examination, we computed two features of average pixel value and local pixel value fluctuation. We then computed mean and difference of each feature computed from two images. When applying the computed features and other two risk factors (woman's age and subjectively rated mammographic density) to predict risk of cancer development, areas under receiver operating characteristic curves (AUC) were computed to evaluate the discriminatory/classification performance. The AUCs are 0.633 {+-} 0.030, 0.535 {+-} 0.036, 0.567 {+-} 0.031, and 0.719 {+-} 0.027 when using woman's age, subjectively rated, computed mean and asymmetry of mammographic density, to classify between two groups of cancer-verified and negative cases, respectively. When using an equal-weighted fusion method to combine woman's age and computed density asymmetry, AUC increased to 0.761 {+-} 0.025 (p < 0.05). The study demonstrated that bilateral mammographic density asymmetry could be a significantly stronger risk factor associated to the risk of women developing breast cancer in near-term than woman's age and assessed mean mammographic density.

Bilateral mammographic density asymmetry and breast cancer risk: A preliminary assessment

International Nuclear Information System (INIS)

Zheng, Bin; Sumkin, Jules H.; Zuley, Margarita L.; Wang, Xingwei; Klym, Amy H.; Gur, David

2012-01-01

To improve efficacy of breast cancer screening and prevention programs, it requires a risk assessment model with high discriminatory power. This study aimed to assess classification performance of using computed bilateral mammographic density asymmetry to predict risk of individual women developing breast cancer in near-term. The database includes 451 cases with multiple screening mammography examinations. The first (baseline) examinations of all case were interpreted negative. In the next sequential examinations, 187 cases developed cancer or surgically excised high-risk lesions, 155 remained negative (not-recalled), and 109 were recalled benign cases. From each of two bilateral cranio-caudal view images acquired from the baseline examination, we computed two features of average pixel value and local pixel value fluctuation. We then computed mean and difference of each feature computed from two images. When applying the computed features and other two risk factors (woman's age and subjectively rated mammographic density) to predict risk of cancer development, areas under receiver operating characteristic curves (AUC) were computed to evaluate the discriminatory/classification performance. The AUCs are 0.633 ± 0.030, 0.535 ± 0.036, 0.567 ± 0.031, and 0.719 ± 0.027 when using woman's age, subjectively rated, computed mean and asymmetry of mammographic density, to classify between two groups of cancer-verified and negative cases, respectively. When using an equal-weighted fusion method to combine woman's age and computed density asymmetry, AUC increased to 0.761 ± 0.025 (p < 0.05). The study demonstrated that bilateral mammographic density asymmetry could be a significantly stronger risk factor associated to the risk of women developing breast cancer in near-term than woman's age and assessed mean mammographic density.

Invasive lobular breast cancer and its variants: how special are they for systemic therapy decisions?

Science.gov (United States)

Guiu, Séverine; Wolfer, Anita; Jacot, William; Fumoleau, Pierre; Romieu, Gilles; Bonnetain, Franck; Fiche, Maryse

2014-12-01

The WHO classification of breast tumors distinguishes, besides invasive breast cancer 'of no special type' (former invasive ductal carcinoma, representing 60-70% of all breast cancers), 30 special types, of which invasive lobular carcinoma (ILC) is the most common (5-15%). We review the literature on (i) the specificity and heterogeneity of ILC biology as documented by various analytical techniques, including the results of molecular testing for risk of recurrence; (ii) the impact of lobular histology on prediction of prognosis and effect of systemic therapies in patients. Though it is generally admitted that ILC has a better prognosis than IDC, is endocrine responsive, and responds poorly to chemotherapy, currently available data do not unanimously support these assumptions. This review demonstrates some lack of specific data and a need for improving clinical research design to allow oncologists to make informed systemic therapy decisions in patients with ILC. Importantly, future studies should compare various endpoints in ILC breast cancer patients among the group of hormonosensitive breast cancer. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Understanding and potentially reducing second breast cancer

International Nuclear Information System (INIS)

Brenner, D.

2011-01-01

Full text: Long term survival after breast cancer diagnosis has increased markedly in the last decade: 15-year relative survival after breast cancer diagnosis is now 75% in the US. Associated with these excellent survival prospects, however, long term studies suggest that contralateral second breast cancer rates are in the range from 10 to 15% at 15 years post treatment, and are still higher for BRCA1/2 carriers, as well as for still longer term survivors. These second cancer risks are much higher than those for a comparable healthy woman to develop a first breast cancer. It follows that women with breast cancer are highly prone to develop a second breast cancer. We propose here a new option for reducing the disturbingly high risk of a contralateral second breast cancer. in patients with both estrogen positive and negative primary breast cancer: prophylactic mammary irradiation (PMI) of the contralateral breast. The rationale behind PMI is evidence that standard post-Iumpectomy radiotherapy of the affected (ipsilateral) breast substantially reduces the long-term genetically-based second cancer risk in the ipsilateral breast, by killing the existing premalignant cells in that breast. This suggests that there are relatively few premalignant cells in the breast (hundreds or thousands, not millions), so even a fairly modest radiation cell-kill level across the whole breast would be expected to kill essentially all of them. If this is so, then a modest radiation dose-much lower than that to the affected breast--delivered uniformly to the whole contralateral breast, and typically delivered at the same time as the radiotherapy of the ipsilateral breast, would have the potential to markedly reduce second-cancer risks in the contralateral breast by killing essentially all the pre-malignant cells in that breast while causing only a very low level of radiation-induced sequelae. Therefore we hypothesize that low-dose prophylactic mammary irradiation of the contralateral breast

Detection of breast cancer using advanced techniques of data mining with neural networks

International Nuclear Information System (INIS)

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

2016-10-01

The breast cancer is one of the biggest health problems worldwide, is the most diagnosed cancer in women and prevention seems impossible since its cause is unknown, due to this; the early detection has a key role in the patient prognosis. In developing countries such as Mexico, where access to specialized health services is minimal, the regular clinical review is infrequent and there are not enough radiologists; the most common form of detection of breast cancer is through self-exploration, but this is only detected in later stages, when is already palpable. For these reasons, the objective of the present work is the creation of a system of computer assisted diagnosis (CAD x) using information analysis techniques such as data mining and advanced techniques of artificial intelligence, seeking to offer a previous medical diagnosis or a second opinion, as if it was a second radiologist in order to reduce the rate of mortality from breast cancer. In this paper, advances in the design of computational algorithms using computer vision techniques for the extraction of features derived from mammograms are presented. Using data mining techniques of data mining is possible to identify patients with a high risk of breast cancer. With the information obtained from the mammography analysis, the objective in the next stage will be to establish a methodology for the generation of imaging bio-markers to establish a breast cancer risk index for Mexican patients. In this first stage we present results of the classification of patients with high and low risk of suffering from breast cancer using neural networks. (Author)

PET scan for breast cancer

Science.gov (United States)

... radioactive substance (called a tracer) to look for breast cancer. This tracer can help identify areas of cancer ... only after a woman has been diagnosed with breast cancer. It is done to see if the cancer ...

Breast cancer and breast health awareness as an evolving health promotion concept

International Nuclear Information System (INIS)

Plesnicar, A.; Kralj, B.; Kovac, V.

2004-01-01

Background. Breast cancer is the most frequent malignant disease in the majority of developed countries. In the last few years the introduction of mammography screening programmes has resulted in an improved survival of breast cancer patients. However, the incidence of the disease in these countries is still on the increase. Present focus on secondary breast cancer prevention activities, consisting of early detection and treatment, cannot ensure a decrease of breast cancer incidence. Improved breast health awareness could therefore represent a part of specific health promotion activities aimed at decreasing the incidence of breast cancer. Conclusions. In developed countries breast cancer is a significant health care issue. Secondary breast cancer prevention activities should therefore be complemented by specific health promotion activities in order to reduce its incidence in the future. Primary breast cancer prevention would include health promotion activities aimed at enhancement of the individual as well as collective breast health awareness. Properly enlightened members of the influential population groups could attain appropriate changes in the fields of legislation, taxation, customs and commercial regulations that would enable women to control their own breast health. (author)

Immunophenotyping of hereditary breast cancer

NARCIS (Netherlands)

van der Groep, P.

2009-01-01

Hereditary breast cancer runs in families where several family members in different generations are affected. Most of these breast cancers are caused by mutations in the high penetrance genes BRCA1 and BRCA2 which account for about 5% of all breast cancers. However, mutations in BRCA1 and BRCA2 may

Radiofrequency Tagged Surgery in Treating Patients With Breast Cancer

Science.gov (United States)

2018-06-18

Positive Axillary Lymph Node; Stage 0 Breast Cancer AJCC v6 and v7; Stage I Breast Cancer AJCC v7; Stage IA Breast Cancer AJCC v7; Stage IB Breast Cancer AJCC v7; Stage II Breast Cancer AJCC v6 and v7; Stage IIA Breast Cancer AJCC v6 and v7; Stage IIB Breast Cancer AJCC v6 and v7; Stage III Breast Cancer AJCC v7; Stage IIIA Breast Cancer AJCC v7; Stage IIIB Breast Cancer AJCC v7; Stage IIIC Breast Cancer AJCC v7

Management of fertility preservation in young breast cancer patients in a large breast cancer centre.

Science.gov (United States)

Lawrenz, B; Neunhoeffer, E; Henes, M; Lessmann-Bechle, S; Krämer, B; Fehm, Tanja

2010-11-01

The increase of breast cancer in young women under 40 years and the increasing age of women at the time of the birth of their first child underlines the importance to implement counselling for fertility-preserving strategies in the management of breast cancer care. We present the fertility-preserving procedures performed after routine counselling for primary breast cancer patients in a large certified breast cancer centre. Since November 2006, patients aged below 40 years with histologically confirmed breast cancer are routinely counselled on fertility-preserving possibilities before breast surgery and chemotherapy in the fertility centre of the University Women's Hospital in Tuebingen. The recommendations are based on the treatment recommendations of the network FertiPROTEKT. During the last 40 months, 56 primary breast cancer patients were counselled. Forty-one of these patients were hormone receptor positive. Thirty-four patients (63%) underwent fertility-preserving strategies. The majority of the patients (n = 22) decided on ovarian tissue cryopreservation. GnRH protection was performed in 14 patients. In 12 patients an ovarian stimulation protocol was initiated to cryopreserve fertilized or unfertilized oocytes. A combination of different fertility-preserving methods was performed in 12 patients. The preservation of ovarian function and fertility are of great importance to young breast cancer patients. Counselling on fertility-preserving strategies is therefore critical in these patients and should be routinely performed.

Statins and breast cancer prognosis

DEFF Research Database (Denmark)

Ahern, Thomas P; Lash, Timothy L; Damkier, Per

2014-01-01

Much preclinical and epidemiological evidence supports the anticancer effects of statins. Epidemiological evidence does not suggest an association between statin use and reduced incidence of breast cancer, but does support a protective effect of statins-especially simvastatin-on breast cancer...... recurrence. Here, we argue that the existing evidence base is sufficient to justify a clinical trial of breast cancer adjuvant therapy with statins and we advocate for such a trial to be initiated without delay. If a protective effect of statins on breast cancer recurrence is supported by trial evidence......, then the indications for a safe, well tolerated, and inexpensive treatment can be expanded to improve outcomes for breast cancer survivors. We discuss several trial design opportunities-including candidate predictive biomarkers of statin safety and efficacy-and off er solutions to the key challenges involved...

Decline in breast cancer mortality

DEFF Research Database (Denmark)

Njor, Sisse Helle; Schwartz, Walter; Blichert-Toft, Mogens

2015-01-01

OBJECTIVES: When estimating the decline in breast cancer mortality attributable to screening, the challenge is to provide valid comparison groups and to distinguish the screening effect from other effects. In Funen, Denmark, multidisciplinary breast cancer management teams started before screening...... was introduced; both activities came later in the rest of Denmark. Because Denmark had national protocols for breast cancer treatment, but hardly any opportunistic screening, Funen formed a "natural experiment", providing valid comparison groups and enabling the separation of the effect of screening from other...... factors. METHODS: Using Poisson regression we compared the observed breast cancer mortality rate in Funen after implementation of screening with the expected rate without screening. The latter was estimated from breast cancer mortality in the rest of Denmark controlled for historical differences between...

Unemployment among breast cancer survivors

DEFF Research Database (Denmark)

Carlsen, Kathrine; Ewertz, Marianne; Dalton, Susanne Oksbjerg

2014-01-01

AIM: Though about 20% of working age breast cancer survivors do not return to work after treatment, few studies have addressed risk factors for unemployment. The majority of studies on occupational consequences of breast cancer focus on non-employment, which is a mixture of sickness absence......, unemployment, retirement pensions and other reasons for not working. Unemployment in combination with breast cancer may represent a particular challenge for these women. The aim of the present study is therefore to analyze the risk for unemployment in the years following diagnosis and treatment for breast...... cancer. METHOD: This study included 14,750 women diagnosed with breast cancer in Denmark 2001-2009 identified through a population-based clinical database and linked with information from Danish administrative population based registers for information on labour market affiliation, socio...

A method to determine the mammographic regions that show early changes due to the development of breast cancer

Science.gov (United States)

Karemore, Gopal; Nielsen, Mads; Karssemeijer, Nico; Brandt, Sami S.

2014-11-01

It is well understood nowadays that changes in the mammographic parenchymal pattern are an indicator of a risk of breast cancer and we have developed a statistical method that estimates the mammogram regions where the parenchymal changes, due to breast cancer, occur. This region of interest is computed from a score map by utilising the anatomical breast coordinate system developed in our previous work. The method also makes an automatic scale selection to avoid overfitting while the region estimates are computed by a nested cross-validation scheme. In this way, it is possible to recover those mammogram regions that show a significant difference in classification scores between the cancer and the control group. Our experiments suggested that the most significant mammogram region is the region behind the nipple and that can be justified by previous findings from other research groups. This result was conducted on the basis of the cross-validation experiments on independent training, validation and testing sets from the case-control study of 490 women, of which 245 women were diagnosed with breast cancer within a period of 2-4 years after the baseline mammograms. We additionally generalised the estimated region to another, mini-MIAS study and showed that the transferred region estimate gives at least a similar classification result when compared to the case where the whole breast region is used. In all, by following our method, one most likely improves both preclinical and follow-up breast cancer screening, but a larger study population will be required to test this hypothesis.

A method to determine the mammographic regions that show early changes due to the development of breast cancer

International Nuclear Information System (INIS)

Karemore, Gopal; Nielsen, Mads; Brandt, Sami S; Karssemeijer, Nico

2014-01-01

It is well understood nowadays that changes in the mammographic parenchymal pattern are an indicator of a risk of breast cancer and we have developed a statistical method that estimates the mammogram regions where the parenchymal changes, due to breast cancer, occur. This region of interest is computed from a score map by utilising the anatomical breast coordinate system developed in our previous work. The method also makes an automatic scale selection to avoid overfitting while the region estimates are computed by a nested cross-validation scheme. In this way, it is possible to recover those mammogram regions that show a significant difference in classification scores between the cancer and the control group. Our experiments suggested that the most significant mammogram region is the region behind the nipple and that can be justified by previous findings from other research groups. This result was conducted on the basis of the cross-validation experiments on independent training, validation and testing sets from the case-control study of 490 women, of which 245 women were diagnosed with breast cancer within a period of 2–4 years after the baseline mammograms. We additionally generalised the estimated region to another, mini-MIAS study and showed that the transferred region estimate gives at least a similar classification result when compared to the case where the whole breast region is used. In all, by following our method, one most likely improves both preclinical and follow-up breast cancer screening, but a larger study population will be required to test this hypothesis. (paper)

Breast cancer in atomic bomb survivors

International Nuclear Information System (INIS)

Tokunga, M.; Land, C.E.; Tokuoka, S.

1986-01-01

Thirty eight years after the atomic bombings, studies of the Radiation Effects Research Foundation (RERF) on the extended Life Span Study (LSS) sample have continued to provide important information on radiation carcinogenesis. The third breast cancer survey among this sample revealed 564 cases during the period 1950-80, of which 412 were reviewed microscopically. The following statements reflect the conclusions from the current investigation; 1) the relationship between radiation dose and breast cancer incidence was consistent with linearity and did not differ markedly between the Hiroshima and Nagasaki survivors, 2) a dose-related breast cancer risk was observed among women who were in their first decade of life at the time of exposure, 3) the relative risk of radiationinduced breast cancer decreased with increasing age at exposure, 4) the pattern over time of age-specific breast cancer incidence is similar for exposed and control women (that is, exposed women have more breast cancer than control women but the excess risk closely follows normal risk as expressed by age-specific population rates), and 5) radiation-induced breast cancer appears to be morphologically similar to other breast cancer

Breast cancer in atomic bomb survivors

International Nuclear Information System (INIS)

Tokunaga, Masayoshi; Tokuoka, Shoji; Land, C.E.

1986-01-01

Thirty eight years after the atomic bombings, studies of the Radiation Effects Research Foundation (RERF) on the extended Life Span Study (LSS) sample have continued to provide important information on radiation carcinogenesis. The third breast cancer survey among this sample revealed 564 cases during the period 1950 - 80, of which 412 were reviewed microscopically. The following statements reflect the conclusions from the current investigation; 1) the relationship between radiation dose and breast cancer incidence was consistent with linearity and did not differ markedly between the Hiroshima and Nagasaki survivors, 2) a dose-related breast cancer risk was observed among women who were in their first decade of life at the time of exposure, 3) the relative risk of radiation-induced breast cancer decreased with increasing age at exposure, 4) the pattern over time of age-specific breast cancer incidence is similar for exposed and control women (that is, exposed women have more breast cancer than control women but the excess risk closely follows normal risk as expressed by age-specific population rates), and 5) radiation-induced breast cancer appears to be morphologically similar to other breast cancer. (author)

Screen-detected versus interval cancers: Effect of imaging modality and breast density in the Flemish Breast Cancer Screening Programme.

Science.gov (United States)

Timmermans, Lore; Bleyen, Luc; Bacher, Klaus; Van Herck, Koen; Lemmens, Kim; Van Ongeval, Chantal; Van Steen, Andre; Martens, Patrick; De Brabander, Isabel; Goossens, Mathieu; Thierens, Hubert

2017-09-01

To investigate if direct radiography (DR) performs better than screen-film mammography (SF) and computed radiography (CR) in dense breasts in a decentralized organised Breast Cancer Screening Programme. To this end, screen-detected versus interval cancers were studied in different BI-RADS density classes for these imaging modalities. The study cohort consisted of 351,532 women who participated in the Flemish Breast Cancer Screening Programme in 2009 and 2010. Information on screen-detected and interval cancers, breast density scores of radiologist second readers, and imaging modality was obtained by linkage of the databases of the Centre of Cancer Detection and the Belgian Cancer Registry. Overall, 67% of occurring breast cancers are screen detected and 33% are interval cancers, with DR performing better than SF and CR. The interval cancer rate increases gradually with breast density, regardless of modality. In the high-density class, the interval cancer rate exceeds the cancer detection rate for SF and CR, but not for DR. DR is superior to SF and CR with respect to cancer detection rates for high-density breasts. To reduce the high interval cancer rate in dense breasts, use of an additional imaging technique in screening can be taken into consideration. • Interval cancer rate increases gradually with breast density, regardless of modality. • Cancer detection rate in high-density breasts is superior in DR. • IC rate exceeds CDR for SF and CR in high-density breasts. • DR performs better in high-density breasts for third readings and false-positives.

Imaging Management of Breast Density, a Controversial Risk Factor for Breast Cancer.

Science.gov (United States)

Falcon, Shannon; Williams, Angela; Weinfurtner, Jared; Drukteinis, Jennifer S

2017-04-01

Breast density is well recognized as an independent risk factor for the development of breast cancer. However, the magnitude of risk is controversial. As the public becomes increasingly aware of breast density as a risk factor, legislation and notification laws in relation to breast density have become common throughout the United States. Awareness of breast density as a risk factor for breast cancer presents new challenges for the clinician in the approach to the management and screening of women with dense breasts. The evidence and controversy surrounding breast density as a risk factor for the development of breast cancer are discussed. Common supplemental screening modalities for breast cancer are also discussed, including tomosynthesis, ultrasonography, and magnetic resonance imaging. A management strategy for screening women with dense breasts is also presented. The American College of Radiology recognizes breast density as a controversial risk factor for breast cancer, whereas the American Congress of Obstetricians and Gynecologists recognizes breast density as a modest risk factor. Neither organization recommends the routine use of supplemental screening in women with dense breasts without considering additional patient-related risk factors. Breast density is a poorly understood and controversial risk factor for the development of breast cancer. Mammography is a screening modality proven to reduce breast cancer-related mortality rates and is the single most appropriate tool for population-based screening. Use of supplemental screening modalities should be tailored to individual risk assessment.

Delayed breast reconstruction with implants after invasive breast cancer does not impair prognosis

DEFF Research Database (Denmark)

Holmich, L.R.; During, M.; Henriksen, T.F.

2008-01-01

We investigated if delayed breast implant reconstruction after breast cancer impairs prognosis. Using data from the Danish Breast Cancer Cooperative Group register, we identified all women......We investigated if delayed breast implant reconstruction after breast cancer impairs prognosis. Using data from the Danish Breast Cancer Cooperative Group register, we identified all women...

Iodide transport and breast cancer.

Science.gov (United States)

Poole, Vikki L; McCabe, Christopher J

2015-10-01

Breast cancer is the second most common cancer worldwide and the leading cause of cancer death in women, with incidence rates that continue to rise. The heterogeneity of the disease makes breast cancer exceptionally difficult to treat, particularly for those patients with triple-negative disease. To address the therapeutic complexity of these tumours, new strategies for diagnosis and treatment are urgently required. The ability of lactating and malignant breast cells to uptake and transport iodide has led to the hypothesis that radioiodide therapy could be a potentially viable treatment for many breast cancer patients. Understanding how iodide is transported, and the factors regulating the expression and function of the proteins responsible for iodide transport, is critical for translating this hypothesis into reality. This review covers the three known iodide transporters - the sodium iodide symporter, pendrin and the sodium-coupled monocarboxylate transporter - and their role in iodide transport in breast cells, along with efforts to manipulate them to increase the potential for radioiodide therapy as a treatment for breast cancer. © 2015 Society for Endocrinology.

Rural-Urban Differences in Late-Stage Breast Cancer: Do Associations Differ by Rural-Urban Classification System?

Science.gov (United States)

Pruitt, Sandi L; Eberth, Jan M; Morris, E Scott; Grinsfelder, David B; Cuate, Erica L

2016-01-01

Introduction Rural residence is associated with later stage of breast cancer diagnosis in some but not all prior studies. The lack of a standardized definition of rural residence may contribute to these mixed findings. We characterize and compare multiple definitions of rural vs. non-rural residence to provide guidance regarding choice of measures and to further elucidate rural disparities in breast cancer stage at diagnosis. Methods We used Texas Cancer Registry data of 120,738 female breast cancer patients ≥50 years old diagnosed between 1995–2009. We defined rural vs. non-rural residence using 7 different measures and examined their agreement using Kappa statistics. Measures were defined at various geographic levels: county, ZIP code, census tract, and census block group. Late-stage was defined as regional or distant disease. For each measure, we tested the association of rural residence and late-stage cancer with unadjusted and adjusted logistic regression. Covariates included: age; patient race/ethnicity; diagnosis year; census block group-level mammography capacity; and census tract-level percent poverty, percent Hispanic, and percent Black. Results We found moderate to high levels of agreement between measures of rural vs. non-rural residence. For 72.9% of all patients, all 7 definitions agreed as to rural vs. non-rural residence. Overall, 6 of 7 definitions demonstrated an adverse association between rural residence and late-stage disease in unadjusted and adjusted models (Adjusted OR Range = 1.09–1.14). Discussion Our results document a clear rural disadvantage in late-stage breast cancer. We contribute to the heterogeneous literature by comparing varied measures of rural residence. We recommend use of the census tract-level Rural Urban Commuting Area Codes in future cancer outcomes research where small area data are available. PMID:27158685

Interleukin-19 in Breast Cancer

Directory of Open Access Journals (Sweden)

Ying-Yin Chen

2013-01-01

Full Text Available Inflammatory cytokines within the tumor microenvironment are linked to progression in breast cancer. Interleukin- (IL- 19, part of the IL-10 family, contributes to a range of diseases and disorders, such as asthma, endotoxic shock, uremia, psoriasis, and rheumatoid arthritis. IL-19 is expressed in several types of tumor cells, especially in squamous cell carcinoma of the skin, tongue, esophagus, and lung and invasive duct carcinoma of the breast. In breast cancer, IL-19 expression is correlated with increased mitotic figures, advanced tumor stage, higher metastasis, and poor survival. The mechanisms of IL-19 in breast cancer have recently been explored both in vitro and in vivo. IL-19 has an autocrine effect in breast cancer cells. It directly promotes proliferation and migration and indirectly provides a microenvironment for tumor progression, which suggests that IL-19 is a prognostic marker in breast cancer and that antagonizing IL-19 may have therapeutic potential.

RAD51B in Familial Breast Cancer

OpenAIRE

Pelttari, L.M.; Khan, S.; et al.,

2016-01-01

Common variation on 14q24.1, close to RAD51B, has been associated with breast cancer: rs999737\\ud and rs2588809 with the risk of female breast cancer and rs1314913 with the risk of male breast\\ud cancer. The aim of this study was to investigate the role of RAD51B variants in breast cancer\\ud predisposition, particularly in the context of familial breast cancer in Finland. We sequenced the\\ud coding region of RAD51B in 168 Finnish breast cancer patients from the Helsinki region for\\ud identifi...

RAD51B in familial breast cancer

OpenAIRE

Pelttari, LM; Khan, S; Vuorela, M; Kiiski, JI; Vilske, S; Nevanlinna, V; Ranta, S; Schleutker, J; Winqvist, R; Kallioniemi, A; Dörk, T; Bogdanova, NV; Figueroa, J; Pharoah, PDP; Schmidt, MK

2016-01-01

Common variation on 14q24.1, close to RAD51B, has been associated with breast cancer: rs999737 and rs2588809 with the risk of female breast cancer and rs1314913 with the risk of male breast cancer. The aim of this study was to investigate the role of RAD51B variants in breast cancer predisposition, particularly in the context of familial breast cancer in Finland. We sequenced the coding region of RAD51B in 168 Finnish breast cancer patients from the Helsinki region for identification of possi...

Breast Cancer After Chest Radiation Therapy for Childhood Cancer

Science.gov (United States)

Moskowitz, Chaya S.; Chou, Joanne F.; Wolden, Suzanne L.; Bernstein, Jonine L.; Malhotra, Jyoti; Friedman, Danielle Novetsky; Mubdi, Nidha Z.; Leisenring, Wendy M.; Stovall, Marilyn; Hammond, Sue; Smith, Susan A.; Henderson, Tara O.; Boice, John D.; Hudson, Melissa M.; Diller, Lisa R.; Bhatia, Smita; Kenney, Lisa B.; Neglia, Joseph P.; Begg, Colin B.; Robison, Leslie L.; Oeffinger, Kevin C.

2014-01-01

Purpose The risk of breast cancer is high in women treated for a childhood cancer with chest irradiation. We sought to examine variations in risk resulting from irradiation field and radiation dose. Patients and Methods We evaluated cumulative breast cancer risk in 1,230 female childhood cancer survivors treated with chest irradiation who were participants in the CCSS (Childhood Cancer Survivor Study). Results Childhood cancer survivors treated with lower delivered doses of radiation (median, 14 Gy; range, 2 to 20 Gy) to a large volume (whole-lung field) had a high risk of breast cancer (standardized incidence ratio [SIR], 43.6; 95% CI, 27.2 to 70.3), as did survivors treated with high doses of delivered radiation (median, 40 Gy) to the mantle field (SIR, 24.2; 95% CI, 20.7 to 28.3). The cumulative incidence of breast cancer by age 50 years was 30% (95% CI, 25 to 34), with a 35% incidence among Hodgkin lymphoma survivors (95% CI, 29 to 40). Breast cancer–specific mortality at 5 and 10 years was 12% (95% CI, 8 to 18) and 19% (95% CI, 13 to 25), respectively. Conclusion Among women treated for childhood cancer with chest radiation therapy, those treated with whole-lung irradiation have a greater risk of breast cancer than previously recognized, demonstrating the importance of radiation volume. Importantly, mortality associated with breast cancer after childhood cancer is substantial. PMID:24752044

Breast cancer: surgery at the South egypt cancer institute.

Science.gov (United States)

Salem, Ahmed A S; Salem, Mohamed Abou Elmagd; Abbass, Hamza

2010-09-30

Breast cancer is the most frequent malignant tumor in women worldwide. In Egypt, it is the most common cancer among women, representing 18.9% of total cancer cases (35.1% in women and 2.2% in men) among the Egypt National Cancer Institute's (NCI) series of 10,556 patients during the year 2001, with an age-adjusted rate of 49.6 per 100,000 people. In this study, the data of all breast cancer patients presented to the surgical department of the South Egypt cancer Institute (SECI) hospital during the period from Janurary 2001 to December 2008 were reviewed .We report the progress of the availability of breast cancer management and evaluation of the quality of care delivered to breast cancer patients. The total number of patients with a breast lump presented to the SECI during the study period was 1,463 patients (32 males and 1431 females); 616 patients from the total number were admitted at the surgical department .There was a decline in advanced cases. Since 2001, facilities for all lines of comprehensive management have been made accessible for all patients. We found that better management could lead to earlier presentation, and better overall outcome in breast cancer patients.The incidence is steadily increasing with a tendency for breast cancer to occur in younger age groups and with advanced stages.

Breast Cancer: Surgery at the South Egypt Cancer Institute

Directory of Open Access Journals (Sweden)

Ahmed A.S. Salem

2010-09-01

Full Text Available Breast cancer is the most frequent malignant tumor in women worldwide. In Egypt, it is the most common cancer among women, representing 18.9% of total cancer cases (35.1% in women and 2.2% in men among the Egypt National Cancer Institute’s (NCI series of 10,556 patients during the year 2001, with an age-adjusted rate of 49.6 per 100,000 people. In this study, the data of all breast cancer patients presented to the surgical department of the South Egypt cancer Institute (SECI hospital during the period from Janurary 2001 to December 2008 were reviewed .We report the progress of the availability of breast cancer management and evaluation of the quality of care delivered to breast cancer patients. The total number of patients with a breast lump presented to the SECI during the study period was 1,463 patients (32 males and 1431 females; 616 patients from the total number were admitted at the surgical department .There was a decline in advanced cases. Since 2001, facilities for all lines of comprehensive management have been made accessible for all patients. We found that better management could lead to earlier presentation, and better overall outcome in breast cancer patients.The incidence is steadily increasing with a tendency for breast cancer to occur in younger age groups and with advanced stages.

Preeclampsia and breast cancer

DEFF Research Database (Denmark)

Pacheco, Nadja Livia Pekkola; Andersen, Anne-Marie Nybo; Kamper-Jørgensen, Mads

2015-01-01

BACKGROUND: In parous women preeclampsia has been associated with reduced risk of developing breast cancer. Characteristics of births following preeclamptic pregnancies may help understand mechanisms involved in the breast cancer risk reduction inferred by preeclampsia. METHODS: We conducted...... a register-based cohort study of all Danish women giving birth during 1978-2010 (n = 778,701). The association between preeclampsia and breast cancer was evaluated overall and according to birth characteristics by means of incidence rate ratios (IRR) estimated in Poisson regression models. RESULTS: Compared...... with women with non-preeclamptic pregnancies only, women with one or more preeclamptic pregnancies were 19% significantly less likely to develop breast cancer (IRR = 0.81 [95% CI 0.72-0.93]). We found some indication of greater risk reduction in women with term births, one or more previous births...

CDC Vital Signs: Breast Cancer

Science.gov (United States)

... 2.65 MB] Read the MMWR Science Clips Breast Cancer Black Women Have Higher Death Rates from Breast ... of Page U.S. State Info Number of Additional Breast Cancer Deaths Among Black Women, By State SOURCE: National ...

Reproductive History and Breast Cancer Risk

Science.gov (United States)

... Common Cancer Types Recurrent Cancer Common Cancer Types Bladder Cancer Breast Cancer Colorectal Cancer Kidney (Renal Cell) Cancer ... 4 ). This risk reduction is limited to hormone receptor –positive breast cancer; age at first full-term ...

Epigenetic suppression of neprilysin regulates breast cancer invasion.

Science.gov (United States)

Stephen, H M; Khoury, R J; Majmudar, P R; Blaylock, T; Hawkins, K; Salama, M S; Scott, M D; Cosminsky, B; Utreja, N K; Britt, J; Conway, R E

2016-03-07

In women, invasive breast cancer is the second most common cancer and the second cause of cancer-related death. Therefore, identifying novel regulators of breast cancer invasion could lead to additional biomarkers and therapeutic targets. Neprilysin, a cell-surface enzyme that cleaves and inactivates a number of substrates including endothelin-1 (ET1), has been implicated in breast cancer, but whether neprilysin promotes or inhibits breast cancer cell progression and metastasis is unclear. Here, we asked whether neprilysin expression predicts and functionally regulates breast cancer cell invasion. RT-PCR and flow cytometry analysis of MDA-MB-231 and MCF-7 breast cancer cell lines revealed decreased neprilysin expression compared with normal epithelial cells. Expression was also suppressed in invasive ductal carcinoma (IDC) compared with normal tissue. In addition, in vtro invasion assays demonstrated that neprilysin overexpression decreased breast cancer cell invasion, whereas neprilysin suppression augmented invasion. Furthermore, inhibiting neprilysin in MCF-7 breast cancer cells increased ET1 levels significantly, whereas overexpressing neprilysin decreased extracellular-signal related kinase (ERK) activation, indicating that neprilysin negatively regulates ET1-induced activation of mitogen-activated protein kinase (MAPK) signaling. To determine whether neprilysin was epigenetically suppressed in breast cancer, we performed bisulfite conversion analysis of breast cancer cells and clinical tumor samples. We found that the neprilysin promoter was hypermethylated in breast cancer; chemical reversal of methylation in MDA-MB-231 cells reactivated neprilysin expression and inhibited cancer cell invasion. Analysis of cancer databases revealed that neprilysin methylation significantly associates with survival in stage I IDC and estrogen receptor-negative breast cancer subtypes. These results demonstrate that neprilysin negatively regulates the ET axis in breast cancer

Quantitative diffusion weighted imaging parameters in tumor and peritumoral stroma for prediction of molecular subtypes in breast cancer

Science.gov (United States)

He, Ting; Fan, Ming; Zhang, Peng; Li, Hui; Zhang, Juan; Shao, Guoliang; Li, Lihua

2018-03-01

Breast cancer can be classified into four molecular subtypes of Luminal A, Luminal B, HER2 and Basal-like, which have significant differences in treatment and survival outcomes. We in this study aim to predict immunohistochemistry (IHC) determined molecular subtypes of breast cancer using image features derived from tumor and peritumoral stroma region based on diffusion weighted imaging (DWI). A dataset of 126 breast cancer patients were collected who underwent preoperative breast MRI with a 3T scanner. The apparent diffusion coefficients (ADCs) were recorded from DWI, and breast image was segmented into regions comprising the tumor and the surrounding stromal. Statistical characteristics in various breast tumor and peritumoral regions were computed, including mean, minimum, maximum, variance, interquartile range, range, skewness, and kurtosis of ADC values. Additionally, the difference of features between each two regions were also calculated. The univariate logistic based classifier was performed for evaluating the performance of the individual features for discriminating subtypes. For multi-class classification, multivariate logistic regression model was trained and validated. The results showed that the tumor boundary and proximal peritumoral stroma region derived features have a higher performance in classification compared to that of the other regions. Furthermore, the prediction model using statistical features, difference features and all the features combined from these regions generated AUC values of 0.774, 0.796 and 0.811, respectively. The results in this study indicate that ADC feature in tumor and peritumoral stromal region would be valuable for estimating the molecular subtype in breast cancer.

BREAST RECONSTRUCTIONS AFTER BREAST CANCER TREATING

Directory of Open Access Journals (Sweden)

Erik Vrabič

2018-02-01

Full Text Available Background. Breasts are an important symbol of physical beauty, feminity, mothering and sexual desire through the entire history of mankind. Lost of the whole or part of the breast is functional and aesthetic disturbance for woman. It is understandable, that the woman, who is concerned over breast loss, is as appropriate as another person´s concern over the loss of a limb or other body part. Before the 1960, breast reconstruction was considered as a dangerous procedure and it was almost prohibited. Considering the psychological importance of the breast in modern society, the possibility of breast reconstruction for the woman about to undergo a mastectomy is a comforting alternative. We can perform breast reconstruction with autologous tissue (autologous reconstruction, with breast implants and combination of both methods. For autologous reconstruction we can use local tissue (local flaps, or tissue from distant parts of the body (free vascular tissue transfer. Tissue expansion must be performed first, in many cases of breast reconstructions with breast implants. Conclusions. Possibility of breast reconstruction made a big progress last 3 decades. Today we are able to reconstruct almost every defect of the breast and the entire breast. Breast reconstruction rise the quality of life for breast cancer patients. Breast reconstruction is a team work of experts from many medicine specialites. In Slovenia we can offer breast reconstruction for breast cancer patients in Ljubljana, where plastic surgeons from Clinical Department for Plastic Surgery and Burns cooperate with oncologic surgeons. Ten years ago a similar cooperation between plastic surgeons and surgeons of the Centre for Breast Diseases was established in Maribor.

Adherence to Guidelines for Breast Surveillance in Breast Cancer Survivors.

Science.gov (United States)

Ruddy, Kathryn J; Sangaralingham, Lindsey; Freedman, Rachel A; Mougalian, Sarah; Neuman, Heather; Greenberg, Caprice; Jemal, Ahmedin; Duma, Narjust; Haddad, Tufia C; Lemaine, Valerie; Ghosh, Karthik; Hieken, Tina J; Hunt, Katie; Vachon, Celine; Gross, Cary; Shah, Nilay D

2018-05-01

Background: Guidelines recommend annual mammography after curative-intent treatment for breast cancer. The goal of this study was to assess contemporary patterns of breast imaging after breast cancer treatment. Methods: Administrative claims data were used to identify privately insured and Medicare Advantage beneficiaries with nonmetastatic breast cancer who had residual breast tissue (not bilateral mastectomy) after breast surgery between January 2005 and May 2015. We calculated the proportion of patients who had a mammogram, MRI, both, or neither during each of 5 subsequent 13-month periods. Multinomial logistic regression was used to assess associations between patient characteristics, healthcare use, and breast imaging in the first and fifth years after surgery. Results: A total of 27,212 patients were followed for a median of 2.9 years (interquartile range, 1.8-4.6) after definitive breast cancer surgery. In year 1, 78% were screened using mammography alone, 1% using MRI alone, and 8% using both tests; 13% did not undergo either. By year 5, the proportion of the remaining cohort (n=4,790) who had no breast imaging was 19%. Older age was associated with an increased likelihood of mammography and a decreased likelihood of MRI during the first and fifth years. Black race, mastectomy, chemotherapy, and no MRI at baseline were all associated with a decreased likelihood of both types of imaging. Conclusions: Even in an insured cohort, a substantial proportion of breast cancer survivors do not undergo annual surveillance breast imaging, particularly as time passes. Understanding factors associated with imaging in cancer survivors may help improve adherence to survivorship care guidelines. Copyright © 2018 by the National Comprehensive Cancer Network.

RAD51B in Familial Breast Cancer

DEFF Research Database (Denmark)

Pelttari, Liisa M; Khan, Sofia; Vuorela, Mikko

2016-01-01

Common variation on 14q24.1, close to RAD51B, has been associated with breast cancer: rs999737 and rs2588809 with the risk of female breast cancer and rs1314913 with the risk of male breast cancer. The aim of this study was to investigate the role of RAD51B variants in breast cancer predisposition......, particularly in the context of familial breast cancer in Finland. We sequenced the coding region of RAD51B in 168 Finnish breast cancer patients from the Helsinki region for identification of possible recurrent founder mutations. In addition, we studied the known rs999737, rs2588809, and rs1314913 SNPs and RAD......51B haplotypes in 44,791 breast cancer cases and 43,583 controls from 40 studies participating in the Breast Cancer Association Consortium (BCAC) that were genotyped on a custom chip (iCOGS). We identified one putatively pathogenic missense mutation c.541C>T among the Finnish cancer patients...

Contrast-enhanced spectral mammography in patients referred from the breast cancer screening programme.

Science.gov (United States)

Lobbes, Marc B I; Lalji, Ulrich; Houwers, Janneke; Nijssen, Estelle C; Nelemans, Patty J; van Roozendaal, Lori; Smidt, Marjolein L; Heuts, Esther; Wildberger, Joachim E

2014-07-01

Feasibility studies have shown that contrast-enhanced spectral mammography (CESM) increases diagnostic accuracy of mammography. We studied diagnostic accuracy of CESM in patients referred from the breast cancer screening programme, who have a lower disease prevalence than previously published papers on CESM. During 6 months, all women referred to our hospital were eligible for CESM. Two radiologists blinded to the final diagnosis provided BI-RADS classifications for conventional mammography and CESM. Statistical significance of differences between mammography and CESM was calculated using McNemar's test. Receiver operating characteristic (ROC) curves were constructed for both imaging modalities. Of the 116 eligible women, 113 underwent CESM. CESM increased sensitivity to 100.0% (+3.1%), specificity to 87.7% (+45.7%), PPV to 76.2% (+36.5%) and NPV to 100.0% (+2.9%) as compared to mammography. Differences between conventional mammography and CESM were statistically significant (p mammography, AUC was 0.779. With CESM, AUC increased to 0.976 (p mammography, even in lower prevalence patient populations such as referrals from breast cancer screening. • CESM is feasible in the workflow of referrals from routine breast screening. • CESM is superior to mammography, even in low disease prevalence populations. • CESM has an extremely high negative predictive value for breast cancer. • CESM is comparable to MRI in assessment of breast cancer extent. • CESM is comparable to histopathology in assessment of breast cancer extent.

Environmental cadmium and breast cancer risk

OpenAIRE

Gallagher, Carolyn M.; Chen, John J.; Kovach, John S.

2010-01-01

Breast cancer is the most prevalent women's cancer, with an age-adjusted incidence of 122.9 per 100,000 US women. Cadmium, a ubiquitous carcinogenic pollutant with multiple biological effects, has been reported to be associated with breast cancer in one US regional case-control study. We examined the association of breast cancer with urinary cadmium (UCd), in a case-control sample of women living on Long Island (LI), NY (100 with breast cancer and 98 without), a region with an especially high...

Breast cancer in Kumasi, Ghana

International Nuclear Information System (INIS)

Ohene-Yeboah, M.; Adjei, E.

2012-01-01

Breast cancer is the leading cause of cancer deaths in Ghanaian women.To describes the characteristics of breast cancer patients attending the Komfo Anokye Teaching Hospital in Kumasi, Ghana.The study was conducted at the Komfo Anokye Teaching Hospital. Between July 1st 2004 and June 30th 2009 patients presenting with breast lumps were assessed by clinical examination, imaging studies and pathological examination. Relevant clinical and pathological were recorded prospectively data on all patients with microscopically proven breast cancer. The cancers were graded according to the modified Bloom-Richardson system. Tissue immunoperoxidase stains for oestrogen, progesterone receptors and c-erb2 oncogene were performed with commercially prepared antigens and reagents.Nineteen thousand four hundred and twenty – three (19,423) patients were seen during the study period. There were 330 (1.7%) patients with histologically proven breast cancer. The mean age was 49.1 years. A palpable breast lump was detected in 248 patients (75.2%). Two hundred and eighty –one patients (85.2%) presented with Stages III and IV , 271 (82.1%) invasive and 230 ( 85.2%) high grade carcinomas. Oestrogen and progesterone receptors were positive in 32 and 9 cases respectively. Her2 protein was positive in 11 cases. In Kumasi, as in other parts of Ghana, breast cancer affects mostly young pre-menopausal who present with advanced disease. The cancers have unfavourable prognostic features and are unlikely to respond to hormonal therapy. (au)

Hormonal modulation of breast cancer gene expression: implications for intrinsic subtyping in pre-menopausal women

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Sarah M Bernhardt

2016-11-01

Full Text Available Clinics are increasingly adopting gene expression profiling to diagnose breast cancer subtype, providing an intrinsic, molecular portrait of the tumour. For example, the PAM50-based Prosigna test quantifies expression of 50 key genes to classify breast cancer subtype, and this method of classification has been demonstrated to be superior over traditional immunohistochemical methods that detect proteins, to predict risk of disease recurrence. However, these tests were largely developed and validated using breast cancer samples from post-menopausal women. Thus, the accuracy of such tests has not been explored in the context of the hormonal fluctuations in estrogen and progesterone that occur during the menstrual cycle in pre-menopausal women. Concordance between traditional methods of subtyping and the new tests in pre-menopausal women is likely to depend on the stage of the menstrual cycle at which the tissue sample is taken, and the relative effect of hormones on expression of genes versus proteins. The lack of knowledge around the effect of fluctuating estrogen and progesterone on gene expression in breast cancer patients raises serious concerns for intrinsic subtyping in pre-menopausal women, which comprise about 25% of breast cancer diagnoses. Further research on the impact of the menstrual cycle on intrinsic breast cancer profiling is required if pre-menopausal women are to benefit from the new technology of intrinsic subtyping.

Breast cancer screening in older women.

Science.gov (United States)

Caplan, L S; Haynes, S G

1996-01-01

There is currently an epidemic of breast cancer in women 65 years of age and older. The purposes of this paper are to explore the breast cancer screening behaviors of older women and to identify some of the determinants of screening in these women. Data were analyzed from the 1987 National Health Interview Survey, a continuous nationwide household interview survey of the U.S. civilian, noninstitutionalized population. As in other studies, the utilization of breast cancer screening by older women was less in older women than in younger women. This was true for both mammography and clinical breast examination. A number of determinants of screening in older women were identified here. Women with a usual source of care and/or no activity limitation, as well as high school graduates, were the ones most likely to have received a screening mammogram and/or a screening clinical breast exam during the past year. The failure of older women to receive adequate breast cancer screening is an important concern which should be reevaluated, given the breast cancer epidemic in this population. This study identified a number of determinants of breast cancer screening in older women. For the most part, these determinants point to the primary care physician as the key to breast cancer screening in these women. Therefore, the primary care physician must be informed of, and encouraged to follow, the recommendations for periodic breast cancer screening in older women.

Awareness of breast cancer and breast self-examination among ...

African Journals Online (AJOL)

Awareness of breast cancer and breast self-examination among female undergraduate students in a higher teachers training college in Cameroon. ... Conclusion: Though most students are aware of the existence of breast cancer, their overall knowledge on its risk factors and clinical presentation is insufficient with a ...

Urinary estrogen metabolites and breast cancer

DEFF Research Database (Denmark)

Dallal, Cher M; Stone, Roslyn A; Cauley, Jane A

2013-01-01

Background: Circulating estrogens are associated with increased breast cancer risk, yet the role of estrogen metabolites in breast carcinogenesis remains unclear. This combined analysis of 5 published studies evaluates urinary 2-hydroxyestrone (2-OHE1), 16a-hydroxyestrone (16a-OHE1......), and their ratio (2:16a-OHE1) in relation to breast cancer risk. ¿Methods: Primary data on 726 premenopausal women (183 invasive breast cancer cases and 543 controls) and 1,108 postmenopausal women (385 invasive breast cancer cases and 723 controls) were analyzed. Urinary estrogen metabolites were measured using...... premenopausal 2:16a-OHE1 was suggestive of reduced breast cancer risk overall (study-adjusted ORIIIvsI=0.80; 95% CI: 0.49-1.32) and for estrogen receptor negative (ER-) subtype (ORIIIvsI=0.33; 95% CI: 0.13-0.84). Among postmenopausal women, 2:16a-OHE1 was unrelated to breast cancer risk (study-adjusted ORIIIvs...

TOX3 mutations in breast cancer.

Directory of Open Access Journals (Sweden)

James Owain Jones

Full Text Available TOX3 maps to 16q12, a region commonly lost in breast cancers and recently implicated in the risk of developing breast cancer. However, not much is known of the role of TOX3 itself in breast cancer biology. This is the first study to determine the importance of TOX3 mutations in breast cancers. We screened TOX3 for mutations in 133 breast tumours and identified four mutations (three missense, one in-frame deletion of 30 base pairs in six primary tumours, corresponding to an overall mutation frequency of 4.5%. One potentially deleterious missense mutation in exon 3 (Leu129Phe was identified in one tumour (genomic DNA and cDNA. Whilst copy number changes of 16q12 are common in breast cancer, our data show that mutations of TOX3 are present at low frequency in tumours. Our results support that TOX3 should be further investigated to elucidate its role in breast cancer biology.

Breast-Conserving Surgery Followed by Radiation Therapy With MRI-Detected Stage I or Stage II Breast Cancer

Science.gov (United States)

2011-12-07

Ductal Breast Carcinoma in Situ; Estrogen Receptor-negative Breast Cancer; Estrogen Receptor-positive Breast Cancer; HER2-negative Breast Cancer; HER2-positive Breast Cancer; Invasive Ductal Breast Carcinoma; Invasive Lobular Breast Carcinoma; Male Breast Cancer; Medullary Ductal Breast Carcinoma With Lymphocytic Infiltrate; Mucinous Ductal Breast Carcinoma; Papillary Ductal Breast Carcinoma; Progesterone Receptor-negative Breast Cancer; Progesterone Receptor-positive Breast Cancer; Stage I Breast Cancer; Stage II Breast Cancer; Tubular Ductal Breast Carcinoma

Breast cancer with axillary lymph node involvement

International Nuclear Information System (INIS)

Belaid, A.; Kanoun, S.; Kallel, A.; Ghorbel, I.; Azoury, F.; Heymann, S.; Marsiglia, H.; Bourgier, C.; Belaid, A.; Ghorbel, I.; Kanoun, S.; Kallel, A.; Pichenot, C.; Verstraet, R.; Marsiglia, H.

2010-01-01

Breast cancer is the most frequent cancer of women in western countries. There are one million new cases per year in the world which represents 22% of all female cancers, and more than 370.000 deaths due to breast cancer per year (14% of cancer mortality). More than half of breast cancers are associated with axillary nodal involvement. Post-operative radiation therapy (XRT) is a crucial part of locoregional treatment in axillary nodal involvement breast cancer owing to a 15-years risk reduction of locoregional recurrence of 70% and to a 5.4% risk reduction of specific mortality. In 3D-conformal irradiation in such breast cancers, target volumes are chest wall when mastectomy was performed or breast and boost of tumor bed in case of breast conservative surgery, and supra-clavicular and/or axillary and/or internal mammary node areas. The main organs at risk are ipsilateral lung, heart and brachial plexus. The aim of this article is to describe epidemiologic, radio anatomic and prognostic features of axillary nodal involvement breast cancer and to propose guidelines for 3D-conformal treatment planning in locally advanced breast cancers. This review is illustrated by a case report. (authors)

What You Need to Know about Breast Cancer

Science.gov (United States)

... Publications Reports What You Need To Know About™ Breast Cancer This booklet is about breast cancer. Learning about your cancer can help you take ... This booklet covers: Basics about breast anatomy and breast cancer Treatments for breast cancer, including taking part in ...

The potential prognostic value of connexin 26 and 46 expression in neoadjuvant-treated breast cancer

International Nuclear Information System (INIS)

Teleki, Ivett; Varga, Zsuzsanna; Krenacs, Tibor; Szasz, Marcell A; Kulka, Janina; Wichmann, Barna; Leo, Cornelia; Papassotiropoulos, Barbel; Riemenschnitter, Cosima; Moch, Holger

2013-01-01

Several classification systems are available to assess pathological response to neoadjuvant chemotherapy in breast cancer, but reliable biomarkers to predict the efficiency of primary systemic therapy (PST) are still missing. Deregulation of gap junction channel forming connexins (Cx) has been implicated in carcinogenesis and tumour progression through loss of cell cycle control. In this study we correlated Cx expression and cell proliferation with disease survival and pathological response to neoadjuvant chemotherapy in breast cancers using existing classification systems. The expression of Cx26, Cx32, Cx43, Cx46 and Ki67 was evaluated in 96 breast cancer patients prior to and after neoadjuvant chemotherapy using duplicate cores in tissue microarrays (TMA). Cx plaques of <1μm were detected with multilayer, multichannel fluorescence digital microscopy. Current classifications to assess residual tumour burden after primary systemic therapy included the EWGBSP, CPS-EG, Miller-Payne, Sataloff and NSABP systems. In our cohort dominated by hormone receptor (ER/PR) positive and HER2 negative cases, only the CPS-EG classification showed prognostic relevance: cases with scores 1–2 had significantly better overall survival (p=0.015) than cases with scores 3–5. Pre-chemotherapy Cx43 expression correlated positively with hormone receptor status both before and after chemotherapy and had a negative correlation with HER2 expression pre-chemotherapy. There was a positive correlation between Cx32 and HER2 expression pre-chemotherapy and between Cx32 and Ki67 expression post-chemotherapy. A negative correlation was found between post-chemotherapy Cx46 and Ki67 expression. Decreased post-chemotherapy Cx26 expression (<5%) statistically correlated with better overall survival (p=0.011). Moderate or higher Cx46 expression (>20%) pre- and post-chemotherapy correlated with significantly better survival in the intermediate prognostic subgroups of EWGBSP TR2b (p pre-chemo =0

Treatment of locally advanced/locally recurrent breast cancer and inflammatory breast cancer