Of mice and women: a comparative tissue biology perspective of breast stem cells and differentiation.

PubMed

Dontu, Gabriela; Ince, Tan A

2015-06-01

Tissue based research requires a background in human and veterinary pathology, developmental biology, anatomy, as well as molecular and cellular biology. This type of comparative tissue biology (CTB) expertise is necessary to tackle some of the conceptual challenges in human breast stem cell research. It is our opinion that the scarcity of CTB expertise contributed to some erroneous interpretations in tissue based research, some of which are reviewed here in the context of breast stem cells. In this article we examine the dissimilarities between mouse and human mammary tissue and suggest how these may impact stem cell studies. In addition, we consider the differences between breast ducts vs. lobules and clarify how these affect the interpretation of results in stem cell research. Lastly, we introduce a new elaboration of normal epithelial cell types in human breast and discuss how this provides a clinically useful basis for breast cancer classification.

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

DTIC Science & Technology

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

Development of an Automated Modality-Independent Elastographic Image Analysis System for Tumor Screening

DTIC Science & Technology

2006-02-01

further develop modality-independent elastography as a system that is able to reproducibly detect regions of increased stiffness within the breast based...tested on a tissue-like polymer phantom. elastography , breast cancer screening, image processing 16. SECURITY CLASSIFICATION OF: 17. LIMITATION...is a map of the breast (or other tissue of interest) that reflects material inhomogeneity, such as in the case of a tumor mass that disrupts the

Detection of lobular structures in normal breast tissue.

PubMed

Apou, Grégory; Schaadt, Nadine S; Naegel, Benoît; Forestier, Germain; Schönmeyer, Ralf; Feuerhake, Friedrich; Wemmert, Cédric; Grote, Anne

2016-07-01

Ongoing research into inflammatory conditions raises an increasing need to evaluate immune cells in histological sections in biologically relevant regions of interest (ROIs). Herein, we compare different approaches to automatically detect lobular structures in human normal breast tissue in digitized whole slide images (WSIs). This automation is required to perform objective and consistent quantitative studies on large data sets. In normal breast tissue from nine healthy patients immunohistochemically stained for different markers, we evaluated and compared three different image analysis methods to automatically detect lobular structures in WSIs: (1) a bottom-up approach using the cell-based data for subsequent tissue level classification, (2) a top-down method starting with texture classification at tissue level analysis of cell densities in specific ROIs, and (3) a direct texture classification using deep learning technology. All three methods result in comparable overall quality allowing automated detection of lobular structures with minor advantage in sensitivity (approach 3), specificity (approach 2), or processing time (approach 1). Combining the outputs of the approaches further improved the precision. Different approaches of automated ROI detection are feasible and should be selected according to the individual needs of biomarker research. Additionally, detected ROIs could be used as a basis for quantification of immune infiltration in lobular structures. Copyright © 2016 Elsevier Ltd. All rights reserved.

An iterative hyperelastic parameters reconstruction for breast cancer assessment

NASA Astrophysics Data System (ADS)

Mehrabian, Hatef; Samani, Abbas

2008-03-01

In breast elastography, breast tissues usually undergo large compressions resulting in significant geometric and structural changes, and consequently nonlinear mechanical behavior. In this study, an elastography technique is presented where parameters characterizing tissue nonlinear behavior is reconstructed. Such parameters can be used for tumor tissue classification. To model the nonlinear behavior, tissues are treated as hyperelastic materials. The proposed technique uses a constrained iterative inversion method to reconstruct the tissue hyperelastic parameters. The reconstruction technique uses a nonlinear finite element (FE) model for solving the forward problem. In this research, we applied Yeoh and Polynomial models to model the tissue hyperelasticity. To mimic the breast geometry, we used a computational phantom, which comprises of a hemisphere connected to a cylinder. This phantom consists of two types of soft tissue to mimic adipose and fibroglandular tissues and a tumor. Simulation results show the feasibility of the proposed method in reconstructing the hyperelastic parameters of the tumor tissue.

Program for Critical Technologies in Breast Oncology

DTIC Science & Technology

1999-07-01

the tissues, and in a ethical manner that respects the patients’ rights . The Program for Critical Technologies in Breast Oncology helps address all of...diagnosis, database 15. NUMBER OF PAGES 148 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF THIS...closer to clinical utility. Page 17 References Adida C. Crotty PL. McGrath J. Berrebi D. Diebold J. Altieri DC. Developmentally regulated

Automated adipose study for assessing cancerous human breast tissue using optical coherence tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

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

2017-02-01

Breast cancer is the third leading cause of death in women in the United States. In human breast tissue, adipose cells are infiltrated or replaced by cancer cells during the development of breast tumor. Therefore, an adipose map can be an indicator of identifying cancerous region. We developed an automated classification method to generate adipose map within human breast. To facilitate the automated classification, we first mask the B-scans from OCT volumes by comparing the signal noise ratio with a threshold. Then, the image was divided into multiple blocks with a size of 30 pixels by 30 pixels. In each block, we extracted texture features such as local standard deviation, entropy, homogeneity, and coarseness. The features of each block were input to a probabilistic model, relevance vector machine (RVM), which was trained prior to the experiment, to classify tissue types. For each block within the B-scan, RVM identified the region with adipose tissue. We calculated the adipose ratio as the number of blocks identified as adipose over the total number of blocks within the B-scan. We obtained OCT images from patients (n = 19) in Columbia medical center. We automatically generated the adipose maps from 24 B-scans including normal samples (n = 16) and cancerous samples (n = 8). We found the adipose regions show an isolated pattern that in cancerous tissue while a clustered pattern in normal tissue. Moreover, the adipose ratio (52.30 ± 29.42%) in normal tissue was higher than the that in cancerous tissue (12.41 ± 10.07%).

Classification of microscopic images of breast tissue

NASA Astrophysics Data System (ADS)

Ballerini, Lucia; Franzen, Lennart

2004-05-01

Breast cancer is the most common form of cancer among women. The diagnosis is usually performed by the pathologist, that subjectively evaluates tissue samples. The aim of our research is to develop techniques for the automatic classification of cancerous tissue, by analyzing histological samples of intact tissue taken with a biopsy. In our study, we considered 200 images presenting four different conditions: normal tissue, fibroadenosis, ductal cancer and lobular cancer. Methods to extract features have been investigated and described. One method is based on granulometries, which are size-shape descriptors widely used in mathematical morphology. Applications of granulometries lead to distribution functions whose moments are used as features. A second method is based on fractal geometry, that seems very suitable to quantify biological structures. The fractal dimension of binary images has been computed using the euclidean distance mapping. Image classification has then been performed using the extracted features as input of a back-propagation neural network. A new method that combines genetic algorithms and morphological filters has been also investigated. In this case, the classification is based on a correlation measure. Very encouraging results have been obtained with pilot experiments using a small subset of images as training set. Experimental results indicate the effectiveness of the proposed methods. Cancerous tissue was correctly classified in 92.5% of the cases.

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

PubMed

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 average accuracy of 95.38% was obtained. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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.

Inverse imaging of the breast with a material classification technique.

PubMed

Manry, C W; Broschat, S L

1998-03-01

In recent publications [Chew et al., IEEE Trans. Blomed. Eng. BME-9, 218-225 (1990); Borup et al., Ultrason. Imaging 14, 69-85 (1992)] the inverse imaging problem has been solved by means of a two-step iterative method. In this paper, a third step is introduced for ultrasound imaging of the breast. In this step, which is based on statistical pattern recognition, classification of tissue types and a priori knowledge of the anatomy of the breast are integrated into the iterative method. Use of this material classification technique results in more rapid convergence to the inverse solution--approximately 40% fewer iterations are required--as well as greater accuracy. In addition, tumors are detected early in the reconstruction process. Results for reconstructions of a simple two-dimensional model of the human breast are presented. These reconstructions are extremely accurate when system noise and variations in tissue parameters are not too great. However, for the algorithm used, degradation of the reconstructions and divergence from the correct solution occur when system noise and variations in parameters exceed threshold values. Even in this case, however, tumors are still identified within a few iterations.

Coded aperture coherent scatter spectral imaging for assessment of breast cancers: an ex-vivo demonstration

NASA Astrophysics Data System (ADS)

Spencer, James R.; Carter, Joshua E.; Leung, Crystal K.; McCall, Shannon J.; Greenberg, Joel A.; Kapadia, Anuj J.

2017-03-01

A Coded Aperture Coherent Scatter Spectral Imaging (CACSSI) system was developed in our group to differentiate cancer and healthy tissue in the breast. The utility of the experimental system was previously demonstrated using anthropomorphic breast phantoms and breast biopsy specimens. Here we demonstrate CACSSI utility in identifying tumor margins in real time using breast lumpectomy specimens. Fresh lumpectomy specimens were obtained from Surgical Pathology with the suspected cancerous area designated on the specimen. The specimens were scanned using CACSSI to obtain spectral scatter signatures at multiple locations within the tumor and surrounding tissue. The spectral reconstructions were matched with literature form-factors to classify the tissue as cancerous or non-cancerous. The findings were then compared against pathology reports to confirm the presence and location of the tumor. The system was found to be capable of consistently differentiating cancerous and healthy regions in the breast with spatial resolution of 5 mm. Tissue classification results from the scanned specimens could be correlated with pathology results. We now aim to develop CACSSI as a clinical imaging tool to aid breast cancer assessment and other diagnostic purposes.

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

PubMed

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.

Maastricht Delphi Consensus on Event Definitions for Classification of Recurrence in Breast Cancer Research

PubMed Central

van Roozendaal, Lori M.; Strobbe, Luc J. A.; Aebi, Stefan; Cameron, David A.; Dixon, J. Michael; Giuliano, Armando E.; Haffty, Bruce G.; Hickey, Brigid E.; Hudis, Clifford A.; Klimberg, V. Suzanne; Koczwara, Bogda; Kühn, Thorsten; Lippman, Marc E.; Lucci, Anthony; Piccart, Martine; Smith, Benjamin D.; Tjan-Heijnen, Vivianne C. G.; van de Velde, Cornelis J. H.; Van Zee, Kimberly J.; Vermorken, Jan B.; Viale, Giuseppe; Voogd, Adri C.; Wapnir, Irene L.; White, Julia R.; Smidt, Marjolein L.

2014-01-01

Background In breast cancer studies, many different endpoints are used. Definitions are often not provided or vary between studies. For instance, “local recurrence” may include different components in similar studies. This limits transparency and comparability of results. This project aimed to reach consensus on the definitions of local event, second primary breast cancer, regional and distant event for breast cancer studies. Methods The RAND-UCLA Appropriateness method (modified Delphi method) was used. A Consensus Group of international breast cancer experts was formed, including representatives of all involved clinical disciplines. Consensus was reached in two rounds of online questionnaires and one meeting. Results Twenty-four international breast cancer experts participated. Consensus was reached on 134 items in four categories. Local event is defined as any epithelial breast cancer or ductal carcinoma in situ (DCIS) in the ipsilateral breast, or skin and subcutaneous tissue on the ipsilateral thoracic wall. Second primary breast cancer is defined as epithelial breast cancer in the contralateral breast. Regional events are breast cancer in ipsilateral lymph nodes. A distant event is breast cancer in any other location. Therefore, this includes metastasis in contralateral lymph nodes and breast cancer involving the sternal bone. If feasible, tissue sampling of a first, solitary, lesion suspected for metastasis is highly recommended. Conclusion This project resulted in consensus-based event definitions for classification of recurrence in breast cancer research. Future breast cancer research projects should adopt these definitions to increase transparency. This should facilitate comparison of results and conducting reviews as well as meta-analysis. PMID:25381395

Tissue classification using depth-dependent ultrasound time series analysis: in-vitro animal study

NASA Astrophysics Data System (ADS)

Imani, Farhad; Daoud, Mohammad; Moradi, Mehdi; Abolmaesumi, Purang; Mousavi, Parvin

2011-03-01

Time series analysis of ultrasound radio-frequency (RF) signals has been shown to be an effective tissue classification method. Previous studies of this method for tissue differentiation at high and clinical-frequencies have been reported. In this paper, analysis of RF time series is extended to improve tissue classification at the clinical frequencies by including novel features extracted from the time series spectrum. The primary feature examined is the Mean Central Frequency (MCF) computed for regions of interest (ROIs) in the tissue extending along the axial axis of the transducer. In addition, the intercept and slope of a line fitted to the MCF-values of the RF time series as a function of depth have been included. To evaluate the accuracy of the new features, an in vitro animal study is performed using three tissue types: bovine muscle, bovine liver, and chicken breast, where perfect two-way classification is achieved. The results show statistically significant improvements over the classification accuracies with previously reported features.

Accurate Characterization of Benign and Cancerous Breast Tissues: Aspecific Patient Studies using Piezoresistive Microcantilevers

PubMed Central

PANDYA, HARDIK J.; ROY, RAJARSHI; CHEN, WENJIN; CHEKMAREVA, MARINA A.; FORAN, DAVID J.; DESAI, JAYDEV P.

2014-01-01

Breast cancer is the largest detected cancer amongst women in the US. In this work, our team reports on the development of piezoresistive microcantilevers (PMCs) to investigate their potential use in the accurate detection and characterization of benign and diseased breast tissues by performing indentations on the micro-scale tissue specimens. The PMCs used in these experiments have been fabricated using laboratory-made silicon-on-insulator (SOI) substrate, which significantly reduces the fabrication costs. The PMCs are 260 μm long, 35 μm wide and 2 μm thick with resistivity of order 1.316 X 10−3 Ω-cm obtained by using boron diffusion technique. For indenting the tissue, we utilized 8 μm thick cylindrical SU-8 tip. The PMC was calibrated against a known AFM probe. Breast tissue cores from seven different specimens were indented using PMC to identify benign and cancerous tissue cores. Furthermore, field emission scanning electron microscopy (FE-SEM) of benign and cancerous specimens showed marked differences in the tissue morphology, which further validates our observed experimental data with the PMCs. While these patient aspecific feasibility studies clearly demonstrate the ability to discriminate between benign and cancerous breast tissues, further investigation is necessary to perform automated mechano-phenotyping (classification) of breast cancer: from onset to disease progression. PMID:25128621

Prognostic Significance of Telomere Attrition in Ductal Carcinoma in Situ of the Breast

DTIC Science & Technology

2007-02-01

DCIS tissues, (ii) TC is associated with tumor stage and (iii) TC in DCIS is associated with breast cancer -free survival. 15. SUBJECT TERMS Ductal...carcinoma in situ (DCIS), breast cancer , telomeres, prognosis, genomic instability 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18...DCIS who eventually progress to invasive breast cancer is small (4-6). A Danish autopsy study found that 25% of women had in situ carcinomas

Automated breast tissue density assessment using high order regional texture descriptors in mammography

NASA Astrophysics Data System (ADS)

Law, Yan Nei; Lieng, Monica Keiko; Li, Jingmei; Khoo, David Aik-Aun

2014-03-01

Breast cancer is the most common cancer and second leading cause of cancer death among women in the US. The relative survival rate is lower among women with a more advanced stage at diagnosis. Early detection through screening is vital. Mammography is the most widely used and only proven screening method for reliably and effectively detecting abnormal breast tissues. In particular, mammographic density is one of the strongest breast cancer risk factors, after age and gender, and can be used to assess the future risk of disease before individuals become symptomatic. A reliable method for automatic density assessment would be beneficial and could assist radiologists in the evaluation of mammograms. To address this problem, we propose a density classification method which uses statistical features from different parts of the breast. Our method is composed of three parts: breast region identification, feature extraction and building ensemble classifiers for density assessment. It explores the potential of the features extracted from second and higher order statistical information for mammographic density classification. We further investigate the registration of bilateral pairs and time-series of mammograms. The experimental results on 322 mammograms demonstrate that (1) a classifier using features from dense regions has higher discriminative power than a classifier using only features from the whole breast region; (2) these high-order features can be effectively combined to boost the classification accuracy; (3) a classifier using these statistical features from dense regions achieves 75% accuracy, which is a significant improvement from 70% accuracy obtained by the existing approaches.

Automated modification and fusion of voxel models to construct body phantoms with heterogeneous breast tissue: Application to MRI simulations.

PubMed

Rispoli, Joseph V; Wright, Steven M; Malloy, Craig R; McDougall, Mary P

2017-01-01

Human voxel models incorporating detailed anatomical features are vital tools for the computational evaluation of electromagnetic (EM) fields within the body. Besides whole-body human voxel models, phantoms representing smaller heterogeneous anatomical features are often employed; for example, localized breast voxel models incorporating fatty and fibroglandular tissues have been developed for a variety of EM applications including mammography simulation and dosimetry, magnetic resonance imaging (MRI), and ultra-wideband microwave imaging. However, considering wavelength effects, electromagnetic modeling of the breast at sub-microwave frequencies necessitates detailed breast phantoms in conjunction with whole-body voxel models. Heterogeneous breast phantoms are sized to fit within radiofrequency coil hardware, modified by voxel-wise extrusion, and fused to whole-body models using voxel-wise, tissue-dependent logical operators. To illustrate the utility of this method, finite-difference time-domain simulations are performed using a whole-body model integrated with a variety of available breast phantoms spanning the standard four tissue density classifications representing the majority of the population. The software library uses a combination of voxel operations to seamlessly size, modify, and fuse eleven breast phantoms to whole-body voxel models. The software is publicly available on GitHub and is linked to the file exchange at MATLAB ® Central. Simulations confirm the proportions of fatty and fibroglandular tissues in breast phantoms have significant yet predictable implications on projected power deposition in tissue. Breast phantoms may be modified and fused to whole-body voxel models using the software presented in this work; user considerations for the open-source software and resultant phantoms are discussed. Furthermore, results indicate simulating breast models as predominantly fatty tissue can considerably underestimate the potential for tissue heating in women with substantial fibroglandular tissue.

Automated modification and fusion of voxel models to construct body phantoms with heterogeneous breast tissue: Application to MRI simulations

PubMed Central

Rispoli, Joseph V.; Wright, Steven M.; Malloy, Craig R.; McDougall, Mary P.

2017-01-01

Background Human voxel models incorporating detailed anatomical features are vital tools for the computational evaluation of electromagnetic (EM) fields within the body. Besides whole-body human voxel models, phantoms representing smaller heterogeneous anatomical features are often employed; for example, localized breast voxel models incorporating fatty and fibroglandular tissues have been developed for a variety of EM applications including mammography simulation and dosimetry, magnetic resonance imaging (MRI), and ultra-wideband microwave imaging. However, considering wavelength effects, electromagnetic modeling of the breast at sub-microwave frequencies necessitates detailed breast phantoms in conjunction with whole-body voxel models. Methods Heterogeneous breast phantoms are sized to fit within radiofrequency coil hardware, modified by voxel-wise extrusion, and fused to whole-body models using voxel-wise, tissue-dependent logical operators. To illustrate the utility of this method, finite-difference time-domain simulations are performed using a whole-body model integrated with a variety of available breast phantoms spanning the standard four tissue density classifications representing the majority of the population. Results The software library uses a combination of voxel operations to seamlessly size, modify, and fuse eleven breast phantoms to whole-body voxel models. The software is publicly available on GitHub and is linked to the file exchange at MATLAB® Central. Simulations confirm the proportions of fatty and fibroglandular tissues in breast phantoms have significant yet predictable implications on projected power deposition in tissue. Conclusions Breast phantoms may be modified and fused to whole-body voxel models using the software presented in this work; user considerations for the open-source software and resultant phantoms are discussed. Furthermore, results indicate simulating breast models as predominantly fatty tissue can considerably underestimate the potential for tissue heating in women with substantial fibroglandular tissue. PMID:28798837

A novel approach for detection and classification of mammographic microcalcifications using wavelet analysis and extreme learning machine.

PubMed

Malar, E; Kandaswamy, A; Chakravarthy, D; Giri Dharan, A

2012-09-01

The objective of this paper is to reveal the effectiveness of wavelet based tissue texture analysis for microcalcification detection in digitized mammograms using Extreme Learning Machine (ELM). Microcalcifications are tiny deposits of calcium in the breast tissue which are potential indicators for early detection of breast cancer. The dense nature of the breast tissue and the poor contrast of the mammogram image prohibit the effectiveness in identifying microcalcifications. Hence, a new approach to discriminate the microcalcifications from the normal tissue is done using wavelet features and is compared with different feature vectors extracted using Gray Level Spatial Dependence Matrix (GLSDM) and Gabor filter based techniques. A total of 120 Region of Interests (ROIs) extracted from 55 mammogram images of mini-Mias database, including normal and microcalcification images are used in the current research. The network is trained with the above mentioned features and the results denote that ELM produces relatively better classification accuracy (94%) with a significant reduction in training time than the other artificial neural networks like Bayesnet classifier, Naivebayes classifier, and Support Vector Machine. ELM also avoids problems like local minima, improper learning rate, and over fitting. Copyright © 2012 Elsevier Ltd. All rights reserved.

Accuracy assessment and characterization of x-ray coded aperture coherent scatter spectral imaging for breast cancer classification

PubMed Central

Lakshmanan, Manu N.; Greenberg, Joel A.; Samei, Ehsan; Kapadia, Anuj J.

2017-01-01

Abstract. Although transmission-based x-ray imaging is the most commonly used imaging approach for breast cancer detection, it exhibits false negative rates higher than 15%. To improve cancer detection accuracy, x-ray coherent scatter computed tomography (CSCT) has been explored to potentially detect cancer with greater consistency. However, the 10-min scan duration of CSCT limits its possible clinical applications. The coded aperture coherent scatter spectral imaging (CACSSI) technique has been shown to reduce scan time through enabling single-angle imaging while providing high detection accuracy. Here, we use Monte Carlo simulations to test analytical optimization studies of the CACSSI technique, specifically for detecting cancer in ex vivo breast samples. An anthropomorphic breast tissue phantom was modeled, a CACSSI imaging system was virtually simulated to image the phantom, a diagnostic voxel classification algorithm was applied to all reconstructed voxels in the phantom, and receiver-operator characteristics analysis of the voxel classification was used to evaluate and characterize the imaging system for a range of parameters that have been optimized in a prior analytical study. The results indicate that CACSSI is able to identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) in tissue samples with a cancerous voxel identification area-under-the-curve of 0.94 through a scan lasting less than 10 s per slice. These results show that coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue within ex vivo samples. Furthermore, the results indicate potential CACSSI imaging system configurations for implementation in subsequent imaging development studies. PMID:28331884

Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples

PubMed Central

Lakshmanan, Manu N.; Greenberg, Joel A.; Samei, Ehsan; Kapadia, Anuj J.

2016-01-01

Abstract. A scatter imaging technique for the differentiation of cancerous and healthy breast tissue in a heterogeneous sample is introduced in this work. Such a technique has potential utility in intraoperative margin assessment during lumpectomy procedures. In this work, we investigate the feasibility of the imaging method for tumor classification using Monte Carlo simulations and physical experiments. The coded aperture coherent scatter spectral imaging technique was used to reconstruct three-dimensional (3-D) images of breast tissue samples acquired through a single-position snapshot acquisition, without rotation as is required in coherent scatter computed tomography. We perform a quantitative assessment of the accuracy of the cancerous voxel classification using Monte Carlo simulations of the imaging system; describe our experimental implementation of coded aperture scatter imaging; show the reconstructed images of the breast tissue samples; and present segmentations of the 3-D images in order to identify the cancerous and healthy tissue in the samples. From the Monte Carlo simulations, we find that coded aperture scatter imaging is able to reconstruct images of the samples and identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) inside them with a cancerous voxel identification sensitivity, specificity, and accuracy of 92.4%, 91.9%, and 92.0%, respectively. From the experimental results, we find that the technique is able to identify cancerous and healthy tissue samples and reconstruct differential coherent scatter cross sections that are highly correlated with those measured by other groups using x-ray diffraction. Coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue inside samples within a time on the order of a minute per slice. PMID:26962543

Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples.

PubMed

Lakshmanan, Manu N; Greenberg, Joel A; Samei, Ehsan; Kapadia, Anuj J

2016-01-01

A scatter imaging technique for the differentiation of cancerous and healthy breast tissue in a heterogeneous sample is introduced in this work. Such a technique has potential utility in intraoperative margin assessment during lumpectomy procedures. In this work, we investigate the feasibility of the imaging method for tumor classification using Monte Carlo simulations and physical experiments. The coded aperture coherent scatter spectral imaging technique was used to reconstruct three-dimensional (3-D) images of breast tissue samples acquired through a single-position snapshot acquisition, without rotation as is required in coherent scatter computed tomography. We perform a quantitative assessment of the accuracy of the cancerous voxel classification using Monte Carlo simulations of the imaging system; describe our experimental implementation of coded aperture scatter imaging; show the reconstructed images of the breast tissue samples; and present segmentations of the 3-D images in order to identify the cancerous and healthy tissue in the samples. From the Monte Carlo simulations, we find that coded aperture scatter imaging is able to reconstruct images of the samples and identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) inside them with a cancerous voxel identification sensitivity, specificity, and accuracy of 92.4%, 91.9%, and 92.0%, respectively. From the experimental results, we find that the technique is able to identify cancerous and healthy tissue samples and reconstruct differential coherent scatter cross sections that are highly correlated with those measured by other groups using x-ray diffraction. Coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue inside samples within a time on the order of a minute per slice.

Visualization of suspicious lesions in breast MRI based on intelligent neural systems

NASA Astrophysics Data System (ADS)

Twellmann, Thorsten; Lange, Oliver; Nattkemper, Tim Wilhelm; Meyer-Bäse, Anke

2006-05-01

Intelligent medical systems based on supervised and unsupervised artificial neural networks are applied to the automatic visualization and classification of suspicious lesions in breast MRI. These systems represent an important component of future sophisticated computer-aided diagnosis systems and enable the extraction of spatial and temporal features of dynamic MRI data stemming from patients with confirmed lesion diagnosis. By taking into account the heterogenity of the cancerous tissue, these techniques reveal the malignant, benign and normal kinetic signals and and provide a regional subclassification of pathological breast tissue. Intelligent medical systems are expected to have substantial implications in healthcare politics by contributing to the diagnosis of indeterminate breast lesions by non-invasive imaging.

Towards intra-operative diagnosis of tumours during breast conserving surgery by selective-sampling Raman micro-spectroscopy

NASA Astrophysics Data System (ADS)

Kong, Kenny; Zaabar, Fazliyana; Rakha, Emad; Ellis, Ian; Koloydenko, Alexey; Notingher, Ioan

2014-10-01

Breast-conserving surgery (BCS) is increasingly employed for the treatment of early stage breast cancer. One of the key challenges in BCS is to ensure complete removal of the tumour while conserving as much healthy tissue as possible. In this study we have investigated the potential of Raman micro-spectroscopy (RMS) for automated intra-operative evaluation of tumour excision. First, a multivariate classification model based on Raman spectra of normal and malignant breast tissue samples was built and achieved diagnosis of mammary ductal carcinoma (DC) with 95.6% sensitivity and 96.2% specificity (5-fold cross-validation). The tumour regions were discriminated from the healthy tissue structures based on increased concentration of nucleic acids and reduced concentration of collagen and fat. The multivariate classification model was then applied to sections from fresh tissue of new patients to produce diagnosis images for DC. The diagnosis images obtained by raster scanning RMS were in agreement with the conventional histopathology diagnosis but were limited to long data acquisition times (typically 10 000 spectra mm-2, which is equivalent to ~5 h mm-2). Selective-sampling based on integrated auto-fluorescence imaging and Raman spectroscopy was used to reduce the number of Raman spectra to ~20 spectra mm-2, which is equivalent to an acquisition time of ~15 min for 5 × 5 mm2 tissue samples. This study suggests that selective-sampling Raman microscopy has the potential to provide a rapid and objective intra-operative method to detect mammary carcinoma in tissue and assess resection margins.

MO-F-CAMPUS-I-03: Tissue Equivalent Material Phantom to Test and Optimize Coherent Scatter Imaging for Tumor Classification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albanese, K; Morris, R; Lakshmanan, M

Purpose: To accurately model different breast geometries using a tissue equivalent phantom, and to classify these tissues in a coherent x-ray scatter imaging system. Methods: A breast phantom has been designed to assess the capability of coded aperture coherent x-ray scatter imaging system to classify different types of breast tissue (adipose, fibroglandular, tumor). The tissue-equivalent phantom was modeled as a hollow plastic cylinder containing multiple cylindrical and spherical inserts that can be positioned, rearranged, or removed to model different breast geometries. Each enclosure can be filled with a tissue-equivalent material and excised human tumors. In this study, beef and lard,more » placed inside 2-mm diameter plastic Nalgene containers, were used as surrogates for fibroglandular and adipose tissue, respectively. The phantom was imaged at 125 kVp, 40 mA for 10 seconds each with a 1-mm pencil beam. The raw data were reconstructed using a model-based reconstruction algorithm and yielded the location and form factor, or momentum transfer (q) spectrum of the materials that were imaged. The measured material form factors were then compared to the ground truth measurements acquired by x-ray diffraction (XRD) imaging. Results: The tissue equivalent phantom was found to accurately model different types of breast tissue by qualitatively comparing our measured form factors to those of adipose and fibroglandular tissue from literature. Our imaging system has been able to define the location and composition of the various materials in the phantom. Conclusion: This work introduces a new tissue equivalent phantom for testing and optimization of our coherent scatter imaging system for material classification. In future studies, the phantom will enable the use of a variety of materials including excised human tissue specimens in evaluating and optimizing our imaging system using pencil- and fan-beam geometries. United States Department of Homeland Security Duke University Medical Center - Department of Radiology Carl E Ravin Advanced Imaging Laboratories Duke University Medical Physics Graduate Program.« less

Classification of mass and normal breast tissue: A convolution neural network classifier with spatial domain and texture images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sahiner, B.; Chan, H.P.; Petrick, N.

1996-10-01

The authors investigated the classification of regions of interest (ROI`s) on mammograms as either mass or normal tissue using a convolution neural network (CNN). A CNN is a back-propagation neural network with two-dimensional (2-D) weight kernels that operate on images. A generalized, fast and stable implementation of the CNN was developed. The input images to the CNN were obtained form the ROI`s using two techniques. The first technique employed averaging and subsampling. The second technique employed texture feature extraction methods applied to small subregions inside the ROI. Features computed over different subregions were arranged as texture images, which were subsequentlymore » used as CNN inputs. The effects of CNN architecture and texture feature parameters on classification accuracy were studied. Receiver operating characteristic (ROC) methodology was used to evaluate the classification accuracy. A data set consisting of 168 ROI`s containing biopsy-proven masses and 504 ROI`s containing normal breast tissue was extracted from 168 mammograms by radiologists experienced in mammography. This data set was used for training and testing the CNN. With the best combination of CNN architecture and texture feature parameters, the area under the test ROC curve reached 0.87, which corresponded to a true-positive fraction of 90% at a false positive fraction of 31%. The results demonstrate the feasibility of using a CNN for classification of masses and normal tissue on mammograms.« less

Biophysical interpretation and ex-vivo characterization of scattered light from tumor-associated breast stroma

NASA Astrophysics Data System (ADS)

Laughney, Ashley; Krishnaswamy, Venkat; Schwab, Mary; Wells, Wendy A.; Paulsen, Keith D.; Pogue, Brian W.

2009-02-01

The purpose of this study was to extract scatter parameters related to tissue ultra-structures from freshly excised breast tissue and to assess whether evident changes in scatter across diagnostic categories is primarily influenced by variation in the composition of each tissues subtypes or by physical remodeling of the extra-cellular environment. Pathologists easily distinguish between epithelium, stroma and adipose tissues, so this classification was adopted for macroscopic subtype classification. Micro-sampling reflectance spectroscopy was used to characterize single-backscattered photons from fresh, excised tumors and normal reduction specimens with sub-millimeter resolution. Phase contrast microscopy (sub-micron resolution) was used to characterize forward-scattered light through frozen tissue from the DHMC Tissue Bank, representing normal, benign and malignant breast tissue, sectioned at 10 microns. The packing density and orientation of collagen fibers in the extracellular matrix (ECM) associated with invasive, normal and benign epithelium was evaluated using transmission electron microscopy (TEM). Regions of interest (ROIs) in the H&E stained tissues were identified for analysis, as outlined by a pathologist as the gold standard. We conclude that the scatter parameters associated with tumor specimens (Npatients=6, Nspecimens=13) significantly differs from that of normal reductions (Npatients=6, Nspecimens=10). Further, tissue subtypes may be identified by their scatter spectra at sub-micron resolution. Stromal tissue scatters significantly more than the epithelial cells embedded in its ECM and adipose tissue scatters much less. However, the scatter signature of the stroma at the sub-micron level is not particularly differentiating in terms of a diagnosis.

A constrained reconstruction technique of hyperelasticity parameters for breast cancer assessment

NASA Astrophysics Data System (ADS)

Mehrabian, Hatef; Campbell, Gordon; Samani, Abbas

2010-12-01

In breast elastography, breast tissue usually undergoes large compression resulting in significant geometric and structural changes. This implies that breast elastography is associated with tissue nonlinear behavior. In this study, an elastography technique is presented and an inverse problem formulation is proposed to reconstruct parameters characterizing tissue hyperelasticity. Such parameters can potentially be used for tumor classification. This technique can also have other important clinical applications such as measuring normal tissue hyperelastic parameters in vivo. Such parameters are essential in planning and conducting computer-aided interventional procedures. The proposed parameter reconstruction technique uses a constrained iterative inversion; it can be viewed as an inverse problem. To solve this problem, we used a nonlinear finite element model corresponding to its forward problem. In this research, we applied Veronda-Westmann, Yeoh and polynomial models to model tissue hyperelasticity. To validate the proposed technique, we conducted studies involving numerical and tissue-mimicking phantoms. The numerical phantom consisted of a hemisphere connected to a cylinder, while we constructed the tissue-mimicking phantom from polyvinyl alcohol with freeze-thaw cycles that exhibits nonlinear mechanical behavior. Both phantoms consisted of three types of soft tissues which mimic adipose, fibroglandular tissue and a tumor. The results of the simulations and experiments show feasibility of accurate reconstruction of tumor tissue hyperelastic parameters using the proposed method. In the numerical phantom, all hyperelastic parameters corresponding to the three models were reconstructed with less than 2% error. With the tissue-mimicking phantom, we were able to reconstruct the ratio of the hyperelastic parameters reasonably accurately. Compared to the uniaxial test results, the average error of the ratios of the parameters reconstructed for inclusion to the middle and external layers were 13% and 9.6%, respectively. Given that the parameter ratios of the abnormal tissues to the normal ones range from three times to more than ten times, this accuracy is sufficient for tumor classification.

Prevalence of Ectopic Breast Tissue and Tumor: A 20-Year Single Center Experience.

PubMed

Famá, Fausto; Cicciú, Marco; Sindoni, Alessandro; Scarfó, Paola; Pollicino, Andrea; Giacobbe, Giuseppa; Buccheri, Giancarlo; Taranto, Filippo; Palella, Jessica; Gioffré-Florio, Maria

2016-08-01

Ectopic breast tissue, which includes both supernumerary breast and aberrant breast tissue, is the most common congenital breast abnormality. Ectopic breast cancers are rare neoplasms that occur in 0.3% to 0.6% of all cases of breast cancer. We retrospectively report, using a large series of breast abnormalities diagnosed and treated, our clinical experience on the management of the ectopic breast cancer. In 2 decades, we observed 327 (2.7%) patients with ectopic breast tissue out of a total of 12,177 subjects undergoing a breast visit for lesions. All patients were classified into 8 classes, according to the classification of Kajava, and assessed by a physician examination, ultrasounds, and, when appropriate, further studies with fine needle aspiration cytology and mammography. All specimens were submitted to the anatomo-pathologist. The most frequent benign histological diagnosis was fibrocystic disease. A rare granulosa cell tumor was also found in the right anterior thoracic wall of 1 patient. Four malignancies were also diagnosed in 4 women: an infiltrating lobular cancer in 1 patient with a lesion classified as class I, and an infiltrating apocrine carcinoma, an infiltrating ductal cancer, and an infiltrating ductal cancer with tubular pattern, occurring in 3 patients with lesions classified as class IV. Only 1 recurrence was observed. We recommend an earlier surgical approach for patients with lesions from class I to IV. Copyright © 2016 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

Classification of breast abnormalities using artificial neural network

NASA Astrophysics Data System (ADS)

Zaman, Nur Atiqah Kamarul; Rahman, Wan Eny Zarina Wan Abdul; Jumaat, Abdul Kadir; Yasiran, Siti Salmah

2015-05-01

Classification is the process of recognition, differentiation and categorizing objects into groups. Breast abnormalities are calcifications which are tumor markers that indicate the presence of cancer in the breast. The aims of this research are to classify the types of breast abnormalities using artificial neural network (ANN) classifier and to evaluate the accuracy performance using receiver operating characteristics (ROC) curve. The methods used in this research are ANN for breast abnormalities classifications and Canny edge detector as a feature extraction method. Previously the ANN classifier provides only the number of benign and malignant cases without providing information for specific cases. However in this research, the type of abnormality for each image can be obtained. The existing MIAS MiniMammographic database classified the mammogram images into three features only namely characteristic of background tissues, class of abnormality and radius of abnormality. However, in this research three other features are added-in. These three features are number of spots, area and shape of abnormalities. Lastly the performance of the ANN classifier is evaluated using ROC curve. It is found that ANN has an accuracy of 97.9% which is considered acceptable.

Mammographic phenotypes of breast cancer risk driven by breast anatomy

NASA Astrophysics Data System (ADS)

Gastounioti, Aimilia; Oustimov, Andrew; Hsieh, Meng-Kang; Pantalone, Lauren; Conant, Emily F.; Kontos, Despina

2017-03-01

Image-derived features of breast parenchymal texture patterns have emerged as promising risk factors for breast cancer, paving the way towards personalized recommendations regarding women's cancer risk evaluation and screening. The main steps to extract texture features of the breast parenchyma are the selection of regions of interest (ROIs) where texture analysis is performed, the texture feature calculation and the texture feature summarization in case of multiple ROIs. In this study, we incorporate breast anatomy in these three key steps by (a) introducing breast anatomical sampling for the definition of ROIs, (b) texture feature calculation aligned with the structure of the breast and (c) weighted texture feature summarization considering the spatial position and the underlying tissue composition of each ROI. We systematically optimize this novel framework for parenchymal tissue characterization in a case-control study with digital mammograms from 424 women. We also compare the proposed approach with a conventional methodology, not considering breast anatomy, recently shown to enhance the case-control discriminatory capacity of parenchymal texture analysis. The case-control classification performance is assessed using elastic-net regression with 5-fold cross validation, where the evaluation measure is the area under the curve (AUC) of the receiver operating characteristic. Upon optimization, the proposed breast-anatomy-driven approach demonstrated a promising case-control classification performance (AUC=0.87). In the same dataset, the performance of conventional texture characterization was found to be significantly lower (AUC=0.80, DeLong's test p-value<0.05). Our results suggest that breast anatomy may further leverage the associations of parenchymal texture features with breast cancer, and may therefore be a valuable addition in pipelines aiming to elucidate quantitative mammographic phenotypes of breast cancer risk.

Detection of mass regions in mammograms by bilateral analysis adapted to breast density using similarity indexes and convolutional neural networks.

PubMed

Bandeira Diniz, João Otávio; Bandeira Diniz, Pedro Henrique; Azevedo Valente, Thales Levi; Corrêa Silva, Aristófanes; de Paiva, Anselmo Cardoso; Gattass, Marcelo

2018-03-01

The processing of medical image is an important tool to assist in minimizing the degree of uncertainty of the specialist, while providing specialists with an additional source of detect and diagnosis information. Breast cancer is the most common type of cancer that affects the female population around the world. It is also the most deadly type of cancer among women. It is the second most common type of cancer among all others. The most common examination to diagnose breast cancer early is mammography. In the last decades, computational techniques have been developed with the purpose of automatically detecting structures that maybe associated with tumors in mammography examination. This work presents a computational methodology to automatically detection of mass regions in mammography by using a convolutional neural network. The materials used in this work is the DDSM database. The method proposed consists of two phases: training phase and test phase. The training phase has 2 main steps: (1) create a model to classify breast tissue into dense and non-dense (2) create a model to classify regions of breast into mass and non-mass. The test phase has 7 step: (1) preprocessing; (2) registration; (3) segmentation; (4) first reduction of false positives; (5) preprocessing of regions segmented; (6) density tissue classification (7) second reduction of false positives where regions will be classified into mass and non-mass. The proposed method achieved 95.6% of accuracy in classify non-dense breasts tissue and 97,72% accuracy in classify dense breasts. To detect regions of mass in non-dense breast, the method achieved a sensitivity value of 91.5%, and specificity value of 90.7%, with 91% accuracy. To detect regions in dense breasts, our method achieved 90.4% of sensitivity and 96.4% of specificity, with accuracy of 94.8%. According to the results achieved by CNN, we demonstrate the feasibility of using convolutional neural networks on medical image processing techniques for classification of breast tissue and mass detection. Copyright © 2018 Elsevier B.V. All rights reserved.

Analysis of classifiers performance for classification of potential microcalcification

NASA Astrophysics Data System (ADS)

M. N., Arun K.; Sheshadri, H. S.

2013-07-01

Breast cancer is a significant public health problem in the world. According to the literature early detection improve breast cancer prognosis. Mammography is a screening tool used for early detection of breast cancer. About 10-30% cases are missed during the routine check as it is difficult for the radiologists to make accurate analysis due to large amount of data. The Microcalcifications (MCs) are considered to be important signs of breast cancer. It has been reported in literature that 30% - 50% of breast cancer detected radio graphically show MCs on mammograms. Histologic examinations report 62% to 79% of breast carcinomas reveals MCs. MC are tiny, vary in size, shape, and distribution, and MC may be closely connected to surrounding tissues. There is a major challenge using the traditional classifiers in the classification of individual potential MCs as the processing of mammograms in appropriate stage generates data sets with an unequal amount of information for both classes (i.e., MC, and Not-MC). Most of the existing state-of-the-art classification approaches are well developed by assuming the underlying training set is evenly distributed. However, they are faced with a severe bias problem when the training set is highly imbalanced in distribution. This paper addresses this issue by using classifiers which handle the imbalanced data sets. In this paper, we also compare the performance of classifiers which are used in the classification of potential MC.

Foundation and methodologies in computer-aided diagnosis systems for breast cancer detection.

PubMed

Jalalian, Afsaneh; Mashohor, Syamsiah; Mahmud, Rozi; Karasfi, Babak; Saripan, M Iqbal B; Ramli, Abdul Rahman B

2017-01-01

Breast cancer is the most prevalent cancer that affects women all over the world. Early detection and treatment of breast cancer could decline the mortality rate. Some issues such as technical reasons, which related to imaging quality and human error, increase misdiagnosis of breast cancer by radiologists. Computer-aided detection systems (CADs) are developed to overcome these restrictions and have been studied in many imaging modalities for breast cancer detection in recent years. The CAD systems improve radiologists' performance in finding and discriminating between the normal and abnormal tissues. These procedures are performed only as a double reader but the absolute decisions are still made by the radiologist. In this study, the recent CAD systems for breast cancer detection on different modalities such as mammography, ultrasound, MRI, and biopsy histopathological images are introduced. The foundation of CAD systems generally consist of four stages: Pre-processing, Segmentation, Feature extraction, and Classification. The approaches which applied to design different stages of CAD system are summarised. Advantages and disadvantages of different segmentation, feature extraction and classification techniques are listed. In addition, the impact of imbalanced datasets in classification outcomes and appropriate methods to solve these issues are discussed. As well as, performance evaluation metrics for various stages of breast cancer detection CAD systems are reviewed.

Foundation and methodologies in computer-aided diagnosis systems for breast cancer detection

PubMed Central

Jalalian, Afsaneh; Mashohor, Syamsiah; Mahmud, Rozi; Karasfi, Babak; Saripan, M. Iqbal B.; Ramli, Abdul Rahman B.

2017-01-01

Breast cancer is the most prevalent cancer that affects women all over the world. Early detection and treatment of breast cancer could decline the mortality rate. Some issues such as technical reasons, which related to imaging quality and human error, increase misdiagnosis of breast cancer by radiologists. Computer-aided detection systems (CADs) are developed to overcome these restrictions and have been studied in many imaging modalities for breast cancer detection in recent years. The CAD systems improve radiologists' performance in finding and discriminating between the normal and abnormal tissues. These procedures are performed only as a double reader but the absolute decisions are still made by the radiologist. In this study, the recent CAD systems for breast cancer detection on different modalities such as mammography, ultrasound, MRI, and biopsy histopathological images are introduced. The foundation of CAD systems generally consist of four stages: Pre-processing, Segmentation, Feature extraction, and Classification. The approaches which applied to design different stages of CAD system are summarised. Advantages and disadvantages of different segmentation, feature extraction and classification techniques are listed. In addition, the impact of imbalanced datasets in classification outcomes and appropriate methods to solve these issues are discussed. As well as, performance evaluation metrics for various stages of breast cancer detection CAD systems are reviewed. PMID:28435432

Comparison of Clinical and Automated Breast Density Measurements: Implications for Risk Prediction and Supplemental Screening

PubMed Central

Brandt, Kathleen R.; Scott, Christopher G.; Ma, Lin; Mahmoudzadeh, Amir P.; Jensen, Matthew R.; Whaley, Dana H.; Wu, Fang Fang; Malkov, Serghei; Hruska, Carrie B.; Norman, Aaron D.; Heine, John; Shepherd, John; Pankratz, V. Shane; Kerlikowske, Karla

2016-01-01

Purpose To compare the classification of breast density with two automated methods, Volpara (version 1.5.0; Matakina Technology, Wellington, New Zealand) and Quantra (version 2.0; Hologic, Bedford, Mass), with clinical Breast Imaging Reporting and Data System (BI-RADS) density classifications and to examine associations of these measures with breast cancer risk. Materials and Methods In this study, 1911 patients with breast cancer and 4170 control subjects matched for age, race, examination date, and mammography machine were evaluated. Participants underwent mammography at Mayo Clinic or one of four sites within the San Francisco Mammography Registry between 2006 and 2012 and provided informed consent or a waiver for research, in compliance with HIPAA regulations and institutional review board approval. Digital mammograms were retrieved a mean of 2.1 years (range, 6 months to 6 years) before cancer diagnosis, with the corresponding clinical BI-RADS density classifications, and Volpara and Quantra density estimates were generated. Agreement was assessed with weighted κ statistics among control subjects. Breast cancer associations were evaluated with conditional logistic regression, adjusted for age and body mass index. Odds ratios, C statistics, and 95% confidence intervals (CIs) were estimated. Results Agreement between clinical BI-RADS density classifications and Volpara and Quantra BI-RADS estimates was moderate, with κ values of 0.57 (95% CI: 0.55, 0.59) and 0.46 (95% CI: 0.44, 0.47), respectively. Differences of up to 14% in dense tissue classification were found, with Volpara classifying 51% of women as having dense breasts, Quantra classifying 37%, and clinical BI-RADS assessment used to classify 43%. Clinical and automated measures showed similar breast cancer associations; odds ratios for extremely dense breasts versus scattered fibroglandular densities were 1.8 (95% CI: 1.5, 2.2), 1.9 (95% CI: 1.5, 2.5), and 2.3 (95% CI: 1.9, 2.8) for Volpara, Quantra, and BI-RADS classifications, respectively. Clinical BI-RADS assessment showed better discrimination of case status (C = 0.60; 95% CI: 0.58, 0.61) than did Volpara (C = 0.58; 95% CI: 0.56, 0.59) and Quantra (C = 0.56; 95% CI: 0.54, 0.58) BI-RADS classifications. Conclusion Automated and clinical assessments of breast density are similarly associated with breast cancer risk but differ up to 14% in the classification of women with dense breasts. This could have substantial effects on clinical practice patterns. © RSNA, 2015 Online supplemental material is available for this article. PMID:26694052

Quantifying heterogeneity of lesion uptake in dynamic contrast enhanced MRI for breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Karahaliou, A.; Vassiou, K.; Skiadopoulos, S.; Kanavou, T.; Yiakoumelos, A.; Costaridou, L.

2009-07-01

The current study investigates whether texture features extracted from lesion kinetics feature maps can be used for breast cancer diagnosis. Fifty five women with 57 breast lesions (27 benign, 30 malignant) were subjected to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on 1.5T system. A linear-slope model was fitted pixel-wise to a representative lesion slice time series and fitted parameters were used to create three kinetic maps (wash out, time to peak enhancement and peak enhancement). 28 grey level co-occurrence matrices features were extracted from each lesion kinetic map. The ability of texture features per map in discriminating malignant from benign lesions was investigated using a Probabilistic Neural Network classifier. Additional classification was performed by combining classification outputs of most discriminating feature subsets from the three maps, via majority voting. The combined scheme outperformed classification based on individual maps achieving area under Receiver Operating Characteristics curve 0.960±0.029. Results suggest that heterogeneity of breast lesion kinetics, as quantified by texture analysis, may contribute to computer assisted tissue characterization in DCE-MRI.

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

PubMed

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.

Grouped fuzzy SVM with EM-based partition of sample space for clustered microcalcification detection.

PubMed

Wang, Huiya; Feng, Jun; Wang, Hongyu

2017-07-20

Detection of clustered microcalcification (MC) from mammograms plays essential roles in computer-aided diagnosis for early stage breast cancer. To tackle problems associated with the diversity of data structures of MC lesions and the variability of normal breast tissues, multi-pattern sample space learning is required. In this paper, a novel grouped fuzzy Support Vector Machine (SVM) algorithm with sample space partition based on Expectation-Maximization (EM) (called G-FSVM) is proposed for clustered MC detection. The diversified pattern of training data is partitioned into several groups based on EM algorithm. Then a series of fuzzy SVM are integrated for classification with each group of samples from the MC lesions and normal breast tissues. From DDSM database, a total of 1,064 suspicious regions are selected from 239 mammography, and the measurement of Accuracy, True Positive Rate (TPR), False Positive Rate (FPR) and EVL = TPR* 1-FPR are 0.82, 0.78, 0.14 and 0.72, respectively. The proposed method incorporates the merits of fuzzy SVM and multi-pattern sample space learning, decomposing the MC detection problem into serial simple two-class classification. Experimental results from synthetic data and DDSM database demonstrate that our integrated classification framework reduces the false positive rate significantly while maintaining the true positive rate.

Interactive lesion segmentation on dynamic contrast enhanced breast MRI using a Markov model

NASA Astrophysics Data System (ADS)

Wu, Qiu; Salganicoff, Marcos; Krishnan, Arun; Fussell, Donald S.; Markey, Mia K.

2006-03-01

The purpose of this study is to develop a method for segmenting lesions on Dynamic Contrast-Enhanced (DCE) breast MRI. DCE breast MRI, in which the breast is imaged before, during, and after the administration of a contrast agent, enables a truly 3D examination of breast tissues. This functional angiogenic imaging technique provides noninvasive assessment of microcirculatory characteristics of tissues in addition to traditional anatomical structure information. Since morphological features and kinetic curves from segmented lesions are to be used for diagnosis and treatment decisions, lesion segmentation is a key pre-processing step for classification. In our study, the ROI is defined by a bounding box containing the enhancement region in the subtraction image, which is generated by subtracting the pre-contrast image from 1st post-contrast image. A maximum a posteriori (MAP) estimate of the class membership (lesion vs. non-lesion) for each voxel is obtained using the Iterative Conditional Mode (ICM) method. The prior distribution of the class membership is modeled as a multi-level logistic model, a Markov Random Field model in which the class membership of each voxel is assumed to depend upon its nearest neighbors only. The likelihood distribution is assumed to be Gaussian. The parameters of each Gaussian distribution are estimated from a dozen voxels manually selected as representative of the class. The experimental segmentation results demonstrate anatomically plausible breast tissue segmentation and the predicted class membership of voxels from the interactive segmentation algorithm agrees with the manual classifications made by inspection of the kinetic enhancement curves. The proposed method is advantageous in that it is efficient, flexible, and robust.

Applying Data Mining Techniques to Improve Breast Cancer Diagnosis.

PubMed

Diz, Joana; Marreiros, Goreti; Freitas, Alberto

2016-09-01

In the field of breast cancer research, and more than ever, new computer aided diagnosis based systems have been developed aiming to reduce diagnostic tests false-positives. Within this work, we present a data mining based approach which might support oncologists in the process of breast cancer classification and diagnosis. The present study aims to compare two breast cancer datasets and find the best methods in predicting benign/malignant lesions, breast density classification, and even for finding identification (mass / microcalcification distinction). To carry out these tasks, two matrices of texture features extraction were implemented using Matlab, and classified using data mining algorithms, on WEKA. Results revealed good percentages of accuracy for each class: 89.3 to 64.7 % - benign/malignant; 75.8 to 78.3 % - dense/fatty tissue; 71.0 to 83.1 % - finding identification. Among the different tests classifiers, Naive Bayes was the best to identify masses texture, and Random Forests was the first or second best classifier for the majority of tested groups.

Diagnosis of breast cancer using elastic-scattering spectroscopy: preliminary clinical results

NASA Astrophysics Data System (ADS)

Bigio, Irving J.; Brown, Stephen G.; Briggs, Gavin M.; Kelley, Christine; Lakhani, Sunil; Pickard, David; Ripley, Paul M.; Rose, Ian; Saunders, Christobel

2000-04-01

We report on the first stages of a clinical study designed to test elastic-scattering spectroscopy, medicated by fiberoptic probes, for three specific clinical applications in breast-tissue diagnosis: (1) a transdermal-needle (interstitial) measurement for instant diagnosis with minimal invasiveness similar to fine-needle aspiration but with sensitivity to a larger tissue volume, (2) a hand-held diagnostic probe for use in assessing tumor/resection margins during open surgery, and (3) use of the same probe for real-time assessment of the `sentinel' node during surgery to determine the presence or absence of tumor (metastatic). Preliminary results from in vivo measurements on 31 women are encouraging. Optical spectra were measured on 72 histology sites in breast tissue, and 54 histology sites in sentinel nodes. Two different artificial intelligence methods of spectral classification were studied. Artificial neural networks yielded sensitivities of 69% and 58%, and specificities of 85% and 93%, for breast tissue and sentinel nodes, respectively. Hierarchical cluster analysis yielded sensitivities of 67% and 91%, and specificities of 79% and 77%, for breast tissue and sentinel nodes, respectively. These values are expected to improve as the data sets continue to grow and more sophisticated data preprocessing is employed. The study will enroll up to 400 patients over the next two years.

Differential diagnosis of breast cancer using quantitative, label-free and molecular vibrational imaging

PubMed Central

Yang, Yaliang; Li, Fuhai; Gao, Liang; Wang, Zhiyong; Thrall, Michael J.; Shen, Steven S.; Wong, Kelvin K.; Wong, Stephen T. C.

2011-01-01

We present a label-free, chemically-selective, quantitative imaging strategy to identify breast cancer and differentiate its subtypes using coherent anti-Stokes Raman scattering (CARS) microscopy. Human normal breast tissue, benign proliferative, as well as in situ and invasive carcinomas, were imaged ex vivo. Simply by visualizing cellular and tissue features appearing on CARS images, cancerous lesions can be readily separated from normal tissue and benign proliferative lesion. To further distinguish cancer subtypes, quantitative disease-related features, describing the geometry and distribution of cancer cell nuclei, were extracted and applied to a computerized classification system. The results show that in situ carcinoma was successfully distinguished from invasive carcinoma, while invasive ductal carcinoma (IDC) and invasive lobular carcinoma were also distinguished from each other. Furthermore, 80% of intermediate-grade IDC and 85% of high-grade IDC were correctly distinguished from each other. The proposed quantitative CARS imaging method has the potential to enable rapid diagnosis of breast cancer. PMID:21833355

The ESR1 and GPX1 gene expression level in human malignant and non-malignant breast tissues.

PubMed

Król, Magdalena B; Galicki, Michał; Grešner, Peter; Wieczorek, Edyta; Jabłońska, Ewa; Reszka, Edyta; Morawiec, Zbigniew; Wąsowicz, Wojciech; Gromadzińska, Jolanta

2018-01-01

The aim of this study was to establish whether the gene expression of estrogen receptor alpha (encoded by ESR1) correlates with the expression of glutathione peroxidase 1 (encoded by GPX1) in the tumor and adjacent tumor-free breast tissue, and whether this correlation is affected by breast cancer. Such relationships may give further insights into breast cancer pathology with respect to the status of estrogen receptor. We used the quantitative real-time PCR technique to analyze differences in the expression levels of the ESR1 and GPX1 genes in paired malignant and non-malignant tissues from breast cancer patients. ESR1 and GPX1 expression levels were found to be significantly down-regulated by 14.7% and 7.4% (respectively) in the tumorous breast tissue when compared to the non-malignant one. Down-regulation of these genes was independent of the tumor histopathology classification and clinicopathological factors, while the ESR1 mRNA level was reduced with increasing tumor grade (G1: 103% vs. G2: 85.8% vs. G3: 84.5%; p<0.05). In the non-malignant and malignant breast tissues, the expression levels of ESR1 and GPX1 were significantly correlated with each other (Rs=0.450 and Rs=0.360; respectively). Our data suggest that down-regulation of ESR1 and GPX1 was independent of clinicopathological factors. Down-regulation of ESR1 gene expression was enhanced by the development of the disease. Moreover, GPX1 and ESR1 gene expression was interdependent in the malignant breast tissue and further work is needed to determine the mechanism underlying this relationship.

Surgical Masculinization of the Breast: Clinical Classification and Surgical Procedures.

PubMed

Cardenas-Camarena, Lazaro; Dorado, Carlos; Guerrero, Maria Teresa; Nava, Rosa

2017-06-01

Aesthetic breast area improvements for gynecomastia and gender dysphoria patients who seek a more masculine appearance have increased recently. We present our clinical experience in breast masculinization and a classification for these patients. From July 2003 to May 2014, 68 patients seeking a more masculine thorax underwent surgery. They were divided into five groups depending on three factors: excess fatty tissue, breast tissue, and skin. A specific surgical treatment was assigned according to each group. The surgical treatments included thoracic liposuction, subcutaneous mastectomy, periareolar skin resection in one or two stages, and mastectomy with a nipple areola complex graft. The evaluation was performed 6 months after surgery to determine the degree of satisfaction and presence of complications. Surgery was performed on a total of 68 patients, 45 male and 22 female, with ages ranging from 18 to 49 years, and an average age of 33 years. Liposuction alone was performed on five patients; subcutaneous mastectomy was performed on eight patients; subcutaneous mastectomy combined with liposuction was performed on 27 patients; periareolar skin resection was performed on 11 patients; and mastectomy with NAC free grafts was performed on 16 patients. The surgical procedure satisfied 94% of the patients, with very few complications. All patients who wish to obtain a masculine breast shape should be treated with only one objective regardless patient's gender: to obtain a masculine thorax. We recommend a simple mammary gland classification for determining the best surgical treatment for these patients LEVEL OF EVIDENCE V: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Frequential versus spatial colour textons for breast TMA classification.

PubMed

Fernández-Carrobles, M Milagro; Bueno, Gloria; Déniz, Oscar; Salido, Jesús; García-Rojo, Marcial; Gonzández-López, Lucía

2015-06-01

Advances in digital pathology are generating huge volumes of whole slide (WSI) and tissue microarray images (TMA) which are providing new insights into the causes of cancer. The challenge is to extract and process effectively all the information in order to characterize all the heterogeneous tissue-derived data. This study aims to identify an optimal set of features that best separates different classes in breast TMA. These classes are: stroma, adipose tissue, benign and benign anomalous structures and ductal and lobular carcinomas. To this end, we propose an exhaustive assessment on the utility of textons and colour for automatic classification of breast TMA. Frequential and spatial texton maps from eight different colour models were extracted and compared. Then, in a novel way, the TMA is characterized by the 1st and 2nd order Haralick statistical descriptors obtained from the texton maps with a total of 241 × 8 features for each original RGB image. Subsequently, a feature selection process is performed to remove redundant information and therefore to reduce the dimensionality of the feature vector. Three methods were evaluated: linear discriminant analysis, correlation and sequential forward search. Finally, an extended bank of classifiers composed of six techniques was compared, but only three of them could significantly improve accuracy rates: Fisher, Bagging Trees and AdaBoost. Our results reveal that the combination of different colour models applied to spatial texton maps provides the most efficient representation of the breast TMA. Specifically, we found that the best colour model combination is Hb, Luv and SCT for all classifiers and the classifier that performs best for all colour model combinations is the AdaBoost. On a database comprising 628 TMA images, classification yields an accuracy of 98.1% and a precision of 96.2% with a total of 316 features on spatial textons maps. Copyright © 2014 Elsevier Ltd. All rights reserved.

Efficient Cancer Detection Using Multiple Neural Networks.

PubMed

Shell, John; Gregory, William D

2017-01-01

The inspection of live excised tissue specimens to ascertain malignancy is a challenging task in dermatopathology and generally in histopathology. We introduce a portable desktop prototype device that provides highly accurate neural network classification of malignant and benign tissue. The handheld device collects 47 impedance data samples from 1 Hz to 32 MHz via tetrapolar blackened platinum electrodes. The data analysis was implemented with six different backpropagation neural networks (BNN). A data set consisting of 180 malignant and 180 benign breast tissue data files in an approved IRB study at the Aurora Medical Center, Milwaukee, WI, USA, were utilized as a neural network input. The BNN structure consisted of a multi-tiered consensus approach autonomously selecting four of six neural networks to determine a malignant or benign classification. The BNN analysis was then compared with the histology results with consistent sensitivity of 100% and a specificity of 100%. This implementation successfully relied solely on statistical variation between the benign and malignant impedance data and intricate neural network configuration. This device and BNN implementation provides a novel approach that could be a valuable tool to augment current medical practice assessment of the health of breast, squamous, and basal cell carcinoma and other excised tissue without requisite tissue specimen expertise. It has the potential to provide clinical management personnel with a fast non-invasive accurate assessment of biopsied or sectioned excised tissue in various clinical settings.

Efficient Cancer Detection Using Multiple Neural Networks

PubMed Central

Gregory, William D.

2017-01-01

The inspection of live excised tissue specimens to ascertain malignancy is a challenging task in dermatopathology and generally in histopathology. We introduce a portable desktop prototype device that provides highly accurate neural network classification of malignant and benign tissue. The handheld device collects 47 impedance data samples from 1 Hz to 32 MHz via tetrapolar blackened platinum electrodes. The data analysis was implemented with six different backpropagation neural networks (BNN). A data set consisting of 180 malignant and 180 benign breast tissue data files in an approved IRB study at the Aurora Medical Center, Milwaukee, WI, USA, were utilized as a neural network input. The BNN structure consisted of a multi-tiered consensus approach autonomously selecting four of six neural networks to determine a malignant or benign classification. The BNN analysis was then compared with the histology results with consistent sensitivity of 100% and a specificity of 100%. This implementation successfully relied solely on statistical variation between the benign and malignant impedance data and intricate neural network configuration. This device and BNN implementation provides a novel approach that could be a valuable tool to augment current medical practice assessment of the health of breast, squamous, and basal cell carcinoma and other excised tissue without requisite tissue specimen expertise. It has the potential to provide clinical management personnel with a fast non-invasive accurate assessment of biopsied or sectioned excised tissue in various clinical settings. PMID:29282435

Hyperspectral Imaging and K-Means Classification for Histologic Evaluation of Ductal Carcinoma In Situ.

PubMed

Khouj, Yasser; Dawson, Jeremy; Coad, James; Vona-Davis, Linda

2018-01-01

Hyperspectral imaging (HSI) is a non-invasive optical imaging modality that shows the potential to aid pathologists in breast cancer diagnoses cases. In this study, breast cancer tissues from different patients were imaged by a hyperspectral system to detect spectral differences between normal and breast cancer tissues. Tissue samples mounted on slides were identified from 10 different patients. Samples from each patient included both normal and ductal carcinoma tissue, both stained with hematoxylin and eosin stain and unstained. Slides were imaged using a snapshot HSI system, and the spectral reflectance differences were evaluated. Analysis of the spectral reflectance values indicated that wavelengths near 550 nm showed the best differentiation between tissue types. This information was used to train image processing algorithms using supervised and unsupervised data. The K-means method was applied to the hyperspectral data cubes, and successfully detected spectral tissue differences with sensitivity of 85.45%, and specificity of 94.64% with true negative rate of 95.8%, and false positive rate of 4.2%. These results were verified by ground-truth marking of the tissue samples by a pathologist. In the hyperspectral image analysis, the image processing algorithm, K-means, shows the greatest potential for building a semi-automated system that could identify and sort between normal and ductal carcinoma in situ tissues.

Mammographic density estimation with automated volumetric breast density measurement.

PubMed

Ko, Su Yeon; Kim, Eun-Kyung; Kim, Min Jung; Moon, Hee Jung

2014-01-01

To compare automated volumetric breast density measurement (VBDM) with radiologists' evaluations based on the Breast Imaging Reporting and Data System (BI-RADS), and to identify the factors associated with technical failure of VBDM. In this study, 1129 women aged 19-82 years who underwent mammography from December 2011 to January 2012 were included. Breast density evaluations by radiologists based on BI-RADS and by VBDM (Volpara Version 1.5.1) were compared. The agreement in interpreting breast density between radiologists and VBDM was determined based on four density grades (D1, D2, D3, and D4) and a binary classification of fatty (D1-2) vs. dense (D3-4) breast using kappa statistics. The association between technical failure of VBDM and patient age, total breast volume, fibroglandular tissue volume, history of partial mastectomy, the frequency of mass > 3 cm, and breast density was analyzed. The agreement between breast density evaluations by radiologists and VBDM was fair (k value = 0.26) when the four density grades (D1/D2/D3/D4) were used and moderate (k value = 0.47) for the binary classification (D1-2/D3-4). Twenty-seven women (2.4%) showed failure of VBDM. Small total breast volume, history of partial mastectomy, and high breast density were significantly associated with technical failure of VBDM (p = 0.001 to 0.015). There is fair or moderate agreement in breast density evaluation between radiologists and VBDM. Technical failure of VBDM may be related to small total breast volume, a history of partial mastectomy, and high breast density.

Computerized image analysis: estimation of breast density on mammograms

NASA Astrophysics Data System (ADS)

Zhou, Chuan; Chan, Heang-Ping; Petrick, Nicholas; Sahiner, Berkman; Helvie, Mark A.; Roubidoux, Marilyn A.; Hadjiiski, Lubomir M.; Goodsitt, Mitchell M.

2000-06-01

An automated image analysis tool is being developed for estimation of mammographic breast density, which may be useful for risk estimation or for monitoring breast density change in a prevention or intervention program. A mammogram is digitized using a laser scanner and the resolution is reduced to a pixel size of 0.8 mm X 0.8 mm. Breast density analysis is performed in three stages. First, the breast region is segmented from the surrounding background by an automated breast boundary-tracking algorithm. Second, an adaptive dynamic range compression technique is applied to the breast image to reduce the range of the gray level distribution in the low frequency background and to enhance the differences in the characteristic features of the gray level histogram for breasts of different densities. Third, rule-based classification is used to classify the breast images into several classes according to the characteristic features of their gray level histogram. For each image, a gray level threshold is automatically determined to segment the dense tissue from the breast region. The area of segmented dense tissue as a percentage of the breast area is then estimated. In this preliminary study, we analyzed the interobserver variation of breast density estimation by two experienced radiologists using BI-RADS lexicon. The radiologists' visually estimated percent breast densities were compared with the computer's calculation. The results demonstrate the feasibility of estimating mammographic breast density using computer vision techniques and its potential to improve the accuracy and reproducibility in comparison with the subjective visual assessment by radiologists.

Application of texture analysis method for mammogram density classification

NASA Astrophysics Data System (ADS)

Nithya, R.; Santhi, B.

2017-07-01

Mammographic density is considered a major risk factor for developing breast cancer. This paper proposes an automated approach to classify breast tissue types in digital mammogram. The main objective of the proposed Computer-Aided Diagnosis (CAD) system is to investigate various feature extraction methods and classifiers to improve the diagnostic accuracy in mammogram density classification. Texture analysis methods are used to extract the features from the mammogram. Texture features are extracted by using histogram, Gray Level Co-Occurrence Matrix (GLCM), Gray Level Run Length Matrix (GLRLM), Gray Level Difference Matrix (GLDM), Local Binary Pattern (LBP), Entropy, Discrete Wavelet Transform (DWT), Wavelet Packet Transform (WPT), Gabor transform and trace transform. These extracted features are selected using Analysis of Variance (ANOVA). The features selected by ANOVA are fed into the classifiers to characterize the mammogram into two-class (fatty/dense) and three-class (fatty/glandular/dense) breast density classification. This work has been carried out by using the mini-Mammographic Image Analysis Society (MIAS) database. Five classifiers are employed namely, Artificial Neural Network (ANN), Linear Discriminant Analysis (LDA), Naive Bayes (NB), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). Experimental results show that ANN provides better performance than LDA, NB, KNN and SVM classifiers. The proposed methodology has achieved 97.5% accuracy for three-class and 99.37% for two-class density classification.

A Review on Automatic Mammographic Density and Parenchymal Segmentation

PubMed Central

He, Wenda; Juette, Arne; Denton, Erika R. E.; Oliver, Arnau

2015-01-01

Breast cancer is the most frequently diagnosed cancer in women. However, the exact cause(s) of breast cancer still remains unknown. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective way to tackle breast cancer. There are more than 70 common genetic susceptibility factors included in the current non-image-based risk prediction models (e.g., the Gail and the Tyrer-Cuzick models). Image-based risk factors, such as mammographic densities and parenchymal patterns, have been established as biomarkers but have not been fully incorporated in the risk prediction models used for risk stratification in screening and/or measuring responsiveness to preventive approaches. Within computer aided mammography, automatic mammographic tissue segmentation methods have been developed for estimation of breast tissue composition to facilitate mammographic risk assessment. This paper presents a comprehensive review of automatic mammographic tissue segmentation methodologies developed over the past two decades and the evidence for risk assessment/density classification using segmentation. The aim of this review is to analyse how engineering advances have progressed and the impact automatic mammographic tissue segmentation has in a clinical environment, as well as to understand the current research gaps with respect to the incorporation of image-based risk factors in non-image-based risk prediction models. PMID:26171249

Pseudomamma of the inguinal region in a female patient: A case report

PubMed Central

Marinopoulos, Spyridon; Arampatzis, Ioannis; Zagouri, Flora; Dimitrakakis, Constantine

2015-01-01

Introduction Supernumerary breasts are relative common benign congenital anomalies. General population occurrence rates vary up to 6% according to ethnicity and gender. Higher incidence is recorded in Asian individuals, especially Japanese. Embryonic breast development of the mammary ridge (milk line) is explained and supernumerary breast tissue resulting from involution failure of any portion of the embryonic mammary folds is described. Presentation of case We report a case of supernumerary breast (pseudomamma) in a female occupying her right inguinal region that was treated in the breast unit of our hospital. Differential diagnosis, imaging methods, operative approach, surgical treatment and histological verification are specified. Discussion Classification system for supernumerary breast tissue is presented, high risk population is identified and congenital malformations linked to it are outlined. Evaluation of diagnostic workup and limitations are stated. Cancerous degeneration and justification for surgical removal of the accessory gland is discussed. Conclusion Differential diagnosis of lesions along the milk line should always be inclusive of developmental abnormalities such as any type of supernumerary breast, often overlooked due to small size, although carrying a malignant potential equal to normally positioned breasts. Surgical correction is a sensible approach, often encouraged by the patients. Additional evaluation is recommended due to the frequent accompanying urinary tract and cardiac anomalies. PMID:26011805

Automated classification of immunostaining patterns in breast tissue from the human protein atlas.

PubMed

Swamidoss, Issac Niwas; Kårsnäs, Andreas; Uhlmann, Virginie; Ponnusamy, Palanisamy; Kampf, Caroline; Simonsson, Martin; Wählby, Carolina; Strand, Robin

2013-01-01

The Human Protein Atlas (HPA) is an effort to map the location of all human proteins (http://www.proteinatlas.org/). It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA) are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples. The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM) features, complex wavelet co-occurrence matrix (CWCM) features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM)-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM) and linear discriminant analysis (LDA) classifier). Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue. We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert. Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for quantification of staining patterns in histopathology have many applications, ranging from antibody quality control to tumor grading.

Automatic classification of tissue malignancy for breast carcinoma diagnosis.

PubMed

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.

Application of the Minkowski-functionals for automated pattern classification of breast parenchyma depicted by digital mammography

NASA Astrophysics Data System (ADS)

Boehm, Holger F.; Fischer, Tanja; Riosk, Dororthea; Britsch, Stefanie; Reiser, Maximilian

2008-03-01

With an estimated life-time-risk of about 10%, breast cancer is the most common cancer among women in western societies. Extensive mammography-screening programs have been implemented for diagnosis of the disease at an early stage. Several algorithms for computer-aided detection (CAD) have been proposed to help radiologists manage the increasing number of mammographic image-data and identify new cases of cancer. However, a major issue with most CAD-solutions is the fact that performance strongly depends on the structure and density of the breast tissue. Prior information about the global tissue quality in a patient would be helpful for selecting the most effective CAD-approach in order to increase the sensitivity of lesion-detection. In our study, we propose an automated method for textural evaluation of digital mammograms using the Minkowski Functionals in 2D. 80 mammograms are consensus-classified by two experienced readers as fibrosis, involution/atrophy, or normal. For each case, the topology of graylevel distribution is evaluated within a retromamillary image-section of 512 x 512 pixels. In addition, we obtain parameters from the graylevel-histogram (20th percentile, median and mean graylevel intensity). As a result, correct classification of the mammograms based on the densitometic parameters is achieved in between 38 and 48%, whereas topological analysis increases the rate to 83%. The findings demonstrate the effectiveness of the proposed algorithm. Compared to features obtained from graylevel histograms and comparable studies, we draw the conclusion that the presented method performs equally good or better. Our future work will be focused on the characterization of the mammographic tissue according to the Breast Imaging Reporting and Data System (BI-RADS). Moreover, other databases will be tested for an in-depth evaluation of the efficiency of our proposal.

Local binary pattern texture-based classification of solid masses in ultrasound breast images

NASA Astrophysics Data System (ADS)

Matsumoto, Monica M. S.; Sehgal, Chandra M.; Udupa, Jayaram K.

2012-03-01

Breast cancer is one of the leading causes of cancer mortality among women. Ultrasound examination can be used to assess breast masses, complementarily to mammography. Ultrasound images reveal tissue information in its echoic patterns. Therefore, pattern recognition techniques can facilitate classification of lesions and thereby reduce the number of unnecessary biopsies. Our hypothesis was that image texture features on the boundary of a lesion and its vicinity can be used to classify masses. We have used intensity-independent and rotation-invariant texture features, known as Local Binary Patterns (LBP). The classifier selected was K-nearest neighbors. Our breast ultrasound image database consisted of 100 patient images (50 benign and 50 malignant cases). The determination of whether the mass was benign or malignant was done through biopsy and pathology assessment. The training set consisted of sixty images, randomly chosen from the database of 100 patients. The testing set consisted of forty images to be classified. The results with a multi-fold cross validation of 100 iterations produced a robust evaluation. The highest performance was observed for feature LBP with 24 symmetrically distributed neighbors over a circle of radius 3 (LBP24,3) with an accuracy rate of 81.0%. We also investigated an approach with a score of malignancy assigned to the images in the test set. This approach provided an ROC curve with Az of 0.803. The analysis of texture features over the boundary of solid masses showed promise for malignancy classification in ultrasound breast images.

Mammographic Density Estimation with Automated Volumetric Breast Density Measurement

PubMed Central

Ko, Su Yeon; Kim, Eun-Kyung; Kim, Min Jung

2014-01-01

Objective To compare automated volumetric breast density measurement (VBDM) with radiologists' evaluations based on the Breast Imaging Reporting and Data System (BI-RADS), and to identify the factors associated with technical failure of VBDM. Materials and Methods In this study, 1129 women aged 19-82 years who underwent mammography from December 2011 to January 2012 were included. Breast density evaluations by radiologists based on BI-RADS and by VBDM (Volpara Version 1.5.1) were compared. The agreement in interpreting breast density between radiologists and VBDM was determined based on four density grades (D1, D2, D3, and D4) and a binary classification of fatty (D1-2) vs. dense (D3-4) breast using kappa statistics. The association between technical failure of VBDM and patient age, total breast volume, fibroglandular tissue volume, history of partial mastectomy, the frequency of mass > 3 cm, and breast density was analyzed. Results The agreement between breast density evaluations by radiologists and VBDM was fair (k value = 0.26) when the four density grades (D1/D2/D3/D4) were used and moderate (k value = 0.47) for the binary classification (D1-2/D3-4). Twenty-seven women (2.4%) showed failure of VBDM. Small total breast volume, history of partial mastectomy, and high breast density were significantly associated with technical failure of VBDM (p = 0.001 to 0.015). Conclusion There is fair or moderate agreement in breast density evaluation between radiologists and VBDM. Technical failure of VBDM may be related to small total breast volume, a history of partial mastectomy, and high breast density. PMID:24843235

Classification of breast MRI lesions using small-size training sets: comparison of deep learning approaches

NASA Astrophysics Data System (ADS)

Amit, Guy; Ben-Ari, Rami; Hadad, Omer; Monovich, Einat; Granot, Noa; Hashoul, Sharbell

2017-03-01

Diagnostic interpretation of breast MRI studies requires meticulous work and a high level of expertise. Computerized algorithms can assist radiologists by automatically characterizing the detected lesions. Deep learning approaches have shown promising results in natural image classification, but their applicability to medical imaging is limited by the shortage of large annotated training sets. In this work, we address automatic classification of breast MRI lesions using two different deep learning approaches. We propose a novel image representation for dynamic contrast enhanced (DCE) breast MRI lesions, which combines the morphological and kinetics information in a single multi-channel image. We compare two classification approaches for discriminating between benign and malignant lesions: training a designated convolutional neural network and using a pre-trained deep network to extract features for a shallow classifier. The domain-specific trained network provided higher classification accuracy, compared to the pre-trained model, with an area under the ROC curve of 0.91 versus 0.81, and an accuracy of 0.83 versus 0.71. Similar accuracy was achieved in classifying benign lesions, malignant lesions, and normal tissue images. The trained network was able to improve accuracy by using the multi-channel image representation, and was more robust to reductions in the size of the training set. A small-size convolutional neural network can learn to accurately classify findings in medical images using only a few hundred images from a few dozen patients. With sufficient data augmentation, such a network can be trained to outperform a pre-trained out-of-domain classifier. Developing domain-specific deep-learning models for medical imaging can facilitate technological advancements in computer-aided diagnosis.

Measurement of the hyperelastic properties of 44 pathological ex vivo breast tissue samples

NASA Astrophysics Data System (ADS)

O'Hagan, Joseph J.; Samani, Abbas

2009-04-01

The elastic and hyperelastic properties of biological soft tissues have been of interest to the medical community. There are several biomedical applications where parameters characterizing such properties are critical for a reliable clinical outcome. These applications include surgery planning, needle biopsy and brachtherapy where tissue biomechanical modeling is involved. Another important application is interpreting nonlinear elastography images. While there has been considerable research on the measurement of the linear elastic modulus of small tissue samples, little research has been conducted for measuring parameters that characterize the nonlinear elasticity of tissues included in tissue slice specimens. This work presents hyperelastic measurement results of 44 pathological ex vivo breast tissue samples. For each sample, five hyperelastic models have been used, including the Yeoh, N = 2 polynomial, N = 1 Ogden, Arruda-Boyce, and Veronda-Westmann models. Results show that the Yeoh, polynomial and Ogden models are the most accurate in terms of fitting experimental data. The results indicate that almost all of the parameters corresponding to the pathological tissues are between two times to over two orders of magnitude larger than those of normal tissues, with C11 showing the most significant difference. Furthermore, statistical analysis indicates that C02 of the Yeoh model, and C11 and C20 of the polynomial model have very good potential for cancer classification as they show statistically significant differences for various cancer types, especially for invasive lobular carcinoma. In addition to the potential for use in cancer classification, the presented data are very important for applications such as surgery planning and virtual reality based clinician training systems where accurate nonlinear tissue response modeling is required.

Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies.

PubMed

Ehteshami Bejnordi, Babak; Mullooly, Maeve; Pfeiffer, Ruth M; Fan, Shaoqi; Vacek, Pamela M; Weaver, Donald L; Herschorn, Sally; Brinton, Louise A; van Ginneken, Bram; Karssemeijer, Nico; Beck, Andrew H; Gierach, Gretchen L; van der Laak, Jeroen A W M; Sherman, Mark E

2018-06-13

The breast stromal microenvironment is a pivotal factor in breast cancer development, growth and metastases. Although pathologists often detect morphologic changes in stroma by light microscopy, visual classification of such changes is subjective and non-quantitative, limiting its diagnostic utility. To gain insights into stromal changes associated with breast cancer, we applied automated machine learning techniques to digital images of 2387 hematoxylin and eosin stained tissue sections of benign and malignant image-guided breast biopsies performed to investigate mammographic abnormalities among 882 patients, ages 40-65 years, that were enrolled in the Breast Radiology Evaluation and Study of Tissues (BREAST) Stamp Project. Using deep convolutional neural networks, we trained an algorithm to discriminate between stroma surrounding invasive cancer and stroma from benign biopsies. In test sets (928 whole-slide images from 330 patients), this algorithm could distinguish biopsies diagnosed as invasive cancer from benign biopsies solely based on the stromal characteristics (area under the receiver operator characteristics curve = 0.962). Furthermore, without being trained specifically using ductal carcinoma in situ as an outcome, the algorithm detected tumor-associated stroma in greater amounts and at larger distances from grade 3 versus grade 1 ductal carcinoma in situ. Collectively, these results suggest that algorithms based on deep convolutional neural networks that evaluate only stroma may prove useful to classify breast biopsies and aid in understanding and evaluating the biology of breast lesions.

Mammogram classification scheme using 2D-discrete wavelet and local binary pattern for detection of breast cancer

NASA Astrophysics Data System (ADS)

Adi Putra, Januar

2018-04-01

In this paper, we propose a new mammogram classification scheme to classify the breast tissues as normal or abnormal. Feature matrix is generated using Local Binary Pattern to all the detailed coefficients from 2D-DWT of the region of interest (ROI) of a mammogram. Feature selection is done by selecting the relevant features that affect the classification. Feature selection is used to reduce the dimensionality of data and features that are not relevant, in this paper the F-test and Ttest will be performed to the results of the feature extraction dataset to reduce and select the relevant feature. The best features are used in a Neural Network classifier for classification. In this research we use MIAS and DDSM database. In addition to the suggested scheme, the competent schemes are also simulated for comparative analysis. It is observed that the proposed scheme has a better say with respect to accuracy, specificity and sensitivity. Based on experiments, the performance of the proposed scheme can produce high accuracy that is 92.71%, while the lowest accuracy obtained is 77.08%.

Segmentation of HER2 protein overexpression in immunohistochemically stained breast cancer images using Support Vector Machines

NASA Astrophysics Data System (ADS)

Pezoa, Raquel; Salinas, Luis; Torres, Claudio; Härtel, Steffen; Maureira-Fredes, Cristián; Arce, Paola

2016-10-01

Breast cancer is one of the most common cancers in women worldwide. Patient therapy is widely supported by analysis of immunohistochemically (IHC) stained tissue sections. In particular, the analysis of HER2 overexpression by immunohistochemistry helps to determine when patients are suitable to HER2-targeted treatment. Computational HER2 overexpression analysis is still an open problem and a challenging task principally because of the variability of immunohistochemistry tissue samples and the subjectivity of the specialists to assess the samples. In addition, the immunohistochemistry process can produce diverse artifacts that difficult the HER2 overexpression assessment. In this paper we study the segmentation of HER2 overexpression in IHC stained breast cancer tissue images using a support vector machine (SVM) classifier. We asses the SVM performance using diverse color and texture pixel-level features including the RGB, CMYK, HSV, CIE L*a*b* color spaces, color deconvolution filter and Haralick features. We measure classification performance for three datasets containing a total of 153 IHC images that were previously labeled by a pathologist.

TH-AB-209-10: Breast Cancer Identification Through X-Ray Coherent Scatter Spectral Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kapadia, A; Morris, R; Albanese, K

Purpose: We have previously described the development and testing of a coherent-scatter spectral imaging system for identification of cancer. Our prior evaluations were performed using either tissue surrogate phantoms or formalin-fixed tissue obtained from pathology. Here we present the first results from a scatter imaging study using fresh breast tumor tissues obtained through surgical excision. Methods: A coherent-scatter imaging system was built using a clinical X-ray tube, photon counting detectors, and custom-designed coded-apertures. System performance was characterized using calibration phantoms of biological materials. Fresh breast tumors were obtained from patients undergoing mastectomy and lumpectomy surgeries for breast cancer. Each specimenmore » was vacuum-sealed, scanned using the scatter imaging system, and then sent to pathology for histological workup. Scatter images were generated separately for each tissue specimen and analyzed to identify voxels containing malignant tissue. The images were compared against histological analysis (H&E + pathologist identification of tumors) to assess the match between scatter-based and histological diagnosis. Results: In all specimens scanned, the scatter images showed the location of cancerous regions within the specimen. The detection and classification was performed through automated spectral matching without the need for manual intervention. The scatter spectra corresponding to cancer tissue were found to be in agreement with those reported in literature. Inter-patient variability was found to be within limits reported in literature. The scatter images showed agreement with pathologist-identified regions of cancer. Spatial resolution for this configuration of the scanner was determined to be 2–3 mm, and the total scan time for each specimen was under 15 minutes. Conclusion: This work demonstrates the utility of coherent scatter imaging in identifying cancer based on the scatter properties of the tissue. It presents the first results from coherent scatter imaging of fresh (unfixed) breast tissue using our coded-aperture scatter imaging approach for cancer identification.« less

Breast elastography: Identification of benign and malignant cancer based on absolute elastic modulus measurement using vibro-elastography

NASA Astrophysics Data System (ADS)

Arroyo, Junior; Saavedra, Ana Cecilia; Guerrero, Jorge; Montenegro, Pilar; Aguilar, Jorge; Pinto, Joseph A.; Lobo, Julio; Salcudean, Tim; Lavarello, Roberto; Castañeda, Benjamín.

2018-03-01

Breast cancer is a public health problem with 1.7 million new cases per year worldwide and with several limitations in the state-of-art screening techniques. Ultrasound elastography involves a set of techniques intended to facilitate the noninvasive diagnosis of cancer. Among these, Vibro-elastography is an ultrasound-based technique that employs external mechanical excitation to infer the elastic properties of soft tissue. In this paper, we evaluate the Vibro-elastography performance in the differentiation of benign and malignant breast lesions. For this study, a group of 18 women with clinically confirmed tumors or suspected malignant breast lesions were invited to participate. For each volunteer, an elastogram was obtained, and the mean elasticity of the lesion and the adjacent healthy tissue were calculated. After the acquisition, the volunteers underwent core-needle biopsy. The histopathological results allowed to validate the Vibro-elastography diagnosis, which ranged from benign to malignant lesions. Results indicate that the mean elasticity value of the benign lesions, malignant lesions and healthy breast tissue were 39.4 +/- 12 KPa, 55.4 +/- 7.02 KPa and 23.91 +/- 4.57 kPa, respectively. The classification between benign and malignant breast cancer was performed using Support Vector Machine based on the measured lesion stiffness. A ROC curve permitted to quantify the accuracy of the differentiation and to define a suitable cutoff value of stiffness, obtaining an AUC of 0.90 and a cutoff value of 44.75 KPa. The results obtained suggest that Vibro-elastography allows differentiating between benign and malignant lesions. Furthermore, the elasticity values obtained for benign, malignant and healthy tissue are consistent with previous reports.

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

PubMed

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 Curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the biomarkers are associated with Signaling, Hemostasis, Hormones, and Immune System, which are consistent with previous findings. Our prediction model can serve as a general model for biomarker discovery in early detection of other cancers. In the future, Polymerase Chain Reaction (PCR) is planned for validation of the ability of these potential biomarkers for early detection of breast cancer.

Giant accessory breast: a rare occurrence reported, with a review of the literature.

PubMed

Hiremath, Bharati; Subramaniam, Narayana; Chandrashekhar, Nayan

2015-11-05

Polymastia, or the presence of supranumerary breasts, occurs in 2-6% of the female population, the spectrum of the disorder ranging between a small mole and a fully functional ectopic breast. They are often asymptomatic but require treatment when symptomatic or if they harbour malignancy. We present a case of a 41-year-old woman with an accessory breast in the left inframammary fold, which increased in size over the decade following her first pregnancy, to reach a size almost three times that of her right breast. Preoperative fine-needle aspiration and ultrasound was suggestive of accessory breast tissue, distinct from the left breast. Intraoperatively, a 14×10×8 cm accessory breast was found in the inframammary fold, distinct from the left breast and having an accessory nipple areola complex as well. A simple mastectomy was performed with trimming and rotation of the inframammary flap. The patient was happy with the cosmetic outcome. This article also reviews the literature and covers classification of polymastia, diagnostic complexities and challenges associated with surgery. 2015 BMJ Publishing Group Ltd.

Giant accessory breast: a rare occurrence reported, with a review of the literature

PubMed Central

Hiremath, Bharati; Subramaniam, Narayana; Chandrashekhar, Nayan

2015-01-01

Polymastia, or the presence of supranumerary breasts, occurs in 2–6% of the female population, the spectrum of the disorder ranging between a small mole and a fully functional ectopic breast. They are often asymptomatic but require treatment when symptomatic or if they harbour malignancy. We present a case of a 41-year-old woman with an accessory breast in the left inframammary fold, which increased in size over the decade following her first pregnancy, to reach a size almost three times that of her right breast. Preoperative fine-needle aspiration and ultrasound was suggestive of accessory breast tissue, distinct from the left breast. Intraoperatively, a 14×10×8 cm accessory breast was found in the inframammary fold, distinct from the left breast and having an accessory nipple areola complex as well. A simple mastectomy was performed with trimming and rotation of the inframammary flap. The patient was happy with the cosmetic outcome. This article also reviews the literature and covers classification of polymastia, diagnostic complexities and challenges associated with surgery. PMID:26542818

Breast density characterization using texton distributions.

PubMed

Petroudi, Styliani; Brady, Michael

2011-01-01

Breast density has been shown to be one of the most significant risks for developing breast cancer, with women with dense breasts at four to six times higher risk. The Breast Imaging Reporting and Data System (BI-RADS) has a four class classification scheme that describes the different breast densities. However, there is great inter and intra observer variability among clinicians in reporting a mammogram's density class. This work presents a novel texture classification method and its application for the development of a completely automated breast density classification system. The new method represents the mammogram using textons, which can be thought of as the building blocks of texture under the operational definition of Leung and Malik as clustered filter responses. The new proposed method characterizes the mammographic appearance of the different density patterns by evaluating the texton spatial dependence matrix (TDSM) in the breast region's corresponding texton map. The TSDM is a texture model that captures both statistical and structural texture characteristics. The normalized TSDM matrices are evaluated for mammograms from the different density classes and corresponding texture models are established. Classification is achieved using a chi-square distance measure. The fully automated TSDM breast density classification method is quantitatively evaluated on mammograms from all density classes from the Oxford Mammogram Database. The incorporation of texton spatial dependencies allows for classification accuracy reaching over 82%. The breast density classification accuracy is better using texton TSDM compared to simple texton histograms.

Automatic segmentation of mammogram and tomosynthesis images

NASA Astrophysics Data System (ADS)

Sargent, Dusty; Park, Sun Young

2016-03-01

Breast cancer is a one of the most common forms of cancer in terms of new cases and deaths both in the United States and worldwide. However, the survival rate with breast cancer is high if it is detected and treated before it spreads to other parts of the body. The most common screening methods for breast cancer are mammography and digital tomosynthesis, which involve acquiring X-ray images of the breasts that are interpreted by radiologists. The work described in this paper is aimed at optimizing the presentation of mammography and tomosynthesis images to the radiologist, thereby improving the early detection rate of breast cancer and the resulting patient outcomes. Breast cancer tissue has greater density than normal breast tissue, and appears as dense white image regions that are asymmetrical between the breasts. These irregularities are easily seen if the breast images are aligned and viewed side-by-side. However, since the breasts are imaged separately during mammography, the images may be poorly centered and aligned relative to each other, and may not properly focus on the tissue area. Similarly, although a full three dimensional reconstruction can be created from digital tomosynthesis images, the same centering and alignment issues can occur for digital tomosynthesis. Thus, a preprocessing algorithm that aligns the breasts for easy side-by-side comparison has the potential to greatly increase the speed and accuracy of mammogram reading. Likewise, the same preprocessing can improve the results of automatic tissue classification algorithms for mammography. In this paper, we present an automated segmentation algorithm for mammogram and tomosynthesis images that aims to improve the speed and accuracy of breast cancer screening by mitigating the above mentioned problems. Our algorithm uses information in the DICOM header to facilitate preprocessing, and incorporates anatomical region segmentation and contour analysis, along with a hidden Markov model (HMM) for processing the multi-frame tomosynthesis images. The output of the algorithm is a new set of images that have been processed to show only the diagnostically relevant region and align the breasts so that they can be easily compared side-by-side. Our method has been tested on approximately 750 images, including various examples of mammogram, tomosynthesis, and scanned images, and has correctly segmented the diagnostically relevant image region in 97% of cases.

Optimization of breast mass classification using sequential forward floating selection (SFFS) and a support vector machine (SVM) model

PubMed Central

Tan, Maxine; Pu, Jiantao; Zheng, Bin

2014-01-01

Purpose: Improving radiologists’ performance in classification between malignant and benign breast lesions is important to increase cancer detection sensitivity and reduce false-positive recalls. For this purpose, developing computer-aided diagnosis (CAD) schemes has been attracting research interest in recent years. In this study, we investigated a new feature selection method for the task of breast mass classification. Methods: We initially computed 181 image features based on mass shape, spiculation, contrast, presence of fat or calcifications, texture, isodensity, and other morphological features. From this large image feature pool, we used a sequential forward floating selection (SFFS)-based feature selection method to select relevant features, and analyzed their performance using a support vector machine (SVM) model trained for the classification task. On a database of 600 benign and 600 malignant mass regions of interest (ROIs), we performed the study using a ten-fold cross-validation method. Feature selection and optimization of the SVM parameters were conducted on the training subsets only. Results: The area under the receiver operating characteristic curve (AUC) = 0.805±0.012 was obtained for the classification task. The results also showed that the most frequently-selected features by the SFFS-based algorithm in 10-fold iterations were those related to mass shape, isodensity and presence of fat, which are consistent with the image features frequently used by radiologists in the clinical environment for mass classification. The study also indicated that accurately computing mass spiculation features from the projection mammograms was difficult, and failed to perform well for the mass classification task due to tissue overlap within the benign mass regions. Conclusions: In conclusion, this comprehensive feature analysis study provided new and valuable information for optimizing computerized mass classification schemes that may have potential to be useful as a “second reader” in future clinical practice. PMID:24664267

High intra-tumoral stromal content defines Reactive breast cancer as a low-risk breast cancer subtype

PubMed Central

Dennison, Jennifer B.; Shahmoradgoli, Maria; Liu, Wenbin; Ju, Zhenlin; Meric-Bernstam, Funda; Perou, Charles M.; Sahin, Aysegul A.; Welm, Alana; Oesterreich, Steffi; Sikora, Matthew J.; Brown, Robert E.; Mills, Gordon B.

2016-01-01

Purpose The current study evaluated associative effects of breast cancer cells with the tumor microenvironment and its influence on tumor behavior. Experimental design Formalin-fixed paraffin embedded tissue and matched protein lysates were evaluated from two independent breast cancer patient data sets (TCGA and MD Anderson). Reverse-phase protein arrays (RPPA) were utilized to create a proteomics signature to define breast tumor subtypes. Expression patterns of cell lines and normal breast tissues were utilized to determine markers that were differentially expressed in stroma and cancer cells. Protein localization and stromal contents were evaluated for matched cases by imaging. Results A subtype of breast cancers designated “Reactive,” previously identified by RPPA that was not predicted by mRNA profiling, was extensively characterized. These tumors were primarily estrogen receptor (ER)-positive/human epidermal growth factor receptor (HER)2-negative, low-risk cancers as determined by enrichment of low-grade nuclei, lobular or tubular histopathology, and the luminal A subtype by PAM50. Reactive breast cancers contained high numbers of stromal cells and the highest extracellular matrix content typically without infiltration of immune cells. For ER-positive/HER2-negative cancers, the Reactive classification predicted favorable clinical outcomes in the TCGA cohort (HR = 0.36, P < 0.05). Conclusions A protein stromal signature in breast cancers is associated with a highly differentiated phenotype. The stromal compartment content and proteins are an extended phenotype not predicted by mRNA expression that could be utilized to sub-classify ER-positive/HER2-negative breast cancers. PMID:27172895

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: A postmortem study

PubMed Central

Ding, Huanjun; Johnson, Travis; Lin, Muqing; Le, Huy Q.; Ducote, Justin L.; Su, Min-Ying; Molloi, Sabee

2013-01-01

Purpose: Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study. Methods: T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-field-corrected images produced by CLIC method. The left–right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson's r, was used to evaluate the two image segmentation algorithms and the effect of bias field. Results: The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left–right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left–right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson's r increased from 0.86 to 0.92 with the bias field correction. Conclusions: The investigated CLIC method significantly increased the precision and accuracy of breast density quantification using breast MRI images by effectively correcting the bias field. It is expected that a fully automated computerized algorithm for breast density quantification may have great potential in clinical MRI applications. PMID:24320536

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: a postmortem study.

PubMed

Ding, Huanjun; Johnson, Travis; Lin, Muqing; Le, Huy Q; Ducote, Justin L; Su, Min-Ying; Molloi, Sabee

2013-12-01

Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study. T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-field-corrected images produced by CLIC method. The left-right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson's r, was used to evaluate the two image segmentation algorithms and the effect of bias field. The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left-right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left-right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson's r increased from 0.86 to 0.92 with the bias field correction. The investigated CLIC method significantly increased the precision and accuracy of breast density quantification using breast MRI images by effectively correcting the bias field. It is expected that a fully automated computerized algorithm for breast density quantification may have great potential in clinical MRI applications.

Multiple Biomarker Panels for Early Detection of Breast Cancer in Peripheral Blood

PubMed Central

Zhang, Fan; Deng, Youping; Drabier, Renee

2013-01-01

Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers. PMID:24371830

Multiple biomarker panels for early detection of breast cancer in peripheral blood.

PubMed

Zhang, Fan; Deng, Youping; Drabier, Renee

2013-01-01

Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers.

Mass type-specific sparse representation for mass classification in computer-aided detection on mammograms

PubMed Central

2013-01-01

Background Breast cancer is the leading cause of both incidence and mortality in women population. For this reason, much research effort has been devoted to develop Computer-Aided Detection (CAD) systems for early detection of the breast cancers on mammograms. In this paper, we propose a new and novel dictionary configuration underpinning sparse representation based classification (SRC). The key idea of the proposed algorithm is to improve the sparsity in terms of mass margins for the purpose of improving classification performance in CAD systems. Methods The aim of the proposed SRC framework is to construct separate dictionaries according to the types of mass margins. The underlying idea behind our method is that the separated dictionaries can enhance the sparsity of mass class (true-positive), leading to an improved performance for differentiating mammographic masses from normal tissues (false-positive). When a mass sample is given for classification, the sparse solutions based on corresponding dictionaries are separately solved and combined at score level. Experiments have been performed on both database (DB) named as Digital Database for Screening Mammography (DDSM) and clinical Full Field Digital Mammogram (FFDM) DBs. In our experiments, sparsity concentration in the true class (SCTC) and area under the Receiver operating characteristic (ROC) curve (AUC) were measured for the comparison between the proposed method and a conventional single dictionary based approach. In addition, a support vector machine (SVM) was used for comparing our method with state-of-the-arts classifier extensively used for mass classification. Results Comparing with the conventional single dictionary configuration, the proposed approach is able to improve SCTC of up to 13.9% and 23.6% on DDSM and FFDM DBs, respectively. Moreover, the proposed method is able to improve AUC with 8.2% and 22.1% on DDSM and FFDM DBs, respectively. Comparing to SVM classifier, the proposed method improves AUC with 2.9% and 11.6% on DDSM and FFDM DBs, respectively. Conclusions The proposed dictionary configuration is found to well improve the sparsity of dictionaries, resulting in an enhanced classification performance. Moreover, the results show that the proposed method is better than conventional SVM classifier for classifying breast masses subject to various margins from normal tissues. PMID:24564973

Computer-aided diagnosis of breast cancer via Gabor wavelet bank and binary-class SVM in mammographic images

NASA Astrophysics Data System (ADS)

Torrents-Barrena, Jordina; Puig, Domenec; Melendez, Jaime; Valls, Aida

2016-03-01

Breast cancer is one of the most dangerous diseases that attack women in their 40s worldwide. Due to this fact, it is estimated that one in eight women will develop a malignant carcinoma during their life. In addition, the carelessness of performing regular screenings is an important reason for the increase of mortality. However, computer-aided diagnosis systems attempt to enhance the quality of mammograms as well as the detection of early signs related to the disease. In this paper we propose a bank of Gabor filters to calculate the mean, standard deviation, skewness and kurtosis features by four-sized evaluation windows. Therefore, an active strategy is used to select the most relevant pixels. Finally, a supervised classification stage using two-class support vector machines is utilised through an accurate estimation of kernel parameters. In order to show the development of our methodology based on mammographic image analysis, two main experiments are fulfilled: abnormal/normal breast tissue classification and the ability to detect the different breast cancer types. Moreover, the public screen-film mini-MIAS database is compared with a digitised breast cancer database to evaluate the method robustness. The area under the receiver operating characteristic curve is used to measure the performance of the method. Furthermore, both confusion matrix and accuracy are calculated to assess the results of the proposed algorithm.

Classification of cardiac-related artifacts in dynamic contrast breast MRI

NASA Astrophysics Data System (ADS)

Stegbauer, Keith C.; Smith, Justin P.; Niemeyer, Tanya L.; Wood, Chris

2004-05-01

Dynamic contrast breast MRI is becoming an important adjunct in screening women at high risk for breast cancer, determining extent of disease (staging) and monitoring response to therapy. In dynamic contrast breast MRI, regions of rapid contrast uptake indicate increases in vascularity which can be associated with abnormal tissue, sometimes significant for malignant disease. To show these areas of enhancement, subtractions between the pre and post contrast images and maximum intensity projections (MIPs) are computed. Many projections are obscured by normally enhancing anatomy (heart, aorta, pulmonary vessels). Identification of these structures allows their removal from MIPs, which improves image quality, diagnostic utility and the conspicuity of the enhancing regions. In this study, a fully automated classifier is presented which uses the spatial location of enhancing regions to separate those that occur inside the chest wall from those occurring in the tissue of interest (breast, axilla, chest wall). The classifier was trained on 21 studies each acquired at a different institution (699 clusters of pixels), and tested on 7 studies (231 clusters of pixels) that were not part of the training set. Multiple cost functions for training were examined. The measurements for the peak performance of the classifier were sensitivity 97.0%, specificity 99.4%, PPV 99.9%, NPV 78.8%.

Use of a multiseparation fiber optic probe for the optical diagnosis of breast cancer.

PubMed

Zhu, Changfang; Palmer, Gregory M; Breslin, Tara M; Xu, Fushen; Ramanujam, Nirmala

2005-01-01

We explore the effects of the illumination and collection geometry on optical spectroscopic diagnosis of breast cancer. Fluorescence and diffuse reflectance spectroscopy in the UV-visible spectral range are made with a multiseparation probe at three illumination-collection separations of 735, 980, and 1225 microm, respectively, from 13 malignant and 34 nonmalignant breast tissues. Statistical analysis is carried out on two types of data inputs: (1) the fluorescence and diffuse reflectance spectra recorded at each of the three illumination-collection separations and (2) the integrated fluorescence (at each excitation wavelength) or diffuse reflectance over the entire spectrum at all three illumination-collection separations. The results show that using the integrated fluorescence intensities recorded at a single excitation wavelength at all three illumination-collection separations can discriminate malignant from nonmalignant breast tissues with similar classification accuracy to that using spectral data measured at several excitation wavelengths with a single illumination-collection separation. These findings have significant implications with respect to the design of an optical system for breast cancer diagnosis. Examining the intensity attenuation at a single wavelength rather than spectral intensities at multiple wavelengths can significantly reduce the measurement and data processing time in a clinical setting as well as the cost and complexity of the optical system. Copyright 2005 Society of Photo-Optical Instrumentation Engineers.

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

PubMed

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

2015-01-01

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

Classifying breast cancer surgery: a novel, complexity-based system for oncological, oncoplastic and reconstructive procedures, and proof of principle by analysis of 1225 operations in 1166 patients.

PubMed

Hoffmann, Jürgen; Wallwiener, Diethelm

2009-04-08

One of the basic prerequisites for generating evidence-based data is the availability of classification systems. Attempts to date to classify breast cancer operations have focussed on specific problems, e.g. the avoidance of secondary corrective surgery for surgical defects, rather than taking a generic approach. Starting from an existing, simpler empirical scheme based on the complexity of breast surgical procedures, which was used in-house primarily in operative report-writing, a novel classification of ablative and breast-conserving procedures initially needed to be developed and elaborated systematically. To obtain proof of principle, a prospectively planned analysis of patient records for all major breast cancer-related operations performed at our breast centre in 2005 and 2006 was conducted using the new classification. Data were analysed using basic descriptive statistics such as frequency tables. A novel two-type, six-tier classification system comprising 12 main categories, 13 subcategories and 39 sub-subcategories of oncological, oncoplastic and reconstructive breast cancer-related surgery was successfully developed. Our system permitted unequivocal classification, without exception, of all 1225 procedures performed in 1166 breast cancer patients in 2005 and 2006. Breast cancer-related surgical procedures can be generically classified according to their surgical complexity. Analysis of all major procedures performed at our breast centre during the study period provides proof of principle for this novel classification system. We envisage various applications for this classification, including uses in randomised clinical trials, guideline development, specialist surgical training, continuing professional development as well as quality of care and public health research.

SDL: Saliency-Based Dictionary Learning Framework for Image Similarity.

PubMed

Sarkar, Rituparna; Acton, Scott T

2018-02-01

In image classification, obtaining adequate data to learn a robust classifier has often proven to be difficult in several scenarios. Classification of histological tissue images for health care analysis is a notable application in this context due to the necessity of surgery, biopsy or autopsy. To adequately exploit limited training data in classification, we propose a saliency guided dictionary learning method and subsequently an image similarity technique for histo-pathological image classification. Salient object detection from images aids in the identification of discriminative image features. We leverage the saliency values for the local image regions to learn a dictionary and respective sparse codes for an image, such that the more salient features are reconstructed with smaller error. The dictionary learned from an image gives a compact representation of the image itself and is capable of representing images with similar content, with comparable sparse codes. We employ this idea to design a similarity measure between a pair of images, where local image features of one image, are encoded with the dictionary learned from the other and vice versa. To effectively utilize the learned dictionary, we take into account the contribution of each dictionary atom in the sparse codes to generate a global image representation for image comparison. The efficacy of the proposed method was evaluated using three tissue data sets that consist of mammalian kidney, lung and spleen tissue, breast cancer, and colon cancer tissue images. From the experiments, we observe that our methods outperform the state of the art with an increase of 14.2% in the average classification accuracy over all data sets.

How specific Raman spectroscopic models are: a comparative study between different cancers

NASA Astrophysics Data System (ADS)

Singh, S. P.; Kumar, K. Kalyan; Chowdary, M. V. P.; Maheedhar, K.; Krishna, C. Murali

2010-02-01

Optical spectroscopic methods are being contemplated as adjunct/ alternative to existing 'Gold standard' of cancer diagnosis, histopathological examination. Several groups are actively pursuing diagnostic applications of Ramanspectroscopy in cancers. We have developed Raman spectroscopic models for diagnosis of breast, oral, stomach, colon and larynx cancers. So far, specificity and applicability of spectral- models has been limited to particular tissue origin. In this study we have evaluated explicitly of spectroscopic-models by analyzing spectra from already developed spectralmodels representing normal and malignant tissues of breast (46), cervix (52), colon (25), larynx (53), and oral (47). Spectral data was analyzed by Principal Component Analysis (PCA) using scores of factor, Mahalanobis distance and Spectral residuals as discriminating parameters. Multiparametric limit test approach was also explored. The preliminary unsupervised PCA of pooled data indicates that normal tissue types were always exclusive from their malignant counterparts. But when we consider tissue of different origin, large overlap among clusters was found. Supervised analysis by Mahalanobis distance and spectral residuals gave similar results. The 'limit test' approach where classification is based on match / mis-match of the given spectrum against all the available spectra has revealed that spectral models are very exclusive and specific. For example breast normal spectral model show matches only with breast normal spectra and mismatch to rest of the spectra. Same pattern was seen for most of spectral models. Therefore, results of the study indicate the exclusiveness and efficacy of Raman spectroscopic-models. Prospectively, these findings might open new application of Raman spectroscopic models in identifying a tumor as primary or metastatic.

Population of 224 realistic human subject-based computational breast phantoms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erickson, David W.; Wells, Jered R., E-mail: jered.wells@duke.edu; Sturgeon, Gregory M.

Purpose: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. Methods: A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was thenmore » applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. Results: After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. Conclusions: This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns.« less

Population of 224 realistic human subject-based computational breast phantoms

PubMed Central

Erickson, David W.; Wells, Jered R.; Sturgeon, Gregory M.; Dobbins, James T.; Segars, W. Paul; Lo, Joseph Y.

2016-01-01

Purpose: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. Methods: A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was then applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. Results: After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. Conclusions: This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns. PMID:26745896

Single-band upconversion nanoprobes for multiplexed simultaneous in situ molecular mapping of cancer biomarkers.

PubMed

Zhou, Lei; Wang, Rui; Yao, Chi; Li, Xiaomin; Wang, Chengli; Zhang, Xiaoyan; Xu, Congjian; Zeng, Aijun; Zhao, Dongyuan; Zhang, Fan

2015-04-24

The identification of potential diagnostic markers and target molecules among the plethora of tumour oncoproteins for cancer diagnosis requires facile technology that is capable of quantitatively analysing multiple biomarkers in tumour cells and tissues. Diagnostic and prognostic classifications of human tumours are currently based on the western blotting and single-colour immunohistochemical methods that are not suitable for multiplexed detection. Herein, we report a general and novel method to prepare single-band upconversion nanoparticles with different colours. The expression levels of three biomarkers in breast cancer cells were determined using single-band upconversion nanoparticles, western blotting and immunohistochemical technologies with excellent correlation. Significantly, the application of antibody-conjugated single-band upconversion nanoparticle molecular profiling technology can achieve the multiplexed simultaneous in situ biodetection of biomarkers in breast cancer cells and tissue specimens and produce more accurate results for the simultaneous quantification of proteins present at low levels compared with classical immunohistochemical technology.

Computational selection of antibody-drug conjugate targets for breast cancer

PubMed Central

Fauteux, François; Hill, Jennifer J.; Jaramillo, Maria L.; Pan, Youlian; Phan, Sieu; Famili, Fazel; O'Connor-McCourt, Maureen

2016-01-01

The selection of therapeutic targets is a critical aspect of antibody-drug conjugate research and development. In this study, we applied computational methods to select candidate targets overexpressed in three major breast cancer subtypes as compared with a range of vital organs and tissues. Microarray data corresponding to over 8,000 tissue samples were collected from the public domain. Breast cancer samples were classified into molecular subtypes using an iterative ensemble approach combining six classification algorithms and three feature selection techniques, including a novel kernel density-based method. This feature selection method was used in conjunction with differential expression and subcellular localization information to assemble a primary list of targets. A total of 50 cell membrane targets were identified, including one target for which an antibody-drug conjugate is in clinical use, and six targets for which antibody-drug conjugates are in clinical trials for the treatment of breast cancer and other solid tumors. In addition, 50 extracellular proteins were identified as potential targets for non-internalizing strategies and alternative modalities. Candidate targets linked with the epithelial-to-mesenchymal transition were identified by analyzing differential gene expression in epithelial and mesenchymal tumor-derived cell lines. Overall, these results show that mining human gene expression data has the power to select and prioritize breast cancer antibody-drug conjugate targets, and the potential to lead to new and more effective cancer therapeutics. PMID:26700623

Contour classification in thermographic images for detection of breast cancer

NASA Astrophysics Data System (ADS)

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

2016-09-01

Thermographic images of breast taken by the Braster device are uploaded into web application which uses different classification algorithms to automatically decide whether a patient should be more thoroughly examined. This article presents the approach to the task of classifying contours visible on thermographic images of breast taken by the Braster device in order to make the decision about the existence of cancerous tumors in breast. It presents the results of the researches conducted on the different classification algorithms.

Breast fat volume measurement using wide-bore 3 T MRI: comparison of traditional mammographic density evaluation with MRI density measurements using automatic segmentation.

PubMed

Petridou, E; Kibiro, M; Gladwell, C; Malcolm, P; Toms, A; Juette, A; Borga, M; Dahlqvist Leinhard, O; Romu, T; Kasmai, B; Denton, E

2017-07-01

To compare magnetic resonance imaging (MRI)-derived breast density measurements using automatic segmentation algorithms with radiologist estimations using the Breast Imaging Reporting and Data Systems (BI-RADS) density classification. Forty women undergoing mammography and dynamic breast MRI as part of their clinical management were recruited. Fat-water separated MRI images derived from a two-point Dixon technique, phase-sensitive reconstruction, and atlas-based segmentation were obtained before and after intravenous contrast medium administration. Breast density was assessed using software from Advanced MR Analytics (AMRA), Linköping, Sweden, with results compared to the widely used four-quartile quantitative BI-RADS scale. The proportion of glandular tissue in the breast on MRI was derived from the AMRA sequence. The mean unenhanced breast density was 0.31±0.22 (mean±SD; left) and 0.29±0.21 (right). Mean breast density on post-contrast images was 0.32±0.19 (left) and 0.32±0.2 (right). There was "almost perfect" correlation between pre- and post-contrast breast density quantification: Spearman's correlation rho=0.98 (95% confidence intervals [CI]: 0.97-0.99; left) and rho=0.99 (95% CI: 0.98-0.99; right). The 95% limits of agreement were -0.11-0.08 (left) and -0.08-0.03 (right). Interobserver reliability for BI-RADS was "substantial": weighted Kappa k=0.8 (95% CI: 0.74-0.87). The Spearman correlation coefficient between BI-RADS and MRI breast density was rho=0.73 (95% CI: 0.60-0.82; left) and rho=0.75 (95% CI: 0.63-0.83; right) which was also "substantial". The AMRA sequence provides a fully automated, reproducible, objective assessment of fibroglandular breast tissue proportion that correlates well with mammographic assessment of breast density with the added advantage of avoidance of ionising radiation. Copyright © 2017 The Royal College of Radiologists. All rights reserved.

Practical protocols for fast histopathology by Fourier transform infrared spectroscopic imaging

NASA Astrophysics Data System (ADS)

Keith, Frances N.; Reddy, Rohith K.; Bhargava, Rohit

2008-02-01

Fourier transform infrared (FT-IR) spectroscopic imaging is an emerging technique that combines the molecular selectivity of spectroscopy with the spatial specificity of optical microscopy. We demonstrate a new concept in obtaining high fidelity data using commercial array detectors coupled to a microscope and Michelson interferometer. Next, we apply the developed technique to rapidly provide automated histopathologic information for breast cancer. Traditionally, disease diagnoses are based on optical examinations of stained tissue and involve a skilled recognition of morphological patterns of specific cell types (histopathology). Consequently, histopathologic determinations are a time consuming, subjective process with innate intra- and inter-operator variability. Utilizing endogenous molecular contrast inherent in vibrational spectra, specially designed tissue microarrays and pattern recognition of specific biochemical features, we report an integrated algorithm for automated classifications. The developed protocol is objective, statistically significant and, being compatible with current tissue processing procedures, holds potential for routine clinical diagnoses. We first demonstrate that the classification of tissue type (histology) can be accomplished in a manner that is robust and rigorous. Since data quality and classifier performance are linked, we quantify the relationship through our analysis model. Last, we demonstrate the application of the minimum noise fraction (MNF) transform to improve tissue segmentation.

Dual-modal cancer detection based on optical pH sensing and Raman spectroscopy

NASA Astrophysics Data System (ADS)

Kim, Soogeun; Lee, Seung Ho; Min, Sun Young; Byun, Kyung Min; Lee, Soo Yeol

2017-10-01

A dual-modal approach using Raman spectroscopy and optical pH sensing was investigated to discriminate between normal and cancerous tissues. Raman spectroscopy has demonstrated the potential for in vivo cancer detection. However, Raman spectroscopy has suffered from strong fluorescence background of biological samples and subtle spectral differences between normal and disease tissues. To overcome those issues, pH sensing is adopted to Raman spectroscopy as a dual-modal approach. Based on the fact that the pH level in cancerous tissues is lower than that in normal tissues due to insufficient vasculature formation, the dual-modal approach combining the chemical information of Raman spectrum and the metabolic information of pH level can improve the specificity of cancer diagnosis. From human breast tissue samples, Raman spectra and pH levels are measured using fiber-optic-based Raman and pH probes, respectively. The pH sensing is based on the dependence of pH level on optical transmission spectrum. Multivariate statistical analysis is performed to evaluate the classification capability of the dual-modal method. The analytical results show that the dual-modal method based on Raman spectroscopy and optical pH sensing can improve the performance of cancer classification.

A taxonomy of epithelial human cancer and their metastases

PubMed Central

2009-01-01

Background Microarray technology has allowed to molecularly characterize many different cancer sites. This technology has the potential to individualize therapy and to discover new drug targets. However, due to technological differences and issues in standardized sample collection no study has evaluated the molecular profile of epithelial human cancer in a large number of samples and tissues. Additionally, it has not yet been extensively investigated whether metastases resemble their tissue of origin or tissue of destination. Methods We studied the expression profiles of a series of 1566 primary and 178 metastases by unsupervised hierarchical clustering. The clustering profile was subsequently investigated and correlated with clinico-pathological data. Statistical enrichment of clinico-pathological annotations of groups of samples was investigated using Fisher exact test. Gene set enrichment analysis (GSEA) and DAVID functional enrichment analysis were used to investigate the molecular pathways. Kaplan-Meier survival analysis and log-rank tests were used to investigate prognostic significance of gene signatures. Results Large clusters corresponding to breast, gastrointestinal, ovarian and kidney primary tissues emerged from the data. Chromophobe renal cell carcinoma clustered together with follicular differentiated thyroid carcinoma, which supports recent morphological descriptions of thyroid follicular carcinoma-like tumors in the kidney and suggests that they represent a subtype of chromophobe carcinoma. We also found an expression signature identifying primary tumors of squamous cell histology in multiple tissues. Next, a subset of ovarian tumors enriched with endometrioid histology clustered together with endometrium tumors, confirming that they share their etiopathogenesis, which strongly differs from serous ovarian tumors. In addition, the clustering of colon and breast tumors correlated with clinico-pathological characteristics. Moreover, a signature was developed based on our unsupervised clustering of breast tumors and this was predictive for disease-specific survival in three independent studies. Next, the metastases from ovarian, breast, lung and vulva cluster with their tissue of origin while metastases from colon showed a bimodal distribution. A significant part clusters with tissue of origin while the remaining tumors cluster with the tissue of destination. Conclusion Our molecular taxonomy of epithelial human cancer indicates surprising correlations over tissues. This may have a significant impact on the classification of many cancer sites and may guide pathologists, both in research and daily practice. Moreover, these results based on unsupervised analysis yielded a signature predictive of clinical outcome in breast cancer. Additionally, we hypothesize that metastases from gastrointestinal origin either remember their tissue of origin or adapt to the tissue of destination. More specifically, colon metastases in the liver show strong evidence for such a bimodal tissue specific profile. PMID:20017941

Intratumoral heterogeneity as a source of discordance in breast cancer biomarker classification.

PubMed

Allott, Emma H; Geradts, Joseph; Sun, Xuezheng; Cohen, Stephanie M; Zirpoli, Gary R; Khoury, Thaer; Bshara, Wiam; Chen, Mengjie; Sherman, Mark E; Palmer, Julie R; Ambrosone, Christine B; Olshan, Andrew F; Troester, Melissa A

2016-06-28

Spatial heterogeneity in biomarker expression may impact breast cancer classification. The aims of this study were to estimate the frequency of spatial heterogeneity in biomarker expression within tumors, to identify technical and biological factors contributing to spatial heterogeneity, and to examine the impact of discordant biomarker status within tumors on clinical record agreement. Tissue microarrays (TMAs) were constructed using two to four cores (1.0 mm) for each of 1085 invasive breast cancers from the Carolina Breast Cancer Study, which is part of the AMBER Consortium. Immunohistochemical staining for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) was quantified using automated digital imaging analysis. The biomarker status for each core and for each case was assigned using clinical thresholds. Cases with core-to-core biomarker discordance were manually reviewed to distinguish intratumoral biomarker heterogeneity from misclassification of biomarker status by the automated algorithm. The impact of core-to-core biomarker discordance on case-level agreement between TMAs and the clinical record was evaluated. On the basis of automated analysis, discordant biomarker status between TMA cores occurred in 9 %, 16 %, and 18 % of cases for ER, PR, and HER2, respectively. Misclassification of benign epithelium and/or ductal carcinoma in situ as invasive carcinoma by the automated algorithm was implicated in discordance among cores. However, manual review of discordant cases confirmed spatial heterogeneity as a source of discordant biomarker status between cores in 2 %, 7 %, and 8 % of cases for ER, PR, and HER2, respectively. Overall, agreement between TMA and clinical record was high for ER (94 %), PR (89 %), and HER2 (88 %), but it was reduced in cases with core-to-core discordance (agreement 70 % for ER, 61 % for PR, and 57 % for HER2). Intratumoral biomarker heterogeneity may impact breast cancer classification accuracy, with implications for clinical management. Both manually confirmed biomarker heterogeneity and misclassification of biomarker status by automated image analysis contribute to discordant biomarker status between TMA cores. Given that manually confirmed heterogeneity is uncommon (<10 % of cases), large studies are needed to study the impact of heterogeneous biomarker expression on breast cancer classification and outcomes.

Analysis of framelets for breast cancer diagnosis.

PubMed

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.

Bmi-1 promotes invasion and metastasis, and its elevated expression is correlated with an advanced stage of breast cancer

PubMed Central

2011-01-01

Background B-lymphoma Moloney murine leukemia virus insertion region-1 (Bmi-1) acts as an oncogene in various tumors, and its overexpression correlates with a poor outcome in several human cancers. Ectopic expression of Bmi-1 can induce epithelial-mesenchymal transition (EMT) and enhance the motility and invasiveness of human nasopharyngeal epithelial cells (NPECs), whereas silencing endogenous Bmi-1 expression can reverse EMT and reduce the metastatic potential of nasopharyngeal cancer cells (NPCs). Mouse xenograft studies indicate that coexpression of Bmi-1 and H-Ras in breast cancer cells can induce an aggressive and metastatic phenotype with an unusual occurrence of brain metastasis; although, Bmi-1 overexpression did not result in oncogenic transformation of MCF-10A cells. However, the underlying molecular mechanism of Bmi-1-mediated progression and the metastasis of breast cancer are not fully elucidated at this time. Results Bmi-1 expression is more pronouncedly increased in primary cancer tissues compared to matched adjacent non-cancerous tissues. High Bmi-1 expression is correlated with advanced clinicopathologic classifications (T, N, and M) and clinical stages. Furthermore, a high level of Bmi-1 indicates an unfavorable overall survival and serves as a high risk marker for breast cancer. In addition, inverse transcriptional expression levels of Bmi-1 and E-cadherin are detected between the primary cancer tissues and the matched adjacent non-cancerous tissues. Higher Bmi-1 levels are found in the cancer tissue, whereas the paired adjacent non-cancer tissue shows higher E-cadherin levels. Overexpression of Bmi-1 increases the motility and invasive properties of immortalized human mammary epithelial cells, which is concurrent with the increased expression of mesenchymal markers, the decreased expression of epithelial markers, the stabilization of Snail and the dysregulation of the Akt/GSK3β pathway. Consistent with these observations, the repression of Bmi-1 in highly metastatic breast cancer cells remarkably reduces cellular motility, invasion and transformation, as well as tumorigenesis and lung metastases in nude mice. In addition, the repression of Bmi-1 reverses the expression of EMT markers and inhibits the Akt/GSK3β/Snail pathway. Conclusions This study demonstrates that Bmi-1 promotes the invasion and metastasis of human breast cancer and predicts poor survival. PMID:21276221

Automatic breast density classification using a convolutional neural network architecture search procedure

NASA Astrophysics Data System (ADS)

Fonseca, Pablo; Mendoza, Julio; Wainer, Jacques; Ferrer, Jose; Pinto, Joseph; Guerrero, Jorge; Castaneda, Benjamin

2015-03-01

Breast parenchymal density is considered a strong indicator of breast cancer risk and therefore useful for preventive tasks. Measurement of breast density is often qualitative and requires the subjective judgment of radiologists. Here we explore an automatic breast composition classification workflow based on convolutional neural networks for feature extraction in combination with a support vector machines classifier. This is compared to the assessments of seven experienced radiologists. The experiments yielded an average kappa value of 0.58 when using the mode of the radiologists' classifications as ground truth. Individual radiologist performance against this ground truth yielded kappa values between 0.56 and 0.79.

High Resolution X-Ray Phase Contrast Imaging With Acoustic Tissue-Selective Contrast Enhancement

DTIC Science & Technology

2006-06-01

1999). 17. Sarvazyan, A. P. Shear Wave Elasticity Imaging: A New Ultrasonic Technology of Medical Diagnostics. Ultrasound in Medicine and Biology 24... elastography 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON USAMRMC a...Body Figure 2 shows the results of a set of experiments involving a simulated breast . The phantom (purchased from CIR, Inc.) was designed to

Computer-aided classification of breast masses using contrast-enhanced digital mammograms

NASA Astrophysics Data System (ADS)

Danala, Gopichandh; Aghaei, Faranak; Heidari, Morteza; Wu, Teresa; Patel, Bhavika; Zheng, Bin

2018-02-01

By taking advantages of both mammography and breast MRI, contrast-enhanced digital mammography (CEDM) has emerged as a new promising imaging modality to improve efficacy of breast cancer screening and diagnosis. The primary objective of study is to develop and evaluate a new computer-aided detection and diagnosis (CAD) scheme of CEDM images to classify between malignant and benign breast masses. A CEDM dataset consisting of 111 patients (33 benign and 78 malignant) was retrospectively assembled. Each case includes two types of images namely, low-energy (LE) and dual-energy subtracted (DES) images. First, CAD scheme applied a hybrid segmentation method to automatically segment masses depicting on LE and DES images separately. Optimal segmentation results from DES images were also mapped to LE images and vice versa. Next, a set of 109 quantitative image features related to mass shape and density heterogeneity was initially computed. Last, four multilayer perceptron-based machine learning classifiers integrated with correlationbased feature subset evaluator and leave-one-case-out cross-validation method was built to classify mass regions depicting on LE and DES images, respectively. Initially, when CAD scheme was applied to original segmentation of DES and LE images, the areas under ROC curves were 0.7585+/-0.0526 and 0.7534+/-0.0470, respectively. After optimal segmentation mapping from DES to LE images, AUC value of CAD scheme significantly increased to 0.8477+/-0.0376 (p<0.01). Since DES images eliminate overlapping effect of dense breast tissue on lesions, segmentation accuracy was significantly improved as compared to regular mammograms, the study demonstrated that computer-aided classification of breast masses using CEDM images yielded higher performance.

Brain metastasis detection by resonant Raman optical biopsy method

NASA Astrophysics Data System (ADS)

Zhou, Yan; Liu, Cheng-hui; Cheng, Gangge; Zhou, Lixin; Zhang, Chunyuan; Pu, Yang; Li, Zhongwu; Liu, Yulong; Li, Qingbo; Wang, Wei; Alfano, Robert R.

2014-03-01

Resonant Raman (RR) spectroscopy provides an effective way to enhance Raman signal from particular bonds associated with key molecules due to changes on a molecular level. In this study, RR is used for detection of human brain metastases of five kinds of primary organs of lung, breast, kidney, rectal and orbital in ex-vivo. The RR spectra of brain metastases cancerous tissues were measured and compared with those of normal brain tissues and the corresponding primary cancer tissues. The differences of five types of brain metastases tissues in key bio-components of carotene, tryptophan, lactate, alanine and methyl/methylene group were investigated. The SVM-KNN classifier was used to categorize a set of RR spectra data of brain metastasis of lung cancerous tissues from normal brain tissue, yielding diagnostic sensitivity and specificity at 100% and 75%, respectively. The RR spectroscopy may provide new moleculebased optical probe tools for diagnosis and classification of brain metastatic of cancers.

Comparison of subjective and fully automated methods for measuring mammographic density.

PubMed

Moshina, Nataliia; Roman, Marta; Sebuødegård, Sofie; Waade, Gunvor G; Ursin, Giske; Hofvind, Solveig

2018-02-01

Background Breast radiologists of the Norwegian Breast Cancer Screening Program subjectively classified mammographic density using a three-point scale between 1996 and 2012 and changed into the fourth edition of the BI-RADS classification since 2013. In 2015, an automated volumetric breast density assessment software was installed at two screening units. Purpose To compare volumetric breast density measurements from the automated method with two subjective methods: the three-point scale and the BI-RADS density classification. Material and Methods Information on subjective and automated density assessment was obtained from screening examinations of 3635 women recalled for further assessment due to positive screening mammography between 2007 and 2015. The score of the three-point scale (I = fatty; II = medium dense; III = dense) was available for 2310 women. The BI-RADS density score was provided for 1325 women. Mean volumetric breast density was estimated for each category of the subjective classifications. The automated software assigned volumetric breast density to four categories. The agreement between BI-RADS and volumetric breast density categories was assessed using weighted kappa (k w ). Results Mean volumetric breast density was 4.5%, 7.5%, and 13.4% for categories I, II, and III of the three-point scale, respectively, and 4.4%, 7.5%, 9.9%, and 13.9% for the BI-RADS density categories, respectively ( P for trend < 0.001 for both subjective classifications). The agreement between BI-RADS and volumetric breast density categories was k w  = 0.5 (95% CI = 0.47-0.53; P < 0.001). Conclusion Mean values of volumetric breast density increased with increasing density category of the subjective classifications. The agreement between BI-RADS and volumetric breast density categories was moderate.

Antibody-supervised deep learning for quantification of tumor-infiltrating immune cells in hematoxylin and eosin stained breast cancer samples.

PubMed

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

2016-01-01

Immune cell infiltration in tumor is an emerging prognostic biomarker in breast cancer. The gold standard for quantification of immune cells in tissue sections is visual assessment through a microscope, which is subjective and semi-quantitative. In this study, we propose and evaluate an approach based on antibody-guided annotation and deep learning to quantify immune cell-rich areas in hematoxylin and eosin (H&E) stained samples. Consecutive sections of formalin-fixed parafin-embedded samples obtained from the primary tumor of twenty breast cancer patients were cut and stained with H&E and the pan-leukocyte CD45 antibody. The stained slides were digitally scanned, and a training set of immune cell-rich and cell-poor tissue regions was annotated in H&E whole-slide images using the CD45-expression as a guide. In analysis, the images were divided into small homogenous regions, superpixels, from which features were extracted using a pretrained convolutional neural network (CNN) and classified with a support of vector machine. The CNN approach was compared to texture-based classification and to visual assessments performed by two pathologists. In a set of 123,442 labeled superpixels, the CNN approach achieved an F-score of 0.94 (range: 0.92-0.94) in discrimination of immune cell-rich and cell-poor regions, as compared to an F-score of 0.88 (range: 0.87-0.89) obtained with the texture-based classification. When compared to visual assessment of 200 images, an agreement of 90% (κ = 0.79) to quantify immune infiltration with the CNN approach was achieved while the inter-observer agreement between pathologists was 90% (κ = 0.78). Our findings indicate that deep learning can be applied to quantify immune cell infiltration in breast cancer samples using a basic morphology staining only. A good discrimination of immune cell-rich areas was achieved, well in concordance with both leukocyte antigen expression and pathologists' visual assessment.

Breast dose in mammography is about 30% lower when realistic heterogeneous glandular distributions are considered

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hernandez, Andrew M., E-mail: amhern@ucdavis.edu; Seibert, J. Anthony; Boone, John M.

2015-11-15

Purpose: Current dosimetry methods in mammography assume that the breast is comprised of a homogeneous mixture of glandular and adipose tissues. Three-dimensional (3D) dedicated breast CT (bCT) data sets were used previously to assess the complex anatomical structure within the breast, characterizing the statistical distribution of glandular tissue in the breast. The purpose of this work was to investigate the effect of bCT-derived heterogeneous glandular distributions on dosimetry in mammography. Methods: bCT-derived breast diameters, volumes, and 3D fibroglandular distributions were used to design realistic compressed breast models comprised of heterogeneous distributions of glandular tissue. The bCT-derived glandular distributions were fitmore » to biGaussian functions and used as probability density maps to assign the density distributions within compressed breast models. The MCNPX 2.6.0 Monte Carlo code was used to estimate monoenergetic normalized mean glandular dose “DgN(E)” values in mammography geometry. The DgN(E) values were then weighted by typical mammography x-ray spectra to determine polyenergetic DgN (pDgN) coefficients for heterogeneous (pDgN{sub hetero}) and homogeneous (pDgN{sub homo}) cases. The dependence of estimated pDgN values on phantom size, volumetric glandular fraction (VGF), x-ray technique factors, and location of the heterogeneous glandular distributions was investigated. Results: The pDgN{sub hetero} coefficients were on average 35.3% (SD, 4.1) and 24.2% (SD, 3.0) lower than the pDgN{sub homo} coefficients for the Mo–Mo and W–Rh x-ray spectra, respectively, across all phantom sizes and VGFs when the glandular distributions were centered within the breast phantom in the coronal plane. At constant breast size, increasing VGF from 7.3% to 19.1% lead to a reduction in pDgN{sub hetero} relative to pDgN{sub homo} of 23.6%–27.4% for a W–Rh spectrum. Displacement of the glandular distribution, at a distance equal to 10% of the compressed breast width in the superior and inferior directions, resulted in a 37.3% and a −26.6% change in the pDgN{sub hetero} coefficient, respectively, relative to the centered distribution for the Mo–Mo spectrum. Lateral displacement of the glandular distribution, at a distance equal to 10% of the compressed breast width, resulted in a 1.5% change in the pDgN{sub hetero} coefficient relative to the centered distribution for the W–Rh spectrum. Conclusions: Introducing bCT-derived heterogeneous glandular distributions into mammography phantom design resulted in decreased glandular dose relative to the widely used homogeneous assumption. A homogeneous distribution overestimates the amount of glandular tissue near the entrant surface of the breast, where dose deposition is exponentially higher. While these findings are based on clinically measured distributions of glandular tissue using a large cohort of women, future work is required to improve the classification of glandular distributions based on breast size and overall glandular fraction.« less

Full Intelligent Cancer Classification of Thermal Breast Images to Assist Physician in Clinical Diagnostic Applications

PubMed Central

Lashkari, AmirEhsan; Pak, Fatemeh; Firouzmand, Mohammad

2016-01-01

Breast cancer is the most common type of cancer among women. The important key to treat the breast cancer is early detection of it because according to many pathological studies more than 75% – 80% of all abnormalities are still benign at primary stages; so in recent years, many studies and extensive research done to early detection of breast cancer with higher precision and accuracy. Infra-red breast thermography is an imaging technique based on recording temperature distribution patterns of breast tissue. Compared with breast mammography technique, thermography is more suitable technique because it is noninvasive, non-contact, passive and free ionizing radiation. In this paper, a full automatic high accuracy technique for classification of suspicious areas in thermogram images with the aim of assisting physicians in early detection of breast cancer has been presented. Proposed algorithm consists of four main steps: pre-processing & segmentation, feature extraction, feature selection and classification. At the first step, using full automatic operation, region of interest (ROI) determined and the quality of image improved. Using thresholding and edge detection techniques, both right and left breasts separated from each other. Then relative suspected areas become segmented and image matrix normalized due to the uniqueness of each person's body temperature. At feature extraction stage, 23 features, including statistical, morphological, frequency domain, histogram and Gray Level Co-occurrence Matrix (GLCM) based features are extracted from segmented right and left breast obtained from step 1. To achieve the best features, feature selection methods such as minimum Redundancy and Maximum Relevance (mRMR), Sequential Forward Selection (SFS), Sequential Backward Selection (SBS), Sequential Floating Forward Selection (SFFS), Sequential Floating Backward Selection (SFBS) and Genetic Algorithm (GA) have been used at step 3. Finally to classify and TH labeling procedures, different classifiers such as AdaBoost, Support Vector Machine (SVM), k-Nearest Neighbors (kNN), Naïve Bayes (NB) and probability Neural Network (PNN) are assessed to find the best suitable one. These steps are applied on different thermogram images degrees. The results obtained on native database showed the best and significant performance of the proposed algorithm in comprise to the similar studies. According to experimental results, GA combined with AdaBoost with the mean accuracy of 85.33% and 87.42% on the left and right breast images with 0 degree, GA combined with AdaBoost with mean accuracy of 85.17% on the left breast images with 45 degree and mRMR combined with AdaBoost with mean accuracy of 85.15% on the right breast images with 45 degree, and also GA combined with AdaBoost with a mean accuracy of 84.67% and 86.21%, on the left and right breast images with 90 degree, are the best combinations of feature selection and classifier for evaluation of breast images. PMID:27014608

Modified Treatment Algorithm for Pseudogynecomastia After Massive Weight Loss.

PubMed

Ziegler, Ulrich E; Lorenz, Udo; Daigeler, Adrien; Ziegler, Selina N; Zeplin, Philip H

2018-06-19

Pseudogynecomastia is the increased aggregation of fatty tissue in the area of the male breast with resultant female appearance. Two forms can appear: pseudogynecomastia after massive weight loss (pseudogynecomastia obese [PO]) and pseudogynecomastia, which is caused only by adipose tissue (pseudogynecomastia fat). For PO, only the Gusenoff classification with corresponding operative treatment options exists. However, this classification is limited by the fact that it underestimates the extensive variability of residual fat tissue and skin excess, both crucial factors for operative planning. For this reason, we propose a modification of the treatment algorithm for the Gusenoff classification based on our results to achieve more masculine results. A total of 43 male patients with PO were included in this retrospective study (grade 1a, n = 1; grade 1b, n = 1; grade 2, n = 17; grade 3, n = 24). Forty-two mastectomies with a free nipple-areola complex (NAC) transposition (grades 2 and 3) and 1 with a subcutaneous mastectomy (grade 1a) with periareolar lifting were performed. A retrospective chart review was performed to obtain data regarding age, body mass index, body mass index loss, weight loss, reason for weight loss, comorbidities, nicotine, and additional procedures, postoperative sensitive on the NAC transplants and complications. None of the free-nipple grafts were lost. Forty (95%) of 42 patients with mastectomy had a resensitivity on the NAC. For pseudogynecomastia, the treatment algorithm of the Gusenoff classification should be modified and adapted according to our recommendations to achieve more optimal masculine results.

Detection of soft tissue densities from digital breast tomosynthesis: comparison of conventional and deep learning approaches

NASA Astrophysics Data System (ADS)

Fotin, Sergei V.; Yin, Yin; Haldankar, Hrishikesh; Hoffmeister, Jeffrey W.; Periaswamy, Senthil

2016-03-01

Computer-aided detection (CAD) has been used in screening mammography for many years and is likely to be utilized for digital breast tomosynthesis (DBT). Higher detection performance is desirable as it may have an impact on radiologist's decisions and clinical outcomes. Recently the algorithms based on deep convolutional architectures have been shown to achieve state of the art performance in object classification and detection. Similarly, we trained a deep convolutional neural network directly on patches sampled from two-dimensional mammography and reconstructed DBT volumes and compared its performance to a conventional CAD algorithm that is based on computation and classification of hand-engineered features. The detection performance was evaluated on the independent test set of 344 DBT reconstructions (GE SenoClaire 3D, iterative reconstruction algorithm) containing 328 suspicious and 115 malignant soft tissue densities including masses and architectural distortions. Detection sensitivity was measured on a region of interest (ROI) basis at the rate of five detection marks per volume. Moving from conventional to deep learning approach resulted in increase of ROI sensitivity from 0:832 +/- 0:040 to 0:893 +/- 0:033 for suspicious ROIs; and from 0:852 +/- 0:065 to 0:930 +/- 0:046 for malignant ROIs. These results indicate the high utility of deep feature learning in the analysis of DBT data and high potential of the method for broader medical image analysis tasks.

Breast reconstruction - natural tissue

MedlinePlus

... flap; TUG; Mastectomy - breast reconstruction with natural tissue; Breast cancer - breast reconstruction with natural tissue ... it harder to find a tumor if your breast cancer comes back. The advantage of breast reconstruction with ...

Dual-modal cancer detection based on optical pH sensing and Raman spectroscopy.

PubMed

Kim, Soogeun; Lee, Seung Ho; Min, Sun Young; Byun, Kyung Min; Lee, Soo Yeol

2017-10-01

A dual-modal approach using Raman spectroscopy and optical pH sensing was investigated to discriminate between normal and cancerous tissues. Raman spectroscopy has demonstrated the potential for in vivo cancer detection. However, Raman spectroscopy has suffered from strong fluorescence background of biological samples and subtle spectral differences between normal and disease tissues. To overcome those issues, pH sensing is adopted to Raman spectroscopy as a dual-modal approach. Based on the fact that the pH level in cancerous tissues is lower than that in normal tissues due to insufficient vasculature formation, the dual-modal approach combining the chemical information of Raman spectrum and the metabolic information of pH level can improve the specificity of cancer diagnosis. From human breast tissue samples, Raman spectra and pH levels are measured using fiber-optic-based Raman and pH probes, respectively. The pH sensing is based on the dependence of pH level on optical transmission spectrum. Multivariate statistical analysis is performed to evaluate the classification capability of the dual-modal method. The analytical results show that the dual-modal method based on Raman spectroscopy and optical pH sensing can improve the performance of cancer classification. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

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

PubMed

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.

N-3 Polyunsaturated Fatty Acids of Marine Origin and Multifocality in Human Breast Cancer.

PubMed

Ouldamer, Lobna; Goupille, Caroline; Vildé, Anne; Arbion, Flavie; Body, Gilles; Chevalier, Stephan; Cottier, Jean Philippe; Bougnoux, Philippe

2016-01-01

The microenvironment of breast epithelial tissue may contribute to the clinical expression of breast cancer. Breast epithelial tissue, whether healthy or tumoral, is directly in contact with fat cells, which in turn could influence tumor multifocality. In this pilot study we investigated whether the fatty acid composition of breast adipose tissue differed according to breast cancer focality. Twenty-three consecutive women presenting with non-metastatic breast cancer underwent breast-imaging procedures including Magnetic Resonance Imaging prior to treatment. Breast adipose tissue specimens were collected during breast surgery. We established a biochemical profile of adipose tissue fatty acids by gas chromatography. We assessed whether there were differences according to breast cancer focality. We found that decreased levels in breast adipose tissue of docosahexaenoic and eicosapentaenoic acids, the two main polyunsaturated n-3 fatty acids of marine origin, were associated with multifocality. These differences in lipid content may contribute to mechanisms through which peritumoral adipose tissue fuels breast cancer multifocality.

Tuning to optimize SVM approach for assisting ovarian cancer diagnosis with photoacoustic imaging.

PubMed

Wang, Rui; Li, Rui; Lei, Yanyan; Zhu, Quing

2015-01-01

Support vector machine (SVM) is one of the most effective classification methods for cancer detection. The efficiency and quality of a SVM classifier depends strongly on several important features and a set of proper parameters. Here, a series of classification analyses, with one set of photoacoustic data from ovarian tissues ex vivo and a widely used breast cancer dataset- the Wisconsin Diagnostic Breast Cancer (WDBC), revealed the different accuracy of a SVM classification in terms of the number of features used and the parameters selected. A pattern recognition system is proposed by means of SVM-Recursive Feature Elimination (RFE) with the Radial Basis Function (RBF) kernel. To improve the effectiveness and robustness of the system, an optimized tuning ensemble algorithm called as SVM-RFE(C) with correlation filter was implemented to quantify feature and parameter information based on cross validation. The proposed algorithm is first demonstrated outperforming SVM-RFE on WDBC. Then the best accuracy of 94.643% and sensitivity of 94.595% were achieved when using SVM-RFE(C) to test 57 new PAT data from 19 patients. The experiment results show that the classifier constructed with SVM-RFE(C) algorithm is able to learn additional information from new data and has significant potential in ovarian cancer diagnosis.

Breast Imaging-Reporting and Data System (BI-RADS) classification in 51 excised palpable pediatric breast masses.

PubMed

Koning, Jeffrey L; Davenport, Katherine P; Poole, Patricia S; Kruk, Peter G; Grabowski, Julia E

2015-10-01

The American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) classification was developed to risk stratify breast lesions and guide surgical management based on imaging. Previous studies validating BI-RADS for US do not include pediatric patients. Most pediatric breast masses present as palpable lesions and frequently undergo ultrasound, which is often accompanied with a BI-RADS classification. Our study aimed to correlate BI-RADS with pathology findings to assess applicability of the classification system to pediatric patients. We performed a retrospective review of all patients who underwent excision of a breast mass at a single center from July 2010 to November 2013. We identified all patients who underwent preoperative ultrasound with BI-RADS classification. Demographic data, imaging results, and surgical pathology were analyzed and correlated. A total of 119 palpable masses were excised from 105 pediatric patients during the study period. Of 119 masses, 81 had preoperative ultrasound, and BI-RADS categories were given to 51 masses. Of these 51, all patients were female and the average age was 15.9 years. BI-RADS 4 was given to 25 of 51 masses (49%), and 100% of these lesions had benign pathology, the most common being fibroadenoma. Treatment algorithm based on BI-RADS classification may not be valid in pediatric patients. In this study, all patients with a BI-RADS 4 lesion had benign pathology. BI-RADS classification may overstate the risk of malignancy or need for biopsy in this population. Further validation of BI-RADS classification with large scale studies is needed in pediatric and adolescent patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data.

PubMed

Alakwaa, Fadhl M; Chaudhary, Kumardeep; Garmire, Lana X

2018-01-05

Metabolomics holds the promise as a new technology to diagnose highly heterogeneous diseases. Conventionally, metabolomics data analysis for diagnosis is done using various statistical and machine learning based classification methods. However, it remains unknown if deep neural network, a class of increasingly popular machine learning methods, is suitable to classify metabolomics data. Here we use a cohort of 271 breast cancer tissues, 204 positive estrogen receptor (ER+), and 67 negative estrogen receptor (ER-) to test the accuracies of feed-forward networks, a deep learning (DL) framework, as well as six widely used machine learning models, namely random forest (RF), support vector machines (SVM), recursive partitioning and regression trees (RPART), linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), and generalized boosted models (GBM). DL framework has the highest area under the curve (AUC) of 0.93 in classifying ER+/ER- patients, compared to the other six machine learning algorithms. Furthermore, the biological interpretation of the first hidden layer reveals eight commonly enriched significant metabolomics pathways (adjusted P-value <0.05) that cannot be discovered by other machine learning methods. Among them, protein digestion and absorption and ATP-binding cassette (ABC) transporters pathways are also confirmed in integrated analysis between metabolomics and gene expression data in these samples. In summary, deep learning method shows advantages for metabolomics based breast cancer ER status classification, with both the highest prediction accuracy (AUC = 0.93) and better revelation of disease biology. We encourage the adoption of feed-forward networks based deep learning method in the metabolomics research community for classification.

Aided diagnosis methods of breast cancer based on machine learning

NASA Astrophysics Data System (ADS)

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%.

A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images

PubMed Central

Xu, Jun; Luo, Xiaofei; Wang, Guanhao; Gilmore, Hannah; Madabhushi, Anant

2016-01-01

Epithelial (EP) and stromal (ST) are two types of tissues in histological images. Automated segmentation or classification of EP and ST tissues is important when developing computerized system for analyzing the tumor microenvironment. In this paper, a Deep Convolutional Neural Networks (DCNN) based feature learning is presented to automatically segment or classify EP and ST regions from digitized tumor tissue microarrays (TMAs). Current approaches are based on handcraft feature representation, such as color, texture, and Local Binary Patterns (LBP) in classifying two regions. Compared to handcrafted feature based approaches, which involve task dependent representation, DCNN is an end-to-end feature extractor that may be directly learned from the raw pixel intensity value of EP and ST tissues in a data driven fashion. These high-level features contribute to the construction of a supervised classifier for discriminating the two types of tissues. In this work we compare DCNN based models with three handcraft feature extraction based approaches on two different datasets which consist of 157 Hematoxylin and Eosin (H&E) stained images of breast cancer and 1376 immunohistological (IHC) stained images of colorectal cancer, respectively. The DCNN based feature learning approach was shown to have a F1 classification score of 85%, 89%, and 100%, accuracy (ACC) of 84%, 88%, and 100%, and Matthews Correlation Coefficient (MCC) of 86%, 77%, and 100% on two H&E stained (NKI and VGH) and IHC stained data, respectively. Our DNN based approach was shown to outperform three handcraft feature extraction based approaches in terms of the classification of EP and ST regions. PMID:28154470

A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images.

PubMed

Xu, Jun; Luo, Xiaofei; Wang, Guanhao; Gilmore, Hannah; Madabhushi, Anant

2016-05-26

Epithelial (EP) and stromal (ST) are two types of tissues in histological images. Automated segmentation or classification of EP and ST tissues is important when developing computerized system for analyzing the tumor microenvironment. In this paper, a Deep Convolutional Neural Networks (DCNN) based feature learning is presented to automatically segment or classify EP and ST regions from digitized tumor tissue microarrays (TMAs). Current approaches are based on handcraft feature representation, such as color, texture, and Local Binary Patterns (LBP) in classifying two regions. Compared to handcrafted feature based approaches, which involve task dependent representation, DCNN is an end-to-end feature extractor that may be directly learned from the raw pixel intensity value of EP and ST tissues in a data driven fashion. These high-level features contribute to the construction of a supervised classifier for discriminating the two types of tissues. In this work we compare DCNN based models with three handcraft feature extraction based approaches on two different datasets which consist of 157 Hematoxylin and Eosin (H&E) stained images of breast cancer and 1376 immunohistological (IHC) stained images of colorectal cancer, respectively. The DCNN based feature learning approach was shown to have a F1 classification score of 85%, 89%, and 100%, accuracy (ACC) of 84%, 88%, and 100%, and Matthews Correlation Coefficient (MCC) of 86%, 77%, and 100% on two H&E stained (NKI and VGH) and IHC stained data, respectively. Our DNN based approach was shown to outperform three handcraft feature extraction based approaches in terms of the classification of EP and ST regions.

Inter- and Intra-Observer Agreement in Ultrasound BI-RADS Classification and Real-Time Elastography Tsukuba Score Assessment of Breast Lesions.

PubMed

Schwab, Fabienne; Redling, Katharina; Siebert, Matthias; Schötzau, Andy; Schoenenberger, Cora-Ann; Zanetti-Dällenbach, Rosanna

2016-11-01

Our aim was to prospectively evaluate inter- and intra-observer agreement between Breast Imaging Reporting and Data System (BI-RADS) classifications and Tsukuba elasticity scores (TSs) of breast lesions. The study included 164 breast lesions (63 malignant, 101 benign). The BI-RADS classification and TS of each breast lesion was assessed by the examiner and twice by three reviewers at an interval of 2 months. Weighted κ values for inter-observer agreement ranged from moderate to substantial for BI-RADS classification (κ = 0.585-0.738) and was substantial for TS (κ = 0.608-0.779). Intra-observer agreement was almost perfect for ultrasound (US) BI-RADS (κ = 0.847-0.872) and TS (κ = 0.879-0.914). Overall, individual reviewers are highly self-consistent (almost perfect intra-observer agreement) with respect to BI-RADS classification and TS, whereas inter-observer agreement was moderate to substantial. Comprehensive training is essential for achieving high agreement and minimizing the impact of subjectivity. Our results indicate that breast US and real-time elastography can achieve high diagnostic performance. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Evidence That Breast Tissue Stiffness Is Associated with Risk of Breast Cancer

PubMed Central

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

2014-01-01

Background 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. Methods 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. Results 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. Conclusion 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. PMID:25010427

Lactational ectopic breast tissue of the vulva: case report and brief historical review.

PubMed

Pieh-Holder, Kelly L

2013-04-01

Ectopic breast tissue is defined as glands of breast tissue located outside of the normal anatomic breasts. Historically, ectopic breast tissue has been thought to arise from a remnant of the embryonic mammary ridge along the "milk line" or the midaxillary line from the axilla to the groin, including the vulvar region. Extramammary tissue displays the same pathologic and physiologic changes as normal breast tissue and is often discovered in multiparous women as the result of swelling from lactational activity. We present a case report of a gravid patient with lactating vulvar mass and a brief historical perspective of vulvar ectopic breast tissue.

Diagnosis of breast cancer by tissue analysis

PubMed Central

Bhattacharyya, Debnath; Bandyopadhyay, Samir Kumar

2013-01-01

In this paper, we propose a technique to locate abnormal growth of cells in breast tissue and suggest further pathological test, when require. We compare normal breast tissue with malignant invasive breast tissue by a series of image processing steps. Normal ductal epithelial cells and ductal/lobular invasive carcinogenic cells also consider for comparison here in this paper. In fact, features of cancerous breast tissue (invasive) are extracted and analyses with normal breast tissue. We also suggest the breast cancer recognition technique through image processing and prevention by controlling p53 gene mutation to some extent. PMID:23372340

Histological, molecular and functional subtypes of breast cancers

PubMed Central

Malhotra, Gautam K; Zhao, Xiangshan; Band, Hamid

2010-01-01

Increased understanding of the molecular heterogeneity that is intrinsic to the various subtypes of breast cancer will likely shape the future of breast cancer diagnosis, prognosis and treatment. Advances in the field over the last several decades have been remarkable and have clearly translated into better patient care as evidenced by the earlier detection, better prognosis and new targeted therapies. There have been two recent advances in the breast cancer research field that have lead to paradigm shifts: first, the identification of intrinsic breast tumor subtypes, which has changed the way we think about breast cancer and second, the recent characterization of cancer stem cells (CSCs), which are suspected to be responsible for tumor initiation, recurrence and resistance to therapy. These findings have opened new exciting avenues to think about breast cancer therapeutic strategies. While these advances constitute major paradigm shifts within the research realm, the clinical arena has yet to adopt and apply our understanding of the molecular basis of the disease to early diagnosis, prognosis and therapy of breast cancers. Here, we will review the current clinical approach to classification of breast cancers, newer molecular-based classification schemes and potential future of biomarkers representing a functional classification of breast cancer. PMID:21057215

Increased Capacity for Work and Productivity After Breast Reduction.

PubMed

Cabral, Isaias Vieira; Garcia, Edgard da Silva; Sobrinho, Rebecca Neponucena; Pinto, Natália Lana Larcher; Juliano, Yara; Veiga-Filho, Joel; Ferreira, Lydia Masako; Veiga, Daniela Francescato

2017-01-01

Breast hypertrophy is a prevalent condition among women worldwide, which can affect different aspects of their quality of life. The physical and emotional impact of breast hypertrophy may harm daily activities, including work. To assess the impact of reduction mammaplasty on the ability to work and productivity of women with breast hypertrophy. A total of 60 patients with breast hypertrophy, already scheduled for breast reduction, aged 18 to 60 years and who had formal or autonomous employment were prospectively enrolled. The Brazilian versions of two validated tools, Work Productivity and Activity Impairment - General Health (WPAI-GH) and Work Limitations Questionnaire (WLQ) were self-administered at the preoperative evaluation and six months following surgery. The median age was 33 years, median body mass index was 24 kg/m 2 , and the median total weight of resected breast tissue was 617.5 g. According to the Brazilian classification of occupation, most patients (53%) had technical, scientific, artistic and similar occupations. There was a significant improvement in work capacity and productivity six months after the reduction mammaplasty, denoted by a decrease in presenteeism, absenteeism, and WLQ Productivity Loss Score (Wilcoxon analysis of variance: P < .0001 for each of these domains). Reduction mammaplasty increases the work capacity and productivity of Brazilian women with breast hypertrophy. LEVEL OF EVIDENCE 4. © 2016 The American Society for Aesthetic Plastic Surgery, Inc. Reprints and permission: journals.permissions@oup.com.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Genomic Changes in Normal Breast Tissue in Women at Normal Risk or at High Risk for Breast Cancer

PubMed Central

Danforth, David N.

2016-01-01

Sporadic breast cancer develops through the accumulation of molecular abnormalities in normal breast tissue, resulting from exposure to estrogens and other carcinogens beginning at adolescence and continuing throughout life. These molecular changes may take a variety of forms, including numerical and structural chromosomal abnormalities, epigenetic changes, and gene expression alterations. To characterize these abnormalities, a review of the literature has been conducted to define the molecular changes in each of the above major genomic categories in normal breast tissue considered to be either at normal risk or at high risk for sporadic breast cancer. This review indicates that normal risk breast tissues (such as reduction mammoplasty) contain evidence of early breast carcinogenesis including loss of heterozygosity, DNA methylation of tumor suppressor and other genes, and telomere shortening. In normal tissues at high risk for breast cancer (such as normal breast tissue adjacent to breast cancer or the contralateral breast), these changes persist, and are increased and accompanied by aneuploidy, increased genomic instability, a wide range of gene expression differences, development of large cancerized fields, and increased proliferation. These changes are consistent with early and long-standing exposure to carcinogens, especially estrogens. A model for the breast carcinogenic pathway in normal risk and high-risk breast tissues is proposed. These findings should clarify our understanding of breast carcinogenesis in normal breast tissue and promote development of improved methods for risk assessment and breast cancer prevention in women. PMID:27559297

Breast Tissue Stromal Cells Preferentially Promote Generation of M2 Macrophages: A Novel Mechanism for Tumor Supportive Properties of Breast Microenvironment

DTIC Science & Technology

2011-08-01

macrophages (MQs), on growth of breast tumor cells, and (2) to test the hypothesis that MSCs of non -breast adipose tissues, in contrast to MSCs of...macrophages in normal and malignant tissues. In contrast to all studies focused on the role of breast tissue microenvironment in growth of primary breast...the phenotype of macrophages, provide an immune environment suitable for growth of breast cancer cells, but MSCs present in non -breast adipose

Concentration of cadmium, nickel and aluminium in female breast cancer.

PubMed

Romanowicz-Makowska, Hanna; Forma, Ewa; Bryś, Magdalena; Krajewska, Wanda M; Smolarz, Beata

2011-12-01

The aim of this study was to investigate the cadmium (Cd), nickel (Ni) and aluminium (Al) concentrations in female breast cancer and normal tissue. The concentration of metals in 16 non-cancerous breast tissues and 67 breast cancer samples was measured by flame atomic absorption spectrometry. In the case of normal breast tissue the concentrations were 0.61 ± 0.24 μg Cd/g dry tissue, 1.84 ± 0.67 μg Ni/g dry tissue, and 3.63 ± 1.00 μg Al/g dry tissue, whereas in breast cancer concentrations of metals were 0.76 ± 0.38 μg/g dry tissue, 2.26 ± 0.79 μg/g dry tissue, and 4.40 ± 1.82 μg/g dry tissue, respectively. The concentration of Cd and Al in normal breast tissue was significantly lower than in breast cancer. In the case of Ni concentration, we did not observe statistically significant differences between normal and cancerous tissue. There were no significant differences in concentration of studied metals, in breast cancer, in the context of age, menopausal status, and cancer histological grading. The data obtained show higher concentration of cadmium and aluminium and support a possible relationship between those metals and breast cancer.

Expression of BMI-1 and Mel-18 in breast tissue - a diagnostic marker in patients with breast cancer

PubMed Central

2010-01-01

Background Polycomb Group (PcG) proteins are epigenetic silencers involved in maintaining cellular identity, and their deregulation can result in cancer. Expression of Mel-18 and Bmi-1 has been studied in tumor tissue, but not in adjacent non-cancerous breast epithelium. Our study compares the expression of the two genes in normal breast epithelium of cancer patients and relates it to the level of expression in the corresponding tumors as well as in breast epithelium of healthy women. Methods A total of 79 tumors, of which 71 malignant tumors of the breast, 6 fibroadenomas, and 2 DCIS were studied and compared to the reduction mammoplastic specimens of 11 healthy women. In addition there was available adjacent cancer free tissue for 23 of the malignant tumors. The tissue samples were stored in RNAlater, RNA was isolated to create expression microarray profile. These two genes were then studied more closely first on mRNA transcription level by microarrays (Agilent 44 K) and quantitative RT-PCR (TaqMan) and then on protein expression level using immunohistochemistry. Results Bmi-1 mRNA is significantly up-regulated in adjacent normal breast tissue in breast cancer patients compared to normal breast tissue from noncancerous patients. Conversely, mRNA transcription level of Mel-18 is lower in normal breast from patients operated for breast cancer compared to breast tissue from mammoplasty. When protein expression of these two genes was evaluated, we observed that most of the epithelial cells were positive for Bmi-1 in both groups of tissue samples, although the expression intensity was stronger in normal tissue from cancer patients compared to mammoplasty tissue samples. Protein expression of Mel-18 showed inversely stronger intensity in tissue samples from mammoplasty compared to normal breast tissue from patients operated for breast cancer. Conclusion Bmi-1 mRNA level is consistently increased and Mel-18 mRNA level is consistently decreased in adjacent normal breast tissue of cancer patients as compared to normal breast tissue in women having had reduction mammoplasties. Bmi-1/Mel-18 ratio can be potentially used as a tool for stratifying women at risk of developing malignancy. PMID:21162745

SU-E-J-107: Supervised Learning Model of Aligned Collagen for Human Breast Carcinoma Prognosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bredfeldt, J; Liu, Y; Conklin, M

Purpose: Our goal is to develop and apply a set of optical and computational tools to enable large-scale investigations of the interaction between collagen and tumor cells. Methods: We have built a novel imaging system for automating the capture of whole-slide second harmonic generation (SHG) images of collagen in registry with bright field (BF) images of hematoxylin and eosin stained tissue. To analyze our images, we have integrated a suite of supervised learning tools that semi-automatically model and score collagen interactions with tumor cells via a variety of metrics, a method we call Electronic Tumor Associated Collagen Signatures (eTACS). Thismore » group of tools first segments regions of epithelial cells and collagen fibers from BF and SHG images respectively. We then associate fibers with groups of epithelial cells and finally compute features based on the angle of interaction and density of the collagen surrounding the epithelial cell clusters. These features are then processed with a support vector machine to separate cancer patients into high and low risk groups. Results: We validated our model by showing that eTACS produces classifications that have statistically significant correlation with manual classifications. In addition, our system generated classification scores that accurately predicted breast cancer patient survival in a cohort of 196 patients. Feature rank analysis revealed that TACS positive fibers are more well aligned with each other, generally lower density, and terminate within or near groups of epithelial cells. Conclusion: We are working to apply our model to predict survival in larger cohorts of breast cancer patients with a diversity of breast cancer types, predict response to treatments such as COX2 inhibitors, and to study collagen architecture changes in other cancer types. In the future, our system may be used to provide metastatic potential information to cancer patients to augment existing clinical assays.« less

A new hybrid method based on fuzzy-artificial immune system and k-nn algorithm for breast cancer diagnosis.

PubMed

Sahan, Seral; Polat, Kemal; Kodaz, Halife; Güneş, Salih

2007-03-01

The use of machine learning tools in medical diagnosis is increasing gradually. This is mainly because the effectiveness of classification and recognition systems has improved in a great deal to help medical experts in diagnosing diseases. Such a disease is breast cancer, which is a very common type of cancer among woman. As the incidence of this disease has increased significantly in the recent years, machine learning applications to this problem have also took a great attention as well as medical consideration. This study aims at diagnosing breast cancer with a new hybrid machine learning method. By hybridizing a fuzzy-artificial immune system with k-nearest neighbour algorithm, a method was obtained to solve this diagnosis problem via classifying Wisconsin Breast Cancer Dataset (WBCD). This data set is a very commonly used data set in the literature relating the use of classification systems for breast cancer diagnosis and it was used in this study to compare the classification performance of our proposed method with regard to other studies. We obtained a classification accuracy of 99.14%, which is the highest one reached so far. The classification accuracy was obtained via 10-fold cross validation. This result is for WBCD but it states that this method can be used confidently for other breast cancer diagnosis problems, too.

Classification and management of gynecomastia: defining the role of ultrasound-assisted liposuction.

PubMed

Rohrich, Rod J; Ha, Richard Y; Kenkel, Jeffrey M; Adams, William P

2003-02-01

Gynecomastia, or excessive male breast development, has an incidence of 32 to 65 percent in the male population. This condition has important physical and psychological impacts. Advances in elucidating the pathophysiology of gynecomastia have been made, though understanding remains limited. Recommendations for evaluation and workup have varied and are often arbitrary. A diagnostic algorithm is suggested, with emphasis on a comprehensive history, physical examination, and minimizing unnecessary diagnostic testing. Medical management has had limited success; surgical therapy, primarily through excisional techniques, has been the accepted standard. Although effective, excisional techniques subject patients to large, visible scars. Ultrasound-assisted liposuction has recently emerged as a safe and effective method for the treatment of gynecomastia. It is particularly efficient in the removal of the dense, fibrous male breast tissue while offering advantages in minimal external scarring. A new system of classification and graduated treatment is proposed, based on glandular versus fibrous hypertrophy and degree of breast ptosis (skin excess). The authors' series of 61 patients with gynecomastia from 1987 to 2000 at the University of Texas Southwestern Department of Plastic Surgery demonstrated an overall success rate of 86.9 percent using suction-assisted lipectomy (1987 to 1997) and ultrasound-assisted liposuction (1997 to 2000). The authors have found ultrasound-assisted liposuction to be effective in treating most grades of gynecomastia. Excisional techniques are reserved for severe gynecomastia with significant skin excess after attempted ultrasound-assisted liposuction.

Parenchymal texture measures weighted by breast anatomy: preliminary optimization in a case-control study

NASA Astrophysics Data System (ADS)

Gastounioti, Aimilia; Keller, Brad M.; Hsieh, Meng-Kang; Conant, Emily F.; Kontos, Despina

2016-03-01

Growing evidence suggests that quantitative descriptors of the parenchymal texture patterns hold a valuable role in assessing an individual woman's risk for breast cancer. In this work, we assess the hypothesis that breast cancer risk factors are not uniformly expressed in the breast parenchymal tissue and, therefore, breast-anatomy-weighted parenchymal texture descriptors, where different breasts ROIs have non uniform contributions, may enhance breast cancer risk assessment. To this end, we introduce an automated breast-anatomy-driven methodology which generates a breast atlas, which is then used to produce a weight map that reinforces the contributions of the central and upper-outer breast areas. We incorporate this methodology to our previously validated lattice-based strategy for parenchymal texture analysis. In the framework of a pilot case-control study, including digital mammograms from 424 women, our proposed breast-anatomy-weighted texture descriptors are optimized and evaluated against non weighted texture features, using regression analysis with leave-one-out cross validation. The classification performance is assessed in terms of the area under the curve (AUC) of the receiver operating characteristic. The collective discriminatory capacity of the weighted texture features was maximized (AUC=0.87) when the central breast area was considered more important than the upperouter area, with significant performance improvement (DeLong's test, p-value<0.05) against the non-weighted texture features (AUC=0.82). Our results suggest that breast-anatomy-driven methodologies have the potential to further upgrade the promising role of parenchymal texture analysis in breast cancer risk assessment and may serve as a reference in the design of future studies towards image-driven personalized recommendations regarding women's cancer risk evaluation.

Convolutional Neural Network for Histopathological Analysis of Osteosarcoma.

PubMed

Mishra, Rashika; Daescu, Ovidiu; Leavey, Patrick; Rakheja, Dinesh; Sengupta, Anita

2018-03-01

Pathologists often deal with high complexity and sometimes disagreement over osteosarcoma tumor classification due to cellular heterogeneity in the dataset. Segmentation and classification of histology tissue in H&E stained tumor image datasets is a challenging task because of intra-class variations, inter-class similarity, crowded context, and noisy data. In recent years, deep learning approaches have led to encouraging results in breast cancer and prostate cancer analysis. In this article, we propose convolutional neural network (CNN) as a tool to improve efficiency and accuracy of osteosarcoma tumor classification into tumor classes (viable tumor, necrosis) versus nontumor. The proposed CNN architecture contains eight learned layers: three sets of stacked two convolutional layers interspersed with max pooling layers for feature extraction and two fully connected layers with data augmentation strategies to boost performance. The use of a neural network results in higher accuracy of average 92% for the classification. We compare the proposed architecture with three existing and proven CNN architectures for image classification: AlexNet, LeNet, and VGGNet. We also provide a pipeline to calculate percentage necrosis in a given whole slide image. We conclude that the use of neural networks can assure both high accuracy and efficiency in osteosarcoma classification.

Breast shape (ptosis) as a marker of a woman's breast attractiveness and age: Evidence from Poland and Papua.

PubMed

Groyecka, Agata; Żelaźniewicz, Agnieszka; Misiak, Michał; Karwowski, Maciej; Sorokowski, Piotr

2017-07-08

A women's breast is a sex-specific and aesthetic bodily attribute. It is suggested that breast morphology signals maturity, health, and fecundity. The perception of a woman's attractiveness and age depends on various cues, such as breast size or areola pigmentation. Conducted in Poland and Papua, the current study investigated how breast attractiveness, and the further estimate of a woman's age based on her breast's appearance, is affected by the occurrence of breast ptosis (ie, sagginess, droopiness). In the Polish sample, 57 women and 50 men (N = 107) were presented with sketches of breasts manipulated to represent different stages of ptosis based on two different breast ptosis classifications. The participants were asked to rate the breast attractiveness and age of the woman whose breasts were depicted in each sketch. In Papua, 45 men aged 20 to 75 years took part in the study, which was conducted using only one of the classifications of breast ptosis. Regardless of the classification used, the results showed that the assessed attractiveness of the breasts decreased as the estimated age increased with respect to the more ptotic breasts depicted in the sketches. The results for Papuan raters were the same as for the Polish sample. Breast ptosis may be yet another physical trait that affects the perception and preferences of a potential sexual partner. The consistency in ratings between Polish and Papuan raters suggests that the tendency to assess ptotic breasts with aging and a loss of attractiveness is cross-culturally universal. © 2017 Wiley Periodicals, Inc.

Adipose-Derived Stromal Vascular Fraction Differentially Expands Breast Progenitors in Tissue Adjacent to Tumors Compared to Healthy Breast Tissue

PubMed Central

Chatterjee, Sumanta; Laliberte, Mike; Blelloch, Sarah; Ratanshi, Imran; Safneck, Janice; Buchel, Ed

2015-01-01

Background: Autologous fat grafts supplemented with adipose-derived stromal vascular fraction are used in reconstructive and cosmetic breast procedures. Stromal vascular fraction contains adipose-derived stem cells that are thought to encourage wound healing, tissue regeneration, and graft retention. Although use of stromal vascular fraction has provided exciting perspectives for aesthetic procedures, no studies have yet been conducted to determine whether its cells contribute to breast tissue regeneration. The authors examined the effect of these cells on the expansion of human breast epithelial progenitors. Methods: From patients undergoing reconstructive breast surgery following mastectomies, abdominal fat, matching tissue adjacent to breast tumors, and the contralateral non–tumor-containing breast tissue were obtained. Ex vivo co-cultures using breast epithelial cells and the stromal vascular fraction cells were used to study the expansion potential of breast progenitors. Breast reduction samples were collected as a source of healthy breast cells. Results: The authors observed that progenitors present in healthy breast tissue or contralateral non–tumor-containing breast tissue showed significant and robust expansion in the presence of stromal vascular fraction (5.2- and 4.8-fold, respectively). Whereas the healthy progenitors expanded up to 3-fold without the stromal vascular fraction cells, the expansion of tissue adjacent to breast tumor progenitors required the presence of stromal vascular fraction cells, leading to a 7-fold expansion, which was significantly higher than the expansion of healthy progenitors with stromal vascular fraction. Conclusions: The use of stromal vascular fraction might be more beneficial to reconstructive operations following mastectomies compared with cosmetic corrections of the healthy breast. Future studies are required to examine the potential risk factors associated with its use. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, V. PMID:26090768

Comb-push ultrasound shear elastography of breast masses: initial results show promise.

PubMed

Denis, Max; Mehrmohammadi, Mohammad; Song, Pengfei; Meixner, Duane D; Fazzio, Robert T; Pruthi, Sandhya; Whaley, Dana H; Chen, Shigao; Fatemi, Mostafa; Alizad, Azra

2015-01-01

To evaluate the performance of Comb-push Ultrasound Shear Elastography (CUSE) for classification of breast masses. CUSE is an ultrasound-based quantitative two-dimensional shear wave elasticity imaging technique, which utilizes multiple laterally distributed acoustic radiation force (ARF) beams to simultaneously excite the tissue and induce shear waves. Female patients who were categorized as having suspicious breast masses underwent CUSE evaluations prior to biopsy. An elasticity estimate within the breast mass was obtained from the CUSE shear wave speed map. Elasticity estimates of various types of benign and malignant masses were compared with biopsy results. Fifty-four female patients with suspicious breast masses from our ongoing study are presented. Our cohort included 31 malignant and 23 benign breast masses. Our results indicate that the mean shear wave speed was significantly higher in malignant masses (6 ± 1.58 m/s) in comparison to benign masses (3.65 ± 1.36 m/s). Therefore, the stiffness of the mass quantified by the Young's modulus is significantly higher in malignant masses. According to the receiver operating characteristic curve (ROC), the optimal cut-off value of 83 kPa yields 87.10% sensitivity, 82.61% specificity, and 0.88 for the area under the curve (AUC). CUSE has the potential for clinical utility as a quantitative diagnostic imaging tool adjunct to B-mode ultrasound for differentiation of malignant and benign breast masses.

Continuous measurement of breast tumor hormone receptor expression: a comparison of two computational pathology platforms

PubMed Central

Ahern, Thomas P.; Beck, Andrew H.; Rosner, Bernard A.; Glass, Ben; Frieling, Gretchen; Collins, Laura C.; Tamimi, Rulla M.

2017-01-01

Background Computational pathology platforms incorporate digital microscopy with sophisticated image analysis to permit rapid, continuous measurement of protein expression. We compared two computational pathology platforms on their measurement of breast tumor estrogen receptor (ER) and progesterone receptor (PR) expression. Methods Breast tumor microarrays from the Nurses’ Health Study were stained for ER (n=592) and PR (n=187). One expert pathologist scored cases as positive if ≥1% of tumor nuclei exhibited stain. ER and PR were then measured with the Definiens Tissue Studio (automated) and Aperio Digital Pathology (user-supervised) platforms. Platform-specific measurements were compared using boxplots, scatter plots, and correlation statistics. Classification of ER and PR positivity by platform-specific measurements was evaluated with areas under receiver operating characteristic curves (AUC) from univariable logistic regression models, using expert pathologist classification as the standard. Results Both platforms showed considerable overlap in continuous measurements of ER and PR between positive and negative groups classified by expert pathologist. Platform-specific measurements were strongly and positively correlated with one another (rho≥0.77). The user-supervised Aperio workflow performed slightly better than the automated Definiens workflow at classifying ER positivity (AUCAperio=0.97; AUCDefiniens=0.90; difference=0.07, 95% CI: 0.05, 0.09) and PR positivity (AUCAperio=0.94; AUCDefiniens=0.87; difference=0.07, 95% CI: 0.03, 0.12). Conclusion Paired hormone receptor expression measurements from two different computational pathology platforms agreed well with one another. The user-supervised workflow yielded better classification accuracy than the automated workflow. Appropriately validated computational pathology algorithms enrich molecular epidemiology studies with continuous protein expression data and may accelerate tumor biomarker discovery. PMID:27729430

Expression characteristic of CXCR1 in different breast tissues and the relevance between its expression and efficacy of neo-adjuvant chemotherapy in breast cancer.

PubMed

Xue, Miao-Qun; Liu, Jun; Sang, Jian-Feng; Su, Lei; Yao, Yong-Zhong

2017-07-25

To investigate chemokine receptor CXCR1 expression characteristic in different breast tissues and analyze the relationship between CXCR1 expression changes in breast cancer tissue and efficacy of neo-adjuvant chemotherapy. Chemokine receptor CXCR1 was lowly expressed in normal breast tissues and breast fibroadenoma, but highly expressed in breast cancer. It was significantly correlated with pathological stage, tumor cell differentiation, and lymph node metastasis (P < 0.05). After neo-adjuvant chemotherapy, CXCR1 expression in breast cancer tissues decreased. Among these 104 breast cancer patients with different molecular subtypes, the survival rate with Luminal A was the highest, followed by the Luminal B breast cancer, TNBC was the worst. 104 cases with breast carcinoma, 20 cases with normal breast and 20 cases with breast fibroadenoma were included and followed up. Immunohistochemistry was used to detect the expression of CXCR1 in the various tissues. The relationship between the CXCR1 expression changes in breast cancer biopsies and surgical specimens, as well as the efficacy of neo-adjuvant chemotherapy, was analyzed. Chemokine receptor CXCR1 could be used as an indicator to predict benign or malignant breast disease, and it can even predict the malignancy degree of breast cancer, as well as its invasive ability and prognosis.

Molecular classifications of breast carcinoma with similar terminology and different definitions: are they the same?

PubMed

Tang, Ping; Wang, Jianmin; Bourne, Patria

2008-04-01

There are 4 major molecular classifications in the literature that divide breast carcinoma into basal and nonbasal subtypes, with basal subtypes associated with poor prognosis. Basal subtype is defined as positive for cytokeratin (CK) 5/6, CK14, and/or CK17 in CK classification; negative for ER, PR, and HER2 in triple negative (TN) classification; negative for ER and negative or positive for HER2 in ER/HER2 classification; and positive for CK5/6, CK14, CK17, and/or EGFR; and negative for ER, PR, and HER2 in CK/TN classification. These classifications use similar terminology but different definitions; it is critical to understand the precise relationship between them. We compared these 4 classifications in 195 breast carcinomas and found that (1) the rates of basal subtypes varied from 5% to 36% for ductal carcinoma in situ and 14% to 40% for invasive ductal carcinoma. (2) The rates of basal subtypes varied from 19% to 76% for HG carcinoma and 1% to 7% for NHG carcinoma. (3) The rates of basal subtypes were strongly associated with tumor grades (P < .001) in all classifications and associated with tumor types (in situ versus invasive ductal carcinomas) in TN (P < .001) and CK/TN classifications (P = .035). (4) These classifications were related but not interchangeable (kappa ranges from 0.140 to 0.658 for HG carcinoma and from 0.098 to 0.654 for NHG carcinoma). In conclusion, although these classifications all divide breast carcinoma into basal and nonbasal subtypes, they are not interchangeable. More studies are needed to evaluate to their values in predicting prognosis and guiding individualized therapy.

Investigation of Epstein-Barr virus DNA in formalin-fixed and paraffin- embedded breast cancer tissues.

PubMed

Kalkan, Ahmet; Ozdarendeli, Aykut; Bulut, Yasemin; Yekeler, Hayrettin; Cobanoglu, Bengu; Doymaz, Mehmet Z

2005-01-01

To investigate etiological role of Epstein-Barr virus (EBV) DNA in breast cancer. The presence of EBV DNA in 57 breast cancer tissues was investigated with a sensitive PCR assay. The breast cancer tissues were from invasive ductular (n=28), lobular (n=20) and other miscellaneous carcinomas (n=9). Tissues from normal breasts and patients with various benign breast diseases (n=55): fibrocystic disease (n=34), fibroadenoma (n=16), hyperplasia, and granulomatous mastitis (n=5), were used as control samples. EBV DNA was detected in 13 (23%) cancerous tissues (7 ductular, 4 lobular, 2 other carcinoma) and 19 (35%) in the control tissues. The difference between EBV presence in malignant and benign tissues was not statistically significant (p>0.05). The presence of EBV DNA was detected almost equally in both breast cancer and normal tissues, which indicates no etiological role for EBV in breast cancer. We suggest further etiological studies. Copyright (c) 2005 S. Karger AG, Basel.

Electromechanical Coupling Factor of Breast Tissue as a Biomarker for Breast Cancer.

PubMed

Park, Kihan; Chen, Wenjin; Chekmareva, Marina A; Foran, David J; Desai, Jaydev P

2018-01-01

This research aims to validate a new biomarker of breast cancer by introducing electromechanical coupling factor of breast tissue samples as a possible additional indicator of breast cancer. Since collagen fibril exhibits a structural organization that gives rise to a piezoelectric effect, the difference in collagen density between normal and cancerous tissue can be captured by identifying the corresponding electromechanical coupling factor. The design of a portable diagnostic tool and a microelectromechanical systems (MEMS)-based biochip, which is integrated with a piezoresistive sensing layer for measuring the reaction force as well as a microheater for temperature control, is introduced. To verify that electromechanical coupling factor can be used as a biomarker for breast cancer, the piezoelectric model for breast tissue is described with preliminary experimental results on five sets of normal and invasive ductal carcinoma (IDC) samples in the 25-45 temperature range. While the stiffness of breast tissues can be captured as a representative mechanical signature which allows one to discriminate among tissue types especially in the higher strain region, the electromechanical coupling factor shows more distinct differences between the normal and IDC groups over the entire strain region than the mechanical signature. From the two-sample -test, the electromechanical coupling factor under compression shows statistically significant differences ( 0.0039) between the two groups. The increase in collagen density in breast tissue is an objective and reproducible characteristic of breast cancer. Although characterization of mechanical tissue property has been shown to be useful for differentiating cancerous tissue from normal tissue, using a single parameter may not be sufficient for practical usage due to inherent variation among biological samples. The portable breast cancer diagnostic tool reported in this manuscript shows the feasibility of measuring multiple parameters of breast tissue allowing for practical application.

Human breast tissue disposition and bioactivity of limonene in women with early-stage breast cancer.

PubMed

Miller, Jessica A; Lang, Julie E; Ley, Michele; Nagle, Ray; Hsu, Chiu-Hsieh; Thompson, Patricia A; Cordova, Catherine; Waer, Amy; Chow, H-H Sherry

2013-06-01

Limonene is a bioactive food component found in citrus peel oil that has shown chemopreventive and chemotherapeutic activities in preclinical studies. We conducted an open-label pilot clinical study to determine the human breast tissue disposition of limonene and its associated bioactivity. We recruited 43 women with newly diagnosed operable breast cancer electing to undergo surgical excision to take 2 grams of limonene daily for two to six weeks before surgery. Blood and breast tissue were collected to determine drug/metabolite concentrations and limonene-induced changes in systemic and tissue biomarkers of breast cancer risk or carcinogenesis. Limonene was found to preferentially concentrate in the breast tissue, reaching high tissue concentration (mean = 41.3 μg/g tissue), whereas the major active circulating metabolite, perillic acid, did not concentrate in the breast tissue. Limonene intervention resulted in a 22% reduction in cyclin D1 expression (P = 0.002) in tumor tissue but minimal changes in tissue Ki67 and cleaved caspase-3 expression. No significant changes in serum leptin, adiponectin, TGF-β1, insulin-like growth factor binding protein-3 (IGFBP-3), and interleukin-6 (IL-6) levels were observed following limonene intervention. There was a small but statistically significant postintervention increase in insulin-like growth factor I (IGF-I) levels. We conclude that limonene distributed extensively to human breast tissue and reduced breast tumor cyclin D1 expression that may lead to cell-cycle arrest and reduced cell proliferation. Furthermore, placebo-controlled clinical trials and translational research are warranted to establish limonene's role for breast cancer prevention or treatment.

Human breast tissue disposition and bioactivity of limonene in women with early stage breast cancer

PubMed Central

Miller, Jessica A.; Lang, Julie E.; Ley, Michele; Nagle, Ray; Hsu, Chiu-Hsieh; Thompson, Patricia A; Cordova, Catherine; Waer, Amy; Chow, H.-H. Sherry

2013-01-01

Limonene is a bioactive food component found in citrus peel oil that has demonstrated chemopreventive and chemotherapeutic activities in preclinical studies. We conducted an open label pilot clinical study to determine the human breast tissue disposition of limonene and its associated bioactivity. We recruited forty-three women with newly diagnosed operable breast cancer electing to undergo surgical excision to take 2 grams of limonene daily for 2 – 6 weeks before surgery. Blood and breast tissue were collected to determine drug/metabolite concentrations and limonene-induced changes in systemic and tissue biomarkers of breast cancer risk or carcinogenesis. Limonene was found to preferentially concentrate in the breast tissue, reaching high tissue concentration (mean=41.3 μg/g tissue) while the major active circulating metabolite, perillic acid, did not concentrate in the breast tissue. Limonene intervention resulted in a 22% reduction in cyclin D1 expression (P=0.002) in tumor tissue but minimal changes in tissue Ki67 and cleaved caspase 3 expression. No significant changes in serum leptin, adiponectin, TGF-β1, IGFBP-3 and IL-6 levels were observed following limonene intervention. There was a small but statistically significant post-intervention increase in IGF-1 levels. We conclude that limonene distributed extensively to human breast tissue and reduced breast tumor cyclin D1 expression that may lead to cell cycle arrest and reduced cell proliferation. Further placebo-controlled clinical trials and translational research are warranted to establish limonene’s role for breast cancer prevention or treatment. PMID:23554130

Antibody-supervised deep learning for quantification of tumor-infiltrating immune cells in hematoxylin and eosin stained breast cancer samples

PubMed Central

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

2016-01-01

Background: Immune cell infiltration in tumor is an emerging prognostic biomarker in breast cancer. The gold standard for quantification of immune cells in tissue sections is visual assessment through a microscope, which is subjective and semi-quantitative. In this study, we propose and evaluate an approach based on antibody-guided annotation and deep learning to quantify immune cell-rich areas in hematoxylin and eosin (H&E) stained samples. Methods: Consecutive sections of formalin-fixed parafin-embedded samples obtained from the primary tumor of twenty breast cancer patients were cut and stained with H&E and the pan-leukocyte CD45 antibody. The stained slides were digitally scanned, and a training set of immune cell-rich and cell-poor tissue regions was annotated in H&E whole-slide images using the CD45-expression as a guide. In analysis, the images were divided into small homogenous regions, superpixels, from which features were extracted using a pretrained convolutional neural network (CNN) and classified with a support of vector machine. The CNN approach was compared to texture-based classification and to visual assessments performed by two pathologists. Results: In a set of 123,442 labeled superpixels, the CNN approach achieved an F-score of 0.94 (range: 0.92–0.94) in discrimination of immune cell-rich and cell-poor regions, as compared to an F-score of 0.88 (range: 0.87–0.89) obtained with the texture-based classification. When compared to visual assessment of 200 images, an agreement of 90% (κ = 0.79) to quantify immune infiltration with the CNN approach was achieved while the inter-observer agreement between pathologists was 90% (κ = 0.78). Conclusions: Our findings indicate that deep learning can be applied to quantify immune cell infiltration in breast cancer samples using a basic morphology staining only. A good discrimination of immune cell-rich areas was achieved, well in concordance with both leukocyte antigen expression and pathologists’ visual assessment. PMID:27688929

The aluminium content of breast tissue taken from women with breast cancer.

PubMed

House, Emily; Polwart, Anthony; Darbre, Philippa; Barr, Lester; Metaxas, George; Exley, Christopher

2013-10-01

The aetiology of breast cancer is multifactorial. While there are known genetic predispositions to the disease it is probable that environmental factors are also involved. Recent research has demonstrated a regionally specific distribution of aluminium in breast tissue mastectomies while other work has suggested mechanisms whereby breast tissue aluminium might contribute towards the aetiology of breast cancer. We have looked to develop microwave digestion combined with a new form of graphite furnace atomic absorption spectrometry as a precise, accurate and reproducible method for the measurement of aluminium in breast tissue biopsies. We have used this method to test the thesis that there is a regional distribution of aluminium across the breast in women with breast cancer. Microwave digestion of whole breast tissue samples resulted in clear homogenous digests perfectly suitable for the determination of aluminium by graphite furnace atomic absorption spectrometry. The instrument detection limit for the method was 0.48 μg/L. Method blanks were used to estimate background levels of contamination of 14.80 μg/L. The mean concentration of aluminium across all tissues was 0.39 μg Al/g tissue dry wt. There were no statistically significant regionally specific differences in the content of aluminium. We have developed a robust method for the precise and accurate measurement of aluminium in human breast tissue. There are very few such data currently available in the scientific literature and they will add substantially to our understanding of any putative role of aluminium in breast cancer. While we did not observe any statistically significant differences in aluminium content across the breast it has to be emphasised that herein we measured whole breast tissue and not defatted tissue where such a distribution was previously noted. We are very confident that the method developed herein could now be used to provide accurate and reproducible data on the aluminium content in defatted tissue and oil from such tissues and thereby contribute towards our knowledge on aluminium and any role in breast cancer. Copyright © 2013 Elsevier GmbH. All rights reserved.

The variation in breast density and its relationship to delayed wound healing: a prospective study of 40 reduction mammoplasties.

PubMed

Baldwin, C J; Kelly, E J; Batchelor, A G

2010-04-01

The proportions of glandular and adipose tissue within the breast vary. This study records the variation in density of breast tissue excised at 40 consecutive bilateral breast reductions. Age, body mass index (BMI), breast size and wound healing problems were related to breast density. The removed breast tissue was weighed and volume determined by water displacement. Delayed wound healing was defined as any breast unhealed after 2 weeks. The density of excised tissue varied between 0.8 and 1.2g/cm(3). There was no correlation between age or BMI and breast density. Delayed wound healing occurred in 32% of patients. There was no correlation between delayed wound healing and breast density. However, there was a direct relationship between increasing BMI and delayed wound healing. In this study, breast density varied by up to 50%. The density of breast tissue cannot be predicted by age, BMI or breast size. There is no relationship between delayed wound healing and breast density. Copyright 2009. Published by Elsevier Ltd.

The effects of Magnetic Resonance Imaging-guided High-Intensity Focused Ultrasound ablation on human cadaver breast tissue.

PubMed

Merckel, Laura G; Deckers, Roel; Baron, Paul; Bleys, Ronald L A W; van Diest, Paul J; Moonen, Chrit T W; Mali, Willem P Th M; van den Bosch, Maurice A A J; Bartels, Lambertus W

2013-10-05

Magnetic Resonance Imaging-guided High-Intensity Focused Ultrasound (MR-HIFU) is a promising technique for non-invasive breast tumor ablation. The purpose of this study was to investigate the effects of HIFU ablation and thermal exposure on ex vivo human breast tissue. HIFU ablations were performed in three unembalmed cadaveric breast specimens using a clinical MR-HIFU system. Sonications were performed in fibroglandular and adipose tissue. During HIFU ablation, time-resolved anatomical MR images were acquired to monitor macroscopic tissue changes. Furthermore, the breast tissue temperature was measured using a thermocouple to investigate heating and cooling under HIFU exposure. After HIFU ablation, breast tissue samples were excised and prepared for histopathological analysis. In addition, thermal exposure experiments were performed to distinguish between different levels of thermal damage using immunohistochemical staining. Irreversible macroscopic deformations up to 3.7 mm were observed upon HIFU ablation both in fibroglandular and in adipose tissue. No relationship was found between the sonication power or the maximum tissue temperature and the size of the deformations. Temperature measurements after HIFU ablation showed a slow decline in breast tissue temperature. Histopathological analysis of sonicated regions demonstrated ablated tissue and morphologically complete cell death. After thermal exposure, samples exposed to three different temperatures could readily be distinguished. In conclusion, the irreversible macroscopic tissue deformations in ex vivo human breast tissue observed during HIFU ablation suggest that it might be relevant to monitor tissue deformations during MR-HIFU treatments. Furthermore, the slow decrease in breast tissue temperature after HIFU ablation increases the risk of heat accumulation between successive sonications. Since cell death was inflicted after already 5 minutes at 75°C, MR-HIFU may find a place in non-invasive treatment of breast tumors. © 2013 Elsevier B.V. All rights reserved.

Classification of breast tissue in mammograms using efficient coding.

PubMed

Costa, Daniel D; Campos, Lúcio F; Barros, Allan K

2011-06-24

Female breast cancer is the major cause of death by cancer in western countries. Efforts in Computer Vision have been made in order to improve the diagnostic accuracy by radiologists. Some methods of lesion diagnosis in mammogram images were developed based in the technique of principal component analysis which has been used in efficient coding of signals and 2D Gabor wavelets used for computer vision applications and modeling biological vision. In this work, we present a methodology that uses efficient coding along with linear discriminant analysis to distinguish between mass and non-mass from 5090 region of interest from mammograms. The results show that the best rates of success reached with Gabor wavelets and principal component analysis were 85.28% and 87.28%, respectively. In comparison, the model of efficient coding presented here reached up to 90.07%. Altogether, the results presented demonstrate that independent component analysis performed successfully the efficient coding in order to discriminate mass from non-mass tissues. In addition, we have observed that LDA with ICA bases showed high predictive performance for some datasets and thus provide significant support for a more detailed clinical investigation.

Scanning in situ Spectroscopy platform for imaging surgical breast tissue specimens

PubMed Central

Krishnaswamy, Venkataramanan; Laughney, Ashley M.; Wells, Wendy A.; Paulsen, Keith D.; Pogue, Brian W.

2013-01-01

A non-contact localized spectroscopic imaging platform has been developed and optimized to scan 1x1cm2 square regions of surgically resected breast tissue specimens with ~150-micron resolution. A color corrected, image-space telecentric scanning design maintained a consistent sampling geometry and uniform spot size across the entire imaging field. Theoretical modeling in ZEMAX allowed estimation of the spot size, which is equal at both the center and extreme positions of the field with ~5% variation across the designed waveband, indicating excellent color correction. The spot sizes at the center and an extreme field position were also measured experimentally using the standard knife-edge technique and were found to be within ~8% of the theoretical predictions. Highly localized sampling offered inherent insensitivity to variations in background absorption allowing direct imaging of local scattering parameters, which was validated using a matrix of varying concentrations of Intralipid and blood in phantoms. Four representative, pathologically distinct lumpectomy tissue specimens were imaged, capturing natural variations in tissue scattering response within a given pathology. Variations as high as 60% were observed in the average reflectance and relative scattering power images, which must be taken into account for robust classification performance. Despite this variation, the preliminary data indicates discernible scatter power contrast between the benign vs malignant groups, but reliable discrimination of pathologies within these groups would require investigation into additional contrast mechanisms. PMID:23389199

The Susan G. Komen for the Cure Tissue Bank at the IU Simon Cancer Center: a unique resource for defining the "molecular histology" of the breast.

PubMed

Sherman, Mark E; Figueroa, Jonine D; Henry, Jill E; Clare, Susan E; Rufenbarger, Connie; Storniolo, Anna Maria

2012-04-01

"Molecular histology" of the breast may be conceptualized as encompassing the normative ranges of histologic structure and marker expression in normal breast tissues in relation to a woman's age and life experiences. Studies of molecular histology can aid our understanding of early events in breast carcinogenesis and provide data for comparison with diseased breast tissues. Until recently, lack of epidemiologically annotated, optimally prepared normal breast tissues obtained from healthy women presented a barrier to breast cancer research. The Komen Tissue Bank at Indiana University (Indianapolis, IN) is a unique biorepository that was developed to overcome this limitation. The Bank enrolls healthy donors who provide questionnaire data, blood, and up to four breast biopsies, which are prepared as both formalin-fixed, paraffin-embedded and frozen tissues. The resource is accessible to researchers worldwide through a proposal submission, review, and approval process. As of November 2010, the Bank had collected specimens and information from 1,174 donors. In this review, we discuss the importance of studying normal breast tissues, assess the strengths and limitations of studying normal tissues obtained from different sources, and summarize the features of the Komen Tissue Bank. As research projects are completed, results will be posted on the Bank's website. 2012 AACR

Breast Cancer Cell Colonization of the Human Bone Marrow Adipose Tissue Niche.

PubMed

Templeton, Zach S; Lie, Wen-Rong; Wang, Weiqi; Rosenberg-Hasson, Yael; Alluri, Rajiv V; Tamaresis, John S; Bachmann, Michael H; Lee, Kitty; Maloney, William J; Contag, Christopher H; King, Bonnie L

2015-12-01

Bone is a preferred site of breast cancer metastasis, suggesting the presence of tissue-specific features that attract and promote the outgrowth of breast cancer cells. We sought to identify parameters of human bone tissue associated with breast cancer cell osteotropism and colonization in the metastatic niche. Migration and colonization patterns of MDA-MB-231-fLuc-EGFP (luciferase-enhanced green fluorescence protein) and MCF-7-fLuc-EGFP breast cancer cells were studied in co-culture with cancellous bone tissue fragments isolated from 14 hip arthroplasties. Breast cancer cell migration into tissues and toward tissue-conditioned medium was measured in Transwell migration chambers using bioluminescence imaging and analyzed as a function of secreted factors measured by multiplex immunoassay. Patterns of breast cancer cell colonization were evaluated with fluorescence microscopy and immunohistochemistry. Enhanced MDA-MB-231-fLuc-EGFP breast cancer cell migration to bone-conditioned versus control medium was observed in 12/14 specimens (P = .0014) and correlated significantly with increasing levels of the adipokines/cytokines leptin (P = .006) and IL-1β (P = .001) in univariate and multivariate regression analyses. Fluorescence microscopy and immunohistochemistry of fragments underscored the extreme adiposity of adult human bone tissues and revealed extensive breast cancer cell colonization within the marrow adipose tissue compartment. Our results show that breast cancer cells migrate to human bone tissue-conditioned medium in association with increasing levels of leptin and IL-1β, and colonize the bone marrow adipose tissue compartment of cultured fragments. Bone marrow adipose tissue and its molecular signals may be important but understudied components of the breast cancer metastatic niche. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Dense Breasts: Answers to Commonly Asked Questions

Cancer.gov

Mammograms detect breast density, breast cancer, and breast changes that are not cancer (benign breast changes). Breast density describes the amount of glandular and fibrous tissue, as compared to fatty tissue. Learn what factors are associated with breast density and about other risk factors for breast cancer.

A new qualitative pattern classification of shear wave elastograghy for solid breast mass evaluation.

PubMed

Cong, Rui; Li, Jing; Guo, Song

2017-02-01

To examine the efficacy of qualitative shear wave elastography (SWE) in the classification and evaluation of solid breast masses, and to compare this method with conventional ultrasonograghy (US), quantitative SWE parameters and qualitative SWE classification proposed before. From April 2015 to March 2016, 314 consecutive females with 325 breast masses who decided to undergo core needle biopsy and/or surgical biopsy were enrolled. Conventional US and SWE were previously performed in all enrolled subjects. Each mass was classified by two different qualitative classifications. One was established in our study, herein named the Qual1. Qual1 could classify the SWE images into five color patterns by the visual evaluations: Color pattern 1 (homogeneous pattern); Color pattern 2 (comparative homogeneous pattern); Color pattern 3 (irregularly heterogeneous pattern); Color pattern 4 (intralesional echo pattern); and Color pattern 5 (the stiff rim sign pattern). The second qualitative classification was named Qual2 here, and included a four-color overlay pattern classification (Tozaki and Fukuma, Acta Radiologica, 2011). The Breast Imaging Reporting and Data System (BI-RADS) assessment and quantitative SWE parameters were recorded. Diagnostic performances of conventional US, SWE parameters, and combinations of US and SWE parameters were compared. With pathological results as the gold standard, of the 325 examined breast masses, 139 (42.77%) samples were malignant and 186 (57.23%) were benign. The Qual1 showed a higher Az value than the Qual2 and quantitative SWE parameters (all P<0.05). When applying Qual1=Color pattern 1 for downgrading and Qual1=Color pattern 5 for upgrading the BI-RADS categories, we obtained the highest Az value (0.951), and achieved a significantly higher specificity (86.56%, P=0.002) than that of the US (81.18%) with the same sensitivity (94.96%). The qualitative classification proposed in this study may be representative of SWE parameters and has potential to be relevant assistance in breast mass diagnoses. Copyright © 2016. Published by Elsevier B.V.

Mapping the cellular and molecular heterogeneity of normal and malignant breast tissues and cultured cell lines

PubMed Central

2010-01-01

Introduction Normal and neoplastic breast tissues are comprised of heterogeneous populations of epithelial cells exhibiting various degrees of maturation and differentiation. While cultured cell lines have been derived from both normal and malignant tissues, it remains unclear to what extent they retain similar levels of differentiation and heterogeneity as that found within breast tissues. Methods We used 12 reduction mammoplasty tissues, 15 primary breast cancer tissues, and 20 human breast epithelial cell lines (16 cancer lines, 4 normal lines) to perform flow cytometry for CD44, CD24, epithelial cell adhesion molecule (EpCAM), and CD49f expression, as well as immunohistochemistry, and in vivo tumor xenograft formation studies to extensively analyze the molecular and cellular characteristics of breast epithelial cell lineages. Results Human breast tissues contain four distinguishable epithelial differentiation states (two luminal phenotypes and two basal phenotypes) that differ on the basis of CD24, EpCAM and CD49f expression. Primary human breast cancer tissues also contain these four cellular states, but in altered proportions compared to normal tissues. In contrast, cultured cancer cell lines are enriched for rare basal and mesenchymal epithelial phenotypes, which are normally present in small numbers within human tissues. Similarly, cultured normal human mammary epithelial cell lines are enriched for rare basal and mesenchymal phenotypes that represent a minor fraction of cells within reduction mammoplasty tissues. Furthermore, although normal human mammary epithelial cell lines exhibit features of bi-potent progenitor cells they are unable to differentiate into mature luminal breast epithelial cells under standard culture conditions. Conclusions As a group breast cancer cell lines represent the heterogeneity of human breast tumors, but individually they exhibit increased lineage-restricted profiles that fall short of truly representing the intratumoral heterogeneity of individual breast tumors. Additionally, normal human mammary epithelial cell lines fail to retain much of the cellular diversity found in human breast tissues and are enriched for differentiation states that are a minority in breast tissues, although they do exhibit features of bi-potent basal progenitor cells. These findings suggest that collections of cell lines representing multiple cell types can be used to model the cellular heterogeneity of tissues. PMID:20964822

Microbial Dysbiosis Is Associated with Human Breast Cancer

PubMed Central

Xuan, Caiyun; Shamonki, Jaime M.; Chung, Alice; DiNome, Maggie L.; Chung, Maureen; Sieling, Peter A.; Lee, Delphine J.

2014-01-01

Breast cancer affects one in eight women in their lifetime. Though diet, age and genetic predisposition are established risk factors, the majority of breast cancers have unknown etiology. The human microbiota refers to the collection of microbes inhabiting the human body. Imbalance in microbial communities, or microbial dysbiosis, has been implicated in various human diseases including obesity, diabetes, and colon cancer. Therefore, we investigated the potential role of microbiota in breast cancer by next-generation sequencing using breast tumor tissue and paired normal adjacent tissue from the same patient. In a qualitative survey of the breast microbiota DNA, we found that the bacterium Methylobacterium radiotolerans is relatively enriched in tumor tissue, while the bacterium Sphingomonas yanoikuyae is relatively enriched in paired normal tissue. The relative abundances of these two bacterial species were inversely correlated in paired normal breast tissue but not in tumor tissue, indicating that dysbiosis is associated with breast cancer. Furthermore, the total bacterial DNA load was reduced in tumor versus paired normal and healthy breast tissue as determined by quantitative PCR. Interestingly, bacterial DNA load correlated inversely with advanced disease, a finding that could have broad implications in diagnosis and staging of breast cancer. Lastly, we observed lower basal levels of antibacterial response gene expression in tumor versus healthy breast tissue. Taken together, these data indicate that microbial DNA is present in the breast and that bacteria or their components may influence the local immune microenvironment. Our findings suggest a previously unrecognized link between dysbiosis and breast cancer which has potential diagnostic and therapeutic implications. PMID:24421902

[A revolution postponed indefinitely.WHO classification of tumors of the breast 2012: the main changes compared to the 3rd edition (2003)].

PubMed

Nenutil, Rudolf

2015-01-01

In 2012, the new classification of the fourth series WHO blue books of breast tumors was released. The current version represents a fluent evolution, compared to the third edition. Some limited changes regarding terminology, definitions and the inclusion of some diagnostic units were adopted. The information about the molecular biology and genetic background of breast carcinoma has been enriched substantially.

Classification of Microcalcification of the Diagnosis of Breast Cancer using Artificial Neural Networks.

DTIC Science & Technology

1995-09-01

employed to classify benign and malignant microcalcifications in the radiographs of pathological specimen. Digital images were acquired by digitizing...associated with benign and malignant processes. The classification of microcalcifications for the diagnosis of breast cancer was achieved at a high level in

Diagnostic classification scheme in Iranian breast cancer patients using a decision tree.

PubMed

Malehi, Amal Saki

2014-01-01

The objective of this study was to determine a diagnostic classification scheme using a decision tree based model. The study was conducted as a retrospective case-control study in Imam Khomeini hospital in Tehran during 2001 to 2009. Data, including demographic and clinical-pathological characteristics, were uniformly collected from 624 females, 312 of them were referred with positive diagnosis of breast cancer (cases) and 312 healthy women (controls). The decision tree was implemented to develop a diagnostic classification scheme using CART 6.0 Software. The AUC (area under curve), was measured as the overall performance of diagnostic classification of the decision tree. Five variables as main risk factors of breast cancer and six subgroups as high risk were identified. The results indicated that increasing age, low age at menarche, single and divorced statues, irregular menarche pattern and family history of breast cancer are the important diagnostic factors in Iranian breast cancer patients. The sensitivity and specificity of the analysis were 66% and 86.9% respectively. The high AUC (0.82) also showed an excellent classification and diagnostic performance of the model. Decision tree based model appears to be suitable for identifying risk factors and high or low risk subgroups. It can also assists clinicians in making a decision, since it can identify underlying prognostic relationships and understanding the model is very explicit.

Expression and significance of CD44s, CD44v6, and nm23 mRNA in human cancer.

PubMed

Liu, Yong-Jun; Yan, Pei-Song; Li, Jun; Jia, Jing-Fen

2005-11-14

To investigate the relationship between the expression levels of nm23 mRNA, CD44s, and CD44v6, and oncogenesis, development and metastasis of human gastric adenocarcinoma, colorectal adenocarcinoma, intraductal carcinoma of breast, and lung cancer. Using tissue microarray by immuhistochemical (IHC) staining and in situ hybridization (ISH), we examined the expression levels of nm23 mRNA, CD44s, and CD44v6 in 62 specimens of human gastric adenocarcinoma and 62 specimens of colorectal adenocarcinoma; the expression of CD44s and CD44v6 in 120 specimens of intraductal carcinoma of breast and 20 specimens of normal breast tissue; the expression of nm23 mRNA in 72 specimens of human lung cancer and 23 specimens of normal tissue adjacent to cancer. The expression of nm23 mRNA in the tissues of gastric and colorectal adenocarcinoma was not significantly different from that in the normal tissues adjacent to cancer (P>0.05), and was not associated with the invasion of tumor and the pathology grade of adenocarcinoma (P>0.05). However, the expression of nm23 mRNA was correlated negatively to the lymph node metastasis of gastric and colorectal adenocarcinoma (r = -0.49, P<0.01; r = -4.93, P<0.01). The expression of CD44s in the tissues of gastric and colorectal adenocarcinoma was significantly different from that in the normal tissues adjacent to cancer (P<0.05; P<0.01). CD44v6 was expressed in the tissues of gastric and colorectal adenocarcinoma only, the expression of CD44v6 was significantly associated with the lymph node metastasis, invasion and pathological grade of the tumor (r = 0.47, P<0.01; r = 5.04, P<0.01). CD44s and CD44v6 were expressed in intraductal carcinoma of breast, the expression of CD44s and CD44v6 was significantly associated with lymph node metastases and invasion (P<0.01). However, neither of them was expressed in the normal breast tissue. In addition, the expression of CD44v6 was closely related to the degree of cell differentiation of intraductal carcinoma of breast (c2 = 5.68, P<0.05). The expressional level of nm23 mRNA was closely related to the degree of cell differentiation (P<0.05) and lymph node metastasis (P<0.01), but the expression of nm23 gene was not related to sex, age, and type of histological classification (P>0.05). Patients with overexpression of CD44s and CD44v6 and low expression of nm23 mRNA have a higher lymph node metastatic rate and invasion. In addition, overexpression of CD44v6 is closely related to the degree of cell differentiation. Detection of the three genes is able to provide a reliable index to evaluate the invasion and metastasis of tumor cells.

Taxonomy of breast cancer based on normal cell phenotype predicts outcome

PubMed Central

Santagata, Sandro; Thakkar, Ankita; Ergonul, Ayse; Wang, Bin; Woo, Terri; Hu, Rong; Harrell, J. Chuck; McNamara, George; Schwede, Matthew; Culhane, Aedin C.; Kindelberger, David; Rodig, Scott; Richardson, Andrea; Schnitt, Stuart J.; Tamimi, Rulla M.; Ince, Tan A.

2014-01-01

Accurate classification is essential for understanding the pathophysiology of a disease and can inform therapeutic choices. For hematopoietic malignancies, a classification scheme based on the phenotypic similarity between tumor cells and normal cells has been successfully used to define tumor subtypes; however, use of normal cell types as a reference by which to classify solid tumors has not been widely emulated, in part due to more limited understanding of epithelial cell differentiation compared with hematopoiesis. To provide a better definition of the subtypes of epithelial cells comprising the breast epithelium, we performed a systematic analysis of a large set of breast epithelial markers in more than 15,000 normal breast cells, which identified 11 differentiation states for normal luminal cells. We then applied information from this analysis to classify human breast tumors based on normal cell types into 4 major subtypes, HR0–HR3, which were differentiated by vitamin D, androgen, and estrogen hormone receptor (HR) expression. Examination of 3,157 human breast tumors revealed that these HR subtypes were distinct from the current classification scheme, which is based on estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. Patient outcomes were best when tumors expressed all 3 hormone receptors (subtype HR3) and worst when they expressed none of the receptors (subtype HR0). Together, these data provide an ontological classification scheme associated with patient survival differences and provides actionable insights for treating breast tumors. PMID:24463450

High mobility group box-1 and its clinical value in breast cancer

PubMed Central

Sun, Shanping; Zhang, Wei; Cui, Zhaoqing; Chen, Qi; Xie, Panpan; Zhou, Changxin; Liu, Baoguo; Peng, Xiangeng; Zhang, Yang

2015-01-01

Background High mobility group box-1 (HMGB1) is a factor regulating malignant tumorigenesis, proliferation, and metastasis, and is associated with poor clinical pathology in various human cancers. We investigated the differential concentrations of HMGB1 in tissues and sera, and their clinical value for diagnosis in patients with breast cancer, benign breast disease, and healthy individuals. Methods HMGB1 levels in tumor tissues, adjacent normal tissues, and benign breast disease tissues was detected via immunohistochemistry. Serum HMGB1 was measured using an enzyme-linked immunosorbent assay in 56 patients with breast cancer, 25 patients with benign breast disease, and 30 healthy control subjects. The clinicopathological features of the patients were compared. Tissues were evaluated histopathologically by pathologists. Results HMGB1 levels in the tissues and sera of patients with breast cancer were significantly higher than those in patients with benign breast disease or normal individuals. The 56 cancer patients were classified as having high tissue HMGB1 levels (n=41) or low tissue HMGB1 levels (n=15), but the corresponsive serum HMGB1 in these two groups was not significantly different. HMGB1 levels in breast cancer tissues significantly correlated with differentiation grade, lymphatic metastasis, and tumor-node-metastasis stage, but not patient age, tumor size, or HER-2/neu expression; no association between serum HMGB1 levels and these clinicopathological parameters was found. The sensitivity and specificity of tissue HMGB1 levels for the diagnosis of breast cancer were 73.21% and 84.00%, respectively, while positive and negative predictive values were 91.11% and 58.33%. Conclusion HMGB1 might be involved in the development and progression of breast cancer and could be a supportive diagnostic marker for breast cancer. Serum HMGB1 could be a useful serological biomarker for diagnosis and screening of breast cancer. PMID:25709474

TH-AB-209-12: Tissue Equivalent Phantom with Excised Human Tissue for Assessing Clinical Capabilities of Coherent Scatter Imaging Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albanese, K; Morris, R; Spencer, J

Purpose: Previously we reported the development of anthropomorphic tissue-equivalent scatter phantoms of the human breast. Here we present the first results from the scatter imaging of the tissue equivalent breast phantoms for breast cancer diagnosis. Methods: A breast phantom was designed to assess the capability of coded aperture coherent x-ray scatter imaging to classify different types of breast tissue (adipose, fibroglandular, tumor). The phantom geometry was obtained from a prone breast geometry scanned on a dedicated breast CT system. The phantom was 3D printed using the segmented DICOM breast CT data. The 3D breast phantom was filled with lard (asmore » a surrogate for adipose tissue) and scanned in different geometries alongside excised human breast tissues (obtained from lumpectomy and mastectomy procedures). The raw data were reconstructed using a model-based reconstruction algorithm and yielded the location and form factor (i.e., momentum transfer (q) spectrum) of the materials that were imaged. The measured material form factors were then compared to the ground truth measurements acquired by x-ray diffraction (XRD) imaging. Results: Our scatter imaging system was able to define the location and composition of the various materials and tissues within the phantom. Cancerous breast tissue was detected and classified through automated spectral matching and an 86% correlation threshold. The total scan time for the sample was approximately 10 minutes and approaches workflow times for clinical use in intra-operative or other diagnostic tasks. Conclusion: This work demonstrates the first results from an anthropomorphic tissue equivalent scatter phantom to characterize a coherent scatter imaging system. The functionality of the system shows promise in applications such as intra-operative margin detection or virtual biopsy in the diagnosis of breast cancer. Future work includes using additional patient-derived tissues (e.g., human fat), and modeling additional organs (e.g., lung).« less

Breast cancer risk assessment and diagnosis model using fuzzy support vector machine based expert system

NASA Astrophysics Data System (ADS)

Dheeba, J.; Jaya, T.; Singh, N. Albert

2017-09-01

Classification of cancerous masses is a challenging task in many computerised detection systems. Cancerous masses are difficult to detect because these masses are obscured and subtle in mammograms. This paper investigates an intelligent classifier - fuzzy support vector machine (FSVM) applied to classify the tissues containing masses on mammograms for breast cancer diagnosis. The algorithm utilises texture features extracted using Laws texture energy measures and a FSVM to classify the suspicious masses. The new FSVM treats every feature as both normal and abnormal samples, but with different membership. By this way, the new FSVM have more generalisation ability to classify the masses in mammograms. The classifier analysed 219 clinical mammograms collected from breast cancer screening laboratory. The tests made on the real clinical mammograms shows that the proposed detection system has better discriminating power than the conventional support vector machine. With the best combination of FSVM and Laws texture features, the area under the Receiver operating characteristic curve reached .95, which corresponds to a sensitivity of 93.27% with a specificity of 87.17%. The results suggest that detecting masses using FSVM contribute to computer-aided detection of breast cancer and as a decision support system for radiologists.

Surgical treatment of gynecomastia with severe ptosis: periareolar incision and dermal double areolar pedicle technique.

PubMed

Cannistra, Claudio; Piedimonte, Andrea; Albonico, Fiorella

2009-11-01

Gynecomastia is a morphostructural impairment of the mammary region in men caused by parenchymal hypertrophy or a cutaneous distortion of breast skin covering or both. The clinical classification introduced by Simon et al. in 1973 ranks gynecomastia in three degrees. Each subtype can be treated with a specific technique. This article describes an alternative surgical procedure for treating gynecomastia with severe ptosis(type III and type IIIb of Simon's classification). Fifty-eight patients were treated for gynecomastia in our Plastic Surgery Unit from 1996 to 2004. The cutaneous excess of periareolar skin is evaluated by a pinching test. A circular periareolar mark is traced corresponding to the cutaneous excess that has to be removed.Initially, liposuction of adipous tissue on the periphery of the mammary region is performed through two cutaneous 3-mm incisions at the 3 o'clock and 9 o'clock positions around the areola. After this, the liposuction incisions are enlarged from 10 o'clock to 8 o'clock and from 2 o'clockto 4 o'clock to create access for the mastectomy. This dissection creates a double dermal areolar pedicle. The new areolar position is fixed with a Benelli round block suture. A resolution of the morphologic deformity without evident scars after hair growth and a correction of the breast deformity has been observed in the 6-month follow-ups conducted for all the patients. We observed that the vascular-nervous net under the areola at 12 o'clock and 6 o'clock is very important, more so than the lateral pedicle, and the conservation of a double vascular-nervous pedicle reduces significantly the risk of areolar necrosis, especially in cases of gynecomastia type III and in cases where there is a high degree of breast malformation such as the tuberous breast.

New method for generating breast models featuring glandular tissue spatial distribution

NASA Astrophysics Data System (ADS)

Paixão, L.; Oliveira, B. B.; Oliveira, M. A.; Teixeira, M. H. A.; Fonseca, T. C. F.; Nogueira, M. S.

2016-02-01

Mammography is the main radiographic technique used for breast imaging. A major concern with mammographic imaging is the risk of radiation-induced breast cancer due to the high sensitivity of breast tissue. The mean glandular dose (DG) is the dosimetric quantity widely accepted to characterize the risk of radiation induced cancer. Previous studies have concluded that DG depends not only on the breast glandular content but also on the spatial distribution of glandular tissue within the breast. In this work, a new method for generating computational breast models featuring skin composition and glandular tissue distribution from patients undergoing digital mammography is proposed. Such models allow a more accurate way of calculating individualized breast glandular doses taking into consideration the glandular tissue fraction. Sixteen breast models of four patients with different glandularity breasts were simulated and the results were compared with those obtained from recommended DG conversion factors. The results show that the internationally recommended conversion factors may be overestimating the mean glandular dose to less dense breasts and underestimating the mean glandular dose for denser breasts. The methodology described in this work constitutes a powerful tool for breast dosimetry, especially for risk studies.

Assessment of the Activation State of RAS and Map Kinase in Human Breast Cancer Specimens (96Breast)

DTIC Science & Technology

1999-09-01

Cancer 16. PRICE CODE 17. SECURITY CLASSIFICATION 18 . SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT OF REPORT OF...THIS PAGE OF ABSTRACT Unclassified Unclassified Unclassified Unlimited NSN 7640-01-280-5500 Standard Form 298 (Rev. 2-89) Prescribed by ANSI Std. Z39- 18 ...transformation and regulate cell morphology, adhesion and motility through cytoskeletal dynamics and play an important role in carcinogenesis ( 18 ). Rho

Regression-Based Approach For Feature Selection In Classification Issues. Application To Breast Cancer Detection And Recurrence

NASA Astrophysics Data System (ADS)

Belciug, Smaranda; Serbanescu, Mircea-Sebastian

2015-09-01

Feature selection is considered a key factor in classifications/decision problems. It is currently used in designing intelligent decision systems to choose the best features which allow the best performance. This paper proposes a regression-based approach to select the most important predictors to significantly increase the classification performance. Application to breast cancer detection and recurrence using publically available datasets proved the efficiency of this technique.

The Susan G. Komen for the Cure® Tissue Bank at the IU Simon Cancer Center: A Unique Resource for Defining the “Molecular Histology” of the Breast

PubMed Central

Sherman, Mark E.; Figueroa, Jonine D.; Henry, Jill E.; Clare, Susan E.; Rufenbarger, Connie; Storniolo, Anna Maria

2014-01-01

“Molecular histology” of the breast may be conceptualized as encompassing the normative ranges of histological structure and marker expression in normal breast tissues in relation to a woman’s age and life experiences. Studies of molecular histology can aid our understanding of early events in breast carcinogenesis and provide data for comparison with diseased breast tissues. Until recently, lack of epidemiologically annotated, optimally prepared normal breast tissues obtained from healthy women presented a barrier to breast cancer research. The Komen Tissue Bank at Indiana University is a unique biorepository that was developed to overcome this limitation. The Bank enrolls healthy donors who provide questionnaire data, blood, and up to four breast biopsies, which are prepared as both formalin fixed paraffin embedded and frozen tissues. The resource is accessible to researchers worldwide through a proposal submission, review, and approval process. As of November 2010, the Bank had collected specimens and information from 1,174 donors. In this review, we discuss the importance of studying normal breast tissues, assess the strengths and limitations of studying normal tissues obtained from different sources, and summarize the features of the Komen Tissue Bank. As research projects are completed, results will be posted on the Bank’s website. PMID:22345117

Mammographic evidence of microenvironment changes in tumorous breasts.

PubMed

Marin, Zach; Batchelder, Kendra A; Toner, Brian C; Guimond, Lyne; Gerasimova-Chechkina, Evgeniya; Harrow, Amy R; Arneodo, Alain; Khalil, Andre

2017-04-01

The microenvironment of breast tumors plays a critical role in tumorigenesis. As long as the structural integrity of the microenvironment is upheld, the tumor is suppressed. If tissue structure is lost through disruptions in the normal cell cycle, the microenvironment may act as a tumor promoter. Therefore, the properties that distinguish between healthy and tumorous tissues may not be solely in the tumor characteristics but rather in surrounding non-tumor tissue. The goal of this paper was to show preliminary evidence that tissue disruption and loss of homeostasis in breast tissue microenvironment and breast bilateral asymmetry can be quantitatively and objectively assessed from mammography via a localized, wavelet-based analysis of the whole breast. A wavelet-based multifractal formalism called the 2D Wavelet Transform Modulus Maxima (WTMM) method was used to quantitate density fluctuations from mammographic breast tissue via the Hurst exponent (H). Each entire mammogram was cut in hundreds of 360 × 360 pixel subregions in a gridding scheme of overlapping sliding windows, with each window boundary separated by 32 pixels. The 2D WTMM method was applied to each subregion individually. A data mining approach was set up to determine which metrics best discriminated between normal vs. cancer cases. These same metrics were then used, without modification, to discriminate between normal vs. benign and benign vs. cancer cases. The density fluctuations in healthy mammographic breast tissue are either monofractal anti-correlated (H < 1/2) for fatty tissue or monofractal long-range correlated (H>1/2) for dense tissue. However, tissue regions with H~1/2, as well as left vs. right breast asymetries, were found preferably in tumorous (benign or cancer) breasts vs. normal breasts, as quantified via a combination metric yielding a P-value ~ 0.0006. No metric considered showed significant differences between cancer vs. benign breasts. Since mammographic tissue regions associated with uncorrelated (H~1/2) density fluctuations were predominantly in tumorous breasts, and since the underlying physical processes associated with a H~1/2 signature are those of randomness, lack of spatial correlation, and free diffusion, it is hypothesized that this signature is also associated with tissue disruption and loss of tissue homeostasis. © 2017 American Association of Physicists in Medicine.

Nonexpansive immediate breast reconstruction using human acellular tissue matrix graft (AlloDerm).

PubMed

Salzberg, C Andrew

2006-07-01

Immediate breast reconstruction has become a standard of care following mastectomy for cancer, largely due to improved esthetic and psychologic outcomes achieved with this technique. However, the current historical standards--transverse rectus abdominis myocutaneous flap reconstruction and expander--implant surgery-still have limitations as regards patient morbidity, short-term body-image improvements, and even cost. To address these shortcomings, we employ a novel concept of human tissue replacement to enhance breast shape and provide total coverage, enabling immediate mound reconstruction without the need for breast expansion prior to permanent implant placement. AlloDerm (human acellular tissue matrix) is a human-derived graft tissue with extensive experience in various settings of skin and soft tissue replacement surgery. This report describes the success using acellular tissue matrix to provide total coverage over the prosthesis in immediate reconstruction, with limited muscle dissection. In this population, 49 patients (76 breasts) successfully underwent the acellular tissue matrix-based immediate reconstruction, resulting in durable breast reconstruction with good symmetry. These findings may predict that acellular tissue matrix-supplemented immediate breast reconstruction will become a new technique for the immediate reconstruction of the postmastectomy breast.

Influence of nuclei segmentation on breast cancer malignancy classification

NASA Astrophysics Data System (ADS)

Jelen, Lukasz; Fevens, Thomas; Krzyzak, Adam

2009-02-01

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

Factors affecting measurement of optic parameters by time-resolved near-infrared spectroscopy in breast cancer

NASA Astrophysics Data System (ADS)

Yoshizawa, Nobuko; Ueda, Yukio; Mimura, Tetsuya; Ohmae, Etsuko; Yoshimoto, Kenji; Wada, Hiroko; Ogura, Hiroyuki; Sakahara, Harumi

2018-02-01

The purpose of this study was to evaluate the effects of the thickness and depth of tumors on hemoglobin measurements in breast cancer by optical spectroscopy and to demonstrate tissue oxygen saturation (SO2) and reduced scattering coefficient (μs‧) in breast tissue and breast cancer in relation to the skin-to-chest wall distance. We examined 53 tumors from 44 patients. Total hemoglobin concentration (tHb), SO2, and μs‧ were measured by time-resolved spectroscopy (TRS). The skin-to-chest wall distance and the size and depth of tumors were measured by ultrasonography. There was a positive correlation between tHb and tumor thickness, and a negative correlation between tHb and tumor depth. SO2 in breast tissue decreased when the skin-to-chest wall distance decreased, and SO2 in tumors tended to be lower than in breast tissue. In breast tissue, there was a negative correlation between μs‧ and the skin-to-chest wall distance, and μs‧ in tumors was higher than in breast tissue. Measurement of tHb in breast cancer by TRS was influenced by tumor thickness and depth. Although SO2 seemed lower and μs‧ was higher in breast cancer than in breast tissue, the skin-to-chest wall distance may have affected the measurements.

Tissue Expander versus Tissue Expander and Latissimus Flap in Morbidly Obese Breast Reconstruction Patients

PubMed Central

Adams, Robert L.; Chandler, Robert G.; Parks, Joseph

2015-01-01

Background: Immediate postmastectomy breast reconstruction in morbidly obese patients represents a challenge because neither prosthetic nor abdominal-based options may be suitable. Methods: This study compared a previously published cohort of immediate prosthetic reconstruction of 346 patients (511 breasts) of whom 49 patients (67 breasts) were morbidly obese (defined as a body mass index > 35) with a morbidly obese patient population whose breasts were reconstructed immediately following postmastectomy with latissimus flap and tissue expander (21 patients and 22 breasts) in the same time period. The preoperative risk factors of mastectomy such as tobacco use, diabetes, and prior radiation and the postoperative complications of mastectomy such as skin necrosis, seroma, and prosthesis loss were examined. The explantation of the tissue expander provided a defined endpoint of reconstruction failure. Results: The average body mass index in the tissue expander/implant group and in the latissimus flap plus tissue expander/implant group was 40.9 and 40.1, respectively. The risk profile of diabetes and tobacco use was similar in both groups. Fifteen of the 67 breasts (22.3%) of the tissue expander/implant group and 15 of the 23 breasts (65.2%) of the latissimus flap group had received prior radiation. The prosthesis loss was 13 of 67 breasts (19.4%) that had tissue-expander–alone reconstruction and 1 of 22 (4.8%) in the latissimus group that had tissue expander reconstruction. Modification of donor-site incision and skin-island location in the latissimus group of patients can minimize scar deformity. Conclusion: The loss rate in immediate postmastectomy reconstruction in morbidly obese patients with latissimus flap plus tissue expander was substantially lower than the loss rate in those with breast reconstructed with tissue expander alone. PMID:25878934

Comb-Push Ultrasound Shear Elastography of Breast Masses: Initial Results Show Promise

PubMed Central

Song, Pengfei; Fazzio, Robert T.; Pruthi, Sandhya; Whaley, Dana H.; Chen, Shigao; Fatemi, Mostafa

2015-01-01

Purpose or Objective To evaluate the performance of Comb-push Ultrasound Shear Elastography (CUSE) for classification of breast masses. Materials and Methods CUSE is an ultrasound-based quantitative two-dimensional shear wave elasticity imaging technique, which utilizes multiple laterally distributed acoustic radiation force (ARF) beams to simultaneously excite the tissue and induce shear waves. Female patients who were categorized as having suspicious breast masses underwent CUSE evaluations prior to biopsy. An elasticity estimate within the breast mass was obtained from the CUSE shear wave speed map. Elasticity estimates of various types of benign and malignant masses were compared with biopsy results. Results Fifty-four female patients with suspicious breast masses from our ongoing study are presented. Our cohort included 31 malignant and 23 benign breast masses. Our results indicate that the mean shear wave speed was significantly higher in malignant masses (6 ± 1.58 m/s) in comparison to benign masses (3.65 ± 1.36 m/s). Therefore, the stiffness of the mass quantified by the Young’s modulus is significantly higher in malignant masses. According to the receiver operating characteristic curve (ROC), the optimal cut-off value of 83 kPa yields 87.10% sensitivity, 82.61% specificity, and 0.88 for the area under the curve (AUC). Conclusion CUSE has the potential for clinical utility as a quantitative diagnostic imaging tool adjunct to B-mode ultrasound for differentiation of malignant and benign breast masses. PMID:25774978

The diagnostic capability of laser induced fluorescence in the characterization of excised breast tissues

NASA Astrophysics Data System (ADS)

Galmed, A. H.; Elshemey, Wael M.

2017-08-01

Differentiating between normal, benign and malignant excised breast tissues is one of the major worldwide challenges that need a quantitative, fast and reliable technique in order to avoid personal errors in diagnosis. Laser induced fluorescence (LIF) is a promising technique that has been applied for the characterization of biological tissues including breast tissue. Unfortunately, only few studies have adopted a quantitative approach that can be directly applied for breast tissue characterization. This work provides a quantitative means for such characterization via introduction of several LIF characterization parameters and determining the diagnostic accuracy of each parameter in the differentiation between normal, benign and malignant excised breast tissues. Extensive analysis on 41 lyophilized breast samples using scatter diagrams, cut-off values, diagnostic indices and receiver operating characteristic (ROC) curves, shows that some spectral parameters (peak height and area under the peak) are superior for characterization of normal, benign and malignant breast tissues with high sensitivity (up to 0.91), specificity (up to 0.91) and accuracy ranking (highly accurate).

Loss of the integral nuclear envelope protein SUN1 induces alteration of nucleoli

PubMed Central

Matsumoto, Ayaka; Sakamoto, Chiyomi; Matsumori, Haruka; Katahira, Jun; Yasuda, Yoko; Yoshidome, Katsuhide; Tsujimoto, Masahiko; Goldberg, Ilya G; Matsuura, Nariaki; Nakao, Mitsuyoshi; Saitoh, Noriko; Hieda, Miki

2016-01-01

ABSTRACT A supervised machine learning algorithm, which is qualified for image classification and analyzing similarities, is based on multiple discriminative morphological features that are automatically assembled during the learning processes. The algorithm is suitable for population-based analysis of images of biological materials that are generally complex and heterogeneous. Here we used the algorithm wndchrm to quantify the effects on nucleolar morphology of the loss of the components of nuclear envelope in a human mammary epithelial cell line. The linker of nucleoskeleton and cytoskeleton (LINC) complex, an assembly of nuclear envelope proteins comprising mainly members of the SUN and nesprin families, connects the nuclear lamina and cytoskeletal filaments. The components of the LINC complex are markedly deficient in breast cancer tissues. We found that a reduction in the levels of SUN1, SUN2, and lamin A/C led to significant changes in morphologies that were computationally classified using wndchrm with approximately 100% accuracy. In particular, depletion of SUN1 caused nucleolar hypertrophy and reduced rRNA synthesis. Further, wndchrm revealed a consistent negative correlation between SUN1 expression and the size of nucleoli in human breast cancer tissues. Our unbiased morphological quantitation strategies using wndchrm revealed an unexpected link between the components of the LINC complex and the morphologies of nucleoli that serves as an indicator of the malignant phenotype of breast cancer cells. PMID:26962703

Loss of the integral nuclear envelope protein SUN1 induces alteration of nucleoli.

PubMed

Matsumoto, Ayaka; Sakamoto, Chiyomi; Matsumori, Haruka; Katahira, Jun; Yasuda, Yoko; Yoshidome, Katsuhide; Tsujimoto, Masahiko; Goldberg, Ilya G; Matsuura, Nariaki; Nakao, Mitsuyoshi; Saitoh, Noriko; Hieda, Miki

2016-01-01

A supervised machine learning algorithm, which is qualified for image classification and analyzing similarities, is based on multiple discriminative morphological features that are automatically assembled during the learning processes. The algorithm is suitable for population-based analysis of images of biological materials that are generally complex and heterogeneous. Here we used the algorithm wndchrm to quantify the effects on nucleolar morphology of the loss of the components of nuclear envelope in a human mammary epithelial cell line. The linker of nucleoskeleton and cytoskeleton (LINC) complex, an assembly of nuclear envelope proteins comprising mainly members of the SUN and nesprin families, connects the nuclear lamina and cytoskeletal filaments. The components of the LINC complex are markedly deficient in breast cancer tissues. We found that a reduction in the levels of SUN1, SUN2, and lamin A/C led to significant changes in morphologies that were computationally classified using wndchrm with approximately 100% accuracy. In particular, depletion of SUN1 caused nucleolar hypertrophy and reduced rRNA synthesis. Further, wndchrm revealed a consistent negative correlation between SUN1 expression and the size of nucleoli in human breast cancer tissues. Our unbiased morphological quantitation strategies using wndchrm revealed an unexpected link between the components of the LINC complex and the morphologies of nucleoli that serves as an indicator of the malignant phenotype of breast cancer cells.

Aberrant Breast in a Rare Site: A Case Report

PubMed Central

Yeniay, Levent; Mulailwa, Kilongo; Asgerov, Elmir; Hoşcoşkun, Cüneyt; Zekioğlu, Osman

2012-01-01

Aberrant breast tissue is an anomaly in the embryogenesis of the breast that is found along the mammary ridge or out of that line. We report a case of a 71-year-old female patient with an abdominal aberrant breast tissue found incidentally in a piece of mesenteric biopsy. The histological features were consistent with breast tissue. PMID:22792115

Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keller, Brad M.; Nathan, Diane L.; Wang Yan

Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., 'FOR PROCESSING') andmore » vendor postprocessed (i.e., 'FOR PRESENTATION'), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then aggregated into a final dense tissue segmentation that is used to compute breast PD%. Our method is validated on a group of 81 women for whom bilateral, mediolateral oblique, raw and processed screening digital mammograms were available, and agreement is assessed with both continuous and categorical density estimates made by a trained breast-imaging radiologist. Results: Strong association between algorithm-estimated and radiologist-provided breast PD% was detected for both raw (r= 0.82, p < 0.001) and processed (r= 0.85, p < 0.001) digital mammograms on a per-breast basis. Stronger agreement was found when overall breast density was assessed on a per-woman basis for both raw (r= 0.85, p < 0.001) and processed (0.89, p < 0.001) mammograms. Strong agreement between categorical density estimates was also seen (weighted Cohen's {kappa}{>=} 0.79). Repeated measures analysis of variance demonstrated no statistically significant differences between the PD% estimates (p > 0.1) due to either presentation of the image (raw vs processed) or method of PD% assessment (radiologist vs algorithm). Conclusions: The proposed fully automated algorithm was successful in estimating breast percent density from both raw and processed digital mammographic images. Accurate assessment of a woman's breast density is critical in order for the estimate to be incorporated into risk assessment models. These results show promise for the clinical application of the algorithm in quantifying breast density in a repeatable manner, both at time of imaging as well as in retrospective studies.« less

Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation

PubMed Central

Keller, Brad M.; Nathan, Diane L.; Wang, Yan; Zheng, Yuanjie; Gee, James C.; Conant, Emily F.; Kontos, Despina

2012-01-01

Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., “FOR PROCESSING”) and vendor postprocessed (i.e., “FOR PRESENTATION”), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then aggregated into a final dense tissue segmentation that is used to compute breast PD%. Our method is validated on a group of 81 women for whom bilateral, mediolateral oblique, raw and processed screening digital mammograms were available, and agreement is assessed with both continuous and categorical density estimates made by a trained breast-imaging radiologist. Results: Strong association between algorithm-estimated and radiologist-provided breast PD% was detected for both raw (r = 0.82, p < 0.001) and processed (r = 0.85, p < 0.001) digital mammograms on a per-breast basis. Stronger agreement was found when overall breast density was assessed on a per-woman basis for both raw (r = 0.85, p < 0.001) and processed (0.89, p < 0.001) mammograms. Strong agreement between categorical density estimates was also seen (weighted Cohen's κ ≥ 0.79). Repeated measures analysis of variance demonstrated no statistically significant differences between the PD% estimates (p > 0.1) due to either presentation of the image (raw vs processed) or method of PD% assessment (radiologist vs algorithm). Conclusions: The proposed fully automated algorithm was successful in estimating breast percent density from both raw and processed digital mammographic images. Accurate assessment of a woman's breast density is critical in order for the estimate to be incorporated into risk assessment models. These results show promise for the clinical application of the algorithm in quantifying breast density in a repeatable manner, both at time of imaging as well as in retrospective studies. PMID:22894417

Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation.

PubMed

Keller, Brad M; Nathan, Diane L; Wang, Yan; Zheng, Yuanjie; Gee, James C; Conant, Emily F; Kontos, Despina

2012-08-01

The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., "FOR PROCESSING") and vendor postprocessed (i.e., "FOR PRESENTATION"), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then aggregated into a final dense tissue segmentation that is used to compute breast PD%. Our method is validated on a group of 81 women for whom bilateral, mediolateral oblique, raw and processed screening digital mammograms were available, and agreement is assessed with both continuous and categorical density estimates made by a trained breast-imaging radiologist. Strong association between algorithm-estimated and radiologist-provided breast PD% was detected for both raw (r = 0.82, p < 0.001) and processed (r = 0.85, p < 0.001) digital mammograms on a per-breast basis. Stronger agreement was found when overall breast density was assessed on a per-woman basis for both raw (r = 0.85, p < 0.001) and processed (0.89, p < 0.001) mammograms. Strong agreement between categorical density estimates was also seen (weighted Cohen's κ ≥ 0.79). Repeated measures analysis of variance demonstrated no statistically significant differences between the PD% estimates (p > 0.1) due to either presentation of the image (raw vs processed) or method of PD% assessment (radiologist vs algorithm). The proposed fully automated algorithm was successful in estimating breast percent density from both raw and processed digital mammographic images. Accurate assessment of a woman's breast density is critical in order for the estimate to be incorporated into risk assessment models. These results show promise for the clinical application of the algorithm in quantifying breast density in a repeatable manner, both at time of imaging as well as in retrospective studies.

Estrogen receptor-beta expression in invasive breast cancer in relation to molecular phenotype: results from the Nurses' Health Study.

PubMed

Marotti, Jonathan D; Collins, Laura C; Hu, Rong; Tamimi, Rulla M

2010-02-01

The expression of estrogen receptor-alpha (ER-alpha) and related genes has emerged as one of the major determinants of molecular classification of invasive breast cancers. Expression of a second ER, estrogen receptor-beta (ER-beta), has not been previously evaluated in a large population-based study. Therefore, we examined ER-beta expression in a large population of women with breast cancer to assess its relationship to molecular categories of invasive breast cancer. We constructed tissue microarrays from paraffin blocks of 3093 breast cancers that developed in women enrolled in the Nurses' Health Study. Tissue microarray sections were immunostained for ER-alpha, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), cytokeratin 5/6, epidermal growth factor receptor (EGFR) and with a monoclonal antibody to ER-beta. Cancers were categorized as luminal A (ER-alpha+ and/or PR+ and HER2-); luminal B (ER-alpha+ and/or PR+ and HER2+); HER2 (ER-alpha- and PR- and HER2+); and basal-like (ER-alpha-, PR-, HER2- and EGFR or cytokeratin 5/6+). The relationship between expression of ER-beta and molecular class of invasive breast cancer was analyzed. Overall, 68% of breast carcinomas were ER-beta+. Expression of ER-beta was significantly associated with expression of ER-alpha (P<0.0001) and PR (P<0.0001), and was inversely related to expression of HER2 (P=0.004), CK5/6 (P=0.02) and EGFR (P=0.006). Among 2170 invasive cancers with complete immunophenotypic data, 73% were luminal A, 5% luminal B, 6 % HER2 and 11% basal-like. ER-beta expression was significantly related to molecular category (P<0.0001) and was more common in luminal A (72% of cases) and B (68% of cases) than in HER2 or basal-like types. However, despite their being defined by the absence of ER-alpha expression, 55% of HER2-type and 60% of basal-like cancers showed expression of ER-beta. The role of ER-beta in the development and progression of breast cancers defined by lack of expression of ER-alpha merits further investigation.

In vivo diagnosis of mammary adenocarcinoma using Raman spectroscopy: an animal model study

NASA Astrophysics Data System (ADS)

Bitar, R. A.; Ribeiro, D. G.; dos Santos, E. A. P.; Ramalho, L. N. Z.; Ramalho, F. S.; Martin, A. A.; Martinho, H. S.

2010-02-01

Breast cancer is the most frequent cancer type in women Worldwide. Sensitivity and specificity of clinical breast examinations have been estimated from clinical trials to be approximately 54 % and 94 %, respectively. Further, approximately 95 % of all positive breast cancer screenings turn out to be false-positive. The optimal method for early detection should be both highly sensitive to ensure that all cancers are detected, and also highly specific to avoid the humanistic and economic costs associated with false-positive results. In vivo optical spectroscopy techniques, Raman in particular, have been pointed out as promising tools to improve the accuracy of screening mammography. The aim of the present study was to apply FT-Raman spectroscopy to discriminate normal and adenocarcinoma breast tissues of Sprague-Dawley female rats. The study was performed on 32 rats divided in the control (N=5) and experimental (N=27) groups. Histological analysis indicated that mammary hyperplasia, cribriform, papillary and solid adenocarcinomas were found in the experimental group subjects. The spectral collection was made using a commercial FT-Raman Spectrometer (Bruker RFS100) equipped with fiber-optic probe (RamProbe) and the spectral region between 900 and 1800 cm-1 was analyzed. Principal Components Analysis, Cluster Analysis, and Linear Discriminant Analysis with cross-validation were applied as spectral classification algorithm. As concluding remarks it is show that normal and adenocarcinoma tissues discriminations was possible (correct proportion for Transcutaneous collection mode was 80.80% and for "Open Sky" mode was 91.70%); however, a conclusive diagnosis among the four lesion subtypes was not possible.

Characterization of human breast cancer tissues by infrared imaging.

PubMed

Verdonck, M; Denayer, A; Delvaux, B; Garaud, S; De Wind, R; Desmedt, C; Sotiriou, C; Willard-Gallo, K; Goormaghtigh, E

2016-01-21

Fourier Transform InfraRed (FTIR) spectroscopy coupled to microscopy (IR imaging) has shown unique advantages in detecting morphological and molecular pathologic alterations in biological tissues. The aim of this study was to evaluate the potential of IR imaging as a diagnostic tool to identify characteristics of breast epithelial cells and the stroma. In this study a total of 19 breast tissue samples were obtained from 13 patients. For 6 of the patients, we also obtained Non-Adjacent Non-Tumor tissue samples. Infrared images were recorded on the main cell/tissue types identified in all breast tissue samples. Unsupervised Principal Component Analyses and supervised Partial Least Square Discriminant Analyses (PLS-DA) were used to discriminate spectra. Leave-one-out cross-validation was used to evaluate the performance of PLS-DA models. Our results show that IR imaging coupled with PLS-DA can efficiently identify the main cell types present in FFPE breast tissue sections, i.e. epithelial cells, lymphocytes, connective tissue, vascular tissue and erythrocytes. A second PLS-DA model could distinguish normal and tumor breast epithelial cells in the breast tissue sections. A patient-specific model reached particularly high sensitivity, specificity and MCC rates. Finally, we showed that the stroma located close or at distance from the tumor exhibits distinct spectral characteristics. In conclusion FTIR imaging combined with computational algorithms could be an accurate, rapid and objective tool to identify/quantify breast epithelial cells and differentiate tumor from normal breast tissue as well as normal from tumor-associated stroma, paving the way to the establishment of a potential complementary tool to ensure safe tumor margins.

A new orthosis reduces pain and mechanical forces in prone position in women with augmented or natural breast tissue: a pilot study.

PubMed

Armstrong, Simon; Ried, Karin; Sali, Avni; McLaughlin, Patrick

2013-07-01

Breast augmentation, post-mastectomy patients as well as some women with natural breast tissue, and lactating, women often experience discomfort in prone activities. Our study, for the first time, examines pain levels, mechanical force and peak pressure in natural, reconstructed and augmented breast tissues with and without a new orthosis designed for reduction of displacement, compression and loading forces through the breast tissue during prone activities. Twelve females with natural, lactating or augmented breast tissue, and cup-sizes C-F volunteered for the study. Pain perception was measured using an 11-point visual-analogue-scale without and with different sizes/textures of the orthosis. Magnetic-Resonance-Imaging captured segmental transverse and para-sagittal mid-breast views, and provided linear measurements of breast tissue displacement and deformation. Capacitance-pliance® sensorstrips were used to measure force and pressure between the breast tissue and the surface of a standard treatment table. Measurements were taken whilst the participants were load bearing in prone positions with and without the orthosis. The new orthosis significantly reduced pain and mechanical forces in participants with natural or augmented breast tissue with cup-sizes C-F. Larger orthotic sizes were correlated with greater reduction in pain and mechanical forces, with all participants reporting no pain with the largest size orthotic. A size-3 orthotic decreased load on the breast tissue by 82% and reduced peak pressure by 42%. The same orthotic decreased medio-lateral spread of breast tissue and implant whilst increasing height. The new orthosis significantly reduced pain and mechanical forces in all women with natural or augmented tissues. Results are of clinical significance, as reduced mechanical forces are associated with greater comfort and reduced pressure and displacement which may lower the probability of breast implant complication. In clinical settings the orthosis is recommended for all augmentation patients when undergoing prone treatment by therapists and clinicians for improved comfort and safety. Copyright © 2013 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Breast Reconstruction After Mastectomy

MedlinePlus

... reconstruct the breast? In autologous tissue reconstruction, a piece of tissue containing skin, fat, blood vessels, and ... body and used to rebuild the breast. This piece of tissue is called a flap. Different sites ...

Breast Cancer Research at NASA

NASA Technical Reports Server (NTRS)

1998-01-01

Breast tissue specimens in traditional sample dishes. NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cells (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunourous tissues.

Trace elemental correlation study in malignant and normal breast tissue by PIXE technique

NASA Astrophysics Data System (ADS)

Raju, G. J. Naga; Sarita, P.; Kumar, M. Ravi; Murty, G. A. V. Ramana; Reddy, B. Seetharami; Lakshminarayana, S.; Vijayan, V.; Lakshmi, P. V. B. Rama; Gavarasana, Satyanarayana; Reddy, S. Bhuloka

2006-06-01

Particle induced X-ray emission technique was used to study the variations in trace elemental concentrations between normal and malignant human breast tissue specimens and to understand the effects of altered homeostasis of these elements in the etiology of breast cancer. A 3 MeV proton beam was used to excite the biological samples of normal and malignant breast tissues. The elements Cl, K, Ca, Ti, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Br, Rb and Sr were identified and their relative concentrations were estimated. Almost all the elements were found to be elevated (p < 0.05, Wilcoxon signed-ranks test) in the cancerous tissues when compared with normal tissues. The excess levels of trace elements observed in the cancerous breast tissues could either be a cause or a consequence of breast cancer. Regarding their role in the initiation or promotion of breast cancer, one possible interpretation is that the elevated levels of Cu, Fe and Cr could have led to the formation of free radicals or other reactive oxygen species (ROS) that adversely affect DNA thereby causing breast cancer, which is mainly attributed to genetic abnormalities. Moreover, since Cu and Fe are required for angiogenesis, elevated concentrations of these elements are likely to promote breast cancer by increasing the blood supply for tumor growth. On the other hand elevated concentrations of elements in breast cancer tissues might also be a consequence of the cancer. This can be understood in terms of the biochemical and histological differences between normal and cancerous breast tissues. Tumors, characterized by unregulated multiplication of cells, need an ever-increasing supply of essential nutrients including trace elements. This probably results in an increased vascularity of malignant tissues, which in turn leads to enhancement of elemental concentrations in tumors.

21 CFR 884.5160 - Powered breast pump.

Code of Federal Regulations, 2010 CFR

2010-04-01

... § 884.5160 Powered breast pump. (a) Identification. A powered breast pump in an electrically powered suction device used to express milk from the breast. (b) Classification. Class II (performance standards). ... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Powered breast pump. 884.5160 Section 884.5160...

21 CFR 884.5160 - Powered breast pump.

Code of Federal Regulations, 2013 CFR

2013-04-01

... § 884.5160 Powered breast pump. (a) Identification. A powered breast pump in an electrically powered suction device used to express milk from the breast. (b) Classification. Class II (performance standards). ... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Powered breast pump. 884.5160 Section 884.5160...

21 CFR 884.5160 - Powered breast pump.

Code of Federal Regulations, 2011 CFR

2011-04-01

... § 884.5160 Powered breast pump. (a) Identification. A powered breast pump in an electrically powered suction device used to express milk from the breast. (b) Classification. Class II (performance standards). ... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Powered breast pump. 884.5160 Section 884.5160...

21 CFR 884.5160 - Powered breast pump.

Code of Federal Regulations, 2012 CFR

2012-04-01

... § 884.5160 Powered breast pump. (a) Identification. A powered breast pump in an electrically powered suction device used to express milk from the breast. (b) Classification. Class II (performance standards). ... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Powered breast pump. 884.5160 Section 884.5160...

21 CFR 884.5160 - Powered breast pump.

Code of Federal Regulations, 2014 CFR

2014-04-01

... § 884.5160 Powered breast pump. (a) Identification. A powered breast pump in an electrically powered suction device used to express milk from the breast. (b) Classification. Class II (performance standards). ... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Powered breast pump. 884.5160 Section 884.5160...

Evaluation of human epidermal growth factor receptor 2 (HER2) single nucleotide polymorphisms (SNPs) in normal and breast tumor tissues and their link with breast cancer prognostic factors.

PubMed

Furrer, Daniela; Lemieux, Julie; Côté, Marc-André; Provencher, Louise; Laflamme, Christian; Barabé, Frédéric; Jacob, Simon; Michaud, Annick; Diorio, Caroline

2016-12-01

Amplification of the human epidermal growth factor receptor 2 (HER2) gene is associated with worse prognosis and decreased overall survival in breast cancer patients. The HER2 gene contains several polymorphisms; two of the best-characterized HER2 polymorphisms are Ile655Val and Ala1170Pro. The aim of this study was to evaluate the association between these two HER2 polymorphisms in normal breast and breast cancer tissues and known breast cancer prognostic factors in a retrospective cohort study of 73 women with non-metastatic HER2-positive breast cancer. HER2 polymorphisms were assessed in breast cancer tissue and normal breast tissue using TaqMan assay. Ala1170Pro polymorphism in normal breast tissue was associated with age at diagnosis (p = 0.007), tumor size (p = 0.004) and lymphovascular invasion (p = 0.06). Similar significant associations in cancer tissues were observed. No association between the Ile655Val polymorphism and prognostic factors were observed. However, we found significant differences in the distribution of Ile655Val (p = 0.03) and Ala1170Pro (p = 0.01) genotypes between normal breast and breast tumor tissues. This study demonstrates that only the Ala1170Pro polymorphism is associated with prognostic factors in HER2-positive breast cancer patients. Moreover, our results suggest that both HER2 polymorphisms could play a significant role in carcinogenesis in non-metastatic HER2-positive breast cancer women. Copyright © 2016 Elsevier Ltd. All rights reserved.

Association between local inflammation and breast tissue age-related lobular involution among premenopausal and postmenopausal breast cancer patients

PubMed Central

Hanna, Mirette; Dumas, Isabelle; Orain, Michèle; Jacob, Simon; Têtu, Bernard; Sanschagrin, François; Bureau, Alexandre; Poirier, Brigitte; Diorio, Caroline

2017-01-01

Increased levels of pro-inflammatory markers and decreased levels of anti-inflammatory markers in the breast tissue can result in local inflammation. We aimed to investigate whether local inflammation in the breast tissue is associated with age-related lobular involution, a process inversely related to breast cancer risk. Levels of eleven pro- and anti-inflammatory markers were assessed by immunohistochemistry in normal breast tissue obtained from 164 pre- and postmenopausal breast cancer patients. Involution status of the breast (degree of lobular involution and the predominant lobule type) was microscopically assessed in normal breast tissue on hematoxylin-eosin stained mastectomy slides. Multivariate generalized linear models were used to assess the associations. In age-adjusted analyses, higher levels of pro-inflammatory markers IL-6, TNF-α, CRP, COX-2, leptin, SAA1 and IL-8; and anti-inflammatory marker IL-10, were inversely associated with the prevalence of complete lobular involution (all P≤0.04). Higher levels of the pro-inflammatory marker COX-2 were also associated with lower prevalence of predominant type 1/no type 3 lobules in the breast, an indicator of complete involution, in age-adjusted analysis (P = 0.017). Higher tissue levels of inflammatory markers, mainly the pro-inflammatory ones, are associated with less involuted breasts and may consequently be associated with an increased risk of developing breast cancer. PMID:28846716

Study of lipid metabolism by estimating the fat fraction in different breast tissues and in various breast tumor sub-types by in vivo 1H MR spectroscopy.

PubMed

Agarwal, Khushbu; Sharma, Uma; Mathur, Sandeep; Seenu, Vurthaluru; Parshad, Rajinder; Jagannathan, Naranamangalam R

2018-06-01

To evaluate the utility of fat fraction (FF) for the differentiation of different breast tissues and in various breast tumor subtypes using in vivo proton ( 1 H) magnetic resonance spectroscopy (MRS). 1 H MRS was performed on 68 malignant, 35 benign, and 30 healthy volunteers at 1.5 T. Malignant breast tissues of patients were characterized into different subtypes based on the differences in the expression of hormone receptors and the FF was calculated. Further, the sensitivity and specificity of FF to differentiate malignant from benign and from normal breast tissues of healthy volunteers was determined using receiver operator curve (ROC) analysis. A significantly lower FF of malignant (median 0.12; range 0.01-0.70) compared to benign lesions (median 0.28; range 0.02-0.71) and normal breast tissue of healthy volunteers (median 0.39; range 0.06-0.76) was observed. No significant difference in FF was seen between benign lesions and normal breast tissues of healthy volunteers. Sensitivity and specificity of 75% and 68.6%, respectively was obtained to differentiate malignant from benign lesions. For the differentiation of malignant from healthy breast tissues, 76% sensitivity and 74.5% specificity was achieved. Higher FF was seen in patients with ER-/PR- status as compared to ER+/PR+ patients. Similarly, FF of HER2neu+ tumors were significantly higher than in HER2neu- breast tumors. The results showed the potential of in vivo 1 H MRS in providing insight into the changes in the fat content of different types of breast tissues and in various breast tumor subtypes. Copyright © 2018 Elsevier Inc. All rights reserved.

A large-scale study of the ultrawideband microwave dielectric properties of normal, benign and malignant breast tissues obtained from cancer surgeries

NASA Astrophysics Data System (ADS)

Lazebnik, Mariya; Popovic, Dijana; McCartney, Leah; Watkins, Cynthia B.; Lindstrom, Mary J.; Harter, Josephine; Sewall, Sarah; Ogilvie, Travis; Magliocco, Anthony; Breslin, Tara M.; Temple, Walley; Mew, Daphne; Booske, John H.; Okoniewski, Michal; Hagness, Susan C.

2007-10-01

The development of microwave breast cancer detection and treatment techniques has been driven by reports of substantial contrast in the dielectric properties of malignant and normal breast tissues. However, definitive knowledge of the dielectric properties of normal and diseased breast tissues at microwave frequencies has been limited by gaps and discrepancies across previously published studies. To address these issues, we conducted a large-scale study to experimentally determine the ultrawideband microwave dielectric properties of a variety of normal, malignant and benign breast tissues, measured from 0.5 to 20 GHz using a precision open-ended coaxial probe. Previously, we reported the dielectric properties of normal breast tissue samples obtained from reduction surgeries. Here, we report the dielectric properties of normal (adipose, glandular and fibroconnective), malignant (invasive and non-invasive ductal and lobular carcinomas) and benign (fibroadenomas and cysts) breast tissue samples obtained from cancer surgeries. We fit a one-pole Cole-Cole model to the complex permittivity data set of each characterized sample. Our analyses show that the contrast in the microwave-frequency dielectric properties between malignant and normal adipose-dominated tissues in the breast is considerable, as large as 10:1, while the contrast in the microwave-frequency dielectric properties between malignant and normal glandular/fibroconnective tissues in the breast is no more than about 10%.

Concentration analysis of breast tissue phantoms with terahertz spectroscopy

PubMed Central

Truong, Bao C. Q.; Fitzgerald, Anthony J.; Fan, Shuting; Wallace, Vincent P.

2018-01-01

Terahertz imaging has been previously shown to be capable of distinguishing normal breast tissue from its cancerous form, indicating its applicability to breast conserving surgery. The heterogeneous composition of breast tissue is among the main challenges to progressing this potential research towards a practical application. In this paper, two concentration analysis methods are proposed for analyzing phantoms mimicking breast tissue. The dielectric properties and the double Debye parameters were used to determine the phantom composition. The first method is wholly based on the conventional effective medium theory while the second one combines this theoretical model with empirical polynomial models. Through assessing the accuracy of these methods, their potential for application to quantifying breast tissue pathology was confirmed. PMID:29541525

A new texture descriptor based on local micro-pattern for detection of architectural distortion in mammographic images

NASA Astrophysics Data System (ADS)

de Oliveira, Helder C. R.; Moraes, Diego R.; Reche, Gustavo A.; Borges, Lucas R.; Catani, Juliana H.; de Barros, Nestor; Melo, Carlos F. E.; Gonzaga, Adilson; Vieira, Marcelo A. C.

2017-03-01

This paper presents a new local micro-pattern texture descriptor for the detection of Architectural Distortion (AD) in digital mammography images. AD is a subtle contraction of breast parenchyma that may represent an early sign of breast cancer. Due to its subtlety and variability, AD is more difficult to detect compared to microcalcifications and masses, and is commonly found in retrospective evaluations of false-negative mammograms. Several computer-based systems have been proposed for automatic detection of AD, but their performance are still unsatisfactory. The proposed descriptor, Local Mapped Pattern (LMP), is a generalization of the Local Binary Pattern (LBP), which is considered one of the most powerful feature descriptor for texture classification in digital images. Compared to LBP, the LMP descriptor captures more effectively the minor differences between the local image pixels. Moreover, LMP is a parametric model which can be optimized for the desired application. In our work, the LMP performance was compared to the LBP and four Haralick's texture descriptors for the classification of 400 regions of interest (ROIs) extracted from clinical mammograms. ROIs were selected and divided into four classes: AD, normal tissue, microcalcifications and masses. Feature vectors were used as input to a multilayer perceptron neural network, with a single hidden layer. Results showed that LMP is a good descriptor to distinguish AD from other anomalies in digital mammography. LMP performance was slightly better than the LBP and comparable to Haralick's descriptors (mean classification accuracy = 83%).

Substrate Induced Conformational Studies of the Hormone Binding Domain of the Human Estrogen Receptor by Fluorine NMR

DTIC Science & Technology

1998-07-01

the progression of breast cancer and the estrogen receptor (ER) has been implicated in reproductive cancers . Our laboratory would like to understand how...function. ൖ. SUBJECT TERMS 15. NUMBER OF PAGES Breast Cancer 41 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION OF THIS 19...production of estrogen or estrogen like materials. Estrogen has been shown to be involved in the progression of breast cancer and the estrogen receptor (ER

A large-scale study of the ultrawideband microwave dielectric properties of normal breast tissue obtained from reduction surgeries.

PubMed

Lazebnik, Mariya; McCartney, Leah; Popovic, Dijana; Watkins, Cynthia B; Lindstrom, Mary J; Harter, Josephine; Sewall, Sarah; Magliocco, Anthony; Booske, John H; Okoniewski, Michal; Hagness, Susan C

2007-05-21

The efficacy of emerging microwave breast cancer detection and treatment techniques will depend, in part, on the dielectric properties of normal breast tissue. However, knowledge of these properties at microwave frequencies has been limited due to gaps and discrepancies in previously reported small-scale studies. To address these issues, we experimentally characterized the wideband microwave-frequency dielectric properties of a large number of normal breast tissue samples obtained from breast reduction surgeries at the University of Wisconsin and University of Calgary hospitals. The dielectric spectroscopy measurements were conducted from 0.5 to 20 GHz using a precision open-ended coaxial probe. The tissue composition within the probe's sensing region was quantified in terms of percentages of adipose, fibroconnective and glandular tissues. We fit a one-pole Cole-Cole model to the complex permittivity data set obtained for each sample and determined median Cole-Cole parameters for three groups of normal breast tissues, categorized by adipose tissue content (0-30%, 31-84% and 85-100%). Our analysis of the dielectric properties data for 354 tissue samples reveals that there is a large variation in the dielectric properties of normal breast tissue due to substantial tissue heterogeneity. We observed no statistically significant difference between the within-patient and between-patient variability in the dielectric properties.

Estimation of effective x-ray tissue attenuation differences for volumetric breast density measurement

NASA Astrophysics Data System (ADS)

Chen, Biao; Ruth, Chris; Jing, Zhenxue; Ren, Baorui; Smith, Andrew; Kshirsagar, Ashwini

2014-03-01

Breast density has been identified to be a risk factor of developing breast cancer and an indicator of lesion diagnostic obstruction due to masking effect. Volumetric density measurement evaluates fibro-glandular volume, breast volume, and breast volume density measures that have potential advantages over area density measurement in risk assessment. One class of volume density computing methods is based on the finding of the relative fibro-glandular tissue attenuation with regards to the reference fat tissue, and the estimation of the effective x-ray tissue attenuation differences between the fibro-glandular and fat tissue is key to volumetric breast density computing. We have modeled the effective attenuation difference as a function of actual x-ray skin entrance spectrum, breast thickness, fibro-glandular tissue thickness distribution, and detector efficiency. Compared to other approaches, our method has threefold advantages: (1) avoids the system calibration-based creation of effective attenuation differences which may introduce tedious calibrations for each imaging system and may not reflect the spectrum change and scatter induced overestimation or underestimation of breast density; (2) obtains the system specific separate and differential attenuation values of fibroglandular and fat for each mammographic image; and (3) further reduces the impact of breast thickness accuracy to volumetric breast density. A quantitative breast volume phantom with a set of equivalent fibro-glandular thicknesses has been used to evaluate the volume breast density measurement with the proposed method. The experimental results have shown that the method has significantly improved the accuracy of estimating breast density.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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 < 0.05) in disease-free survivals between the three CMTC groups after an additional two years of follow-up (median = 55 months). The prognostic 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.

Overexpression of SERBP1 (Plasminogen activator inhibitor 1 RNA binding protein) in human breast cancer is correlated with favourable prognosis.

PubMed

Serce, Nuran Bektas; Boesl, Andreas; Klaman, Irina; von Serényi, Sonja; Noetzel, Erik; Press, Michael F; Dimmler, Arno; Hartmann, Arndt; Sehouli, Jalid; Knuechel, Ruth; Beckmann, Matthias W; Fasching, Peter A; Dahl, Edgar

2012-12-13

Plasminogen activator inhibitor 1 (PAI-1) overexpression is an important prognostic and predictive biomarker in human breast cancer. SERBP1, a protein that is supposed to regulate the stability of PAI-1 mRNA, may play a role in gynaecological cancers as well, since upregulation of SERBP1 was described in ovarian cancer recently. This is the first study to present a systematic characterisation of SERBP1 expression in human breast cancer and normal breast tissue at both the mRNA and the protein level. Using semiquantitative realtime PCR we analysed SERBP1 expression in different normal human tissues (n = 25), and in matched pairs of normal (n = 7) and cancerous breast tissues (n = 7). SERBP1 protein expression was analysed in two independent cohorts on tissue microarrays (TMAs), an initial evaluation set, consisting of 193 breast carcinomas and 48 normal breast tissues, and a second large validation set, consisting of 605 breast carcinomas. In addition, a collection of benign (n = 2) and malignant (n = 6) mammary cell lines as well as breast carcinoma lysates (n = 16) were investigated for SERBP1 expression by Western blot analysis. Furthermore, applying non-radioisotopic in situ hybridisation a subset of normal (n = 10) and cancerous (n = 10) breast tissue specimens from the initial TMA were analysed for SERBP1 mRNA expression. SERBP1 is not differentially expressed in breast carcinoma compared to normal breast tissue, both at the RNA and protein level. However, recurrence-free survival analysis showed a significant correlation (P = 0.008) between abundant SERBP1 expression in breast carcinoma and favourable prognosis. Interestingly, overall survival analysis also displayed a tendency (P = 0.09) towards favourable prognosis when SERBP1 was overexpressed in breast cancer. The RNA-binding protein SERBP1 is abundantly expressed in human breast cancer and may represent a novel breast tumour marker with prognostic significance. Its potential involvement in the plasminogen activator protease cascade warrants further investigation.

Applying the Health Belief Model and an Integrated Behavioral Model to Promote Breast Tissue Donation Among Asian Americans.

PubMed

Shafer, Autumn; Kaufhold, Kelly; Luo, Yunjuan

2018-07-01

An important part in the effort to prevent, treat, and cure breast cancer is research done with healthy breast tissue. The Susan G. Komen for the Cure Tissue Bank at Indiana University Simon Cancer Center (KTB) encourages women to donate a small amount of healthy breast tissue and then provides that tissue to researchers studying breast cancer. Although KTB has a large donor base, the volume of tissue samples from Asian women is low despite prior marketing efforts to encourage donation among this population. This study builds on prior work promoting breast cancer screenings among Asian women by applying constructs from the Health Belief Model (HBM) and the Integrated Behavioral Model (IBM) to investigate why Asian-American women are less inclined to donate their healthy breast tissue than non-Asian women and how this population may be motivated to donate in the future. A national online survey (N = 1,317) found Asian women had significantly lower perceived severity, some lower perceived benefits, and higher perceived barriers to tissue donation than non-Asian women under HBM and significantly lower injunctive norms supporting breast tissue donation, lower perceived behavioral control, and lower intentions to donate under IBM. This study also compares and discusses similarities and differences among East, Southeast, and South Asian women on these same constructs.

Different CHEK2 germline mutations are associated with distinct immunophenotypic molecular subtypes of breast cancer.

PubMed

Domagala, Pawel; Wokolorczyk, Dominika; Cybulski, Cezary; Huzarski, Tomasz; Lubinski, Jan; Domagala, Wenancjusz

2012-04-01

Germline mutations in BRCA1 were already linked to basal-like subtype of immunophenotypic molecular classification of breast cancer (BC). However, it is not known whether mutations in other BC susceptibility genes are associated with molecular subtypes of this cancer. We tested the hypothesis that distinct mutations in another BC susceptibility gene involved in DNA repair, i.e., CHEK2 may be associated with particular immunophenotypic molecular subtypes of this cancer. Two groups of patients: 1255 with BCs and 5496 healthy controls were genotyped for four CHEK2 mutations (I157T and three truncating mutations: 1100delC, IVS2 + 1G > A, del5395). BCs were tested by immunohistochemistry on tissue microarrays for ER, PR, HER-2, EGFR, and CK5/6 and were assigned to appropriate subtypes of immunophenotypic molecular classification. There was a significant association between CHEK2 mutations and the immunophenotypic molecular classification (P = 0.004). CHEK2-associated cancers were predominantly luminal (108/117 = 92.3%). CHEK2-I157T variant was associated with the luminal A subtype (P = 0.01), whereas CHEK2-truncating mutations were associated with the luminal B subtype (P = 0.005). Comparing the prevalence of CHEK2 mutations in BC with controls revealed that carriers of an I157T variant had OR of 1.80 for luminal A subtype and carriers of truncating mutations had OR of 6.26 for luminal B subtype of BC. To our knowledge, this is the first study showing that specific mutations in the same susceptibility gene are associated with different immunophenotypic molecular subtypes of BC. This association represents independent evidence supporting the biological significance of immunophenotypic molecular classification of BC.

Status of estrogen receptor 1 (ESR1) gene in mastopathy predicts subsequent development of breast cancer.

PubMed

Soysal, Savas D; Kilic, Incken B; Regenbrecht, Christian R A; Schneider, Sandra; Muenst, Simone; Kilic, Nerbil; Güth, Uwe; Dietel, Manfred; Terracciano, Luigi M; Kilic, Ergin

2015-06-01

Mastopathy is a common disease of the breast likely associated with elevated estrogen levels and a putative risk factor for breast cancer. The role of estrogen receptor alpha (ESR1) in mastopathy has not been investigated previously. Here, we investigated the prevalence of ESR1 gene amplification in mastopathy and its prediction for breast cancer. Paraffin-embedded tissues from 58 women with invasive breast cancer were analyzed. For all women, tissues with mastopathy taken at least 1.5 years before first diagnosis of breast cancer were available. Tissue from 46 women with mastopathy without a diagnosis of breast carcinoma in the observed time frame (12-18 years) was used as control. Fluorescence in situ hybridization analysis revealed that ESR1 was amplified in nine of 58 (15.5 %) breast cancers. All ESR1-amplified breast cancers were strongly positive for estrogen receptor with ER immunohistochemistry. Interestingly, in women with ESR1 amplification in breast cancer, the amplification was detectable in mastopathic tissues prior to the first diagnosis of breast cancer but was absent in tissues from women with mastopathy who did not develop breast cancer. Our study suggests that ESR1 gene amplification is an early event in breast pathology and might be a helpful predictive marker to identify patients at high risk of developing breast cancer.

Blood and Tissue Enzymatic Activities of GDH and LDH, Index of Glutathione, and Oxidative Stress among Breast Cancer Patients Attending Referral Hospitals of Addis Ababa, Ethiopia: Hospital-Based Comparative Cross-Sectional Study

PubMed Central

Seyoum, Nebiyou; Bekele, Mahteme; Tigeneh, Wondimagegn; Seifu, Daniel

2018-01-01

The exact cause of breast cancer is unknown; it is a multifactorial disease. It is the most diagnosed and the second killer cancer among women. Breast cancer can be originated from tissues of breast or secondary from other organs via metastasis. Generally, cancer cells show aberrant metabolism and oxidative stress when compared to noncancerous tissues of breast cancer patients. The current study aims at evaluating glutamate and glucose metabolism through GDH and LDH enzyme activities, oxidant, and antioxidative status among breast cancer patients attending referral hospitals of Addis Ababa, Ethiopia. Result. Catalytic activities of glutamate dehydrogenase, lactate dehydrogenase, and oxidative stress index were significantly increased in both serum (4.2 mU/ml, 78.6 mU/ml, and 3.3 : 1, resp.) and cancerous tissues (1.4 mU/ml, 111.7 mU/ml, and 2.15 : 1, resp.) of breast cancer patients as compared to those in serum of control group (3.15 mU/ml, 30.4 mU/ml, and 2.05 : 1, resp.) and noncancerous tissues of breast cancer patients (0.92 mU/ml, 70.5 mU/ml, and 1.1 : 1, resp.) (P ≤ 0.05). Correspondingly, ratios of reduced to oxidized glutathione were significantly decreased in both serum (20 : 1) and cancerous tissues (23.5 : 1) of breast cancer patients when compared to those in serum of control group (104.5 : 1) and noncancerous tissues of breast cancer patients (70.9 : 1) (P ≤ 0.05). Conclusion. Catalytic activities of GDH and LDH, ratios of GSH to GSSG, and concentration of TOS among breast cancer patients were significantly higher than were those among control group and noncancerous tissues of breast cancer patients, while TAC of breast cancer patients is significantly lower than that of control group and normal tissues of breast cancer patients. PMID:29770168

Blood and Tissue Enzymatic Activities of GDH and LDH, Index of Glutathione, and Oxidative Stress among Breast Cancer Patients Attending Referral Hospitals of Addis Ababa, Ethiopia: Hospital-Based Comparative Cross-Sectional Study.

PubMed

Mehdi, Mohammed; Menon, M K C; Seyoum, Nebiyou; Bekele, Mahteme; Tigeneh, Wondimagegn; Seifu, Daniel

2018-01-01

The exact cause of breast cancer is unknown; it is a multifactorial disease. It is the most diagnosed and the second killer cancer among women. Breast cancer can be originated from tissues of breast or secondary from other organs via metastasis. Generally, cancer cells show aberrant metabolism and oxidative stress when compared to noncancerous tissues of breast cancer patients. The current study aims at evaluating glutamate and glucose metabolism through GDH and LDH enzyme activities, oxidant, and antioxidative status among breast cancer patients attending referral hospitals of Addis Ababa, Ethiopia. Result . Catalytic activities of glutamate dehydrogenase, lactate dehydrogenase, and oxidative stress index were significantly increased in both serum (4.2 mU/ml, 78.6 mU/ml, and 3.3 : 1, resp.) and cancerous tissues (1.4 mU/ml, 111.7 mU/ml, and 2.15 : 1, resp.) of breast cancer patients as compared to those in serum of control group (3.15 mU/ml, 30.4 mU/ml, and 2.05 : 1, resp.) and noncancerous tissues of breast cancer patients (0.92 mU/ml, 70.5 mU/ml, and 1.1 : 1, resp.) ( P ≤ 0.05). Correspondingly, ratios of reduced to oxidized glutathione were significantly decreased in both serum (20 : 1) and cancerous tissues (23.5 : 1) of breast cancer patients when compared to those in serum of control group (104.5 : 1) and noncancerous tissues of breast cancer patients (70.9 : 1) ( P ≤ 0.05). Conclusion . Catalytic activities of GDH and LDH, ratios of GSH to GSSG, and concentration of TOS among breast cancer patients were significantly higher than were those among control group and noncancerous tissues of breast cancer patients, while TAC of breast cancer patients is significantly lower than that of control group and normal tissues of breast cancer patients.

Identification and prognostic value of anterior gradient protein 2 expression in breast cancer based on tissue microarray.

PubMed

Guo, Jilong; Gong, Guohua; Zhang, Bin

2017-07-01

Breast cancer has attracted substantial attention as one of the major cancers causing death in women. It is crucial to find potential biomarkers of prognostic value in breast cancer. In this study, the expression pattern of anterior gradient protein 2 in breast cancer was identified based on the main molecular subgroups. Through analysis of 69 samples from the Gene Expression Omnibus database, we found that anterior gradient protein 2 expression was significantly higher in non-triple-negative breast cancer tissues compared with normal tissues and triple-negative breast cancer tissues (p < 0.05). The data from a total of 622 patients from The Cancer Genome Atlas were analysed. The data from The Cancer Genome Atlas and results from quantitative reverse transcription polymerase chain reaction also verified the anterior gradient protein 2 expression pattern. Furthermore, we performed immunohistochemical analysis. The quantification results revealed that anterior gradient protein 2 is highly expressed in non-triple-negative breast cancer (grade 3 excluded) and grade 1 + 2 (triple-negative breast cancer excluded) tumours compared with normal tissues. Anterior gradient protein 2 was significantly highly expressed in non-triple-negative breast cancer (grade 3 excluded) and non-triple-negative breast cancer tissues compared with triple-negative breast cancer tissues (p < 0.01). In addition, anterior gradient protein 2 was significantly highly expressed in grade 1 + 2 (triple-negative breast cancer excluded) and grade 1 + 2 tissues compared with grade 3 tissues (p < 0.05). Analysis by Fisher's exact test revealed that anterior gradient protein 2 expression was significantly associated with histologic type, histological grade, oestrogen status and progesterone status. Univariate analysis of clinicopathological variables showed that anterior gradient protein 2 expression, tumour size and lymph node status were significantly correlated with overall survival in patients with grade 1 and 2 tumours. Cox multivariate analysis revealed anterior gradient protein 2 as a putative independent indicator of unfavourable outcomes (p = 0.031). All these data clearly showed that anterior gradient protein 2 is highly expressed in breast cancer and can be regarded as a putative biomarker for breast cancer prognosis.

Investigation of the accuracy of breast tissue segmentation methods for the purpose of developing breast deformation models for use in adaptive radiotherapy

NASA Astrophysics Data System (ADS)

Juneja, P.; Harris, E. J.; Evans, P. M.

2014-03-01

Realistic modelling of breast deformation requires the breast tissue to be segmented into fibroglandular and fatty tissue and assigned suitable material properties. There are a number of breast tissue segmentation methods proposed and used in the literature. The purpose of this study was to validate and compare the accuracy of various segmentation methods and to investigate the effect of the tissue distribution on the segmentation accuracy. Computed tomography (CT) data for 24 patients, both in supine and prone positions were segmented into fibroglandular and fatty tissue. The segmentation methods explored were: physical density thresholding; interactive thresholding; fuzzy c-means clustering (FCM) with three classes (FCM3) and four classes (FCM4); and k-means clustering. Validation was done in two-stages: firstly, a new approach, supine-prone validation based on the assumption that the breast composition should appear the same in the supine and prone scans was used. Secondly, outlines from three experts were used for validation. This study found that FCM3 gave the most accurate segmentation of breast tissue from CT data and that the segmentation accuracy is adversely affected by the sparseness of the fibroglandular tissue distribution.

21 CFR 884.5150 - Nonpowered breast pump.

Code of Federal Regulations, 2013 CFR

2013-04-01

... device used to express milk from the breast. (b) Classification. Class I. The device is exempt from the... 250 mm Hg suction, and the device materials that contact breast or breast milk do not produce... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Nonpowered breast pump. 884.5150 Section 884.5150...

21 CFR 884.5150 - Nonpowered breast pump.

Code of Federal Regulations, 2010 CFR

2010-04-01

... device used to express milk from the breast. (b) Classification. Class I. The device is exempt from the... 250 mm Hg suction, and the device materials that contact breast or breast milk do not produce... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Nonpowered breast pump. 884.5150 Section 884.5150...

21 CFR 884.5150 - Nonpowered breast pump.

Code of Federal Regulations, 2014 CFR

2014-04-01

... device used to express milk from the breast. (b) Classification. Class I. The device is exempt from the... 250 mm Hg suction, and the device materials that contact breast or breast milk do not produce... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Nonpowered breast pump. 884.5150 Section 884.5150...

21 CFR 884.5150 - Nonpowered breast pump.

Code of Federal Regulations, 2012 CFR

2012-04-01

... device used to express milk from the breast. (b) Classification. Class I. The device is exempt from the... 250 mm Hg suction, and the device materials that contact breast or breast milk do not produce... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Nonpowered breast pump. 884.5150 Section 884.5150...

21 CFR 884.5150 - Nonpowered breast pump.

Code of Federal Regulations, 2011 CFR

2011-04-01

... device used to express milk from the breast. (b) Classification. Class I. The device is exempt from the... 250 mm Hg suction, and the device materials that contact breast or breast milk do not produce... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Nonpowered breast pump. 884.5150 Section 884.5150...

Tumor response estimation in radar-based microwave breast cancer detection.

PubMed

Kurrant, Douglas J; Fear, Elise C; Westwick, David T

2008-12-01

Radar-based microwave imaging techniques have been proposed for early stage breast cancer detection. A considerable challenge for the successful implementation of these techniques is the reduction of clutter, or components of the signal originating from objects other than the tumor. In particular, the reduction of clutter from the late-time scattered fields is required in order to detect small (subcentimeter diameter) tumors. In this paper, a method to estimate the tumor response contained in the late-time scattered fields is presented. The method uses a parametric function to model the tumor response. A maximum a posteriori estimation approach is used to evaluate the optimal values for the estimates of the parameters. A pattern classification technique is then used to validate the estimation. The ability of the algorithm to estimate a tumor response is demonstrated by using both experimental and simulated data obtained with a tissue sensing adaptive radar system.

Estimation of percentage breast tissue density: comparison between digital mammography (2D full field digital mammography) and digital breast tomosynthesis according to different BI-RADS categories.

PubMed

Tagliafico, A S; Tagliafico, G; Cavagnetto, F; Calabrese, M; Houssami, N

2013-11-01

To compare breast density estimated from two-dimensional full-field digital mammography (2D FFDM) and from digital breast tomosynthesis (DBT) according to different Breast Imaging-Reporting and Data System (BI-RADS) categories, using automated software. Institutional review board approval and written informed patient consent were obtained. DBT and 2D FFDM were performed in the same patients to allow within-patient comparison. A total of 160 consecutive patients (mean age: 50±14 years; mean body mass index: 22±3) were included to create paired data sets of 40 patients for each BI-RADS category. Automatic software (MedDensity(©), developed by Giulio Tagliafico) was used to compare the percentage breast density between DBT and 2D FFDM. The estimated breast percentage density obtained using DBT and 2D FFDM was examined for correlation with the radiologists' visual BI-RADS density classification. The 2D FFDM differed from DBT by 16.0% in BI-RADS Category 1, by 11.9% in Category 2, by 3.5% in Category 3 and by 18.1% in Category 4. These differences were highly significant (p<0.0001). There was a good correlation between the BI-RADS categories and the density evaluated using 2D FFDM and DBT (r=0.56, p<0.01 and r=0.48, p<0.01, respectively). Using DBT, breast density values were lower than those obtained using 2D FFDM, with a non-linear relationship across the BI-RADS categories. These data are relevant for clinical practice and research studies using density in determining the risk. On DBT, breast density values were lower than with 2D FFDM, with a non-linear relationship across the classical BI-RADS categories.

Breast Cancer Research at NASA

NASA Technical Reports Server (NTRS)

1998-01-01

Dr. Robert Richmond extracts breast cell tissue from one of two liquid nitrogen dewars. NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cells (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunourous tissues.

DNA methylation age is elevated in breast tissue of healthy women.

PubMed

Sehl, Mary E; Henry, Jill E; Storniolo, Anna Maria; Ganz, Patricia A; Horvath, Steve

2017-07-01

Limited evidence suggests that female breast tissue ages faster than other parts of the body according to an epigenetic biomarker of aging known as the "epigenetic clock." However, it is unknown whether breast tissue samples from healthy women show a similar accelerated aging effect relative to other tissues, and what could drive this acceleration. The goal of this study is to validate our initial finding of advanced DNA methylation (DNAm) age in breast tissue, by directly comparing it to that of peripheral blood tissue from the same individuals, and to do a preliminary assessment of hormonal factors that could explain the difference. We utilized n = 80 breast and 80 matching blood tissue samples collected from 40 healthy female participants of the Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center who donated these samples at two time points spaced at least a year apart. DNA methylation levels (Illumina 450K platform) were used to estimate the DNAm age. DNAm age was highly correlated with chronological age in both peripheral blood (r = 0.94, p < 0.0001) and breast tissues (r = 0.86, p < 0.0001). A measure of epigenetic age acceleration (age-adjusted DNAm Age) was substantially increased in breast relative to peripheral blood tissue (p = 1.6 × 10 -11 ). The difference between DNAm age of breast and blood decreased with advancing chronologic age (r = -0.53, p = 4.4 × 10 -4 ). Our data clearly demonstrate that female breast tissue has a higher epigenetic age than blood collected from the same subject. We also observe that the degree of elevation in breast diminishes with advancing age. Future larger studies will be needed to examine associations between epigenetic age acceleration and cumulative hormone exposure.

Lightweight Breast Implants: A Novel Solution for Breast Augmentation and Reconstruction Mammaplasty

PubMed Central

Govrin-Yehudain, Jacky; Dvir, Haim; Preise, Dina; Govrin-Yehudain, Orel; Govreen-Segal, Dael

2015-01-01

Breast augmentation and reconstruction mammaplasty have been in practice for decades and are highly prevalent surgeries performed worldwide. While overall patient satisfaction is high, common long-term effects include breast tissue atrophy, accelerated ptosis and inframammary fold breakdown. Increasing evidence attributes these events to the durative loading and compressive forces introduced by the breast implants. Mechanical challenges exceeding the elastic capacity of the breast tissue components, eventually lead to irreversible tissue stretching, directly proportional to the introduced mass. Thus, it is suggested that, contrary to long-standing dogmas, implant weight, rather than its volume, stands at the basis of future tissue compromise and deformation. A novel lightweight implant has been developed to address the drawbacks of traditional breast implants, which demonstrate equivalence between their size and weight. The B-Lite® breast implant (G&G Biotechnology Ltd., Haifa, Israel) design allows for a reduction in implant weight of up to 30%, while maintaining the size, form, and function of traditional breast implants. The CE-marked device can be effectively implanted using standard of care procedures and has been established safe for human use. Implantation of the B-Lite® breast implant is projected to significantly reduce the inherent strains imposed by standard implants, thereby conserving tissue stability and integrity over time. In summary, this novel, lightweight breast implant promises to reduce breast tissue compromise and deformation and subsequent reoperation, further improving patient safety and satisfaction. PMID:26333989

Preclinical evaluation of transcriptional targeting strategies for carcinoma of the breast in a tissue slice model system

PubMed Central

Stoff-Khalili, Mariam A; Stoff, Alexander; Rivera, Angel A; Banerjee, Nilam S; Everts, Maaike; Young, Scott; Siegal, Gene P; Richter, Dirk F; Wang, Minghui; Dall, Peter; Mathis, J Michael; Zhu, Zeng B; Curiel, David T

2005-01-01

Introduction In view of the limited success of available treatment modalities for metastatic breast cancer, alternative and complementary strategies need to be developed. Adenoviral vector mediated strategies for breast cancer gene therapy and virotherapy are a promising novel therapeutic platform for the treatment of breast cancer. However, the promiscuous tropism of adenoviruses (Ads) is a major concern. Employing tissue specific promoters (TSPs) to restrict transgene expression or viral replication is an effective way to increase specificity towards tumor tissues and to reduce adverse effects in non-target tissues such as the liver. In this regard, candidate breast cancer TSPs include promoters of the genes for the epithelial glycoprotein 2 (EGP-2), cyclooxygenase-2 (Cox-2), α-chemokine SDF-1 receptor (stromal-cell-derived factor, CXCR4), secretory leukoprotease inhibitor (SLPI) and survivin. Methods We employed E1-deleted Ads that express the reporter gene luciferase under the control of the promoters of interest. We evaluated this class of vectors in various established breast cancer cell lines, primary breast cancer cells and finally in the most stringent preclinical available substrate system, constituted by precision cut tissue slices of human breast cancer and liver. Results Overall, the CXCR4 promoter exhibited the highest luciferase activity in breast cancer cell lines, primary breast cancer cells and breast cancer tissue slices. Importantly, the CXCR4 promoter displayed a very low activity in human primary fibroblasts and human liver tissue slices. Interestingly, gene expression profiles correlated with the promoter activities both in breast cancer cell lines and primary breast cancer cells. Conclusion These data suggest that the CXCR4 promoter has an ideal 'breast cancer-on/liver-off' profile, and could, therefore, be a powerful tool in Ad vector based gene therapy or virotherapy of the carcinoma of the breast. PMID:16457694

Circulating testosterone and prostate-specific antigen in nipple aspirate fluid and tissue are associated with breast cancer.

PubMed Central

Sauter, Edward R; Tichansky, David S; Chervoneva, Inna; Diamandis, Eleftherios P

2002-01-01

Preliminary evidence has associated testosterone and prostate-specific antigen (PSA) with breast cancer. Our objective was to determine whether a) testosterone levels in nipple aspirate fluid (NAF), serum, or breast tissue are associated with breast cancer; b) testosterone levels in serum are associated with levels in NAF; c) PSA in NAF, serum, or breast tissue is associated with breast cancer; and d) serum PSA is associated with NAF PSA levels. We obtained 342 NAF specimens from 171 women by means of a modified breast pump. Additionally, we collected 201 blood samples from 99 women and 51 tissue samples from 41 subjects who underwent surgical resection for suspected disease. Women currently using birth control pills or hormone replacement therapy were excluded from the study. Controlling for age and menopausal status, serum testosterone was significantly increased in women with breast cancer (p = 0.002). NAF and serum testosterone levels were not associated. Neither NAF nor tissue testosterone was associated with breast cancer. Controlling for menopausal status and age, NAF PSA was significantly decreased in women with breast cancer (p < 0.001). We did not find serum PSA to be associated with breast cancer, although we found an indication that, in postmenopausal women, its levels were lower in women with cancer. Serum PSA was associated with NAF PSA in postmenopausal women (p < 0.001). PSA levels in cancerous tissue were significantly lower than in benign breast specimens from subjects without cancer (p = 0.011), whereas levels of PSA in histologically benign specimens from subjects with cancer were intermediate. Our results suggest that serum testosterone is increased and NAF PSA is decreased in women with breast cancer, with PSA expression being higher in normal than in cancerous breast tissues. NAF and serum PSA levels in postmenopausal women are correlated, suggesting that as laboratory assessment of PSA becomes more sensitive, serum PSA may become useful in identifying women with breast cancer. PMID:11882474

Expression of Leukemia/Lymphoma-Related Factor (LRF/POKEMON) in Human Breast Carcinoma and Other Cancers

PubMed Central

Aggarwal, Anshu; Hunter, William J.; Aggarwal, Himanshu; Silva, Edibaldo D.; Davey, Mary S.; Murphy, Richard F.; Agrawal, Devendra K.

2010-01-01

The POK family of proteins plays an important role in not only embryonic development and cell differentiation, but also in oncogenesis. Leukemia/lymphoma-related factor (LRF) belongs to the POK family of transcriptional repressors and is also known as POK erythroid myeloid ontogenic factor (POKEMON), which binds to short transcripts of HIV-1 (FBI-1) and TTF-1 interacting peptide (TIP21). Its oncogenic role is known only in lymphoma, non-small cell lung carcinoma, and malignant gliomas. The functional expression of LRF in human breast carcinoma has not yet been confirmed. The aim of this study was to investigate and compare the expression of LRF in human breast cancer tissues and other human tumors. The expression of LRF mRNA transcripts and protein was observed in twenty human benign and malignant breast biopsy tissues. Expression of LRF was observed in several formalin-fixed tissues by immunohistochemistry and immunofluorescence. All malignant breast tissues expressed mRNA transcripts and protein for LRF. However, 40% and 15% benign breast biopsy tissues expressed LRF mRNA transcripts and protein, respectively. The overall expression of LRF mRNA transcripts and total protein was significantly more in malignant breast tissues than the benign breast tissues. LRF expression was also observed in the nuclei of human colon, renal, lung, hepatocellular carcinomas and thymoma tumor cells. In general, a significantly higher expression of LRF was seen in malignant tissues than in the corresponding benign or normal tissue. Further studies are warranted to determine the malignant role of LRF in human breast carcinoma. PMID:20471975

Adipose and mammary epithelial tissue engineering.

PubMed

Zhu, Wenting; Nelson, Celeste M

2013-01-01

Breast reconstruction is a type of surgery for women who have had a mastectomy, and involves using autologous tissue or prosthetic material to construct a natural-looking breast. Adipose tissue is the major contributor to the volume of the breast, whereas epithelial cells comprise the functional unit of the mammary gland. Adipose-derived stem cells (ASCs) can differentiate into both adipocytes and epithelial cells and can be acquired from autologous sources. ASCs are therefore an attractive candidate for clinical applications to repair or regenerate the breast. Here we review the current state of adipose tissue engineering methods, including the biomaterials used for adipose tissue engineering and the application of these techniques for mammary epithelial tissue engineering. Adipose tissue engineering combined with microfabrication approaches to engineer the epithelium represents a promising avenue to replicate the native structure of the breast.

Adipose and mammary epithelial tissue engineering

PubMed Central

Zhu, Wenting; Nelson, Celeste M.

2013-01-01

Breast reconstruction is a type of surgery for women who have had a mastectomy, and involves using autologous tissue or prosthetic material to construct a natural-looking breast. Adipose tissue is the major contributor to the volume of the breast, whereas epithelial cells comprise the functional unit of the mammary gland. Adipose-derived stem cells (ASCs) can differentiate into both adipocytes and epithelial cells and can be acquired from autologous sources. ASCs are therefore an attractive candidate for clinical applications to repair or regenerate the breast. Here we review the current state of adipose tissue engineering methods, including the biomaterials used for adipose tissue engineering and the application of these techniques for mammary epithelial tissue engineering. Adipose tissue engineering combined with microfabrication approaches to engineer the epithelium represents a promising avenue to replicate the native structure of the breast. PMID:23628872

Expression and significance of CHIP in canine mammary gland tumors

PubMed Central

WANG, Huanan; YANG, Xu; JIN, Yipeng; PEI, Shimin; ZHANG, Di; MA, Wen; HUANG, Jian; QIU, Hengbin; ZHANG, Xinke; JIANG, Qiuyue; SUN, Weidong; ZHANG, Hong; LIN, Degui

2015-01-01

CHIP (Carboxy terminus of Hsc70 Interacting Protein) is an E3 ubiquitin ligase that can induce ubiquitination and degradation of several oncogenic proteins. The expression of CHIP is frequently lower in human breast cancer than in normal breast tissue. However, the expression and role of CHIP in the canine mammary gland tumor (CMGT) remain unclear. We investigated the potential correlation between CHIP expression and mammary gland tumor prognosis in female dogs. CHIP expression was measured in 54 dogs by immunohistochemistry and real-time RT-PCR. CHIP protein expression was significantly correlated with the histopathological diagnosis, outcome of disease and tumor classification. The transcriptional level of CHIP was significantly higher in normal tissues (P=0.001) and benign tumors (P=0.009) than it in malignant tumors. CHIP protein expression was significantly correlated with the transcriptional level of CHIP (P=0.0102). The log-rank test survival curves indicated that patients with low expression of CHIP had shorter overall periods of survival than those with higher CHIP protein expression (P=0.050). Our data suggest that CHIP may play an important role in the formation and development of CMGTs and serve as a valuable prognostic marker and potential target for genetic therapy. PMID:26156079

Immunohistochemical analysis of S6K1 and S6K2 localization in human breast tumors.

PubMed

Filonenko, Valeriy V; Tytarenko, Ruslana; Azatjan, Sergey K; Savinska, Lilya O; Gaydar, Yuriy A; Gout, Ivan T; Usenko, Vasiliy S; Lyzogubov, Valeriy V

2004-12-01

To perform an immunohistochemical analysis of human breast adenomas and adenocarcinomas as well as normal breast tissues in respect of S6 ribosomal protein kinase (S6K) expression and localization in normal and transformed cells. The expression level and localization of S6K have been detected in formalin fixed, paraffin embedded sections of normal human breast tissues, adenomas and adenocarcinomas with different grade of differentiation. Immunohistochemical detection of S6K1 and S6K2 in normal human breast tissues and breast tumors were performed using specific monoclonal and polyclonal antibodies against S6K1 and S6K2 with following semiquantitative analysis. The increase of S6K content in the cytoplasm of epithelial cells in benign and malignant tumors has been detected. Nuclear accumulation of S6K1 and to a greater extend S6K2 have been found in breast adenocarcinomas. About 80% of breast adenocarcinomas cases revealed S6K2 nuclear staining comparing to normal tissues. In 31% of cases more then 50% of cancer cells had strong nuclear staining. Accumulation of S6K1 in the nucleus of neoplastic cells has been demonstrated in 25% of cases. Nuclear localization of S6K in the epithelial cells in normal breast tissues has not been detected. Immunohistochemical analysis of S6K1 and S6K2 expression in normal human breast tissues, benign and malignant breast tumors clearly indicates that both kinases are overexpressed in breast tumors. Semiquantitative analysis of peculiarities of S6K localization in normal tissues and tumors revealed that nucleoplasmic accumulation of S6K (especially S6K2) is a distinguishing feature of cancer cells.

An approach to analyze the breast tissues in infrared images using nonlinear adaptive level sets and Riesz transform features.

PubMed

Prabha, S; Suganthi, S S; Sujatha, C M

2015-01-01

Breast thermography is a potential imaging method for the early detection of breast cancer. The pathological conditions can be determined by measuring temperature variations in the abnormal breast regions. Accurate delineation of breast tissues is reported as a challenging task due to inherent limitations of infrared images such as low contrast, low signal to noise ratio and absence of clear edges. Segmentation technique is attempted to delineate the breast tissues by detecting proper lower breast boundaries and inframammary folds. Characteristic features are extracted to analyze the asymmetrical thermal variations in normal and abnormal breast tissues. An automated analysis of thermal variations of breast tissues is attempted using nonlinear adaptive level sets and Riesz transform. Breast thermal images are initially subjected to Stein's unbiased risk estimate based orthonormal wavelet denoising. These denoised images are enhanced using contrast-limited adaptive histogram equalization method. The breast tissues are then segmented using non-linear adaptive level set method. The phase map of enhanced image is integrated into the level set framework for final boundary estimation. The segmented results are validated against the corresponding ground truth images using overlap and regional similarity metrics. The segmented images are further processed with Riesz transform and structural texture features are derived from the transformed coefficients to analyze pathological conditions of breast tissues. Results show that the estimated average signal to noise ratio of denoised images and average sharpness of enhanced images are improved by 38% and 6% respectively. The interscale consideration adopted in the denoising algorithm is able to improve signal to noise ratio by preserving edges. The proposed segmentation framework could delineate the breast tissues with high degree of correlation (97%) between the segmented and ground truth areas. Also, the average segmentation accuracy and sensitivity are found to be 98%. Similarly, the maximum regional overlap between segmented and ground truth images obtained using volume similarity measure is observed to be 99%. Directionality as a feature, showed a considerable difference between normal and abnormal tissues which is found to be 11%. The proposed framework for breast thermal image analysis that is aided with necessary preprocessing is found to be useful in assisting the early diagnosis of breast abnormalities.

Classification of breast microcalcifications using spectral mammography

NASA Astrophysics Data System (ADS)

Ghammraoui, B.; Glick, S. J.

2017-03-01

Purpose: To investigate the potential of spectral mammography to distinguish between type I calcifications, consisting of calcium oxalate dihydrate or weddellite compounds that are more often associated with benign lesions, and type II calcifications containing hydroxyapatite which are predominantly associated with malignant tumors. Methods: Using a ray tracing algorithm, we simulated the total number of x-ray photons recorded by the detector at one pixel from a single pencil-beam projection through a breast of 50/50 (adipose/glandular) tissues with inserted microcalcifications of different types and sizes. Material decomposition using two energy bins was then applied to characterize the simulated calcifications into hydroxyapatite and weddellite using maximumlikelihood estimation, taking into account the polychromatic source, the detector response function and the energy dependent attenuation. Results: Simulation tests were carried out for different doses and calcification sizes for multiple realizations. The results were summarized using receiver operating characteristic (ROC) analysis with the area under the curve (AUC) taken as an overall indicator of discrimination performance and showing high AUC values up to 0.99. Conclusion: Our simulation results obtained for a uniform breast imaging phantom indicate that spectral mammography using two energy bins has the potential to be used as a non-invasive method for discrimination between type I and type II microcalcifications to improve early breast cancer diagnosis and reduce the number of unnecessary breast biopsies.

Increased COX-2 expression in epithelial and stromal cells of high mammographic density tissues and in a xenograft model of mammographic density.

PubMed

Chew, G L; Huo, C W; Huang, D; Hill, P; Cawson, J; Frazer, H; Hopper, J L; Haviv, I; Henderson, M A; Britt, K; Thompson, E W

2015-08-01

Mammographic density (MD) adjusted for age and body mass index is one of the strongest known risk factors for breast cancer. Given the high attributable risk of MD for breast cancer, chemoprevention with a safe and available agent that reduces MD and breast cancer risk would be beneficial. Cox-2 has been implicated in MD-related breast cancer risk, and was increased in stromal cells in high MD tissues in one study. Our study assessed differential Cox-2 expression in epithelial and stromal cells in paired samples of high and low MD human breast tissue, and in a validated xenograft biochamber model of MD. We also examined the effects of endocrine treatment upon Cox-2 expression in high and low MD tissues in the MD xenograft model. Paired high and low MD human breast tissue samples were immunostained for Cox-2, then assessed for differential expression and staining intensity in epithelial and stromal cells. High and low MD human breast tissues were separately maintained in biochambers in mice treated with Tamoxifen, oestrogen or placebo implants, then assessed for percentage Cox-2 staining in epithelial and stromal cells. Percentage Cox-2 staining was greater for both epithelial (p = 0.01) and stromal cells (p < 0.0001) of high compared with low MD breast tissues. In high MD biochamber tissues, percentage Cox-2 staining was greater in stromal cells of oestrogen-treated versus placebo-treated tissues (p = 0.05).

Automated palpation for breast tissue discrimination based on viscoelastic biomechanical properties.

PubMed

Tsukune, Mariko; Kobayashi, Yo; Miyashita, Tomoyuki; Fujie, G Masakatsu

2015-05-01

Accurate, noninvasive methods are sought for breast tumor detection and diagnosis. In particular, a need for noninvasive techniques that measure both the nonlinear elastic and viscoelastic properties of breast tissue has been identified. For diagnostic purposes, it is important to select a nonlinear viscoelastic model with a small number of parameters that highly correlate with histological structure. However, the combination of conventional viscoelastic models with nonlinear elastic models requires a large number of parameters. A nonlinear viscoelastic model of breast tissue based on a simple equation with few parameters was developed and tested. The nonlinear viscoelastic properties of soft tissues in porcine breast were measured experimentally using fresh ex vivo samples. Robotic palpation was used for measurements employed in a finite element model. These measurements were used to calculate nonlinear viscoelastic parameters for fat, fibroglandular breast parenchyma and muscle. The ability of these parameters to distinguish the tissue types was evaluated in a two-step statistical analysis that included Holm's pairwise [Formula: see text] test. The discrimination error rate of a set of parameters was evaluated by the Mahalanobis distance. Ex vivo testing in porcine breast revealed significant differences in the nonlinear viscoelastic parameters among combinations of three tissue types. The discrimination error rate was low among all tested combinations of three tissue types. Although tissue discrimination was not achieved using only a single nonlinear viscoelastic parameter, a set of four nonlinear viscoelastic parameters were able to reliably and accurately discriminate fat, breast fibroglandular tissue and muscle.

Molecular specialization of breast vasculature: A breast-homing phage-displayed peptide binds to aminopeptidase P in breast vasculature

NASA Astrophysics Data System (ADS)

Essler, Markus; Ruoslahti, Erkki

2002-02-01

In vivo phage display identifies peptides that selectively home to the vasculature of individual organs, tissues, and tumors. Here we report the identification of a cyclic nonapeptide, CPGPEGAGC, which homes to normal breast tissue with a 100-fold selectivity over nontargeted phage. The homing of the phage is inhibited by its cognate synthetic peptide. Phage localization in tissue sections showed that the breast-homing phage binds to the blood vessels in the breast, but not in other tissues. The phage also bound to the vasculature of hyperplastic and malignant lesions in transgenic breast cancer mice. Expression cloning with a phage-displayed cDNA library yielded a phage that specifically bound to the breast-homing peptide. The cDNA insert was homologous to a fragment of aminopeptidase P. The homing peptide bound aminopeptidase P from malignant breast tissue in affinity chromatography. Antibodies against aminopeptidase P inhibited the in vitro binding of the phage-displayed cDNA to the peptide and the in vivo homing of phage carrying the peptide. These results indicate that aminopeptidase P is the receptor for the breast-homing peptide. This peptide may be useful in designing drugs for the prevention and treatment of breast cancer.

Retinoids, carotenoids, and tocopherols in breast adipose tissue and serum of benign breast disease and breast cancer patients

USDA-ARS?s Scientific Manuscript database

Various retinoic acid (RA) isomers (all-trans, 13-cis, 11-cis, and 9-cis) as well as retinol, carotenoids, and tocopherol concentrations were determined in both serum and breast adipose tissue of 22 benign breast disease patients and 52 breast cancer patients categorized into 4 stages by malignancy....

Reconstruction of Absorbed Doses to Fibroglandular Tissue of the Breast of Women undergoing Mammography (1960 to the Present)

PubMed Central

Thierry-Chef, Isabelle; Simon, Steven L.; Weinstock, Robert M.; Kwon, Deukwoo; Linet, Martha S.

2013-01-01

The assessment of potential benefits versus harms from mammographic examinations as described in the controversial breast cancer screening recommendations of the U.S. Preventive Task Force included limited consideration of absorbed dose to the fibroglandular tissue of the breast (glandular tissue dose), the tissue at risk for breast cancer. Epidemiological studies on cancer risks associated with diagnostic radiological examinations often lack accurate information on glandular tissue dose, and there is a clear need for better estimates of these doses. Our objective was to develop a quantitative summary of glandular tissue doses from mammography by considering sources of variation over time in key parameters including imaging protocols, x-ray target materials, voltage, filtration, incident air kerma, compressed breast thickness, and breast composition. We estimated the minimum, maximum, and mean values for glandular tissue dose for populations of exposed women within 5-year periods from 1960 to the present, with the minimum to maximum range likely including 90% to 95% of the entirety of the dose range from mammography in North America and Europe. Glandular tissue dose from a single view in mammography is presently about 2 mGy, about one-sixth the dose in the 1960s. The ratio of our estimates of maximum to minimum glandular tissue doses for average-size breasts was about 100 in the 1960s compared to a ratio of about 5 in recent years. Findings from our analysis provide quantitative information on glandular tissue doses from mammographic examinations which can be used in epidemiologic studies of breast cancer. PMID:21988547

[Breast abnormalities: a retrospective study of 208 patients].

PubMed

Famà, Fausto; Gioffrè Florio, Maria Antonietta; Villari, Santa Alessandra; Caruso, Rosario; Barresi, Valeria; Mazzei, Sergio; Pollicino, Andrea; Scarfò, Paola

2007-01-01

Ectopic breast tissue occurs in 0.4-6% of the general population. Usually, these tissues develop along the embryonic milk line but other sites are reported in the literature. Accessory breasts are commonly axillary and may undergo hormonal changes. Some pathologies of normally positioned breasts can occur in ectopic breast tissue, including carcinoma, and therefore require traditional senological flow-charts and imaging strategies. Supernumerary nipples are generally asymptomatic but may sometimes be associated with urological malformations. In our 10-year experience, 208 patients were observed (138 polythelia and 70 polymastia) and 159 surgical procedures were performed, 97 for supernumerary nipple excision and 67 for accessory breast ablation. Five neoplastic lesions and 25 fibrocystic mastopathies were detected in specimens; normal nipple or breast tissue was found in 129. In view of the potentially malignant transformation of accessory breasts, thorough physician evaluation is needed. Surgery is currently suggested in cases of suspected malignancy, in symptomatic cases and for cosmetic problems.

SU-F-I-14: 3D Breast Digital Phantom for XACT Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, S; Laaroussi, R; Chen, J

Purpose: The X-ray induced acoustic computed tomography (XACT) is a new imaging modality which combines X-ray contrast and high ultrasonic resolution in a single modality. Using XACT in breast imaging, a 3D breast volume can be imaged by only one pulsed X-ray radiation, which could dramatically reduce the imaging dose for patients undergoing breast cancer screening and diagnosis. A 3D digital phantom that contains both X-ray properties and acoustic properties of different tissue types is indeed needed for developing and optimizing the XACT system. The purpose of this study is to offer a realistic breast digital phantom as a valuablemore » tool for improving breast XACT imaging techniques and potentially leading to better diagnostic outcomes. Methods: A series of breast CT images along the coronal plane from a patient who has breast calcifications are used as the source images. A HU value based segmentation algorithm is employed to identify breast tissues in five categories, namely the skin tissue, fat tissue, glandular tissue, chest bone and calcifications. For each pixel, the dose related parameters, such as material components and density, and acoustic related parameters, such as frequency-dependent acoustic attenuation coefficient and bandwidth, are assigned based on tissue types. Meanwhile, other parameters which are used in sound propagation, including the sound speed, thermal expansion coefficient, and heat capacity are also assigned to each tissue. Results: A series of 2D tissue type image is acquired first and the 3D digital breast phantom is obtained by using commercial 3D reconstruction software. When giving specific settings including dose depositions and ultrasound center frequency, the X-ray induced initial pressure rise can be calculated accordingly. Conclusion: The proposed 3D breast digital phantom represents a realistic breast anatomic structure and provides a valuable tool for developing and evaluating the system performance for XACT.« less

Continuous measurement of breast tumour hormone receptor expression: a comparison of two computational pathology platforms.

PubMed

Ahern, Thomas P; Beck, Andrew H; Rosner, Bernard A; Glass, Ben; Frieling, Gretchen; Collins, Laura C; Tamimi, Rulla M

2017-05-01

Computational pathology platforms incorporate digital microscopy with sophisticated image analysis to permit rapid, continuous measurement of protein expression. We compared two computational pathology platforms on their measurement of breast tumour oestrogen receptor (ER) and progesterone receptor (PR) expression. Breast tumour microarrays from the Nurses' Health Study were stained for ER (n=592) and PR (n=187). One expert pathologist scored cases as positive if ≥1% of tumour nuclei exhibited stain. ER and PR were then measured with the Definiens Tissue Studio (automated) and Aperio Digital Pathology (user-supervised) platforms. Platform-specific measurements were compared using boxplots, scatter plots and correlation statistics. Classification of ER and PR positivity by platform-specific measurements was evaluated with areas under receiver operating characteristic curves (AUC) from univariable logistic regression models, using expert pathologist classification as the standard. Both platforms showed considerable overlap in continuous measurements of ER and PR between positive and negative groups classified by expert pathologist. Platform-specific measurements were strongly and positively correlated with one another (r≥0.77). The user-supervised Aperio workflow performed slightly better than the automated Definiens workflow at classifying ER positivity (AUC Aperio =0.97; AUC Definiens =0.90; difference=0.07, 95% CI 0.05 to 0.09) and PR positivity (AUC Aperio =0.94; AUC Definiens =0.87; difference=0.07, 95% CI 0.03 to 0.12). Paired hormone receptor expression measurements from two different computational pathology platforms agreed well with one another. The user-supervised workflow yielded better classification accuracy than the automated workflow. Appropriately validated computational pathology algorithms enrich molecular epidemiology studies with continuous protein expression data and may accelerate tumour biomarker discovery. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Basic physics and doubts about relationship between mammographically determined tissue density and breast cancer risk.

PubMed

Kopans, Daniel B

2008-02-01

Numerous studies have suggested a link between breast tissue patterns, as defined with mammography, and risk for breast cancer. There may be a relationship, but the author believes all of these studies have methodological flaws. It is impossible, with the parameters used in these studies, to accurately measure the percentage of tissues by volume when two-dimensional x-ray mammographic images are used. Without exposure values, half-value layer information, and knowledge of the compressed thickness of the breast, an accurate volume of tissue cannot be calculated. The great variability in positioning the breast for a mammogram is also an uncontrollable factor in measuring tissue density. Computerized segmentation algorithms can accurately assess the percentage of the x-ray image that is "dense," but this does not accurately measure the true volume of tissue. Since the percentage of dense tissue is ultimately measured in relation to the complete volume of the breast, defining the true boundaries of the breast is also a problem. Studies that purport to show small percentage differences between groups are likely inaccurate. Future investigations need to use three-dimensional information. (c) RSNA, 2008.

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

PubMed

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%.

Micro-anatomical quantitative optical imaging: toward automated assessment of breast tissues.

PubMed

Dobbs, Jessica L; Mueller, Jenna L; Krishnamurthy, Savitri; Shin, Dongsuk; Kuerer, Henry; Yang, Wei; Ramanujam, Nirmala; Richards-Kortum, Rebecca

2015-08-20

Pathologists currently diagnose breast lesions through histologic assessment, which requires fixation and tissue preparation. The diagnostic criteria used to classify breast lesions are qualitative and subjective, and inter-observer discordance has been shown to be a significant challenge in the diagnosis of selected breast lesions, particularly for borderline proliferative lesions. Thus, there is an opportunity to develop tools to rapidly visualize and quantitatively interpret breast tissue morphology for a variety of clinical applications. Toward this end, we acquired images of freshly excised breast tissue specimens from a total of 34 patients using confocal fluorescence microscopy and proflavine as a topical stain. We developed computerized algorithms to segment and quantify nuclear and ductal parameters that characterize breast architectural features. A total of 33 parameters were evaluated and used as input to develop a decision tree model to classify benign and malignant breast tissue. Benign features were classified in tissue specimens acquired from 30 patients and malignant features were classified in specimens from 22 patients. The decision tree model that achieved the highest accuracy for distinguishing between benign and malignant breast features used the following parameters: standard deviation of inter-nuclear distance and number of duct lumens. The model achieved 81 % sensitivity and 93 % specificity, corresponding to an area under the curve of 0.93 and an overall accuracy of 90 %. The model classified IDC and DCIS with 92 % and 96 % accuracy, respectively. The cross-validated model achieved 75 % sensitivity and 93 % specificity and an overall accuracy of 88 %. These results suggest that proflavine staining and confocal fluorescence microscopy combined with image analysis strategies to segment morphological features could potentially be used to quantitatively diagnose freshly obtained breast tissue at the point of care without the need for tissue preparation.

Determination of the Elasticity of Breast Tissue during the Menstrual Cycle Using Real-Time Shear Wave Elastography.

PubMed

Li, Xiang; Wang, Jian-Nan; Fan, Zhi-Ying; Kang, Shu; Liu, Yan-Jun; Zhang, Yi-Xia; Wang, Xue-Mei

2015-12-01

We examined breast tissue elasticity during the menstrual cycle using real-time shear wave elastography (RT-SWE), a recent technique developed for soft tissue imaging. Written informed consent for RT-SWE was obtained from all eligible patients, who were healthy women aged between 19 and 52 y. Young's moduli of the breast tissue in the early follicular, late phase and luteal phase were compared. There were no significant differences in the mean, maximum and minimum elasticity values (Emean, Emax and Emin) and standard deviation (ESD). RT-SWE of glandular tissue revealed that ESD was increased in the early follicular phase compared with the luteal phase. Means ± SD of Emin, Emax and Emean in glandular tissue were 5.174 ± 2.138, 8.308 ± 3.166 and 6.593 ± 2.510, respectively, and in adipose tissue, 3.589 ± 2.083, 6.733 ± 3.522 and 4.857 ± 2.564, respectively. There were no significant differences in stiffness between glandular and adipose tissues throughout the menstrual cycle, but glandular tissue stiffness was lower in the luteal phase than in the early follicular phase. On the basis of these observations in normal healthy women, we believe we have obtained sufficient information to establish the baseline changes in human breast elasticity during the menstrual cycle. In the future, we intend to compare the elasticity values of healthy breast tissue with those of breast tissue affected by various pathologies. Our results reveal the significant potential of RT-SWE in the rapid and non-invasive clinical diagnosis of breast diseases, such as breast cancers. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Ceramide species are elevated in human breast cancer and are associated with less aggressiveness

PubMed Central

Moro, Kazuki; Kawaguchi, Tsutomu; Tsuchida, Junko; Gabriel, Emmanuel; Qi, Qianya; Yan, Li; Wakai, Toshifumi; Takabe, Kazuaki; Nagahashi, Masayuki

2018-01-01

Sphingolipids have emerged as key regulatory molecules in cancer cell survival and death. Although important roles of sphingolipids in breast cancer progression have been reported in experimental models, their roles in human patients are yet to be revealed. The aim of this study was to investigate the ceramide levels and its biosynthesis pathways in human breast cancer patients. Breast cancer, peri-tumor and normal breast tissue samples were collected from surgical specimens from a series of 44 patients with breast cancer. The amount of sphingolipid metabolites in the tissue were determined by mass spectrometry. The Cancer Genome Atlas was used to analyze gene expression related to the sphingolipid metabolism. Ceramide levels were higher in breast cancer tissue compared to both normal and peri-tumor breast tissue. Substrates and enzymes that generate ceramide were significantly increased in all three ceramide biosynthesis pathways in cancer. Further, higher levels of ceramide in breast cancer were associated with less aggressive cancer biology presented by Ki-67 index and nuclear grade of the cancer. Interestingly, patients with higher gene expressions of enzymes in the three major ceramide synthesis pathways showed significantly worse prognosis. This is the first study to reveal the clinical relevance of ceramide metabolism in breast cancer patients. We demonstrated that ceramide levels in breast cancer tissue were significantly higher than those in normal tissue, with activation of the three ceramide biosynthesis pathways. We also identified that ceramide levels have a significant association with aggressive phenotype and its enzymes have prognostic impact on breast cancer patients. PMID:29731990

Overexpression of SERBP1 (Plasminogen activator inhibitor 1 RNA binding protein) in human breast cancer is correlated with favourable prognosis

PubMed Central

2012-01-01

Background Plasminogen activator inhibitor 1 (PAI-1) overexpression is an important prognostic and predictive biomarker in human breast cancer. SERBP1, a protein that is supposed to regulate the stability of PAI-1 mRNA, may play a role in gynaecological cancers as well, since upregulation of SERBP1 was described in ovarian cancer recently. This is the first study to present a systematic characterisation of SERBP1 expression in human breast cancer and normal breast tissue at both the mRNA and the protein level. Methods Using semiquantitative realtime PCR we analysed SERBP1 expression in different normal human tissues (n = 25), and in matched pairs of normal (n = 7) and cancerous breast tissues (n = 7). SERBP1 protein expression was analysed in two independent cohorts on tissue microarrays (TMAs), an initial evaluation set, consisting of 193 breast carcinomas and 48 normal breast tissues, and a second large validation set, consisting of 605 breast carcinomas. In addition, a collection of benign (n = 2) and malignant (n = 6) mammary cell lines as well as breast carcinoma lysates (n = 16) were investigated for SERBP1 expression by Western blot analysis. Furthermore, applying non-radioisotopic in situ hybridisation a subset of normal (n = 10) and cancerous (n = 10) breast tissue specimens from the initial TMA were analysed for SERBP1 mRNA expression. Results SERBP1 is not differentially expressed in breast carcinoma compared to normal breast tissue, both at the RNA and protein level. However, recurrence-free survival analysis showed a significant correlation (P = 0.008) between abundant SERBP1 expression in breast carcinoma and favourable prognosis. Interestingly, overall survival analysis also displayed a tendency (P = 0.09) towards favourable prognosis when SERBP1 was overexpressed in breast cancer. Conclusions The RNA-binding protein SERBP1 is abundantly expressed in human breast cancer and may represent a novel breast tumour marker with prognostic significance. Its potential involvement in the plasminogen activator protease cascade warrants further investigation. PMID:23236990

Global loss of a nuclear lamina component, lamin A/C, and LINC complex components SUN1, SUN2, and nesprin-2 in breast cancer.

PubMed

Matsumoto, Ayaka; Hieda, Miki; Yokoyama, Yuhki; Nishioka, Yu; Yoshidome, Katsuhide; Tsujimoto, Masahiko; Matsuura, Nariaki

2015-10-01

Cancer cells exhibit a variety of features indicative of atypical nuclei. However, the molecular mechanisms underlying these phenomena remain to be elucidated. The linker of nucleoskeleton and cytoskeleton (LINC) complex, a nuclear envelope protein complex consisting mainly of the SUN and nesprin proteins, connects nuclear lamina and cytoskeletal filaments and helps to regulate the size and shape of the nucleus. Using immunohistology, we found that a nuclear lamina component, lamin A/C and all of the investigated LINC complex components, SUN1, SUN2, and nesprin-2, were downregulated in human breast cancer tissues. In the majority of cases, we observed lower expression levels of these analytes in samples' cancerous regions as compared to their cancer-associated noncancerous regions (in cancerous regions, percentage of tissue samples exhibiting low protein expression: lamin A/C, 85% [n = 73]; SUN1, 88% [n = 43]; SUN2, 74% [n = 43]; and nesprin-2, 79% [n = 53]). Statistical analysis showed that the frequencies of recurrence and HER2 expression were negatively correlated with lamin A/C expression (P < 0.05), and intrinsic subtype and ki-67 level were associated with nesprin-2 expression (P < 0.05). In addition, combinatorial analysis using the above four parameters showed that all patients exhibited reduced expression of at least one of four components despite the tumor's pathological classification. Furthermore, several cultured breast cancer cell lines expressed less SUN1, SUN2, nesprin-2 mRNA, and lamin A/C compared to noncancerous mammary gland cells. Together, these results suggest that the strongly reduced expression of LINC complex and nuclear lamina components may play fundamental pathological functions in breast cancer progression. © 2015 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Deep learning and three-compartment breast imaging in breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Drukker, Karen; Huynh, Benjamin Q.; Giger, Maryellen L.; Malkov, Serghei; Avila, Jesus I.; Fan, Bo; Joe, Bonnie; Kerlikowske, Karla; Drukteinis, Jennifer S.; Kazemi, Leila; Pereira, Malesa M.; Shepherd, John

2017-03-01

We investigated whether deep learning has potential to aid in the diagnosis of breast cancer when applied to mammograms and biologic tissue composition images derived from three-compartment (3CB) imaging. The dataset contained diagnostic mammograms and 3CB images (water, lipid, and protein content) of biopsy-sampled BIRADS 4 and 5 lesions in 195 patients. In 58 patients, the lesion manifested as a mass (13 malignant vs. 45 benign), in 87 as microcalcifications (19 vs. 68), and in 56 as (focal) asymmetry or architectural distortion (11 vs. 45). Six patients had both a mass and calcifications. For each mammogram and corresponding 3CB images, a 128x128 region of interest containing the lesion was selected by an expert radiologist and used directly as input to a deep learning method pretrained on a very large independent set of non-medical images. We used a nested leave-one-out-by-case (patient) model selection and classification protocol. The area under the ROC curve (AUC) for the task of distinguishing between benign and malignant lesions was used as performance metric. For the cases with mammographic masses, the AUC increased from 0.83 (mammograms alone) to 0.89 (mammograms+3CB, p=.162). For the microcalcification and asymmetry/architectural distortion cases the AUC increased from 0.84 to 0.91 (p=.116) and from 0.61 to 0.87 (p=.006), respectively. Our results indicate great potential for the application of deep learning methods in the diagnosis of breast cancer and additional knowledge of the biologic tissue composition appeared to improve performance, especially for lesions mammographically manifesting as asymmetries or architectural distortions.

Expression of Caspase-1 in breast cancer tissues and its effects on cell proliferation, apoptosis and invasion.

PubMed

Sun, Yanxia; Guo, Yingzhen

2018-05-01

The present study aimed to detect the expression of Caspase-1 in the tumor tissues and tumor-adjacent tissues of patients with breast cancer, and to investigate the effects of Caspase-1 on the proliferation, apoptosis and invasion of breast cancer cells. Reverse transcription-quantitative polymerase chain reaction was used to detect Caspase-1 mRNA expression in breast cancer tissues and tumor-adjacent tissues from patients. Additionally, the human breast cancer MDA-MB-231 cell line was treated with the Caspase-1 small molecule inhibitor Ac-YVAD-CMK, following which the changes to Caspase-1 protein expression were detected via western blotting. The MTT method detected the changes to cell proliferation, flow cytometry detected the rate of apoptosis, and a Transwell assay was employed to assess invasion. Caspase-1 mRNA expression was significantly decreased in the breast cancer tissues of patients, compared with in the tumor-adjacent tissues, a difference that was statistically significant (P<0.05). Treatment with the Ac-YVAD-CMK markedly decreased the protein expression of Caspase-1 in MDA-MB-231 cells, and the difference was statistically significant (P<0.05). Following this treatment of Ac-YVAD-CMK cells, the proliferation and invasion abilities markedly increased, while the apoptotic levels significantly decreased (P<0.05). In conclusion, the expression of Caspase-1 is low in breast cancer tissues, which may promote the proliferation and invasion of breast cancer cells and could be closely associated with the occurrence and development of breast cancer.

Image segmentation and 3D visualization for MRI mammography

NASA Astrophysics Data System (ADS)

Li, Lihua; Chu, Yong; Salem, Angela F.; Clark, Robert A.

2002-05-01

MRI mammography has a number of advantages, including the tomographic, and therefore three-dimensional (3-D) nature, of the images. It allows the application of MRI mammography to breasts with dense tissue, post operative scarring, and silicon implants. However, due to the vast quantity of images and subtlety of difference in MR sequence, there is a need for reliable computer diagnosis to reduce the radiologist's workload. The purpose of this work was to develop automatic breast/tissue segmentation and visualization algorithms to aid physicians in detecting and observing abnormalities in breast. Two segmentation algorithms were developed: one for breast segmentation, the other for glandular tissue segmentation. In breast segmentation, the MRI image is first segmented using an adaptive growing clustering method. Two tracing algorithms were then developed to refine the breast air and chest wall boundaries of breast. The glandular tissue segmentation was performed using an adaptive thresholding method, in which the threshold value was spatially adaptive using a sliding window. The 3D visualization of the segmented 2D slices of MRI mammography was implemented under IDL environment. The breast and glandular tissue rendering, slicing and animation were displayed.

Adipose tissue and breast epithelial cells: a dangerous dynamic duo in breast cancer.

PubMed

Wang, Yuan-Yuan; Lehuédé, Camille; Laurent, Victor; Dirat, Béatrice; Dauvillier, Stéphanie; Bochet, Ludivine; Le Gonidec, Sophie; Escourrou, Ghislaine; Valet, Philippe; Muller, Catherine

2012-11-28

Among the many different cell types surrounding breast cancer cells, the most abundant are those that compose mammary adipose tissue, mainly mature adipocytes and progenitors. New accumulating recent evidences bring the tumor-surrounding adipose tissue into the light as a key component of breast cancer progression. The purpose of this review is to emphasize the role that adipose tissue might play by locally affecting breast cancer cell behavior and subsequent clinical consequences arising from this dialog. Two particular clinical aspects are addressed: obesity that was identified as an independent negative prognostic factor in breast cancer and the oncological safety of autologous fat transfer used in reconstructive surgery for breast cancer patients. This is preceded by the overall description of adipose tissue composition and function with special emphasis on the specificity of adipose depots and the species differences, key experimental aspects that need to be taken in account when cancer is considered. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

A Serum Protein Profile Predictive of the Resistance to Neoadjuvant Chemotherapy in Advanced Breast Cancers*

PubMed Central

Hyung, Seok-Won; Lee, Min Young; Yu, Jong-Han; Shin, Byunghee; Jung, Hee-Jung; Park, Jong-Moon; Han, Wonshik; Lee, Kyung-Min; Moon, Hyeong-Gon; Zhang, Hui; Aebersold, Ruedi; Hwang, Daehee; Lee, Sang-Won; Yu, Myeong-Hee; Noh, Dong-Young

2011-01-01

Prediction of the responses to neoadjuvant chemotherapy (NACT) can improve the treatment of patients with advanced breast cancer. Genes and proteins predictive of chemoresistance have been extensively studied in breast cancer tissues. However, noninvasive serum biomarkers capable of such prediction have been rarely exploited. Here, we performed profiling of N-glycosylated proteins in serum from fifteen advanced breast cancer patients (ten patients sensitive to and five patients resistant to NACT) to discover serum biomarkers of chemoresistance using a label-free liquid chromatography-tandem MS method. By performing a series of statistical analyses of the proteomic data, we selected thirteen biomarker candidates and tested their differential serum levels by Western blotting in 13 independent samples (eight patients sensitive to and five patients resistant to NACT). Among the candidates, we then selected the final set of six potential serum biomarkers (AHSG, APOB, C3, C9, CP, and ORM1) whose differential expression was confirmed in the independent samples. Finally, we demonstrated that a multivariate classification model using the six proteins could predict responses to NACT and further predict relapse-free survival of patients. In summary, global N-glycoproteome profile in serum revealed a protein pattern predictive of the responses to NACT, which can be further validated in large clinical studies. PMID:21799047

Radiological assessment of breast density by visual classification (BI-RADS) compared to automated volumetric digital software (Quantra): implications for clinical practice.

PubMed

Regini, Elisa; Mariscotti, Giovanna; Durando, Manuela; Ghione, Gianluca; Luparia, Andrea; Campanino, Pier Paolo; Bianchi, Caterina Chiara; Bergamasco, Laura; Fonio, Paolo; Gandini, Giovanni

2014-10-01

This study was done to assess breast density on digital mammography and digital breast tomosynthesis according to the visual Breast Imaging Reporting and Data System (BI-RADS) classification, to compare visual assessment with Quantra software for automated density measurement, and to establish the role of the software in clinical practice. We analysed 200 digital mammograms performed in 2D and 3D modality, 100 of which positive for breast cancer and 100 negative. Radiological density was assessed with the BI-RADS classification; a Quantra density cut-off value was sought on the 2D images only to discriminate between BI-RADS categories 1-2 and BI-RADS 3-4. Breast density was correlated with age, use of hormone therapy, and increased risk of disease. The agreement between the 2D and 3D assessments of BI-RADS density was high (K 0.96). A cut-off value of 21% is that which allows us to best discriminate between BI-RADS categories 1-2 and 3-4. Breast density was negatively correlated to age (r = -0.44) and positively to use of hormone therapy (p = 0.0004). Quantra density was higher in breasts with cancer than in healthy breasts. There is no clear difference between the visual assessments of density on 2D and 3D images. Use of the automated system requires the adoption of a cut-off value (set at 21%) to effectively discriminate BI-RADS 1-2 and 3-4, and could be useful in clinical practice.

Development and Feasibility Testing of Image-Guided Minimally Invasive Tissue for Diagnosis Treatment of Benign and Malignant Breast Disease

NASA Technical Reports Server (NTRS)

Jeffrey, Stefanie S.

1999-01-01

Dr. Robert Mah and Dr. Stefanie Jeffrey worked on the development of the NASA Smart Probe in its application as a device to measure and interpret physiologic and image-based parameters of breast tissue. To date the following has been achieved: 1 . Choice of candidate sensors to be tested in breast tissue. 2. Preliminary designs for probe tip, specifically use of different tip shapes, cutting edges, and sensor configuration. 3. Design of sonographic guidance system. 4. Design of data extraction and analysis tool using scanned information of images of the breast tissue to provide a higher dimension of information for breast tissue characterization and interpretation. 5. Initial ex-vivo (fruit and tofu) and in-vivo (rodent) testing to confirm unique substance and tissue characterization by the Smart Probe software.

Raman imaging at biological interfaces: applications in breast cancer diagnosis.

PubMed

Surmacki, Jakub; Musial, Jacek; Kordek, Radzislaw; Abramczyk, Halina

2013-05-24

One of the most important areas of Raman medical diagnostics is identification and characterization of cancerous and noncancerous tissues. The methods based on Raman scattering has shown significant potential for probing human breast tissue to provide valuable information for early diagnosis of breast cancer. A vibrational fingerprint from the biological tissue provides information which can be used to identify, characterize and discriminate structures in breast tissue, both in the normal and cancerous environment. The paper reviews recent progress in understanding structure and interactions at biological interfaces of the human tissue by using confocal Raman imaging and IR spectroscopy. The important differences between the noncancerous and cancerous human breast tissues were found in regions characteristic for vibrations of carotenoids, fatty acids, proteins, and interfacial water. Particular attention was paid to the role played by unsaturated fatty acids and their derivatives as well as carotenoids and interfacial water. We demonstrate that Raman imaging has reached a clinically relevant level in regard to breast cancer diagnosis applications. The results presented in the paper may have serious implications on understanding mechanisms of interactions in living cells under realistically crowded conditions of biological tissue.

Fibroadenoma in Axillary Ectopic Breast Tissue Mimicking Lymphadenopathy

PubMed Central

Maheshwari, Ujwala M

2017-01-01

Swellings in the axilla especially in women are always viewed with suspicion owing to a large number of these being associated with breast carcinoma presenting as nodal metastasis. In a country like India, tuberculous lymphadenopathy is also amongst the first differentials. We present a case of a woman with right sided axillary swelling mimicking lymphadenopathy which on Fine Needle Aspiration Cytology (FNAC) turned out to be fibroadenoma of the ectopic breast tissue. This condition is a rare occurrence in Ectopic Breast Tissue (EBT) as opposed to that in the normal breast, the most common pathology affecting ectopic breast being carcinomas. PMID:28511397

A tumor specific antibody to aid breast cancer screening in women with dense breast tissue

PubMed Central

Roy, Lopamudra Das; Dillon, Lloye M.; Zhou, Ru; Moore, Laura J.; Livasy, Chad; El-Khoury, Joe M.; Puri, Rahul; Mukherjee, Pinku

2017-01-01

Screening for breast cancer has predominantly been done using mammography. Unfortunately, mammograms miss 50% cancers in women with dense breast tissue. Multi-modal screenings offer the best chance of enhancing breast cancer screening effectiveness. We evaluated the use of TAB004, an antibody that recognizes the tumor form of the glycoprotein MUC1 (tMUC1), to aid early detection of breast cancer. Our experimental approach was to follow tMUC1 from the tissue into circulation. We found that 95% of human breast cancer tissues across all subtypes stained positive for TAB004. In breast cancer cell lines, we showed that the amount of tMUC1 released from tumor cells is proportional to the cell's tMUC1 expression level. Finally, we showed that TAB004 can be used to assess circulating tMUC1 levels, which when monitored in the context of cancer immunoediting, can aid earlier diagnosis of breast cancer regardless of breast tissue density. In a blinded pilot study with banked serial samples, tMUC1 levels increased significantly up to 2 years before diagnosis. Inclusion of tMUC1 monitoring as part of a multi-modal screening strategy may lead to earlier stage diagnosis of women whose cancers are missed by mammography. PMID:28680538

Defining Genomic Changes in Triple Negative Breast Cancer in Women of African Descent

DTIC Science & Technology

2013-07-01

Triple negative breast cancer , Ethnic disparities, Breast cancer amongst African - Americans and Africans , Gene expression... Americans . Adjacent Normal AA Native African TN BC Tissue Figure 1. Gene Expression Pattern of Native African Triple Negative Breast Cancer ...and African - American Adjacent Normal Breast Tissue Genes PI: Pegram & Baumbach

Defining Genomic Changes in Triple-Negative Breast Cancer in Women of African Descent

DTIC Science & Technology

2012-06-01

African and African - American breast cancer cases. Gene Expression Array Studies The 31 triple negative Kijabe samples were... American Adjacent Normal Breast Tissue PI: Pegram & Baumbach Defining Genomic Changes in Triple Negative Breast Cancer in Women of African ...Tissues from African - American and East African Patients with Triple Negative Breast

Clinical Data as an Adjunct to Ultrasound Reduces the False-Negative Malignancy Rate in BI-RADS 3 Breast Lesions

PubMed Central

Ackermann, S.; Schoenenberger, C.-A.; Zanetti-Dällenbach, R.

2016-01-01

Purpose: Ultrasound (US) is a well-established diagnostic procedure for breast examination. We investigated the malignancy rate in solid breast lesions according to their BI-RADS classification with a particular focus on false-negative BI-RADS 3 lesions. We examined whether patient history and clinical findings could provide additional information that would help determine further diagnostic steps in breast lesions. Materials and Methods: We conducted a retrospective study by exploring US BI-RADS in 1469 breast lesions of 1201 patients who underwent minimally invasive breast biopsy (MIBB) from January 2002 to December 2011. Results: The overall sensitivity and specificity of BI-RADS classification was 97.4% and 66.4%, respectively, with a positive (PPV) and negative predictive value (NPV) of 65% and 98%, respectively. In 506 BI-RADS 3 lesions, histology revealed 15 malignancies (2.4% malignancy rate), which corresponds to a false-negative rate (FNR) of 2.6%. Clinical evaluation and patient requests critically influenced the further diagnostic procedure, thereby prevailing over the recommendation given by the BI-RADS 3 classification. Conclusion: Clinical criteria including age, family and personal history, clinical examination, mammography and patient choice ensure adequate diagnostic procedures such as short-term follow-up or MIBB in patients with lesions classified as US-BI-RADS 3. PMID:27689181

Classification of ductal carcinoma in situ by gene expression profiling.

PubMed

Hannemann, Juliane; Velds, Arno; Halfwerk, Johannes B G; Kreike, Bas; Peterse, Johannes L; van de Vijver, Marc J

2006-01-01

Ductal carcinoma in situ (DCIS) is characterised by the intraductal proliferation of malignant epithelial cells. Several histological classification systems have been developed, but assessing the histological type/grade of DCIS lesions is still challenging, making treatment decisions based on these features difficult. To obtain insight in the molecular basis of the development of different types of DCIS and its progression to invasive breast cancer, we have studied differences in gene expression between different types of DCIS and between DCIS and invasive breast carcinomas. Gene expression profiling using microarray analysis has been performed on 40 in situ and 40 invasive breast cancer cases. DCIS cases were classified as well- (n = 6), intermediately (n = 18), and poorly (n = 14) differentiated type. Of the 40 invasive breast cancer samples, five samples were grade I, 11 samples were grade II, and 24 samples were grade III. Using two-dimensional hierarchical clustering, the basal-like type, ERB-B2 type, and the luminal-type tumours originally described for invasive breast cancer could also be identified in DCIS. Using supervised classification, we identified a gene expression classifier of 35 genes, which differed between DCIS and invasive breast cancer; a classifier of 43 genes could be identified separating between well- and poorly differentiated DCIS samples.

Classification of ductal carcinoma in situ by gene expression profiling

PubMed Central

Hannemann, Juliane; Velds, Arno; Halfwerk, Johannes BG; Kreike, Bas; Peterse, Johannes L; van de Vijver, Marc J

2006-01-01

Introduction Ductal carcinoma in situ (DCIS) is characterised by the intraductal proliferation of malignant epithelial cells. Several histological classification systems have been developed, but assessing the histological type/grade of DCIS lesions is still challenging, making treatment decisions based on these features difficult. To obtain insight in the molecular basis of the development of different types of DCIS and its progression to invasive breast cancer, we have studied differences in gene expression between different types of DCIS and between DCIS and invasive breast carcinomas. Methods Gene expression profiling using microarray analysis has been performed on 40 in situ and 40 invasive breast cancer cases. Results DCIS cases were classified as well- (n = 6), intermediately (n = 18), and poorly (n = 14) differentiated type. Of the 40 invasive breast cancer samples, five samples were grade I, 11 samples were grade II, and 24 samples were grade III. Using two-dimensional hierarchical clustering, the basal-like type, ERB-B2 type, and the luminal-type tumours originally described for invasive breast cancer could also be identified in DCIS. Conclusion Using supervised classification, we identified a gene expression classifier of 35 genes, which differed between DCIS and invasive breast cancer; a classifier of 43 genes could be identified separating between well- and poorly differentiated DCIS samples. PMID:17069663

Ultrasound-guided breast-sparing surgery to improve cosmetic outcomes and quality of life. A prospective multicentre randomised controlled clinical trial comparing ultrasound-guided surgery to traditional palpation-guided surgery (COBALT trial)

PubMed Central

2011-01-01

Background Breast-conserving surgery for breast cancer was developed as a method to preserve healthy breast tissue, thereby improving cosmetic outcomes. Thus far, the primary aim of breast-conserving surgery has been the achievement of tumour-free resection margins and prevention of local recurrence, whereas the cosmetic outcome has been considered less important. Large studies have reported poor cosmetic outcomes in 20-40% of patients after breast-conserving surgery, with the volume of the resected breast tissue being the major determinant. There is clear evidence for the efficacy of ultrasonography in the resection of nonpalpable tumours. Surgical resection of palpable breast cancer is performed with guidance by intra-operative palpation. These palpation-guided excisions often result in an unnecessarily wide resection of adjacent healthy breast tissue, while the rate of tumour-involved resection margins is still high. It is hypothesised that the use of intra-operative ultrasonography in the excision of palpable breast cancer will improve the ability to spare healthy breast tissue while maintaining or even improving the oncological margin status. The aim of this study is to compare ultrasound-guided surgery for palpable tumours with the standard palpation-guided surgery in terms of the extent of healthy breast tissue resection, the percentage of tumour-free margins, cosmetic outcomes and quality of life. Methods/design In this prospective multicentre randomised controlled clinical trial, 120 women who have been diagnosed with palpable early-stage (T1-2N0-1) primary invasive breast cancer and deemed suitable for breast-conserving surgery will be randomised between ultrasound-guided surgery and palpation-guided surgery. With this sample size, an expected 20% reduction of resected breast tissue and an 18% difference in tumour-free margins can be detected with a power of 80%. Secondary endpoints include cosmetic outcomes and quality of life. The rationale, study design and planned analyses are described. Conclusion The COBALT trial is a prospective, multicentre, randomised controlled study to assess the efficacy of ultrasound-guided breast-conserving surgery in patients with palpable early-stage primary invasive breast cancer in terms of the sparing of breast tissue, oncological margin status, cosmetic outcomes and quality of life. Trial Registration Number Netherlands Trial Register (NTR): NTR2579 PMID:21410949

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

PubMed

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

2006-04-20

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

Time domain diffuse optical spectroscopy: In vivo quantification of collagen in breast tissue

NASA Astrophysics Data System (ADS)

Taroni, Paola; Pifferi, Antonio; Quarto, Giovanna; Farina, Andrea; Ieva, Francesca; Paganoni, Anna Maria; Abbate, Francesca; Cassano, Enrico; Cubeddu, Rinaldo

2015-05-01

Time-resolved diffuse optical spectroscopy provides non-invasively the optical characterization of highly diffusive media, such as biological tissues. Light pulses are injected into the tissue and the effects of light propagation on re-emitted pulses are interpreted with the diffusion theory to assess simultaneously tissue absorption and reduced scattering coefficients. Performing spectral measurements, information on tissue composition and structure is derived applying the Beer law to the measured absorption and an empiric approximation to Mie theory to the reduced scattering. The absorption properties of collagen powder were preliminarily measured in the range of 600-1100 nm using a laboratory set-up for broadband time-resolved diffuse optical spectroscopy. Optical projection images were subsequently acquired in compressed breast geometry on 218 subjects, either healthy or bearing breast lesions, using a portable instrument for optical mammography that operates at 7 wavelengths selected in the range 635-1060 nm. For all subjects, tissue composition was estimated in terms of oxy- and deoxy-hemoglobin, water, lipids, and collagen. Information on tissue microscopic structure was also derived. Good correlation was obtained between mammographic breast density (a strong risk factor for breast cancer) and an optical index based on collagen content and scattering power (that accounts mostly for tissue collagen). Logistic regression applied to all optically derived parameters showed that subjects at high risk for developing breast cancer for their high breast density can effectively be identified based on collagen content and scattering parameters. Tissue composition assessed in breast lesions with a perturbative approach indicated that collagen and hemoglobin content are significantly higher in malignant lesions than in benign ones.

Multiresolution Local Binary Pattern texture analysis for false positive reduction in computerized detection of breast masses on mammograms

NASA Astrophysics Data System (ADS)

Choi, Jae Young; Kim, Dae Hoe; Choi, Seon Hyeong; Ro, Yong Man

2012-03-01

We investigated the feasibility of using multiresolution Local Binary Pattern (LBP) texture analysis to reduce falsepositive (FP) detection in a computerized mass detection framework. A new and novel approach for extracting LBP features is devised to differentiate masses and normal breast tissue on mammograms. In particular, to characterize the LBP texture patterns of the boundaries of masses, as well as to preserve the spatial structure pattern of the masses, two individual LBP texture patterns are then extracted from the core region and the ribbon region of pixels of the respective ROI regions, respectively. These two texture patterns are combined to produce the so-called multiresolution LBP feature of a given ROI. The proposed LBP texture analysis of the information in mass core region and its margin has clearly proven to be significant and is not sensitive to the precise location of the boundaries of masses. In this study, 89 mammograms were collected from the public MAIS database (DB). To perform a more realistic assessment of FP reduction process, the LBP texture analysis was applied directly to a total of 1,693 regions of interest (ROIs) automatically segmented by computer algorithm. Support Vector Machine (SVM) was applied for the classification of mass ROIs from ROIs containing normal tissue. Receiver Operating Characteristic (ROC) analysis was conducted to evaluate the classification accuracy and its improvement using multiresolution LBP features. With multiresolution LBP features, the classifier achieved an average area under the ROC curve, , z A of 0.956 during testing. In addition, the proposed LBP features outperform other state-of-the-arts features designed for false positive reduction.

Computer-aided diagnostics of screening mammography using content-based image retrieval

NASA Astrophysics Data System (ADS)

Deserno, Thomas M.; Soiron, Michael; de Oliveira, Júlia E. E.; de A. Araújo, Arnaldo

2012-03-01

Breast cancer is one of the main causes of death among women in occidental countries. In the last years, screening mammography has been established worldwide for early detection of breast cancer, and computer-aided diagnostics (CAD) is being developed to assist physicians reading mammograms. A promising method for CAD is content-based image retrieval (CBIR). Recently, we have developed a classification scheme of suspicious tissue pattern based on the support vector machine (SVM). In this paper, we continue moving towards automatic CAD of screening mammography. The experiments are based on in total 10,509 radiographs that have been collected from different sources. From this, 3,375 images are provided with one and 430 radiographs with more than one chain code annotation of cancerous regions. In different experiments, this data is divided into 12 and 20 classes, distinguishing between four categories of tissue density, three categories of pathology and in the 20 class problem two categories of different types of lesions. Balancing the number of images in each class yields 233 and 45 images remaining in each of the 12 and 20 classes, respectively. Using a two-dimensional principal component analysis, features are extracted from small patches of 128 x 128 pixels and classified by means of a SVM. Overall, the accuracy of the raw classification was 61.6 % and 52.1 % for the 12 and the 20 class problem, respectively. The confusion matrices are assessed for detailed analysis. Furthermore, an implementation of a SVM-based CBIR system for CADx in screening mammography is presented. In conclusion, with a smarter patch extraction, the CBIR approach might reach precision rates that are helpful for the physicians. This, however, needs more comprehensive evaluation on clinical data.

Application of Abbreviated Protocol of Magnetic Resonance Imaging for Breast Cancer Screening in Dense Breast Tissue.

PubMed

Chen, Shuang-Qing; Huang, Min; Shen, Yu-Ying; Liu, Chen-Lu; Xu, Chuan-Xiao

2017-03-01

The study aimed to evaluate the usefulness of an abbreviated protocol (AP) of magnetic resonance imaging (MRI) in comparison to a full diagnostic protocol (FDP) of MRI in the breast cancer screening with dense breast tissue. There are 478 female participants with dense breast tissue and negative mammography results, who were imaged with MRI using AP and FDP. The AP and FDP images were analyzed separately, and the sensitivity and specificity of breast cancer detection were calculated. The chi-square test and receiver operating characteristics curves were used to assess the breast cancer diagnostic capabilities of the two protocols. Sixteen cases of breast cancer from 478 patients with dense breasts were detected using the FDP method, with pathologic confirmation of nine cases of ductal carcinoma in situ, six cases of invasive ductal carcinoma, and one case of mucinous carcinoma. Fifteen cases of breast cancer were successfully screened using the AP method. The sensitivity showed no obvious significant difference between AP and FDP (χ 2  = 0.592, P = 0.623), but the specificity showed a statistically significant difference (χ 2  = 4.619, P = 0.036). The receiver operating characteristics curves showed high efficacy of both methods in the detection of breast cancer in dense breast tissue (the areas under the curve were 0.931 ± 0.025 and 0.947 ± 0.024, respectively), and the ability to diagnose breast cancer was not statistically significantly different between the two methods. The AP of MRI may improve the detection rate of breast cancer in dense breast tissue, and it may be useful in efficient breast cancer screening. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Breast cancer detection in rotational thermography images using texture features

NASA Astrophysics Data System (ADS)

Francis, Sheeja V.; Sasikala, M.; Bhavani Bharathi, G.; Jaipurkar, Sandeep D.

2014-11-01

Breast cancer is a major cause of mortality in young women in the developing countries. Early diagnosis is the key to improve survival rate in cancer patients. Breast thermography is a diagnostic procedure that non-invasively images the infrared emissions from breast surface to aid in the early detection of breast cancer. Due to limitations in imaging protocol, abnormality detection by conventional breast thermography, is often a challenging task. Rotational thermography is a novel technique developed in order to overcome the limitations of conventional breast thermography. This paper evaluates this technique's potential for automatic detection of breast abnormality, from the perspective of cold challenge. Texture features are extracted in the spatial domain, from rotational thermogram series, prior to and post the application of cold challenge. These features are fed to a support vector machine for automatic classification of normal and malignant breasts, resulting in a classification accuracy of 83.3%. Feature reduction has been performed by principal component analysis. As a novel attempt, the ability of this technique to locate the abnormality has been studied. The results of the study indicate that rotational thermography holds great potential as a screening tool for breast cancer detection.

Development, fabrication and evaluation of a novel biomimetic human breast tissue derived breast implant surface.

PubMed

Barr, S; Hill, E W; Bayat, A

2017-02-01

Breast implant use has tripled in the last decade with over 320,000 breast implant based reconstructions and augmentations performed in the US per annum. Unfortunately a considerable number of women will experience capsular contracture, the irrepressible and disfiguring, tightening and hardening of the fibrous capsule that envelops the implant. Functionalising implant surfaces with biocompatible tissue-specific textures may improve in vivo performance. A novel biomimetic breast implant is presented here with anti-inflammatory in vitro abilities. Topographical assessment of native breast tissue facilitated the development of a statistical model of adipose tissue. 3D grayscale photolithography and ion etching were combined to successfully replicate a surface modelled upon the statistics of breast tissue. Pro-inflammatory genes ILβ1, TNFα, and IL6 were downregulated (p<0.001) and anti-inflammatory gene IL-10 were upregulated on the novel surface. Pro-inflammatory cytokines Gro-Alpha, TNFα and neutrophil chemoattractant IL8 were produced in lower quantities and anti-inflammatory IL-10 in higher quantities in culture with the novel surface (p<0.01). Immunocytochemistry and SEM demonstrated favourable fibroblast and macrophage responses to these novel surfaces. This study describes the first biomimetic breast tissue derived breast implant surface. Our findings attest to its potential translational ability to reduce the inflammatory phase of the implant driven foreign body reaction. Breast implants are still manufactured using outdated techniques and have changed little since their inception in the 1960's. Breast implants can cause a medical condition, capsular contracture which often results in disfigurement, pain, implant removal and further surgery. This condition is due to the body's reaction to these breast implants. This article describes the successful development and testing of a novel breast implant surface inspired by the native shapes present in breast tissue. Results show that this novel implant surface is capable of reducing the negative reaction of human cells to these surfaces which may help reduce capsular contracture formation. This work represents the first steps in producing a biocompatible breast implant. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

X-ray-induced acoustic computed tomography for 3D breast imaging: A simulation study.

PubMed

Tang, Shanshan; Yang, Kai; Chen, Yong; Xiang, Liangzhong

2018-04-01

The objective of this study is to demonstrate the feasibility of x-ray-induced acoustic computed tomography (XACT) for early breast un-palpable microcalcification (μCa) detection in three dimensions (3D). The proposed technique provides the true 3D imaging for breast volume which overcomes the disadvantage of the tissue superposition in mammography. A 3D breast digital phantom was rendered from two-dimensional (2D) breast CT slices. Three different tissue types, including the skin, adipose tissue, and glandular tissue, were labeled in the 3D breast phantom. μCas were manually embedded in different locations inside the breast phantom. For each tissue type, the initial pressure rise caused by the x-ray-induced acoustic (XA) effect was calculated according to its themoacoustic properties. The XA wave's propagation from the point of generation and its detection by ultrasound detector array were simulated by Matlab K-Wave toolbox. The 3D breast XACT volume with μCa was acquired without tissue superposition, and the system was characterized by μCas placed at different locations. The simulation results illustrated that the proposed breast XACT system has the ability to show the μCa cluster in 3D without any tissue superposition. Meanwhile, μCa as small as 100 μm in size can be detected with high imaging contrast, high signal to noise ratio (SNR), and high contrast to noise ratio (CNR). The dose required by the proposed XACT configuration was calculated to be 0.4 mGy for a 4.5 cm-thick compressed breast. This is one-tenth of the dose level of a typical two-view mammography for a breast with the same compression thickness. The initial exploration for the feasibility of 3D breast XACT has been conducted in this study. The system feasibility and characterization were illustrated through a 3D breast phantom and simulation works. The 3D breast XACT with the proposed system configuration has great potential to be applied as a low-dose screening and diagnostic technique for early un-palpable lesion in the breast. © 2018 American Association of Physicists in Medicine.

Microgravity

NASA Image and Video Library

1998-10-10

Breast tissue specimens in traditional sample dishes. NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cells (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunourous tissues.

Identification of Differentially Expressed IGFBP5-Related Genes in Breast Cancer Tumor Tissues Using cDNA Microarray Experiments.

PubMed

Akkiprik, Mustafa; Peker, İrem; Özmen, Tolga; Amuran, Gökçe Güllü; Güllüoğlu, Bahadır M; Kaya, Handan; Özer, Ayşe

2015-11-10

IGFBP5 is an important regulatory protein in breast cancer progression. We tried to identify differentially expressed genes (DEGs) between breast tumor tissues with IGFBP5 overexpression and their adjacent normal tissues. In this study, thirty-eight breast cancer and adjacent normal breast tissue samples were used to determine IGFBP5 expression by qPCR. cDNA microarrays were applied to the highest IGFBP5 overexpressed tumor samples compared to their adjacent normal breast tissue. Microarray analysis revealed that a total of 186 genes were differentially expressed in breast cancer compared with normal breast tissues. Of the 186 genes, 169 genes were downregulated and 17 genes were upregulated in the tumor samples. KEGG pathway analyses showed that protein digestion and absorption, focal adhesion, salivary secretion, drug metabolism-cytochrome P450, and phenylalanine metabolism pathways are involved. Among these DEGs, the prominent top two genes (MMP11 and COL1A1) which potentially correlated with IGFBP5 were selected for validation using real time RT-qPCR. Only COL1A1 expression showed a consistent upregulation with IGFBP5 expression and COL1A1 and MMP11 were significantly positively correlated. We concluded that the discovery of coordinately expressed genes related with IGFBP5 might contribute to understanding of the molecular mechanism of the function of IGFBP5 in breast cancer. Further functional studies on DEGs and association with IGFBP5 may identify novel biomarkers for clinical applications in breast cancer.

[Ectopic breast fibroadenoma. Case report].

PubMed

Senatore, G; Zanotti, S; Cambrini, P; Montroni, I; Pellegrini, A; Montanari, E; Santini, D; Taffurelli, M

2010-03-01

Among the rare anomalies of the breast development, polythelia is the most common, between 1% and 5% of women and men present supernumerary nipples. Polymastia, usually presenting as ectopic breast tissue without areola-nipple complex, is seen mostly along the milk line, extending from the axilla to the pubic region. Ectopic breast tissue is functionally analogous to mammary gland and it is subjected to the same alterations and diseases, whether benign or malignant, that affect normal breast tissue. We report the case of a 21 years-old female evaluated by the medical staff after founding a solid nodular mass by suspect axillary lymphadenopathy. Differential diagnosis with lymphoma is the major problem in these cases. The mass was removed and the intraoperative histological examination showed fibroadenoma in axillary supernumerary breast. Presence of ectopic breast tissue is a rare condition; development of benign mass or malignant degeneration is possible, but it is very unusual. In case of polymastia diagnosis is simple; in case of isolated nodule, without local inflammation or infection, there are greater difficulties. Ultrasonography is diagnostic in case of breast fibroadenoma, but it might be inadequate in ectopic localizations owing to the shortage of mammary tissue around the mass. Preoperative diagnosis is important to plan an adequate surgical treatment; lumpectomy is indicated in case of benign tissue; in case of malignancy, therapy is based on the standard treatment used for breast cancer (surgery, chemotherapy and radiation therapy).

X-ray phase contrast imaging of the breast: Analysis of tissue simulating materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vedantham, Srinivasan; Karellas, Andrew

Purpose: Phase contrast imaging, particularly of the breast, is being actively investigated. The purpose of this work is to investigate the x-ray phase contrast properties of breast tissues and commonly used breast tissue substitutes or phantom materials with an aim of determining the phantom materials best representative of breast tissues. Methods: Elemental compositions of breast tissues including adipose, fibroglandular, and skin were used to determine the refractive index, n= 1 -{delta}+i {beta}. The real part of the refractive index, specifically the refractive index decrement ({delta}), over the energy range of 5-50 keV were determined using XOP software (version 2.3, Europeanmore » Synchrotron Radiation Facility, France). Calcium oxalate and calcium hydroxyapatite were considered to represent the material compositions of microcalcifications in vivo. Nineteen tissue substitutes were considered as possible candidates to represent adipose tissue, fibroglandular tissue and skin, and four phantom materials were considered as possible candidates to represent microcalcifications. For each material, either the molecular formula, if available, or the elemental composition based on weight fraction, was used to determine {delta}. At each x-ray photon energy, the absolute percent difference in {delta} between the breast tissue and the substitute material was determined, from which three candidates were selected. From these candidate tissue substitutes, the material that minimized the absolute percent difference in linear attenuation coefficient {mu}, and hence {beta}, was considered to be best representative of that breast tissue. Results: Over the energy range of 5-50 keV, while the {delta} of CB3 and fibroglandular tissue-equivalent material were within 1% of that of fibroglandular tissue, the {mu} of fibroglandular tissue-equivalent material better approximated the fibroglandular tissue. While the {delta} of BR10 and adipose tissue-equivalent material were within 1% of that of adipose tissue, the tissue-equivalent material better approximated the adipose tissue in terms of {mu}. Polymethyl methacrylate, a commonly used tissue substitute, exhibited {delta} greater than fibroglandular tissue by {approx}12%. The A-150 plastic closely approximated the skin. Several materials exhibited {delta} between that of adipose and fibroglandular tissue. However, there was an energy-dependent mismatch in terms of equivalent fibroglandular weight fraction between {delta} and {mu} for these materials. For microcalcifications, aluminum and calcium carbonate were observed to straddle the {delta} and {mu} of calcium oxalate and calcium hydroxyapatite. Aluminum oxide, commonly used to represent microcalcifications in the American College of Radiology recommended phantoms for accreditation exhibited {delta} greater than calcium hydroxyapatite by {approx}23%. Conclusions: A breast phantom comprising A-150 plastic to represent the skin, commercially available adipose and fibroglandular tissue-equivalent formulations to represent adipose and fibroglandular tissue, respectively, was found to be best suited for x-ray phase-sensitive imaging of the breast. Calcium carbonate or aluminum can be used to represent microcalcifications.« less

X-ray phase contrast imaging of the breast: Analysis of tissue simulating materials1

PubMed Central

Vedantham, Srinivasan; Karellas, Andrew

2013-01-01

Purpose: Phase contrast imaging, particularly of the breast, is being actively investigated. The purpose of this work is to investigate the x-ray phase contrast properties of breast tissues and commonly used breast tissue substitutes or phantom materials with an aim of determining the phantom materials best representative of breast tissues. Methods: Elemental compositions of breast tissues including adipose, fibroglandular, and skin were used to determine the refractive index, n = 1 − δ + i β. The real part of the refractive index, specifically the refractive index decrement (δ), over the energy range of 5–50 keV were determined using XOP software (version 2.3, European Synchrotron Radiation Facility, France). Calcium oxalate and calcium hydroxyapatite were considered to represent the material compositions of microcalcifications in vivo. Nineteen tissue substitutes were considered as possible candidates to represent adipose tissue, fibroglandular tissue and skin, and four phantom materials were considered as possible candidates to represent microcalcifications. For each material, either the molecular formula, if available, or the elemental composition based on weight fraction, was used to determine δ. At each x-ray photon energy, the absolute percent difference in δ between the breast tissue and the substitute material was determined, from which three candidates were selected. From these candidate tissue substitutes, the material that minimized the absolute percent difference in linear attenuation coefficient μ, and hence β, was considered to be best representative of that breast tissue. Results: Over the energy range of 5–50 keV, while the δ of CB3 and fibroglandular tissue-equivalent material were within 1% of that of fibroglandular tissue, the μ of fibroglandular tissue-equivalent material better approximated the fibroglandular tissue. While the δ of BR10 and adipose tissue-equivalent material were within 1% of that of adipose tissue, the tissue-equivalent material better approximated the adipose tissue in terms of μ. Polymethyl methacrylate, a commonly used tissue substitute, exhibited δ greater than fibroglandular tissue by ∼12%. The A-150 plastic closely approximated the skin. Several materials exhibited δ between that of adipose and fibroglandular tissue. However, there was an energy-dependent mismatch in terms of equivalent fibroglandular weight fraction between δ and μ for these materials. For microcalcifications, aluminum and calcium carbonate were observed to straddle the δ and μ of calcium oxalate and calcium hydroxyapatite. Aluminum oxide, commonly used to represent microcalcifications in the American College of Radiology recommended phantoms for accreditation exhibited δ greater than calcium hydroxyapatite by ∼23%. Conclusions: A breast phantom comprising A-150 plastic to represent the skin, commercially available adipose and fibroglandular tissue-equivalent formulations to represent adipose and fibroglandular tissue, respectively, was found to be best suited for x-ray phase-sensitive imaging of the breast. Calcium carbonate or aluminum can be used to represent microcalcifications. PMID:23556900

Defining the Role of Free Flaps in Partial Breast Reconstruction.

PubMed

Smith, Mark L; Molina, Bianca J; Dayan, Erez; Jablonka, Eric M; Okwali, Michelle; Kim, Julie N; Dayan, Joseph H

2018-03-01

 Free flaps have a well-established role in breast reconstruction after mastectomy; however, their role in partial breast reconstruction remains poorly defined. We reviewed our experience with partial breast reconstruction to better understand indications for free tissue transfer.  A retrospective review was performed of all patients undergoing partial breast reconstruction at our center between February 2009 and October 2015. We evaluated the characteristics of patients who underwent volume displacement procedures versus volume replacement procedures and free versus pedicled flap reconstruction.  There were 78 partial breast reconstructions, with 52 reductions/tissue rearrangements (displacement group) and 26 flaps (replacement group). Bra cup size and body mass index (BMI) were significantly smaller in the replacement group. Fifteen pedicled and 11 free flaps were performed. Most pedicled flaps (80.0%) were used for lateral or upper pole defects. Most free flaps (72.7%) were used for medial and inferior defects or when there was inadequate donor tissue for a pedicled flap. Complications included hematoma, cellulitis, and one aborted pedicled flap.  Free and pedicled flaps are useful for partial breast reconstruction, particularly in breast cancer patients with small breasts undergoing breast-conserving treatment (BCT). Flap selection depends on defect size, location, and donor tissue availability. Medial defects are difficult to reconstruct using pedicled flaps due to arc of rotation and intervening breast tissue. Free tissue transfer can overcome these obstacles. Confirming negative margins before flap reconstruction ensures harvest of adequate volume and avoids later re-operation. Judicious use of free flaps for oncoplastic reconstruction expands the possibility for breast conservation. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Development and Psychometric Evaluation of a Questionnaire Based on the Nursing Outcomes Classification to Determine the Knowledge of Parents on Breast-Feeding: Research Protocol.

PubMed

Paloma-Castro, Olga; Romero-Sánchez, José Manuel; Paramio-Cuevas, Juan Carlos; Pastor-Montero, Sonia María; Del Carmen Sánchez-Dalda, María; Rozadillas-Sanmiguel, Elena; Moreno-Corral, Luis Javier

2017-04-01

To develop and psychometrically evaluate a questionnaire based on the outcome "Knowledge: Breast-feeding" of the Nursing Outcomes Classification (NOC) to determine the knowledge of parents on breast-feeding. The NOC outcome "Knowledge: Breast-feeding" allows for nurses/midwives to assess the efficacy of interventions aimed to improve the knowledge on breast-feeding in parents thought the clinical interview/observation. However, the use of self-administered questionnaires by patients could facilitate its evaluation. Two-phased study: (1) Development of the questionnaire based on experts' opinions; (2) Methodological design to assess its psychometric properties. The availability of tools that enable the determination of the knowledge of patients would facilitate nurses/midwives to set objectives, individualize interventions, and measure their effectiveness. © 2015 NANDA International, Inc.

Differences in elongation of very long chain fatty acids and fatty acid metabolism between triple-negative and hormone receptor-positive breast cancer.

PubMed

Yamashita, Yuji; Nishiumi, Shin; Kono, Seishi; Takao, Shintaro; Azuma, Takeshi; Yoshida, Masaru

2017-08-29

Triple-negative breast cancer (TN) is more aggressive than other subtypes of breast cancer and has a lower survival rate. Furthermore, detailed biological information about the disease is lacking. This study investigated characteristics of metabolic pathways in TN. We performed the metabolome analysis of 74 breast cancer tissues and the corresponding normal breast tissues using LC/MS. Furthermore, we classified the breast cancer tissues into ER-positive, PgR-positive, HER2-negative breast cancer (EP+H-) and TN, and then the differences in their metabolic pathways were investigated. The RT-PCR and immunostaining were carried out to examine the expression of ELOVL1, 2, 3, 4, 5, 6, and 7. We identified 142 of hydrophilic metabolites and 278 of hydrophobic lipid metabolites in breast tissues. We found the differences between breast cancer and normal breast tissues in choline metabolism, glutamine metabolism, lipid metabolism, and so on. Most characteristic of comparison between EP+H- and TN were differences in fatty acid metabolism was which were related to the elongation of very long chain fatty acids were detected between TN and EP+H-. Real-time RT-PCR showed that the mRNA expression levels of ELOVL1, 5, and 6 were significantly upregulated by 8.5-, 4.6- and 7.0-fold, respectively, in the TN tumors compared with their levels in the corresponding normal breast tissue samples. Similarly, the mRNA expression levels of ELOVL1, 5, and 6 were also significantly higher in the EP+H- tissues than in the corresponding normal breast tissues (by 4.9-, 3.4-, and 2.1-fold, respectively). The mRNA expression level of ELOVL6 was 2.6-fold higher in the TN tumors than in the EP+H- tumors. During immunostaining, the TN and EP+H- tumors demonstrated stronger ELOVL1 and 6 staining than the corresponding normal breast tissues, but ELOVL5 was not stained strongly in the TN or EP+H- tumors. Furthermore, the TN tumors exhibited stronger ELOVL1 and 6 staining than the EP+H- tumors. Marked differences in fatty acid metabolism pathways, including those related to ELOVL1 and 6, were detected between TN and EP+H-, and it was suggested that ELOVL1 and 6-related fatty acid metabolism pathways may be targets for therapies against TN.

Estimation and imaging of breast lesions using a two-layer tissue structure by ultrasound-guided optical tomography

PubMed Central

Xu, Yan; Zhu, Quing

2015-01-01

Abstract. A new two-step estimation and imaging method is developed for a two-layer breast tissue structure consisting of a breast tissue layer and a chest wall underneath. First, a smaller probe with shorter distance source-detector pairs was used to collect the reflected light mainly from the breast tissue layer. Then, a larger probe with 9×14 source-detector pairs and a centrally located ultrasound transducer was used to collect reflected light from the two-layer tissue structure. The data collected from the smaller probe were used to estimate breast tissue optical properties. With more accurate estimation of the average breast tissue properties, the second layer properties can be assessed from data obtained from the larger probe. Using this approach, the unknown variables have been reduced from four to two and the estimated bulk tissue optical properties are more accurate and robust. In addition, a two-step reconstruction using a genetic algorithm and conjugate gradient method is implemented to simultaneously reconstruct the absorption and reduced scattering maps of targets inside a two-layer tissue structure. Simulations and phantom experiments have been performed to validate the new reconstruction method, and a clinical example is given to demonstrate the feasibility of this approach. PMID:26046722

Local curvature analysis for classifying breast tumors: Preliminary analysis in dedicated breast CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Juhun, E-mail: leej15@upmc.edu; Nishikawa, Robert M.; Reiser, Ingrid

2015-09-15

Purpose: The purpose of this study is to measure the effectiveness of local curvature measures as novel image features for classifying breast tumors. Methods: A total of 119 breast lesions from 104 noncontrast dedicated breast computed tomography images of women were used in this study. Volumetric segmentation was done using a seed-based segmentation algorithm and then a triangulated surface was extracted from the resulting segmentation. Total, mean, and Gaussian curvatures were then computed. Normalized curvatures were used as classification features. In addition, traditional image features were also extracted and a forward feature selection scheme was used to select the optimalmore » feature set. Logistic regression was used as a classifier and leave-one-out cross-validation was utilized to evaluate the classification performances of the features. The area under the receiver operating characteristic curve (AUC, area under curve) was used as a figure of merit. Results: Among curvature measures, the normalized total curvature (C{sub T}) showed the best classification performance (AUC of 0.74), while the others showed no classification power individually. Five traditional image features (two shape, two margin, and one texture descriptors) were selected via the feature selection scheme and its resulting classifier achieved an AUC of 0.83. Among those five features, the radial gradient index (RGI), which is a margin descriptor, showed the best classification performance (AUC of 0.73). A classifier combining RGI and C{sub T} yielded an AUC of 0.81, which showed similar performance (i.e., no statistically significant difference) to the classifier with the above five traditional image features. Additional comparisons in AUC values between classifiers using different combinations of traditional image features and C{sub T} were conducted. The results showed that C{sub T} was able to replace the other four image features for the classification task. Conclusions: The normalized curvature measure contains useful information in classifying breast tumors. Using this, one can reduce the number of features in a classifier, which may result in more robust classifiers for different datasets.« less

A feasibility study of soft embalmed human breast tissue for preclinical trials of HIFU- preliminary results

NASA Astrophysics Data System (ADS)

Joy, Joyce; Yang, Yang; Purdie, Colin; Eisma, Roos; Melzer, Andreas; Cochran, Sandy; Vinnicombe, Sarah

2017-03-01

Breast cancer is the commonest cancer in women in the UK, accounting for 30% of all new cancers in women, with an estimated 49,500 new cases in 20101. With the widespread negative publicity around over-diagnosis and over-treatment of low risk breast cancers, interest in the application of non-invasive treatments such as magnetic resonance imaging (MRI) guided high intensity focused ultrasound (HIFU) has increased. Development has begun of novel US transducers and platforms specifically designed for use with breast lesions, so as to improve the range of breast lesions that can be safely treated. However, before such transducers can be evaluated in patients in clinical trials, there is a need to establish their efficacy. A particular issue is the accuracy of temperature monitoring of FUS with MRI in the breast, since the presence of large amounts of surrounding fat can hinder temperature measurement. An appropriate anatomical model that imposes similar physical constraints to the breast and that responds to FUS in the same way would be extremely advantageous. The aim of this feasibility study is to explore the use of Thiel embalmed cadaveric tissue for these purposes. We report here the early results of laboratory-based experiments sonicating dissected breast samples from a Thiel embalmed soft human cadaver with high body mass index (BMI). A specially developed MRI compatible chamber and sample holder was developed to secure the sample and ensure reproducible sonications at the transducer focus. The efficacy of sonication was first studied with chicken breast and porcine tissue. The experiments were then repeated with the dissected fatty breast tissue samples from the soft-embalmed human cadavers. The sonicated Thiel breast tissue was examined histopathologically, which confirmed the absence of any discrete lesion. To investigate further, fresh chicken breast tissue was embalmed and the embalmed tissue was sonicated with the same parameters. The results confirmed the inability to produce a discrete lesion in any of the Thiel embalmed samples.

A probable risk factor of female breast cancer: study on benign and malignant breast tissue samples.

PubMed

Rehman, Sohaila; Husnain, Syed M

2014-01-01

The study reports enhanced Fe, Cu, and Zn contents in breast tissues, a probable risk factor of breast cancer in females. Forty-one formalin-fixed breast tissues were analyzed using atomic absorption spectrophotometry. Twenty malignant, six adjacent to malignant and 15 benign tissues samples were investigated. The malignant tissues samples were of grade 11 and type invasive ductal carcinoma. The quantitative comparison between the elemental levels measured in the two types of specimen (benign and malignant) tissues (removed after surgery) suggests significant elevation of these metals (Fe, Cu, and Zn) in the malignant tissue. The specimens were collected just after mastectomy of women aged 19 to 59 years from the hospitals of Islamabad and Rawalpindi, Pakistan. Most of the patients belong to urban areas of Pakistan. Findings of study depict that these elements have a promising role in the initiation and development of carcinoma as consistent pattern of elevation for Fe, Cu, and Zn was observed. The results showed the excessive accumulation of Fe (229 ± 121 mg/L) in malignant breast tissue samples of patients (p < 0.05) to that in benign tissues samples (49.1 ± 11.4 mg/L). Findings indicated that excess accumulation of iron in malignant tissues can be a risk factor of breast cancer. In order to validate our method of analysis, certified reference material muscle tissue lyophilized (IAEA) MA-M-2/TM was analyzed for metal studied. Determined concentrations were quite in good agreement with certified levels. Asymmetric concentration distribution for Fe, Cu, and Zn was observed in both malignant and benign tissue samples.

Feasibility of spatial frequency-domain imaging for monitoring palpable breast lesions

NASA Astrophysics Data System (ADS)

Robbins, Constance M.; Raghavan, Guruprasad; Antaki, James F.; Kainerstorfer, Jana M.

2017-12-01

In breast cancer diagnosis and therapy monitoring, there is a need for frequent, noninvasive disease progression evaluation. Breast tumors differ from healthy tissue in mechanical stiffness as well as optical properties, which allows optical methods to detect and monitor breast lesions noninvasively. Spatial frequency-domain imaging (SFDI) is a reflectance-based diffuse optical method that can yield two-dimensional images of absolute optical properties of tissue with an inexpensive and portable system, although depth penetration is limited. Since the absorption coefficient of breast tissue is relatively low and the tissue is quite flexible, there is an opportunity for compression of tissue to bring stiff, palpable breast lesions within the detection range of SFDI. Sixteen breast tissue-mimicking phantoms were fabricated containing stiffer, more highly absorbing tumor-mimicking inclusions of varying absorption contrast and depth. These phantoms were imaged with an SFDI system at five levels of compression. An increase in absorption contrast was observed with compression, and reliable detection of each inclusion was achieved when compression was sufficient to bring the inclusion center within ˜12 mm of the phantom surface. At highest compression level, contrasts achieved with this system were comparable to those measured with single source-detector near-infrared spectroscopy.

Anatomical classification of breast sentinel lymph nodes using computed tomography-lymphography.

PubMed

Fujita, Tamaki; Miura, Hiroyuki; Seino, Hiroko; Ono, Shuichi; Nishi, Takashi; Nishimura, Akimasa; Hakamada, Kenichi; Aoki, Masahiko

2018-05-03

To evaluate the anatomical classification and location of breast sentinel lymph nodes, preoperative computed tomography-lymphography examinations were retrospectively reviewed for sentinel lymph nodes in 464 cases clinically diagnosed with node-negative breast cancer between July 2007 and June 2016. Anatomical classification was performed based on the numbers of lymphatic routes and sentinel lymph nodes, the flow direction of lymphatic routes, and the location of sentinel lymph nodes. Of the 464 cases reviewed, anatomical classification could be performed in 434 (93.5 %). The largest number of cases showed single route/single sentinel lymph node (n = 296, 68.2 %), followed by multiple routes/multiple sentinel lymph nodes (n = 59, 13.6 %), single route/multiple sentinel lymph nodes (n = 53, 12.2 %), and multiple routes/single sentinel lymph node (n = 26, 6.0 %). Classification based on the flow direction of lymphatic routes showed that 429 cases (98.8 %) had outward flow on the superficial fascia toward axillary lymph nodes, whereas classification based on the height of sentinel lymph nodes showed that 323 cases (74.4 %) belonged to the upper pectoral group of axillary lymph nodes. There was wide variation in the number of lymphatic routes and their branching patterns and in the number, location, and direction of flow of sentinel lymph nodes. It is clinically very important to preoperatively understand the anatomical morphology of lymphatic routes and sentinel lymph nodes for optimal treatment of breast cancer, and computed tomography-lymphography is suitable for this purpose.

TU-CD-207-01: Characterization of Breast Tissue Composition Using Spectral Mammography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, H; Cho, H; Kumar, N

Purpose: To investigate the feasibility of characterizing the chemical composition of breast tissue, in terms of water and lipid, by using spectral mammography in simulation and postmortem studies. Methods: Analytical simulations were performed to obtain low- and high-energy signals of breast tissue based on previously reported water, lipid, and protein contents. Dual-energy decomposition was used to characterize the simulated breast tissue into water and lipid basis materials and the measured water density was compared to the known value. In experimental studies, postmortem breasts were imaged with a spectral mammography system based on a scanning multi-slit Si strip photon-counting detector. Low-more » and high-energy images were acquired simultaneously from a single exposure by sorting the recorded photons into the corresponding energy bins. Dual-energy material decomposition of the low- and high-energy images yielded individual pixel measurements of breast tissue composition in terms of water and lipid thicknesses. After imaging, each postmortem breast was chemically decomposed into water, lipid and protein. The water density calculated from chemical analysis was used as the reference gold standard. Correlation of the water density measurements between spectral mammography and chemical analysis was analyzed using linear regression. Results: Both simulation and postmortem studies showed good linear correlation between the decomposed water thickness using spectral mammography and chemical analysis. The slope of the linear fitting function in the simulation and postmortem studies were 1.15 and 1.21, respectively. Conclusion: The results indicate that breast tissue composition, in terms of water and lipid, can be accurately measured using spectral mammography. Quantitative breast tissue composition can potentially be used to stratify patients according to their breast cancer risk.« less

Normal breast tissue DNA methylation differences at regulatory elements are associated with the cancer risk factor age.

PubMed

Johnson, Kevin C; Houseman, E Andres; King, Jessica E; Christensen, Brock C

2017-07-10

The underlying biological mechanisms through which epidemiologically defined breast cancer risk factors contribute to disease risk remain poorly understood. Identification of the molecular changes associated with cancer risk factors in normal tissues may aid in determining the earliest events of carcinogenesis and informing cancer prevention strategies. Here we investigated the impact cancer risk factors have on the normal breast epigenome by analyzing DNA methylation genome-wide (Infinium 450 K array) in cancer-free women from the Susan G. Komen Tissue Bank (n = 100). We tested the relation of established breast cancer risk factors, age, body mass index, parity, and family history of disease, with DNA methylation adjusting for potential variation in cell-type proportions. We identified 787 cytosine-guanine dinucleotide (CpG) sites that demonstrated significant associations (Q value <0.01) with subject age. Notably, DNA methylation was not strongly associated with the other evaluated breast cancer risk factors. Age-related DNA methylation changes are primarily increases in methylation enriched at breast epithelial cell enhancer regions (P = 7.1E-20), and binding sites of chromatin remodelers (MYC and CTCF). We validated the age-related associations in two independent populations, using normal breast tissue samples (n = 18) and samples of normal tissue adjacent to tumor tissue (n = 97). The genomic regions classified as age-related were more likely to be regions altered in both pre-invasive (n = 40, P = 3.0E-03) and invasive breast tumors (n = 731, P = 1.1E-13). DNA methylation changes with age occur at regulatory regions, and are further exacerbated in cancer, suggesting that age influences breast cancer risk in part through its contribution to epigenetic dysregulation in normal breast tissue.

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

PubMed Central

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 < 0.05) in disease-free survivals between the three CMTC groups after an additional two years of follow-up (median = 55 months). The prognostic 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. 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

Improved Hardware for Higher Spatial Resolution Strain-ENCoded (SENC) Breast MRI for Strain Measurements

PubMed Central

Harouni, Ahmed A.; Hossain, Jakir; Jacobs, Michael A.; Osman, Nael F.

2012-01-01

Introduction Early detection of breast lesions using mammography has resulted in lower mortality-rates. However, some breast lesions are mammography occult and magnetic resonance imaging (MRI) is recommended, but has lower specificity. It is possible to achieve higher specificity by using Strain-ENCoded (SENC) MRI and/or magnetic resonance elastography(MRE). SENC breast MRI can measure the strain properties of breast tissue. Similarly, MRE is used to measure elasticity (i.e., shear stiffness) of different tissue compositions interrogating the tissue mechanical properties. Reports have shown that malignant tumors are 3–13 times stiffer than normal tissue and benign tumors. Methods We have developed a Strain-ENCoded (SENC) breast hardware device capable of periodically compressing the breast, thus allowing for longer scanning time and measuring the strain characteristics of breast tissue. This hardware enabled us to use SENC MRI with high spatial resolution (1×1×5mm3) instead of Fast SENC(FSENC). Simple controls and multiple safety measures were added to ensure accurate, repeatable and safe in-vivo experiments. Results Phantom experiments showed that SENC breast MRI has higher SNR and CNR than FSENC under different scanning resolutions. Finally, the SENC breast device reproducibility measurements resulted in a difference of less than one mm with a 1% strain difference. Conclusion SENC breast MR images have higher SNR and CNR than FSENC images. Thus, combining SENC breast strain measurements with diagnostic breast MRI to differentiate benign from malignant lesions could potentially increase the specificity of diagnosis in the clinical setting. PMID:21440464

MicroRNA-9 promotes the proliferation, migration, and invasion of breast cancer cells via down-regulating FOXO1.

PubMed

Liu, D-Z; Chang, B; Li, X-D; Zhang, Q-H; Zou, Y-H

2017-09-01

The objective of the study was to investigate the role of microRNA-9 (miR-9) targeting forkhead box O1 (FOXO1) in the proliferation, migration, and invasion of breast cancer cells. Quantitative real-time polymerase chain reaction (qRT-PCR) was employed to determine the expressions of miR-9 and FOXO1 mRNA in breast cancer tissues, normal breast tissues, breast cancer cell lines, and normal breast epithelial cells. After the up-regulation of miR-9 expression, qRT-PCR and Western blotting were used to determine the expression of FOXO1. The luciferase reporter gene assay was used to validate the target gene. The CCK-8 assay, scratch-wound healing assay, and Transwell invasion assay were used to investigate the changes in the proliferation, migration, and invasion of breast cancer cells, respectively. MicroRNA-9 expression was significantly up-regulated in breast cancer tissues and breast cancer cell lines when compared with normal breast tissues and normal breast epithelial cells (both P < 0.05). FOXO1 mRNA and protein expressions were substantially down-regulated in breast cancer tissues and breast cancer cell lines when compared with normal breast tissues and normal breast epithelial cells (both P < 0.05). There can be a negative correlation between miR-9 and FOXO1 mRNA in breast cancer. Luciferase reporter gene assay indicated that miR-9 can down-regulate FOXO1 expression at a post-transcriptional level through binding specifically to FOXO1 3'UTR. The results of CCK-8 assay, scratch-wound healing assay, and Transwell invasion assay revealed that the inhibition of miR-9 can suppress MCF7 cell proliferation, migration, and invasion. Additionally, the expression of miR-9 increased significantly whilst that of FOXO1 decreased substantially as the disease progressed (P < 0.05). Our study provides evidence that miR-9 can promote the proliferation, migration, and invasion of breast cancer cells via down-regulating FOXO1.

Antiandrogenic actions of medroxyprogesterone acetate on epithelial cells within normal human breast tissues cultured ex vivo.

PubMed

Ochnik, Aleksandra M; Moore, Nicole L; Jankovic-Karasoulos, Tanja; Bianco-Miotto, Tina; Ryan, Natalie K; Thomas, Mervyn R; Birrell, Stephen N; Butler, Lisa M; Tilley, Wayne D; Hickey, Theresa E

2014-01-01

Medroxyprogesterone acetate (MPA), a component of combined estrogen-progestin therapy (EPT), has been associated with increased breast cancer risk in EPT users. MPA can bind to the androgen receptor (AR), and AR signaling inhibits cell growth in breast tissues. Therefore, the aim of this study was to investigate the potential of MPA to disrupt AR signaling in an ex vivo culture model of normal human breast tissue. Histologically normal breast tissues from women undergoing breast surgical operation were cultured in the presence or in the absence of the native AR ligand 5α-dihydrotestosterone (DHT), MPA, or the AR antagonist bicalutamide. Ki67, bromodeoxyuridine, B-cell CLL/lymphoma 2 (BCL2), AR, estrogen receptor α, and progesterone receptor were detected by immunohistochemistry. DHT inhibited the proliferation of breast epithelial cells in an AR-dependent manner within tissues from postmenopausal women, and MPA significantly antagonized this androgenic effect. These hormonal responses were not commonly observed in cultured tissues from premenopausal women. In tissues from postmenopausal women, DHT either induced or repressed BCL2 expression, and the antiandrogenic effect of MPA on BCL2 was variable. MPA significantly opposed the positive effect of DHT on AR stabilization, but these hormones had no significant effect on estrogen receptor α or progesterone receptor levels. In a subset of postmenopausal women, MPA exerts an antiandrogenic effect on breast epithelial cells that is associated with increased proliferation and destabilization of AR protein. This activity may contribute mechanistically to the increased risk of breast cancer in women taking MPA-containing EPT.

Minimising Immunohistochemical False Negative ER Classification Using a Complementary 23 Gene Expression Signature of ER Status

PubMed Central

Li, Qiyuan; Eklund, Aron C.; Juul, Nicolai; Haibe-Kains, Benjamin; Workman, Christopher T.; Richardson, Andrea L.; Szallasi, Zoltan; Swanton, Charles

2010-01-01

Background Expression of the oestrogen receptor (ER) in breast cancer predicts benefit from endocrine therapy. Minimising the frequency of false negative ER status classification is essential to identify all patients with ER positive breast cancers who should be offered endocrine therapies in order to improve clinical outcome. In routine oncological practice ER status is determined by semi-quantitative methods such as immunohistochemistry (IHC) or other immunoassays in which the ER expression level is compared to an empirical threshold[1], [2]. The clinical relevance of gene expression-based ER subtypes as compared to IHC-based determination has not been systematically evaluated. Here we attempt to reduce the frequency of false negative ER status classification using two gene expression approaches and compare these methods to IHC based ER status in terms of predictive and prognostic concordance with clinical outcome. Methodology/Principal Findings Firstly, ER status was discriminated by fitting the bimodal expression of ESR1 to a mixed Gaussian model. The discriminative power of ESR1 suggested bimodal expression as an efficient way to stratify breast cancer; therefore we identified a set of genes whose expression was both strongly bimodal, mimicking ESR expression status, and highly expressed in breast epithelial cell lines, to derive a 23-gene ER expression signature-based classifier. We assessed our classifiers in seven published breast cancer cohorts by comparing the gene expression-based ER status to IHC-based ER status as a predictor of clinical outcome in both untreated and tamoxifen treated cohorts. In untreated breast cancer cohorts, the 23 gene signature-based ER status provided significantly improved prognostic power compared to IHC-based ER status (P = 0.006). In tamoxifen-treated cohorts, the 23 gene ER expression signature predicted clinical outcome (HR = 2.20, P = 0.00035). These complementary ER signature-based strategies estimated that between 15.1% and 21.8% patients of IHC-based negative ER status would be classified with ER positive breast cancer. Conclusion/Significance Expression-based ER status classification may complement IHC to minimise false negative ER status classification and optimise patient stratification for endocrine therapies. PMID:21152022

An Ectopic Breast Tissue Presenting with Fibroadenoma in Axilla

PubMed Central

Amaranathan, Anandhi; Balaguruswamy, Kanchana; Bhat, Ramachandra V.; Bora, Manash Kumar

2013-01-01

Introduction. The congenital anomalies of breast, especially the polymastia (supernumerary breast) and polythelia (supernumerary nipple), always do not fail to amuse the clinicians because of their varied presentations, associated renal anomalies, and pathologies arising from them. The axillary polymastia is a variant of ectopic breast tissue (EBT). Ectopic breast tissue can undergo the same physiological and pathological processes as the normally located breast. The incidence of fibroadenoma developing in ectopic breast is reported as a rare entity, the most common being the carcinoma. Case Presentation. A 31-year-old Dravidian female presented with a lump of 4 cm in the right axilla for the past year which gradually increased in size, giving discomfort. Our initial differential diagnosis was fibroadenoma, lipoma, and lymphadenopathy. Further investigation and histopathological report of excision biopsy confirmed it as a fibroadenoma on ectopic breast tissue in the axilla. Patient has no associated urological or cardiac anomaly. Conclusion. This case has been reported for its rarity and to reemphasise the importance of screening of EBT for any pathology during routine screening of breast. PMID:23607040

An ectopic breast tissue presenting with fibroadenoma in axilla.

PubMed

Amaranathan, Anandhi; Balaguruswamy, Kanchana; Bhat, Ramachandra V; Bora, Manash Kumar

2013-01-01

Introduction. The congenital anomalies of breast, especially the polymastia (supernumerary breast) and polythelia (supernumerary nipple), always do not fail to amuse the clinicians because of their varied presentations, associated renal anomalies, and pathologies arising from them. The axillary polymastia is a variant of ectopic breast tissue (EBT). Ectopic breast tissue can undergo the same physiological and pathological processes as the normally located breast. The incidence of fibroadenoma developing in ectopic breast is reported as a rare entity, the most common being the carcinoma. Case Presentation. A 31-year-old Dravidian female presented with a lump of 4 cm in the right axilla for the past year which gradually increased in size, giving discomfort. Our initial differential diagnosis was fibroadenoma, lipoma, and lymphadenopathy. Further investigation and histopathological report of excision biopsy confirmed it as a fibroadenoma on ectopic breast tissue in the axilla. Patient has no associated urological or cardiac anomaly. Conclusion. This case has been reported for its rarity and to reemphasise the importance of screening of EBT for any pathology during routine screening of breast.

Clinical significance of Mena and Her-2 expression in breast cancer.

PubMed

Du, J W; Xu, K Y; Fang, L Y; Qi, X L

2012-01-01

The aim of this study was to determine the expression patterns of Mena and Her-2 in breast cancer tissues and to explore their clinical significance and correlation with clinicopathological parameters. The expression of Mena and Her-2 was detected in 40 breast cancer tissues and 14 normal breast tissues by immunohistochemistry, and the relationship of Mena and Her-2 expression with clinicopathological parameters was analyzed. Both Mena (70%) and Her-2 (40%) were more commonly expressed in breast cancer than in normal breast tissue (7.1%, 0%, respectively; p < 0.05); further, Mena and Her-2 expression in breast cancer were positively correlated (r = 0.530, p < 0.05). In comparing expression with clinicopathological parameters of tumor samples, Mena and Her-2 were both associated with axillary lymph node metastasis and TNM stage (p < 0.05), but not with patient age or pathological type. Mena and Her-2 are related to the malignancy degree and metastasis of breast cancer, and thus may play a coordinating role in the occurrence and progression of breast cancer.

Identifying Breast Tumor Suppressors Using in Vitro and in Vivo RNAi Screens

DTIC Science & Technology

2011-10-01

vivo RNA interference screen, breast cancer , tumor suppressor, leukemia inhibitory factor receptor (LIFR) 16. SECURITY CLASSIFICATION OF: 17...The identification of these genes will improve the understanding of the causes of breast cancer , which may lead to therapeutic advancements for... breast cancer prevention and treatment. BODY Objective 1: Identification of breast tumor suppressors using in vitro and in vivo RNAi screens

Prevention and treatment of breast cancer by suppressing aromatase activity and expression.

PubMed

Chen, Shiuan; Zhou, Dujin; Okubo, Tomoharu; Kao, Yeh-Chih; Eng, Elizabeth T; Grube, Baiba; Kwon, Annette; Yang, Chun; Yu, Bin

2002-06-01

Estrogen promotes the proliferation of breast cancer cells. Aromatase is the enzyme that converts androgen to estrogen. In tumors, expression of aromatase is upregulated compared to that of surrounding noncancerous tissue. Tumor aromatase is thought to stimulate breast cancer growth in both an autocrine and a paracrine manner. A treatment strategy for breast cancer is to abolish in situ estrogen formation with aromatase inhibitors. In addition, aromatase suppression in postmenapausal women is being evaluated as a potential chemopreventive modality against breast cancer. One area of aromatase research in this laboratory is the identification of foods and dietary compounds that can suppress aromatase activity. In vitro and in vivo studies have found that grapes and mushrooms contain chemicals that can inhibit aromatase. Therefore, a diet that includes grapes and mushrooms would be considered preventative against breast cancer. Another area of our aromatase research is the elucidation of the regulatory mechanism of aromatase expression in breast cancer tissue. Increased aromatase expression in breast tumors is attributed to changes in the transcriptional control of aromatase expression. Whereas promoter I.4 is the main promoter that controls aromatase expression in noncancerous breast tissue, promoters II and I.3 are the dominant promoters that drive aromatase expression in breast cancer tissue. Our recent gene regulation studies revealed that in cancerous versus normal tissue, several positive regulatory proteins (e.g., nuclear receptors and CREB1) are present at higher levels and several negative regulatory proteins (e.g., snail and slug proteins) are present at lower levels. This may explain why the activity of promoters II and I.3 is upregulated in cancerous tissue. In addition, our in vitro transcription/translation analysis using plasmids containing T7 promoter and the human snail gene as a reporter capped with different untranslated exon Is revealed that exon PII-containing transcripts were translated more effectively than were exon I.3-containing transcripts. An understanding of the molecular mechanisms of aromatase expression between noncancerous and cancerous breast tissue, at both transcriptional and translational levels, may help in the design of a therapy based on suppressing aromatase expression in breast cancer tissue.

Non-Invasive Imaging of In Vivo Breast Cancer Tissue Utilizing Metabolically Incorporated Unnatural Sugars

DTIC Science & Technology

2004-08-01

or misdiagnosed (4). Therefore, much effort is now directed toward developing alternative breast cancer detection technologies that exploit the...AD Award Number: DAMD17-03-1-0548 TITLE: Non-Invasive Imaging of In Vivo Breast Cancer Tissue Utilizing Metabolically Incorporated Unnatrual Sugars...5. FUNDING NUMBERS Non-Invasive Imaging of In Vivo Breast Cancer Tissue DAMD17-03-1-0548 Utilizing Metabolically Incorporated Unnatrual Sugars 6. A

Advancing Our Understanding of the Etiologies and Mutational Landscapes of Basal-Like, Luminal A, and Luminal B Breast Cancers

DTIC Science & Technology

2017-10-01

various breast cancer risk factors differ in their relationships to different molecular subtypes of breast cancer and to further characterize... molecular differences between these subtypes. To address the existing research gaps regarding the etiologies of different molecular subtypes of breast... molecular subtypes of breast cancer, basal-like, luminal A, and luminal B tumors, breast cancer risk factors 16. SECURITY CLASSIFICATION OF: 17. LIMITATION

The role of lipid droplets and adipocytes in cancer. Raman imaging of cell cultures: MCF10A, MCF7, and MDA-MB-231 compared to adipocytes in cancerous human breast tissue.

PubMed

Abramczyk, Halina; Surmacki, Jakub; Kopeć, Monika; Olejnik, Alicja Klaudia; Lubecka-Pietruszewska, Katarzyna; Fabianowska-Majewska, Krystyna

2015-04-07

We have studied live non-malignant (MCF10A), mildly malignant (MCF7) and malignant (MDA-MB-231) breast cancer cells and human breast cancer tissue. We demonstrate the first application of Raman imaging and spectroscopy in diagnosing the role of lipid droplets in cell line cultures that closely mimic an in vivo environment of various stages in human breast cancer tissue. We have analyzed the composition of the lipid droplets in non-malignant and malignant human breast epithelial cell lines and discussed the potential of lipid droplets as a prognostic marker in breast cancer. To identify any difference in the lipid droplet-associated biochemistry and to correlate it with different stages of breast cancer, the PCA method was employed. The chemical composition of lipids and proteins, both in the cell line models and in human breast tissue has been analyzed. The paper shows the alterations in lipid metabolism that have been reported in cancer, at both the cellular and tissue levels, and discusses how they contribute to the different aspects of tumourigenesis.

Analysis of breast thermograms using Gabor wavelet anisotropy index.

PubMed

Suganthi, S S; Ramakrishnan, S

2014-09-01

In this study, an attempt is made to distinguish the normal and abnormal tissues in breast thermal images using Gabor wavelet transform. Thermograms having normal, benign and malignant tissues are considered in this study and are obtained from public online database. Segmentation of breast tissues is performed by multiplying raw image and ground truth mask. Left and right breast regions are separated after removing the non-breast regions from the segmented image. Based on the pathological conditions, the separated breast regions are grouped as normal and abnormal tissues. Gabor features such as energy and amplitude in different scales and orientations are extracted. Anisotropy and orientation measures are calculated from the extracted features and analyzed. A distinctive variation is observed among different orientations of the extracted features. It is found that the anisotropy measure is capable of differentiating the structural changes due to varied metabolic conditions. Further, the Gabor features also showed relative variations among different pathological conditions. It appears that these features can be used efficiently to identify normal and abnormal tissues and hence, improve the relevance of breast thermography in early detection of breast cancer and content based image retrieval.

Circular RNA hsa_circ_0001982 Promotes Breast Cancer Cell Carcinogenesis Through Decreasing miR-143.

PubMed

Tang, Yi-Yin; Zhao, Ping; Zou, Tian-Ning; Duan, Jia-Jun; Zhi, Rong; Yang, Si-Yuan; Yang, De-Chun; Wang, Xiao-Li

2017-11-01

Circular RNAs (circRNAs) are a type of noncoding RNAs generated from back-splicing, which have been verified to mediate multiple tumorigenesis. With the development of high-throughput sequencing, massive circRNAs are discovered in tumorous tissue. However, the potential physiological effect of circRNAs in breast cancer is still unknown. The purpose of this study is to investigate the expression profile of circRNA in breast cancer tissue and explore the in-depth regulatory mechanism in breast cancer tumorigenesis. In the present study, we screened the circRNA expression profiles in breast cancer tissue using circRNA microarray analysis. Totally 1705 circRNAs were identified to be significantly aberrant. Among these dysregulated circRNAs, hsa_circ_0001982 was markedly overexpressed in breast cancer tissue and cell lines. Bioinformatics analysis predicted that miR-143 acted as target of hsa_circ_0001982, which was confirmed by Dual-luciferase reporter assay. Loss-of-function and rescue experiments revealed that hsa_circ_0001982 knockdown suppressed breast cancer cell proliferation and invasion and induced apoptosis by targeting miR-143. In summary, our study preliminarily investigates the circRNA expression in breast cancer tissue and explores the role of competing endogenous RNA (ceRNA) mechanism in the progression, providing a novel insight for breast cancer tumorigenesis.

Validation of Monte Carlo simulation of mammography with TLD measurement and depth dose calculation with a detailed breast model

NASA Astrophysics Data System (ADS)

Wang, Wenjing; Qiu, Rui; Ren, Li; Liu, Huan; Wu, Zhen; Li, Chunyan; Li, Junli

2017-09-01

Mean glandular dose (MGD) is not only determined by the compressed breast thickness (CBT) and the glandular content, but also by the distribution of glandular tissues in breast. Depth dose inside the breast in mammography has been widely concerned as glandular dose decreases rapidly with increasing depth. In this study, an experiment using thermo luminescent dosimeters (TLDs) was carried out to validate Monte Carlo simulations of mammography. Percent depth doses (PDDs) at different depth values were measured inside simple breast phantoms of different thicknesses. The experimental values were well consistent with the values calculated by Geant4. Then a detailed breast model with a CBT of 4 cm and a glandular content of 50%, which has been constructed in previous work, was used to study the effects of the distribution of glandular tissues in breast with Geant4. The breast model was reversed in direction of compression to get a reverse model with a different distribution of glandular tissues. Depth dose distributions and glandular tissue dose conversion coefficients were calculated. It revealed that the conversion coefficients were about 10% larger when the breast model was reversed, for glandular tissues in the reverse model are concentrated in the upper part of the model.

Characterization of human breast cancer by scanning acoustic microscopy

NASA Astrophysics Data System (ADS)

Chen, Di; Malyarenko, Eugene; Seviaryn, Fedar; Yuan, Ye; Sherman, Mark; Bandyopadhyay, Sudeshna; Gierach, Gretchen; Greenway, Christopher W.; Maeva, Elena; Strumban, Emil; Duric, Neb; Maev, Roman

2013-03-01

Objectives: The purpose of this study was to characterize human breast cancer tissues by the measurement of microacoustic properties. Methods: We investigated eight breast cancer patients using acoustic microscopy. For each patient, seven blocks of tumor tissue were collected from seven different positions around a tumor mass. Frozen sections (10 micrometer, μm) of human breast cancer tissues without staining and fixation were examined in a scanning acoustic microscope with focused transducers at 80 and 200 MHz. Hematoxylin and Eosin (H and E) stained sections from the same frozen breast cancer tissues were imaged by optical microscopy for comparison. Results: The results of acoustic imaging showed that acoustic attenuation and sound speed in cancer cell-rich tissue regions were significantly decreased compared with the surrounding tissue regions, where most components are normal cells/tissues, such as fibroblasts, connective tissue and lymphocytes. Our observation also showed that the ultrasonic properties were influenced by arrangements of cells and tissue patterns. Conclusions: Our data demonstrate that attenuation and sound speed imaging can provide biomechanical information of the tumor and normal tissues. The results also demonstrate the potential of acoustic microscopy as an auxiliary method for operative detection and localization of cancer affected regions.

[Immunoexpression of c-erbB-2 in intraductal proliferative lesions of the female breast].

PubMed

Oliveira, Agliberto Barbosa de; De Luca, Laurival Antônio; Carvalho, Grigna Teixeira; Arias, Victor Eduardo Arua; Carvalho, Lídia Raquel de; Assunção, Maria do Carmo

2004-01-01

Genetic modifications are related to genesis and development of cancer. Neoplasias in various organs express the c-erbB-2 oncogene. In intraductal proliferations of the breast it has been assessed as a risk factor for subsequent development of carcinoma. The c-erbB-2 immunoexpression in intraductal epithelial proliferations and the relationship with histopathological characteristics of ductal carcinoma in situ (DCIS) were evaluated. File material from 88 women, which were tissue samples formalin-fixed, paraffin-embedded blocks, was used. Of these 51 presented with DCIS and 37 with ductal hyperplasia without atypia. Ages of the women ranged from 35 to 76 years. All cases were reviewed and nuclear grade, presence of necrosis, preponderance of histological subtype and its extension were verified. Specimens were obtained for the c-erB-2 immunohistochemical study of 84 of the women in question. No expression of the oncogene was verified in the hyperplasias without atypias and in tissues adjacent to all tissue samples. Expression of c-erbB-2 was verified in 9 (19.1%) of the DCIS (p = 0.0001). Immunoexpression was not related to the extension of the lesions. The c-erbB-2 immunoexpression in DCIS was correlated to the histological subtype (p = 0.019), necrosis (p = 0.0066), nuclear grade (p = 0.0084) and Van Nuys Classification (p = 0.039). Expression of c-erbB-2 was significant in proliferative lesions with risk (DCIS) and was correlated to histopathological characteristics: high nuclear grade, presence of necrosis and comedy subtype. There was no expression in the hyperplasias without atypias and adjacent tissues.

Optical diagnostic of breast cancer using Raman, polarimetric and fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Anwar, Shahzad; Firdous, Shamaraz; Rehman, Aziz-ul; Nawaz, Muhammed

2015-04-01

We presented the optical diagnostic of normal and cancerous human breast tissues using Raman, polarimetric and fluorescence spectroscopic techniques. Breast cancer is the second leading cause of cancer death among women worldwide. Optical diagnostics of cancer offered early intervention and the greatest chance of cure. Spectroscopic data were collected from freshly excised surgical specimens of normal tissues with Raman bands at 800, 1171 and 1530 cm-1 arising mainly by lipids, nucleic acids, proteins, carbohydrates and amino acids. For breast cancer, Raman bands are observed at 1070, 1211, 1495, 1583 and 1650 cm-1. Results demonstrate that the spectra of normal tissue are dominated by lipids and amino acids. Polarization decomposition of the Mueller matrix and confocal microscopic fluorescence provides detailed description of cancerous tissue and distinguishes between the normal and malignant one. Based on these findings, we successfully differentiate normal and malignant breast tissues at an early stage of disease. There is a need to develop a new tool for noninvasive, real-time diagnosis of tissue abnormalities and a test procedure for detecting breast cancer at an early stage.

Raman imaging at biological interfaces: applications in breast cancer diagnosis

PubMed Central

2013-01-01

Background One of the most important areas of Raman medical diagnostics is identification and characterization of cancerous and noncancerous tissues. The methods based on Raman scattering has shown significant potential for probing human breast tissue to provide valuable information for early diagnosis of breast cancer. A vibrational fingerprint from the biological tissue provides information which can be used to identify, characterize and discriminate structures in breast tissue, both in the normal and cancerous environment. Results The paper reviews recent progress in understanding structure and interactions at biological interfaces of the human tissue by using confocal Raman imaging and IR spectroscopy. The important differences between the noncancerous and cancerous human breast tissues were found in regions characteristic for vibrations of carotenoids, fatty acids, proteins, and interfacial water. Particular attention was paid to the role played by unsaturated fatty acids and their derivatives as well as carotenoids and interfacial water. Conclusions We demonstrate that Raman imaging has reached a clinically relevant level in regard to breast cancer diagnosis applications. The results presented in the paper may have serious implications on understanding mechanisms of interactions in living cells under realistically crowded conditions of biological tissue. PMID:23705882

Atypia and DNA methylation in nipple duct lavage in relation to predicted breast cancer risk.

PubMed

Euhus, David M; Bu, Dawei; Ashfaq, Raheela; Xie, Xian-Jin; Bian, Aihua; Leitch, A Marilyn; Lewis, Cheryl M

2007-09-01

Tumor suppressor gene (TSG) methylation is identified more frequently in random periareolar fine needle aspiration samples from women at high risk for breast cancer than women at lower risk. It is not known whether TSG methylation or atypia in nipple duct lavage (NDL) samples is related to predicted breast cancer risk. 514 NDL samples obtained from 150 women selected to represent a wide range of breast cancer risk were evaluated cytologically and by quantitative multiplex methylation-specific PCR for methylation of cyclin D2, APC, HIN1, RASSF1A, and RAR-beta2. Based on methylation patterns and cytology, NDL retrieved cancer cells from only 9% of breasts ipsilateral to a breast cancer. Methylation of >/=2 genes correlated with marked atypia by univariate analysis, but not multivariate analysis, that adjusted for sample cellularity and risk group classification. Both marked atypia and TSG methylation independently predicted abundant cellularity in multivariate analyses. Discrimination between Gail lower-risk ducts and Gail high-risk ducts was similar for marked atypia [odds ratio (OR), 3.48; P = 0.06] and measures of TSG methylation (OR, 3.51; P = 0.03). However, marked atypia provided better discrimination between Gail lower-risk ducts and ducts contralateral to a breast cancer (OR, 6.91; P = 0.003, compared with methylation OR, 4.21; P = 0.02). TSG methylation in NDL samples does not predict marked atypia after correcting for sample cellularity and risk group classification. Rather, both methylation and marked atypia are independently associated with highly cellular samples, Gail model risk classifications, and a personal history of breast cancer. This suggests the existence of related, but independent, pathogenic pathways in breast epithelium.

Time-resolved fluorescence (TRF) and diffuse reflectance spectroscopy (DRS) for margin analysis in breast cancer.

PubMed

Shalaby, Nourhan; Al-Ebraheem, Alia; Le, Du; Cornacchi, Sylvie; Fang, Qiyin; Farrell, Thomas; Lovrics, Peter; Gohla, Gabriela; Reid, Susan; Hodgson, Nicole; Farquharson, Michael

2018-03-01

One of the major problems in breast cancer surgery is defining surgical margins and establishing complete tumor excision within a single surgical procedure. The goal of this work is to establish instrumentation that can differentiate between tumor and normal breast tissue with the potential to be implemented in vivo during a surgical procedure. A time-resolved fluorescence and reflectance spectroscopy (tr-FRS) system is used to measure fluorescence intensity and lifetime as well as collect diffuse reflectance (DR) of breast tissue, which can subsequently be used to extract optical properties (absorption and reduced scatter coefficient) of the tissue. The tr-FRS data obtained from patients with Invasive Ductal Carcinoma (IDC) whom have undergone lumpectomy and mastectomy surgeries is presented. A preliminary study was conducted to determine the validity of using banked pre-frozen breast tissue samples to study the fluorescence response and optical properties. Once the validity was established, the tr-FRS system was used on a data-set of 40 pre-frozen matched pair cases to differentiate between tumor and normal breast tissue. All measurements have been conducted on excised normal and tumor breast samples post surgery. Our results showed the process of freezing and thawing did not cause any significant differences between fresh and pre-frozen normal or tumor breast tissue. The tr-FRS optical data obtained from 40 banked matched pairs showed significant differences between normal and tumor breast tissue. The work detailed in the main study showed the tr-FRS system has the potential to differentiate malignant from normal breast tissue in women undergoing surgery for known invasive ductal carcinoma. With further work, this successful outcome may result in the development of an accurate intraoperative real-time margin assessment system. Lasers Surg. Med. 50:236-245, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Ectopic Male Breast Cancer: A Case Report

PubMed Central

Samanta, Dipti Rani; Upadhyay, Ashish; Sheet, Saikat; Senapati, Surendra Nath

2015-01-01

Carcinoma of male breast constitutes 1% of total breast malignancy. Carcinoma arising from ectopic breast tissue in male is an extremely rare entity and can be misdiagnosed. Ectopic breast tissue may be supernumerary or aberrant one. Despite morphologic difference, ectopic breast tissue presents characteristics analogous to orthoptic breast in terms of functional and pathologic degeneration. Most of the ectopic breast tissue occurs in thoracic or abdominal portion of milk line. If found in a location outside the milk line, it proves a diagnostic dilemma. We are reporting a case of 60-year-old male who presented with a fixed mass of size 10cm×8cm, in right chest wall infraclavicular area of 6 months duration. Histopathology of the mass revealed invasive duct carcinoma. He had no evidence of malignant or occult primary lesion in the bilateral mammary glands. Due to the paucity of the literature, incidence of ectopic male breast cancer and its management is not well understood. There is high probability of misdiagnosis of this disease. To the best of our knowledge this is the first described case of ectopic male breast cancer in the chest wall, not along the milk line, which is being reported here for documentation. PMID:26436033

A Proposal to Unify the Classification of Breast and Prostate Cancers Based on the Anatomic Site of Cancer Origin and on Long-term Patient Outcome

PubMed Central

Tabár, László; Dean, Peter B.; Yen, Amy M.-F.; Tarján, Miklós; Chiu, Sherry Y.-H.; Chen, Sam L.-S.; Fann, Jean C.-Y.; Chen, Tony H.-H.

2014-01-01

The similarity between the structure and function of the breast and prostate has been known for a long time, but there are serious discrepancies in the terminology describing breast and prostate cancers. The use of the large, thick-section (3D) histology technique for both organs exposes the irrationality of the breast cancer terminology. Pathologists with expertise in diagnosing prostate cancer take the anatomic site of cancer origin into account when using the terms AAP (acinar adenocarcinoma of the prostate) and DAP (ductal adenocarcinoma of the prostate) to distinguish between the prostate cancers originating primarily from the fluid-producing acinar portion of the organ (AAP) and the tumors originating either purely from the larger ducts (DAP) or from both the acini and the main ducts combined (DAP and AAP). Long-term patient outcome is closely correlated with the terminology, because patients with DAP have a significantly poorer prognosis than patients with AAP. The current breast cancer terminology could be improved by modeling it after the method of classifying prostate cancer to reflect the anatomic site of breast cancer origin and the patient outcome. The long-term survival curves of our consecutive breast cancer cases collected since 1977 clearly show that the non-palpable, screen-detected breast cancers originating from the milk-producing acini have excellent prognosis, irrespective of their histologic malignancy grade or biomarkers. Correspondingly, the breast cancer subtypes of truly ductal origin have a significantly poorer outcome, despite recent improvements in diagnosis and therapy. The mammographic appearance of breast cancers reflects the underlying tissue structure. Addition of these “mammographic tumor features” to the currently used histologic phenotypes makes it possible to distinguish the breast cancer cases of ductal origin with a poor outcome, termed DAB (ductal adenocarcinoma of the breast), from the more easily managed breast cancers of acinar origin, termed AAB (acinar adenocarcinoma of the breast), which have a significantly better outcome. This simple and easily communicable terminology could lead to better communication between the diagnostic and therapeutic team members and result in more rational treatment planning for the benefit of their patients. PMID:24653647

Relationship between reflection spectra of breast adipose tissue with histologic grade

NASA Astrophysics Data System (ADS)

Muñoz Morales, Aarón; Vázquez Y Montiel, Sergio; Reigosa, Aldo

2011-08-01

Optical spectroscopy allows the characterization, recognition and differentiation of subcutaneous tissues healthy and no-healthy, to facilitate the diagnosis or early detection for breast cancer are studied white adipose tissue by the subcutaneous region with the help of the diffuse reflection spectroscopy in the visible areas (400 to 700 nm) of electromagnetic spectrum for them using a spectrometer portable of integrating sphere, Hunter lab Model Mini-Scan. The problem to be solved for cancer detection by optical techniques is to find the solution to the inverse problem of scattering of radiation in tissue where it is necessary to solve the equation of energy transfer. us through the trigonometric interpolation and by the data adjustment by least squares using Fourier series expansion to parameterize the spectral response curves of each sample of breast adipose tissue then correlated with histological grades established by the optical biopsy for each one of the samples, allowing use this technique to the study of anomalies in White Adipose Tissue Breast, changes are evident in the spectral response for Breast Adipose Tissue carcinogens with respect to healthy tissues and for the different histological grades.

Characterization and Clinical Implication of Th1/Th2/Th17 Cytokines Produced from Three-Dimensionally Cultured Tumor Tissues Resected from Breast Cancer Patients

PubMed Central

Kiyomi, Anna; Makita, Masujiro; Ozeki, Tomoko; Li, Na; Satomura, Aiko; Tanaka, Sachiko; Onda, Kenji; Sugiyama, Kentaro; Iwase, Takuji; Hirano, Toshihiko

2015-01-01

OBJECTIVES: Several cytokines secreted from breast cancer tissues are suggested to be related to disease prognosis. We examined Th1/Th2/Th17 cytokines produced from three-dimensionally cultured breast cancer tissues and related them with patient clinical profiles. METHODS: 21 tumor tissues and 9 normal tissues surgically resected from breast cancer patients were cultured in thermoreversible gelatin polymer–containing medium. Tissue growth and Th1/Th2/Th17 cytokine concentrations in the culture medium were analyzed and were related with hormone receptor expressions and patient clinical profiles. RESULTS: IL-6 and IL-10 were expressed highly in culture medium of both cancer and normal tissues. However, IFN-γ, TNF-α, IL-2, and IL-17A were not detected in the supernatant of the three-dimensionally cultured normal mammary gland and are seemed to be specific to breast cancer tissues. The growth abilities of hormone receptor–negative cancer tissues were significantly higher than those of receptor-positive tissues (P = 0.0383). Cancer tissues of stage ≥ IIB patients expressed significantly higher TNF-α levels as compared with those of patients with stage < IIB (P = 0.0096). CONCLUSIONS: The tumor tissues resected from breast cancer patients can grow in the three-dimensional thermoreversible gelatin polymer culture system and produce Th1/Th2/Th17 cytokines. Hormone receptor–positive cancer tissues showed less growth ability. TNF-α is suggested to be a biomarker for the cancer stage. PMID:26310378

Breast lump removal - series (image)

MedlinePlus

... be a cyst filled with fluid or a solid mass of tissue. A sample of the breast tissue (biopsy) must be made to determine whether malignant (cancerous) cells are present. Almost two-thirds of all breast ...

Raman microspectroscopy of Hematoporphyrins. Imaging of the noncancerous and the cancerous human breast tissues with photosensitizers

NASA Astrophysics Data System (ADS)

Brozek-Pluska, B.; Kopec, M.

2016-12-01

Raman microspectroscopy combined with fluorescence were used to study the distribution of Hematoporphyrin (Hp) in noncancerous and cancerous breast tissues. The results demonstrate the ability of Raman spectroscopy to distinguish between noncancerous and cancerous human breast tissue and to identify differences in the distribution and photodegradation of Hematoporphyrin, which is a photosensitizer in photodynamic therapy (PDT), photodynamic diagnosis (PDD) and photoimmunotherapy (PIT) of cancer. Presented results show that Hematoporphyrin level in the noncancerous breast tissue is lower compared to the cancerous one. We have proved also that the Raman intensity of lipids and proteins doesn't change dramatically after laser light irradiation, which indicates that the PDT treatment destroys preferably cancer cells, in which the photosensitizer is accumulated. The specific subcellular localization of photosensitizer for breast tissues samples soaked with Hematoporphyrin was not observed.

Microgravity

NASA Image and Video Library

1998-10-10

Dr. Robert Richmond extracts breast cell tissue from one of two liquid nitrogen dewars. NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cells (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunourous tissues.

Treatment of a supernumerary large breast with medial pedicle reduction mammaplasty.

PubMed

Cinpolat, Anı; Bektas, Gamze; Seyhan, Tamer; Ozad, Ulvan; Coskunfirat, O Koray

2013-08-01

Accessory breast tissues including nipples, areolas, and glandular tissue may develop on the chest in addition to two normal breasts. An accessory breast with a complete ductal system, areola, and nipple is termed a "supernumerary breast." Supernumerary nipples are fairly common, but complete supernumerary breasts are rare. This report describes an 18-year-old woman who presented with a complete supernumerary breast including a nipple-areola complex located on the upper outer quadrant of her left breast and causing severe breast asymmetry. She was referred to the authors for aesthetic reasons. Unilateral reduction mammaplasty was performed to remove the supernumerary breast and correct the breast asymmetry. The medial pedicle Wise technique was used for en bloc resection of the ectopic breast, including the nipple-areola complex together with the upper outer breast quadrant. The woman's postoperative course was uneventful. At 8 months after surgery, she was very satisfied with the results. Ectopic breast tissue can be treated by a variety of methods such as liposuction or excision. However, breast deformation because of a complete supernumerary breast is very rare, and research on the treatment of such patients is lacking. No reports describing surgical treatment for this condition were identified in the literature. The authors suggest that unilateral breast reduction is the most appropriate treatment, allowing excision of the accessory tissues, with the best possible cosmetic outcome. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

MR elastography of the breast:preliminary clinical results.

PubMed

Lorenzen, J; Sinkus, R; Lorenzen, M; Dargatz, M; Leussler, C; Röschmann, P; Adam, G

2002-07-01

Imaging of breast tumors and various breast tissues using magnetic resonance (MR) elastography (MRE) to explore the potential of elasticity as a new parameter for the diagnosis of breast lesions. Low-frequency mechanical waves are transmitted into breast tissue by means of an oscillator. The local characteristics of the mechanical wave are determined by the underlying elastic properties of the tissue. Theses waves can be displayed by means of a motion-sensitive spin-echo MR sequence within the phase of the MR image. Elasticity reconstruction is performed on the basis of 8 "snapshots" of each wave within the three spatial directions. We performed in-vivo measurements in 15 female patients with malignant tumors of the breast, 5 patients with benign breast tumors, and 15 healthy volunteers. Malignant invasive breast tumors documented the highest values of elasticity with a median of 15.9 kPa and a wide range of stiffnesses between 8 and 28 kPa. In contrast, benign breast lesions represented low values of elasticity, which were significantly different from malignant breast tumors (median elasticity: 7.0 kPa; p = 0.0012). This was comparable to the stiffest tissue areas in healthy volunteers (median elasticity 7.0 kPa), whereas breast parenchyma (median: 2.5 kPa) and fatty breast tissue (median: 1.7 kPa) showed the lowest values of elasticity. Two invasive ductal carcinomas had elasticity values of 8 kPa and two stiff parenchyma areas in healthy volunteers had elasticities of 13 and 15 kPa. These lesions could not be differentiated by their elasticity. We conclude that MRE is a promising new imaging modality with the capability to assess the viscoelastic properties of breast tumors and the surrounding tissues. However, from our preliminary results in a small number of patients it is obvious that there is an overlap in the elasticity ranges of soft malignant tumors and stiff benign lesions.

Classification of breast cancer cytological specimen using convolutional neural network

NASA Astrophysics Data System (ADS)

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.

Breast Cancer Research at NASA

NASA Technical Reports Server (NTRS)

1998-01-01

Dr. Harry Mahtani analyzes the gas content of nutrient media from Bioreactor used in research on human breast cancer. NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cells (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunourous tissues.

Digital Mammography and Digital Breast Tomosynthesis.

PubMed

Moseley, Tanya W

2016-06-01

Breast imaging technology has advanced significantly from the 1930s until the present. American women have a 1 in 8 chance of developing breast cancer. Mammography has been proven in multiple clinical trials to reduce breast cancer mortality. Although a mainstay of breast imaging and improved from film-screen mammography, digital mammography is not a perfect examination. Overlapping obscuring breast tissue limits mammographic interpretation. Breast digital tomosynthesis reduces and/or eliminates overlapping obscuring breast tissue. Although there are some disadvantages with digital breast tomosynthesis, this relatively lost-cost technology may be used effectively in the screening and diagnostic settings.

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

PubMed

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.

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

PubMed

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.

Breast Cancer Research at NASA

NASA Technical Reports Server (NTRS)

1998-01-01

Isolation of human mammary epithelial cells (HMEC) from breast cancer susceptible tissue. Same long-term growth human mammary epithelial cells (HMEC), but after 3 weeks in concinuous culture. Note attempts to reform duct elements, but this time in two dimensions in a dish rather that in three demensions in tissue. NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cell (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunorous tissue. Credit: Dr. Robert Tichmond, NASA/Marshall Space Flight Center (MSFC).

Symmetry-based detection and diagnosis of DCIS in breast MRI

NASA Astrophysics Data System (ADS)

Srikantha, Abhilash; Harz, Markus T.; Newstead, Gillian; Wang, Lei; Platel, Bram; Hegenscheid, Katrin; Mann, Ritse M.; Hahn, Horst K.; Peitgen, Heinz-Otto

2013-02-01

The delineation and diagnosis of non-mass-like lesions, most notably DCIS (ductal carcinoma in situ), is among the most challenging tasks in breast MRI reading. Even for human observers, DCIS is not always easy to diferentiate from patterns of active parenchymal enhancement or from benign alterations of breast tissue. In this light, it is no surprise that CADe/CADx approaches often completely fail to classify DCIS. Of the several approaches that have tried to devise such computer aid, none achieve performances similar to mass detection and classification in terms of sensitivity and specificity. In our contribution, we show a novel approach to combine a newly proposed metric of anatomical breast symmetry calculated on subtraction images of dynamic contrast-enhanced (DCE) breast MRI, descriptive kinetic parameters, and lesion candidate morphology to achieve performances comparable to computer-aided methods used for masses. We have based the development of the method on DCE MRI data of 18 DCIS cases with hand-annotated lesions, complemented by DCE-MRI data of nine normal cases. We propose a novel metric to quantify the symmetry of contralateral breasts and derive a strong indicator for potentially malignant changes from this metric. Also, we propose a novel metric for the orientation of a finding towards a fix point (the nipple). Our combined scheme then achieves a sensitivity of 89% with a specificity of 78%, matching CAD results for breast MRI on masses. The processing pipeline is intended to run on a CAD server, hence we designed all processing to be automated and free of per-case parameters. We expect that the detection results of our proposed non-mass aimed algorithm will complement other CAD algorithms, or ideally be joined with them in a voting scheme.

[Surgical treatment of gynecomastia: an algorithm].

PubMed

Wolter, A; Scholz, T; Diedrichson, J; Liebau, J

2013-04-01

Gynecomastia is a persistent benign uni- or bilateral enlargement of the male breast ranging from small to excessive findings with marked skin redundancy. In this paper we introduce an algorithm to facilitate the selection of the appropriate surgical technique according to the presented morphological aspects. The records of 118 patients (217 breasts) with gynecomastia from 01/2009 to 08/2012 were retrospectively reviewed. The authors conducted three different surgical techniques depending on four severity grades. The outcome parameters complication rate, patient satisfaction with the aesthetic result, nipple sensitivity and the need to re-operate were observed and related to the employed technique. In 167 (77%) breasts with moderate breast enlargement without skin redundancy (Grade I-IIa by Simon's classification) a subcutaneous semicircular periareolar mastectomy was performed in combination with water-jet assisted liposuction. In 40 (18%) breasts with skin redundancy (Grade IIb) a circumferential mastopexy was performed additionally. An inferior pedicled mammaplasty was used in 10 (5%) severe cases (Grade III). Complication rate was 4.1%. Surgical corrections were necessary in 17 breasts (7.8%). The patient survey revealed a high satisfaction level: 88% of the patients rated the aesthetic results as "very good" or "good", nipple sensitivity was rated as "very good" or "good" by 83%. Surgical treatment of gynecomastia should ensure minimal scarring while respecting the aesthetic unit. The selection of the appropriate surgical method depends on the severity grade, the presence of skin redundancy and the volume of the male breast glandular tissue. The presented algorithm rarely leads to complications, is simple to perform and shows a high satisfaction rate and a preservation of the nipple sensitivity. © Georg Thieme Verlag KG Stuttgart · New York.

Assessment of two mammographic density related features in predicting near-term breast cancer risk

NASA Astrophysics Data System (ADS)

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

2012-02-01

In order to establish a personalized breast cancer screening program, it is important to develop risk models that have high discriminatory power in predicting the likelihood of a woman developing an imaging detectable breast cancer in near-term (e.g., <3 years after a negative examination in question). In epidemiology-based breast cancer risk models, mammographic density is considered the second highest breast cancer risk factor (second to woman's age). In this study we explored a new feature, namely bilateral mammographic density asymmetry, and investigated the feasibility of predicting near-term screening outcome. The database consisted of 343 negative examinations, of which 187 depicted cancers that were detected during the subsequent screening examination and 155 that remained negative. We computed the average pixel value of the segmented breast areas depicted on each cranio-caudal view of the initial negative examinations. We then computed the mean and difference mammographic density for paired bilateral images. Using woman's age, subjectively rated density (BIRADS), and computed mammographic density related features we compared classification performance in estimating the likelihood of detecting cancer during the subsequent examination using areas under the ROC curves (AUC). The AUCs were 0.63+/-0.03, 0.54+/-0.04, 0.57+/-0.03, 0.68+/-0.03 when using woman's age, BIRADS rating, computed mean density and difference in computed bilateral mammographic density, respectively. Performance increased to 0.62+/-0.03 and 0.72+/-0.03 when we fused mean and difference in density with woman's age. The results suggest that, in this study, bilateral mammographic tissue density is a significantly stronger (p<0.01) risk indicator than both woman's age and mean breast density.

Molecular classification and molecular forecasting of breast cancer: ready for clinical application?

PubMed

Brenton, James D; Carey, Lisa A; Ahmed, Ahmed Ashour; Caldas, Carlos

2005-10-10

Profiling breast cancer with expression arrays has become common, and it has been suggested that the results from early studies will lead to understanding of the molecular differences between clinical cases and allow individualization of care. We critically review two main applications of expression profiling; studies unraveling novel breast cancer classifications and those that aim to identify novel markers for prediction of clinical outcome. Breast cancer may now be subclassified into luminal, basal, and HER2 subtypes with distinct differences in prognosis and response to therapy. However, profiling studies to identify predictive markers have suffered from methodologic problems that prevent general application of their results. Future work will need to reanalyze existing microarray data sets to identify more representative sets of candidate genes for use as prognostic signatures and will need to take into account the new knowledge of molecular subtypes of breast cancer when assessing predictive effects.

Signal enhancement ratio (SER) quantified from breast DCE-MRI and breast cancer risk

NASA Astrophysics Data System (ADS)

Wu, Shandong; Kurland, Brenda F.; Berg, Wendie A.; Zuley, Margarita L.; Jankowitz, Rachel C.; Sumkin, Jules; Gur, David

2015-03-01

Breast magnetic resonance imaging (MRI) is recommended as an adjunct to mammography for women who are considered at elevated risk of developing breast cancer. As a key component of breast MRI, dynamic contrast-enhanced MRI (DCE-MRI) uses a contrast agent to provide high intensity contrast between breast tissues, making it sensitive to tissue composition and vascularity. Breast DCE-MRI characterizes certain physiologic properties of breast tissue that are potentially related to breast cancer risk. Studies have shown that increased background parenchymal enhancement (BPE), which is the contrast enhancement occurring in normal cancer-unaffected breast tissues in post-contrast sequences, predicts increased breast cancer risk. Signal enhancement ratio (SER) computed from pre-contrast and post-contrast sequences in DCE-MRI measures change in signal intensity due to contrast uptake over time and is a measure of contrast enhancement kinetics. SER quantified in breast tumor has been shown potential as a biomarker for characterizing tumor response to treatments. In this work we investigated the relationship between quantitative measures of SER and breast cancer risk. A pilot retrospective case-control study was performed using a cohort of 102 women, consisting of 51 women who had diagnosed with unilateral breast cancer and 51 matched controls (by age and MRI date) with a unilateral biopsy-proven benign lesion. SER was quantified using fully-automated computerized algorithms and three SER-derived quantitative volume measures were compared between the cancer cases and controls using logistic regression analysis. Our preliminary results showed that SER is associated with breast cancer risk, after adjustment for the Breast Imaging Reporting and Data System (BI-RADS)-based mammographic breast density measures. This pilot study indicated that SER has potential for use as a risk factor for breast cancer risk assessment in women at elevated risk of developing breast cancer.

Backscattering analysis of high frequency ultrasonic imaging for ultrasound-guided breast biopsy

NASA Astrophysics Data System (ADS)

Cummins, Thomas; Akiyama, Takahiro; Lee, Changyang; Martin, Sue E.; Shung, K. Kirk

2017-03-01

A new ultrasound-guided breast biopsy technique is proposed. The technique utilizes conventional ultrasound guidance coupled with a high frequency embedded ultrasound array located within the biopsy needle to improve the accuracy in breast cancer diagnosis.1 The array within the needle is intended to be used to detect micro- calcifications indicative of early breast cancers such as ductal carcinoma in situ (DCIS). Backscattering analysis has the potential to characterize tissues to improve localization of lesions. This paper describes initial results of the application of backscattering analysis of breast biopsy tissue specimens and shows the usefulness of high frequency ultrasound for the new biopsy related technique. Ultrasound echoes of ex-vivo breast biopsy tissue specimens were acquired by using a single-element transducer with a bandwidth from 41 MHz to 88 MHz utilizing a UBM methodology, and the backscattering coefficients were calculated. These values as well as B-mode image data were mapped in 2D and matched with each pathology image for the identification of tissue type for the comparison to the pathology images corresponding to each plane. Microcalcifications were significantly distinguished from normal tissue. Adenocarcinoma was also successfully differentiated from adipose tissue. These results indicate that backscattering analysis is able to quantitatively distinguish tissues into normal and abnormal, which should help radiologists locate abnormal areas during the proposed ultrasound-guided breast biopsy with high frequency ultrasound.

[Primary breast lymphoma: a clinical, pathological and immunophenotypic study of eight cases].

PubMed

Ying, Jianming; Feng, Xiaoli; Liu, Xiuyun; Xie, Yongqiang; Sun, Yuntian

2002-12-01

To study the clinical, pathological and immunophenotypic characteristics of the primary breast lymphoma (PBL). Analyses of clinical history, preoperative findings, histological and immunohistochemical features of eight patients with PBL were performed. Malignant lymphoma was difficult to diagnose preoperatively. All patients were women. The age range was from 34 approximately 65 years (mean 46.4 years). The right breast was involved initially in three patients, the left in four. One patient presented bilateral involvement. Seven patients were assessed at stage IE, one with ipsolateral axillary lymph nodes involvement at stage IIE. According to the WHO classification, five patients were diagnosed as diffuse large B-cell lymphoma (4/5 centroblast, 1/5 immunoblast); the other three patients as MALT lymphoma, all with lymphoepithelial lesions. The paraffin-embedded tissues of all cases showed immunoreactivity for B-cell markers CD20, CD45RA. CD5 and CD10 were negative in all cases. Follow-up data were obtained in six patients, none recurred or died within 8 to 108 months after diagnosis. This study indicates that most PBL are diffuse large B-cell lymphoma and MALT lymphoma and have a better prognosis after comprehensive therapy.

Assessment of three different software systems in the evaluation of dynamic MRI of the breast.

PubMed

Kurz, K D; Steinhaus, D; Klar, V; Cohnen, M; Wittsack, H J; Saleh, A; Mödder, U; Blondin, D

2009-02-01

The aim was to compare the diagnostic performance and handling of dynamic contrast-enhanced MRI of the breast with two commercial software solutions ("CADstream" and "3TP") and one self-developed software system ("Mammatool"). Identical data sets of dynamic breast MRI from 21 patients were evaluated retrospectively with all three software systems. The exams were classified according to the BI-RADS classification. The number of lesions in the parametric mapping was compared to histology or follow-up of more than 2 years. In addition, 25 quality criteria were judged by 3 independent investigators with a score from 0 to 5. Statistical analysis was performed to document the quality ranking of the different software systems. There were 9 invasive carcinomas, one pure DCIS, one papilloma, one radial scar, three histologically proven changes due to mastopathy, one adenosis and two fibroadenomas. Additionally two patients with enhancing parenchyma followed with MRI for more than 3 years and one scar after breast conserving therapy were included. All malignant lesions were classified as BI-RADS 4 or 5 using all software systems and showed significant enhancement in the parametric mapping. "CADstream" showed the best score on subjective quality criteria. "3TP" showed the lowest number of false-positive results. "Mammatool" produced the lowest number of benign tissues indicated with parametric overlay. All three software programs tested were adequate for sensitive and efficient assessment of dynamic MRI of the breast. Improvements in specificity may be achievable.

Expression of phosphodiesterase 6 (PDE6) in human breast cancer cells.

PubMed

Dong, Hongli; Claffey, Kevin P; Brocke, Stefan; Epstein, Paul M

2013-01-01

Considerable epidemiological evidence demonstrates a positive association between artificial light at night (LAN) levels and incidence rates of breast cancer, suggesting that exposure to LAN is a risk factor for breast cancer. There is a 30-50% higher risk of breast cancer in the highest LAN exposed countries compared to the lowest LAN countries, and studies showing higher incidence of breast cancer among shift workers exposed to more LAN have led the International Agency for Research on Cancer to classify shift work as a probable human carcinogen. Nevertheless, the means by which light can affect breast cancer is still unknown. In this study we examined established human breast cancer cell lines and patients' primary breast cancer tissues for expression of genetic components of phosphodiesterase 6 (PDE6), a cGMP-specific PDE involved in transduction of the light signal, and previously thought to be selectively expressed in photoreceptors. By microarray analysis we find highly significant expression of mRNA for the PDE6B, PDE6C, and PDE6D genes in both the cell lines and patients' tissues, minimal expression of PDE6A and PDE6G and no expression of PDE6H. Using antibody specific for PDE6β, we find expression of PDE6B protein in a wide range of patients' tissues by immunohistochemistry, and in MCF-7 breast cancer cells by immunofluorescence and Western blot analysis. Considerable expression of key circadian genes, PERIOD 2, CLOCK, TIMELESS, CRYPTOCHROME 1, and CRYPTOCHROME 2 was also seen in all breast cancer cell lines and all patients' breast cancer tissues. These studies indicate that genes for PDE6 and control of circadian rhythm are expressed in human breast cancer cells and tissues and may play a role in transducing the effects of light on breast cancer.

Application of Raman Spectroscopy and Infrared Spectroscopy in the Identification of Breast Cancer.

PubMed

Depciuch, Joanna; Kaznowska, Ewa; Zawlik, Izabela; Wojnarowska, Renata; Cholewa, Marian; Heraud, Philip; Cebulski, Józef

2016-02-01

Raman spectroscopy and infrared (IR) spectroscopy are both techniques that allow for the investigation of vibrating chemical particles. These techniques provide information not only about chemical particles through the identification of functional groups and spectral analysis of so-called "fingerprints", these methods allow for the qualitative and quantitative analyses of chemical substances in the sample. Both of these spectral techniques are frequently being used in biology and medicine in diagnosing illnesses and monitoring methods of therapy. The type of breast cancer found in woman is often a malignant tumor, causing 1.38 million new cases of breast cancer and 458 000 deaths in the world in 2013. The most important risk factors for breast cancer development are: sex, age, family history, specific benign breast conditions in the breast, ionizing radiation, and lifestyle. The main purpose of breast cancer screening tests is to establish early diagnostics and to apply proper treatment. Diagnoses of breast cancer are based on: (1) physical techniques (e.g., ultrasonography, mammography, elastography, magnetic resonance, positron emission tomography [PET]); (2) histopathological techniques; (3) biological techniques; and (4) optical techniques (e.g., photo acoustic imaging, fluorescence tomography). However, none of these techniques provides unique or especially revealing answers. The aim of our study is comparative spectroscopic measurements on patients with the following: normal non-cancerous breast tissue; breast cancer tissues before chemotherapy; breast cancer tissues after chemotherapy; and normal breast tissues received around the cancerous breast region. Spectra collected from breast cancer patients shows changes in amounts of carotenoids and fats. We also observed changes in carbohydrate and protein levels (e.g., lack of amino acids, changes in the concentration of amino acids, structural changes) in comparison with normal breast tissues. This fact verifies that Raman spectroscopy and IR spectroscopy are very useful diagnostic tools that will shed new light in understanding the etiology of breast cancer. © The Author(s) 2016.

Characterizing viscoelastic properties of breast cancer tissue in a mouse model using indentation.

PubMed

Qiu, Suhao; Zhao, Xuefeng; Chen, Jiayao; Zeng, Jianfeng; Chen, Shuangqing; Chen, Lei; Meng, You; Liu, Biao; Shan, Hong; Gao, Mingyuan; Feng, Yuan

2018-03-01

Breast cancer is one of the leading cancer forms affecting females worldwide. Characterizing the mechanical properties of breast cancer tissue is important for diagnosis and uncovering the mechanobiology mechanism. Although most of the studies were based on human cancer tissue, an animal model is still describable for preclinical analysis. Using a custom-build indentation device, we measured the viscoelastic properties of breast cancer tissue from 4T1 and SKBR3 cell lines. A total of 7 samples were tested for each cancer tissue using a mouse model. We observed that a viscoelastic model with 2-term Prony series could best describe the ramp and stress relaxation of the tissue. For long-term responses, the SKBR3 tissues were stiffer in the strain levels of 4-10%, while no significant differences were found for the instantaneous elastic modulus. We also found tissues from both cell lines appeared to be strain-independent for the instantaneous elastic modulus and for the long-term elastic modulus in the strain level of 4-10%. In addition, by inspecting the cellular morphological structure of the two tissues, we found that SKBR3 tissues had a larger volume ratio of nuclei and a smaller volume ratio of extracellular matrix (ECM). Compared with prior cellular mechanics studies, our results indicated that ECM could contribute to the stiffening the tissue-level behavior. The viscoelastic characterization of the breast cancer tissue contributed to the scarce animal model data and provided support for the linear viscoelastic model used for in vivo elastography studies. Results also supplied helpful information for modeling of the breast cancer tissue in the tissue and cellular levels. Copyright © 2018 Elsevier Ltd. All rights reserved.

High-resolution breast tomography at high energy: a feasibility study of phase contrast imaging on a whole breast

NASA Astrophysics Data System (ADS)

Sztrókay, A.; Diemoz, P. C.; Schlossbauer, T.; Brun, E.; Bamberg, F.; Mayr, D.; Reiser, M. F.; Bravin, A.; Coan, P.

2012-05-01

Previous studies on phase contrast imaging (PCI) mammography have demonstrated an enhancement of breast morphology and cancerous tissue visualization compared to conventional imaging. We show here the first results of the PCI analyser-based imaging (ABI) in computed tomography (CT) mode on whole and large (>12 cm) tumour-bearing breast tissues. We demonstrate in this work the capability of the technique of working at high x-ray energies and producing high-contrast images of large and complex specimens. One entire breast of an 80-year-old woman with invasive ductal cancer was imaged using ABI-CT with monochromatic 70 keV x-rays and an area detector of 92×92 µm2 pixel size. Sagittal slices were reconstructed from the acquired data, and compared to corresponding histological sections. Comparison with conventional absorption-based CT was also performed. Five blinded radiologists quantitatively evaluated the visual aspects of the ABI-CT images with respect to sharpness, soft tissue contrast, tissue boundaries and the discrimination of different structures/tissues. ABI-CT excellently depicted the entire 3D architecture of the breast volume by providing high-resolution and high-contrast images of the normal and cancerous breast tissues. These results are an important step in the evolution of PCI-CT towards its clinical implementation.

Breast tissue engineering.

PubMed

Patrick, Charles W

2004-01-01

Tissue engineering has the potential to redefine rehabilitation for the breast cancer patient by providing a translatable strategy that restores the postmastectomy breast mound while concomitantly obviating limitations realized with contemporary reconstructive surgery procedures. The engineering design goal is to provide a sufficient volume of viable fat tissue based on a patient's own cells such that deficits in breast volume can be abrogated. To be sure, adipose tissue engineering is in its infancy, but tremendous strides have been made. Numerous studies attest to the feasibility of adipose tissue engineering. The field is now poised to challenge barriers to clinical translation that are germane to most tissue engineering applications, namely scale-up, large animal model development, and vascularization. The innovative and rapid progress of adipose engineering to date, as well as opportunities for its future growth, is presented.

Amount of stroma is associated with mammographic density and stromal expression of oestrogen receptor in normal breast tissues.

PubMed

Gabrielson, Marike; Chiesa, Flaminia; Paulsson, Janna; Strell, Carina; Behmer, Catharina; Rönnow, Katarina; Czene, Kamila; Östman, Arne; Hall, Per

2016-07-01

Following female sex and age, mammographic density is considered one of the strongest risk factors for breast cancer. Despite the association between mammographic density and breast cancer risk, little is known about the underlying histology and biological basis of breast density. To better understand the mechanisms behind mammographic density we assessed morphology, proliferation and hormone receptor status in relation to mammographic density in breast tissues from healthy women. Tissues were obtained from 2012-2013 by ultrasound-guided core needle biopsy from 160 women as part of the Karma (Karolinska mammography project for risk prediction for breast cancer) project. Mammograms were collected through routine mammography screening and mammographic density was calculated using STRATUS. The histological composition, epithelial and stromal proliferation status and hormone receptor status were assessed through immunohistochemical staining. Higher mammographic density was significantly associated with a greater proportion of stromal and epithelial tissue and a lower proportion of adipose tissue. Epithelial expression levels of Ki-67, oestrogen receptor (ER) and progesterone receptor (PR) were not associated with mammographic density. Epithelial Ki-67 was associated with a greater proportion of epithelial tissue, and epithelial PR was associated with a greater proportion of stromal and a lower proportion of adipose tissue. Epithelial ER was not associated with any tissues. In contrast, expression of ER in the stroma was significantly associated with a greater proportion of stroma, and negatively associated with the amount of adipose tissue. High mammographic density is associated with higher amount of stroma and epithelium and less amount of fat, but is not associated with a change in epithelial proliferation or receptor status. Increased expressions of both epithelial PR and stromal ER are associated with a greater proportion of stroma, suggesting hormonal involvement in regulating breast tissue composition.

Apparent diffusion coefficient of breast cancer and normal fibroglandular tissue in diffusion-weighted imaging: the effects of menstrual cycle and menopausal status.

PubMed

Kim, Jin You; Suh, Hie Bum; Kang, Hyun Jung; Shin, Jong Ki; Choo, Ki Seok; Nam, Kyung Jin; Lee, Seok Won; Jung, Young Lae; Bae, Young Tae

2016-05-01

The purpose of this study was to investigate prospectively whether the apparent diffusion coefficients (ADCs) of both breast cancer and normal fibroglandular tissue vary with the menstrual cycle and menopausal status. Institutional review board approval was obtained, and informed consent was obtained from each participant. Fifty-seven women (29 premenopausal, 28 postmenopausal) with newly diagnosed breast cancer underwent diffusion-weighted imaging twice (interval 12-20 days) before surgery. Two radiologists independently measured ADC of breast cancer and normal contralateral breast tissue, and we quantified the differences according to the phases of menstrual cycle and menopausal status. With normal fibroglandular tissue, ADC was significantly lower in postmenopausal than in premenopausal women (P = 0.035). In premenopausal women, ADC did not differ significantly between proliferative and secretory phases in either breast cancer or normal fibroglandular tissue (P = 0.969 and P = 0.519, respectively). In postmenopausal women, no significant differences were found between ADCs measured at different time intervals in either breast cancer or normal fibroglandular tissue (P = 0.948 and P = 0.961, respectively). The within-subject variability of the ADC measurements was quantified using the coefficient of variation (CV) and was small: the mean CVs of tumor ADC were 2.90 % (premenopausal) and 3.43 % (postmenopausal), and those of fibroglandular tissue ADC were 4.37 % (premenopausal) and 2.55 % (postmenopausal). Both intra- and interobserver agreements were excellent for ADC measurements, with intraclass correlation coefficients in the range of 0.834-0.974. In conclusion, the measured ADCs of breast cancer and normal fibroglandular tissue were not affected significantly by menstrual cycle, and the measurements were highly reproducible both within and between observers.

A Presurgical Study of Lecithin Formulation of Green Tea Extract in Women with Early Breast Cancer.

PubMed

Lazzeroni, Matteo; Guerrieri-Gonzaga, Aliana; Gandini, Sara; Johansson, Harriet; Serrano, Davide; Cazzaniga, Massimiliano; Aristarco, Valentina; Macis, Debora; Mora, Serena; Caldarella, Pietro; Pagani, Gianmatteo; Pruneri, Giancarlo; Riva, Antonella; Petrangolini, Giovanna; Morazzoni, Paolo; DeCensi, Andrea; Bonanni, Bernardo

2017-06-01

Epidemiologic data support an inverse association between green tea intake and breast cancer risk. Greenselect Phytosome (GSP) is a lecithin formulation of a caffeine-free green tea catechin extract. The purpose of the study was to determine the tissue distribution of epigallocatechin-3-O-gallate (EGCG) and its effect on cell proliferation and circulating biomarkers in breast cancer patients. Twelve early breast cancer patients received GSP 300 mg, equivalent to 44.9 mg of EGCG, daily for 4 weeks prior to surgery. The EGCG levels were measured before (free) and after (total) enzymatic hydrolysis by HPLC-MS/MS in plasma, urine, breast cancer tissue, and surrounding normal breast tissue. Fasting blood samples were taken at baseline, before the last administration, and 2 hours later. Repeated administration of GSP achieved levels of total EGCG ranging from 17 to 121 ng/mL in plasma. Despite a high between-subject variability, total EGCG was detectable in all tumor tissue samples collected up to 8 ng/g. Median total EGCG concentration was higher in the tumor as compared with the adjacent normal tissue (3.18 ng/g vs. 0 ng/g, P = 0.02). Free EGCG concentrations ranged from 8 to 65.8 ng/mL in plasma ( P between last administration and 2 hours after <0.001). Free EGCG plasma levels showed a significant positive correlation with the Ki-67 decrease in tumor tissue ( P = 0.02). No change in any other biomarkers was noted, except for a slight increase in testosterone levels after treatment. Oral GSP increases bioavailability of EGCG, which is detectable in breast tumor tissue and is associated with antiproliferative effects on breast cancer tissue. Cancer Prev Res; 10(6); 363-9. ©2017 AACR . ©2017 American Association for Cancer Research.

A deep learning method for classifying mammographic breast density categories.

PubMed

Mohamed, Aly A; Berg, Wendie A; Peng, Hong; Luo, Yahong; Jankowitz, Rachel C; Wu, Shandong

2018-01-01

Mammographic breast density is an established risk marker for breast cancer and is visually assessed by radiologists in routine mammogram image reading, using four qualitative Breast Imaging and Reporting Data System (BI-RADS) breast density categories. It is particularly difficult for radiologists to consistently distinguish the two most common and most variably assigned BI-RADS categories, i.e., "scattered density" and "heterogeneously dense". The aim of this work was to investigate a deep learning-based breast density classifier to consistently distinguish these two categories, aiming at providing a potential computerized tool to assist radiologists in assigning a BI-RADS category in current clinical workflow. In this study, we constructed a convolutional neural network (CNN)-based model coupled with a large (i.e., 22,000 images) digital mammogram imaging dataset to evaluate the classification performance between the two aforementioned breast density categories. All images were collected from a cohort of 1,427 women who underwent standard digital mammography screening from 2005 to 2016 at our institution. The truths of the density categories were based on standard clinical assessment made by board-certified breast imaging radiologists. Effects of direct training from scratch solely using digital mammogram images and transfer learning of a pretrained model on a large nonmedical imaging dataset were evaluated for the specific task of breast density classification. In order to measure the classification performance, the CNN classifier was also tested on a refined version of the mammogram image dataset by removing some potentially inaccurately labeled images. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were used to measure the accuracy of the classifier. The AUC was 0.9421 when the CNN-model was trained from scratch on our own mammogram images, and the accuracy increased gradually along with an increased size of training samples. Using the pretrained model followed by a fine-tuning process with as few as 500 mammogram images led to an AUC of 0.9265. After removing the potentially inaccurately labeled images, AUC was increased to 0.9882 and 0.9857 for without and with the pretrained model, respectively, both significantly higher (P < 0.001) than when using the full imaging dataset. Our study demonstrated high classification accuracies between two difficult to distinguish breast density categories that are routinely assessed by radiologists. We anticipate that our approach will help enhance current clinical assessment of breast density and better support consistent density notification to patients in breast cancer screening. © 2017 American Association of Physicists in Medicine.

High frame-rate MR-guided near-infrared tomography system to monitor breast hemodynamics

NASA Astrophysics Data System (ADS)

Li, Zhiqiu; Jiang, Shudong; Krishnaswamy, Venkataramanan; Davis, Scott C.; Srinivasan, Subhadra; Paulsen, Keith D.; Pogue, Brian W.

2011-02-01

A near-infrared (NIR) tomography system with spectral-encoded sources at two wavelength bands was built to quantify the temporal contrast at 20 Hz bandwidth, while imaging breast tissue. The NIR system was integrated with a magnetic resonance (MR) machine through a custom breast coil interface, and both NIR data and MR images were acquired simultaneously. MR images provided breast tissue structural information for NIR reconstruction. Acquisition of finger pulse oximeter (PO) plethysmogram was synchronized with the NIR system in the experiment to offer a frequency-locked reference. The recovered absorption coefficients of the breast at two wavelengths showed identical temporal frequency as the PO output, proving this multi-modality design can recover the small pulsatile variation of absorption property in breast tissue related to the heartbeat. And it also showed the system's ability on novel contrast imaging of fast flow signals in deep tissue.

Raman microspectroscopy of Hematoporphyrins. Imaging of the noncancerous and the cancerous human breast tissues with photosensitizers.

PubMed

Brozek-Pluska, B; Kopec, M

2016-12-05

Raman microspectroscopy combined with fluorescence were used to study the distribution of Hematoporphyrin (Hp) in noncancerous and cancerous breast tissues. The results demonstrate the ability of Raman spectroscopy to distinguish between noncancerous and cancerous human breast tissue and to identify differences in the distribution and photodegradation of Hematoporphyrin, which is a photosensitizer in photodynamic therapy (PDT), photodynamic diagnosis (PDD) and photoimmunotherapy (PIT) of cancer. Presented results show that Hematoporphyrin level in the noncancerous breast tissue is lower compared to the cancerous one. We have proved also that the Raman intensity of lipids and proteins doesn't change dramatically after laser light irradiation, which indicates that the PDT treatment destroys preferably cancer cells, in which the photosensitizer is accumulated. The specific subcellular localization of photosensitizer for breast tissues samples soaked with Hematoporphyrin was not observed. Copyright © 2016 Elsevier B.V. All rights reserved.

Mastectomy - discharge

MedlinePlus

... Elsevier Saunders; 2015:chap 109. Read More Breast cancer Breast lump removal Breast reconstruction - implants Breast reconstruction - natural tissue Mastectomy Patient Instructions Cosmetic breast surgery - discharge Mastectomy and breast ...

Gynecomastia Management: An Evolution and Refinement in Technique at UT Southwestern Medical Center

PubMed Central

Bailey, Steven H.; Guenther, Dax; Constantine, Fadi

2016-01-01

Summary: Gynecomastia is a benign proliferation of male breast glandular tissue. Gynecomastia can affect men at any stage of life. Traditional treatment options involved excisional surgeries with periareolar or T-shaped scars, which can leave more visible scars on the chest. The technique presented represents a technique used by the senior author, which relies on ultrasonic liposuction and pull-through technique to remove breast tissue. A retrospective chart review was performed, including all patients who were treated, from 2000 to 2013 by the senior author, for gynecomastia. A deidentified database was created to record patient characteristics, including age, height, weight, ptosis, stage of gynecomastia, and gynecomastia classification. Surgical approaches, complications, and revisions were also recorded. Our experience includes 75 patients with all grades of gynecomastia from 2000 to 2013. These cases span the evolution of our technique to include direct pull-through excision with ultrasound-assisted liposuction. The distribution of the grades I, II, III, and IV ptosis was 30.6%, 36 %, 22.6%, and 10.6% respectively. There were no complications in this series. Only one patient with grade III ptosis required revision surgery. This technique provides a safe and aesthetically pleasing way to treat gynecomastia with a low need for revision. PMID:27482482

Average Dielectric Property Analysis of Complex Breast Tissue with Microwave Transmission Measurements

PubMed Central

Garrett, John D.; Fear, Elise C.

2015-01-01

Prior information about the average dielectric properties of breast tissue can be implemented in microwave breast imaging techniques to improve the results. Rapidly providing this information relies on acquiring a limited number of measurements and processing these measurement with efficient algorithms. Previously, systems were developed to measure the transmission of microwave signals through breast tissue, and simplifications were applied to estimate the average properties. These methods provided reasonable estimates, but they were sensitive to multipath. In this paper, a new technique to analyze the average properties of breast tissues while addressing multipath is presented. Three steps are used to process transmission measurements. First, the effects of multipath were removed. In cases where multipath is present, multiple peaks were observed in the time domain. A Tukey window was used to time-gate a single peak and, therefore, select a single path through the breast. Second, the antenna response was deconvolved from the transmission coefficient to isolate the response from the tissue in the breast interior. The antenna response was determined through simulations. Finally, the complex permittivity was estimated using an iterative approach. This technique was validated using simulated and physical homogeneous breast models and tested with results taken from a recent patient study. PMID:25585106

Thyroid peroxidase (TPO) expressed in thyroid and breast tissues shows similar antigenic properties.

PubMed

Godlewska, Marlena; Arczewska, Katarzyna D; Rudzińska, Magdalena; Łyczkowska, Anna; Krasuska, Wanda; Hanusek, Karolina; Ruf, Jean; Kiedrowski, Mirosław; Czarnocka, Barbara

2017-01-01

Thyroid peroxidase (TPO) is essential for physiological function of the thyroid gland. The high prevalence of thyroid peroxidase antibodies (TPOAbs) in patients with breast cancer and their protective role had previously been demonstrated, indicating a link between breast cancer and thyroid autoimmunity. Recently, TPO was shown to be present in breast cancer tissue samples but its antigenicity has not been analyzed. In this study, we investigated TPO expression levels in a series of fifty-six breast cancer samples paired with normal (peri-tumoral) tissue and its antigenic activity using a panel of well-characterized murine anti-human TPOAbs. We have shown that TPO transcripts were present in both normal and cancer tissue samples, although the amounts in the latter were reduced. Additionally, we observed that TPO levels are lower in more advanced cancers. TPO protein expression was confirmed in all tissue samples, both normal and cancerous. We also found that the antigenicity of the immunodominant regions (IDRs) in breast TPO resembles that of thyroid TPO, which is crucial for effective interactions with human TPOAbs. Expression of TPO in breast cancer together with its antigenic activity may have beneficial effects in TPOAb-positive breast cancer patients. However, further studies are needed to confirm the beneficial role of TPOAbs and to better understand the underlying mechanism.

Fibroblast growth factor 8 is expressed at higher levels in lactating human breast and in breast cancer.

PubMed

Zammit, C; Coope, R; Gomm, J J; Shousha, S; Johnston, C L; Coombes, R C

2002-04-08

Fibroblast growth factor 8 can transform NIH3T3 cells and its expression has been found to be associated with breast and prostate cancer. Following our finding that fibroblast growth factor 8 mRNA expression is increased in breast cancer, we have undertaken an immunohistochemistry study of fibroblast growth factor 8 expression in a series of human breast tissues and other normal tissues. Our findings confirm increased expression of fibroblast growth factor 8 in malignant breast tissue but also show significant fibroblast growth factor 8 expression in non-malignant breast epithelial cells. No significant difference in fibroblast growth factor 8 expression was found between different grades of ductal carcinoma, lobular carcinoma and ductal carcinoma in-situ or cancer of different oestrogen receptor, progesterone receptor or nodal status. The highest levels of fibroblast growth factor 8 expression were found in lactating breast tissues and fibroblast growth factor 8 was also detected in human milk. A survey of other normal tissues showed that fibroblast growth factor 8 is expressed in the proliferative cells of the dermis and epithelial cells in colon, ovary fallopian tube and uterus. Fibroblast growth factor 8 appears to be expressed in several organs in man and appears to have an importance in lactation.

NASA SMART Probe: Breast Cancer Application

NASA Technical Reports Server (NTRS)

Mah, Robert W.; Norvig, Peter (Technical Monitor)

2000-01-01

There is evidence in breast cancer and other malignancies that the physiologic environment within a tumor correlates with clinical outcome. We are developing a unique percutaneous Smart Probe to be used at the time of needle biopsy of the breast. The Smart Probe will simultaneously measure multiple physiologic parameters within a breast tumor. Direct and indirect measurements of tissue oxygen levels, blood flow, pH, and tissue fluid pressure will be analyzed in real-time. These parameters will be interpreted individually and collectively by innovative neural network techniques using advanced intelligent software. The goals are 1) develop a pecutaneous Smart Probe with multiple sensor modalities and applying advanced Information Technologies to provide real time diagnostic information of the tissue at tip of the probe, 2) test the percutaneous Smart Probe in women with benign and malignant breast masses who will be undergoing surgical biopsy, 3) correlate probe sensor data with benign and malignant status of breast masses, 4) determine whether the probe can detect physiologic differences within a breast tumor, and its margins, and in adjacent normal breast tissue, 5) correlate probe sensor data with known prognostic factors for breast caner, including tumor size, tumor grade, axillary lymph node metastases, estrogen receptor and progesterone receptor status.

Toll Like Receptor-9 Mediated Invasion in Breast Cancer

DTIC Science & Technology

2012-07-01

cancer models, but only in triple negative breast cancer cells. In line with these...expression and“dead DNA” are biologically important in triple negative breast cancer . 15. SUBJECT TERMS None provided 16. SECURITY CLASSIFICATION OF...experiments done so far in the Specific Aim # 1: Tumor TLR9 expression has a dramatic effect on prognosis in triple negative breast cancers . The lack

Molecular classification of breast cancer: what the pathologist needs to know.

PubMed

Rakha, Emad A; Green, Andrew R

2017-02-01

Breast cancer is a heterogeneous disease featuring distinct histological, molecular and clinical phenotypes. Although traditional classification systems utilising clinicopathological and few molecular markers are well established and validated, they remain insufficient to reflect the diverse biological and clinical heterogeneity of breast cancer. Advancements in high-throughput molecular techniques and bioinformatics have contributed to the improved understanding of breast cancer biology, refinement of molecular taxonomies and the development of novel prognostic and predictive molecular assays. Application of such technologies is already underway, and is expected to change the way we manage breast cancer. Despite the enormous amount of work that has been carried out to develop and refine breast cancer molecular prognostic and predictive assays, molecular testing is still in evolution. Pathologists should be aware of the new technology and be ready for the challenge. In this review, we provide an update on the application of molecular techniques with regard to breast cancer diagnosis, prognosis and outcome prediction. The current contribution of emerging technology to our understanding of breast cancer is also highlighted. Copyright © 2016 Royal College of Pathologists of Australasia. Published by Elsevier B.V. All rights reserved.

The membrane mucin MUC4 is elevated in breast tumor lymph node metastases relative to matched primary tumors and confers aggressive properties to breast cancer cells.

PubMed

Workman, Heather C; Miller, Jamie K; Ingalla, Ellen Q; Kaur, Rouminder P; Yamamoto, Diane I; Beckett, Laurel A; Young, Lawrence Jt; Cardiff, Robert D; Borowsky, Alexander D; Carraway, Kermit L; Sweeney, Colleen; Carraway, Kermit L

2009-01-01

Previous studies indicate that overexpression of the membrane-associated mucin MUC4 is potently anti-adhesive to cultured tumor cells, and suppresses cellular apoptotic response to a variety of insults. Such observations raise the possibility that MUC4 expression could contribute to tumor progression or metastasis, but the potential involvement of MUC4 in breast cancer has not been rigorously assessed. The present study aimed to investigate the expression of the membrane mucin MUC4 in normal breast tissue, primary breast tumors and lymph node metastases, and to evaluate the role of MUC4 in promoting the malignant properties of breast tumor cells. MUC4 expression levels in patient-matched normal and tumor breast tissue was initially examined by immunoblotting lysates of fresh frozen tissue samples with a highly specific preparation of anti-MUC4 monoclonal antibody 1G8. Immunohistochemical analysis was then carried out using tissue microarrays encompassing patient-matched normal breast tissue and primary tumors, and patient-matched lymph node metastases and primary tumors. Finally, shRNA-mediated knockdown was employed to assess the contribution of MUC4 to the cellular growth and malignancy properties of JIMT-1 breast cancer cells. Immunoblotting and immunohistochemistry revealed that MUC4 levels are suppressed in the majority (58%, p < 0.001) of primary tumors relative to patient-matched normal tissue. On the other hand, lymph node metastatic lesions from 37% (p < 0.05) of patients expressed higher MUC4 protein levels than patient-matched primary tumors. MUC4-positive tumor emboli were often found in lymphovascular spaces of lymph node metastatic lesions. shRNA-mediated MUC4 knockdown compromised the migration, proliferation and anoikis resistance of JIMT-1 cells, strongly suggesting that MUC4 expression actively contributes to cellular properties associated with breast tumor metastasis. Our observations suggest that after an initial loss of MUC4 levels during the transition of normal breast tissue to primary tumor, the re-establishment of elevated MUC4 levels confers an advantage to metastasizing breast tumor cells by promoting the acquisition of cellular properties associated with malignancy.

miR-411-5p inhibits proliferation and metastasis of breast cancer cell via targeting GRB2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yunda; State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen 361102; Xu, Guoxing

miR-411-5p (previously called miR-411) is severely involved in human diseases, however, the relationship between miR-411-5p and breast cancer has not been investigated thoroughly. Here, we found that the expression of miR-411-5p was downregulated in breast cancer tissues compared with their matched adjacent non-neoplastic tissues. In addition, the expression of miR-411-5p was also lower in breast cancer cell lines in contrast with MCF-10A. Moreover, we investigated the target and mechanism of miR-411-5p in breast cancer using mimic and inhibitor, and demonstrated the involvement of GRB2 and Ras activation. Ectopic expression of miR-411-5p suppressed the breast cancer cell proliferation, migration and invasionmore » while low expression of miR-411-5p exhibited the opposite effect. Furthermore, GRB2 was demonstrated to be significantly overexpressed in breast cancer tissues compared with normal tissues, and low expression of GRB2 had a longer overall survival compared with high expression of GRB2 in breast cancer. In general, our study shed light on the miR-411-5p related mechanism in the progression of breast cancer and, miR-411-5p/GRB2/Ras axis is potential to be molecular target for breast cancer therapy. - Highlights: • miR-411-5p is downregulated in breast cancer tissues and cell lines. • miR-411-5p inhibits breast cancer cells growth, migration and invasion in vitro. • GRB2 is a direct target of miR-411-5p in breast cancer. • GRB2 is overexpressed in breast cancer and associates with disease outcome. • miR-411-5p suppresses breast cancer progression though GRB2-SOS-Ras pathway.« less

BCCTBbp: the Breast Cancer Campaign Tissue Bank bioinformatics portal.

PubMed

Cutts, Rosalind J; Guerra-Assunção, José Afonso; Gadaleta, Emanuela; Dayem Ullah, Abu Z; Chelala, Claude

2015-01-01

BCCTBbp (http://bioinformatics.breastcancertissue bank.org) was initially developed as the data-mining portal of the Breast Cancer Campaign Tissue Bank (BCCTB), a vital resource of breast cancer tissue for researchers to support and promote cutting-edge research. BCCTBbp is dedicated to maximising research on patient tissues by initially storing genomics, methylomics, transcriptomics, proteomics and microRNA data that has been mined from the literature and linking to pathways and mechanisms involved in breast cancer. Currently, the portal holds 146 datasets comprising over 227,795 expression/genomic measurements from various breast tissues (e.g. normal, malignant or benign lesions), cell lines and body fluids. BCCTBbp can be used to build on breast cancer knowledge and maximise the value of existing research. By recording a large number of annotations on samples and studies, and linking to other databases, such as NCBI, Ensembl and Reactome, a wide variety of different investigations can be carried out. Additionally, BCCTBbp has a dedicated analytical layer allowing researchers to further analyse stored datasets. A future important role for BCCTBbp is to make available all data generated on BCCTB tissues thus building a valuable resource of information on the tissues in BCCTB that will save repetition of experiments and expand scientific knowledge. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Quantitative shear wave ultrasound elastography: initial experience in solid breast masses

PubMed Central

2010-01-01

Introduction Shear wave elastography is a new method of obtaining quantitative tissue elasticity data during breast ultrasound examinations. The aims of this study were (1) to determine the reproducibility of shear wave elastography (2) to correlate the elasticity values of a series of solid breast masses with histological findings and (3) to compare shear wave elastography with greyscale ultrasound for benign/malignant classification. Methods Using the Aixplorer® ultrasound system (SuperSonic Imagine, Aix en Provence, France), 53 solid breast lesions were identified in 52 consecutive patients. Two orthogonal elastography images were obtained of each lesion. Observers noted the mean elasticity values in regions of interest (ROI) placed over the stiffest areas on the two elastography images and a mean value was calculated for each lesion. A sub-set of 15 patients had two elastography images obtained by an additional operator. Reproducibility of observations was assessed between (1) two observers analysing the same pair of images and (2) findings from two pairs of images of the same lesion taken by two different operators. All lesions were subjected to percutaneous biopsy. Elastography measurements were correlated with histology results. After preliminary experience with 10 patients a mean elasticity cut off value of 50 kilopascals (kPa) was selected for benign/malignant differentiation. Greyscale images were classified according to the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS). BI-RADS categories 1-3 were taken as benign while BI-RADS categories 4 and 5 were classified as malignant. Results Twenty-three benign lesions and 30 cancers were diagnosed on histology. Measurement of mean elasticity yielded an intraclass correlation coefficient of 0.99 for two observers assessing the same pairs of elastography images. Analysis of images taken by two independent operators gave an intraclass correlation coefficient of 0.80. Shear wave elastography versus greyscale BI-RADS performance figures were sensitivity: 97% vs 87%, specificity: 83% vs 78%, positive predictive value (PPV): 88% vs 84%, negative predictive value (NPV): 95% vs 82% and accuracy: 91% vs 83% respectively. These differences were not statistically significant. Conclusions Shear wave elastography gives quantitative and reproducible information on solid breast lesions with diagnostic accuracy at least as good as greyscale ultrasound with BI-RADS classification. PMID:21122101

Quantitative shear wave ultrasound elastography: initial experience in solid breast masses.

PubMed

Evans, Andrew; Whelehan, Patsy; Thomson, Kim; McLean, Denis; Brauer, Katrin; Purdie, Colin; Jordan, Lee; Baker, Lee; Thompson, Alastair

2010-01-01

Shear wave elastography is a new method of obtaining quantitative tissue elasticity data during breast ultrasound examinations. The aims of this study were (1) to determine the reproducibility of shear wave elastography (2) to correlate the elasticity values of a series of solid breast masses with histological findings and (3) to compare shear wave elastography with greyscale ultrasound for benign/malignant classification. Using the Aixplorer® ultrasound system (SuperSonic Imagine, Aix en Provence, France), 53 solid breast lesions were identified in 52 consecutive patients. Two orthogonal elastography images were obtained of each lesion. Observers noted the mean elasticity values in regions of interest (ROI) placed over the stiffest areas on the two elastography images and a mean value was calculated for each lesion. A sub-set of 15 patients had two elastography images obtained by an additional operator. Reproducibility of observations was assessed between (1) two observers analysing the same pair of images and (2) findings from two pairs of images of the same lesion taken by two different operators. All lesions were subjected to percutaneous biopsy. Elastography measurements were correlated with histology results. After preliminary experience with 10 patients a mean elasticity cut off value of 50 kilopascals (kPa) was selected for benign/malignant differentiation. Greyscale images were classified according to the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS). BI-RADS categories 1-3 were taken as benign while BI-RADS categories 4 and 5 were classified as malignant. Twenty-three benign lesions and 30 cancers were diagnosed on histology. Measurement of mean elasticity yielded an intraclass correlation coefficient of 0.99 for two observers assessing the same pairs of elastography images. Analysis of images taken by two independent operators gave an intraclass correlation coefficient of 0.80. Shear wave elastography versus greyscale BI-RADS performance figures were sensitivity: 97% vs 87%, specificity: 83% vs 78%, positive predictive value (PPV): 88% vs 84%, negative predictive value (NPV): 95% vs 82% and accuracy: 91% vs 83% respectively. These differences were not statistically significant. Shear wave elastography gives quantitative and reproducible information on solid breast lesions with diagnostic accuracy at least as good as greyscale ultrasound with BI-RADS classification.

Compensatory neurofuzzy model for discrete data classification in biomedical

NASA Astrophysics Data System (ADS)

Ceylan, Rahime

2015-03-01

Biomedical data is separated to two main sections: signals and discrete data. So, studies in this area are about biomedical signal classification or biomedical discrete data classification. There are artificial intelligence models which are relevant to classification of ECG, EMG or EEG signals. In same way, in literature, many models exist for classification of discrete data taken as value of samples which can be results of blood analysis or biopsy in medical process. Each algorithm could not achieve high accuracy rate on classification of signal and discrete data. In this study, compensatory neurofuzzy network model is presented for classification of discrete data in biomedical pattern recognition area. The compensatory neurofuzzy network has a hybrid and binary classifier. In this system, the parameters of fuzzy systems are updated by backpropagation algorithm. The realized classifier model is conducted to two benchmark datasets (Wisconsin Breast Cancer dataset and Pima Indian Diabetes dataset). Experimental studies show that compensatory neurofuzzy network model achieved 96.11% accuracy rate in classification of breast cancer dataset and 69.08% accuracy rate was obtained in experiments made on diabetes dataset with only 10 iterations.

Breast Cancer Research at NASA

NASA Technical Reports Server (NTRS)

1998-01-01

Isolation of human mammary epithelial cells (HMEC) from breast cancer susceptible tissue. Isolate of long-term growth human mammary epithelial cells (HMEC) from outgrowth of duct element; cells shown soon after isolation and early in culture in a dish. NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cell (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunorous tissue. Credit: Dr. Robert Tichmond, NASA/Marshall Space Flight Center (MSFC).

Sensitivity of Breast Tumors to Oncolytic Viruses

DTIC Science & Technology

2006-08-01

therapies for breast cancer based on the oncolytic virus, vesicular stomatitis virus (VSV). Studies have shown that matrix (M) protein mutants of VSV, such...more resistant to VSV-induced cytopathic effect than breast cancer cells. However, in syngeneic breast cancer system in vivo, rM51R-M virus is only...interleukin 12, breast cancer , interferon 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE

Advancing Our Understanding of the Etiologies and Mutational Landscapes of Basal-Like, Luminal A, and Luminal B Breast Cancers

DTIC Science & Technology

2017-10-01

study to identify how various breast cancer risk factors differ in their relationships to different molecular subtypes of breast cancer and to further...characterize molecular differences between these subtypes. To address the existing research gaps regarding the etiologies of different molecular ... molecular subtypes of breast cancer, basal-like, luminal A, and luminal B tumors, breast cancer risk factors 16. SECURITY CLASSIFICATION OF: 17

Cosmetic sequelae after oncoplastic surgery of the breast. Classification and factors for prevention.

PubMed

Acea Nebril, Benigno; Cereijo Garea, Carmen; García Novoa, Alejandra

2015-02-01

Oncoplastic surgery is an essential tool in the surgical approach to women with breast cancer. These techniques are not absolute guarantee for a good cosmetic result and therefore some patients will have cosmetic sequelae secondary to poor surgical planning, the effects of adjuvant treatments or the need for resection greater than originally planned. The high frequency of these cosmetic sequelae in oncology practice makes it necessary to classify them for optimal surgical planning. The aim of this paper is to present a classification of cosmetic sequelae after oncoplastic procedures to identify those factors that are crucial to its prevention. This classification contains 4 groups: breast contour deformities, asymmetries, alterations in nipple-aréola complex (NAC) and defects in the three dimensional structure of the breast. A significant group of these sequelae (asymmetries and deformities) are associated with breast irradiation and need an accurate information process with patients to set realistic expectations about cosmetic results. Finally, there is another group of sequelae (NAC disorders and three-dimensional structure) that are related to poor planning and deficiencies in surgical approach, therfore specific training is essential for learning these surgical techniques. Copyright © 2014 AEC. Publicado por Elsevier España, S.L.U. All rights reserved.

21 CFR 866.6040 - Gene expression profiling test system for breast cancer prognosis.

Code of Federal Regulations, 2010 CFR

2010-04-01

... cancer prognosis. 866.6040 Section 866.6040 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... cancer prognosis. (a) Identification. A gene expression profiling test system for breast cancer prognosis... previously diagnosed breast cancer. (b) Classification. Class II (special controls). The special control is...

21 CFR 866.6040 - Gene expression profiling test system for breast cancer prognosis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... cancer prognosis. 866.6040 Section 866.6040 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... cancer prognosis. (a) Identification. A gene expression profiling test system for breast cancer prognosis... previously diagnosed breast cancer. (b) Classification. Class II (special controls). The special control is...

Visible and near-infrared hyperspectral imaging for cooking loss classification of fresh broiler breast fillets

USDA-ARS?s Scientific Manuscript database

Cooking loss (CL) is a critical quality attribute directly relating to meat juiciness. The potential of the hyperspectral imaging (HSI) technique was investigated for non-invasively classifying and visualizing the CL of fresh broiler breast meat. Hyperspectral images of total 75 fresh broiler breast...

21 CFR 866.6040 - Gene expression profiling test system for breast cancer prognosis.

Code of Federal Regulations, 2013 CFR

2013-04-01

... cancer prognosis. 866.6040 Section 866.6040 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... cancer prognosis. (a) Identification. A gene expression profiling test system for breast cancer prognosis... previously diagnosed breast cancer. (b) Classification. Class II (special controls). The special control is...

21 CFR 866.6040 - Gene expression profiling test system for breast cancer prognosis.

Code of Federal Regulations, 2012 CFR

2012-04-01

... cancer prognosis. 866.6040 Section 866.6040 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... cancer prognosis. (a) Identification. A gene expression profiling test system for breast cancer prognosis... previously diagnosed breast cancer. (b) Classification. Class II (special controls). The special control is...

21 CFR 866.6040 - Gene expression profiling test system for breast cancer prognosis.

Code of Federal Regulations, 2014 CFR

2014-04-01

... cancer prognosis. 866.6040 Section 866.6040 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... cancer prognosis. (a) Identification. A gene expression profiling test system for breast cancer prognosis... previously diagnosed breast cancer. (b) Classification. Class II (special controls). The special control is...

Voting strategy for artifact reduction in digital breast tomosynthesis.

PubMed

Wu, Tao; Moore, Richard H; Kopans, Daniel B

2006-07-01

Artifacts are observed in digital breast tomosynthesis (DBT) reconstructions due to the small number of projections and the narrow angular range that are typically employed in tomosynthesis imaging. In this work, we investigate the reconstruction artifacts that are caused by high-attenuation features in breast and develop several artifact reduction methods based on a "voting strategy." The voting strategy identifies the projection(s) that would introduce artifacts to a voxel and rejects the projection(s) when reconstructing the voxel. Four approaches to the voting strategy were compared, including projection segmentation, maximum contribution deduction, one-step classification, and iterative classification. The projection segmentation method, based on segmentation of high-attenuation features from the projections, effectively reduces artifacts caused by metal and large calcifications that can be reliably detected and segmented from projections. The other three methods are based on the observation that contributions from artifact-inducing projections have higher value than those from normal projections. These methods attempt to identify the projection(s) that would cause artifacts by comparing contributions from different projections. Among the three methods, the iterative classification method provides the best artifact reduction; however, it can generate many false positive classifications that degrade the image quality. The maximum contribution deduction method and one-step classification method both reduce artifacts well from small calcifications, although the performance of artifact reduction is slightly better with the one-step classification. The combination of one-step classification and projection segmentation removes artifacts from both large and small calcifications.

Cell Proliferation (KI-67) Expression Is Associated with Poorer Prognosis in Nigerian Compared to British Breast Cancer Women

PubMed Central

Agboola, Ayodeji O. J.; Banjo, Adekumbiola A. F.; Anunobi, Charles C.; Salami, Babatunde; Agboola, Mopelola Deji; Musa, Adewale A.; Nolan, Christopher C.; Rakha, Emad A.; Ellis, Ian O.; Green, Andrew R.

2013-01-01

Background. Black women with breast cancer (BC) in Nigeria have higher mortality rate compared with British women. This study investigated prognostic features of cell proliferation biomarker (Ki-67) in Nigerian breast cancer women. Materials and Methods. The protein expression of Ki-67 was investigated in series of 308 Nigerian women, prepared as a tissue microarray (TMA), using immunohistochemistry. Clinic-pathological parameters, biomarkers, and patient outcome of tumours expressing Ki-67 in Nigerian women were correlated with UK grade-matched series. Results. A significantly larger proportion of breast tumours from Nigerian women showed high Ki-67 expression. Those tumours were significantly correlated with negative expression of the steroid hormone receptors (ER and PgR), p21, p27, E-cadherin, BRCA-1, and Bcl-2 (all P < 0.001), but positively associated with EGFR (P = 0.003), p53, basal cytokeratins: CK56, CK14, triple negative, and basal phenotype using Nielsen's classification (all P < 0.001) compared to UK women. Multivariate analyses showed that race was also associated with BCSS independent of tumour size, lymph node status, and ER status. Conclusion. Ki-67 expression was observed to have contributed to the difference in the BCSS in Nigerian compared with British BC women. Therefore, targeting Ki-67 in the indigenous black women with BC might improve the patient outcome in the black women with BC. PMID:23691362

Pseudogynecomastia secondary to injection of heroin into breast tissue.

PubMed

Carlson, R H; Velez, R; Rivlin, R S

1978-03-01

A 50-year-old man who has a heroin addict developed bilateral, symmetrical swelling of the breasts as a result of injecting himself directly into the breasts for several years. Results of histologic examination of the breast tissue showed granulomatous inflammation and a foreign body reaction without gynecomastia or tumor. Liver and endocrine functions were generally normal.

Breast Cancer Research at NASA

NASA Technical Reports Server (NTRS)

1998-01-01

High magnification view of human primary breast tumor cells after 56 days of culture in a NASA Bioreactor. The arrow points to bead surface indicating breast cancer cells (as noted by the staining of tumor cell intermediate filaments). NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cell (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunorous tissue. Credit: Dr. Jearne Becker, University of South Florida

Transcriptional expression analysis of survivin splice variants reveals differential expression of survivin-3α in breast cancer.

PubMed

Moniri Javadhesari, Solmaz; Gharechahi, Javad; Hosseinpour Feizi, Mohammad Ali; Montazeri, Vahid; Halimi, Monireh

2013-04-01

Survivin, which is a novel member of the inhibitor of apoptosis family proteins, is known to play an important role in the regulation of cell cycle and apoptosis. Differential expression of survivin in tumor tissues introduces it as a new candidate molecular marker for cancer. Here we investigated the expression of survivin and its splice variants in breast tumors, as well as normal adjacent tissues obtained from the same patients. Thirty five tumors and 17 normal adjacent tissues from women diagnosed with breast cancer were explored in this study. Differential expression of different survivin splice variants was detected and semiquantitatively analyzed using reverse transcription-polymerase chain reaction. Results showed that survivin and its splice variants were differentially expressed in tumor specimens compared with normal adjacent tissues. The expression of survivin-3B and survivin-3α was specifically detected in tumor tissues compared with normal adjacent ones (53% in tumor tissues compared to 5% in normal adjacent for survivin-3B and 65% in tumor tissues and 0.0% in normal adjacent tissues for survivin-3α). Statistical analysis showed that survivin and survivin-ΔEx3 were upregulated in benign (90%, p<0.034) and malignant (76%, p<0.042) tumors, respectively. On the other hand, our results showed that survivin-2α (100% of the cases) was the dominant expressed variant of survivin in breast cancer. The data presented here showed that survivin splice variants were differentially expressed in benign and malignant breast cancer tissues, suggesting their potential role in breast cancer development. Differential expression of survivin-2α and survivin-3α splice variants highlights their usefulness as new candidate markers for breast cancer diagnosis and prognosis.

Phase transitions in oleic acid and in human breast tissue as studied by Raman spectroscopy and Raman imaging.

PubMed

Brozek-Pluska, Beata; Jablonska-Gajewicz, Joanna; Kordek, Radzislaw; Abramczyk, Halina

2011-05-12

We present the results of differential scanning calorimetry (DSC) and Raman studies in the temperature range of 293-77 K on vibrational properties of the oleic acid and the human breast tissue as a function of temperature. We have found that vibrational properties are very sensitive indicators to specify phases and phase transitions at the molecular level. We have found that water content confined in the cancerous tissue is markedly different from that in the noncancerous tissue. The OH stretching vibrations of water are useful as potential Raman biomarkers to distinguish between the cancerous and the noncancerous human breast tissues. Our results provide experimental evidence on the role of lipid profile and cell hydration as factors of particular significance in differentiation of the noncancerous and cancerous breast tissues.

Mutual information criterion for feature selection with application to classification of breast microcalcifications

NASA Astrophysics Data System (ADS)

Diamant, Idit; Shalhon, Moran; Goldberger, Jacob; Greenspan, Hayit

2016-03-01

Classification of clustered breast microcalcifications into benign and malignant categories is an extremely challenging task for computerized algorithms and expert radiologists alike. In this paper we present a novel method for feature selection based on mutual information (MI) criterion for automatic classification of microcalcifications. We explored the MI based feature selection for various texture features. The proposed method was evaluated on a standardized digital database for screening mammography (DDSM). Experimental results demonstrate the effectiveness and the advantage of using the MI-based feature selection to obtain the most relevant features for the task and thus to provide for improved performance as compared to using all features.

MMP13 is potentially a new tumor marker for breast cancer diagnosis.

PubMed

Chang, Hui-Jen; Yang, Ming-Je; Yang, Yu-Hsiang; Hou, Ming-Feng; Hsueh, Er-Jung; Lin, Shiu-Ru

2009-11-01

Within the past decade, the incidence of breast cancer in Taiwan has been rising year after year. Breast cancer is the first most prevalent cancer and the fourth leading cause of cancer-related deaths among women in Taiwan. The early stage of breast cancer not only have a wider range of therapeutic options, but also obtain a higher success rate of therapy than those with advanced breast cancer. A test for tumor markers is the most convenient method to screen for breast cancer. However, the tumor markers currently available for breast cancer detection include carcinoembryonic antigen (CEA), carbohydrate antigen 15.3 (CA15.3), and carbohydrate antigen 27.29 (CA27.29) exhibited certain limitations. Poor sensitivity and specificity greatly limits the diagnostic accuracy of these markers. This study aims to identify potential tumor markers for breast cancer. At first, we analyzed genes expression in infiltrating lobular carcinoma, metaplastic carcinoma, and infiltrating ductal carcinoma of paired specimens (tumor and normal tissue) from breast cancer patients using microarray technology. We selected 371 overexpressed genes in all of the three cell type. In advanced breast cancer tissue, we detected four genes MMP13, CAMP, COL10A1 and FLJ25416 from 25 overexpressed genes which encoded secretion protein more specifically for breast cancer than other genes. After validation with 15 pairs of breast cancer tissue and paired to normal adjacent tissues by membrane array and quantitative RT-PCR, we found MMP13 was 100% overexpressed and confirmed to be a secreted protein by Western blot analysis of the cell culture medium. The expression level of MMP13 was also measured by immunohistochemical staining. We suggest that MMP13 is a highly overexpressed secretion protein in breast cancer tissue. It has potential to be a new tumor marker for breast cancer diagnosis.

Biomarkers in Tissue Samples From Patients With Newly Diagnosed Breast Cancer Treated With Zoledronic Acid

ClinicalTrials.gov

2018-06-01

Estrogen Receptor-positive Breast Cancer; Invasive Ductal Breast Carcinoma; Progesterone Receptor-positive Breast Cancer; Stage IA Breast Cancer; Stage IB Breast Cancer; Stage IIA Breast Cancer; Stage IIB Breast Cancer

RCL2, a New Fixative, Preserves Morphology and Nucleic Acid Integrity in Paraffin-Embedded Breast Carcinoma and Microdissected Breast Tumor Cells

PubMed Central

Delfour, Christophe; Roger, Pascal; Bret, Caroline; Berthe, Marie-Laurence; Rochaix, Philippe; Kalfa, Nicolas; Raynaud, Pierre; Bibeau, Frédéric; Maudelonde, Thierry; Boulle, Nathalie

2006-01-01

Methacarn and RCL2, a new noncrosslinking fixative, were compared to formalin-fixed or frozen tissue samples of the same invasive breast carcinoma and were evaluated for their effects on tissue morphology and immunohistochemistry as well as DNA and RNA integrity. The histomorphology of methacarn- or RCL2-fixed paraffin-embedded tumors was similar to that observed with the matched formalin-fixed tissues. Immunohistochemistry using various antibodies showed comparable results with either fixative, leading to accurate breast tumor diagnosis and determination of estrogen and progesterone receptors, and HER2 status. Methacarn and RCL2 fixation preserved DNA integrity as demonstrated by successful amplification and sequencing of large DNA amplicons. Similarly, high-quality RNA could be extracted from methacarn- or RCL2-fixed paraffin-embedded MCF-7 cells, whole breast tumor tissues, or microdissected breast tumor cells, as assessed by electropherogram profiles and real-time reverse transcriptase-polymerase chain reaction quantification of various genes. Moreover, tissue morphology and RNA integrity were preserved after 8 months of storage. Altogether, these results indicate that methacarn, as previously shown, and RCL2, a promising new fixative, have great potential for performing both morphological and molecular analyses on the same fixed tissue sample, even after laser-capture microdissection, and can open new doors for investigating small target lesions such as premalignant breast lesions. PMID:16645201

Estimation of stress relaxation time for normal and abnormal breast phantoms using optical technique

NASA Astrophysics Data System (ADS)

Udayakumar, K.; Sujatha, N.

2015-03-01

Many of the early occurring micro-anomalies in breast may transform into a deadliest cancer tumor in future. Probability of curing early occurring abnormalities in breast is more if rightly identified. Even in mammogram, considered as a golden standard technique for breast imaging, it is hard to pick up early occurring changes in the breast tissue due to the difference in mechanical behavior of the normal and abnormal tissue when subjected to compression prior to x-ray or laser exposure. In this paper, an attempt has been made to estimate the stress relaxation time of normal and abnormal breast mimicking phantom using laser speckle image correlation. Phantoms mimicking normal breast is prepared and subjected to precise mechanical compression. The phantom is illuminated by a Helium Neon laser and by using a CCD camera, a sequence of strained phantom speckle images are captured and correlated by the image mean intensity value at specific time intervals. From the relation between mean intensity versus time, tissue stress relaxation time is quantified. Experiments were repeated for phantoms with increased stiffness mimicking abnormal tissue for similar ranges of applied loading. Results shows that phantom with more stiffness representing abnormal tissue shows uniform relaxation for varying load of the selected range, whereas phantom with less stiffness representing normal tissue shows irregular behavior for varying loadings in the given range.

Update on Breast Cancer Detection Using Comb-Push Ultrasound Shear Elastography.

PubMed

Denis, Max; Bayat, Mahdi; Mehrmohammadi, Mohammad; Gregory, Adriana; Song, Pengfei; Whaley, Dana H; Pruthi, Sandhya; Chen, Shigao; Fatemi, Mostafa; Alizad, Azra

2015-09-01

In this work, tissue stiffness estimates are used to differentiate between benign and malignant breast masses in a group of pre-biopsy patients. The rationale is that breast masses are often stiffer than healthy tissue; furthermore, malignant masses are stiffer than benign masses. The comb-push ultrasound shear elastography (CUSE) method is used to noninvasively assess a tissue's mechanical properties. CUSE utilizes a sequence of simultaneous multiple laterally spaced acoustic radiation force (ARF) excitations and detection to reconstruct the region of interest (ROI) shear wave speed map, from which a tissue stiffness property can be quantified. In this study, the tissue stiffnesses of 73 breast masses were interrogated. The mean shear wave speeds for benign masses (3.42 ± 1.32 m/s) were lower than malignant breast masses (6.04 ± 1.25 m/s). These speed values correspond to higher stiffness in malignant breast masses (114.9 ± 40.6 kPa) than benign masses (39.4 ± 28.1 kPa and p <; 0.001), when tissue elasticity is quantified by Young's modulus. A Young's modulus >83 kPa is established as a cut-off value for differentiating between malignant and benign suspicious breast masses, with a receiver operating characteristic curve (ROC) of 89.19% sensitivity, 88.69% specificity, and 0.911 for the area under the curve (AUC).

Summer Student Breast Cancer Research Training Program

DTIC Science & Technology

2006-05-01

by phosphatidic acid in Jurkat leukemic cells: the role of protein phos- phatase-1. Biochim Biophys Acta 2001;1541:188–200. 25. Tonnetti L, Veri MC...Asian mushroom, Ganoderma lucidum, upon highly invasive breast cancer cells, on the role of omega-3 fatty acids in preventing and treating breast...research training; breast cancer; fatty acids and prevention; nutrition and prevention; alternative prevention 16. SECURITY CLASSIFICATION OF

TH-AB-209-08: Next Generation Dedicated 3D Breast Imaging with XACT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, S; Chen, J; Samant, P

Purpose: Exposure to radiation increases the risk of cancer. We have designed a new imaging paradigm, X-ray induced acoustic computed tomography (XACT). Applying this innovative technology to breast imaging, an X-ray exposure can generate a 3D acoustic image, which dramatically reduces the radiation dose to patients when compared to conventional breast CT. Methods: Theoretical calculations are done to determine the appropriate X-ray energy and ultrasound frequency in breast XACT imaging. A series of breast CT image along the coronal plane from a patient with calcifications in the breast tissue are used as the source image. HU value based segmentation ismore » done to distinguish the skin, adipose tissue, glandular tissue, breast calcification, and chest bone from each CT image. X-ray dose deposition in each pixel is calculated based on the tissue type by using GEANT4 Monte Carlo toolkits. The initial pressure rise caused by X-ray energy deposition is calculated according to tissue properties. Then, the X-ray induced acoustic wave propagation is simulated by K-WAVE toolkit. Breast XACT images are reconstructed from the recorded time-dependent ultrasound waves. Results: For imaging a breast with large size (16cm in diameter at chest wall), the photon energy of X-ray source and the central frequency of ultrasound detector is determined as 20keV and 5.5MHz. Approximately 10 times contrast between a calcification and the breast tissue can be acquire from XACT image. The calcification can be clearly identified from the reconstructed XACT image. Conclusion: XACT technique takes the advantages of X-ray absorption contrast and high ultrasonic resolution. With the proposed innovative technology, one can potentially reduce radiation dose to patient in 3D breast imaging as compared with current x-ray modalities, while still maintaining high imaging contrast and spatial resolution.« less

Breast Cancer Research at NASA

NASA Technical Reports Server (NTRS)

1998-01-01

Time-lapse exposure depicts Bioreactor rotation. NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cells (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunourous tissues.

Breast Cancer Research at NASA

NASA Technical Reports Server (NTRS)

1998-01-01

Human primary breast tumor cells after 49 days of growth in a NASA Bioreactor. Tumor cells aggregate on microcarrier beads (indicated by arrow). NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cell (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunorous tissue. Credit: Dr. Jearne Becker, University of South Florida

Predicting Time-to-Relapse in Breast Cancer Using Neural Networks

DTIC Science & Technology

1997-12-01

CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 118. SECURITY CLASSIFICATION OF THIS PAGE Unclassified 19. SECURITY CLASSIFICATION OF...Lowell WE, and Davis GL. A neural network that predicts psychiatric length of stay. MD Computing 10:87-92, 1993. Ebell MH. Artificial neural netowrks

The prognostic value of histidine-rich glycoprotein RNA in breast tissue using unmodified gold nanoparticles assay.

PubMed

Eissa, Sanaa; Azzazy, Hassan M E; Matboli, Marwa; Shawky, Sherif M; Said, Hebatallah; Anous, Fatin A

2014-09-01

The aim of is this study is to explore the role of tissue histidine-rich glycoprotein (HRG) RNA as a promising clinically useful biomarker for breast cancer patients prognosis using nanogold assay. Expression of the HRG RNA was assessed by gold nanoparticles and conventional RT-PCR after purification by magnetic nanoparticles in breast tissue samples. The study included 120 patients, 60 of which were histologically proven breast carcinoma cases, 30 had benign breast lesions and 30 were healthy individuals who had undergone reductive plastic surgery. ER, PR and HER2 status were also investigated. The prognostic significance of tissue HRG RNA expression in breast cancer was explored. The magnetic nanoparticles coated with specific thiol modified oligonucleotide probe were used successfully in purification of HRG RNA from breast tissue total RNAs with satisfactory yield. The developed HRG AuNPs assay had a sensitivity and a specificity of 90 %, and a detection limit of 1.5 nmol/l. The concordance rate between the HRG AuNPs assay with RT-PCR after RNA purification using magnetic nanoparticles was 93.3 %. The median follow-up period was 60 months. Among traditional prognostic biomarkers, HRG was a significant independent prognostic marker in relapse-free survival (RFS). HRG RNA is an independent prognostic marker for breast cancer and can be detected using gold NPs assay, which is rapid, sensitive, specific, inexpensive to extend the value for breast cancer prognosis.

Oxidative Stress and Metabolic Perturbations in Wooden Breast Disorder in Chickens.

PubMed

Abasht, Behnam; Mutryn, Marie F; Michalek, Ryan D; Lee, William R

2016-01-01

This study was conducted to characterize metabolic features of the breast muscle (pectoralis major) in chickens affected with the Wooden Breast myopathy. Live birds from two purebred chicken lines and one crossbred commercial broiler population were clinically examined by manual palpation of the breast muscle (pectoralis major) at 47-48 days of age. Metabolite abundance was determined by gas chromatography/mass spectrometry (GC/MS) and liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) using breast muscle tissue samples from 16 affected and 16 unaffected chickens. Muscle glycogen content was also quantified in breast muscle tissue samples from affected and unaffected chickens. In total, levels of 140 biochemicals were significantly different (FDR<0.1 and fold-change A/U>1.3 or <0.77) between affected and unaffected chickens. Glycogen content measurements were considerably lower (1.7-fold) in samples taken from Wooden Breast affected birds when compared with samples from unaffected birds. Affected tissues exhibited biomarkers related to increased oxidative stress, elevated protein levels, muscle degradation, and altered glucose utilization. Affected muscle also showed elevated levels of hypoxanthine, xanthine, and urate molecules, the generation of which can contribute to altered redox homeostasis. In conclusion, our findings show that Wooden Breast affected tissues possess a unique metabolic signature. This unique profile may identify candidate biomarkers for diagnostic utilization and provide mechanistic insight into altered biochemical processes contributing to tissue hardening associated with the Wooden Breast myopathy in commercial chickens.

Oxidative Stress and Metabolic Perturbations in Wooden Breast Disorder in Chickens

PubMed Central

Abasht, Behnam; Mutryn, Marie F.; Michalek, Ryan D.; Lee, William R.

2016-01-01

This study was conducted to characterize metabolic features of the breast muscle (pectoralis major) in chickens affected with the Wooden Breast myopathy. Live birds from two purebred chicken lines and one crossbred commercial broiler population were clinically examined by manual palpation of the breast muscle (pectoralis major) at 47–48 days of age. Metabolite abundance was determined by gas chromatography/mass spectrometry (GC/MS) and liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) using breast muscle tissue samples from 16 affected and 16 unaffected chickens. Muscle glycogen content was also quantified in breast muscle tissue samples from affected and unaffected chickens. In total, levels of 140 biochemicals were significantly different (FDR < 0.1 and fold-change A/U > 1.3 or < 0.77) between affected and unaffected chickens. Glycogen content measurements were considerably lower (1.7-fold) in samples taken from Wooden Breast affected birds when compared with samples from unaffected birds. Affected tissues exhibited biomarkers related to increased oxidative stress, elevated protein levels, muscle degradation, and altered glucose utilization. Affected muscle also showed elevated levels of hypoxanthine, xanthine, and urate molecules, the generation of which can contribute to altered redox homeostasis. In conclusion, our findings show that Wooden Breast affected tissues possess a unique metabolic signature. This unique profile may identify candidate biomarkers for diagnostic utilization and provide mechanistic insight into altered biochemical processes contributing to tissue hardening associated with the Wooden Breast myopathy in commercial chickens. PMID:27097013

Tamoxifen Downregulates Ets-oncogene Family Members ETV4 and ETV5 in Benign Breast Tissue: Implications for Durable Risk Reduction

PubMed Central

Euhus, David; Bu, Dawei; Xie, Xian-Jin; Sarode, Venetia; Ashfaq, Raheela; Hunt, Kelly; Xia, Weiya; O’Shaughnessy, Joyce; Grant, Michael; Arun, Banu; Dooley, William; Miller, Alexander; Flockhart, David; Lewis, Cheryl

2011-01-01

Background Five years of tamoxifen reduces breast cancer risk by nearly 50% but is associated with significant side-effects and toxicities. A better understanding of the direct and indirect effects of tamoxifen in benign breast tissue could elucidate new mechanisms of breast carcinogenesis, suggest novel chemoprevention targets, and provide relevant early response biomarkers for Phase II prevention trials. Methods Seventy-three women at increased risk for breast cancer were randomized to tamoxifen (20 mg daily) or placebo for three months. Blood and breast tissue samples were collected at baseline and post-treatment. Sixty-nine women completed all study activities (37 tamoxifen and 32 placebo). The selected biomarkers focused on estradiol and IGFs in the blood, DNA methylation and cytology in random periareolar fine needle aspirates, and tissue morphometry, proliferation, apoptosis, and gene expression (microarray and RT-PCR) in the tissue core samples. Results Tamoxifen downregulated ets-oncogene transcription factor family members ETV4 and ETV5 and reduced breast epithelial cell proliferation independent of CYP2D6 genotypes or effects on estradiol, ESR1 or IGFs. Reduction in proliferation was correlated with downregulation of ETV4 and DNAJC12. Tamoxifen reduced the expression of ETV4- and ETV5-regulated genes implicated in epithelial-stromal interaction and tissue remodeling. Three months of tamoxifen did not affect breast tissue composition, cytological atypia, preneoplasia or apoptosis. Conclusions A plausible mechanism for the chemopreventive effects of tamoxifen is restriction of lobular expansion into stroma through downregulation of ETV4 and ETV5. Multipotential progenitor cap cells of terminal end buds may be the primary target. PMID:21778330

Omega-3 and omega-6 Fatty acids in blood and breast tissue of high-risk women and association with atypical cytomorphology.

PubMed

Hidaka, Brandon H; Li, Shengqi; Harvey, Katherine E; Carlson, Susan E; Sullivan, Debra K; Kimler, Bruce F; Zalles, Carola M; Fabian, Carol J

2015-05-01

The ratio of omega-3 to omega-6 fatty acids, especially the long-chain eicosapentaenoic acid (EPA) + docosahexaenoic acid (DHA) to arachidonic acid (AA) ratio, is inversely associated with breast cancer risk. We measured the association between cytologic atypia, a biomarker for short-term risk of breast cancer development, and omega-3 and omega-6 fatty acid intake and levels in blood and breast tissue. Blood and benign breast tissue, sampled by random periareolar fine-needle aspiration (RPFNA), was obtained from 70 women at elevated risk for breast cancer. Self-reported dietary intake was assessed by the NCI's Food Frequency Questionnaire. The fatty acid composition of five lipid compartments, red blood cell, plasma and breast phospholipids, and plasma and breast triaclyglycerides (TAG), was analyzed by gas chromatography as weight percent. Median daily intakes of EPA+DHA and total omega-3 fatty acids were 80 mg and 1.1 g, respectively. The median total omega-3:6 intake ratio was 1:10. Compared with women without atypia, those with cytologic atypia had lower total omega-3 fatty acids in red blood cell and plasma phospholipids and lower omega-3:6 ratios in plasma TAGs and breast TAGs (P < 0.05). The EPA+DHA:AA ratio in plasma TAGs was also lower among women with atypia. This is the first report of associations between tissue levels of omega-3 and omega-6 fatty acids and a reversible tissue biomarker of breast cancer risk. RPFNA cytomorphology could serve as a surrogate endpoint for breast cancer prevention trials of omega-3 fatty acid supplementation. ©2015 American Association for Cancer Research.

Biochemical properties of thyroid peroxidase (TPO) expressed in human breast and mammary-derived cell lines

PubMed Central

Godlewska, Marlena; Krasuska, Wanda

2018-01-01

Thyroid peroxidase (TPO) is an enzyme and autoantigen expressed in thyroid and breast tissues. Thyroid TPO undergoes a complex maturation process however, nothing is known about post-translational modifications of breast-expressed TPO. In this study, we have investigated the biochemical properties of TPO expressed in normal and cancerous human breast tissues, and the maturation process and antigenicity of TPO present in a panel of human breast tissue-derived cell lines. We found that the molecular weight of breast TPO was slightly lower than that of thyroid TPO due to decreased glycosylation and as suggest results of Western blot also shorter amino acid chain. Breast TPO exhibit enzymatic activity and isoelectric point comparable to that of thyroid TPO. The biochemical properties of TPO expressed in mammary cell lines and normal thyrocytes are similar regarding glycan content, molecular weight and isoelectric point. However, no peroxidase activity and dimer formation was detected in any of these cell lines since the majority of TPO protein was localized in the cytoplasmic compartment, and the TPO expression at the cell surface was too low to detect its enzymatic activity. Lactoperoxidase, a protein highly homologous to TPO expressed also in breast tissues, does not influence the obtained data. TPO expressed in the cell lines was recognized by a broad panel of TPO-specific antibodies. Although some differences in biochemical properties between thyroid and breast TPO were observed, they do not seem to be critical for the overall three-dimensional structure. This conclusion is supported by the fact that TPO expressed in breast tissues and cell lines reacts well with conformation-sensitive antibodies. Taking into account a close resemblance between both proteins, especially high antigenicity, future studies should investigate the potential immunotherapies directed against breast-expressed TPO and its specific epitopes. PMID:29513734

Biochemical properties of thyroid peroxidase (TPO) expressed in human breast and mammary-derived cell lines.

PubMed

Godlewska, Marlena; Krasuska, Wanda; Czarnocka, Barbara

2018-01-01

Thyroid peroxidase (TPO) is an enzyme and autoantigen expressed in thyroid and breast tissues. Thyroid TPO undergoes a complex maturation process however, nothing is known about post-translational modifications of breast-expressed TPO. In this study, we have investigated the biochemical properties of TPO expressed in normal and cancerous human breast tissues, and the maturation process and antigenicity of TPO present in a panel of human breast tissue-derived cell lines. We found that the molecular weight of breast TPO was slightly lower than that of thyroid TPO due to decreased glycosylation and as suggest results of Western blot also shorter amino acid chain. Breast TPO exhibit enzymatic activity and isoelectric point comparable to that of thyroid TPO. The biochemical properties of TPO expressed in mammary cell lines and normal thyrocytes are similar regarding glycan content, molecular weight and isoelectric point. However, no peroxidase activity and dimer formation was detected in any of these cell lines since the majority of TPO protein was localized in the cytoplasmic compartment, and the TPO expression at the cell surface was too low to detect its enzymatic activity. Lactoperoxidase, a protein highly homologous to TPO expressed also in breast tissues, does not influence the obtained data. TPO expressed in the cell lines was recognized by a broad panel of TPO-specific antibodies. Although some differences in biochemical properties between thyroid and breast TPO were observed, they do not seem to be critical for the overall three-dimensional structure. This conclusion is supported by the fact that TPO expressed in breast tissues and cell lines reacts well with conformation-sensitive antibodies. Taking into account a close resemblance between both proteins, especially high antigenicity, future studies should investigate the potential immunotherapies directed against breast-expressed TPO and its specific epitopes.

Detection of mitotic nuclei in breast histopathology images using localized ACM and Random Kitchen Sink based classifier.

PubMed

Beevi, K Sabeena; Nair, Madhu S; Bindu, G R

2016-08-01

The exact measure of mitotic nuclei is a crucial parameter in breast cancer grading and prognosis. This can be achieved by improving the mitotic detection accuracy by careful design of segmentation and classification techniques. In this paper, segmentation of nuclei from breast histopathology images are carried out by Localized Active Contour Model (LACM) utilizing bio-inspired optimization techniques in the detection stage, in order to handle diffused intensities present along object boundaries. Further, the application of a new optimal machine learning algorithm capable of classifying strong non-linear data such as Random Kitchen Sink (RKS), shows improved classification performance. The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS) dataset provided for MITOS-ATYPIA CONTEST 2014. The proposed framework achieved 95% recall, 98% precision and 96% F-score.

Tumor Heterogeneity in Breast Cancer

PubMed Central

Turashvili, Gulisa; Brogi, Edi

2017-01-01

Breast cancer is a heterogeneous disease and differs greatly among different patients (intertumor heterogeneity) and even within each individual tumor (intratumor heterogeneity). Clinical and morphologic intertumor heterogeneity is reflected by staging systems and histopathologic classification of breast cancer. Heterogeneity in the expression of established prognostic and predictive biomarkers, hormone receptors, and human epidermal growth factor receptor 2 oncoprotein is the basis for targeted treatment. Molecular classifications are indicators of genetic tumor heterogeneity, which is probed with multigene assays and can lead to improved stratification into low- and high-risk groups for personalized therapy. Intratumor heterogeneity occurs at the morphologic, genomic, transcriptomic, and proteomic levels, creating diagnostic and therapeutic challenges. Understanding the molecular and cellular mechanisms of tumor heterogeneity that are relevant to the development of treatment resistance is a major area of research. Despite the improved knowledge of the complex genetic and phenotypic features underpinning tumor heterogeneity, there has been only limited advancement in diagnostic, prognostic, or predictive strategies for breast cancer. The current guidelines for reporting of biomarkers aim to maximize patient eligibility for targeted therapy, but do not take into account intratumor heterogeneity. The molecular classification of breast cancer is not implemented in routine clinical practice. Additional studies and in-depth analysis are required to understand the clinical significance of rapidly accumulating data. This review highlights inter- and intratumor heterogeneity of breast carcinoma with special emphasis on pathologic findings, and provides insights into the clinical significance of molecular and cellular mechanisms of heterogeneity. PMID:29276709

MiR-300 regulate the malignancy of breast cancer by targeting p53.

PubMed

Xu, Xiao-Heng; Li, Da-Wei; Feng, Hui; Chen, Hong-Mei; Song, Yan-Qiu

2015-01-01

In this study, we investigated the role of miR-300 in regulating cell proliferation and invasion of breast cancer (BC) cells. MicroRNA and protein expression patterns were compared between breast cancer tissue and normal tissue and between two different prognostic groups. The up-regulation of miR-300 was confirmed by real-time reverse transcription polymerase chain reaction and its expression was analyzed in MCF-7 breast cancer cells. We observed that miR-300 expression was frequently and dramatically up-regulated in human breast cancer tissues and cell lines compared with the matched adjacent normal tissues and cells. We further showed that transient and stable over-expression of miR-300 could promote cell proliferation and cell cycle progression. Moreover, p53, a key inhibitor of cell cycle, was verified as a direct target of miR-300, suggesting that miR-300 might promote breast cancer cell proliferation and invasion by regulating p53 expression. Our findings indicated that miR-300 up-regulation might exert some sort of antagonistic function by targeting p53 in breast cancer cell proliferation during breast tumorigenesis.

MiR-300 regulate the malignancy of breast cancer by targeting p53

PubMed Central

Xu, Xiao-Heng; Li, Da-Wei; Feng, Hui; Chen, Hong-Mei; Song, Yan-Qiu

2015-01-01

Objective: In this study, we investigated the role of miR-300 in regulating cell proliferation and invasion of breast cancer (BC) cells. Methods: MicroRNA and protein expression patterns were compared between breast cancer tissue and normal tissue and between two different prognostic groups. The up-regulation of miR-300 was confirmed by real-time reverse transcription polymerase chain reaction and its expression was analyzed in MCF-7 breast cancer cells. Results: We observed that miR-300 expression was frequently and dramatically up-regulated in human breast cancer tissues and cell lines compared with the matched adjacent normal tissues and cells. We further showed that transient and stable over-expression of miR-300 could promote cell proliferation and cell cycle progression. Moreover, p53, a key inhibitor of cell cycle, was verified as a direct target of miR-300, suggesting that miR-300 might promote breast cancer cell proliferation and invasion by regulating p53 expression. Conclusion: Our findings indicated that miR-300 up-regulation might exert some sort of antagonistic function by targeting p53 in breast cancer cell proliferation during breast tumorigenesis. PMID:26221232

Thyroid peroxidase (TPO) expressed in thyroid and breast tissues shows similar antigenic properties

PubMed Central

Godlewska, Marlena; Arczewska, Katarzyna D.; Rudzińska, Magdalena; Łyczkowska, Anna; Krasuska, Wanda; Hanusek, Karolina; Ruf, Jean; Kiedrowski, Mirosław

2017-01-01

Background Thyroid peroxidase (TPO) is essential for physiological function of the thyroid gland. The high prevalence of thyroid peroxidase antibodies (TPOAbs) in patients with breast cancer and their protective role had previously been demonstrated, indicating a link between breast cancer and thyroid autoimmunity. Recently, TPO was shown to be present in breast cancer tissue samples but its antigenicity has not been analyzed. Methods In this study, we investigated TPO expression levels in a series of fifty-six breast cancer samples paired with normal (peri-tumoral) tissue and its antigenic activity using a panel of well-characterized murine anti-human TPOAbs. Results We have shown that TPO transcripts were present in both normal and cancer tissue samples, although the amounts in the latter were reduced. Additionally, we observed that TPO levels are lower in more advanced cancers. TPO protein expression was confirmed in all tissue samples, both normal and cancerous. We also found that the antigenicity of the immunodominant regions (IDRs) in breast TPO resembles that of thyroid TPO, which is crucial for effective interactions with human TPOAbs. Conclusions Expression of TPO in breast cancer together with its antigenic activity may have beneficial effects in TPOAb-positive breast cancer patients. However, further studies are needed to confirm the beneficial role of TPOAbs and to better understand the underlying mechanism. PMID:28575127

Automated assessment of breast tissue density in non-contrast 3D CT images without image segmentation based on a deep CNN

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Kano, Takuya; Koyasu, Hiromi; Li, Shuo; Zhou, Xinxin; Hara, Takeshi; Matsuo, Masayuki; Fujita, Hiroshi

2017-03-01

This paper describes a novel approach for the automatic assessment of breast density in non-contrast three-dimensional computed tomography (3D CT) images. The proposed approach trains and uses a deep convolutional neural network (CNN) from scratch to classify breast tissue density directly from CT images without segmenting the anatomical structures, which creates a bottleneck in conventional approaches. Our scheme determines breast density in a 3D breast region by decomposing the 3D region into several radial 2D-sections from the nipple, and measuring the distribution of breast tissue densities on each 2D section from different orientations. The whole scheme is designed as a compact network without the need for post-processing and provides high robustness and computational efficiency in clinical settings. We applied this scheme to a dataset of 463 non-contrast CT scans obtained from 30- to 45-year-old-women in Japan. The density of breast tissue in each CT scan was assigned to one of four categories (glandular tissue within the breast <25%, 25%-50%, 50%-75%, and >75%) by a radiologist as ground truth. We used 405 CT scans for training a deep CNN and the remaining 58 CT scans for testing the performance. The experimental results demonstrated that the findings of the proposed approach and those of the radiologist were the same in 72% of the CT scans among the training samples and 76% among the testing samples. These results demonstrate the potential use of deep CNN for assessing breast tissue density in non-contrast 3D CT images.

Breast Cancer Research at NASA

NASA Technical Reports Server (NTRS)

1998-01-01

NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cells (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunourous tissues. Here, two High-Aspect Ratio Vessels turn at about 12 rmp to keep breast tissue constructs suspended inside the culture media. Syringes allow scientists to pull for analysis during growth sequences. The tube in the center is a water bubbler that dehumidifies the air to prevent evaporation of the media and thus the appearance of destructive bubbles in the bioreactor.

Breast Cancer Research at NASA

NASA Technical Reports Server (NTRS)

1998-01-01

Isolation of human mammary epithelial cells (HMEC) from breast cancer susceptible tissue. Outgrowth of cells from duct element in upper right corner cultured in a standard dish; most cells spontaneously die during early cell divisions, but a few will establish long-term growth. NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cell (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunorous tissue. Credit: Dr. Robert Tichmond, NASA/Marshall Space Flight Center (MSFC).

Expression of metalloprotease insulin-degrading enzyme insulysin in normal and malignant human tissues.

PubMed

Yfanti, Christina; Mengele, Karin; Gkazepis, Apostolos; Weirich, Gregor; Giersig, Cecylia; Kuo, Wen-Liang; Tang, Wei-Jen; Rosner, Marsha; Schmitt, Manfred

2008-10-01

Insulin-degrading enzyme (IDE, insulysin, insulinase; EC 3.4.22.11), a thiol metalloendopeptidase, is involved in intracellular degradation of insulin, thereby inhibiting its translocation and accumulation to the nucleus. Recently, protein expression of IDE has been demonstrated in the epithelial ducts of normal breast and breast cancer tissue. Utilizing four different antibodies generated against different epitopes of the IDE molecule, we performed Western blot analysis and immunohistochemical staining on several normal human tissues, on a plethora of tumor cell lines of different tissue origin, and on malignant breast and ovarian tissue. Applying the four IDE-directed antibodies, we demonstrated IDE expression at the protein level, by means of immunoblotting and immunocytochemistry, in each of the tumor cell lines analyzed. Insulin-degrading enzyme protein expression was found in normal tissues of the kidney, liver, lung, brain, breast and skeletal muscle, as well as in breast and ovarian cancer tissues. Immunohistochemical visualization of IDE indicated cytoplasmic localization of IDE in each of the cell lines and tissues assessed. In conclusion, we performed for the first time a wide-ranging survey on IDE protein expression in normal and malignant tissues and cells thus extending our knowledge on the cellular and tissue distribution of IDE, an enzyme which to date has mainly been studied in connection with Alzheimer's disease and diabetes but not in cancer.

Benign Breast Conditions

MedlinePlus

... common benign breast condition in men is called gynecomastia. This condition causes enlarged breast tissue. Female breasts ... with these less common, benign breast conditions. Male gynecomastia: A man’s breast will feel swollen and tender ...

Nearest Neighbor Classification Using a Density Sensitive Distance Measurement

DTIC Science & Technology

2009-09-01

both the proposed density sensitive distance measurement and Euclidean distance are compared on the Wisconsin Diagnostic Breast Cancer dataset and...proposed density sensitive distance measurement and Euclidean distance are compared on the Wisconsin Diagnostic Breast Cancer dataset and the MNIST...35 1. The Wisconsin Diagnostic Breast Cancer (WDBC) Dataset..........35 2. The

Classification of broiler breast fillets according to storage and to freeze-thaw treatment using near infrared spectroscopy and multivariate analysis

USDA-ARS?s Scientific Manuscript database

Visible/near-infrared (NIR) spectroscopy has shown potential for successfully classifying broiler breast fillets according to their texture properties. Freshness and shelf life are also important quality characteristics of boneless skinless chicken breast products in the marketplace. This study deal...

The hallmarks of breast cancer by Raman spectroscopy

NASA Astrophysics Data System (ADS)

Abramczyk, H.; Surmacki, J.; Brożek-Płuska, B.; Morawiec, Z.; Tazbir, M.

2009-04-01

This paper presents new biological results on ex vivo breast tissue based on Raman spectroscopy and demonstrates its power as diagnostic tool with the key advantage in breast cancer research. The results presented here demonstrate the ability of Raman spectroscopy to accurately characterize cancer tissue and distinguish between normal, malignant and benign types. The goal of the paper is to develop the diagnostic ability of Raman spectroscopy in order to find an optical marker of cancer in the breast tissue. Applications of Raman spectroscopy in breast cancer research are in the early stages of development in the world. To the best of our knowledge, this paper is one of the most statistically reliable reports (1100 spectra, 99 patients) on Raman spectroscopy-based diagnosis of breast cancers among the world women population.

KernelADASYN: Kernel Based Adaptive Synthetic Data Generation for Imbalanced Learning

DTIC Science & Technology

2015-08-17

eases [35], Indian liver patient dataset (ILPD) [36], Parkinsons dataset [37], Vertebral Column dataset [38], breast cancer dataset [39], breast tissue...Both the data set of Breast Cancer and Breast Tissue aim to predict the patient is normal or abnormal according to the measurements. The data set SPECT...9, pp. 1263–1284, 2009. [3] M. Elter, R. Schulz-Wendtland, and T. Wittenberg, “The prediction of breast cancer biopsy outcomes using two cad

Phase Contrast Microscopy Analysis of Breast Tissue

PubMed Central

Wells, Wendy A.; Wang, Xin; Daghlian, Charles P.; Paulsen, Keith D.; Pogue, Brian W.

2010-01-01

OBJECTIVE To assess how optical scatter properties in breast tissue, as measured by phase contrast microscopy and interpreted pathophysiologically, might be exploited as a diagnostic tool to differentiate cancer from benign tissue. STUDY DESIGN We evaluated frozen human breast tissue sections of adipose tissue, normal breast parenchyma, benign fibroadenoma tumors and noninvasive and invasive malignant cancers by phase contrast microscopy through quantification of grayscale values, using multiple regions of interest (ROI). Student’s t tests were performed on phase contrast measures across diagnostic categories testing data from individual cases; all ROI data were used as separate measures. RESULTS Stroma demonstrated significantly higher scatter intensity than did epithelium, with lower scattering in tumor-associated stroma as compared with normal or benign-associated stroma. Measures were comparable for invasive and noninvasive malignant tumors but were higher than those found in benign tumors and were lowest in adipose tissue. CONCLUSION Significant differences were found in scatter coefficient properties of epithelium and stroma across diagnostic categories of breast tissue, particularly between benign and malignant-associated stroma. Improved understanding of how scatter properties correlate with morphologic criteria used in routine pathologic diagnoses could have a significant clinical impact as developing optical technology allows macroscopic in situ phase contrast imaging. PMID:19736867

Quantitative breast tissue characterization using grating-based x-ray phase-contrast imaging

NASA Astrophysics Data System (ADS)

Willner, M.; Herzen, J.; Grandl, S.; Auweter, S.; Mayr, D.; Hipp, A.; Chabior, M.; Sarapata, A.; Achterhold, K.; Zanette, I.; Weitkamp, T.; Sztrókay, A.; Hellerhoff, K.; Reiser, M.; Pfeiffer, F.

2014-04-01

X-ray phase-contrast imaging has received growing interest in recent years due to its high capability in visualizing soft tissue. Breast imaging became the focus of particular attention as it is considered the most promising candidate for a first clinical application of this contrast modality. In this study, we investigate quantitative breast tissue characterization using grating-based phase-contrast computed tomography (CT) at conventional polychromatic x-ray sources. Different breast specimens have been scanned at a laboratory phase-contrast imaging setup and were correlated to histopathology. Ascertained tumor types include phylloides tumor, fibroadenoma and infiltrating lobular carcinoma. Identified tissue types comprising adipose, fibroglandular and tumor tissue have been analyzed in terms of phase-contrast Hounsfield units and are compared to high-quality, high-resolution data obtained with monochromatic synchrotron radiation, as well as calculated values based on tabulated tissue properties. The results give a good impression of the method’s prospects and limitations for potential tumor detection and the associated demands on such a phase-contrast breast CT system. Furthermore, the evaluated quantitative tissue values serve as a reference for simulations and the design of dedicated phantoms for phase-contrast mammography.

High expressions of LDHA and AMPK as prognostic biomarkers for breast cancer.

PubMed

Huang, Xiaojia; Li, Xing; Xie, Xinhua; Ye, Feng; Chen, Bo; Song, Cailu; Tang, Hailin; Xie, Xiaoming

2016-12-01

The purpose of this study was to investigate the potential correlation between lactate dehydrogenase A (LDHA) and AMP-activated protein kinase (AMPK) and their clinicopathologic significance in breast cancer. Western blot and qRT-PCR were used to detect the expression levels of LDHA and AMPK in eight breast cancer lines and eight breast cancer tissues. In addition, LDHA and AMPK were detected by immunohistochemistry (IHC) using breast cancer tissue microarrays (TMAs) of 112 patients. The association between LDHA and AMPK expression levels was statistically analyzed. So were the prognostic roles and clinicopathologic significances in breast cancer. The expression levels of LDHA and AMPK were relatively higher in triple-negative breast cancer (TNBC) cell lines than in non-triple-negative breast cancer (NTNBC) cell lines. LDHA and AMPK were also further up-regulated in TNBC tissues than in NTNBC tissues. Correlation analysis showed a positive correlation between LDHA and AMPK expression levels. Expression of LDHA and AMPK were significantly correlated with TNM stage, distant metastasis, Ki67 status and survival outcomes of patients. Patients with both positive expression of LDHA and AMPK showed shorter overall survival (OS) and disease-free survival (DFS). These findings improve our understanding of the expression pattern of LDHA and AMPK in breast cancer and clarify the role of LDHA and AMPK as promising prognostic biomarkers for breast cancer. Copyright © 2016. Published by Elsevier Ltd.

Methylation of PLCD1 and adenovirus-mediated PLCD1 overexpression elicits a gene therapy effect on human breast cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mu, Haixi; Department of Endocrine and breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016; Wang, Na

Our previous study showed that PLCD1 significantly decreases cell proliferation and affects cell cycle progression in breast cancer cells. In the present study, we aimed to investigate its functional and molecular mechanisms, and whether or not can become a new target for gene therapies. We found reduced PLCD1 protein expression in breast tumor tissues compared with paired surgical margin tissues. PLCD1 promoter CpG methylation was detected in 55 of 96 (57%) primary breast tumors, but not in surgical-margin tissues and normal breast tissues. Ectopic expression of PLCD1 inhibited breast tumor cell proliferation in vivo by inducing apoptosis and suppressed tumormore » cell migration by regulating cytoskeletal reorganization proteins including RhoA and phospho-cofilin. Furthermore, we found that PLCD1 induced p53 accumulation, increased p27 and p21 protein levels, and cleaved PARP. Finally, we constructed an adenoviral vector expressing PLCD1 (AdH5-PLCD1), which exhibited strong cytotoxicity in breast cancer cells. Our findings provide insights into the development of PLCD1 gene therapies for breast cancer and perhaps, other human cancers. - Highlights: • PLCD1 is downregulated via hypermethylation in breast cancer. • PLCD1 suppressed cell migration by regulating cytoskeletal reorganization proteins. • Adenovirus AdHu5-PLCD1 may be a novel therapeutic option for breast cancer.« less

Epigenetic silencing of ADAMTS18 promotes cell migration and invasion of breast cancer through AKT and NF-κB signaling.

PubMed

Xu, Hongying; Xiao, Qian; Fan, Yu; Xiang, Tingxiu; Li, Chen; Li, Chunhong; Li, Shuman; Hui, Tianli; Zhang, Lu; Li, Hongzhong; Li, Lili; Ren, Guosheng

2017-06-01

ADAMTS18 dysregulation plays an important role in many disease processes including cancer. We previously found ADAMTS18 as frequently methylated tumor suppressor gene (TSG) for multiple carcinomas, however, its biological functions and underlying molecular mechanisms in breast carcinogenesis remain unknown. Here, we found that ADAMTS18 was silenced or downregulated in breast cancer cell lines. ADAMTS18 was reduced in primary breast tumor tissues as compared with their adjacent noncancer tissues. ADAMTS18 promoter methylation was detected in 70.8% of tumor tissues by methylation-specific PCR, but none of the normal tissues. Demethylation treatment restored ADAMTS18 expression in silenced breast cell lines. Ectopic expression of ADAMTS18 in breast tumor cells resulted in inhibition of cell migration and invasion. Nude mouse model further confirmed that ADAMTS18 suppressed breast cancer metastasis in vivo. Further mechanistic studies showed that ADAMTS18 suppressed epithelial-mesenchymal transition (EMT), further inhibited migration and invasion of breast cancer cells. ADAMT18 deregulated AKT and NF-κB signaling, through inhibiting phosphorylation levels of AKT and p65. Thus, ADAMTS18 as an antimetastatic tumor suppressor antagonizes AKT and NF-κB signaling in breast tumorigenesis. Its methylation could be a potential tumor biomarker for breast cancer. © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Minireview: The Androgen Receptor in Breast Tissues: Growth Inhibitor, Tumor Suppressor, Oncogene?

PubMed Central

Hickey, T. E.; Robinson, J. L. L.; Carroll, J. S.

2012-01-01

Androgen receptor (AR) signaling exerts an antiestrogenic, growth-inhibitory influence in normal breast tissue, and this role may be sustained in estrogen receptor α (ERα)-positive luminal breast cancers. Conversely, AR signaling may promote growth of a subset of ERα-negative, AR-positive breast cancers with a molecular apocrine phenotype. Understanding the molecular mechanisms whereby androgens can elicit distinct gene expression programs and opposing proliferative responses in these two breast cancer phenotypes is critical to the development of new therapeutic strategies to target the AR in breast cancer. PMID:22745190

3D BREAST TISSUE CO-CULTURES FOR SCREENING MAMMARY CARCINOGENS - PHASE I

EPA Science Inventory

Breast cancer is not a disease of individual cells, but principally a failure of cells and tissues to communicate properly. One communication mechanism that is frequently disrupted in breast cancer involves the hormone estrogen. Despite recognition that exposure to compound...

Expression of Estrogen Receptors in Relation to Hormone Levels and the Nottingham Prognostic Index.

PubMed

Fahlén, Mia; Zhang, Hua; Löfgren, Lars; Masironi, Britt; VON Schoultz, Eva; VON Schoultz, B O; Sahlin, Lena

2016-06-01

Estrogen hormones have a large impact on both normal development and tumorigenesis of the breast. Breast tissue samples from 49 women undergoing surgery were included. The estrogen receptors (ERα and ERβ), ERα36 and G-coupled estrogen receptor-1 (GPER) were determined in benign and malignant breast tissue. The ERα36 and ERα mRNA levels were highest in malignant tumors. Stromal ERβ immunostaining in benign tumors was higher than in the paired normal tissue. GPER expression was lowest in benign tumors. In the malignant tumors, the Nottingham Prognostic Index (NPI) correlated positively with stromal GPER and the serum testosterone level. The serum insulin-like growth factor-1 (IGF-1) level correlated negatively with GPER mRNA and glandular ERα. The expression of ERα36 is stronger in malignant breast tissue. The strong positive correlation between NPI and GPER in malignant breast stroma indicates an important role for GPER in breast cancer prognosis. Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Imaging of breast cancer with mid- and long-wave infrared camera.

PubMed

Joro, R; Lääperi, A-L; Dastidar, P; Soimakallio, S; Kuukasjärvi, T; Toivonen, T; Saaristo, R; Järvenpää, R

2008-01-01

In this novel study the breasts of 15 women with palpable breast cancer were preoperatively imaged with three technically different infrared (IR) cameras - micro bolometer (MB), quantum well (QWIP) and photo voltaic (PV) - to compare their ability to differentiate breast cancer from normal tissue. The IR images were processed, the data for frequency analysis were collected from dynamic IR images by pixel-based analysis and from each image selectively windowed regional analysis was carried out, based on angiogenesis and nitric oxide production of cancer tissue causing vasomotor and cardiogenic frequency differences compared to normal tissue. Our results show that the GaAs QWIP camera and the InSb PV camera demonstrate the frequency difference between normal and cancerous breast tissue; the PV camera more clearly. With selected image processing operations more detailed frequency analyses could be applied to the suspicious area. The MB camera was not suitable for tissue differentiation, as the difference between noise and effective signal was unsatisfactory.

Adipose-Derived Stem Cells in Novel Approaches to Breast Reconstruction: Their Suitability for Tissue Engineering and Oncological Safety.

PubMed

O'Halloran, Niamh; Courtney, Donald; Kerin, Michael J; Lowery, Aoife J

2017-01-01

Adipose-derived stem cells (ADSCs) are rapidly becoming the gold standard cell source for tissue engineering strategies and hold great potential for novel breast reconstruction strategies. However, their use in patients with breast cancer is controversial and their oncological safety, particularly in relation to local disease recurrence, has been questioned. In vitro, in vivo, and clinical studies using ADSCs report conflicting data on their suitability for adipose tissue regeneration in patients with cancer. This review aims to provide an overview of the potential role for ADSCs in breast reconstruction and to examine the evidence relating to the oncologic safety of their use in patients with breast cancer.

Breast Cancer Research at NASA

NASA Technical Reports Server (NTRS)

1998-01-01

Human primary breast tumor cells after 56 days of culture in a NASA Bioreactor. A cross-section of a construct, grown from surgical specimens of brease cancer, stained for microscopic examination, reveals areas of tumor cells dispersed throughout the non-epithelial cell background. The arrow denotes the foci of breast cancer cells. NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cell (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunorous tissue. Credit: Dr. Jearne Becker, University of South Florida

An Examination of Ultrasound Measured Tissue Perfusion on Breast Cancer

DTIC Science & Technology

1998-12-01

is similar to those of the study by Ivey et al. [9] in which high intensity fields were used to produce cavitation bubbles for ultrasound contrast...ft * * AD AWARD NUMBER DAMD17-94-J-4144 TITLE: ^ Examination of Ultrasound Measured Tissue Perfusion on Breast Cancer...Examination of Ultrasound Measured Tissue Perfusion on Breast Cancer 3. REPORT TYPE AND DATES COVERED Final (1 Jun 94 - 30 Nov 98) 5. FUNDING

Cyclin-dependent kinase 11p110 (CDK11p110) is crucial for human breast cancer cell proliferation and growth

PubMed Central

Zhou, Yubing; Han, Chao; Li, Duolu; Yu, Zujiang; Li, Fengmei; Li, Feng; An, Qi; Bai, Huili; Zhang, Xiaojian; Duan, Zhenfeng; Kan, Quancheng

2015-01-01

Cyclin-dependent kinases (CDKs) play important roles in the development of many types of cancers by binding with their paired cyclins. However, the function of CDK11 larger protein isomer, CDK11p110, in the tumorigenesis of human breast cancer remains unclear. In the present study, we explored the effects and molecular mechanisms of CDK11p110 in the proliferation and growth of breast cancer cells by determining the expression of CDK11p110 in breast tumor tissues and examining the phenotypic changes of breast cancer cells after CDK11p110 knockdown. We found that CDK11p110 was highly expressed in breast tumor tissues and cell lines. Tissue microarray analysis showed that elevated CDK11p110 expression in breast cancer tissues significantly correlated with poor differentiation, and was also associated with advanced TNM stage and poor clinical prognosis for breast cancer patients. In vitro knockdown of CDK11p110 by siRNA significantly inhibited cell growth and migration, and dramatically induced apoptosis in breast cancer cells. Flow cytometry demonstrated that cells were markedly arrested in G1 phase of the cell cycle after CDK11p110 downregulation. These findings suggest that CDK11p110 is critical for the proliferation and growth of breast cancer cells, which highlights CDK11p110 may be a promising therapeutic target for the treatment of breast cancer. PMID:25990212

Methylation status and protein expression of RASSF1A in breast cancer patients.

PubMed

Hagrass, Hoda A; Pasha, Heba F; Shaheen, Mohamed A; Abdel Bary, Eman H; Kassem, Rasha

2014-01-01

Recently genetics and epigenetics alterations have been found to be characteristic of malignancy and hence can be used as targets for detection of neoplasia. RAS association domain family protein 1A (RASSF1A) gene hypermethylation has been a subject of interest in recent researches on cancer breast patients. The aim of the present study was to evaluate whether RASSF1A methylation status and RASSF1A protein expression are associated with the major clinico-pathological parameters. One hundred and twenty breast cancer Egyptian patients and 100-control subjects diagnosed with benign lesions of the breast were enrolled in this study. We evaluated RASSF1A methylation status in tissue and serum samples using Methyl specific PCR together with RASSF1A protein expression in tissues by immunohistochemistry. Results were studied in relation to known prognostic clinicopathological features in breast cancer. Frequency of RASSF1A methylation in tissues and serum were 70 and 63.3 % respectively and RASSF1A protein expression showed frequency of 46.7 %. There was an association between RASSF1A methylation in tissues, serum and loss of protein expression in tissues with invasive carcinoma, advanced stage breast cancer, L.N. metastasis, ER/PR and HER2 negativity. RASSF1A methylation in serum showed high degree of concordance with methylation in tissues (Kappa = 0.851, P < 0.001). RASSF1A hypermethylation in tissues and serum and its protein expression may be a valid, reliable and sensitive tool for detection and follow up of breast cancer patients.

A Molecular Framework for Understanding DCIS

DTIC Science & Technology

2015-10-01

a precursor to invasive breast cancer. Improvements in early diagnosis have led to increased numbers of DCIS cases, however, we presently have no way...ultimately alter the course of treatment for women with a diagnosis of DCIS. 15. SUBJECT TERMS Breast cancer, DCIS 16. SECURITY CLASSIFICATION OF: U 17...Ductal Carcinoma (IDC), the most common form of breast cancer. IDC accounts for 80% of all breast cancers, predominantly affecting women aged 55 and

Diagnostic value of coustic radiation force impulse for BI-RADS category 4 breast lesions of different sizes.

PubMed

Wu, Rong

2018-04-14

To determine the diagnostic value of combined conventional ultrasound (US) and acoustic radiation force impulse (ARFI) imaging for the differential diagnosis of BI-RADS category 4 breast lesions of different sizes. From April 2013 to January 2015, 283 patients (with a total of 292 breast lesions) who underwent US and ARFI examination were included in this retrospective study. The SWV for the lesion and adjacent normal breast tissue were measured and the SWV ratio was calculated. VTI grade was also assessed. The lesions were separated into three groups on the basis of size, and two combinations of ARFI parameters (SWV + VTI and SWV ratio + VTI) were applied to reassess the BI-RADS categories. Diagnoses were confirmed by pathological examination after biopsy or surgery. ROC analysis was performed to assess the diagnostic efficiency of each method. The Z test was used to compare the difference between AUC of the two methods. Significant improvement was seen in the diagnostic performance of US with the use of the ARFI parameters SWV + VTI (77/179 [43.0%] of BI-RADS category 4A breast lesions were downgraded) and SWV ratio + VTI (64/179 [35.8%] of BI-RADS category 4A breast lesions were downgraded, including two malignant cases that were misdiagnosed as benign) (P < 0.01). The difference between the performances of the two combinations-SWV + VTI and SWV ratio + VTI-was significant only in breast lesions <10 mm in size, where the AUC of SWV ratio + VTI was significantly greater than the AUC of SWV + VTI (0.929 vs. 0.874; P < 0.01). Combination of US with ARFI can improve diagnostic performance and help avoid unnecessary biopsy in BI-RADS category 4 breast lesions. The combination of SWV ratio + VTI can improve BI-RADS classification of small lesions (<10 mm size).

A new breast cancer risk analysis approach using features extracted from multiple sub-regions on bilateral mammograms

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Tseng, Tzu-Liang B.; Zheng, Bin; Zhang, Jianying; Qian, Wei

2015-03-01

A novel breast cancer risk analysis approach is proposed for enhancing performance of computerized breast cancer risk analysis using bilateral mammograms. Based on the intensity of breast area, five different sub-regions were acquired from one mammogram, and bilateral features were extracted from every sub-region. Our dataset includes 180 bilateral mammograms from 180 women who underwent routine screening examinations, all interpreted as negative and not recalled by the radiologists during the original screening procedures. A computerized breast cancer risk analysis scheme using four image processing modules, including sub-region segmentation, bilateral feature extraction, feature selection, and classification was designed to detect and compute image feature asymmetry between the left and right breasts imaged on the mammograms. The highest computed area under the curve (AUC) is 0.763 ± 0.021 when applying the multiple sub-region features to our testing dataset. The positive predictive value and the negative predictive value were 0.60 and 0.73, respectively. The study demonstrates that (1) features extracted from multiple sub-regions can improve the performance of our scheme compared to using features from whole breast area only; (2) a classifier using asymmetry bilateral features can effectively predict breast cancer risk; (3) incorporating texture and morphological features with density features can boost the classification accuracy.

[Breast reconstruction: autologous tissue versus implant].

PubMed

Plogmeier, K; Handstein, S; Schneider, W

1998-01-01

Modified radical mastectomy remains the standard for treatment of breast cancer. Women faced with the diagnosis of breast cancer often find it difficult to cope with the arousing emotions. Fear of death or cancer recurrence and a perceived loss of femininity often coexists with the desire for a return to normality and wholeness. For women seeking breast reconstruction various techniques have been developed. Two different ways for breast reconstruction have become a standard. One way is the reconstruction by tissue expansion or transposing locally available tissue with the use of implants. The other way is the reconstruction of the breast without using any implants with the Latissimus dorsi flap or the TRAM flap. We performed 291 breast reconstructions. In 125 women available tissue and an implant was used. The Latissimus dorsi flap was used in 57 cases and 109 TRAM flaps either pedicled or as a microvascular flap were performed. Using expanders we found a perforation of the device in 2 cases. After using implants there were capsular contracture in 2 cases and in 1 case we had an infection. Using autologous tissue we had 2 partial flap necrosis, 4 hematomas, and 4 prolonged healings. There was no complete flap necrosis. Breast reconstruction using autologous tissue i.e. the TRAM flap is supposed to be a standard technique. Microsurgical transplantation of the TRAM flap shows almost no morbidity of the donor site area. Autologous tissue follows the changes of the body like weight gain or reduction to a certain extend and shows neither capsular contracture nor other implant associated side effects. Women get the impression that the TRAM flap is like soft tissue to the touch and not like a foreign body. The aesthetic results were in all cases superior sometimes needing minor secondary correction and mostly shaping of the nippel-areola complex. All patients were pleased with the result.

21 CFR 900.4 - Standards for accreditation bodies.

Code of Federal Regulations, 2010 CFR

2010-04-01

.... Sufficient breast tissue shall be imaged to ensure that cancers are not likely to be missed because of... potential obscuring effect of overlying breast tissue and motion artifact. (iii) Exposure level. Exposure level shall be adequate to visualize breast structures. Images shall be neither underexposed nor...

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

PubMed

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.

Effect of hypoxia on tissue factor pathway inhibitor expression in breast cancer.

PubMed

Cui, X Y; Tinholt, M; Stavik, B; Dahm, A E A; Kanse, S; Jin, Y; Seidl, S; Sahlberg, K K; Iversen, N; Skretting, G; Sandset, P M

2016-02-01

ESSENTIALS: A hypoxic microenvironment is a common feature of tumors that may influence activation of coagulation. MCF-7 and SK-BR-3 breast cancer cells and breast cancer tissue samples were used. The results showed transcriptional repression of tissue factor pathway inhibitor expression in hypoxia. Hypoxia-inducible factor 1α may be a target for the therapy of cancer-related coagulation and thrombosis. Activation of coagulation is a common finding in patients with cancer, and is associated with an increased risk of venous thrombosis. As a hypoxic microenvironment is a common feature of solid tumors, we investigated the role of hypoxia in the regulation of tissue factor (TF) pathway inhibitor (TFPI) expression in breast cancer. To explore the transcriptional regulation of TFPI by hypoxia-inducible factor (HIF)-1α in breast cancer cells and their correlation in breast cancer tissues. MCF-7 and SK-BR-3 breast cancer cells were cultured in 1% oxygen or treated with cobalt chloride (CoCl2 ) to mimic hypoxia. Time-dependent and dose-dependent downregulation of TFPI mRNA (quantitative RT-PCR) and of free TFPI protein (ELISA) were observed in hypoxia. Western blotting showed parallel increases in the levels of HIF-1α protein and TF. HIF-1α inhibitor abolished or attenuated the hypoxia-induced downregulation of TFPI. Luciferase reporter assay showed that both hypoxia and HIF-1α overexpression caused strong repression of TFPI promoter activity. Subsequent chromatin immunoprecipitation and mutagenesis analysis demonstrated a functional hypoxia response element within the TFPI promoter, located at -1065 to -1060 relative to the transcriptional start point. In breast cancer tissue samples, gene expression analyses showed a positive correlation between the mRNA expression of TFPI and that of HIF-1α. This study demonstrates that HIF-1α is involved in the transcriptional regulation of the TFPI gene, and suggests that a hypoxic microenvironment inside a breast tumor may induce a procoagulant state in breast cancer patients. © 2015 International Society on Thrombosis and Haemostasis.

Ultrasound Shear Wave Simulation of Breast Tumor Using Nonlinear Tissue Elasticity

PubMed Central

Park, Dae Woo

2016-01-01

Shear wave elasticity imaging (SWEI) can assess the elasticity of tissues, but the shear modulus estimated in SWEI is often less sensitive to a subtle change of the stiffness that produces only small mechanical contrast to the background tissues. Because most soft tissues exhibit mechanical nonlinearity that differs in tissue types, mechanical contrast can be enhanced if the tissues are compressed. In this study, a finite element- (FE-) based simulation was performed for a breast tissue model, which consists of a circular (D: 10 mm, hard) tumor and surrounding tissue (soft). The SWEI was performed with 0% to 30% compression of the breast tissue model. The shear modulus of the tumor exhibited noticeably high nonlinearity compared to soft background tissue above 10% overall applied compression. As a result, the elastic modulus contrast of the tumor to the surrounding tissue was increased from 0.46 at 0% compression to 1.45 at 30% compression. PMID:27293476

Extravasation of paclitaxel into breast tissue from central catheter port.

PubMed

Barutca, Sabri; Kadikoylu, Gurhan; Bolaman, Zahit; Meydan, Nezih; Yavasoglu, Irfan

2002-10-01

A 53-year-old woman with advanced-stage ovarian cancer experienced extravasation of paclitaxel into the breast tissue as a result of inappropriate needle insertion and/or dislodgement; it came from a central catheter port (CCP) that was found to be intact under radiological examination with contrast material. The breast became tender and oedematous with erythema, and local warming was observed within a few hours. The patient improved in the next few days during nonsteroidal anti-inflammatory medication and close observation, and the breast healed with thickened and darkened skin and central scarring in the 6th month of follow-up. To the best of our knowledge, extravasation into breast tissue is rare in the literature. Extravasation of vesicant drugs from CCP can cause tissue necrosis; it is therefore essential that ports be carefully assessed and used by experienced staff to lessen the likelihood of such an unpleasant complication.

A finite element model of remote palpation of breast lesions using radiation force: factors affecting tissue displacement.

PubMed

Nightingale, K R; Nightingale, R W; Palmeri, M L; Trahey, G E

2000-01-01

The early detection of breast cancer reduces patient mortality. The most common method of breast cancer detection is palpation. However, lesions that lie deep within the breast are difficult to palpate when they are small. Thus, a method of remote palpation, which may allow the detection of small lesions lying deep within the breast, is currently under investigation. In this method, acoustic radiation force is used to apply localized forces within tissue (to tissue volumes on the order of 2 mm3) and the resulting tissue displacements are mapped using ultrasonic correlation based methods. A volume of tissue that is stiffer than the surrounding medium (i.e., a lesion) distributes the force throughout the tissue beneath it, resulting in larger regions of displacement, and smaller maximum displacements. The resulting displacement maps may be used to image tissue stiffness. A finite-element-model (FEM) of acoustic remote palpation is presented in this paper. Using this model, a parametric analysis of the affect of varying tissue and acoustic beam characteristics on radiation force induced tissue displacements is performed. The results are used to evaluate the potential of acoustic remote palpation to provide useful diagnostic information in a clinical setting. The potential for using a single diagnostic transducer to both generate radiation force and track the resulting displacements is investigated.

[Imaging of breast tumors using MR elastography].

PubMed

Lorenzen, J; Sinkus, R; Schrader, D; Lorenzen, M; Leussler, C; Dargatz, M; Röschmann, P

2001-01-01

Imaging of breast tumors using MR-Elastography. Low-frequency mechanical waves are transmitted into breast-tissue by means of an oscillator. The local characteristics of the mechanical wave are determined by the elastic properties of the tissue. By means of a motion-sensitive spin-echo-sequence these waves can be displayed within the phase of the MR image. Subsequently, these images can be used to reconstruct the local distribution of elasticity. In-vivo measurements were performed in 3 female patients with malignant tumors of the breast. All patients tolerated the measurement set-up without any untoward sensation in the contact area of skin and oszillator. The waves completely penetrated the breast, encompassing the axilla and regions close to the chest wall. All tumors were localized by MRE as structures of markedly stiffer tissue when compared to the surrounding tissue. Furthermore, in one patient, a metastasis in an axillary lymph node was detected. In all patients, local regions of increased elasticity were found in the remaining parenchyma of the breast, which, however, did not reach the high levels of elasticity found in the tumors. MRE is an imaging modality enabling adjunct tissue differentiation of mammary tumors.

Association of proteasomal activity with metastasis in luminal breast cancer

NASA Astrophysics Data System (ADS)

Shashova, E. E.; Fesik, E. A.; Doroshenko, A. V.

2017-09-01

Chimotrypsin-like (ChTL) and caspase-like (CL) proteasomal activities were investigated in different variants of the tumor progression of luminal breast cancer. Patients with primary luminal breast cancer (n = 123) in stage T1-3N0-2M0 who had not received neoadjuvant treatment were included in this study. Proteasome ChTL and CL activities were determined in the samples of tumor and adjacent tissues. The coefficients of chymotrypsin-like (kChTL) and caspase-like (kCL) proteasome activity were also calculated as the ratio of the corresponding activity in the tumor tissue to activity in the adjacent tissue. ChTL, CL, kChTL and kCL in the tissues of luminal A and B breast cancer with lymphogenic metastasis were compared, and their association with hematogenous metastasis was evaluated. On the one hand, CL activity of proteasomes increased in luminal A breast cancer with extensive lymphogenic metastasis (N2), on the other hand it decreased in the luminal B subtype of cancer. The ratio of proteasomal activity in the tumor and adjacent tissues plays a significant role in the hematogenic pathway of breast cancer progression and is associated with poor metastatic-free survival.

Distribution of phthalocyanines and Raman reporters in human cancerous and noncancerous breast tissue as studied by Raman imaging.

PubMed

Brozek-Pluska, Beata; Jarota, Arkadiusz; Jablonska-Gajewicz, Joanna; Kordek, Radzislaw; Czajkowski, Wojciech; Abramczyk, Halina

2012-08-01

There is a considerable interest in the developing new diagnostic techniques allowing noninvasive tracking of the progress of therapies used to treat a cancer. Raman imaging of distribution of phthalocyanine photosensitizers may open new possibilities of Photodynamic Therapy (PDT) to treat a wide range of neoplastic lesions with improved effectiveness of treatment through precise identification of malignant areas. We have employed Raman imaging and Raman spectroscopy to analyze human breast cancer tissue that interacts with photosensitizers used in the photodynamic therapy of cancer. PCA (Principal Component Analysis) has been employed to analyze various areas of the noncancerous and cancerous breast tissues. The results show that the emission spectra combined with the Raman images are very sensitive indicators to specify the aggregation state and the distribution of phthalocyanines in the cancerous and noncancerous breast tissues. Our results provide experimental evidence on the role of aggregation of phthalocyanines as a factor of particular significance in differentiation of the normal and tumourous (cancerous or benign pathology) breast tissues. We conclude that the Raman imaging reported here has a potential to be a novel and effective photodynamic therapeutic method with improved selectivity for the treatment of breast cancer.

Spatial and temporal age-related spectral alterations in benign human breast tissue

NASA Astrophysics Data System (ADS)

Theophilou, Georgios; Fogarty, Simon W.; Trevisan, Júlio; Strong, Rebecca J.; Heys, Kelly A.; Patel, Imran I.; Stringfellow, Helen F.; Martin-Hirsch, Pierre L.; Martin, Francis L.

2016-02-01

Epidemiological evidence suggests that cancers attributable to exogenous carcinogenic agents may appear decades after initiating exposures. Environmental factors including lifestyle and/or diet have been implicated in the aetiology of breast cancer. Breast tissue undergoes continuous molecular and morphological changes from the time of thelarche to menopause and thereafter. These alterations are both cyclical and longitudinal, and can be influenced by several environmental factors including exposure to oestrogens. Research into the latent period leading to breast carcinogenesis has been mostly limited to when hyperplastic lesions are present. Investigations to identify a biomarker of commitment to disease in normal breast tissue are hindered by the molecular and histological diversity of disease-free breast tissue. Benign tissue from reduction mammoplasties provides an opportunity to study biochemical differences between women of similar ages as well as alterations with advancing age. Herein, synchrotron radiation-based Fourier-transform infrared (SR-FTIR) microspectroscopy was used to examine the terminal ductal lobular epithelium (TDLU) and, intra- and inter-lobular epithelium to identify spatial and temporal changes within these areas. Principal component analysis (PCA) followed by linear discriminant analysis of mid-infrared spectra revealed unambiguous inter-individual as well as age-related differences in each histological compartment interrogated. Moreover, exploratory PCA of luminal and myoepithelial cells within the TDLU indicated the presence of specific cells, potentially stem cells. Understanding alterations within benign tissue may assist in the identification of alterations in latent pre-clinical stages of breast cancer.

Microgravity

NASA Image and Video Library

1998-10-10

High magnification view of human primary breast tumor cells after 56 days of culture in a NASA Bioreactor. The arrow points to bead surface indicating breast cancer cells (as noted by the staining of tumor cell intermediate filaments). NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cell (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunorous tissue. Credit: Dr. Jearne Becker, University of South Florida

Knockdown of Ran GTPase expression inhibits the proliferation and migration of breast cancer cells.

PubMed

Sheng, Chenyi; Qiu, Jian; Wang, Yingying; He, Zhixian; Wang, Hua; Wang, Qingqing; Huang, Yeqing; Zhu, Lianxin; Shi, Feng; Chen, Yingying; Xiong, Shiyao; Xu, Zhen; Ni, Qichao

2018-05-03

Breast cancer is the second leading cause of cancer‑associated mortality in women worldwide. Strong evidence has suggested that Ran, which is a small GTP binding protein involved in the transport of RNA and protein across the nucleus, may be a key cellular protein involved in the metastatic progression of cancer. The present study investigated Ran gene expression in breast cancer tissue samples obtained from 140 patients who had undergone surgical resection for breast cancer. Western blot analysis of Ran in breast cancer tissues and paired adjacent normal tissues showed that expression of Ran was significantly increased in breast cancer tissues. Immunohistochemistry analyses conducted on formalin‑fixed paraffin‑embedded breast cancer tissue sections revealed that Ran expression was associated with tumor histological grade, nerve invasion and metastasis, vascular metastasis and Ki‑67 expression (a marker of cell proliferation). Kaplan‑Meier survival analysis showed that increased Ran expression in patients with breast cancer was positively associated with a poor survival prognosis. Furthermore, in vitro experiments demonstrated that highly migratory MDA‑MB‑231 cancer cells treated with Ran‑si‑RNA (si‑Ran), which knocked down expression of Ran, exhibited decreased motility in trans‑well migration and wound healing assays. Cell cycle analysis of Ran knocked down MDA‑MB‑231 cells implicated Ran in cell cycle arrest and the inhibition of proliferation. Furthermore, a starvation and re‑feeding (CCK‑8) assay was performed, which indicated that Ran regulated breast cancer cell proliferation. Taken together, the results provide strong in vitro evidence of the involvement of Ran in the progression of breast cancer and suggest that it could have high potential as a therapeutic target and/or marker of disease.

Abnormality detection of mammograms by discriminative dictionary learning on DSIFT descriptors.

PubMed

Tavakoli, Nasrin; Karimi, Maryam; Nejati, Mansour; Karimi, Nader; Reza Soroushmehr, S M; Samavi, Shadrokh; Najarian, Kayvan

2017-07-01

Detection and classification of breast lesions using mammographic images are one of the most difficult studies in medical image processing. A number of learning and non-learning methods have been proposed for detecting and classifying these lesions. However, the accuracy of the detection/classification still needs improvement. In this paper we propose a powerful classification method based on sparse learning to diagnose breast cancer in mammograms. For this purpose, a supervised discriminative dictionary learning approach is applied on dense scale invariant feature transform (DSIFT) features. A linear classifier is also simultaneously learned with the dictionary which can effectively classify the sparse representations. Our experimental results show the superior performance of our method compared to existing approaches.

Impact of Tumour Epithelial Subtype on Circulating microRNAs in Breast Cancer Patients

PubMed Central

Brougham, Cathy; Glynn, Claire L.; Wall, Deirdre; Hyland, Peter; Duignan, Maria; McLoughlin, Mark; Newell, John; Kerin, Michael J.

2014-01-01

While a range of miRNAs have been shown to be dysregulated in the circulation of patients with breast cancer, little is known about the relationship between circulating levels and tumour characteristics. The aim of this study was to analyse alterations in circulating miRNA expression during tumour progression in a murine model of breast cancer, and to detemine the clinical relevance of identified miRNAs at both tissue and circulating level in patient samples. Athymic nude mice received a subcutaneous or mammary fat pad injection of MDA-MB-231 cells. Blood sampling was performed at weeks 1, 3 and 6 following tumour induction, and microRNA extracted. MicroRNA microArray analysis was performed comparing samples harvested at week 1 to those collected at week 6 from the same animals. Significantly altered miRNAs were validated across all murine samples by RQ-PCR (n = 45). Three miRNAs of interest were then quantified in the circulation(n = 166) and tissue (n = 100) of breast cancer patients and healthy control individuals. MicroArray-based analysis of murine blood samples revealed levels of 77 circulating microRNAs to be changed during disease progression, with 44 demonstrating changes >2-fold. Validation across all samples revealed miR-138 to be significantly elevated in the circulation of animals during disease development, with miR-191 and miR-106a levels significantly decreased. Analysis of patient tissue and blood samples revealed miR-138 to be significantly up-regulated in the circulation of patients with breast cancer, with no change observed in the tissue setting. While not significantly changed overall in breast cancer patients compared to controls, circulating miR-106a and miR-191 were significantly decreased in patients with basal breast cancer. In tissue, both miRNAs were significantly elevated in breast cancer compared to normal breast tissue. The data demonstrates an impact of tumour epithelial subtype on circulating levels of miRNAs, and highlights divergent miRNA profiles between tissue and blood samples from breast cancer patients. PMID:24626163

Power-assisted liposuction and the pull-through technique for the treatment of gynecomastia.

PubMed

Lista, Frank; Ahmad, Jamil

2008-03-01

Gynecomastia is a common condition affecting many adolescent and adult males. Surgical techniques utilizing a variety of incisions, excisions, suction-assisted lipectomy, ultrasound-assisted liposuction, power-assisted liposuction, or some combination of these methods have been used in the treatment of gynecomastia. This article describes the authors' method of using power-assisted liposuction and the pull-through technique to treat gynecomastia. This technique involves the use of power-assisted liposuction to remove fatty breast tissue. The pull-through technique is then performed utilizing several instruments to sever the subdermal attachments of fibroglandular breast tissue; this tissue is removed through the incision used for liposuction. Finally, power-assisted liposuction is performed again to contour the remaining breast tissue. A chart review of 99 consecutive patients (197 breasts) treated between January of 2003 and November of 2006 was performed. Ninety-six patients (192 breasts) were successfully treated using this technique. Power-assisted liposuction was performed in all cases, and the average volume aspirated per breast was 459 ml (range, 25 to 1400 ml). Using the pull-through technique, the authors were able to remove between 5 and 70 g of tissue per breast. Complications were minimal (1.0 percent of breasts), and no revisions were required. Since January of 2003, the authors have used this technique to successfully treat 97 percent of their gynecomastia patients. Combining power-assisted liposuction and the pull-through technique has proven to be a versatile approach for the treatment of gynecomastia and consistently produces a naturally contoured male breast while resulting in a single inconspicuous scar.

Prospective Study Validating Inter- and Intraobserver Variability of Tissue Compliance Meter in Breast Tissue of Healthy Volunteers: Potential Implications for Patients With Radiation-Induced Fibrosis of the Breast

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wernicke, A. Gabriella, E-mail: gaw9008@med.cornell.ed; Parashar, Bhupesh; Kulidzhanov, Fridon

2011-05-01

Purpose: Accurate detection of radiation-induced fibrosis (RIF) is crucial in management of breast cancer survivors. Tissue compliance meter (TCM) has been validated in musculature. We validate TCM in healthy breast tissue with respect to interobserver and intraobserver variability before applying it in RIF. Methods and Materials: Three medical professionals obtained three consecutive TCM measurements in each of the four quadrants of the right and left breasts of 40 women with no breast disease or surgical intervention. The intraclass correlation coefficient (ICC) assessed interobserver variability. The paired t test and Pearson correlation coefficient (r) were used to assess intraobserver variability withinmore » each rater. Results: The median age was 45 years (range, 24-68 years). The median bra size was 35C (range, 32A-40DD). Of the participants, 27 were white (67%), 4 black (10%), 5 Asian (13%), and 4 Hispanic (10%). ICCs indicated excellent interrater reliability (low interobserver variability) among the three raters, by breast and quadrant (all ICC {>=}0.99). The paired t test and Pearson correlation coefficient both indicated low intraobserver variability within each rater (right vs. left breast), stratified by quadrant (all r{>=} 0.94, p < 0.0001). Conclusions: The interobserver and intraobserver variability is small using TCM in healthy mammary tissue. We are now embarking on a prospective study using TCM in women with breast cancer at risk of developing RIF that may guide early detection, timely therapeutic intervention, and assessment of success of therapy for RIF.« less

A hybrid cost-sensitive ensemble for imbalanced breast thermogram classification.

PubMed

Krawczyk, Bartosz; Schaefer, Gerald; Woźniak, Michał

2015-11-01

Early recognition of breast cancer, the most commonly diagnosed form of cancer in women, is of crucial importance, given that it leads to significantly improved chances of survival. Medical thermography, which uses an infrared camera for thermal imaging, has been demonstrated as a particularly useful technique for early diagnosis, because it detects smaller tumors than the standard modality of mammography. In this paper, we analyse breast thermograms by extracting features describing bilateral symmetries between the two breast areas, and present a classification system for decision making. Clearly, the costs associated with missing a cancer case are much higher than those for mislabelling a benign case. At the same time, datasets contain significantly fewer malignant cases than benign ones. Standard classification approaches fail to consider either of these aspects. In this paper, we introduce a hybrid cost-sensitive classifier ensemble to address this challenging problem. Our approach entails a pool of cost-sensitive decision trees which assign a higher misclassification cost to the malignant class, thereby boosting its recognition rate. A genetic algorithm is employed for simultaneous feature selection and classifier fusion. As an optimisation criterion, we use a combination of misclassification cost and diversity to achieve both a high sensitivity and a heterogeneous ensemble. Furthermore, we prune our ensemble by discarding classifiers that contribute minimally to the decision making. For a challenging dataset of about 150 thermograms, our approach achieves an excellent sensitivity of 83.10%, while maintaining a high specificity of 89.44%. This not only signifies improved recognition of malignant cases, it also statistically outperforms other state-of-the-art algorithms designed for imbalanced classification, and hence provides an effective approach for analysing breast thermograms. Our proposed hybrid cost-sensitive ensemble can facilitate a highly accurate early diagnostic of breast cancer based on thermogram features. It overcomes the difficulties posed by the imbalanced distribution of patients in the two analysed groups. Copyright © 2015 Elsevier B.V. All rights reserved.

Assessment of Interradiologist Agreement Regarding Mammographic Breast Density Classification Using the Fifth Edition of the BI-RADS Atlas.

PubMed

Ekpo, Ernest U; Ujong, Ujong Peter; Mello-Thoms, Claudia; McEntee, Mark F

2016-05-01

The objective of the present study was to assess interradiologist agreement regarding mammographic breast density assessment performed using the rating scale outlined in the fifth edition of the BI-RADS atlas of the American College of Radiology. Breast density assessments of 1000 cases were conducted by five radiologists from the same institution who together had recently undergone retraining in mammographic breast density classification based on the fifth edition of BI-RADS. The readers assigned breast density grades (A-D) on the basis of the BI-RADS classification scheme. Repeat assessment of 100 cases was performed by all readers 1 month after the initial assessment. A weighted kappa was used to calculate intrareader and interreader agreement. Intrareader agreement ranged from a kappa value of 0.86 (95% CI, 0.77-0.93) to 0.89 (95% CI, 0.81-0.95) on a four-category scale (categories A-D) and from 0.89 (95% CI, 0.86-0.92) to 0.94 (95% CI, 0.89-0.97) on a two-category scale (category A-B vs category C-D). Interreader agreement ranged from substantial (κ = 0.76; 95% CI, 0.73-0.78) to almost perfect (κ = 0.87; 95% CI, 0.86-0.89) on a four-category scale, and the overall weighted kappa value was substantial (0.79; 95% CI, 0.78-0.83). Interreader agreement on a two-category scale ranged from a kappa value of 0.85 (95% CI, 0.83-0.86) to 0.91 (95% CI, 0.90-0.92), and the overall weighted kappa was 0.88 (95% CI, 0.87-0.89). Overall, with regard to mammographic breast density classification, radiologists had substantial interreader agreement when a four-category scale was used and almost perfect interreader agreement when a dichotomous scale was used.

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

PubMed Central

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 the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical. Conclusion Feature variability can have a strong impact on breast cancer signature composition, as well as the classification of individual patient samples. We therefore strongly recommend that feature variability is considered in analyzing data from microarray breast cancer expression profiling experiments. PMID:19941644

Identifying metastatic breast tumors using textural kinetic features of a contrast based habitat in DCE-MRI

NASA Astrophysics Data System (ADS)

Chaudhury, Baishali; Zhou, Mu; Goldgof, Dmitry B.; Hall, Lawrence O.; Gatenby, Robert A.; Gillies, Robert J.; Drukteinis, Jennifer S.

2015-03-01

The ability to identify aggressive tumors from indolent tumors using quantitative analysis on dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) would dramatically change the breast cancer treatment paradigm. With this prognostic information, patients with aggressive tumors that have the ability to spread to distant sites outside of the breast could be selected for more aggressive treatment and surveillance regimens. Conversely, patients with tumors that do not have the propensity to metastasize could be treated less aggressively, avoiding some of the morbidity associated with surgery, radiation and chemotherapy. We propose a computer aided detection framework to determine which breast cancers will metastasize to the loco-regional lymph nodes as well as which tumors will eventually go on to develop distant metastses using quantitative image analysis and radiomics. We defined a new contrast based tumor habitat and analyzed textural kinetic features from this habitat for classification purposes. The proposed tumor habitat, which we call combined-habitat, is derived from the intersection of two individual tumor sub-regions: one that exhibits rapid initial contrast uptake and the other that exhibits rapid delayed contrast washout. Hence the combined-habitat represents the tumor sub-region within which the pixels undergo both rapid initial uptake and rapid delayed washout. We analyzed a dataset of twenty-seven representative two dimensional (2D) images from volumetric DCE-MRI of breast tumors, for classification of tumors with no lymph nodes from tumors with positive number of axillary lymph nodes. For this classification an accuracy of 88.9% was achieved. Twenty of the twenty-seven patients were analyzed for classification of distant metastatic tumors from indolent cancers (tumors with no lymph nodes), for which the accuracy was 84.3%.

miRNA-205 affects infiltration and metastasis of breast cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Zhouquan; Department of Tumor, SenGong Hospital of Shaanxi, Xi’an 710300; Liao, Hehe

2013-11-08

Highlights: •We detected expression of miR-205 in breast cancer cell lines and tissue samples. •We suggest miR-205 is downregulated in human breast cancer tissues and MCF7 cells. •We suggest the lower expression of miR-205 play a role in breast cancer onset. •These data suggest that miR-205 directly targets HER3 in human breast cancer. -- Abstract: Background: An increasing number of studies have shown that miRNAs are commonly deregulated in human malignancies, but little is known about the function of miRNA-205 (miR-205) in human breast cancer. The present study investigated the influence of miR-205 on breast cancer malignancy. Methods: The expressionmore » level of miR-205 in the MCF7 breast cancer cell line was determined by quantitative (q)RT-PCR. We then analyzed the expression of miR-205 in breast cancer and paired non-tumor tissues. Finally, the roles of miR-205 in regulating tumor proliferation, apoptosis, migration, and target gene expression were studied by MTT assay, flow cytometry, qRT-PCR, Western blotting and luciferase assay. Results: miR-205 was downregulated in breast cancer cells or tissues compared with normal breast cell lines or non-tumor tissues. Overexpression of miR-205 reduced the growth and colony-formation capacity of MCF7 cells by inducing apoptosis. Overexpression of miR-205 inhibited MCF7 cell migration and invasiveness. By bioinformation analysis, miR-205 was predicted to bind to the 3′ untranslated regions of human epidermal growth factor receptor (HER)3 mRNA, and upregulation of miR-205 reduced HER3 protein expression. Conclusion: miR-205 is a tumor suppressor in human breast cancer by post-transcriptional inhibition of HER3 expression.« less

Computational Simulation of Breast Compression Based on Segmented Breast and Fibroglandular Tissues on Magnetic Resonance Images

PubMed Central

Shih, Tzu-Ching; Chen, Jeon-Hor; Liu, Dongxu; Nie, Ke; Sun, Lizhi; Lin, Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying

2010-01-01

This study presents a finite element based computational model to simulate the three-dimensional deformation of the breast and the fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and the craniocaudal and mediolateral oblique compression as used in mammography was applied. The geometry of whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo® 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the non-linear elastic tissue deformation under compression, using the MSC.Marc® software package. The model was tested in 4 cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these 4 cases at 60% compression ratio was in the range of 5-7 cm, which is the typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at 60% compression ratio was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on MRI, which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density measurements needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities – such as MRI, mammography, whole breast ultrasound, and molecular imaging – that are performed using different body positions and different compression conditions. PMID:20601773

Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images.

PubMed

Shih, Tzu-Ching; Chen, Jeon-Hor; Liu, Dongxu; Nie, Ke; Sun, Lizhi; Lin, Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying

2010-07-21

This study presents a finite element-based computational model to simulate the three-dimensional deformation of a breast and fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and craniocaudal and mediolateral oblique compression, as used in mammography, was applied. The geometry of the whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the nonlinear elastic tissue deformation under compression, using the MSC.Marc software package. The model was tested in four cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these four cases at a compression ratio of 60% was in the range of 5-7 cm, which is a typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at a compression ratio of 60% was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on magnetic resonance imaging (MRI), which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities--such as MRI, mammography, whole breast ultrasound and molecular imaging--that are performed using different body positions and under different compression conditions.

Microgravity

NASA Image and Video Library

1998-10-10

Dr. Harry Mahtani analyzes the gas content of nutrient media from Bioreactor used in research on human breast cancer. NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cells (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunourous tissues.

21st century paradigm of tissue banking: the Clinical Breast Care Project.

PubMed

Shriver, Craig D

2010-07-01

The Clinical Breast Care Project (CBCP) is a congressionally mandated program that began in the year 2000. The military-civilian collaboration was founded on five pillars: (1) center of excellence in clinical care, (2) risk reduction for women at risk for developing breast cancer, (3) tissue banking to develop and maintain the world's finest repository of human biospecimens of breast diseases, (4) targeted research into the molecular signatures of breast diseases and cancer, and (5) biomedical informatics core to support the data warehouse needs of the project. Now in its eighth year of operation, these efforts have resulted in more than 300 peer-reviewed scientific publications and dozens of collaborations with world leaders in cancer research. In this short time, CBCP has created what is believed to be the world's largest breast tissue biorepository.

Diffusion-weighted MR imaging: role in the differential diagnosis of breast lesions.

PubMed

Altay, C; Balci, P; Altay, S; Karasu, S; Saydam, S; Canda, T; Dicle, O

2014-01-01

To evaluate the diagnostic value of magnetic resonance diffusion-weighted imaging (DWI) using apparent diffusion coefficient (ADC) values to the characterization of breast lesions and differentiation of benign and malignant lesions. Thirty-seven women (mean age, 38 years) with 37 enrolled in the study. DWI and ADC maps in the axial plane were obtained using a 1.5 Tesla MRI device. Mean ADC measurements were calculated among cysts, normal fibroglandular tissue, benign lesions and malignant lesions were evaluated. Out of 37 women, 4 had normally breast MRI findings. The diagnosis of remaining 33 patients with 37 breast lesions were as follows; malign lesions (n = 23), benign lesions (n = 10) and simple breast cyst (n = 4). The ADC values were as follows (in units of 10(-3) mm2/s): Normal fibroglandular tissue (range: 1.39-2.06; mean: 1.61 ± 0.23), benign breast lesions (range: 1.09-1.76; mean: 1.47 ± 0.25), cyts (range: 2.27-2.46, mean: 2.37 ± 0.07) and malignant breast lesions (range: 0.78-1.26, mean: 0.96 ± 0.25). The mean ADC obtained from malignant breast lesions was statistically different from that observed in benign solid lesions (p < < 0.01) and normal fibroglandular breast tissue (p < 0.01). Furthermore, the mean ADC values of benign breast lesions was not statistically different from cyst (p ≥ 0.01) and normal fibroglandular breast tissue (p ≥ 0.01). A ADC value of 1.1 x 10(-3) mm'/s as a treshold value provided differantiation for malign and benign lesions, with a sensitivity of 91.3% and a specificity of 85.7% compared with conventional breast MRI values. DWI with quantitative ADC measurements is a reliable tool for differentiation of benign and malignant breast lesions.

Suppression of NFkB by Tetrathiomolybdate Inhibits Tumor Angiogenesis and Enhances Apoptosis in Human Breast Cancers

DTIC Science & Technology

2005-05-01

to treat breast cancer. 15. SUBJECT TERMS NFkappaB , tetrathiomolybdate, breast cancer 16. SECURITY CLASSIFICATION OF: 17. LIMITATION 18. NUMBER 19a...Sonenshein, G. E. Aberrant nuclear factor-icB/Rel expression and the pathogen- HER-2/neu blocks tumor necrosis factor-induced apoptosis via the Akt /NF

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

DTIC Science & Technology

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

Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues

PubMed Central

Lago, M. A.; Rúperez, M. J.; Martínez-Martínez, F.; Martínez-Sanchis, S.; Bakic, P. R.; Monserrat, C.

2015-01-01

This paper presents a novel methodology to in-vivo estimate the elastic constants of a constitutive model proposed to characterize the mechanical behavior of the breast tissues. An iterative search algorithm based on genetic heuristics was constructed to in-vivo estimate these parameters using only medical images, thus avoiding invasive measurements of the mechanical response of the breast tissues. For the first time, a combination of overlap and distance coefficients were used for the evaluation of the similarity between a deformed MRI of the breast and a simulation of that deformation. The methodology was validated using breast software phantoms for virtual clinical trials, compressed to mimic MRI-guided biopsies. The biomechanical model chosen to characterize the breast tissues was an anisotropic neo-Hookean hyperelastic model. Results from this analysis showed that the algorithm is able to find the elastic constants of the constitutive equations of the proposed model with a mean relative error of about 10%. Furthermore, the overlap between the reference deformation and the simulated deformation was of around 95% showing the good performance of the proposed methodology. This methodology can be easily extended to characterize the real biomechanical behavior of the breast tissues, which means a great novelty in the field of the simulation of the breast behavior for applications such as surgical planing, surgical guidance or cancer diagnosis. This reveals the impact and relevance of the presented work. PMID:27103760

Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues.

PubMed

Lago, M A; Rúperez, M J; Martínez-Martínez, F; Martínez-Sanchis, S; Bakic, P R; Monserrat, C

2015-11-30

This paper presents a novel methodology to in-vivo estimate the elastic constants of a constitutive model proposed to characterize the mechanical behavior of the breast tissues. An iterative search algorithm based on genetic heuristics was constructed to in-vivo estimate these parameters using only medical images, thus avoiding invasive measurements of the mechanical response of the breast tissues. For the first time, a combination of overlap and distance coefficients were used for the evaluation of the similarity between a deformed MRI of the breast and a simulation of that deformation. The methodology was validated using breast software phantoms for virtual clinical trials, compressed to mimic MRI-guided biopsies. The biomechanical model chosen to characterize the breast tissues was an anisotropic neo-Hookean hyperelastic model. Results from this analysis showed that the algorithm is able to find the elastic constants of the constitutive equations of the proposed model with a mean relative error of about 10%. Furthermore, the overlap between the reference deformation and the simulated deformation was of around 95% showing the good performance of the proposed methodology. This methodology can be easily extended to characterize the real biomechanical behavior of the breast tissues, which means a great novelty in the field of the simulation of the breast behavior for applications such as surgical planing, surgical guidance or cancer diagnosis. This reveals the impact and relevance of the presented work.

A new bias field correction method combining N3 and FCM for improved segmentation of breast density on MRI.

PubMed

Lin, Muqing; Chan, Siwa; Chen, Jeon-Hor; Chang, Daniel; Nie, Ke; Chen, Shih-Ting; Lin, Cheng-Ju; Shih, Tzu-Ching; Nalcioglu, Orhan; Su, Min-Ying

2011-01-01

Quantitative breast density is known as a strong risk factor associated with the development of breast cancer. Measurement of breast density based on three-dimensional breast MRI may provide very useful information. One important step for quantitative analysis of breast density on MRI is the correction of field inhomogeneity to allow an accurate segmentation of the fibroglandular tissue (dense tissue). A new bias field correction method by combining the nonparametric nonuniformity normalization (N3) algorithm and fuzzy-C-means (FCM)-based inhomogeneity correction algorithm is developed in this work. The analysis is performed on non-fat-sat T1-weighted images acquired using a 1.5 T MRI scanner. A total of 60 breasts from 30 healthy volunteers was analyzed. N3 is known as a robust correction method, but it cannot correct a strong bias field on a large area. FCM-based algorithm can correct the bias field on a large area, but it may change the tissue contrast and affect the segmentation quality. The proposed algorithm applies N3 first, followed by FCM, and then the generated bias field is smoothed using Gaussian kernal and B-spline surface fitting to minimize the problem of mistakenly changed tissue contrast. The segmentation results based on the N3+FCM corrected images were compared to the N3 and FCM alone corrected images and another method, coherent local intensity clustering (CLIC), corrected images. The segmentation quality based on different correction methods were evaluated by a radiologist and ranked. The authors demonstrated that the iterative N3+FCM correction method brightens the signal intensity of fatty tissues and that separates the histogram peaks between the fibroglandular and fatty tissues to allow an accurate segmentation between them. In the first reading session, the radiologist found (N3+FCM > N3 > FCM) ranking in 17 breasts, (N3+FCM > N3 = FCM) ranking in 7 breasts, (N3+FCM = N3 > FCM) in 32 breasts, (N3+FCM = N3 = FCM) in 2 breasts, and (N3 > N3+FCM > FCM) in 2 breasts. The results of the second reading session were similar. The performance in each pairwise Wilcoxon signed-rank test is significant, showing N3+FCM superior to both N3 and FCM, and N3 superior to FCM. The performance of the new N3+FCM algorithm was comparable to that of CLIC, showing equivalent quality in 57/60 breasts. Choosing an appropriate bias field correction method is a very important preprocessing step to allow an accurate segmentation of fibroglandular tissues based on breast MRI for quantitative measurement of breast density. The proposed algorithm combining N3+FCM and CLIC both yield satisfactory results.

Percutaneous irreversible electroporation for breast tissue and breast cancer: safety, feasibility, skin effects and radiologic-pathologic correlation in an animal study.

PubMed

Li, Sheng; Chen, Fei; Shen, Lujun; Zeng, Qi; Wu, Peihong

2016-08-05

To study the safety, feasibility and skin effects of irreversible electroporation (IRE) for breast tissue and breast cancer in animal models. Eight pigs were used in this study. IRE was performed on the left breasts of the pigs with different skin-electrode distances, and the right breasts were used as controls. The electrodes were placed 1-8 mm away from the skin, with an electrode spacing of 1.5-2 cm. Imaging and pathological examinations were performed at specific time points for follow-up evaluation. Vital signs, skin damage, breast tissue changes and ablation efficacy were also closely observed. Eight rabbit models with or without VX2 breast tumor implantations were used to further assess the damage caused by and the repair of thin skin after IRE treatment for breast cancer. Contrast-enhanced ultrasound and elastosonography were used to investigate ablation efficacy and safety. During IRE, the color of the pig breast skin reversibly changed. When the skin-electrode distance was 3 mm, the breast skin clearly changed, becoming white in the center and purple in the surrounding region during IRE. One small purulent skin lesion was detected several days after IRE. When the skin-electrode distance was 5-8 mm, the breast skin became red during IRE. However, the skin architecture was normal when evaluated using gross pathology and hematoxylin-eosin staining. When the skin-electrode distance was 1 mm, skin atrophy and yellow glabrescence occurred in the rabbit breasts after IRE. When the skin-electrode distance was ≥5 mm, there was no skin damage in the rabbit model regardless of breast cancer implantation. After IRE, complete ablation of the targeted breast tissue or cancer was confirmed, and apoptosis was detected in the target tissue and outermost epidermal layer. In the ablated breasts of the surviving animals, complete mammary regeneration with normal skin and hair was observed. Furthermore, no massive fibrosis or mass formation were detected on ultrasound or through hematoxylin-eosin staining. After IRE, the skin architecture was well preserved when the skin-electrode distance was ≥5 mm. Moreover, breast regeneration occurred without mass formation or obvious fibrosis.

A Global Covariance Descriptor for Nuclear Atypia Scoring in Breast Histopathology Images.

PubMed

Khan, Adnan Mujahid; Sirinukunwattana, Korsuk; Rajpoot, Nasir

2015-09-01

Nuclear atypia scoring is a diagnostic measure commonly used to assess tumor grade of various cancers, including breast cancer. It provides a quantitative measure of deviation in visual appearance of cell nuclei from those in normal epithelial cells. In this paper, we present a novel image-level descriptor for nuclear atypia scoring in breast cancer histopathology images. The method is based on the region covariance descriptor that has recently become a popular method in various computer vision applications. The descriptor in its original form is not suitable for classification of histopathology images as cancerous histopathology images tend to possess diversely heterogeneous regions in a single field of view. Our proposed image-level descriptor, which we term as the geodesic mean of region covariance descriptors, possesses all the attractive properties of covariance descriptors lending itself to tractable geodesic-distance-based k-nearest neighbor classification using efficient kernels. The experimental results suggest that the proposed image descriptor yields high classification accuracy compared to a variety of widely used image-level descriptors.

Adipose Tissue Quantification by Imaging Methods: A Proposed Classification

PubMed Central

Shen, Wei; Wang, ZiMian; Punyanita, Mark; Lei, Jianbo; Sinav, Ahmet; Kral, John G.; Imielinska, Celina; Ross, Robert; Heymsfield, Steven B.

2007-01-01

Recent advances in imaging techniques and understanding of differences in the molecular biology of adipose tissue has rendered classical anatomy obsolete, requiring a new classification of the topography of adipose tissue. Adipose tissue is one of the largest body compartments, yet a classification that defines specific adipose tissue depots based on their anatomic location and related functions is lacking. The absence of an accepted taxonomy poses problems for investigators studying adipose tissue topography and its functional correlates. The aim of this review was to critically examine the literature on imaging of whole body and regional adipose tissue and to create the first systematic classification of adipose tissue topography. Adipose tissue terminology was examined in over 100 original publications. Our analysis revealed inconsistencies in the use of specific definitions, especially for the compartment termed “visceral” adipose tissue. This analysis leads us to propose an updated classification of total body and regional adipose tissue, providing a well-defined basis for correlating imaging studies of specific adipose tissue depots with molecular processes. PMID:12529479

Fibroadenomatosis involving bilateral breasts and axillary accessory breast tissues in a renal transplant recipient given cyclosporin A.

PubMed

Bulakci, Mesut; Gocmez, Ahmet; Demir, Ali Aslan; Salmaslioglu, Artur; Tukenmez, Mustafa; Yavuz, Ekrem; Acunas, Gulden

2014-10-01

We present the mammographic and sonographic findings in a case of fibroadenomatosis involving both breasts and axillae in a renal transplant patient after 16 years of treatment with cyclosporin A. Awareness of the fact that cyclosporin A may induce the formation of fibroadenomas, including in accessory breast tissue, is important for correct diagnosis and preventing unnecessary intervention. © 2014 Wiley Periodicals, Inc.

Noninvasive Spatially Offset and Transmission Raman Mapping of Breast Tissue: A Multimodal Approach Towards the In Vivo Assessment of Tissue Pathology

DTIC Science & Technology

2013-06-01

spectroscopy on tissue biopsies to correlate spectral bands with healthy and diseased breast tissue. Observed spectral changes are compared to infrared...capabilities and performance. Additionally, we conduct spectroscopy on tissue biopsies to correlate spectral bands with healthy and diseased ... disease states, ie hyperplasia, dysplasia, malignant, benign. The instrumentation has been built and characterized using archived tissue that was

Expression of metalloprotease insulin-degrading enzyme (insulysin) in normal and malignant human tissues

PubMed Central

Yfanti, Christina; Mengele, Karin; Gkazepis, Apostolos; Weirich, Gregor; Giersig, Cecylia; Kuo, Wen-Liang; Tang, Wei-Jen; Rosner, Marsha; Schmitt, Manfred

2013-01-01

Background Insulin-degrading enzyme (IDE, insulysin, insulinase; EC 3.4.22.11), a thiol metalloendopeptidase, is involved in intracellular degradation of insulin, thereby inhibiting its translocation and accumulation to the nucleus. Recently, protein expression of IDE has been demonstrated in the epithelial ducts of normal breast and in breast cancer tissue (Radulescu et al., Int J Oncol 30:73; 2007). Materials and Methods Utilizing four different antibodies generated against different epitopes of the IDE molecule, we performed western blot analysis and immunohistochemical staining on several normal human tissues, on a plethora of tumor cell lines of different tissue origin, and on malignant breast and ovarian tissue. Results Applying the four IDE-directed antibodies, we demonstrate IDE expression at the protein level, both by means of immunoblotting and immunocytochemistry, in all of the tumor cell lines analyzed. Besides, IDE protein expression was found in normal tissues of the kidney, liver, lung, brain, breast and skeletal muscle, as well as in breast and ovarian cancer tissues. Immunohistochemical visualization of IDE indicated cytoplasmic localization of IDE in all of the cell lines and tissues assessed. Conclusions We performed for the first time a wide-ranging survey on IDE protein expression in normal and malignant tissues and cells and thus extend knowledge about cellular and tissue distribution of IDE, an enzyme which so far has mainly been studied in connection with Alzheimer’s disease and diabetes but not in cancer. PMID:18813847

A multistage selective weighting method for improved microwave breast tomography.

PubMed

Shahzad, Atif; O'Halloran, Martin; Jones, Edward; Glavin, Martin

2016-12-01

Microwave tomography has shown potential to successfully reconstruct the dielectric properties of the human breast, thereby providing an alternative to other imaging modalities used in breast imaging applications. Considering the costly forward solution and complex iterative algorithms, computational complexity becomes a major bottleneck in practical applications of microwave tomography. In addition, the natural tendency of microwave inversion algorithms to reward high contrast breast tissue boundaries, such as the skin-adipose interface, usually leads to a very slow reconstruction of the internal tissue structure of human breast. This paper presents a multistage selective weighting method to improve the reconstruction quality of breast dielectric properties and minimize the computational cost of microwave breast tomography. In the proposed two stage approach, the skin layer is approximated using scaled microwave measurements in the first pass of the inversion algorithm; a numerical skin model is then constructed based on the estimated skin layer and the assumed dielectric properties of the skin tissue. In the second stage of the algorithm, the skin model is used as a priori information to reconstruct the internal tissue structure of the breast using a set of temporal scaling functions. The proposed method is evaluated on anatomically accurate MRI-derived breast phantoms and a comparison with the standard single-stage technique is presented. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Congenital anomalies of the breast.

PubMed

Caouette-Laberge, Louise; Borsuk, Daniel

2013-02-01

Poland syndrome is a combination of chest wall deformity and absent or hypoplastic pectoralis muscle and breast associated with shortening and brachysyndactyly of the upper limb. Clinical presentation varies widely; therefore, reconstructive procedures have to be adapted to the deformity, ranging from chest wall stabilization or augmentation, dynamic muscle transfer, nipple and areola repositioning, and breast augmentation using prosthesis or autologous tissue transfer. Other congenital breast anomalies include supernumerary nipple and areola (polythelia) and breast (polymastia), which can generally be found on the embryonic mammary ridge. Absence of the nipple, areola (athelia), or the breast tissue (amastia) is less frequent.

Congenital Anomalies of the Breast

PubMed Central

Caouette-Laberge, Louise; Borsuk, Daniel

2013-01-01

Poland syndrome is a combination of chest wall deformity and absent or hypoplastic pectoralis muscle and breast associated with shortening and brachysyndactyly of the upper limb. Clinical presentation varies widely; therefore, reconstructive procedures have to be adapted to the deformity, ranging from chest wall stabilization or augmentation, dynamic muscle transfer, nipple and areola repositioning, and breast augmentation using prosthesis or autologous tissue transfer. Other congenital breast anomalies include supernumerary nipple and areola (polythelia) and breast (polymastia), which can generally be found on the embryonic mammary ridge. Absence of the nipple, areola (athelia), or the breast tissue (amastia) is less frequent. PMID:24872738

Quantification of Estrogen Receptor Expression in Normal Breast Tissue in Postmenopausal Women With Breast Cancer and Association With Tumor Subtypes.

PubMed

Gulbahce, H Evin; Blair, Cindy K; Sweeney, Carol; Salama, Mohamed E

2017-09-01

Estrogen exposure is important in the pathogenesis of breast cancer and is a contributing risk factor. In this study we quantified estrogen receptor (ER) alpha expression in normal breast epithelium (NBR) in women with breast cancer and correlated it with breast cancer subtypes. Tissue microarrays were constructed from 204 breast cancer patients for whom normal breast tissue away from tumor was available. Slides stained with ER were scanned and expression in normal terminal duct lobular epithelium was quantitated using computer-assisted image analysis. ER expression in normal terminal duct lobular epithelium of postmenopausal women with breast cancer was significantly associated with estrogen and triple (estrogen, progesterone receptors, and HER2) negative phenotypes. Also increased age at diagnosis was significantly associated with ER expression in NBR. ER positivity in normal epithelium did not vary by tumor size, lymph node status, tumor grade, or stage. On the basis of quantitative image analysis, we confirm that ER expression in NBR increases with age in women with breast cancer, and report for the first time, a significant association between ER expression in NBR with ER-negative and triple-negative cancers in postmenopausal women.

MicroRNA Expression in Laser Micro-dissected Breast Cancer Tissue Samples - a Pilot Study.

PubMed

Seclaman, Edward; Narita, Diana; Anghel, Andrei; Cireap, Natalia; Ilina, Razvan; Sirbu, Ioan Ovidiu; Marian, Catalin

2017-10-28

Breast cancer continues to represent a significant public health burden despite outstanding research advances regarding the molecular mechanisms of cancer biology, biomarkers for diagnostics and prognostic and therapeutic management of this disease. The studies of micro RNAs in breast cancer have underlined their potential as biomarkers and therapeutic targets; however most of these studies are still done on largely heterogeneous whole breast tissue samples. In this pilot study we have investigated the expression of four micro RNAs (miR-21, 145, 155, 92) known to be involved in breast cancer, in homogenous cell populations collected by laser capture microdissection from breast tissue section slides. Micro RNA expression was assessed by real time PCR, and associations with clinical and pathological characteristics were also explored. Our results have confirmed previous associations of miR-21 expression with poor prognosis characteristics of breast cancers such as high stage, large and highly proliferative tumors. No statistically significant associations were found with the other micro RNAs investigated, possibly due to the small sample size of our study. Our results also suggest that miR-484 could be a suitable endogenous control for data normalization in breast tissues, these results needing further confirmation by future studies. In summary, our pilot study showed the feasibility of detecting micro RNAs expression in homogenous laser captured microdissected invasive breast cancer samples, and confirmed some of the previously reported associations with poor prognostic characteristics of breast tumors.

Elucidating the Tumor Suppressive Role of SLITs in Maintaining the Basal Cell Niche

DTIC Science & Technology

2009-07-01

deregulated upon cancerous transformation. 15. SUBJECT TERMS breast , Slit2, Robo1, basal cell 16. SECURITY CLASSIFICATION OF: 17. LIMITATION...natural
tumor
suppressor”
of
the
 breast 
because
they
 maintain
 breast 
tissue
integrity
by
organizing
the
cells
in
contact
with
them, including cells in...the breast stem cell niche, located between the myoepithelial and luminal epithelial cell layers.
SLITs
are
a
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 secreted
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were

Breast Density Assessment by Dual Energy X-ray Absorptiometry in Women and Girls

DTIC Science & Technology

2009-07-01

of this project among adult women and adolescent girls, who will be recruited as mothers and daughters, will be to 1. Correlate breast density...scans to their association with mammographic density; 3. Assess DXA breast density by Tanner stage of breast maturation among adolescent girls; 4...cancer risk, adolescents 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON USAMRMC

Gynaecomastia--pathophysiology, diagnosis and treatment.

PubMed

Narula, Harmeet S; Carlson, Harold E

2014-11-01

Gynaecomastia (enlargement of the male breast tissue) is a common finding in the general population. Most cases of gynaecomastia are benign and of cosmetic, rather than clinical, importance. However, the condition might cause local pain and tenderness, could occasionally be the result of a serious underlying illness or a medication, or be inherited. Breast cancer in men is much less common than benign gynaecomastia, and the two conditions can usually be distinguished by a careful physical examination. Estrogens are known to stimulate the growth of breast tissue, whereas androgens inhibit it; most cases of gynaecomastia result from deficient androgen action or excessive estrogen action in the breast tissue. In some cases, such as pubertal gynaecomastia, the breast enlargement resolves spontaneously. In other situations, more active treatment might be required to correct an underlying condition (such as hyperthyroidism or a benign Leydig cell tumour of the testis) or medications that could cause breast enlargement (such as spironolactone) might need to be discontinued. For men with hypogonadism, administration of androgens might be helpful, as might antiestrogen therapy in men with endogenous overproduction of estrogens. Surgery to remove the enlarged breast tissue might be necessary when gynaecomastia does not resolve spontaneously or with medical therapy.

A tissue-engineered humanized xenograft model of human breast cancer metastasis to bone

PubMed Central

Thibaudeau, Laure; Taubenberger, Anna V.; Holzapfel, Boris M.; Quent, Verena M.; Fuehrmann, Tobias; Hesami, Parisa; Brown, Toby D.; Dalton, Paul D.; Power, Carl A.; Hollier, Brett G.; Hutmacher, Dietmar W.

2014-01-01

ABSTRACT The skeleton is a preferred homing site for breast cancer metastasis. To date, treatment options for patients with bone metastases are mostly palliative and the disease is still incurable. Indeed, key mechanisms involved in breast cancer osteotropism are still only partially understood due to the lack of suitable animal models to mimic metastasis of human tumor cells to a human bone microenvironment. In the presented study, we investigate the use of a human tissue-engineered bone construct to develop a humanized xenograft model of breast cancer-induced bone metastasis in a murine host. Primary human osteoblastic cell-seeded melt electrospun scaffolds in combination with recombinant human bone morphogenetic protein 7 were implanted subcutaneously in non-obese diabetic/severe combined immunodeficient mice. The tissue-engineered constructs led to the formation of a morphologically intact ‘organ’ bone incorporating a high amount of mineralized tissue, live osteocytes and bone marrow spaces. The newly formed bone was largely humanized, as indicated by the incorporation of human bone cells and human-derived matrix proteins. After intracardiac injection, the dissemination of luciferase-expressing human breast cancer cell lines to the humanized bone ossicles was detected by bioluminescent imaging. Histological analysis revealed the presence of metastases with clear osteolysis in the newly formed bone. Thus, human tissue-engineered bone constructs can be applied efficiently as a target tissue for human breast cancer cells injected into the blood circulation and replicate the osteolytic phenotype associated with breast cancer-induced bone lesions. In conclusion, we have developed an appropriate model for investigation of species-specific mechanisms of human breast cancer-related bone metastasis in vivo. PMID:24713276

Local breast density assessment using reacquired mammographic images.

PubMed

García, Eloy; Diaz, Oliver; Martí, Robert; Diez, Yago; Gubern-Mérida, Albert; Sentís, Melcior; Martí, Joan; Oliver, Arnau

2017-08-01

The aim of this paper is to evaluate the spatial glandular volumetric tissue distribution as well as the density measures provided by Volpara™ using a dataset composed of repeated pairs of mammograms, where each pair was acquired in a short time frame and in a slightly changed position of the breast. We conducted a retrospective analysis of 99 pairs of repeatedly acquired full-field digital mammograms from 99 different patients. The commercial software Volpara™ Density Maps (Volpara Solutions, Wellington, New Zealand) is used to estimate both the global and the local glandular tissue distribution in each image. The global measures provided by Volpara™, such as breast volume, volume of glandular tissue, and volumetric breast density are compared between the two acquisitions. The evaluation of the local glandular information is performed using histogram similarity metrics, such as intersection and correlation, and local measures, such as statistics from the difference image and local gradient correlation measures. Global measures showed a high correlation (breast volume R=0.99, volume of glandular tissue R=0.94, and volumetric breast density R=0.96) regardless the anode/filter material. Similarly, histogram intersection and correlation metric showed that, for each pair, the images share a high degree of information. Regarding the local distribution of glandular tissue, small changes in the angle of view do not yield significant differences in the glandular pattern, whilst changes in the breast thickness between both acquisition affect the spatial parenchymal distribution. This study indicates that Volpara™ Density Maps is reliable in estimating the local glandular tissue distribution and can be used for its assessment and follow-up. Volpara™ Density Maps is robust to small variations of the acquisition angle and to the beam energy, although divergences arise due to different breast compression conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

[Application of support vector machine-recursive feature elimination algorithm in Raman spectroscopy for differential diagnosis of benign and malignant breast diseases].

PubMed

Zhang, Haipeng; Fu, Tong; Zhang, Zhiru; Fan, Zhimin; Zheng, Chao; Han, Bing

2014-08-01

To explore the value of application of support vector machine-recursive feature elimination (SVM-RFE) method in Raman spectroscopy for differential diagnosis of benign and malignant breast diseases. Fresh breast tissue samples of 168 patients (all female; ages 22-75) were obtained by routine surgical resection from May 2011 to May 2012 at the Department of Breast Surgery, the First Hospital of Jilin University. Among them, there were 51 normal tissues, 66 benign and 51 malignant breast lesions. All the specimens were assessed by Raman spectroscopy, and the SVM-RFE algorithm was used to process the data and build the mathematical model. Mahalanobis distance and spectral residuals were used as discriminating criteria to evaluate this data-processing method. 1 800 Raman spectra were acquired from the fresh samples of human breast tissues. Based on spectral profiles, the presence of 1 078, 1 267, 1 301, 1 437, 1 653, and 1 743 cm(-1) peaks were identified in the normal tissues; and 1 281, 1 341, 1 381, 1 417, 1 465, 1 530, and 1 637 cm(-1) peaks were found in the benign and malignant tissues. The main characteristic peaks differentiating benign and malignant lesions were 1 340 and 1 480 cm(-1). The accuracy of SVM-RFE in discriminating normal and malignant lesions was 100.0%, while that in the assessment of benign lesions was 93.0%. There are distinct differences among the Raman spectra of normal, benign and malignant breast tissues, and SVM-RFE method can be used to build differentiation model of breast lesions.

Monitoring breast cancer treatment using a Fourier transform infrared spectroscopy-based computational model.

PubMed

Depciuch, J; Kaznowska, E; Golowski, S; Koziorowska, A; Zawlik, I; Cholewa, M; Szmuc, K; Cebulski, J

2017-09-05

Breast cancer affects one in four women, therefore, the search for new diagnostic technologies and therapeutic approaches is of critical importance. This involves the development of diagnostic tools to facilitate the detection of cancer cells, which is useful for assessing the efficacy of cancer therapies. One of the major challenges for chemotherapy is the lack of tools to monitor efficacy during the course of treatment. Vibrational spectroscopy appears to be a promising tool for such a purpose, as it yields Fourier transformation infrared (FTIR) spectra which can be used to provide information on the chemical composition of the tissue. Previous research by our group has demonstrated significant differences between the infrared spectra of healthy, cancerous and post-chemotherapy breast tissue. Furthermore, the results obtained for three extreme patient cases revealed that the infrared spectra of post-chemotherapy breast tissue closely resembles that of healthy breast tissue when chemotherapy is effective (i.e., a good therapeutic response is achieved), or that of cancerous breast tissue when chemotherapy is ineffective. In the current study, we compared the infrared spectra of healthy, cancerous and post-chemotherapy breast tissue. Characteristic parameters were designated for the obtained spectra, spreading the function of absorbance using the Kramers-Kronig transformation and the best fit procedure to obtain Lorentz functions, which represent components of the bands. The Lorentz function parameters were used to develop a physics-based computational model to verify the efficacy of a given chemotherapy protocol in a given case. The results obtained using this model reflected the actual patient data retrieved from medical records (health improvement or no improvement). Therefore, we propose this model as a useful tool for monitoring the efficacy of chemotherapy in patients with breast cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

A breast-specific, negligible-dose scatter correction technique for dedicated cone-beam breast CT: a physics-based approach to improve Hounsfield Unit accuracy

NASA Astrophysics Data System (ADS)

Yang, Kai; Burkett, George, Jr.; Boone, John M.

2014-11-01

The purpose of this research was to develop a method to correct the cupping artifact caused from x-ray scattering and to achieve consistent Hounsfield Unit (HU) values of breast tissues for a dedicated breast CT (bCT) system. The use of a beam passing array (BPA) composed of parallel-holes has been previously proposed for scatter correction in various imaging applications. In this study, we first verified the efficacy and accuracy using BPA to measure the scatter signal on a cone-beam bCT system. A systematic scatter correction approach was then developed by modeling the scatter-to-primary ratio (SPR) in projection images acquired with and without BPA. To quantitatively evaluate the improved accuracy of HU values, different breast tissue-equivalent phantoms were scanned and radially averaged HU profiles through reconstructed planes were evaluated. The dependency of the correction method on object size and number of projections was studied. A simplified application of the proposed method on five clinical patient scans was performed to demonstrate efficacy. For the typical 10-18 cm breast diameters seen in the bCT application, the proposed method can effectively correct for the cupping artifact and reduce the variation of HU values of breast equivalent material from 150 to 40 HU. The measured HU values of 100% glandular tissue, 50/50 glandular/adipose tissue, and 100% adipose tissue were approximately 46, -35, and -94, respectively. It was found that only six BPA projections were necessary to accurately implement this method, and the additional dose requirement is less than 1% of the exam dose. The proposed method can effectively correct for the cupping artifact caused from x-ray scattering and retain consistent HU values of breast tissues.

Nanoscale imaging of clinical specimens using pathology-optimized expansion microscopy.

PubMed

Zhao, Yongxin; Bucur, Octavian; Irshad, Humayun; Chen, Fei; Weins, Astrid; Stancu, Andreea L; Oh, Eun-Young; DiStasio, Marcello; Torous, Vanda; Glass, Benjamin; Stillman, Isaac E; Schnitt, Stuart J; Beck, Andrew H; Boyden, Edward S

2017-08-01

Expansion microscopy (ExM), a method for improving the resolution of light microscopy by physically expanding a specimen, has not been applied to clinical tissue samples. Here we report a clinically optimized form of ExM that supports nanoscale imaging of human tissue specimens that have been fixed with formalin, embedded in paraffin, stained with hematoxylin and eosin, and/or fresh frozen. The method, which we call expansion pathology (ExPath), converts clinical samples into an ExM-compatible state, then applies an ExM protocol with protein anchoring and mechanical homogenization steps optimized for clinical samples. ExPath enables ∼70-nm-resolution imaging of diverse biomolecules in intact tissues using conventional diffraction-limited microscopes and standard antibody and fluorescent DNA in situ hybridization reagents. We use ExPath for optical diagnosis of kidney minimal-change disease, a process that previously required electron microscopy, and we demonstrate high-fidelity computational discrimination between early breast neoplastic lesions for which pathologists often disagree in classification. ExPath may enable the routine use of nanoscale imaging in pathology and clinical research.

Markers of fibrosis and epithelial to mesenchymal transition demonstrate field cancerization in histologically normal tissue adjacent to breast tumors

PubMed Central

Trujillo, Kristina A.; Heaphy, Christopher M.; Mai, Minh; Vargas, Keith M.; Jones, Anna C.; Vo, Phung; Butler, Kimberly S.; Joste, Nancy E.; Bisoffi, Marco; Griffith, Jeffrey K

2011-01-01

Previous studies have shown that a field of genetically altered but histologically normal tissue extends 1 cm or more from the margins of human breast tumors. The extent, composition and biological significance of this field are only partially understood, but the molecular alterations in affected cells could provide mechanisms for limitless replicative capacity, genomic instability and a microenvironment that supports tumor initiation and progression. We demonstrate by microarray, qRT-PCR and immunohistochemistry a signature of differential gene expression that discriminates between patient-matched, tumor-adjacent histologically normal breast tissues located 1 cm and 5 cm from the margins of breast adenocarcinomas (TAHN-1 and TAHN-5, respectively). The signature includes genes involved in extracellular matrix remodeling, wound healing, fibrosis and epithelial to mesenchymal transition (EMT). Myofibroblasts, which are mediators of wound healing and fibrosis, and intra-lobular fibroblasts expressing MMP2, SPARC, TGF-β3, which are inducers of EMT, were both prevalent in TAHN-1 tissues, sparse in TAHN-5 tissues, and absent in normal tissues from reduction mammoplasty. Accordingly, EMT markers S100A4 and vimentin were elevated in both luminal and myoepithelial cells, and EMT markers α-smooth muscle actin and SNAIL were elevated in luminal epithelial cells of TAHN-1 tissues. These results identify cellular processes that are differentially activated between TAHN-1 and TAHN-5 breast tissues, implicate myofibroblasts as likely mediators of these processes, provide evidence that EMT is occurring in histologically normal tissues within the affected field and identify candidate biomarkers to investigate whether or how field cancerization contributes to the development of primary or recurrent breast tumors. PMID:21105047

Breast Cancer Research at NASA

NASA Technical Reports Server (NTRS)

1998-01-01

Isolation of human mammary epithelial cells (HMEC) from breast cancer susceptible tissue; A: Duct element recovered from breast tissue digest. B: Outgrowth of cells from duct element in upper right corner cultured in a standard dish; most cells spontaneousely die during early cell divisions, but a few will establish long-term growth. C: Isolate of long-term frowth HMEC from outgrowth of duct element; cells shown soon after isolation and in early full-cell contact growth in culture in a dish. D: same long-term growth HMEC, but after 3 weeks in late full-cell contact growth in a continuous culture in a dish. Note attempts to reform duct elements but this in two demensions in a dish rather than in three dimensions in tissue. NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cell (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunorous tissue. Credit: Dr. Robert Richmond, NASA/Marshall Space Flight Center (MSFC).

A post-reconstruction method to correct cupping artifacts in cone beam breast computed tomography

PubMed Central

Altunbas, M. C.; Shaw, C. C.; Chen, L.; Lai, C.; Liu, X.; Han, T.; Wang, T.

2007-01-01

In cone beam breast computed tomography (CT), scattered radiation leads to nonuniform biasing of CT numbers known as a cupping artifact. Besides being visual distractions, cupping artifacts appear as background nonuniformities, which impair efficient gray scale windowing and pose a problem in threshold based volume visualization/segmentation. To overcome this problem, we have developed a background nonuniformity correction method specifically designed for cone beam breast CT. With this technique, the cupping artifact is modeled as an additive background signal profile in the reconstructed breast images. Due to the largely circularly symmetric shape of a typical breast, the additive background signal profile was also assumed to be circularly symmetric. The radial variation of the background signals were estimated by measuring the spatial variation of adipose tissue signals in front view breast images. To extract adipose tissue signals in an automated manner, a signal sampling scheme in polar coordinates and a background trend fitting algorithm were implemented. The background fits compared with targeted adipose tissue signal value (constant throughout the breast volume) to get an additive correction value for each tissue voxel. To test the accuracy, we applied the technique to cone beam CT images of mastectomy specimens. After correction, the images demonstrated significantly improved signal uniformity in both front and side view slices. The reduction of both intra-slice and inter-slice variations in adipose tissue CT numbers supported our observations. PMID:17822018

Update on Breast Cancer Detection Using Comb-push Ultrasound Shear Elastography

PubMed Central

Denis, Max; Bayat, Mahdi; Mehrmohammadi, Mohammad; Gregory, Adriana; Song, Pengfei; Whaley, Dana H.; Pruthi, Sandhya; Chen, Shigao; Fatemi, Mostafa; Alizad, Azra

2015-01-01

In this work, tissue stiffness estimates are used to differentiate between benign and malignant breast masses in a group of pre-biopsy patients. The rationale being that breast masses are often stiffer than healthy tissue; furthermore, malignant masses are stiffer than benign masses. The comb-push ultrasound shear elastography (CUSE) method is used to noninvasively assess a tissue’s mechanical properties. CUSE utilizes a simultaneous multiple laterally spaced radiation force (ARF) excitations and detection sequence to reconstruct the region of interest (ROI) shear wave speed map, from which a tissue stiffness property is quantified by Young’s modulus. In this study, the tissue stiffness of 73 breast masses is interrogated. The mean shear wave speeds for malignant masses (3.42 ± 1.32 m/s) were higher than benign breast masses (6.04 ± 1.25 m/s). These speed values correspond to higher stiffness in malignant breast masses (114.9 ± 40.6 kPa) than benign masses (39.4 ± 28.1 kPa and p < 0.001), when tissue elasticity is quantified by Young’s modulus. A Young’s modulus > 83 kPa is established as a cut-off value for differentiating between malignant and benign suspicious breast masses, with receiver operating characteristic curve (ROC) of 89.19% sensitivity, 88.69% specificity, and 0.911 for the area under the curve (AUC). PMID:26688871