Detection and Evaluation of Early Breast Cancer via Magnetic Resonance Imaging: Studies of Mouse Models and Clinical Implementation

DTIC Science & Technology

2009-03-01

compartment modeling on breast 3D DCE-MRI data, to relate kinetic curves to the underlying physiology of the lesions (14–18). However, for low time...classification provided high sensitivity and low specificity in diagnosing malignant lesions. The results demonstrated that the modified EMM fit the 3D...lesion localization and characterization.11 However, for low time resolution 3D DCEMRI data, the accuracy of physiological parameters ob- tained from

Comparison between Breast MRI and Contrast-Enhanced Spectral Mammography

PubMed Central

Łuczyńska, Elżbieta; Heinze-Paluchowska, Sylwia; Hendrick, Edward; Dyczek, Sonia; Ryś, Janusz; Herman, Krzysztof; Blecharz, Paweł; Jakubowicz, Jerzy

2015-01-01

Background The main goal of this study was to compare contrast-enhanced spectral mammography (CESM) and breast magnetic resonance imaging (MRI) with histopathological results and to compare the sensitivity, accuracy, and positive and negative predictive values for both imaging modalities. Material/Methods After ethics approval, CESM and MRI examinations were performed in 102 patients who had suspicious lesions described in conventional mammography. All visible lesions were evaluated independently by 2 experienced radiologists using BI-RADS classifications (scale 1–5). Dimensions of lesions measured with each modality were compared to postoperative histopathology results. Results There were 102 patients entered into CESM/MRI studies and 118 lesions were identified by the combination of CESM and breast MRI. Histopathology confirmed that 81 of 118 lesions were malignant and 37 were benign. Of the 81 malignant lesions, 72 were invasive cancers and 9 were in situ cancers. Sensitivity was 100% with CESM and 93% with breast MRI. Accuracy was 79% with CESM and 73% with breast MRI. ROC curve areas based on BI-RADS were 0.83 for CESM and 0.84 for breast MRI. Lesion size estimates on CESM and breast MRI were similar, both slightly larger than those from histopathology. Conclusions Our results indicate that CESM has the potential to be a valuable diagnostic method that enables accurate detection of malignant breast lesions, has high negative predictive value, and a false-positive rate similar to that of breast MRI. PMID:25963880

Characterization of invisible breast cancers in digital mammography and tomosynthesis: radio-pathological correlation.

PubMed

Aguilar Angulo, P M; Romero Castellano, C; Ruiz Martín, J; Sánchez-Camacho González-Carrato, M P; Cruz Hernández, L M

To review the radio-pathologic features of symptomatic breast cancers not detected at digital mammography (DM) and digital breast tomosynthesis (DBT). Retrospective analysis of 169 lesions from symptomatic patients with breast cancer that were studied with DM, DBT, ultrasound (US) and magnetic resonance (MR). We identified occult lesions (true false negatives) in DM and DBT. Clinical data, density, US and MR findings were analyzed as well as histopathological results. We identified seven occult lesions in DM and DBT. 57% (4/7) of the lesions were identified in high-density breasts (type c and d), and the rest of them in breasts of density type b. Six carcinomas were identified at US and MR (BI-RADS 4 masses); the remaining lesion was only identified at MR. The tumor size was larger than 3cm at MRI in 57% of the lesions. All tumors were ductal infiltrating carcinomas, six of them with high stromal proportion. According to molecular classification, we found only one triple-negative breast cancer, the other lesions were luminal-type. We analyzed the tumor margins of two resected carcinomas that were not treated with neoadjuvant chemotherapy, both lesions presented margins that displaced the adjacent parenchyma without infiltrating it. Occult breast carcinomas in DM and DBT accounted for 4% of lesions detected in patients with symptoms. They were mostly masses, all of them presented the diagnosis of infiltrating ductal carcinoma (with predominance of the luminal immunophenotype) and were detected in breasts of density type b, c and d. Copyright © 2017 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

3D quantitative breast ultrasound analysis for differentiating fibroadenomas and carcinomas smaller than 1cm.

PubMed

Meel-van den Abeelen, A S S; Weijers, G; van Zelst, J C M; Thijssen, J M; Mann, R M; de Korte, C L

2017-03-01

In (3D) ultrasound, accurate discrimination of small solid masses is difficult, resulting in a high frequency of biopsies for benign lesions. In this study, we investigate whether 3D quantitative breast ultrasound (3DQBUS) analysis can be used for improving non-invasive discrimination between benign and malignant lesions. 3D US studies of 112 biopsied solid breast lesions (size <1cm), were included (34 fibroadenomas and 78 invasive ductal carcinomas). The lesions were manually delineated and, based on sonographic criteria used by radiologists, 3 regions of interest were defined in 3D for analysis: ROI (ellipsoid covering the inside of the lesion), PER (peritumoural surrounding: 0.5mm around the lesion), and POS (posterior-tumoural acoustic phenomena: region below the lesion with the same size as delineated for the lesion). After automatic gain correction (AGC), the mean and standard deviation of the echo level within the regions were calculated. For the ROI and POS also the residual attenuation coefficient was estimated in decibel per cm [dB/cm]. The resulting eight features were used for classification of the lesions by a logistic regression analysis. The classification accuracy was evaluated by leave-one-out cross-validation. Receiver operating characteristic (ROC) curves were constructed to assess the performance of the classification. All lesions were delineated by two readers and results were compared to assess the effect of the manual delineation. The area under the ROC curve was 0.86 for both readers. At 100% sensitivity, a specificity of 26% and 50% was achieved for reader 1 and 2, respectively. Inter-reader variability in lesion delineation was marginal and did not affect the accuracy of the technique. The area under the ROC curve of 0.86 was reached for the second reader when the results of the first reader were used as training set yielding a sensitivity of 100% and a specificity of 40%. Consequently, 3DQBUS would have achieved a 40% reduction in biopsies for benign lesions for reader 2, without a decrease in sensitivity. This study shows that 3DQBUS is a promising technique to classify suspicious breast lesions as benign, potentially preventing unnecessary biopsies. Copyright © 2017 Elsevier B.V. All rights reserved.

A deep learning framework for supporting the classification of breast lesions in ultrasound images.

PubMed

Han, Seokmin; Kang, Ho-Kyung; Jeong, Ja-Yeon; Park, Moon-Ho; Kim, Wonsik; Bang, Won-Chul; Seong, Yeong-Kyeong

2017-09-15

In this research, we exploited the deep learning framework to differentiate the distinctive types of lesions and nodules in breast acquired with ultrasound imaging. A biopsy-proven benchmarking dataset was built from 5151 patients cases containing a total of 7408 ultrasound breast images, representative of semi-automatically segmented lesions associated with masses. The dataset comprised 4254 benign and 3154 malignant lesions. The developed method includes histogram equalization, image cropping and margin augmentation. The GoogLeNet convolutionary neural network was trained to the database to differentiate benign and malignant tumors. The networks were trained on the data with augmentation and the data without augmentation. Both of them showed an area under the curve of over 0.9. The networks showed an accuracy of about 0.9 (90%), a sensitivity of 0.86 and a specificity of 0.96. Although target regions of interest (ROIs) were selected by radiologists, meaning that radiologists still have to point out the location of the ROI, the classification of malignant lesions showed promising results. If this method is used by radiologists in clinical situations it can classify malignant lesions in a short time and support the diagnosis of radiologists in discriminating malignant lesions. Therefore, the proposed method can work in tandem with human radiologists to improve performance, which is a fundamental purpose of computer-aided diagnosis.

A deep learning framework for supporting the classification of breast lesions in ultrasound images

NASA Astrophysics Data System (ADS)

Han, Seokmin; Kang, Ho-Kyung; Jeong, Ja-Yeon; Park, Moon-Ho; Kim, Wonsik; Bang, Won-Chul; Seong, Yeong-Kyeong

2017-10-01

In this research, we exploited the deep learning framework to differentiate the distinctive types of lesions and nodules in breast acquired with ultrasound imaging. A biopsy-proven benchmarking dataset was built from 5151 patients cases containing a total of 7408 ultrasound breast images, representative of semi-automatically segmented lesions associated with masses. The dataset comprised 4254 benign and 3154 malignant lesions. The developed method includes histogram equalization, image cropping and margin augmentation. The GoogLeNet convolutionary neural network was trained to the database to differentiate benign and malignant tumors. The networks were trained on the data with augmentation and the data without augmentation. Both of them showed an area under the curve of over 0.9. The networks showed an accuracy of about 0.9 (90%), a sensitivity of 0.86 and a specificity of 0.96. Although target regions of interest (ROIs) were selected by radiologists, meaning that radiologists still have to point out the location of the ROI, the classification of malignant lesions showed promising results. If this method is used by radiologists in clinical situations it can classify malignant lesions in a short time and support the diagnosis of radiologists in discriminating malignant lesions. Therefore, the proposed method can work in tandem with human radiologists to improve performance, which is a fundamental purpose of computer-aided diagnosis.

Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification

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

Drukker, Karen, E-mail: kdrukker@uchicago.edu; Giger, Maryellen L.; Li, Hui

2014-03-15

Purpose: To investigate whether biologic image composition of mammographic lesions can improve upon existing mammographic quantitative image analysis (QIA) in estimating the probability of malignancy. Methods: The study population consisted of 45 breast lesions imaged with dual-energy mammography prior to breast biopsy with final diagnosis resulting in 10 invasive ductal carcinomas, 5 ductal carcinomain situ, 11 fibroadenomas, and 19 other benign diagnoses. Analysis was threefold: (1) The raw low-energy mammographic images were analyzed with an established in-house QIA method, “QIA alone,” (2) the three-compartment breast (3CB) composition measure—derived from the dual-energy mammography—of water, lipid, and protein thickness were assessed, “3CBmore » alone”, and (3) information from QIA and 3CB was combined, “QIA + 3CB.” Analysis was initiated from radiologist-indicated lesion centers and was otherwise fully automated. Steps of the QIA and 3CB methods were lesion segmentation, characterization, and subsequent classification for malignancy in leave-one-case-out cross-validation. Performance assessment included box plots, Bland–Altman plots, and Receiver Operating Characteristic (ROC) analysis. Results: The area under the ROC curve (AUC) for distinguishing between benign and malignant lesions (invasive and DCIS) was 0.81 (standard error 0.07) for the “QIA alone” method, 0.72 (0.07) for “3CB alone” method, and 0.86 (0.04) for “QIA+3CB” combined. The difference in AUC was 0.043 between “QIA + 3CB” and “QIA alone” but failed to reach statistical significance (95% confidence interval [–0.17 to + 0.26]). Conclusions: In this pilot study analyzing the new 3CB imaging modality, knowledge of the composition of breast lesions and their periphery appeared additive in combination with existing mammographic QIA methods for the distinction between different benign and malignant lesion types.« less

Diagnosis of breast masses from dynamic contrast-enhanced and diffusion-weighted MR: a machine learning approach.

PubMed

Cai, Hongmin; Peng, Yanxia; Ou, Caiwen; Chen, Minsheng; Li, Li

2014-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly used for breast cancer diagnosis as supplementary to conventional imaging techniques. Combining of diffusion-weighted imaging (DWI) of morphology and kinetic features from DCE-MRI to improve the discrimination power of malignant from benign breast masses is rarely reported. The study comprised of 234 female patients with 85 benign and 149 malignant lesions. Four distinct groups of features, coupling with pathological tests, were estimated to comprehensively characterize the pictorial properties of each lesion, which was obtained by a semi-automated segmentation method. Classical machine learning scheme including feature subset selection and various classification schemes were employed to build prognostic model, which served as a foundation for evaluating the combined effects of the multi-sided features for predicting of the types of lesions. Various measurements including cross validation and receiver operating characteristics were used to quantify the diagnostic performances of each feature as well as their combination. Seven features were all found to be statistically different between the malignant and the benign groups and their combination has achieved the highest classification accuracy. The seven features include one pathological variable of age, one morphological variable of slope, three texture features of entropy, inverse difference and information correlation, one kinetic feature of SER and one DWI feature of apparent diffusion coefficient (ADC). Together with the selected diagnostic features, various classical classification schemes were used to test their discrimination power through cross validation scheme. The averaged measurements of sensitivity, specificity, AUC and accuracy are 0.85, 0.89, 90.9% and 0.93, respectively. Multi-sided variables which characterize the morphological, kinetic, pathological properties and DWI measurement of ADC can dramatically improve the discriminatory power of breast lesions.

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.

Breast lesions of uncertain malignant nature and limited metastatic potential: Proposals to improve their recognition and clinical management

PubMed Central

Rakha, Emad A.; Badve, Sunil; Eusebi, Vincenzo; Reis-Filho, Jorge S.; Fox, Stephen B.; Dabbs, David J.; Decker, Thomas; Hodi, Zsolt; Ichihara, Shu; Lee, Andrew HS.; Palacios, José; Richardson, Andrea L.; Vincent-Salomon, Anne; Schmitt, Fernando C.; Tan, Puay-Hoon; Tse, Gary M.; Ellis, Ian O.

2016-01-01

Breast lesions comprise a family of heterogeneous entities with variable patterns of presentation, morphology and clinical behaviour. The majority of breast lesions are traditionally classified into benign and malignant conditions and their behaviour can, in the vast majority of cases, be predicted with a reasonable degree of accuracy. However, there remain lesions which show borderline features and lie in a grey-zone between benign and malignant as their behaviour cannot be predicted reliably. Defined pathological categorisation of such lesions is challenging and for some entities is recognised to be subjective and include a range of diagnoses, and forms of terminology, which may trigger over-treatment or under-treatment. The rarity of these lesions makes acquisition of clinical evidence problematic and limits the development of a sufficient evidence base to support informed decision making by clinicians and patients. Emerging molecular evidence is providing a greater understanding of the biology of these lesions, but this may or may not be reflected in their clinical behaviour. Herein we discuss some breast lesions that are associated with uncertainty regarding classification, behaviour and hence management. These include biologically invasive malignant lesions associated with uncertain metastatic potential such as low-grade adenosquamous carcinoma, low-grade fibromatosis-like spindle cell carcinoma and encapsulated papillary carcinoma. Other lesions remain of uncertain malignant nature such as mammary cylindroma, atypical microglandular adenosis, mammary pleomorphic adenoma and infiltrating epitheliosis. The concept of categories of 1) breast lesions of uncertain malignant nature and 2) breast lesions of limited metastatic potential, are proposed with details of which histological entities could be included in each category, and their management implications are discussed. PMID:26348644

Metabolic impact of partial volume correction of [18F]FDG PET-CT oncological studies on the assessment of tumor response to treatment.

PubMed

Stefano, A; Gallivanone, F; Messa, C; Gilardi, M C; Gastiglioni, I

2014-12-01

The aim of this work is to evaluate the metabolic impact of Partial Volume Correction (PVC) on the measurement of the Standard Uptake Value (SUV) from [18F]FDG PET-CT oncological studies for treatment monitoring purpose. Twenty-nine breast cancer patients with bone lesions (42 lesions in total) underwent [18F]FDG PET-CT studies after surgical resection of breast cancer primitives, and before (PET-II) chemotherapy and hormone treatment. PVC of bone lesion uptake was performed on the two [18F]FDG PET-CT studies, using a method based on Recovery Coefficients (RC) and on an automatic measurement of lesion metabolic volume. Body-weight average SUV was calculated for each lesion, with and without PVC. The accuracy, reproducibility, clinical feasibility and the metabolic impact on treatment response of the considered PVC method was evaluated. The PVC method was found clinically feasible in bone lesions, with an accuracy of 93% for lesion sphere-equivalent diameter >1 cm. Applying PVC, average SUV values increased, from 7% up to 154% considering both PET-I and PET-II studies, proving the need of the correction. As main finding, PVC modified the therapy response classification in 6 cases according to EORTC 1999 classification and in 5 cases according to PERCIST 1.0 classification. PVC has an important metabolic impact on the assessment of tumor response to treatment by [18F]FDG PET-CT oncological studies.

Implementation of several mathematical algorithms to breast tissue density classification

NASA Astrophysics Data System (ADS)

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

2014-02-01

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

Computer-Aided Diagnosis of Solid Breast Lesions Using an Ultrasonic Multi-Feature Analysis Procedure

DTIC Science & Technology

2011-01-01

areas. We quantified morphometric features by geometric and fractal analysis of traced lesion boundaries. Although no single parameter can reliably...These include acoustic descriptors (“echogenicity,” “heterogeneity,” “shadowing”) and morphometric descriptors (“area,” “aspect ratio,” “border...quantitative descriptors; some morphometric features (such as border irregularity) also were particularly effective in lesion classification. Our

Shear-wave elastography in the diagnosis of solid breast masses: what leads to false-negative or false-positive results?

PubMed

Yoon, Jung Hyun; Jung, Hae Kyoung; Lee, Jong Tae; Ko, Kyung Hee

2013-09-01

To investigate the factors that have an effect on false-positive or false-negative shear-wave elastography (SWE) results in solid breast masses. From June to December 2012, 222 breast lesions of 199 consecutive women (mean age: 45.3 ± 10.1 years; range, 21 to 88 years) who had been scheduled for biopsy or surgical excision were included. Greyscale ultrasound and SWE were performed in all women before biopsy. Final ultrasound assessments and SWE parameters (pattern classification and maximum elasticity) were recorded and compared with histopathology results. Patient and lesion factors in the 'true' and 'false' groups were compared. Of the 222 masses, 175 (78.8 %) were benign, and 47 (21.2 %) were malignant. False-positive rates of benign masses were significantly higher than false-negative rates of malignancy in SWE patterns, 36.6 % to 6.4 % (P < 0.001). Among both benign and malignant masses, factors showing significance among false SWE features were lesion size, breast thickness and lesion depth (all P < 0.05). All 47 malignant breast masses had SWE images of good quality. False SWE features were more significantly seen in benign masses. Lesion size, breast thickness and lesion depth have significance in producing false results, and this needs consideration in SWE image acquisition. • Shear-wave elastography (SWE) is widely used during breast imaging • At SWE, false-positive rates were significantly higher than false-negative rates • Larger size, breast thickness, depth and fair quality influences false-positive SWE features • Smaller size, larger breast thickness and depth influences false-negative SWE features.

Evolutionary pruning of transfer learned deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis.

PubMed

Samala, Ravi K; Chan, Heang-Ping; Hadjiiski, Lubomir M; Helvie, Mark A; Richter, Caleb; Cha, Kenny

2018-05-01

Deep learning models are highly parameterized, resulting in difficulty in inference and transfer learning for image recognition tasks. In this work, we propose a layered pathway evolution method to compress a deep convolutional neural network (DCNN) for classification of masses in digital breast tomosynthesis (DBT). The objective is to prune the number of tunable parameters while preserving the classification accuracy. In the first stage transfer learning, 19 632 augmented regions-of-interest (ROIs) from 2454 mass lesions on mammograms were used to train a pre-trained DCNN on ImageNet. In the second stage transfer learning, the DCNN was used as a feature extractor followed by feature selection and random forest classification. The pathway evolution was performed using genetic algorithm in an iterative approach with tournament selection driven by count-preserving crossover and mutation. The second stage was trained with 9120 DBT ROIs from 228 mass lesions using leave-one-case-out cross-validation. The DCNN was reduced by 87% in the number of neurons, 34% in the number of parameters, and 95% in the number of multiply-and-add operations required in the convolutional layers. The test AUC on 89 mass lesions from 94 independent DBT cases before and after pruning were 0.88 and 0.90, respectively, and the difference was not statistically significant (p  >  0.05). The proposed DCNN compression approach can reduce the number of required operations by 95% while maintaining the classification performance. The approach can be extended to other deep neural networks and imaging tasks where transfer learning is appropriate.

Evolutionary pruning of transfer learned deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Richter, Caleb; Cha, Kenny

2018-05-01

Deep learning models are highly parameterized, resulting in difficulty in inference and transfer learning for image recognition tasks. In this work, we propose a layered pathway evolution method to compress a deep convolutional neural network (DCNN) for classification of masses in digital breast tomosynthesis (DBT). The objective is to prune the number of tunable parameters while preserving the classification accuracy. In the first stage transfer learning, 19 632 augmented regions-of-interest (ROIs) from 2454 mass lesions on mammograms were used to train a pre-trained DCNN on ImageNet. In the second stage transfer learning, the DCNN was used as a feature extractor followed by feature selection and random forest classification. The pathway evolution was performed using genetic algorithm in an iterative approach with tournament selection driven by count-preserving crossover and mutation. The second stage was trained with 9120 DBT ROIs from 228 mass lesions using leave-one-case-out cross-validation. The DCNN was reduced by 87% in the number of neurons, 34% in the number of parameters, and 95% in the number of multiply-and-add operations required in the convolutional layers. The test AUC on 89 mass lesions from 94 independent DBT cases before and after pruning were 0.88 and 0.90, respectively, and the difference was not statistically significant (p  >  0.05). The proposed DCNN compression approach can reduce the number of required operations by 95% while maintaining the classification performance. The approach can be extended to other deep neural networks and imaging tasks where transfer learning is appropriate.

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).

Interobserver variation in the diagnosis of fibroepithelial lesions of the breast: a multicentre audit by digital pathology.

PubMed

Dessauvagie, Benjamin F; Lee, Andrew H S; Meehan, Katie; Nijhawan, Anju; Tan, Puay Hoon; Thomas, Jeremy; Tie, Bibiana; Treanor, Darren; Umar, Seemeen; Hanby, Andrew M; Millican-Slater, Rebecca

2018-02-13

Fibroepithelial lesions (FELs) of the breast span a morphological continuum including lesions where distinction between cellular fibroadenoma (FA) and benign phyllodes tumour (PT) is difficult. The distinction is clinically important with FAs managed conservatively while equivocal lesions and PTs are managed with surgery. We sought to audit core biopsy diagnoses of equivocal FELs by digital pathology and to investigate whether digital point counting is useful in clarifying FEL diagnoses. Scanned slide images from cores and subsequent excisions of 69 equivocal FELs were examined in a multicentre audit by eight pathologists to determine the agreement and accuracy of core needle biopsy (CNB) diagnoses and by digital point counting of stromal cellularity and expansion to determine if classification could be improved. Interobserver variation was high on CNB with a unanimous diagnosis from all pathologists in only eight cases of FA, diagnoses of both FA and PT on the same CNB in 15 and a 'weak' mean kappa agreement between pathologists (k=0.36). 'Moderate' agreement was observed on CNBs among breast specialists (k=0.44) and on excision samples (k=0.49). Up to 23% of lesions confidently diagnosed as FA on CNB were PT on excision and up to 30% of lesions confidently diagnosed as PT on CNB were FA on excision. Digital point counting did not aid in the classification of FELs. Accurate and reproducible diagnosis of equivocal FELs is difficult, particularly on CNB, resulting in poor interobserver agreement and suboptimal accuracy. Given the diagnostic difficulty, and surgical implications, equivocal FELs should be reported in consultation with experienced breast pathologists as a small number of benign FAs can be selected out from equivocal lesions. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

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.

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.

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.

Lesion classification using clinical and visual data fusion by multiple kernel learning

NASA Astrophysics Data System (ADS)

Kisilev, Pavel; Hashoul, Sharbell; Walach, Eugene; Tzadok, Asaf

2014-03-01

To overcome operator dependency and to increase diagnosis accuracy in breast ultrasound (US), a lot of effort has been devoted to developing computer-aided diagnosis (CAD) systems for breast cancer detection and classification. Unfortunately, the efficacy of such CAD systems is limited since they rely on correct automatic lesions detection and localization, and on robustness of features computed based on the detected areas. In this paper we propose a new approach to boost the performance of a Machine Learning based CAD system, by combining visual and clinical data from patient files. We compute a set of visual features from breast ultrasound images, and construct the textual descriptor of patients by extracting relevant keywords from patients' clinical data files. We then use the Multiple Kernel Learning (MKL) framework to train SVM based classifier to discriminate between benign and malignant cases. We investigate different types of data fusion methods, namely, early, late, and intermediate (MKL-based) fusion. Our database consists of 408 patient cases, each containing US images, textual description of complaints and symptoms filled by physicians, and confirmed diagnoses. We show experimentally that the proposed MKL-based approach is superior to other classification methods. Even though the clinical data is very sparse and noisy, its MKL-based fusion with visual features yields significant improvement of the classification accuracy, as compared to the image features only based classifier.

Automated classification of focal breast lesions according to S-detect: validation and role as a clinical and teaching tool.

PubMed

Di Segni, Mattia; de Soccio, Valeria; Cantisani, Vito; Bonito, Giacomo; Rubini, Antonello; Di Segni, Gabriele; Lamorte, Sveva; Magri, Valentina; De Vito, Corrado; Migliara, Giuseppe; Bartolotta, Tommaso Vincenzo; Metere, Alessio; Giacomelli, Laura; de Felice, Carlo; D'Ambrosio, Ferdinando

2018-06-01

To assess the diagnostic performance and the potential as a teaching tool of S-detect in the assessment of focal breast lesions. 61 patients (age 21-84 years) with benign breast lesions in follow-up or candidate to pathological sampling or with suspicious lesions candidate to biopsy were enrolled. The study was based on a prospective and on a retrospective phase. In the prospective phase, after completion of baseline US by an experienced breast radiologist and S-detect assessment, 5 operators with different experience and dedication to breast radiology performed elastographic exams. In the retrospective phase, the 5 operators performed a retrospective assessment and categorized lesions with BI-RADS 2013 lexicon. Integration of S-detect to in-training operators evaluations was performed by giving priority to S-detect analysis in case of disagreement. 2 × 2 contingency tables and ROC analysis were used to assess the diagnostic performances; inter-rater agreement was measured with Cohen's k; Bonferroni's test was used to compare performances. A significance threshold of p = 0.05 was adopted. All operators showed sensitivity > 90% and varying specificity (50-75%); S-detect showed sensitivity > 90 and 70.8% specificity, with inter-rater agreement ranging from moderate to good. Lower specificities were improved by the addition of S-detect. The addition of elastography did not lead to any improvement of the diagnostic performance. S-detect is a feasible tool for the characterization of breast lesions; it has a potential as a teaching tool for the less experienced operators.

Comparison of the Mammography, Contrast-Enhanced Spectral Mammography and Ultrasonography in a Group of 116 patients.

PubMed

Luczyńska, Elzbieta; Heinze, Sylwia; Adamczyk, Agnieszka; Rys, Janusz; Mitus, Jerzy W; Hendrick, Edward

2016-08-01

Mammography (MG) is the gold-standard in breast cancer detection - the only method documented to reduce breast cancer mortality. Breast ultrasound (US) has been shown to increase sensitivity to breast cancers in screening women with dense breasts. Contrast-enhanced spectral mammography (CESM) is a novel technique intensively developed in the last few years. The goal of this study was to compare the sensitivity, specificity and accuracy of MG, US and CESM in detecting malignant breast lesions. The study included 116 patients. All patients were symptomatic and underwent MG, US and CESM. A radiologist with 20 years of experience in US and MG breast imaging and 1 year of experience in CESM reviewed images acquired in each of the three modalities separately, within an interval of 14-30 days. All identified lesions were confirmed at core biopsy. BI-RADS classifications on US, MG and CESM were compared to histopathology. MG, CESM and US were compared among 116 patients with 137 lesions encountered. Sensitivity of CESM was 100%, significantly higher than that of MG (90%, p<0.004) or US (92%, p<0.01). CESM accuracy was 78%, also higher than MG (69%, p<0.004) and US (70%, p=0.03). There was no statistically significant difference between AUCs for CESM and US (both 0.83). The AUCs of both US and CESM, however, were significantly larger than that of MG (p<0.0004 for each). CESM permitted better detection of malignant lesions than both MG and US, read individually. CESM found lesion enhancement in some benign lesions, as well, yielding a rate of false-positive diagnoses similar to that of MG and US. Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Comparison of synthetic mammography, reconstructed from digital breast tomosynthesis, and digital mammography: evaluation of lesion conspicuity and BI-RADS assessment categories.

PubMed

Mariscotti, Giovanna; Durando, Manuela; Houssami, Nehmat; Fasciano, Mirella; Tagliafico, Alberto; Bosco, Davide; Casella, Cristina; Bogetti, Camilla; Bergamasco, Laura; Fonio, Paolo; Gandini, Giovanni

2017-12-01

To compare the interpretive performance of synthetic mammography (SM), reconstructed from digital breast tomosynthesis (DBT), and full-field digital mammography (FFDM) in a diagnostic setting, covering different conditions of breast density and mammographic signs. A retrospective analysis was conducted on 231 patients, who underwent FFDM and DBT (from which SM images were reconstructed) between September 2014-September 2015. The study included 250 suspicious breast lesions, all biopsy proven: 148 (59.2%) malignant and 13 (5.2%) high-risk lesions were confirmed by surgery, 89 (35.6%) benign lesions had radiological follow-up. Two breast radiologists, blinded to histology, independently reviewed all cases. Readings were performed with SM alone, then with FFDM, collecting data on: probability of malignancy for each finding, lesion conspicuity, mammographic features and dimensions of detected lesions. Agreement between readers was good for BI-RADS classification (Cohen's k-coefficient = 0.93 ± 0.02) and for lesion dimension (Wilcoxon's p = 0.76). Visibility scores assigned to SM and FFDM for each lesion were similar for non-dense and dense breasts, however, there were significant differences (p = 0.0009) in distribution of mammographic features subgroups. SM and FFDM had similar sensitivities in non-dense (respectively 94 vs. 91%) and dense breasts (88 vs. 80%) and for all mammographic signs (93 vs. 87% for asymmetric densities, 96 vs. 75% for distortion, 92 vs. 85% for microcalcifications, and both 94% for masses). Based on all data, there was a significant difference in sensitivity for SM (92%) vs. FFDM (87%), p = 0.02, whereas the two modalities yielded similar results for specificity (SM: 60%, FFDM: 62%, p = 0.21). SM alone showed similar interpretive performance to FFDM, confirming its potential role as an alternative to FFDM in women having tomosynthesis, with the added advantage of halving the patient's dose exposure.

The diagnosis and management of pre-invasive breast disease: Flat epithelial atypia – classification, pathologic features and clinical significance

PubMed Central

Schnitt, Stuart J

2003-01-01

Flat epithelial atypia is a descriptive term that encompasses lesions of the breast terminal duct lobular units in which variably dilated acini are lined by one to several layers of epithelial cells, which are usually columnar in shape and which display low-grade cytologic atypia. Observational studies have suggested that at least some of these lesions may represent either a precursor of ductal carcinoma in situ (DCIS) or the earliest morphological manifestation of DCIS. In contrast, the limited available clinical follow-up data suggest that the risk of both local recurrence and progression of these lesions to invasive cancer is extremely low, supporting the notion that categorizing such lesions as 'clinging carcinoma' and managing them as if they were fully developed DCIS will result in overtreatment of many patients. Additional studies are needed to better understand the biological nature and clinical significance of these lesions. PMID:12927037

Multimodality imaging and state-of-art GPU technology in discriminating benign from malignant breast lesions on real time decision support system

NASA Astrophysics Data System (ADS)

Kostopoulos, S.; Sidiropoulos, K.; Glotsos, D.; Dimitropoulos, N.; Kalatzis, I.; Asvestas, P.; Cavouras, D.

2014-03-01

The aim of this study was to design a pattern recognition system for assisting the diagnosis of breast lesions, using image information from Ultrasound (US) and Digital Mammography (DM) imaging modalities. State-of-art computer technology was employed based on commercial Graphics Processing Unit (GPU) cards and parallel programming. An experienced radiologist outlined breast lesions on both US and DM images from 59 patients employing a custom designed computer software application. Textural features were extracted from each lesion and were used to design the pattern recognition system. Several classifiers were tested for highest performance in discriminating benign from malignant lesions. Classifiers were also combined into ensemble schemes for further improvement of the system's classification accuracy. Following the pattern recognition system optimization, the final system was designed employing the Probabilistic Neural Network classifier (PNN) on the GPU card (GeForce 580GTX) using CUDA programming framework and C++ programming language. The use of such state-of-art technology renders the system capable of redesigning itself on site once additional verified US and DM data are collected. Mixture of US and DM features optimized performance with over 90% accuracy in correctly classifying the lesions.

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.

Transfer learning with convolutional neural networks for lesion classification on clinical breast tomosynthesis

NASA Astrophysics Data System (ADS)

Mendel, Kayla R.; Li, Hui; Sheth, Deepa; Giger, Maryellen L.

2018-02-01

With growing adoption of digital breast tomosynthesis (DBT) in breast cancer screening protocols, it is important to compare the performance of computer-aided diagnosis (CAD) in the diagnosis of breast lesions on DBT images compared to conventional full-field digital mammography (FFDM). In this study, we retrospectively collected FFDM and DBT images of 78 lesions from 76 patients, each containing lesions that were biopsy-proven as either malignant or benign. A square region of interest (ROI) was placed to fully cover the lesion on each FFDM, DBT synthesized 2D images, and DBT key slice images in the cranial-caudal (CC) and mediolateral-oblique (MLO) views. Features were extracted on each ROI using a pre-trained convolutional neural network (CNN). These features were then input to a support vector machine (SVM) classifier, and area under the ROC curve (AUC) was used as the figure of merit. We found that in both the CC view and MLO view, the synthesized 2D image performed best (AUC = 0.814, AUC = 0.881 respectively) in the task of lesion characterization. Small database size was a key limitation in this study, and could lead to overfitting in the application of the SVM classifier. In future work, we plan to expand this dataset and to explore more robust deep learning methodology such as fine-tuning.

Impact of Strain Elastography on BI-RADS classification in small invasive lobular carcinoma.

PubMed

Chiorean, Angelica Rita; Szep, Mădălina Brîndușa; Feier, Diana Sorina; Duma, Magdalena; Chiorean, Marco Andrei; Strilciuc, Ștefan

2018-05-02

The purpose of this study was to determine the impact of strain elastography (SE) on the Breast Imaging Reporting Data System (BI-RADS) classification depending on invasive lobular carcinoma (ILC) lesion size. We performed a retrospective analysis on a sample of 152 female subjects examined between January 2010 - January 2017. SE was performed on all patients and ILC was subsequently diagnosed by surgical or ultrasound-guided biopsy. BI-RADS 1, 2, 6 and Tsukuba BGR cases were omitted. BI-RADS scores were recorded before and after the use of SE. The differences between scores were compared to the ILC tumor size using nonparametric tests and logistic binary regression. We controlled for age, focality, clinical assessment, heredo-collateral antecedents, B-mode and Doppler ultrasound examination. An ROC curve was used to identify the optimal cut-off point for size in relationship to BI-RADS classificationdifference using Youden's index. The histological subtypes of ILC lesions (n=180) included in the sample were luminal A (70%, n=126), luminal B (27.78%, n=50), triple negative (1.67%, n=3) and HER2+ (0.56%, n=1). The BI-RADS classification was higher when SE was performed (Z=- 6.629, p<0.000). The ROC curve identified a cut-off point of 13 mm for size in relationship to BI-RADS classification difference (J=0.670, p<0.000). Small ILC tumors were 17.92% more likely to influence BI-RADS classification (p<0.000). SE offers enhanced BI-RADS classification in small ILC tumors (<13 mm). Sonoelastography brings added value to B-mode breast ultrasound as an adjacent to mammography in breast cancer screening.

Computational Pathology to Discriminate Benign from Malignant Intraductal Proliferations of the Breast

PubMed Central

Oh, Eun-Yeong; Lerwill, Melinda F.; Brachtel, Elena F.; Jones, Nicholas C.; Knoblauch, Nicholas W.; Montaser-Kouhsari, Laleh; Johnson, Nicole B.; Rao, Luigi K. F.; Faulkner-Jones, Beverly; Wilbur, David C.; Schnitt, Stuart J.; Beck, Andrew H.

2014-01-01

The categorization of intraductal proliferative lesions of the breast based on routine light microscopic examination of histopathologic sections is in many cases challenging, even for experienced pathologists. The development of computational tools to aid pathologists in the characterization of these lesions would have great diagnostic and clinical value. As a first step to address this issue, we evaluated the ability of computational image analysis to accurately classify DCIS and UDH and to stratify nuclear grade within DCIS. Using 116 breast biopsies diagnosed as DCIS or UDH from the Massachusetts General Hospital (MGH), we developed a computational method to extract 392 features corresponding to the mean and standard deviation in nuclear size and shape, intensity, and texture across 8 color channels. We used L1-regularized logistic regression to build classification models to discriminate DCIS from UDH. The top-performing model contained 22 active features and achieved an AUC of 0.95 in cross-validation on the MGH data-set. We applied this model to an external validation set of 51 breast biopsies diagnosed as DCIS or UDH from the Beth Israel Deaconess Medical Center, and the model achieved an AUC of 0.86. The top-performing model contained active features from all color-spaces and from the three classes of features (morphology, intensity, and texture), suggesting the value of each for prediction. We built models to stratify grade within DCIS and obtained strong performance for stratifying low nuclear grade vs. high nuclear grade DCIS (AUC = 0.98 in cross-validation) with only moderate performance for discriminating low nuclear grade vs. intermediate nuclear grade and intermediate nuclear grade vs. high nuclear grade DCIS (AUC = 0.83 and 0.69, respectively). These data show that computational pathology models can robustly discriminate benign from malignant intraductal proliferative lesions of the breast and may aid pathologists in the diagnosis and classification of these lesions. PMID:25490766

Invasion in breast lesions: the role of the epithelial-stroma barrier.

PubMed

Rakha, Emad A; Miligy, Islam M; Gorringe, Kylie L; Toss, Michael S; Green, Andrew R; Fox, Stephen B; Schmitt, Fernando C; Tan, Puay-Hoon; Tse, Gary M; Badve, Sunil; Decker, Thomas; Vincent-Salomon, Anne; Dabbs, David J; Foschini, Maria P; Moreno, Filipa; Wentao, Yang; Geyer, Felipe C; Reis-Filho, Jorge S; Pinder, Sarah E; Lakhani, Sunil R; Ellis, Ian O

2018-06-01

Despite the significant biological, behavioural and management differences between ductal carcinoma in situ (DCIS) and invasive carcinoma of the breast, they share many morphological and molecular similarities. Differentiation of these two different lesions in breast pathological diagnosis is based typically on the presence of an intact barrier between the malignant epithelial cells and stroma; namely, the myoepithelial cell (MEC) layer and surrounding basement membrane (BM). Despite being robust diagnostic criteria, the identification of MECs and BM to differentiate in-situ from invasive carcinoma is not always straightforward. The MEC layer around DCIS may be interrupted and/or show an altered immunoprofile. MECs may be absent in some benign locally infiltrative lesions such as microglandular adenosis and infiltrating epitheliosis, and occasionally in non-infiltrative conditions such as apocrine lesions, and in these contexts this does not denote malignancy or invasive disease with metastatic potential. MECs may also be absent around some malignant lesions such as some forms of papillary carcinoma, yet these behave in an indolent fashion akin to some DCIS. In Paget's disease, malignant mammary epithelial cells extend anteriorly from the ducts to infiltrate the epidermis of the nipple but do not typically infiltrate through the BM into the dermis. Conversely, BM-like material can be seen around invasive carcinoma cells and around metastatic tumour cell deposits. Here, we review the role of MECs and BM in breast pathology and highlight potential clinical implications. We advise caution in interpretation of MEC features in breast pathology and mindfulness of the substantive evidence base in the literature associated with behaviour and clinical outcome of lesions classified as benign on conventional morphological examination before changing classification to an invasive lesion on the sole basis of MEC characteristics. © 2017 John Wiley & Sons Ltd.

A new Fourier transform based CBIR scheme for mammographic mass classification: a preliminary invariance assessment

NASA Astrophysics Data System (ADS)

Gundreddy, Rohith Reddy; Tan, Maxine; Qui, Yuchen; Zheng, Bin

2015-03-01

The purpose of this study is to develop and test a new content-based image retrieval (CBIR) scheme that enables to achieve higher reproducibility when it is implemented in an interactive computer-aided diagnosis (CAD) system without significantly reducing lesion classification performance. This is a new Fourier transform based CBIR algorithm that determines image similarity of two regions of interest (ROI) based on the difference of average regional image pixel value distribution in two Fourier transform mapped images under comparison. A reference image database involving 227 ROIs depicting the verified soft-tissue breast lesions was used. For each testing ROI, the queried lesion center was systematically shifted from 10 to 50 pixels to simulate inter-user variation of querying suspicious lesion center when using an interactive CAD system. The lesion classification performance and reproducibility as the queried lesion center shift were assessed and compared among the three CBIR schemes based on Fourier transform, mutual information and Pearson correlation. Each CBIR scheme retrieved 10 most similar reference ROIs and computed a likelihood score of the queried ROI depicting a malignant lesion. The experimental results shown that three CBIR schemes yielded very comparable lesion classification performance as measured by the areas under ROC curves with the p-value greater than 0.498. However, the CBIR scheme using Fourier transform yielded the highest invariance to both queried lesion center shift and lesion size change. This study demonstrated the feasibility of improving robustness of the interactive CAD systems by adding a new Fourier transform based image feature to CBIR schemes.

Classification of small lesions on dynamic breast MRI: Integrating dimension reduction and out-of-sample extension into CADx methodology

PubMed Central

Nagarajan, Mahesh B.; Huber, Markus B.; Schlossbauer, Thomas; Leinsinger, Gerda; Krol, Andrzej; Wismüller, Axel

2014-01-01

Objective While dimension reduction has been previously explored in computer aided diagnosis (CADx) as an alternative to feature selection, previous implementations of its integration into CADx do not ensure strict separation between training and test data required for the machine learning task. This compromises the integrity of the independent test set, which serves as the basis for evaluating classifier performance. Methods and Materials We propose, implement and evaluate an improved CADx methodology where strict separation is maintained. This is achieved by subjecting the training data alone to dimension reduction; the test data is subsequently processed with out-of-sample extension methods. Our approach is demonstrated in the research context of classifying small diagnostically challenging lesions annotated on dynamic breast magnetic resonance imaging (MRI) studies. The lesions were dynamically characterized through topological feature vectors derived from Minkowski functionals. These feature vectors were then subject to dimension reduction with different linear and non-linear algorithms applied in conjunction with out-of-sample extension techniques. This was followed by classification through supervised learning with support vector regression. Area under the receiver-operating characteristic curve (AUC) was evaluated as the metric of classifier performance. Results Of the feature vectors investigated, the best performance was observed with Minkowski functional ’perimeter’ while comparable performance was observed with ’area’. Of the dimension reduction algorithms tested with ’perimeter’, the best performance was observed with Sammon’s mapping (0.84 ± 0.10) while comparable performance was achieved with exploratory observation machine (0.82 ± 0.09) and principal component analysis (0.80 ± 0.10). Conclusions The results reported in this study with the proposed CADx methodology present a significant improvement over previous results reported with such small lesions on dynamic breast MRI. In particular, non-linear algorithms for dimension reduction exhibited better classification performance than linear approaches, when integrated into our CADx methodology. We also note that while dimension reduction techniques may not necessarily provide an improvement in classification performance over feature selection, they do allow for a higher degree of feature compaction. PMID:24355697

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

PubMed

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

2018-05-01

Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentially be improved by machine learning. To evaluate classification of malignant and benign tumors and breast cancer subtypes using support vector machine (SVM). Prospective. Fifty-one patients with benign (n = 23) and malignant (n = 28) breast tumors (26 ER+, whereof six were HER2+). Patients were imaged with DW-MRI (3T) using twice refocused spin-echo echo-planar imaging with echo time / repetition time (TR/TE) = 9000/86 msec, 90 × 90 matrix size, 2 × 2 mm in-plane resolution, 2.5 mm slice thickness, and 13 b-values. Apparent diffusion coefficient (ADC), relative enhanced diffusivity (RED), and the intravoxel incoherent motion (IVIM) parameters diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The histogram properties (median, mean, standard deviation, skewness, kurtosis) were used as features in SVM (10-fold cross-validation) for differentiation of lesions and subtyping. Accuracies of the SVM classifications were calculated to find the combination of features with highest prediction accuracy. Mann-Whitney tests were performed for univariate comparisons. For benign versus malignant tumors, univariate analysis found 11 histogram properties to be significant differentiators. Using SVM, the highest accuracy (0.96) was achieved from a single feature (mean of RED), or from three feature combinations of IVIM or ADC. Combining features from all models gave perfect classification. No single feature predicted HER2 status of ER + tumors (univariate or SVM), although high accuracy (0.90) was achieved with SVM combining several features. Importantly, these features had to include higher-order statistics (kurtosis and skewness), indicating the importance to account for heterogeneity. Our findings suggest that SVM, using features from a combination of diffusion models, improves prediction accuracy for differentiation of benign versus malignant breast tumors, and may further assist in subtyping of breast cancer. 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1205-1216. © 2017 International Society for Magnetic Resonance in Medicine.

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.

Detection of breast cancer in automated 3D breast ultrasound

NASA Astrophysics Data System (ADS)

Tan, Tao; Platel, Bram; Mus, Roel; Karssemeijer, Nico

2012-03-01

Automated 3D breast ultrasound (ABUS) is a novel imaging modality, in which motorized scans of the breasts are made with a wide transducer through a membrane under modest compression. The technology has gained high interest and may become widely used in screening of dense breasts, where sensitivity of mammography is poor. ABUS has a high sensitivity for detecting solid breast lesions. However, reading ABUS images is time consuming, and subtle abnormalities may be missed. Therefore, we are developing a computer aided detection (CAD) system to help reduce reading time and errors. In the multi-stage system we propose, segmentations of the breast and nipple are performed, providing landmarks for the detection algorithm. Subsequently, voxel features characterizing coronal spiculation patterns, blobness, contrast, and locations with respect to landmarks are extracted. Using an ensemble of classifiers, a likelihood map indicating potential malignancies is computed. Local maxima in the likelihood map are determined using a local maxima detector and form a set of candidate lesions in each view. These candidates are further processed in a second detection stage, which includes region segmentation, feature extraction and a final classification. Region segmentation is performed using a 3D spiral-scanning dynamic programming method. Region features include descriptors of shape, acoustic behavior and texture. Performance was determined using a 78-patient dataset with 93 images, including 50 malignant lesions. We used 10-fold cross-validation. Using FROC analysis we found that the system obtains a lesion sensitivity of 60% and 70% at 2 and 4 false positives per image respectively.

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

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.

WE-G-207-05: Relationship Between CT Image Quality, Segmentation Performance, and Quantitative Image Feature Analysis

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

Lee, J; Nishikawa, R; Reiser, I

Purpose: Segmentation quality can affect quantitative image feature analysis. The objective of this study is to examine the relationship between computed tomography (CT) image quality, segmentation performance, and quantitative image feature analysis. Methods: A total of 90 pathology proven breast lesions in 87 dedicated breast CT images were considered. An iterative image reconstruction (IIR) algorithm was used to obtain CT images with different quality. With different combinations of 4 variables in the algorithm, this study obtained a total of 28 different qualities of CT images. Two imaging tasks/objectives were considered: 1) segmentation and 2) classification of the lesion as benignmore » or malignant. Twenty-three image features were extracted after segmentation using a semi-automated algorithm and 5 of them were selected via a feature selection technique. Logistic regression was trained and tested using leave-one-out-cross-validation and its area under the ROC curve (AUC) was recorded. The standard deviation of a homogeneous portion and the gradient of a parenchymal portion of an example breast were used as an estimate of image noise and sharpness. The DICE coefficient was computed using a radiologist’s drawing on the lesion. Mean DICE and AUC were used as performance metrics for each of the 28 reconstructions. The relationship between segmentation and classification performance under different reconstructions were compared. Distributions (median, 95% confidence interval) of DICE and AUC for each reconstruction were also compared. Results: Moderate correlation (Pearson’s rho = 0.43, p-value = 0.02) between DICE and AUC values was found. However, the variation between DICE and AUC values for each reconstruction increased as the image sharpness increased. There was a combination of IIR parameters that resulted in the best segmentation with the worst classification performance. Conclusion: There are certain images that yield better segmentation or classification performance. The best segmentation Result does not necessarily lead to the best classification Result. This work has been supported in part by grants from the NIH R21-EB015053. R Nishikawa is receives royalties form Hologic, Inc.« less

[Practical problems in breast screening. Columnar cell lesions including flat epithelial atypia and lobular neoplasia].

PubMed

Nährig, J

2008-11-01

Columnar cell lesions (CCL) and lobular neoplasia (LN) are encountered with increasing frequency in breast screening biopsies. CCLs are frequently associated with microcalcifications, whereas LN is an incidental finding in most cases. Flat epithelia atypia (FEA) the atypical variant of CLL, LN and atypical ductal hyperplasia (ADH) are frequently associated lesions. Molecular genetic studies of CCL, ductal carcinoma in situ (DCIS) and low grade invasive carcinomas revealed similar chromosomal alterations supporting the assumption that CCLs are neoplastic proliferations. The frequent association of FEA together with well differentiated invasive carcinomas provides further evidence of this concept. There is no internationally accepted classification of CCLs at present. CDH1-gene mutations are the cardinal feature of LN and invasive lobular carcinoma. In immunohistochemically CDH1-positive cases, alternative genetic alterations of the CDH1 pathway can lead to functional loss of CDH1. In our opinion morphologically and immunohistochemically hybrid lesions may represent this group of lobular lesions. Recent follow-up data suggest a higher rate of ipsilateral carcinomas in patients with previously diagnosed LN. It is currently an open question whether FEA and LN are members of a common family of intralobular proliferations, which are non-obligatory precursors of a low nuclear grade breast neoplasia family.

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

Time to enhancement derived from ultrafast breast MRI as a novel parameter to discriminate benign from malignant breast lesions.

PubMed

Mus, Roel D; Borelli, Cristina; Bult, Peter; Weiland, Elisabeth; Karssemeijer, Nico; Barentsz, Jelle O; Gubern-Mérida, Albert; Platel, Bram; Mann, Ritse M

2017-04-01

To investigate time to enhancement (TTE) as novel dynamic parameter for lesion classification in breast magnetic resonance imaging (MRI). In this retrospective study, 157 women with 195 enhancing abnormalities (99 malignant and 96 benign) were included. All patients underwent a bi-temporal MRI protocol that included ultrafast time-resolved angiography with stochastic trajectory (TWIST) acquisitions (1.0×0.9×2.5mm, temporal resolution 4.32s), during the inflow of contrast agent. TTE derived from TWIST series and relative enhancement versus time curve type derived from volumetric interpolated breath-hold examination (VIBE) series were assessed and combined with basic morphological information to differentiate benign from malignant lesions. Receiver operating characteristic analysis and kappa statistics were applied. TTE had a significantly better discriminative ability than curve type (p<0.001 and p=0.026 for reader 1 and 2, respectively). Including morphology, sensitivity of TWIST and VIBE assessment was equivalent (p=0.549 and p=0.344, respectively). Specificity and diagnostic accuracy were significantly higher for TWIST than for VIBE assessment (p<0.001). Inter-reader agreement in differentiating malignant from benign lesions was almost perfect for TWIST evaluation (κ=0.86) and substantial for conventional assessment (κ=0.75). TTE derived from ultrafast TWIST acquisitions is a valuable parameter that allows robust differentiation between malignant and benign breast lesions with high accuracy. Copyright © 2017 Elsevier B.V. All rights reserved.

Diagnostic Pitfalls in Papillary Lesions of the Breast: Experience from a Single Tertiary Care Center

PubMed Central

Basavaiah, Sridevi Hanaganahalli; Sreeram, Saraswathy; Suresh, Pooja Kundapur; Kini, Hema; Adiga, Deepa; Sahu, Kausalya Kumari; Pai, Radha R

2016-01-01

Introduction Papillary neoplasms are a group of lesions that are characterized by presence of papillae supported by fibrovascular cores lined by epithelial cells with or without myoepithelial cell layer. These neoplasms may be benign, atypical or malignant. Aims This study was conducted to analyse the clinicopathological characteristics of papillary lesions of the breast. Materials and Methods A retrospective and prospective analysis of 34 cases of papillary lesions received over a period of 7 years from 2009 to 2015 was done. The patient’s clinical details were collected from medical archives and the histopathological findings were reviewed. The lesions were classified into benign, atypical and malignant categories. Results During the study period, there were 34 cases of papillary lesions of breast. The mean age was 58 years. The central quadrant was the most common location (66.6%). The most common presenting complaint was lump (76.5% cases). Papillary lesions presented more commonly as solitary lump (82.4%) rather than multifocal disease. Benign papillary lesions were more common than the atypical and malignant lesions. The most common papillary lesion accounting for 43% of the cases was intraductal papilloma. Malignant lesions accounted for 41.2% cases with intraductal papillary carcinoma and invasive papillary carcinoma constituting 14.7% cases each. Conclusion Diagnosis of papillary carcinoma is challenging and its classification includes different entities that have specific diagnostic criteria. Due to their heterozygosity in morphology with benign, atypical and malignant subtypes, morphological features such as type of fibrovascular core and continuity of myoepithelial layer along with immunohistochemical stains for myoepithelial cells should be considered for proper and accurate diagnosis. PMID:27656446

Evaluation of a prospective scoring system designed for a multicenter breast MR imaging screening study.

PubMed

Warren, Ruth M L; Thompson, Deborah; Pointon, Linda J; Hoff, Rebecca; Gilbert, Fiona J; Padhani, Anwar R; Easton, Douglas F; Lakhani, Sunil R; Leach, Martin O

2006-06-01

To evaluate prospectively the accuracy of a lesion classification system designed for use in a magnetic resonance (MR) imaging high-breast-cancer-risk screening study. All participating patients provided written informed consent. Ethics committee approval was obtained. The results of 1541 contrast material-enhanced breast MR imaging examinations were analyzed; 1441 screening examinations were performed in 638 women aged 24-51 years at high risk for breast cancer, and 100 examinations were performed in 100 women aged 23-81 years. Lesion analysis was performed in 991 breasts, which were divided into design (491 breasts) and testing (500 breasts) sets. The reference standard was histologic analysis of biopsy samples, fine-needle aspiration cytology, or minimal follow-up of 24 months. The scoring system involved the use of five features: morphology (MOR), pattern of enhancement (POE), percentage of maximal focal enhancement (PMFE), maximal signal intensity-time ratio (MITR), and pattern of contrast material washout (POCW). The system was evaluated by means of (a) assessment of interreader agreement, as expressed in kappa statistics, for 315 breasts in which both readers analyzed the same lesion, (b) assessment of the diagnostic accuracy of the scored components with receiver operating characteristic curve analysis, and (c) logistic regression analysis to determine which components of the scoring system were critical to the final score. A new simplified scoring system developed with the design set was applied to the testing set. There was moderate reader agreement regarding overall lesion outcome (ie, malignant, suspicious, or benign) (kappa=0.58) and less agreement regarding the scored components. The area under the receiver operating characteristic curve (AUC) for the overall lesion score, 0.88, was higher than the AUC for any one component. The components MOR, POE, and POCW yielded the best overall result. PMFE and MITR did not contribute to diagnostic utility. Applying a simplified scoring system to the testing set yielded a nonsignificantly (P=.2) higher AUC than did applying the original scoring system (sensitivity, 84%; specificity, 86.0%). Good diagnostic accuracy can be achieved by using simple qualitative descriptors of lesion enhancement, including POCW. In the context of screening, quantitative enhancement parameters appear to be less useful for lesion characterization. Copyright (c) RSNA, 2006.

Computer-Aided Diagnosis for Breast Ultrasound Using Computerized BI-RADS Features and Machine Learning Methods.

PubMed

Shan, Juan; Alam, S Kaisar; Garra, Brian; Zhang, Yingtao; Ahmed, Tahira

2016-04-01

This work identifies effective computable features from the Breast Imaging Reporting and Data System (BI-RADS), to develop a computer-aided diagnosis (CAD) system for breast ultrasound. Computerized features corresponding to ultrasound BI-RADs categories were designed and tested using a database of 283 pathology-proven benign and malignant lesions. Features were selected based on classification performance using a "bottom-up" approach for different machine learning methods, including decision tree, artificial neural network, random forest and support vector machine. Using 10-fold cross-validation on the database of 283 cases, the highest area under the receiver operating characteristic (ROC) curve (AUC) was 0.84 from a support vector machine with 77.7% overall accuracy; the highest overall accuracy, 78.5%, was from a random forest with the AUC 0.83. Lesion margin and orientation were optimum features common to all of the different machine learning methods. These features can be used in CAD systems to help distinguish benign from worrisome lesions. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. All rights reserved.

Targeting Therapy Resistant Tumor Vessels

DTIC Science & Technology

2008-08-01

No 6 C8161 s.c. xenografts No 5 K14-HPV16 skin cancer No 4 MDA-MB-435 orthotopic xenografts No 4 AGR TRAMP PIN lesions TRAMP PIN lesions Yes 18 TRAMP...CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18 . NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON USAMRMC a. REPORT U b. ABSTRACT U c...Summary We developed three tumor models under this project: 4T1 mouse breast cancer and MDA-MB-435 human cancer xenograft tumors treated with anti

Diagnostic value of commercially available shear-wave elastography for breast cancers: integration into BI-RADS classification with subcategories of category 4.

PubMed

Youk, Ji Hyun; Gweon, Hye Mi; Son, Eun Ju; Han, Kyung Hwa; Kim, Jeong-Ah

2013-10-01

To evaluate the diagnostic performance of shear-wave elastography (SWE) for breast cancer and to determine whether the integration of SWE into BI-RADS with subcategories of category 4 improves the diagnostic performance. A total of 389 breast masses (malignant 120, benign 269) in 324 women who underwent SWE before ultrasound-guided core biopsy or surgery were included. The qualitative SWE feature was assessed using a four-colour overlay pattern. Quantitative elasticity values including the lesion-to-fat elasticity ratio (Eratio) were measured. Diagnostic performance of B-mode ultrasound, SWE, or their combined studies was compared using the area under the ROC curve (AUC). AUC of Eratio (0.952) was the highest among elasticity values (mean, maximum, and minimum elasticity, 0.949, 0.939, and 0.928; P = 0.04) and AUC of colour pattern was 0.947. AUC of combined studies was significantly higher than for a single study (P < 0.0001). When adding SWE to category 4 lesions, lesions were dichotomised according to % of malignancy: 2.1 % vs. 43.2 % (category 4a) and 0 % vs. 100 % (category 4b) for Eratio and 2.4 % vs. 25.8 % (category 4a) for colour pattern (P < 0.05). Shear-wave elastography showed a good diagnostic performance. Adding SWE features to BI-RADS improved the diagnostic performance and may be helpful to stratify category 4 lesions. • Quantitative and qualitative shear-wave elastography provides further diagnostic information during breast ultrasound. • The elasticity ratio (E ratio ) showed the best diagnostic performance in SWE. • E ratio and four-colour overlay pattern significantly differed between benign and malignant lesions. • SWE features allowed further stratification of BI-RADS category 4 lesions.

Changing attitudes toward needle biopsies of breast cancer in Shanghai: experience and current status over the past 8 years

PubMed Central

Hao, Shuang; Liu, Zhe-Bin; Ling, Hong; Chen, Jia-Jian; Shen, Ju-Ping; Yang, Wen-Tao; Shao, Zhi-Min

2015-01-01

Diagnostic patterns in breast cancer have greatly changed over the past few decades, and core needle biopsy (CNB) has become a reliable procedure for detecting breast cancer without invasive surgery. To estimate the changing diagnostic patterns of breast cancer in urban Shanghai, 11,947 women with breast lesions detected by preoperative needle biopsy between January 1995 and December 2012 were selected from the Shanghai Cancer Data base, which integrates information from approximately 50% of breast cancer patients in Shanghai. The CNB procedure uses an automated prone unit, biopsy gun, and 14-gauge needles under freehand or ultrasound guidance and was performed by experienced radiologists and surgeons specializing in needle biopsies. Diagnosis and classification for each patient were independently evaluated by pathologists. Over the indicated 8-year period, biopsy type consisted of 11,947 ultrasound-guided core needle biopsies (UCNBs), 2,015 ultrasound-guided vacuum-assisted biopsies (UVABs), and 654 stereotactic X-ray-guided vacuum-assisted biopsies (XVABs). For all the 11,947 women included in this study, image-guided needle biopsy was the initial diagnostic procedure. Approximately 81.0% of biopsied samples were histopathologically determined to be malignant lesions, 5.5% were determined to be high-risk lesions, and 13.5% were determined to be benign lesions. The number of patients choosing UCNB increased at the greatest rate, and UCNB has become a standard procedure for histodiagnosis because it is inexpensive, convenient, and accurate. The overall false-negative rate of CNB was 1.7%, and the specific false-negative rates for UCNB, UVAB, and XVAB, were 1.7%, 0%, and 0%, respectively. This study suggests that the use of preoperative needle biopsy as the initial breast cancer diagnostic procedure is acceptable in urban Shanghai. Preoperative needle biopsy is now a standard procedure in the Shanghai Cancer Center because it may reduce the number of surgeries needed to treat breast cancer. PMID:26491359

Performance comparison of deep learning and segmentation-based radiomic methods in the task of distinguishing benign and malignant breast lesions on DCE-MRI

NASA Astrophysics Data System (ADS)

Antropova, Natasha; Huynh, Benjamin; Giger, Maryellen

2017-03-01

Intuitive segmentation-based CADx/radiomic features, calculated from the lesion segmentations of dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) have been utilized in the task of distinguishing between malignant and benign lesions. Additionally, transfer learning with pre-trained deep convolutional neural networks (CNNs) allows for an alternative method of radiomics extraction, where the features are derived directly from the image data. However, the comparison of computer-extracted segmentation-based and CNN features in MRI breast lesion characterization has not yet been conducted. In our study, we used a DCE-MRI database of 640 breast cases - 191 benign and 449 malignant. Thirty-eight segmentation-based features were extracted automatically using our quantitative radiomics workstation. Also, 2D ROIs were selected around each lesion on the DCE-MRIs and directly input into a pre-trained CNN AlexNet, yielding CNN features. Each method was investigated separately and in combination in terms of performance in the task of distinguishing between benign and malignant lesions. Area under the ROC curve (AUC) served as the figure of merit. Both methods yielded promising classification performance with round-robin cross-validated AUC values of 0.88 (se =0.01) and 0.76 (se=0.02) for segmentationbased and deep learning methods, respectively. Combination of the two methods enhanced the performance in malignancy assessment resulting in an AUC value of 0.91 (se=0.01), a statistically significant improvement over the performance of the CNN method alone.

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

Breast fine-needle aspiration samples reported as "proliferative breast lesion": clinical utility of the subcategory "proliferative breast lesion with atypia".

PubMed

Zhao, Chengquan; Raza, Anwar; Martin, Sue E; Pan, Jiangqiu; Greaves, Timothy S; Cobb, Camilla J

2009-04-25

The fine-needle aspiration (FNA) diagnosis of proliferative breast lesion is an indeterminate category. The aim of this correlative study was to determine whether a subcategory of "proliferative breast lesion with atypia" was achievable and whether this subcategory has management utility. Breast FNA cases from 2000 through 2005 diagnosed as proliferative breast lesion and proliferative breast lesion with atypia were retrieved. Both cytologic and surgical slides of these cases were reviewed blindly. A cytologic diagnosis of proliferative breast lesion (without atypia) or proliferative breast lesion with atypia was used if the findings of the proliferative breast lesion did not fit a more specific category. Of the 3934 breast FNAs performed on palpable breast masses from January 2000 to December 2005 at the LAC + USC Medical Center, 317 (8.1%) were diagnosed cytologically as proliferative breast lesion with atypia, without atypia or without mention of atypia. There was subsequent histopathology on 201 of these cases. After the cytologic smears were reviewed, 29 cases were excluded from this study. Of the 172 remaining cases, 21 (12.2%) were found to be malignant and the remaining 151 (87.8%) were found to be benign on histology. Of the malignant cases, 90% had an FNA diagnosis of proliferative breast lesion with atypia; of the benign cases, 78% were interpreted as proliferative breast lesion without atypia. Proliferative breast lesion with atypia was clinically significant because it was associated with a significantly increased likelihood of malignancy compared with proliferative breast lesion without atypia. Most of the malignancies had hypocellularity or low nuclear grade on the FNA smears. Fibroadenoma accounted for most of the benign lesions in both proliferative breast lesion and proliferative breast lesion with atypia. (c) 2009 American Cancer Society.

[Malignant and benign diseases of the breast in 41 male patients: mammography, sonography and pathohistological correlations].

PubMed

Partik, B; Mallek, R; Rudas, M; Pokieser, P; Wunderbaldinger, P; Helbich, T H

2001-11-01

The goal of our study was to evaluate findings in mammography and sonography in male patients with pathohistologically proven diseases of the breast. Mammographies and sonographies, which were obtained in 41 male patients in a 6-year period, were retrospectively evaluated in accordance with the BI-RADS(R) classification. Histologically 13 carcinomas, 21 gynecomastias, 3 pseudogynecomastias, 2 epithelial inclusion cysts and 2 other benign lesions were diagnosed. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of mammography in differentiation of benign versus malignant disease were 92 %, 89 %, 80 %, 96 % and 90 %, respectively. Additional sonography did not change these results. However, sonography increased diagnostic confidence in 18.2 % (2/11) of suspicious lesions. In our study the invasive ductal carcinoma of male patients was a predominantly lobulated, ill-defined lesion in mammography and sonography. The differentiation of carcinoma to pseudogynecomastia and diffuse or dendritic gynecomastia was securely feasible. However, we could not reliably distinguish between carcinoma and some benign mass lesions. In cases of mammographically diagnosed masses or unclear mammography, additional sonography should be performed to increase the diagnostic confidence.

Digital mammographic tumor classification using transfer learning from deep convolutional neural networks.

PubMed

Huynh, Benjamin Q; Li, Hui; Giger, Maryellen L

2016-07-01

Convolutional neural networks (CNNs) show potential for computer-aided diagnosis (CADx) by learning features directly from the image data instead of using analytically extracted features. However, CNNs are difficult to train from scratch for medical images due to small sample sizes and variations in tumor presentations. Instead, transfer learning can be used to extract tumor information from medical images via CNNs originally pretrained for nonmedical tasks, alleviating the need for large datasets. Our database includes 219 breast lesions (607 full-field digital mammographic images). We compared support vector machine classifiers based on the CNN-extracted image features and our prior computer-extracted tumor features in the task of distinguishing between benign and malignant breast lesions. Five-fold cross validation (by lesion) was conducted with the area under the receiver operating characteristic (ROC) curve as the performance metric. Results show that classifiers based on CNN-extracted features (with transfer learning) perform comparably to those using analytically extracted features [area under the ROC curve [Formula: see text

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.

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.

Investigation of Three-Group Classifiers to Fully Automate Detection and Classification of Breast Lesions in an Intelligent CAD Mammography Workstation

DTIC Science & Technology

2007-05-01

evaluation of approximations,” tech. rep., Dep. Sistemes Informàtics i Computació, Univ. Politècnica de València (Spain), 2003. [7] D. C. Edwards, C. E...Maryellen L. Giger, scientific collaborator • Lorenzo Pesce, computer programmer 16 C The Hypervolume under the ROC Hypersurface of “Near-Guessing...the simple model we have just described corresponds in the two-class classification task to ROC analysis performed ‘‘per ARTICLE IN PRESS

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

Factors affecting the palpability of breast lesion by self-examination.

PubMed

Lam, W W M; Chan, C P; Chan, C F; Mak, C C C; Chan, C F; Chong, K W H; Leung, M H J; Tang, M H

2008-03-01

This study aims to assess the accuracy of detection of breast lesion by breast self-examination and to assess different factors affecting the accuracy. All consecutive Chinese female patients, who attended our breast imaging unit in 2001, completed our questionnaire, had retrievable hard copy films, and had more than three years clinical follow-up, were recruited for this study. Different factors, such as age, menopausal status, previous experience of breastfeeding, family history of breast cancer, previous history of mastectomy or lumpectomy, hormonal therapy, oral contraceptive pills and previous history of mammography, were correlated with accuracy in self-detection of breast lesions retrospectively. The nature, size and location of the lesion, and breast size based on imaging, were also correlated with the accuracy in self-detection of breast lesions. A total of 163 questionnaires were analysed. 111 patients detected a breast lesion themselves and 24 of these lesions were false-positives. A total of 173 lesions (27 cancerous, 146 benign lesions) were documented by either ultrasonography and/or mammography, and confirmed by either histology or three-year clinical follow-up. The overall sensitivity in detecting both benign and malignant breast lesions was 71% when number of breast lesions was used as the denominator, and up to 78% sensitivity was achieved when number of patients was used as the denominator. History of mastectomy, and size and nature of the lesions were found to affect the accuracy of self-detection of breast lesions. Overall, breast self-examinations were effective in the detection of breast lesions and factors such as size of lesion, nature of the lesion and history of mastectomy affect the accuracy of the detections. Breast self-examination should be promoted for early detection of breast cancer.

ROC analysis of lesion descriptors in breast ultrasound images

NASA Astrophysics Data System (ADS)

Andre, Michael P.; Galperin, Michael; Phan, Peter; Chiu, Peter

2003-05-01

Breast biopsy serves as the key diagnostic tool in the evaluation of breast masses for malignancy, yet the procedure affects patients physically and emotionally and may obscure results of future mammograms. Studies show that high quality ultrasound can distinguish a benign from malignant lesions with accuracy, however, it has proven difficult to teach and clinical results are highly variable. The purpose of this study is to develop a means to optimize an automated Computer Aided Imaging System (CAIS) to assess Level of Suspicion (LOS) of a breast mass. We examine the contribution of 15 object features to lesion classification by calculating the Wilcoxon area under the ROC curve, AW, for all combinations in a set of 146 masses with known findings. For each interval A, the frequency of appearance of each feature and its combinations with others was computed as a means to find an "optimum" feature vector. The original set of 15 was reduced to 6 (area, perimeter, diameter ferret Y, relief, homogeneity, average energy) with an improvement from Aw=0.82-/+0.04 for the original 15 to Aw=0.93-/+0.02 for the subset of 6, p=0.03. For comparison, two sub-specialty mammography radiologists also scored the images for LOS resulting in Az of 0.90 and 0.87. The CAIS performed significantly higher, p=0.02.

Surgical upgrade rate of breast atypia to malignancy: An academic center's experience and validation of a predictive model.

PubMed

Linsk, Ali; Mehta, Tejas S; Dialani, Vandana; Brook, Alexander; Chadashvili, Tamuna; Houlihan, Mary Jane; Sharma, Ranjna

2018-03-01

Atypical ductal hyperplasia (ADH), atypical lobular hyperplasia (ALH), and lobular carcinoma in situ (LCIS) are commonly seen on breast core needle biopsy (CNB). Many institutions recommend excision of these lesions to exclude malignancy. A retrospective chart review was performed on patients who had ADH, ALH, or LCIS on breast CNB from 1/1/08 to 12/31/10 who subsequently had surgical excision of the biopsy site. Study objectives included determining upgrade to malignancy at surgical excision, identification of predictors of upgrade, and validation of a recently published predictive model. Clinical and demographic factors, pathology, characteristics of the biopsy procedure and visible residual lesion were recorded. T test and chi-squared test were used to identify predictors. Classification tree was used to predict upgrade. 151 patients had mean age of 53 years. The mean maximum lesion size on imaging was 11 mm. The primary atypia was ADH in 63.6%, ALH in 27.8%, and LCIS in 8.6%. 16.6% of patients had upgrade to malignancy, with 72% DCIS and 28% invasive carcinoma. Risk factors for upgrade included maximum lesion size (P = .002) and radiographic presence of residual lesion (P = .001). A predictive model based on these factors had sensitivity 78%, specificity 80% and AUC = 0.88. Validating a published nomogram with our data produced accuracy figures (AUC = 0.65) within published CI of 0.63-0.82. In CNB specimens containing ADH, ALH, or LCIS, initial lesion size and presence of residual lesion are predictors of upgrade to malignancy. A validated model may be helpful in developing patient management strategies. © 2017 Wiley Periodicals, Inc.

Adding the power of iodinated contrast media to the credibility of mammography in breast cancer diagnosis.

PubMed

Tsigginou, Alexandra; Gkali, Christina; Chalazonitis, Athanasios; Feida, Eleni; Vlachos, Dimitrios Efthymios; Zagouri, Flora; Rellias, Ioannis; Dimitrakakis, Constantine

2016-11-01

Dual-energy contrast-enhanced spectral mammography (CESM) represents a relatively new diagnostic tool adjunct to mammography. The aim of this study was to strengthen the breast imaging-reporting and data system (BIRADS) classification score in order to improve early breast cancer diagnosis. For this reason, we propose a sum score, termed malignancy potential score (MPS), incorporating the standard BIRADS score and our proposed CESM score. From September 2014 to September 2015, 216 females (age range, 26-85 years; mean age 54.6 years) underwent CESM evaluation of mammographic findings that were primarily assessed as BIRADS 2-5. 10 of these patients had bilateral findings; a total of 226 lesions were examined. High-energy image evaluation was based on the intensity of contrast enhancement of the lesion compared with background enhancement, categorized as Type -1, 0, 1 or 2 enhancement. Histopathology reports were compared with imaging assessment. 98 of 226 lesions were malignant and 128 of 226 lesions were benign. The area under the curve was 0.843, 0.888 and 0.917 for mammographic BIRADS score, CESM score and MPS, respectively, with p-value < 0.05. The sensitivity, specificity and accuracy rates were 91.83, 80.47 and 85.40%, respectively, when a best MPS cut-off point of 4 was used. The malignancy potential score (MPS) has higher diagnostic performance than digital mammography or CESM alone. MPS empowers the credibility of the digital mammography BIRADS score and our proposed type of enhancement in dual-energy CESM and is a diagnostic tool that increases the accuracy rate in early breast cancer diagnosis.

Computer-aided diagnosis of contrast-enhanced spectral mammography: A feasibility study.

PubMed

Patel, Bhavika K; Ranjbar, Sara; Wu, Teresa; Pockaj, Barbara A; Li, Jing; Zhang, Nan; Lobbes, Mark; Zhang, Bin; Mitchell, J Ross

2018-01-01

To evaluate whether the use of a computer-aided diagnosis-contrast-enhanced spectral mammography (CAD-CESM) tool can further increase the diagnostic performance of CESM compared with that of experienced radiologists. This IRB-approved retrospective study analyzed 50 lesions described on CESM from August 2014 to December 2015. Histopathologic analyses, used as the criterion standard, revealed 24 benign and 26 malignant lesions. An expert breast radiologist manually outlined lesion boundaries on the different views. A set of morphologic and textural features were then extracted from the low-energy and recombined images. Machine-learning algorithms with feature selection were used along with statistical analysis to reduce, select, and combine features. Selected features were then used to construct a predictive model using a support vector machine (SVM) classification method in a leave-one-out-cross-validation approach. The classification performance was compared against the diagnostic predictions of 2 breast radiologists with access to the same CESM cases. Based on the SVM classification, CAD-CESM correctly identified 45 of 50 lesions in the cohort, resulting in an overall accuracy of 90%. The detection rate for the malignant group was 88% (3 false-negative cases) and 92% for the benign group (2 false-positive cases). Compared with the model, radiologist 1 had an overall accuracy of 78% and a detection rate of 92% (2 false-negative cases) for the malignant group and 62% (10 false-positive cases) for the benign group. Radiologist 2 had an overall accuracy of 86% and a detection rate of 100% for the malignant group and 71% (8 false-positive cases) for the benign group. The results of our feasibility study suggest that a CAD-CESM tool can provide complementary information to radiologists, mainly by reducing the number of false-positive findings. Copyright © 2017 Elsevier B.V. All rights reserved.

TU-F-18C-09: Mammogram Surveillance Using Texture Analysis for Breast Cancer Patients After Radiation Therapy

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

Kuo, H; Tome, W; FOX, J

2014-06-15

Purpose: To study the feasibility of applying cancer risk model established from treated patients to predict the risk of recurrence on follow-up mammography after radiation therapy for both ipsilateral and contralateral breast. Methods: An extensive set of textural feature functions was applied to a set of 196 Mammograms from 50 patients. 56 Mammograms from 28 patients were used as training set, 44 mammograms from 22 patients were used as test set and the rest were used for prediction. Feature functions include Histogram, Gradient, Co-Occurrence Matrix, Run-Length Matrix and Wavelet Energy. An optimum subset of the feature functions was selected bymore » Fisher Coefficient (FO) or Mutual Information (MI) (up to top 10 features) or a method combined FO, MI and Principal Component (FMP) (up to top 30 features). One-Nearest Neighbor (1-NN), Linear Discriminant Analysis (LDA) and Nonlinear Discriminant Analysis (NDA) were utilized to build a risk model of breast cancer from the training set of mammograms at the time of diagnosis. The risk model was then used to predict the risk of recurrence from mammogram taken one year and three years after RT. Results: FPM with NDA has the best classification power in classifying the training set of the mammogram with lesions versus those without lesions. The model of FPM with NDA achieved a true positive (TP) rate of 82% compared to 45.5% of using FO with 1-NN. The best false positive (FP) rates were 0% and 3.6% in contra-lateral breast of 1-year and 3-years after RT, and 10.9% in ipsi-lateral breast of 3-years after RT. Conclusion: Texture analysis offers high dimension to differentiate breast tissue in mammogram. Using NDA to classify mammogram with lesion from mammogram without lesion, it can achieve rather high TP and low FP in the surveillance of mammogram for patient with conservative surgery combined RT.« less

Task-Driven Dictionary Learning Based on Mutual Information for Medical Image Classification.

PubMed

Diamant, Idit; Klang, Eyal; Amitai, Michal; Konen, Eli; Goldberger, Jacob; Greenspan, Hayit

2017-06-01

We present a novel variant of the bag-of-visual-words (BoVW) method for automated medical image classification. Our approach improves the BoVW model by learning a task-driven dictionary of the most relevant visual words per task using a mutual information-based criterion. Additionally, we generate relevance maps to visualize and localize the decision of the automatic classification algorithm. These maps demonstrate how the algorithm works and show the spatial layout of the most relevant words. We applied our algorithm to three different tasks: chest x-ray pathology identification (of four pathologies: cardiomegaly, enlarged mediastinum, right consolidation, and left consolidation), liver lesion classification into four categories in computed tomography (CT) images and benign/malignant clusters of microcalcifications (MCs) classification in breast mammograms. Validation was conducted on three datasets: 443 chest x-rays, 118 portal phase CT images of liver lesions, and 260 mammography MCs. The proposed method improves the classical BoVW method for all tested applications. For chest x-ray, area under curve of 0.876 was obtained for enlarged mediastinum identification compared to 0.855 using classical BoVW (with p-value 0.01). For MC classification, a significant improvement of 4% was achieved using our new approach (with p-value = 0.03). For liver lesion classification, an improvement of 6% in sensitivity and 2% in specificity were obtained (with p-value 0.001). We demonstrated that classification based on informative selected set of words results in significant improvement. Our new BoVW approach shows promising results in clinically important domains. Additionally, it can discover relevant parts of images for the task at hand without explicit annotations for training data. This can provide computer-aided support for medical experts in challenging image analysis tasks.

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.

Computer-aided diagnosis with textural features for breast lesions in sonograms.

PubMed

Chen, Dar-Ren; Huang, Yu-Len; Lin, Sheng-Hsiung

2011-04-01

Computer-aided diagnosis (CAD) systems provided second beneficial support reference and enhance the diagnostic accuracy. This paper was aimed to develop and evaluate a CAD with texture analysis in the classification of breast tumors for ultrasound images. The ultrasound (US) dataset evaluated in this study composed of 1020 sonograms of region of interest (ROI) subimages from 255 patients. Two-view sonogram (longitudinal and transverse views) and four different rectangular regions were utilized to analyze each tumor. Six practical textural features from the US images were performed to classify breast tumors as benign or malignant. However, the textural features always perform as a high dimensional vector; high dimensional vector is unfavorable to differentiate breast tumors in practice. The principal component analysis (PCA) was used to reduce the dimension of textural feature vector and then the image retrieval technique was performed to differentiate between benign and malignant tumors. In the experiments, all the cases were sampled with k-fold cross-validation (k=10) to evaluate the performance with receiver operating characteristic (ROC) curve. The area (A(Z)) under the ROC curve for the proposed CAD system with the specific textural features was 0.925±0.019. The classification ability for breast tumor with textural information is satisfactory. This system differentiates benign from malignant breast tumors with a good result and is therefore clinically useful to provide a second opinion. Copyright © 2010 Elsevier Ltd. All rights reserved.

Computerized Interpretation of Dynamic Breast MRI

DTIC Science & Technology

2006-05-01

correction, tumor segmentation , extraction of computerized features that help distinguish between benign and malignant lesions, and classification. Our...for assessing tumor extent in 3D. The primary feature used for 3D tumor segmentation is the postcontrast enhancement vector. Tumor segmentation is a...Appendix B. 4. Investigation of methods for automatic tumor segmentation We developed an automatic method for assessing tumor extent in 3D. The

Supine breast US: how to correlate breast lesions from prone MRI.

PubMed

Telegrafo, Michele; Rella, Leonarda; Stabile Ianora, Amato A; Angelelli, Giuseppe; Moschetta, Marco

2016-01-01

To evaluate spatial displacement of breast lesions from prone MR to supine ultrasound positions, and to determine whether the degree of displacement may be associated with breast density and lesion histotype. 380 patients underwent breast MR and second-look ultrasound. The MR and ultrasound lesion location within the breast gland, distances from anatomical landmarks (nipple, skin and pectoral muscle), spatial displacement (distance differences from the landmarks within the same breast region) and region displacement (breast region change) were prospectively evaluated. Differences between MR and ultrasound measurements, association between the degree of spatial displacement and both breast density and lesion histotypes were calculated. In 290/380 (76%) patients, 300 MR lesions were detected. 285/300 (95%) lesions were recognized on ultrasound. By comparing MR and ultrasound, spatial displacement occurred in 183/285 (64.3%) cases while region displacement in 102/285 (35.7%) cases with a circumferential movement along an arc centred on the nipple, having supine ultrasound as the reference standard. A significant association between the degree of lesion displacement and breast density was found (p < 0.00001) with a significant higher displacement in case of fatty breasts. No significant association between the degree of displacement and lesion histotype was found (p = 0.1). Lesion spatial displacement from MRI to ultrasound may occur especially in adipose breasts. Lesion-nipple distance and circumferential displacement from the nipple need to be considered for ultrasound lesion detection. Second-look ultrasound breast lesion detection could be improved by calculating the lesion-nipple distance and considering that spatial displacement from MRI occurs with a circumferential movement along an arc centred on the nipple.

Spectral embedding based active contour (SEAC) for lesion segmentation on breast dynamic contrast enhanced magnetic resonance imaging.

PubMed

Agner, Shannon C; Xu, Jun; Madabhushi, Anant

2013-03-01

Segmentation of breast lesions on dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is the first step in lesion diagnosis in a computer-aided diagnosis framework. Because manual segmentation of such lesions is both time consuming and highly susceptible to human error and issues of reproducibility, an automated lesion segmentation method is highly desirable. Traditional automated image segmentation methods such as boundary-based active contour (AC) models require a strong gradient at the lesion boundary. Even when region-based terms are introduced to an AC model, grayscale image intensities often do not allow for clear definition of foreground and background region statistics. Thus, there is a need to find alternative image representations that might provide (1) strong gradients at the margin of the object of interest (OOI); and (2) larger separation between intensity distributions and region statistics for the foreground and background, which are necessary to halt evolution of the AC model upon reaching the border of the OOI. In this paper, the authors introduce a spectral embedding (SE) based AC (SEAC) for lesion segmentation on breast DCE-MRI. SE, a nonlinear dimensionality reduction scheme, is applied to the DCE time series in a voxelwise fashion to reduce several time point images to a single parametric image where every voxel is characterized by the three dominant eigenvectors. This parametric eigenvector image (PrEIm) representation allows for better capture of image region statistics and stronger gradients for use with a hybrid AC model, which is driven by both boundary and region information. They compare SEAC to ACs that employ fuzzy c-means (FCM) and principal component analysis (PCA) as alternative image representations. Segmentation performance was evaluated by boundary and region metrics as well as comparing lesion classification using morphological features from SEAC, PCA+AC, and FCM+AC. On a cohort of 50 breast DCE-MRI studies, PrEIm yielded overall better region and boundary-based statistics compared to the original DCE-MR image, FCM, and PCA based image representations. Additionally, SEAC outperformed a hybrid AC applied to both PCA and FCM image representations. Mean dice similarity coefficient (DSC) for SEAC was significantly better (DSC = 0.74 ± 0.21) than FCM+AC (DSC = 0.50 ± 0.32) and similar to PCA+AC (DSC = 0.73 ± 0.22). Boundary-based metrics of mean absolute difference and Hausdorff distance followed the same trends. Of the automated segmentation methods, breast lesion classification based on morphologic features derived from SEAC segmentation using a support vector machine classifier also performed better (AUC = 0.67 ± 0.05; p < 0.05) than FCM+AC (AUC = 0.50 ± 0.07), and PCA+AC (AUC = 0.49 ± 0.07). In this work, we presented SEAC, an accurate, general purpose AC segmentation tool that could be applied to any imaging domain that employs time series data. SE allows for projection of time series data into a PrEIm representation so that every voxel is characterized by the dominant eigenvectors, capturing the global and local time-intensity curve similarities in the data. This PrEIm allows for the calculation of strong tensor gradients and better region statistics than the original image intensities or alternative image representations such as PCA and FCM. The PrEIm also allows for building a more accurate hybrid AC scheme.

False positive or negative results of shear-wave elastography in differentiating benign from malignant breast masses: analysis of clinical and ultrasonographic characteristics.

PubMed

Kim, Mi Young; Choi, Nami; Yang, Jung-Hyun; Yoo, Young Bum; Park, Kyoung Sik

2015-10-01

Shear-wave elastography (SWE) has the potential to improve diagnostic performance of conventional ultrasound (US) in differentiating benign from malignant breast masses. To investigate false positive or negative results of SWE in differentiating benign from malignant breast masses and to analyze clinical and imaging characteristics of the masses with false SWE findings. From May to October 2013, 166 breast lesions of 164 consecutive women (mean age, 45.3 ± 10.1 years) who had been scheduled for biopsy were included. Conventional US and SWE were performed in all women before biopsy. Clinical, ultrasonographic morphologic features and SWE parameters (pattern classification and standard deviation [SD]) were recorded and compared with the histopathology results. Patient and lesion factors in the "true" and "false" groups were compared. Of the 166 masses, 118 (71.1%) were benign and 48 (28.9%) were malignant. False SWE features were more frequently observed in benign masses. False positive rates of benign masses and false negative rates of malignancy were 53% and 8.2%, respectively, using SWE pattern analysis and were 22.4% and 10.3%, respectively, using SD values. A lesion boundary of the masses on US (P = 0.039) and younger patient age (P = 0.047) were significantly associated with false SWE findings. These clinical and ultrasonographic features need to be carefully evaluated in performance and interpretation of SWE examinations. © The Foundation Acta Radiologica 2014.

Adding the power of iodinated contrast media to the credibility of mammography in breast cancer diagnosis

PubMed Central

Tsigginou, Alexandra; Chalazonitis, Athanasios; Feida, Eleni; Vlachos, Dimitrios Efthymios; Zagouri, Flora; Rellias, Ioannis; Dimitrakakis, Constantine

2016-01-01

Dual-energy contrast-enhanced spectral mammography (CESM) represents a relatively new diagnostic tool adjunct to mammography. The aim of this study was to strengthen the breast imaging-reporting and data system (BIRADS) classification score in order to improve early breast cancer diagnosis. For this reason, we propose a sum score, termed malignancy potential score (MPS), incorporating the standard BIRADS score and our proposed CESM score. From September 2014 to September 2015, 216 females (age range, 26–85 years; mean age 54.6 years) underwent CESM evaluation of mammographic findings that were primarily assessed as BIRADS 2–5. 10 of these patients had bilateral findings; a total of 226 lesions were examined. High-energy image evaluation was based on the intensity of contrast enhancement of the lesion compared with background enhancement, categorized as Type -1, 0, 1 or 2 enhancement. Histopathology reports were compared with imaging assessment. 98 of 226 lesions were malignant and 128 of 226 lesions were benign. The area under the curve was 0.843, 0.888 and 0.917 for mammographic BIRADS score, CESM score and MPS, respectively, with p-value < 0.05. The sensitivity, specificity and accuracy rates were 91.83, 80.47 and 85.40%, respectively, when a best MPS cut-off point of 4 was used. The malignancy potential score (MPS) has higher diagnostic performance than digital mammography or CESM alone. MPS empowers the credibility of the digital mammography BIRADS score and our proposed type of enhancement in dual-energy CESM and is a diagnostic tool that increases the accuracy rate in early breast cancer diagnosis. PMID:27452266

Computer-aided Classification of Mammographic Masses Using Visually Sensitive Image Features

PubMed Central

Wang, Yunzhi; Aghaei, Faranak; Zarafshani, Ali; Qiu, Yuchen; Qian, Wei; Zheng, Bin

2017-01-01

Purpose To develop a new computer-aided diagnosis (CAD) scheme that computes visually sensitive image features routinely used by radiologists to develop a machine learning classifier and distinguish between the malignant and benign breast masses detected from digital mammograms. Methods An image dataset including 301 breast masses was retrospectively selected. From each segmented mass region, we computed image features that mimic five categories of visually sensitive features routinely used by radiologists in reading mammograms. We then selected five optimal features in the five feature categories and applied logistic regression models for classification. A new CAD interface was also designed to show lesion segmentation, computed feature values and classification score. Results Areas under ROC curves (AUC) were 0.786±0.026 and 0.758±0.027 when to classify mass regions depicting on two view images, respectively. By fusing classification scores computed from two regions, AUC increased to 0.806±0.025. Conclusion This study demonstrated a new approach to develop CAD scheme based on 5 visually sensitive image features. Combining with a “visual aid” interface, CAD results may be much more easily explainable to the observers and increase their confidence to consider CAD generated classification results than using other conventional CAD approaches, which involve many complicated and visually insensitive texture features. PMID:27911353

Supine breast US: how to correlate breast lesions from prone MRI

PubMed Central

Telegrafo, Michele; Rella, Leonarda; Stabile Ianora, Amato A; Angelelli, Giuseppe

2016-01-01

Objective: To evaluate spatial displacement of breast lesions from prone MR to supine ultrasound positions, and to determine whether the degree of displacement may be associated with breast density and lesion histotype. Methods: 380 patients underwent breast MR and second-look ultrasound. The MR and ultrasound lesion location within the breast gland, distances from anatomical landmarks (nipple, skin and pectoral muscle), spatial displacement (distance differences from the landmarks within the same breast region) and region displacement (breast region change) were prospectively evaluated. Differences between MR and ultrasound measurements, association between the degree of spatial displacement and both breast density and lesion histotypes were calculated. Results: In 290/380 (76%) patients, 300 MR lesions were detected. 285/300 (95%) lesions were recognized on ultrasound. By comparing MR and ultrasound, spatial displacement occurred in 183/285 (64.3%) cases while region displacement in 102/285 (35.7%) cases with a circumferential movement along an arc centred on the nipple, having supine ultrasound as the reference standard. A significant association between the degree of lesion displacement and breast density was found (p < 0.00001) with a significant higher displacement in case of fatty breasts. No significant association between the degree of displacement and lesion histotype was found (p = 0.1). Conclusion: Lesion spatial displacement from MRI to ultrasound may occur especially in adipose breasts. Lesion–nipple distance and circumferential displacement from the nipple need to be considered for ultrasound lesion detection. Advances in knowledge: Second-look ultrasound breast lesion detection could be improved by calculating the lesion–nipple distance and considering that spatial displacement from MRI occurs with a circumferential movement along an arc centred on the nipple. PMID:26689093

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

Absence of epithelial atypia in B3-lesions of the breast is associated with decreased risk for malignancy.

PubMed

Mayer, Sebastian; Kayser, Gian; Rücker, Gerta; Bögner, Diana; Hirschfeld, Marc; Hug, Christiane; Stickeler, Elmar; Gitsch, Gerald; Erbes, Thalia

2017-02-01

Lesions of uncertain malignant potential (B3) represent a heterogeneous group with an overall risk for malignancy of 9.85-35.1% after total resection. Positive predictive values (PPV) for malignancy vary depending on B3 subtype. The aim of this study was to evaluate the PPV for malignancy in B3 lesions and to determine the clinical significance of atypia-dependent sub-classification (a = without epithelial atypia; b = with epithelial atypia) of B3 into B3a and B3b and papillary lesions (PL) in PLa and PLb. 219 patients with histopathologically proven B3 lesions on core needle/vacuum-assisted biopsy who subsequently underwent diagnostic excision biopsy were included in this study. PPVs for malignancy were reported for B3 in general and all B3 sub-categories. Logistic regression analysis identified associations between B3-subgroups and outcome after excision biopsy as well as the impact of clinical and diagnostic findings on excision diagnosis. The overall PPV rate was 10.0% (22/219). Excision histology exhibited a higher malignancy rate in PLb (2/7; PPV: 28.6%) than in PLa (6/127; PPV: 4.7%) (p = 0.057) and in B3b (12/50; PPV: 24.0%) compared to B3a category (8/165; PPV: 4.8%) (p < 0.001). These findings support the necessity of B3 lesion sub-classification into B3a and B3b and of PL into PLa and PLb when considering epithelial atypia. The determination of atypia status represents a relevant factor in risk-stratification for clinical management of B3 lesions. Should future studies using the sub-classification of PL confirm these results, observation may be a safe option for the clinical management of patients with asymptomatic PLa lesions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Contrast-enhanced spectral mammography (CESM) versus breast magnetic resonance imaging (MRI): A retrospective comparison in 66 breast lesions.

PubMed

Li, L; Roth, R; Germaine, P; Ren, S; Lee, M; Hunter, K; Tinney, E; Liao, L

2017-02-01

The purpose of this study was to retrospectively compare the diagnostic performance of contrast-enhanced spectral mammography (CESM) with that of breast magnetic resonance imaging (BMRI) in breast cancer detection using parameters, including sensitivity, positive predictive value (PPV), lesion size, morphology, lesion and background enhancement, and examination time. A total of 48 women (mean age, 56years±10.6 [SD]) with breast lesions detected between October 2012 and March 2014 were included. Both CESM and BMRI were performed for each patient within 30 days. The enhancement intensity of lesions and breast background parenchyma was subjectively assessed for both modalities and was quantified for comparison. Statistical significance was analyzed using paired t-test for mean size of index lesions in all malignant breasts (an index lesion defined as the largest lesion in each breast), and a mean score of enhancement intensity for index lesions and breast background. PPV, sensitivity, and accuracy were calculated for both CESM and BMRI. The average duration time of CESM and MRI examinations was also compared. A total of 66 lesions were identified, including 62 malignant and 4 benign lesions. Both CESM and BMRI demonstrated a sensitivity of 100% for detection of breast cancer. There was no statistically significant difference between the mean size of index lesions (P=0.108). The enhancement intensity of breast background was significantly lower for CESM than for BMRI (P<0.01). The mean score of enhancement intensity of index lesions on CESM was significantly less than that for BMRI (P<0.01). The smallest lesion that was detected by both modalities measured 4mm. CESM had a higher PPV than BMRI (P>0.05). The average examination time for CESM was significantly shorter than that of BMRI (P<0.01). CESM has similar sensitivity than BMRI in breast cancer detection, with higher PPV and less background enhancement. CESM is associate with significantly shorter exam time thus a more accessible alternative to BMRI, and has the potential to play an important tool in breast cancer detection and staging. Copyright © 2016 Éditions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Computer-aided classification of mammographic masses using the deep learning technology: a preliminary study

NASA Astrophysics Data System (ADS)

Qiu, Yuchen; Yan, Shiju; Tan, Maxine; Cheng, Samuel; Liu, Hong; Zheng, Bin

2016-03-01

Although mammography is the only clinically acceptable imaging modality used in the population-based breast cancer screening, its efficacy is quite controversy. One of the major challenges is how to help radiologists more accurately classify between benign and malignant lesions. The purpose of this study is to investigate a new mammographic mass classification scheme based on a deep learning method. In this study, we used an image dataset involving 560 regions of interest (ROIs) extracted from digital mammograms, which includes 280 malignant and 280 benign mass ROIs, respectively. An eight layer deep learning network was applied, which employs three pairs of convolution-max-pooling layers for automatic feature extraction and a multiple layer perception (MLP) classifier for feature categorization. In order to improve robustness of selected features, each convolution layer is connected with a max-pooling layer. A number of 20, 10, and 5 feature maps were utilized for the 1st, 2nd and 3rd convolution layer, respectively. The convolution networks are followed by a MLP classifier, which generates a classification score to predict likelihood of a ROI depicting a malignant mass. Among 560 ROIs, 420 ROIs were used as a training dataset and the remaining 140 ROIs were used as a validation dataset. The result shows that the new deep learning based classifier yielded an area under the receiver operation characteristic curve (AUC) of 0.810+/-0.036. This study demonstrated the potential superiority of using a deep learning based classifier to distinguish malignant and benign breast masses without segmenting the lesions and extracting the pre-defined image features.

Can we apply the MRI BI-RADS lexicon morphology descriptors on contrast-enhanced spectral mammography?

PubMed

Kamal, Rasha M; Helal, Maha H; Mansour, Sahar M; Haggag, Marwa A; Nada, Omniya M; Farahat, Iman G; Alieldin, Nelly H

2016-07-12

To assess the feasibility of using the MRI breast imaging reporting and data system (BI-RADS) lexicon morphology descriptors to characterize enhancing breast lesions identified on contrast-enhanced spectral mammography (CESM). The study is a retrospective analysis of the morphology descriptors of 261 enhancing breast lesions identified on CESM in 239 patients. We presented the morphological categorization of the included lesions into focus, mass and non-mass. Further classifications included (1) the multiplicity for "focus" category, (2) the shape, margin and internal enhancement for "mass" category and (3) the distribution and internal enhancement for "non-mass" category. Each morphology descriptor was evaluated individually (irrespective of all other descriptors) by calculating its sensitivity, specificity, positive-predictive value (PPV) and negative-predictive value (NPV) and likelihood ratios (LRs). The study included 68/261 (26.1%) benign lesions and 193/261 (73.9%) malignant lesions. Intensely enhancing foci, whether single (7/12, 58.3%) or multiple (2/12, 16.7%), were malignant. Descriptors of "irregular"-shape (PPV: 92.4%) and "non-circumscribed" margin (odds ratio: 55.2, LR positive: 4.77; p-value: <0.001) were more compatible with malignancy. Internal mass enhancement patterns showed a very low specificity (58.0%) and NPV (40.0%). Non-mass enhancement (NME) was detected in 81/261 lesions. Asymmetrical NME in 81% (n = 52/81) lesions was malignant lesions and internal enhancement patterns indicative of malignancy were the heterogeneous and clumped ones. We can apply the MRI morphology descriptors to characterize lesions on CESM, but with few expectations. In many situations, irregular-shaped, non-circumscribed masses and NME with focal, ductal or segmental distribution and heterogeneous or clumped enhancement are the most suggestive descriptors of malignant pathologies. (1) The MRI BI-RADS lexicon morphology descriptors can be applied in the characterization of enhancing lesions on CESM with a few exceptions. (2) Multiple bilateral intensely enhancing foci should not be included under the normal background parenchymal enhancement unless they are proved to be benign by biopsy. (3) Mass lesion features that indicated malignancy were irregular-shaped, spiculated and irregular margins and heterogeneous internal enhancement patterns. The rim enhancement pattern should not be considered as a descriptor of malignant lesions unless CESM is coupled with an ultrasound examination.

Can we apply the MRI BI-RADS lexicon morphology descriptors on contrast-enhanced spectral mammography?

PubMed Central

Kamal, Rasha M; Helal, Maha H; Haggag, Marwa A; Nada, Omniya M; Farahat, Iman G; Alieldin, Nelly H

2016-01-01

Objective: To assess the feasibility of using the MRI breast imaging reporting and data system (BI-RADS) lexicon morphology descriptors to characterize enhancing breast lesions identified on contrast-enhanced spectral mammography (CESM). Methods: The study is a retrospective analysis of the morphology descriptors of 261 enhancing breast lesions identified on CESM in 239 patients. We presented the morphological categorization of the included lesions into focus, mass and non-mass. Further classifications included (1) the multiplicity for “focus” category, (2) the shape, margin and internal enhancement for “mass” category and (3) the distribution and internal enhancement for “non-mass” category. Each morphology descriptor was evaluated individually (irrespective of all other descriptors) by calculating its sensitivity, specificity, positive-predictive value (PPV) and negative-predictive value (NPV) and likelihood ratios (LRs). Results: The study included 68/261 (26.1%) benign lesions and 193/261 (73.9%) malignant lesions. Intensely enhancing foci, whether single (7/12, 58.3%) or multiple (2/12, 16.7%), were malignant. Descriptors of “irregular”-shape (PPV: 92.4%) and “non-circumscribed” margin (odds ratio: 55.2, LR positive: 4.77; p-value: <0.001) were more compatible with malignancy. Internal mass enhancement patterns showed a very low specificity (58.0%) and NPV (40.0%). Non-mass enhancement (NME) was detected in 81/261 lesions. Asymmetrical NME in 81% (n = 52/81) lesions was malignant lesions and internal enhancement patterns indicative of malignancy were the heterogeneous and clumped ones. Conclusion: We can apply the MRI morphology descriptors to characterize lesions on CESM, but with few expectations. In many situations, irregular-shaped, non-circumscribed masses and NME with focal, ductal or segmental distribution and heterogeneous or clumped enhancement are the most suggestive descriptors of malignant pathologies. Advances in knowledge: (1) The MRI BI-RADS lexicon morphology descriptors can be applied in the characterization of enhancing lesions on CESM with a few exceptions. (2) Multiple bilateral intensely enhancing foci should not be included under the normal background parenchymal enhancement unless they are proved to be benign by biopsy. (3) Mass lesion features that indicated malignancy were irregular-shaped, spiculated and irregular margins and heterogeneous internal enhancement patterns. The rim enhancement pattern should not be considered as a descriptor of malignant lesions unless CESM is coupled with an ultrasound examination. PMID:27327403

Transcutaneous in vivo Raman spectroscopic studies in a mouse model: evaluation of changes in the breast associated with pregnancy and lactation

NASA Astrophysics Data System (ADS)

Bhattacharjee, Tanmoy; Maru, Girish; Ingle, Arvind; Krishna, C. Murali

2013-04-01

Raman spectroscopy (RS) has been extensively explored as an alternative diagnostic tool for breast cancer. This can be attributed to its sensitivity to malignancy-associated biochemical changes. However, biochemical changes due to nonmalignant conditions like benign lesions, inflammatory diseases, aging, menstrual cycle, pregnancy, and lactation may act as confounding factors in diagnosis of breast cancer. Therefore, in this study, the efficacy of RS to classify pregnancy and lactation-associated changes as well as its effect on breast tumor diagnosis was evaluated. Since such studies are difficult in human subjects, a mouse model was used. Spectra were recorded transcutaneously from the breast region of six Swiss bare mice postmating, during pregnancy, and during lactation. Data were analyzed using multivariate statistical tool Principal Component-Linear Discriminant Analysis. Results suggest that RS can differentiate breasts of pregnant/lactating mice from those of normal mice, the classification efficiencies being 100%, 60%, and 88% for normal, pregnant, and lactating mice, respectively. Frank breast tumors could be classified with 97.5% efficiency, suggesting that these physiological changes do not affect the ability of RS to detect breast tumors.

Automatic classification for mammogram backgrounds based on bi-rads complexity definition and on a multi content analysis framework

NASA Astrophysics Data System (ADS)

Wu, Jie; Besnehard, Quentin; Marchessoux, Cédric

2011-03-01

Clinical studies for the validation of new medical imaging devices require hundreds of images. An important step in creating and tuning the study protocol is the classification of images into "difficult" and "easy" cases. This consists of classifying the image based on features like the complexity of the background, the visibility of the disease (lesions). Therefore, an automatic medical background classification tool for mammograms would help for such clinical studies. This classification tool is based on a multi-content analysis framework (MCA) which was firstly developed to recognize image content of computer screen shots. With the implementation of new texture features and a defined breast density scale, the MCA framework is able to automatically classify digital mammograms with a satisfying accuracy. BI-RADS (Breast Imaging Reporting Data System) density scale is used for grouping the mammograms, which standardizes the mammography reporting terminology and assessment and recommendation categories. Selected features are input into a decision tree classification scheme in MCA framework, which is the so called "weak classifier" (any classifier with a global error rate below 50%). With the AdaBoost iteration algorithm, these "weak classifiers" are combined into a "strong classifier" (a classifier with a low global error rate) for classifying one category. The results of classification for one "strong classifier" show the good accuracy with the high true positive rates. For the four categories the results are: TP=90.38%, TN=67.88%, FP=32.12% and FN =9.62%.

Evaluation of clinical breast examination and breast ultrasonography among pregnant women in Abakaliki, Nigeria

PubMed Central

Ezeonu, Paul Olisaemeka; Ajah, Leonard Ogbonna; Onoh, Robinson Chukwudi; Lawani, Lucky Osaheni; Enemuo, Vincent Chidi; Agwu, Uzoma MaryRose

2015-01-01

Background Breast cancer in pregnancy accounts for 2%–3% of all breast cancers. The increased vascularity and lymphatic drainage from the breast during pregnancy potentiate the metastatic spread of the cancer to the regional lymph nodes. However, the increased breast density in pregnancy makes it difficult to detect breast lesions early. Aim To evaluate and compare the detection rate of breast lesions using clinical breast examination (CBE) and breast ultrasonography among pregnant women. Methodology A cross-sectional comparative study involving antenatal clinic attendees at the Federal Teaching Hospital, Abakaliki, was conducted between March 3, 2014, and December 31, 2014. CBE and breast ultrasonography were done in the participants at booking and repeated at 6 weeks postpartum. Fine-needle aspiration cytology and histology were done in women with suspicious breast lesions on CBE or breast ultrasonography or both. Data analysis was both descriptive and inferential at the 95% confidence level using the Statistical Package for the Social Sciences (SPSS) software version 17.0. Test of significance was done using chi-square test. A P-value of less than or equal to 0.05 was considered statistically significant. Results A total of 320 pregnant women participated in the study. Of these, 267 (83.4%) were aware of breast cancer. Although more lesions were detected with breast ultrasonography than by CBE, there was no statistically significant difference between them (25 versus 17; P=0.26). The histology of the lesions revealed 21 benign lesions and 4 normal breast tissues. The sensitivity of breast ultrasonography was 95.2%, while that of CBE was 66.7%. The specificity, positive predictive value, and negative predictive value were similar between CBE and breast ultrasonography. Conclusion The detection rates of breast lesions by both CBE and breast ultrasonography were equivalent during pregnancy and 6 weeks postpartum, making CBE a convenient and very cost-effective method of detecting breast lesions in the low-risk population. However, both CBE and breast ultrasonography should be done in women with high risk of breast malignancy. PMID:25999736

Ultrafast dynamic contrast-enhanced mri of the breast using compressed sensing: breast cancer diagnosis based on separate visualization of breast arteries and veins.

PubMed

Onishi, Natsuko; Kataoka, Masako; Kanao, Shotaro; Sagawa, Hajime; Iima, Mami; Nickel, Marcel Dominik; Toi, Masakazu; Togashi, Kaori

2018-01-01

To evaluate the feasibility of ultrafast dynamic contrast-enhanced (UF-DCE) magnetic resonance imaging (MRI) with compressed sensing (CS) for the separate identification of breast arteries/veins and perform temporal evaluations of breast arteries and veins with a focus on the association with ipsilateral cancers. Our Institutional Review Board approved this study with retrospective design. Twenty-five female patients who underwent UF-DCE MRI at 3T were included. UF-DCE MRI consisting of 20 continuous frames was acquired using a prototype 3D gradient-echo volumetric interpolated breath-hold sequence including a CS reconstruction: temporal resolution, 3.65 sec/frame; spatial resolution, 0.9 × 1.3 × 2.5 mm. Two readers analyzed 19 maximum intensity projection images reconstructed from subtracted images, separately identified breast arteries/veins and the earliest frame in which they were respectively visualized, and calculated the time interval between arterial and venous visualization (A-V interval) for each breast. In total, 49 breasts including 31 lesions (breast cancer, 16; benign lesion, 15) were identified. In 39 of the 49 breasts (breasts with cancers, 16; breasts with benign lesions, 10; breasts with no lesions, 13), both breast arteries and veins were separately identified. The A-V intervals for breasts with cancers were significantly shorter than those for breasts with benign lesions (P = 0.043) and no lesions (P = 0.007). UF-DCE MRI using CS enables the separate identification of breast arteries/veins. Temporal evaluations calculating the time interval between arterial and venous visualization might be helpful in the differentiation of ipsilateral breast cancers from benign lesions. 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:97-104. © 2017 International Society for Magnetic Resonance in Medicine.

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.

Classification of breast cancer in ultrasound imaging using a generic deep learning analysis software: a pilot study.

PubMed

Becker, Anton S; Mueller, Michael; Stoffel, Elina; Marcon, Magda; Ghafoor, Soleen; Boss, Andreas

2018-02-01

To train a generic deep learning software (DLS) to classify breast cancer on ultrasound images and to compare its performance to human readers with variable breast imaging experience. In this retrospective study, all breast ultrasound examinations from January 1, 2014 to December 31, 2014 at our institution were reviewed. Patients with post-surgical scars, initially indeterminate, or malignant lesions with histological diagnoses or 2-year follow-up were included. The DLS was trained with 70% of the images, and the remaining 30% were used to validate the performance. Three readers with variable expertise also evaluated the validation set (radiologist, resident, medical student). Diagnostic accuracy was assessed with a receiver operating characteristic analysis. 82 patients with malignant and 550 with benign lesions were included. Time needed for training was 7 min (DLS). Evaluation time for the test data set were 3.7 s (DLS) and 28, 22 and 25 min for human readers (decreasing experience). Receiver operating characteristic analysis revealed non-significant differences (p-values 0.45-0.47) in the area under the curve of 0.84 (DLS), 0.88 (experienced and intermediate readers) and 0.79 (inexperienced reader). DLS may aid diagnosing cancer on breast ultrasound images with an accuracy comparable to radiologists, and learns better and faster than a human reader with no prior experience. Further clinical trials with dedicated algorithms are warranted. Advances in knowledge: DLS can be trained classify cancer on breast ultrasound images high accuracy even with comparably few training cases. The fast evaluation speed makes real-time image analysis feasible.

Phyllodes tumours of the breast: a consensus review

PubMed Central

Tan, Benjamin Y; Acs, Geza; Apple, Sophia K; Badve, Sunil; Bleiweiss, Ira J; Brogi, Edi; Calvo, José P; Dabbs, David J; Ellis, Ian O; Eusebi, Vincenzo; Farshid, Gelareh; Fox, Stephen B; Ichihara, Shu; Lakhani, Sunil R; Rakha, Emad A; Reis-Filho, Jorge S; Richardson, Andrea L; Sahin, Aysegul; Schmitt, Fernando C; Schnitt, Stuart J; Siziopikou, Kalliopi P; Soares, Fernando A; Tse, Gary M; Vincent-Salomon, Anne; Tan, Puay Hoon

2016-01-01

Phyllodes tumours constitute an uncommon but complex group of mammary fibroepithelial lesions. Accurate and reproducible grading of these tumours has long been challenging, owing to the need to assess multiple stratified histological parameters, which may be weighted differently by individual pathologists. Distinction of benign phyllodes tumours from cellular fibroadenomas is fraught with difficulty, due to overlapping microscopic features. Similarly, separation of the malignant phyllodes tumour from spindle cell metaplastic carcinoma and primary breast sarcoma can be problematic. Phyllodes tumours are treated by surgical excision. However, there is no consensus on the definition of an appropriate surgical margin to ensure completeness of excision and reduction of recurrence risk. Interpretive subjectivity, overlapping histological diagnostic criteria, suboptimal correlation between histological classification and clinical behaviour and the lack of robust molecular predictors of outcome make further investigation of the pathogenesis of these fascinating tumours a matter of active research. This review consolidates the current understanding of their pathobiology and clinical behaviour, and includes proposals for a rational approach to the classification and management of phyllodes tumours. PMID:26768026

Identification of Genes Expressed in Premalignant Breast Disease by Microscopy-Directed Cloning

NASA Astrophysics Data System (ADS)

Jensen, Roy A.; Page, David L.; Holt, Jeffrey T.

1994-09-01

Histopathologic study of human breast biopsy samples has identified specific lesions which are associated with a high risk of development of invasive breast cancer. Presumably, these lesions (collectively termed premalignant breast disease) represent the earliest recognizable morphologic expression of fundamental molecular events that lead to the development of invasive breast cancer. To study molecular events underlying premalignant breast disease, we have developed a method for isolating RNA from histologically identified lesions from frozen human breast tissue. This method specifically obtains mRNA from breast epithelial cells and has identified three genes which are differentially expressed in premalignant breast epithelial lesions. One gene identified by this method is overexpressed in four of five noncomedo ductal carcinoma in situ lesions and appears to be the human homologue of the gene encoding the M2 subunit of ribonucleotide reductase, an enzyme involved in DNA synthesis.

Breast cancer molecular subtype classification using deep features: preliminary results

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Visually assessed colour overlay features in shear-wave elastography for breast masses: quantification and diagnostic performance.

PubMed

Gweon, Hye Mi; Youk, Ji Hyun; Son, Eun Ju; Kim, Jeong-Ah

2013-03-01

To determine whether colour overlay features can be quantified by the standard deviation (SD) of the elasticity measured in shear-wave elastography (SWE) and to evaluate the diagnostic performance for breast masses. One hundred thirty-three breast lesions in 119 consecutive women who underwent SWE before US-guided core needle biopsy or surgical excision were analysed. SWE colour overlay features were assessed using two different colour overlay pattern classifications. Quantitative SD of the elasticity value was measured with the region of interest including the whole breast lesion. For the four-colour overlay pattern, the area under the ROC curve (Az) was 0.947; with a cutoff point between pattern 2 and 3, sensitivity and specificity were 94.4 % and 81.4 %. According to the homogeneity of the elasticity, the Az was 0.887; with a cutoff point between reasonably homogeneous and heterogeneous, sensitivity and specificity were 86.1 % and 82.5 %. For the SD of the elasticity, the Az was 0.944; with a cutoff point of 12.1, sensitivity and specificity were 88.9 % and 89.7 %. The colour overlay features showed significant correlations with the quantitative SD of the elasticity (P < 0.001). The colour overlay features and the SD of the elasticity in SWE showed excellent diagnostic performance and showed good correlations between them.

Differentiation of benign and malignant breast lesions by mechanical imaging

PubMed Central

Kearney, Thomas; Pollak, Stanley B.; Rohatgi, Chand; Sarvazyan, Noune; Airapetian, Suren; Browning, Stephanie; Sarvazyan, Armen

2009-01-01

Mechanical imaging yields tissue elasticity map and provides quantitative characterization of a detected pathology. The changes in the surface stress patterns as a function of applied load provide information about the elastic composition and geometry of the underlying tissue structures. The objective of this study is the clinical evaluation of breast mechanical imager for breast lesion characterization and differentiation between benign and malignant lesions. The breast mechanical imager includes a probe with pressure sensor array, an electronic unit providing data acquisition from the pressure sensors and communication with a touch-screen laptop computer. We have developed an examination procedure and algorithms to provide assessment of breast lesion features such as hardness related parameters, mobility, and shape. A statistical Bayesian classifier was constructed to distinguish between benign and malignant lesions by utilizing all the listed features as the input. Clinical results for 179 cases, collected at four different clinical sites, have demonstrated that the breast mechanical imager provides a reliable image formation of breast tissue abnormalities and calculation of lesion features. Malignant breast lesions (histologically confirmed) demonstrated increased hardness and strain hardening as well as decreased mobility and longer boundary length in comparison with benign lesions. Statistical analysis of differentiation capability for 147 benign and 32 malignant lesions revealed an average sensitivity of 91.4% and specificity of 86.8% with a standard deviation of ±6.1%. The area under the receiver operating characteristic curve characterizing benign and malignant lesion discrimination is 86.1% with the confidence interval ranging from 80.3 to 90.9%, with a significance level of P = 0.0001 (area = 50%). The multisite clinical study demonstrated the capability of mechanical imaging for characterization and differentiation of benign and malignant breast lesions. We hypothesize that the breast mechanical imager has the potential to be used as a cost effective device for cancer diagnostics that could reduce the benign biopsy rate, serve as an adjunct to mammography and to be utilized as a screening device for breast cancer detection. PMID:19306059

A hybrid deep learning approach to predict malignancy of breast lesions using mammograms

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Heidari, Morteza; Mirniaharikandehei, Seyedehnafiseh; Gong, Jing; Qian, Wei; Qiu, Yuchen; Zheng, Bin

2018-03-01

Applying deep learning technology to medical imaging informatics field has been recently attracting extensive research interest. However, the limited medical image dataset size often reduces performance and robustness of the deep learning based computer-aided detection and/or diagnosis (CAD) schemes. In attempt to address this technical challenge, this study aims to develop and evaluate a new hybrid deep learning based CAD approach to predict likelihood of a breast lesion detected on mammogram being malignant. In this approach, a deep Convolutional Neural Network (CNN) was firstly pre-trained using the ImageNet dataset and serve as a feature extractor. A pseudo-color Region of Interest (ROI) method was used to generate ROIs with RGB channels from the mammographic images as the input to the pre-trained deep network. The transferred CNN features from different layers of the CNN were then obtained and a linear support vector machine (SVM) was trained for the prediction task. By applying to a dataset involving 301 suspicious breast lesions and using a leave-one-case-out validation method, the areas under the ROC curves (AUC) = 0.762 and 0.792 using the traditional CAD scheme and the proposed deep learning based CAD scheme, respectively. An ensemble classifier that combines the classification scores generated by the two schemes yielded an improved AUC value of 0.813. The study results demonstrated feasibility and potentially improved performance of applying a new hybrid deep learning approach to develop CAD scheme using a relatively small dataset of medical images.

Radiologic and histopathologic review of rare benign and malignant breast diseases

PubMed Central

Dağıstan, Emine; Kızıldağ, Betül; Gürel, Safiye; Barut, Yüksel; Paşaoğlu, Esra

2017-01-01

High social awareness of breast diseases and the rise in breast imaging facilities have led to an increase in the detection of even rare benign and malignant breast lesions. Breast lesions are associated with a broad spectrum of imaging characteristics, and each radiologic imaging technique reflects different characteristics of them. We aimed to increase familiarity of the radiologist with these uncommon lesions as well as correlate histopathologic findings with the radiologic imaging features of the tumors. Histopathologic examination is necessary in the evaluation of such breast lesions, particularly when radiologic images are not definitive for a specific diagnosis. PMID:28508760

CADx Mammography

NASA Astrophysics Data System (ADS)

Costaridou, Lena

Although a wide variety of Computer-Aided Diagnosis (CADx) schemes have been proposed across breast imaging modalities, and especially in mammography, research is still ongoing to meet the high performance CADx requirements. In this chapter, methodological contributions to CADx in mammography and adjunct breast imaging modalities are reviewed, as they play a major role in early detection, diagnosis and clinical management of breast cancer. At first, basic terms and definitions are provided. Then, emphasis is given to lesion content derivation, both anatomical and functional, considering only quantitative image features of micro-calcification clusters and masses across modalities. Additionally, two CADx application examples are provided. The first example investigates the effect of segmentation accuracy on micro-calcification cluster morphology derivation in X-ray mammography. The second one demonstrates the efficiency of texture analysis in quantification of enhancement kinetics, related to vascular heterogeneity, for mass classification in dynamic contrast-enhanced magnetic resonance imaging.

Observer efficiency in discrimination tasks simulating malignant and benign breast lesions imaged with ultrasound

PubMed Central

Abbey, Craig K.; Zemp, Roger J.; Liu, Jie; Lindfors, Karen K.; Insana, Michael F.

2009-01-01

We investigate and extend the ideal observer methodology developed by Smith and Wagner to detection and discrimination tasks related to breast sonography. We provide a numerical approach for evaluating the ideal observer acting on radio-frequency (RF) frame data, which involves inversion of large nonstationary covariance matrices, and we describe a power-series approach to computing this inverse. Considering a truncated power series suggests that the RF data be Wiener-filtered before forming the final envelope image. We have compared human performance for Wiener-filtered and conventional B-mode envelope images using psychophysical studies for 5 tasks related to breast cancer classification. We find significant improvements in visual detection and discrimination efficiency in four of these five tasks. We also use the Smith-Wagner approach to distinguish between human and processing inefficiencies, and find that generally the principle limitation comes from the information lost in computing the final envelope image. PMID:16468454

Computer-aided diagnosis of breast microcalcifications based on dual-tree complex wavelet transform.

PubMed

Jian, Wushuai; Sun, Xueyan; Luo, Shuqian

2012-12-19

Digital mammography is the most reliable imaging modality for breast carcinoma diagnosis and breast micro-calcifications is regarded as one of the most important signs on imaging diagnosis. In this paper, a computer-aided diagnosis (CAD) system is presented for breast micro-calcifications based on dual-tree complex wavelet transform (DT-CWT) to facilitate radiologists like double reading. Firstly, 25 abnormal ROIs were extracted according to the center and diameter of the lesions manually and 25 normal ROIs were selected randomly. Then micro-calcifications were segmented by combining space and frequency domain techniques. We extracted three texture features based on wavelet (Haar, DB4, DT-CWT) transform. Totally 14 descriptors were introduced to define the characteristics of the suspicious micro-calcifications. Principal Component Analysis (PCA) was used to transform these descriptors to a compact and efficient vector expression. Support Vector Machine (SVM) classifier was used to classify potential micro-calcifications. Finally, we used the receiver operating characteristic (ROC) curve and free-response operating characteristic (FROC) curve to evaluate the performance of the CAD system. The results of SVM classifications based on different wavelets shows DT-CWT has a better performance. Compared with other results, DT-CWT method achieved an accuracy of 96% and 100% for the classification of normal and abnormal ROIs, and the classification of benign and malignant micro-calcifications respectively. In FROC analysis, our CAD system for clinical dataset detection achieved a sensitivity of 83.5% at a false positive per image of 1.85. Compared with general wavelets, DT-CWT could describe the features more effectively, and our CAD system had a competitive performance.

Computer-aided diagnosis of breast microcalcifications based on dual-tree complex wavelet transform

PubMed Central

2012-01-01

Background Digital mammography is the most reliable imaging modality for breast carcinoma diagnosis and breast micro-calcifications is regarded as one of the most important signs on imaging diagnosis. In this paper, a computer-aided diagnosis (CAD) system is presented for breast micro-calcifications based on dual-tree complex wavelet transform (DT-CWT) to facilitate radiologists like double reading. Methods Firstly, 25 abnormal ROIs were extracted according to the center and diameter of the lesions manually and 25 normal ROIs were selected randomly. Then micro-calcifications were segmented by combining space and frequency domain techniques. We extracted three texture features based on wavelet (Haar, DB4, DT-CWT) transform. Totally 14 descriptors were introduced to define the characteristics of the suspicious micro-calcifications. Principal Component Analysis (PCA) was used to transform these descriptors to a compact and efficient vector expression. Support Vector Machine (SVM) classifier was used to classify potential micro-calcifications. Finally, we used the receiver operating characteristic (ROC) curve and free-response operating characteristic (FROC) curve to evaluate the performance of the CAD system. Results The results of SVM classifications based on different wavelets shows DT-CWT has a better performance. Compared with other results, DT-CWT method achieved an accuracy of 96% and 100% for the classification of normal and abnormal ROIs, and the classification of benign and malignant micro-calcifications respectively. In FROC analysis, our CAD system for clinical dataset detection achieved a sensitivity of 83.5% at a false positive per image of 1.85. Conclusions Compared with general wavelets, DT-CWT could describe the features more effectively, and our CAD system had a competitive performance. PMID:23253202

Breast cancers not detected at MRI: review of false-negative lesions.

PubMed

Shimauchi, Akiko; Jansen, Sanaz A; Abe, Hiroyuki; Jaskowiak, Nora; Schmidt, Robert A; Newstead, Gillian M

2010-06-01

The objective of our study was to determine the sensitivity of cancer detection at breast MRI using current imaging techniques and to evaluate the characteristics of lesions with false-negative examinations. Two hundred seventeen patients with 222 newly diagnosed breast cancers or highly suspicious breast lesions that were subsequently shown to be malignant underwent breast MRI examinations for staging. Two breast imaging radiologists performed a consensus review of the breast MRI examinations. The absence of perceptible contrast enhancement at the expected site was considered to be a false-negative MRI. Histology of all lesions was reviewed by an experienced breast pathologist. Enhancement was observed in 213 (95.9%) of the 222 cancer lesions. Of the nine lesions without visible enhancement, two lesions were excluded because the entire tumor had been excised at percutaneous biopsy performed before the MRI examination and no residual tumor was noted on the final histology. The overall sensitivity of MRI for the known cancers was 96.8% (213/220); for invasive cancer, 98.3% (176/179); and for ductal carcinoma in situ, 90.2% (37/41). In a population of 220 sequentially diagnosed breast cancer lesions, we found seven (3.2%) MRI-occult cancers, fewer than seen in other published studies. Small tumor size and diffuse parenchymal enhancement were the principal reasons for these false-negative results. Although the overall sensitivity of cancer detection was high (96.8%), it should be emphasized that a negative MRI should not influence the management of a lesion that appears to be of concern on physical examination or on other imaging techniques.

Exploring nonlinear feature space dimension reduction and data representation in breast Cadx with Laplacian eigenmaps and t-SNE.

PubMed

Jamieson, Andrew R; Giger, Maryellen L; Drukker, Karen; Li, Hui; Yuan, Yading; Bhooshan, Neha

2010-01-01

In this preliminary study, recently developed unsupervised nonlinear dimension reduction (DR) and data representation techniques were applied to computer-extracted breast lesion feature spaces across three separate imaging modalities: Ultrasound (U.S.) with 1126 cases, dynamic contrast enhanced magnetic resonance imaging with 356 cases, and full-field digital mammography with 245 cases. Two methods for nonlinear DR were explored: Laplacian eigenmaps [M. Belkin and P. Niyogi, "Laplacian eigenmaps for dimensionality reduction and data representation," Neural Comput. 15, 1373-1396 (2003)] and t-distributed stochastic neighbor embedding (t-SNE) [L. van der Maaten and G. Hinton, "Visualizing data using t-SNE," J. Mach. Learn. Res. 9, 2579-2605 (2008)]. These methods attempt to map originally high dimensional feature spaces to more human interpretable lower dimensional spaces while preserving both local and global information. The properties of these methods as applied to breast computer-aided diagnosis (CADx) were evaluated in the context of malignancy classification performance as well as in the visual inspection of the sparseness within the two-dimensional and three-dimensional mappings. Classification performance was estimated by using the reduced dimension mapped feature output as input into both linear and nonlinear classifiers: Markov chain Monte Carlo based Bayesian artificial neural network (MCMC-BANN) and linear discriminant analysis. The new techniques were compared to previously developed breast CADx methodologies, including automatic relevance determination and linear stepwise (LSW) feature selection, as well as a linear DR method based on principal component analysis. Using ROC analysis and 0.632+bootstrap validation, 95% empirical confidence intervals were computed for the each classifier's AUC performance. In the large U.S. data set, sample high performance results include, AUC0.632+ = 0.88 with 95% empirical bootstrap interval [0.787;0.895] for 13 ARD selected features and AUC0.632+ = 0.87 with interval [0.817;0.906] for four LSW selected features compared to 4D t-SNE mapping (from the original 81D feature space) giving AUC0.632+ = 0.90 with interval [0.847;0.919], all using the MCMC-BANN. Preliminary results appear to indicate capability for the new methods to match or exceed classification performance of current advanced breast lesion CADx algorithms. While not appropriate as a complete replacement of feature selection in CADx problems, DR techniques offer a complementary approach, which can aid elucidation of additional properties associated with the data. Specifically, the new techniques were shown to possess the added benefit of delivering sparse lower dimensional representations for visual interpretation, revealing intricate data structure of the feature space.

Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.

PubMed

Al-Masni, Mohammed A; Al-Antari, Mugahed A; Park, Jeong-Min; Gi, Geon; Kim, Tae-Yeon; Rivera, Patricio; Valarezo, Edwin; Choi, Mun-Taek; Han, Seung-Moo; Kim, Tae-Seong

2018-04-01

Automatic detection and classification of the masses in mammograms are still a big challenge and play a crucial role to assist radiologists for accurate diagnosis. In this paper, we propose a novel Computer-Aided Diagnosis (CAD) system based on one of the regional deep learning techniques, a ROI-based Convolutional Neural Network (CNN) which is called You Only Look Once (YOLO). Although most previous studies only deal with classification of masses, our proposed YOLO-based CAD system can handle detection and classification simultaneously in one framework. The proposed CAD system contains four main stages: preprocessing of mammograms, feature extraction utilizing deep convolutional networks, mass detection with confidence, and finally mass classification using Fully Connected Neural Networks (FC-NNs). In this study, we utilized original 600 mammograms from Digital Database for Screening Mammography (DDSM) and their augmented mammograms of 2,400 with the information of the masses and their types in training and testing our CAD. The trained YOLO-based CAD system detects the masses and then classifies their types into benign or malignant. Our results with five-fold cross validation tests show that the proposed CAD system detects the mass location with an overall accuracy of 99.7%. The system also distinguishes between benign and malignant lesions with an overall accuracy of 97%. Our proposed system even works on some challenging breast cancer cases where the masses exist over the pectoral muscles or dense regions. Copyright © 2018 Elsevier B.V. All rights reserved.

Gynecomastia Classification for Surgical Management: A Systematic Review and Novel Classification System.

PubMed

Waltho, Daniel; Hatchell, Alexandra; Thoma, Achilleas

2017-03-01

Gynecomastia is a common deformity of the male breast, where certain cases warrant surgical management. There are several surgical options, which vary depending on the breast characteristics. To guide surgical management, several classification systems for gynecomastia have been proposed. A systematic review was performed to (1) identify all classification systems for the surgical management of gynecomastia, and (2) determine the adequacy of these classification systems to appropriately categorize the condition for surgical decision-making. The search yielded 1012 articles, and 11 articles were included in the review. Eleven classification systems in total were ascertained, and a total of 10 unique features were identified: (1) breast size, (2) skin redundancy, (3) breast ptosis, (4) tissue predominance, (5) upper abdominal laxity, (6) breast tuberosity, (7) nipple malposition, (8) chest shape, (9) absence of sternal notch, and (10) breast skin elasticity. On average, classification systems included two or three of these features. Breast size and ptosis were the most commonly included features. Based on their review of the current classification systems, the authors believe the ideal classification system should be universal and cater to all causes of gynecomastia; be surgically useful and easy to use; and should include a comprehensive set of clinically appropriate patient-related features, such as breast size, breast ptosis, tissue predominance, and skin redundancy. None of the current classification systems appears to fulfill these criteria.

Can Raman spectroscopy identify the origin of Paget disease?

NASA Astrophysics Data System (ADS)

Martin, A. A.; Marcelo, Moreno; Bitar, R.; Martinho, H., .; Santos, E. A. P.; Arisawa, E. A. L.

2008-02-01

The histogenesis of the breast Paget's disease was investigated by the optical diagnosis technique using Raman spectroscopy. A total of 15 spectra of the associated breast lesion, 21 spectra of the eczematoid skin lesion and 396 spectra of invasive breast cancer not otherwise specified were compared by clustering the spectral data between 800 - 1800 cm -1 at level of similarity of 95%, using a correlation distance measurement by computing the covariance matrix. The Raman spectral-biochemical characterization of invasive breast cancer and breast Paget's disease with eczematoid skin lesion associated with underlying invasive breast lesion tissues enabled one concludes that the parenchymal disease had similar characteristics to the skin's Paget lesion. This could indicate a similar histogenesis for both. Thus, the findings of the present work adds a relevant experimental evidence that agrees with the epidermotropic theory of Paget's disease, that states that the cells originate in the breast ducts and migrate to the nipple's skin.

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

Breast MR segmentation and lesion detection with cellular neural networks and 3D template matching.

PubMed

Ertaş, Gökhan; Gülçür, H Ozcan; Osman, Onur; Uçan, Osman N; Tunaci, Mehtap; Dursun, Memduh

2008-01-01

A novel fully automated system is introduced to facilitate lesion detection in dynamic contrast-enhanced, magnetic resonance mammography (DCE-MRM). The system extracts breast regions from pre-contrast images using a cellular neural network, generates normalized maximum intensity-time ratio (nMITR) maps and performs 3D template matching with three layers of 12x12 cells to detect lesions. A breast is considered to be properly segmented when relative overlap >0.85 and misclassification rate <0.10. Sensitivity, false-positive rate per slice and per lesion are used to assess detection performance. The system was tested with a dataset of 2064 breast MR images (344slicesx6 acquisitions over time) from 19 women containing 39 marked lesions. Ninety-seven percent of the breasts were segmented properly and all the lesions were detected correctly (detection sensitivity=100%), however, there were some false-positive detections (31%/lesion, 10%/slice).

Multi-probe-based resonance-frequency electrical impedance spectroscopy for detection of suspicious breast lesions: improving performance using partial ROC optimization

NASA Astrophysics Data System (ADS)

Lederman, Dror; Zheng, Bin; Wang, Xingwei; Wang, Xiao Hui; Gur, David

2011-03-01

We have developed a multi-probe resonance-frequency electrical impedance spectroscope (REIS) system to detect breast abnormalities. Based on assessing asymmetry in REIS signals acquired between left and right breasts, we developed several machine learning classifiers to classify younger women (i.e., under 50YO) into two groups of having high and low risk for developing breast cancer. In this study, we investigated a new method to optimize performance based on the area under a selected partial receiver operating characteristic (ROC) curve when optimizing an artificial neural network (ANN), and tested whether it could improve classification performance. From an ongoing prospective study, we selected a dataset of 174 cases for whom we have both REIS signals and diagnostic status verification. The dataset includes 66 "positive" cases recommended for biopsy due to detection of highly suspicious breast lesions and 108 "negative" cases determined by imaging based examinations. A set of REIS-based feature differences, extracted from the two breasts using a mirror-matched approach, was computed and constituted an initial feature pool. Using a leave-one-case-out cross-validation method, we applied a genetic algorithm (GA) to train the ANN with an optimal subset of features. Two optimization criteria were separately used in GA optimization, namely the area under the entire ROC curve (AUC) and the partial area under the ROC curve, up to a predetermined threshold (i.e., 90% specificity). The results showed that although the ANN optimized using the entire AUC yielded higher overall performance (AUC = 0.83 versus 0.76), the ANN optimized using the partial ROC area criterion achieved substantially higher operational performance (i.e., increasing sensitivity level from 28% to 48% at 95% specificity and/ or from 48% to 58% at 90% specificity).

Breast metastasis from cutaneous malignant melanoma mimicking a breast cancer.

PubMed

Maniglio, Marina; Capalbo, Emanuela; Viganò, Sara; Trecate, Giovanna; Scaperrotta, Gianfranco Paride; Panizza, Pietro

2015-06-25

Breast metastases are very uncommon, either from solid tumors or malignant melanoma. We present the case of a 42-year-old woman with a history of cutaneous melanoma of the shoulder excised 21 years ago. She presented with a palpable lump in the upper outer quadrant of the right breast. Ultrasound demonstrated a solid mass within a cystic lesion. A core biopsy was taken and first histology reported a poorly differentiated primary breast cancer suspected to be triple negative. MRI detected a satellite lesion in the same breast, a focus of suspected enhancement in the other breast, and the extramammary finding of an enhancing pulmonary lesion. Staging computed tomography detected widespread metastases to the lungs, brain, subcutaneous left shoulder, liver, pancreas, and hepatorenal recess. A core biopsy was taken from the left breast lesion and the previous slides were reviewed; histopathology and immunohistochemistry were in keeping with metastasis from melanoma. The possibility of a metastatic lesion to the breast should be taken into account in any patient presenting with a breast lump and a previous history of melanoma. Breast involvement cannot be considered an isolated finding, as it might be the first manifestation of widespread disease.

Contrast-enhanced spectral mammography: Impact of the qualitative morphology descriptors on the diagnosis of breast lesions.

PubMed

Mohamed Kamal, Rasha; Hussien Helal, Maha; Wessam, Rasha; Mahmoud Mansour, Sahar; Godda, Iman; Alieldin, Nelly

2015-06-01

To analyze the morphology and enhancement characteristics of breast lesions on contrast-enhanced spectral mammography (CESM) and to assess their impact on the differentiation between benign and malignant lesions. This ethics committee approved study included 168 consecutive patients with 211 breast lesions over 18 months. Lesions classified as non-enhancing and enhancing and then the latter group was subdivided into mass and non-mass. Mass lesions descriptors included: shape, margins, pattern and degree of internal enhancement. Non-mass lesions descriptors included: distribution, pattern and degree of internal enhancement. The impact of each descriptor on diagnosis individually assessed using Chi test and the validity compared in both benign and malignant lesions. The overall performance of CESM were also calculated. The study included 102 benign (48.3%) and 109 malignant (51.7%) lesions. Enhancement was encountered in 145/211 (68.7%) lesions. They further classified into enhancing mass (99/145, 68.3%) and non-mass lesions (46/145, 31.7%). Contrast uptake was significantly more frequent in malignant breast lesions (p value ≤ 0.001). Irregular mass lesions with intense and heterogeneous enhancement patterns correlated with a malignant pathology (p value ≤ 0.001). CESM showed an overall sensitivity of 88.99% and specificity of 83.33%. The positive and negative likelihood ratios were 5.34 and 0.13 respectively. The assessment of the morphology and enhancement characteristics of breast lesions on CESM enhances the performance of digital mammography in the differentiation between benign and malignant breast lesions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Evaluation of the SAVI SCOUT Surgical Guidance System for Localization and Excision of Nonpalpable Breast Lesions: A Feasibility Study.

PubMed

Mango, Victoria; Ha, Richard; Gomberawalla, Ameer; Wynn, Ralph; Feldman, Sheldon

2016-06-15

The purpose of this study is to evaluate the feasibility of the SAVI SCOUT surgical guidance system, which uses a nonradioactive infrared-activated electromagnetic wave reflector, to localize and excise nonpalpable breast lesions. We evaluated the system's use in 15 nonpalpable breast lesions in 13 patients. Image-guided placement was successful for 15 of 15 (100%) reflectors. The final pathologic analysis found that lesion excision was successful, including five malignancies with negative margins. No patients required reexcision or experienced complications. SAVI SCOUT is a feasible method for breast lesion localization and excision.

The breast lesion excision system (BLES) A preliminary experience.

PubMed

Citgez, Bulent; Atay, Murat; Yetkin, Gu Rkan; Kartal, Abdulcabbar; Mihmanli, Mehmet; Uludag, Mehmet

2016-01-01

BLES (Intact Breast lesion Excision System) is a new defined system which can remove the lesion completely. We aimed to evaluate and compare the results of BLES used for breast lesions requiring histological verification with other percutaneous biopsy methods in the literature. Patients with breast lesions smaller than 20mm and for whom biopsy was indicated were involved in the study. 18(1 male, 17 female, mean age: 41. 83, age range: 26-72) patients were included the study. BLES is applied with a single insertion. Radiofrequency is used to excise the breast tissue after the insertion. Around the lesion, tissue capture basket is moved back and forth. Once captured, the basket and the probe is removed from the incision area. All of the lesions were excised en-bloc. The only complication occured was subdermal hematoma in one case (5.5%) which resolved spontenously. Pathological analysis of the specimens revealed 9 fibroadenoma, 3 fibroadenomatosis hyperplasia, 3 complicated and calcified cysts, 1 ductal epithelial hyperplasia, 1 carcinoma in situ with intraductal papillary carcinoma focus and 1 ductal carcinoma in situ with 2 mm invasive carcinoma focus. The last two cases underwent resectıon and sentınal lymph node procedure. BLES is a is non-invasive method which has no need for additional initiatives in benign cases, provide sufficient samples for pathological diagnosis and remove the lesion in one piece. BLES method can be applied in selected cases. Breast Lesion Excision System, Breast, Biopsy, Radiofrequency, Lesion.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

NASA Astrophysics Data System (ADS)

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-04-01

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans.

PubMed

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-04-15

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

PubMed Central

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-01-01

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features. PMID:27079888

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.

Diagnostic performance and color overlay pattern in shear wave elastography (SWE) for palpable breast mass.

PubMed

Park, Jiyoon; Woo, Ok Hee; Shin, Hye Seon; Cho, Kyu Ran; Seo, Bo Kyoung; Kang, Eun Young

2015-10-01

The purpose of this study is to evaluate the diagnostic performance of SWE in palpable breast mass and to compare with color overlay pattern in SWE with conventional US and quantitative SWE for assessing palpable breast mass. SWE and conventional breast US were performed in 133 women with 156 palpable breast lesions (81 benign, 75 malignant) between August 2013 to June 2014. Either pathology or periodic imaging surveillance more than 2 years was a reference standard. Existence of previous image was blinded to performing radiologists. US BI-RADS final assessment, qualitative and quantitative SWE measurements were evaluated. Diagnostic performances of grayscale US, SWE and US combined to SWE were calculated and compared. Correlation between pattern classification and quantitative SWE was evaluated. Both color overlay pattern and quantitative SWE improved the specificity of conventional US, from 81.48% to 96.30% (p=0.0005), without improvement in sensitivity. Color overlay pattern was significantly related to all quantitative SWE parameters and malignancy rate (p<0.0001.). The optimal cutoff of color overlay pattern was between 2 and 3. Emax with optimal cutoff at 45.1 kPa showed the highest Az value, sensitivity, specificity and accuracy among other quantitative SWE parameters (p<0.0001). Echogenic halo on grayscale US showed significant correlation with color overlay pattern and pathology (p<0.0001). In evaluation of palpable breast mass, conventional US combine to SWE improves specificity and reduces the number of biopsies that ultimately yield a benign result. Color overlay pattern classification is more quick and easy and may represent quantitative SWE measurements with similar diagnostic performances. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Mass classification in mammography with multi-agent based fusion of human and machine intelligence

NASA Astrophysics Data System (ADS)

Xi, Dongdong; Fan, Ming; Li, Lihua; Zhang, Juan; Shan, Yanna; Dai, Gang; Zheng, Bin

2016-03-01

Although the computer-aided diagnosis (CAD) system can be applied for classifying the breast masses, the effects of this method on improvement of the radiologist' accuracy for distinguishing malignant from benign lesions still remain unclear. This study provided a novel method to classify breast masses by integrating the intelligence of human and machine. In this research, 224 breast masses were selected in mammography from database of DDSM with Breast Imaging Reporting and Data System (BI-RADS) categories. Three observers (a senior and a junior radiologist, as well as a radiology resident) were employed to independently read and classify these masses utilizing the Positive Predictive Values (PPV) for each BI-RADS category. Meanwhile, a CAD system was also implemented for classification of these breast masses between malignant and benign. To combine the decisions from the radiologists and CAD, the fusion method of the Multi-Agent was provided. Significant improvements are observed for the fusion system over solely radiologist or CAD. The area under the receiver operating characteristic curve (AUC) of the fusion system increased by 9.6%, 10.3% and 21% compared to that of radiologists with senior, junior and resident level, respectively. In addition, the AUC of this method based on the fusion of each radiologist and CAD are 3.5%, 3.6% and 3.3% higher than that of CAD alone. Finally, the fusion of the three radiologists with CAD achieved AUC value of 0.957, which was 5.6% larger compared to CAD. Our results indicated that the proposed fusion method has better performance than radiologist or CAD alone.

Analysis of the impact of digital watermarking on computer-aided diagnosis in medical imaging.

PubMed

Garcia-Hernandez, Jose Juan; Gomez-Flores, Wilfrido; Rubio-Loyola, Javier

2016-01-01

Medical images (MI) are relevant sources of information for detecting and diagnosing a large number of illnesses and abnormalities. Due to their importance, this study is focused on breast ultrasound (BUS), which is the main adjunct for mammography to detect common breast lesions among women worldwide. On the other hand, aiming to enhance data security, image fidelity, authenticity, and content verification in e-health environments, MI watermarking has been widely used, whose main goal is to embed patient meta-data into MI so that the resulting image keeps its original quality. In this sense, this paper deals with the comparison of two watermarking approaches, namely spread spectrum based on the discrete cosine transform (SS-DCT) and the high-capacity data-hiding (HCDH) algorithm, so that the watermarked BUS images are guaranteed to be adequate for a computer-aided diagnosis (CADx) system, whose two principal outcomes are lesion segmentation and classification. Experimental results show that HCDH algorithm is highly recommended for watermarking medical images, maintaining the image quality and without introducing distortion into the output of CADx. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evolving paradigms in multifocal breast cancer.

PubMed

Salgado, Roberto; Aftimos, Philippe; Sotiriou, Christos; Desmedt, Christine

2015-04-01

The 7th edition of the TNM defines multifocal breast cancer as multiple simultaneous ipsilateral and synchronous breast cancer lesions, provided they are macroscopically distinct and measurable using current traditional pathological and clinical tools. According to the College of American Pathologists (CAP), the characterization of only the largest lesion is considered sufficient, unless the grade and/or histology are different between the lesions. Here, we review three potentially clinically relevant aspects of multifocal breast cancers: first, the importance of a different intrinsic breast cancer subtype of the various lesions; second, the emerging awareness of inter-lesion heterogeneity; and last but not least, the potential introduction of bias in clinical trials due to the unrecognized biological diversity of these cancers. Although the current strategy to assess the lesion with the largest diameter has clearly its advantages in terms of costs and feasibility, this recommendation may not be sustainable in time and might need to be adapted to be compliant with new evolving paradigms in breast cancer. Copyright © 2014 Elsevier Ltd. All rights reserved.

Preliminary Results of Acoustic Radiation Force Impulse Imaging by Combined Qualitative and Quantitative Analyses for Evaluation of Breast Lesions.

PubMed

Wang, Lin; Wan, Cai-Feng; Du, Jing; Li, Feng-Hua

2018-04-15

The purpose of this study was to evaluate the application of a new elastographic technique, acoustic radiation force impulse (ARFI) imaging, and its diagnostic performance for characterizing breast lesions. One hundred consecutive female patients with 126 breast lesions were enrolled in our study. After routine breast ultrasound examinations, the patients underwent ARFI elasticity imaging. Virtual Touch tissue imaging (VTI) and Virtual Touch tissue quantification (Siemens Medical Solutions, Mountain View, CA) were used to qualitatively and quantitatively analyze the elasticity and hardness of tumors. A receiver operating characteristic curve analysis was performed to evaluate the diagnostic performance of ARFI for discrimination between benign and malignant breast lesions. Pathologic analysis revealed 40 lesions in the malignant group and 86 lesions in the benign group. Different VTI patterns were observed in benign and malignant breast lesions. Eighty lesions (93.0%) of benign group had pattern 1, 2, or 3, whereas all pattern 4b lesions (n = 20 [50.0%]) were malignant. Regarding the quantitative analysis, the mean VTI-to-B-mode area ratio, internal shear wave velocity, and marginal shear wave velocity of benign lesions were statistically significantly lower than those of malignant lesions (all P < .001). The cutoff point for a scoring system constructed to evaluate the diagnostic performance of ARFI was estimated to be between 3 and 4 points for malignancy, with sensitivity of 77.5%, specificity of 96.5%, accuracy of 90.5%, and an area under the curve of 0.933. The application of ARFI technology has shown promising results by noninvasively providing substantial complementary information and could potentially serve as an effective diagnostic tool for differentiation between benign and malignant breast lesions. © 2018 by the American Institute of Ultrasound in Medicine.

Inflammatory Breast Carcinoma Presenting with Two Different Patterns of Cutaneous Metastases: Carcinoma Telangiectaticum and Carcinoma Erysipeloides

PubMed Central

Yaghoobi, Reza; Talaizade, Abdolhasan; Lal, Karan; Ranjbari, Nastaran; Sohrabiaan, Nasibe

2015-01-01

Cutaneous metastases can have many different clinical presentations. They are seen in patients with advanced malignant disease; however, they can be the initial manifestation of undetected malignancies. Inflammatory breast carcinoma is a rare and aggressive form of breast cancer that has a nonspecific appearance mimicking many benign conditions including mastitis, breast abscesses, and/or dermatitis. The authors report the case of a 40-year-old woman with inflammatory breast carcinoma presenting with violaceous papulovesicular lesions resembling lymphangioma circumscriptum and erythematous patches resembling erysipelas. These lesions represent two different types of cutaneous metastases, both of which were the initial signs of inflammatory breast carcinoma in the patient described herein. Skin biopsy of lesions confirmed invasive breast cancer and further prompted a work up for inflammatory breast carcinoma. This case demonstrates the importance of follow-up for all breast lesions, even those considered to be of benign nature, for they can be presenting signs of metastatic breast cancer. PMID:26345728

A Radio-genomics Approach for Identifying High Risk Estrogen Receptor-positive Breast Cancers on DCE-MRI: Preliminary Results in Predicting OncotypeDX Risk Scores

PubMed Central

Wan, Tao; Bloch, B. Nicolas; Plecha, Donna; Thompson, CheryI L.; Gilmore, Hannah; Jaffe, Carl; Harris, Lyndsay; Madabhushi, Anant

2016-01-01

To identify computer extracted imaging features for estrogen receptor (ER)-positive breast cancers on dynamic contrast en-hanced (DCE)-MRI that are correlated with the low and high OncotypeDX risk categories. We collected 96 ER-positivebreast lesions with low (<18, N = 55) and high (>30, N = 41) OncotypeDX recurrence scores. Each lesion was quantitatively charac-terize via 6 shape features, 3 pharmacokinetics, 4 enhancement kinetics, 4 intensity kinetics, 148 textural kinetics, 5 dynamic histogram of oriented gradient (DHoG), and 6 dynamic local binary pattern (DLBP) features. The extracted features were evaluated by a linear discriminant analysis (LDA) classifier in terms of their ability to distinguish low and high OncotypeDX risk categories. Classification performance was evaluated by area under the receiver operator characteristic curve (Az). The DHoG and DLBP achieved Az values of 0.84 and 0.80, respectively. The 6 top features identified via feature selection were subsequently combined with the LDA classifier to yield an Az of 0.87. The correlation analysis showed that DHoG (ρ = 0.85, P < 0.001) and DLBP (ρ = 0.83, P < 0.01) were significantly associated with the low and high risk classifications from the OncotypeDX assay. Our results indicated that computer extracted texture features of DCE-MRI were highly correlated with the high and low OncotypeDX risk categories for ER-positive cancers. PMID:26887643

Development of array piezoelectric fingers towards in vivo breast tumor detection

NASA Astrophysics Data System (ADS)

Xu, Xin; Chung, Youngsoo; Brooks, Ari D.; Shih, Wei-Heng; Shih, Wan Y.

2016-12-01

We have investigated the development of a handheld 4 × 1 piezoelectric finger (PEF) array breast tumor detector system towards in vivo patient testing, particularly, on how the duration of the DC applied voltage, the depression depth of the handheld unit, and breast density affect the PEF detection sensitivity on 40 patients. The tests were blinded and carried out in four phases: with DC voltage durations 5, 3, 2, to 0.8 s corresponding to scanning a quadrant, a half, a whole breast, and both breasts within 30 min, respectively. The results showed that PEF detection sensitivity was unaffected by shortening the applied voltage duration from 5 to 0.8 s nor was it affected by increasing the depression depth from 2 to 6 mm. Over the 40 patients, PEF detected 46 of the 48 lesions (46/48)—with the smallest lesion detected being 5 mm in size. Of 28 patients (some have more than one lesion) with mammography records, PEF detected 31/33 of all lesions (94%) and 14/15 of malignant lesions (93%), while mammography detected 30/33 of all lesions (91%) and 12/15 of malignant lesions (80%), indicating that PEF could detect malignant lesions not detectable by mammography without significantly increasing false positives. PEF's detection sensitivity is also shown to be independent of breast density, suggesting that PEF could be a potential tool for detecting breast cancer in young women and women with dense breasts.

Pattern Recognition Approaches for Breast Cancer DCE-MRI Classification: A Systematic Review.

PubMed

Fusco, Roberta; Sansone, Mario; Filice, Salvatore; Carone, Guglielmo; Amato, Daniela Maria; Sansone, Carlo; Petrillo, Antonella

2016-01-01

We performed a systematic review of several pattern analysis approaches for classifying breast lesions using dynamic, morphological, and textural features in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Several machine learning approaches, namely artificial neural networks (ANN), support vector machines (SVM), linear discriminant analysis (LDA), tree-based classifiers (TC), and Bayesian classifiers (BC), and features used for classification are described. The findings of a systematic review of 26 studies are presented. The sensitivity and specificity are respectively 91 and 83 % for ANN, 85 and 82 % for SVM, 96 and 85 % for LDA, 92 and 87 % for TC, and 82 and 85 % for BC. The sensitivity and specificity are respectively 82 and 74 % for dynamic features, 93 and 60 % for morphological features, 88 and 81 % for textural features, 95 and 86 % for a combination of dynamic and morphological features, and 88 and 84 % for a combination of dynamic, morphological, and other features. LDA and TC have the best performance. A combination of dynamic and morphological features gives the best performance.

Pathologic Findings of Breast Lesions Detected on Magnetic Resonance Imaging.

PubMed

Jabbar, Seema B; Lynch, Beverly; Seiler, Stephen; Hwang, Helena; Sahoo, Sunati

2017-11-01

- Breast magnetic resonance imaging (MRI) is now used routinely for high-risk screening and in the evaluation of the extent of disease in newly diagnosed breast cancer patients. Morphologic characteristics and the kinetic pattern largely determine how suspicious a breast lesion is on MRI. Because of its high sensitivity, MRI identifies a large number of suspicious lesions. However, the low to moderate specificity and the additional cost have raised questions regarding its frequent use. - To identify the pathologic entities that frequently present as suspicious enhancing lesions and to identify specific MRI characteristics that may be predictive of malignancy. - One hundred seventy-seven MRI-guided biopsies from 152 patients were included in the study. The indication for MRI, MRI features, pathologic findings, and patient demographics were recorded. The MRI findings and the pathology slides were reviewed by a dedicated breast radiologist and breast pathologists. - Seventy-one percent (126 of 177) of MRI-guided breast biopsies were benign, 11% (20 of 177) showed epithelial atypia, and 18% (31 of 177) showed malignancy. The vast majority (84%; 62 of 74) of MRI lesions with persistent kinetics were benign. However, 57% (17 of 30) of lesions with washout kinetics and 65% (62 of 95) of mass lesions were also benign. - Magnetic resonance imaging detects malignancies undetected by other imaging modalities but also detects a wide variety of benign lesions. Benign and malignant lesions identified by MRI share similar morphologic and kinetic features, necessitating biopsy for histologic confirmation.

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.

Application of whole-lesion histogram analysis of pharmacokinetic parameters in dynamic contrast-enhanced MRI of breast lesions with the CAIPIRINHA-Dixon-TWIST-VIBE technique.

PubMed

Li, Zhiwei; Ai, Tao; Hu, Yiqi; Yan, Xu; Nickel, Marcel Dominik; Xu, Xiao; Xia, Liming

2018-01-01

To investigate the application of whole-lesion histogram analysis of pharmacokinetic parameters for differentiating malignant from benign breast lesions on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In all, 92 women with 97 breast lesions (26 benign and 71 malignant lesions) were enrolled in this study. Patients underwent dynamic breast MRI at 3T using a prototypical CAIPIRINHA-Dixon-TWIST-VIBE (CDT-VIBE) sequence and a subsequent surgery or biopsy. Inflow rate of the agent between plasma and interstitium (K trans ), outflow rate of agent between interstitium and plasma (K ep ), extravascular space volume per unit volume of tissue (v e ) including mean value, 25th/50th/75th/90th percentiles, skewness, and kurtosis were then calculated based on the whole lesion. A single-sample Kolmogorov-Smirnov test, paired t-test, and receiver operating characteristic curve (ROC) analysis were used for statistical analysis. Malignant breast lesions had significantly higher K trans , K ep , and lower v e in mean values, 25th/50th/75th/90th percentiles, and significantly higher skewness of v e than benign breast lesions (all P < 0.05). There was no significant difference in kurtosis values between malignant and benign breast lesions (all P > 0.05). The 90th percentile of K trans , the 90th percentile of K ep , and the 50th percentile of v e showed the greatest areas under the ROC curve (AUC) for each pharmacokinetic parameter derived from DCE-MRI. The 90th percentile of K ep achieved the highest AUC value (0.927) among all histogram-derived values. The whole-lesion histogram analysis of pharmacokinetic parameters can improve the diagnostic accuracy of breast DCE-MRI with the CDT-VIBE technique. The 90th percentile of K ep may be the best indicator in differentiation between malignant and benign breast lesions. 4 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2018;47:91-96. © 2017 International Society for Magnetic Resonance in Medicine.

Flat epithelial atypia of the breast.

PubMed

Nasser, Selim M

2009-01-01

"Flat epithelial atypia" is the adopted term by the WHO working group on breast tumor referring to an early neoplastic breast lesion affecting the terminal duct-lobular units. Pathologists have described this lesion under a variety of names including columnar cell lesions and low-grade clinging carcinoma in situ. It is usually encountered on breast biopsies performed for mammographically-identified microcalcifications. Because of its relatively frequent association with carcinomas, its recognition in biopsy specimens is important. This review will focus on the histopathologic features, differential diagnosis, biologic potential, clinical significance and management of this lesion.

Shear-Wave Elastography for the Differential Diagnosis of Breast Papillary Lesions

PubMed Central

Chung, Jin; Lee, Won Kyung; Cha, Eun-Suk; Lee, Jee Eun; Kim, Jeoung Hyun; Ryu, Young Hoon

2016-01-01

Objective To evaluate the diagnostic performance of shear-wave elastography (SWE) for the differential diagnosis of breast papillary lesions. Methods This study was an institutional review board-approved retrospective study, with a waiver of informed consent. A total of 79 breast papillary lesions in 71 consecutive women underwent ultrasound and SWE prior to biopsy. Ultrasound features and quantitative SWE parameters were recorded for each lesion. All lesions were surgically excised or excised using an ultrasound-guided vacuum-assisted method. The diagnostic performances of the quantitative SWE parameters were compared using the area under the receiver operating characteristic curve (AUC). Results Of the 79 lesions, six (7.6%) were malignant and 12 (15.2%) were atypical. Orientation, margin, and the final BI-RADS ultrasound assessments were significantly different for the papillary lesions (p < 0.05). All qualitative SWE parameters were significantly different (p < 0.05). The AUC values for SWE parameters of benign and atypical or malignant papillary lesions ranged from 0.707 to 0.757 (sensitivity, 44.4–94.4%; specificity, 42.6–88.5%). The maximum elasticity and the mean elasticity showed the highest AUC (0.757) to differentiate papillary lesions. Conclusion SWE provides additional information for the differential diagnosis of breast papillary lesions. Quantitative SWE features were helpful to differentiate breast papillary lesions. PMID:27893857

[MRI findings and pathological features of occult breast cancer].

PubMed

Zhang, J J; Yang, X T; Du, X S; Zhang, J X; Hou, L N; Niu, J L

2018-01-23

Objective: To investigate the magnetic resonance imaging (MRI) findings and clinicopathological features of primary lesions in patients with occult breast cancer (OBC). Methods: The imaging reports from the Breast Imaging Reporting and Data System in 2013 were retrospectively analyzed to investigate the morphology and the time signal intensity curve (TIC) of breast lesions in patients with OBC. The clinical and pathological characteristics of these patients were also included. Results: A total of 34 patients were enrolled. Among these patients, 24 patients underwent modified radical mastectomy and 18 of them had primary breast carcinoma in pathological sections. MRI detected 17 cases of primary lesions, including six masse lesions with a diameter of 0.6-1.2 cm (average 0.9 cm), and 11 non-mass lesions with four linear distributions, three segmental distributions, three focal distributions, and one regions distribution. Five patients had TIC typeⅠprimary lesions, ten had TIC type Ⅱ primary lesions, and two had TIC type Ⅲ primary lesions. Among all 34 cases, 23 of them had complete results of immunohistochemistry: 11 estrogen receptor (ER) positive lesions (47.8%), tenprogesterone receptor (PR) positive lesions (43.5%), seven human epidermal growth factor receptor 2 (HER-2) positive lesions (30.4%), and 20high expression(>14%) of Ki-67 (87.0%). The proportion of type luminal A was 4.3%, type luminal B was 43.5%, triple negative breast cancer (TNBC) was 30.4%, and HER-2 over expression accounted for 21.7%. Conclusions: The primary lesions of OBC usually manifested as small mass lesions, or focal, linear or segmental distribution of non-mass lesions. The positive rate of ER and PR was low, but the positive rate of HER-2 and the proliferation index of Ki-67 was high. Type luminal B is the most common molecular subtype.

Mammographic appearances of male breast disease.

PubMed

Appelbaum, A H; Evans, G F; Levy, K R; Amirkhan, R H; Schumpert, T D

1999-01-01

Various male breast diseases have characteristic mammographic appearances that can be correlated with their pathologic diagnoses. Male breast cancer is usually subareolar and eccentric to the nipple. Margins of the lesions are more frequently well defined, and calcifications are rarer and coarser than those occurring in female breast cancer. Gynecomastia usually appears as a fan-shaped density emanating from the nipple, gradually blending into surrounding fat. It may have prominent extensions into surrounding fat and, in some cases, an appearance similar to that of a heterogeneously dense female breast. Although there are characteristic mammographic features that allow breast cancer in men to be recognized, there is substantial overlap between these features and the mammographic appearance of benign nodular lesions. The mammographic appearance of gynecomastia is not similar to that of male breast cancer, but in rare cases, it can mask malignancy. Gynecomastia can be mimicked by chronic inflammation. All mammographically lucent lesions of the male breast appear to be benign, similar to such lesions in the female breast.

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.

Use of shear wave elastography to differentiate benign and malignant breast lesions.

PubMed

Çebi Olgun, Deniz; Korkmazer, Bora; Kılıç, Fahrettin; Dikici, Atilla Süleyman; Velidedeoğlu, Mehmet; Aydoğan, Fatih; Kantarcı, Fatih; Yılmaz, Mehmet Halit

2014-01-01

We aimed to determine the correlations between the elasticity values of solid breast masses and histopathological findings to define cutoff elasticity values differentiating malignant from benign lesions. A total of 115 solid breast lesions of 109 consecutive patients were evaluated prospectively using shear wave elastography (SWE). Two orthogonal elastographic images of each lesion were obtained. Minimum, mean, and maximum elasticity values were calculated in regions of interest placed over the stiffest areas on the two images; we also calculated mass/fat elasticity ratios. Correlation of elastographic measurements with histopathological results were studied. Eighty-three benign and thirty-two malignant lesions were histopathologically diagnosed. The minimum, mean, and maximum elasticity values, and the mass/fat elasticity ratios of malignant lesions, were significantly higher than those of benign lesions. The cutoff value was 45.7 kPa for mean elasticity (sensitivity, 96%; specificity, 95%), 54.3 kPa for maximum elasticity (sensitivity, 95%; specificity, 94%), 37.1 kPa for minimum elasticity (sensitivity, 96%; specificity, 95%), and 4.6 for the mass/fat elasticity ratio (sensitivity, 97%; specificity, 95%). SWE yields additional valuable quantitative data to ultrasonographic examination on solid breast lesions. SWE may serve as a complementary tool for diagnosis of breast lesions. Long-term clinical studies are required to accurately select lesions requiring biopsy.

Breast 3 T-MR imaging: indication for stereotactic vacuum-assisted breast biopsy.

PubMed

Yamamoto, Nobuko; Yoshizako, Takeshi; Yoshikawa, Kazuaki; Itakura, Masayuki; Maruyama, Riruke; Kitagaki, Hajime

2014-01-01

The purpose of this study was to assess indications for stereotactic vacuum-assisted breast biopsy (SVAB) evaluated by breast 3 T-magnetic resonance (3 T-MR) imaging in patients showing suspicious microcalcifications on mammography and negative ultrasound (US) findings. Fifty-five patients with 55 breast lesions showing suspicious microcalcifications on mammography and negative US findings underwent preoperative 3 T-MR examination including dynamic MR imaging. All patients underwent SVAB within 1 month of MR imaging. The pathological diagnosis of each breast lesion was made by examining tissues obtained by SVAB or radical/partial mastectomy. 3 T-MR imaging findings were evaluated by using the American College of Radiology Breast Imaging Reporting and Data System Atlas (BI-RADS-MRI) and then were correlated with the histopathological findings. When BI-RADS 4 and 5 MR imaging lesions were assumed to be malignant, the usefulness of 3 T-MR imaging was evaluated for diagnosis of impalpable breast lesions by SVAB among lesions with microcalcification detected by mammography and negative US findings. There were 21 malignant lesions, including 5 invasive ductal carcinomas, 16 lesions of ductal carcinoma in situ (DCIS). The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 3 T-MR imaging for deciding the indications for SVAB was 90.5%, 97.1%, 95.0%, 94.3%, and 94.5%, respectively. The one-false negative case was a DCIS with small enhancing lesions (0.5 mm). The one false-positive case was ductal adenoma with a linear ductal pattern of enhancement. 3 T-MR imaging may be useful for deciding the indications for SVAB in patients who have breast lesions with microcalcification that are impalpable and are detected by mammography and negative US findings. However, our findings should be considered preliminary and further prospective investigation is required.

[Diagnostic efficiency of decline rate of signal intensity and apparent diffusion coefficient with different b values for differentiating benign and malignant breast lesions on diffusion-weighted 3.0T magnetic resonance imaging].

PubMed

Jiang, Jing; Liu, Wanhua; Ye, Yuanyuan; Wang, Rui; Li, Fengfang; Peng, Chengyu

2014-06-17

To investigate the diagnostic efficiency of decline rate of signal intensity and apparent diffusion coefficient with different b values for differentiating benign and malignant breast lesions on diffusion-weighted 3.0 T magnetic resonance imaging. A total of 152 patients with 162 confirmed histopathologically breast lesions (85 malignant and 77 benign) underwent 3.0 T diffusion-weighted magnetic resonance imaging. Four b values (0, 400, 800 and 1 000 s/mm²) were used. The signal intensity and ADC values of breast lesions were measured respectively. The signal intensity decline rate (SIDR) and apparent diffusion coefficient decline rate (ADCDR) were calculated respectively. SIDR = (signal intensity of lesions with low b value-signal intensity of lesions with high b value)/signal intensity of lesions with low b value, ADCDR = (ADC value of lesions with low b value-ADC value of lesions with high b value) /ADC value of lesions with low b value. The independent sample t-test was employed for statistical analyses and the receiver operating characteristic (ROC) curve for evaluating the diagnosis efficiency of SIDR and ADCDR values. Significant differences were observed in SIDR between benign and malignant breast lesions with b values of 0-400, 400-800 and 800-1 000 s/mm². The sensitivities of SIDR for differentiating benign and malignant breast lesions were 61.2%, 68.2% and 67.1%, the specificities 74.0%, 85.7% and 67.5%, the diagnosis accordance rates 67.3%, 76.5% and 67.3%, the positive predictive values 72.2%, 84.1% and 69.5% and the negative predictive values 63.3%, 71.0% and 65.0% respectively. Significant differences were observed in ADCDR between benign and malignant breast lesions with b values of 400-800 s/mm² and 800-1 000 s/mm². The sensitivities of SDR for differentiating benign and malignant breast lesions were 80.0% and 65.9%, the specificities 72.7% and 65.0%, the diagnostic accordance rates 76.5% and 65.4%, the positive predictive values 76.4% and 67.5% and the negative predictive values 76.7% and 63.3% respectively. The decline rate of signal intensity and apparent diffusion coefficient with different b values may be used for differentiating benign and malignant breast lesions. And the diagnostic efficiency with b values of 400-800 s/mm² is optimal.

Prediction of malignancy by a radiomic signature from contrast agent-free diffusion MRI in suspicious breast lesions found on screening mammography.

PubMed

Bickelhaupt, Sebastian; Paech, Daniel; Kickingereder, Philipp; Steudle, Franziska; Lederer, Wolfgang; Daniel, Heidi; Götz, Michael; Gählert, Nils; Tichy, Diana; Wiesenfarth, Manuel; Laun, Frederik B; Maier-Hein, Klaus H; Schlemmer, Heinz-Peter; Bonekamp, David

2017-08-01

To assess radiomics as a tool to determine how well lesions found suspicious on breast cancer screening X-ray mammography can be categorized into malignant and benign with unenhanced magnetic resonance (MR) mammography with diffusion-weighted imaging and T 2 -weighted sequences. From an asymptomatic screening cohort, 50 women with mammographically suspicious findings were examined with contrast-enhanced breast MRI (ceMRI) at 1.5T. Out of this protocol an unenhanced, abbreviated diffusion-weighted imaging protocol (ueMRI) including T 2 -weighted, (T 2 w), diffusion-weighted imaging (DWI), and DWI with background suppression (DWIBS) sequences and corresponding apparent diffusion coefficient (ADC) maps were extracted. From ueMRI-derived radiomic features, three Lasso-supervised machine-learning classifiers were constructed and compared with the clinical performance of a highly experienced radiologist: 1) univariate mean ADC model, 2) unconstrained radiomic model, 3) constrained radiomic model with mandatory inclusion of mean ADC. The unconstrained and constrained radiomic classifiers consisted of 11 parameters each and achieved differentiation of malignant from benign lesions with a .632 + bootstrap receiver operating characteristics (ROC) area under the curve (AUC) of 84.2%/85.1%, compared to 77.4% for mean ADC and 95.9%/95.9% for the experienced radiologist using ceMRI/ueMRI. In this pilot study we identified two ueMRI radiomics classifiers that performed well in the differentiation of malignant from benign lesions and achieved higher performance than the mean ADC parameter alone. Classification was lower than the almost perfect performance of a highly experienced breast radiologist. The potential of radiomics to provide a training-independent diagnostic decision tool is indicated. A performance reaching the human expert would be highly desirable and based on our results is considered possible when the concept is extended in larger cohorts with further development and validation of the technique. 1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:604-616. © 2017 International Society for Magnetic Resonance in Medicine.

Can Breast Cancer Biopsy Influence Sentinel Lymph Node Status?

PubMed

Giuliani, Michela; Patrolecco, Federica; Rella, Rossella; Di Giovanni, Silvia Eleonora; Infante, Amato; Rinaldi, Pierluigi; Romani, Maurizio; Mulè, Antonino; Arciuolo, Damiano; Belli, Paolo; Bonomo, Lorenzo

2016-12-01

We evaluated whether the needle size could influence metastasis occurrence in the axillary sentinel lymph node (SLN) in ultrasound-guided core needle biopsy (US-CNB) of breast cancer (BC). The data from all patients with breast lesions who had undergone US-CNB at our institution from January 2011 to January 2015 were retrospectively reviewed. A total of 377 BC cases were included using the following criteria: (1) percutaneous biopsy-proven invasive BC; and (2) SLN dissection with histopathologic examination. The patients were divided into 2 groups according to the needle size used: 14 gauge versus 16 or 18 gauge. SLN metastasis classification followed the 7th American Joint Committee on Cancer (2010) TNM pathologic staging factors: macrometastases, micrometastases, isolated tumor cells, or negative. Only macrometastases and micrometastases were considered positive, and the positive and negative rates were calculated for the overall population and for both needle size groups. Of the 377 BC cases, 268 US-CNB procedures were performed using a 14-gauge needle and 109 with a 16- or 18-gauge needle, respectively. The negative rate was significantly related statistically with the needle size, with a greater prevalence in the 14-gauge group on both extemporaneous analysis (P = .019) and definitive analysis (P = .002). The macrometastasis rate was 17% (63 of 377) for the 14-gauge and 3% (12 of 377) for the 16- and 18-gauge needles, respectively. Our preliminary results have suggested that use of a large needle size in CNB does not influence SLN status; thus, preoperative breast biopsy can be considered a safe procedure in the diagnosis of malignant breast lesions. Copyright © 2016 Elsevier Inc. All rights reserved.

Anisotropy of Solid Breast Lesions in 2D Shear Wave Elastography is an Indicator of Malignancy.

PubMed

Skerl, Katrin; Vinnicombe, Sarah; Thomson, Kim; McLean, Denis; Giannotti, Elisabetta; Evans, Andrew

2016-01-01

To investigate if anisotropy at two-dimensional shear wave elastography (SWE) suggests malignancy and whether it correlates with prognostic and predictive factors in breast cancer. Study group A of 244 solid breast lesions was imaged with SWE between April 2013 and May 2014. Each lesion was imaged in radial and in antiradial planes, and the maximum elasticity, mean elasticity, and standard deviation were recorded and correlated with benign/malignant status, and if malignant, correlated with conventional predictive and prognostic factors. The results were compared to a study group B of 968 solid breast lesions, which were imaged in sagittal and in axial planes between 2010 and 2013. Neither benign nor malignant lesion anisotropy is plane dependent. However, malignant lesions are more anisotropic than benign lesions (P ≤ 0.001). Anisotropy correlates with increasing elasticity parameters, breast imaging-reporting and data system categories, core biopsy result, and tumor grade. Large cancers are significantly more anisotropic than small cancers (P ≤ 0.001). The optimal anisotropy cutoff threshold for benign/malignant differentiation of 150 kPa(2) achieves the best sensitivity (74%) with a reasonable specificity (63%). Anisotropy may be useful during benign/malignant differentiation of solid breast masses using SWE. Anisotropy also correlates with some prognostic factors in breast cancer. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Breast tumor size assessment: comparison of conventional ultrasound and contrast-enhanced ultrasound.

PubMed

Jiang, Yu-Xin; Liu, He; Liu, Ji-Bin; Zhu, Qing-Li; Sun, Qiang; Chang, Xiao-Yan

2007-12-01

Accurate assessment of tumor size is necessary when selecting patients for breast-conserving surgery. In the study of breast contrast-enhanced ultrasound (CEUS), we found that tumor size discrepancy between CEUS and conventional ultrasound (US) existed in some breast lesions, for which the reasons are not clear. Breast CEUS examinations were performed in 104 patients with breast lesions. The measurement of the 104 breast tumors on conventional US was obtained and compared with the measurement on CEUS. A difference in measuring tumor size of >3 mm for tumors up to 1.7 cm and 4 mm for tumors >or=1.7 cm, was defined as a significant discrepancy between conventional US and CEUS. The histopathological examination of size discrepancy was performed and the margin characteristics of breast cancers with larger measurements were compared with those with unchanged measurements. Among the 104 lesions (43 malignant, 60 benign, 1 borderline), the size of 27 breast cancers and one granulomatous mastitis appeared larger at CEUS. Pathologic examinations of the region corresponding to the measurement discrepancy were mainly ductal carcinomas in situ (DCIS), invasive carcinoma with a DCIS component, adenosis with lobular hyperplasia in breast cancers and inflammatory cell infiltration in one granulomatous mastitis. Well-defined margin characteristics were significantly different between breast cancers with larger measurements at CEUS and those with unchanged measurements of size (p = 0.002), whereas no significant difference was found between the two groups in ill-defined, spiculated, hyperechoic halo, microlobulated and angulated margins (p = 0.463, 0.117, 0.194, 0.666 and 0.780, respectively). This initial study suggests that significant discrepancy of breast lesion measurement between conventional US and CEUS is more likely presented in breast cancer than benign lesions. The pathologic findings corresponding to the region of size increased at CEUS are malignant in most malignant lesions and benign in benign lesions. It is difficult to predict whether the size measurement of the breast cancer increases at CEUS based on the margin characteristics showed on conventional US.

[The lesions of flat epithelial atypia diagnosed on breast biopsy].

PubMed

Peres, A; Becette, V; Guinebretiere, J-M; Cherel, P; Barranger, E

2011-10-01

Among pre-invasive breast diseases, the lesion of flat epithelial atypia has a level of risk that remains unclear. The clinical significance of these lesions and how to behave during their diagnostic biopsy (monitoring vs. surgery) are still uncertain, because few studies (including monitoring) are available and because of the polymorphic spectrum of lesions and their many denominations across the studies in the literature. This article aims to update our knowledge and provide elements for the management of these lesions diagnosed on breast biopsy. Copyright © 2011. Published by Elsevier SAS.

Risk of invasive breast cancer and ductal carcinoma in situ in women with atypical papillary lesions of the breast.

PubMed

Cuneo, Kyle C; Dash, Rajesh C; Wilke, Lee G; Horton, Janet K; Koontz, Bridget F

2012-09-01

Benign papillary lesions of the breast include papilloma and papillomatosis. A retrospective analysis of patients with a papillary breast lesion diagnosed between October 1992 and December 2009 was performed. Patients were excluded if they had a previous or concurrent diagnosis of invasive or in situ cancer or less than 6 months of follow-up. The Kaplan-Meier method was used to determine the risk of developing subsequent malignancy. The log rank test was used to compare groups of patients. Median follow-up for the 167 patients included in the study was 4.6 years. Fifty-one patients had a papillary lesion with atypia and 116 patients had a papillary lesion without atypia. Patients with a papillary lesion with atypia were more likely to develop invasive or in situ breast cancer with a 5 year risk of 13.0% versus 4.6% in patients with no atypia (p = 0.03). © 2012 Wiley Periodicals, Inc.

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

Parekh, V; Jacobs, MA

Purpose: Multiparametric radiological imaging is used for diagnosis in patients. Potentially extracting useful features specific to a patient’s pathology would be crucial step towards personalized medicine and assessing treatment options. In order to automatically extract features directly from multiparametric radiological imaging datasets, we developed an advanced unsupervised machine learning algorithm called the multidimensional imaging radiomics-geodesics(MIRaGe). Methods: Seventy-six breast tumor patients underwent 3T MRI breast imaging were used for this study. We tested the MIRaGe algorithm to extract features for classification of breast tumors into benign or malignant. The MRI parameters used were T1-weighted, T2-weighted, dynamic contrast enhanced MR imaging (DCE-MRI)more » and diffusion weighted imaging(DWI). The MIRaGe algorithm extracted the radiomics-geodesics features (RGFs) from multiparametric MRI datasets. This enable our method to learn the intrinsic manifold representations corresponding to the patients. To determine the informative RGF, a modified Isomap algorithm(t-Isomap) was created for a radiomics-geodesics feature space(tRGFS) to avoid overfitting. Final classification was performed using SVM. The predictive power of the RGFs was tested and validated using k-fold cross validation. Results: The RGFs extracted by the MIRaGe algorithm successfully classified malignant lesions from benign lesions with a sensitivity of 93% and a specificity of 91%. The top 50 RGFs identified as the most predictive by the t-Isomap procedure were consistent with the radiological parameters known to be associated with breast cancer diagnosis and were categorized as kinetic curve characterizing RGFs, wash-in rate characterizing RGFs, wash-out rate characterizing RGFs and morphology characterizing RGFs. Conclusion: In this paper, we developed a novel feature extraction algorithm for multiparametric radiological imaging. The results demonstrated the power of the MIRaGe algorithm at automatically discovering useful feature representations directly from the raw multiparametric MRI data. In conclusion, the MIRaGe informatics model provides a powerful tool with applicability in cancer diagnosis and a possibility of extension to other kinds of pathologies. NIH (P50CA103175, 5P30CA006973 (IRAT), R01CA190299, U01CA140204), Siemens Medical Systems (JHU-2012-MR-86-01) and Nivida Graphics Corporation.« less

Cupping artifact correction and automated classification for high-resolution dedicated breast CT images.

PubMed

Yang, Xiaofeng; Wu, Shengyong; Sechopoulos, Ioannis; Fei, Baowei

2012-10-01

To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors' classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors' automatic classification and manual segmentation were 91.6% ± 2.0%. A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution.

Cupping artifact correction and automated classification for high-resolution dedicated breast CT images

PubMed Central

Yang, Xiaofeng; Wu, Shengyong; Sechopoulos, Ioannis; Fei, Baowei

2012-01-01

Purpose: To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. Methods: The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors’ classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. Results: The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors’ automatic classification and manual segmentation were 91.6% ± 2.0%. Conclusions: A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution. PMID:23039675

Exploring nonlinear feature space dimension reduction and data representation in breast CADx with Laplacian eigenmaps and t-SNE

PubMed Central

Jamieson, Andrew R.; Giger, Maryellen L.; Drukker, Karen; Li, Hui; Yuan, Yading; Bhooshan, Neha

2010-01-01

Purpose: In this preliminary study, recently developed unsupervised nonlinear dimension reduction (DR) and data representation techniques were applied to computer-extracted breast lesion feature spaces across three separate imaging modalities: Ultrasound (U.S.) with 1126 cases, dynamic contrast enhanced magnetic resonance imaging with 356 cases, and full-field digital mammography with 245 cases. Two methods for nonlinear DR were explored: Laplacian eigenmaps [M. Belkin and P. Niyogi, “Laplacian eigenmaps for dimensionality reduction and data representation,” Neural Comput. 15, 1373–1396 (2003)] and t-distributed stochastic neighbor embedding (t-SNE) [L. van der Maaten and G. Hinton, “Visualizing data using t-SNE,” J. Mach. Learn. Res. 9, 2579–2605 (2008)]. Methods: These methods attempt to map originally high dimensional feature spaces to more human interpretable lower dimensional spaces while preserving both local and global information. The properties of these methods as applied to breast computer-aided diagnosis (CADx) were evaluated in the context of malignancy classification performance as well as in the visual inspection of the sparseness within the two-dimensional and three-dimensional mappings. Classification performance was estimated by using the reduced dimension mapped feature output as input into both linear and nonlinear classifiers: Markov chain Monte Carlo based Bayesian artificial neural network (MCMC-BANN) and linear discriminant analysis. The new techniques were compared to previously developed breast CADx methodologies, including automatic relevance determination and linear stepwise (LSW) feature selection, as well as a linear DR method based on principal component analysis. Using ROC analysis and 0.632+bootstrap validation, 95% empirical confidence intervals were computed for the each classifier’s AUC performance. Results: In the large U.S. data set, sample high performance results include, AUC0.632+=0.88 with 95% empirical bootstrap interval [0.787;0.895] for 13 ARD selected features and AUC0.632+=0.87 with interval [0.817;0.906] for four LSW selected features compared to 4D t-SNE mapping (from the original 81D feature space) giving AUC0.632+=0.90 with interval [0.847;0.919], all using the MCMC-BANN. Conclusions: Preliminary results appear to indicate capability for the new methods to match or exceed classification performance of current advanced breast lesion CADx algorithms. While not appropriate as a complete replacement of feature selection in CADx problems, DR techniques offer a complementary approach, which can aid elucidation of additional properties associated with the data. Specifically, the new techniques were shown to possess the added benefit of delivering sparse lower dimensional representations for visual interpretation, revealing intricate data structure of the feature space. PMID:20175497

Screening breast magnetic resonance imaging in women with atypia or lobular carcinoma in situ.

PubMed

Schwartz, Theresa; Cyr, Amy; Margenthaler, Julie

2015-02-01

Atypical lesions and lobular carcinoma in situ (LCIS) are associated with an increased risk of breast malignancy. The utility of breast magnetic resonance imaging (MRI) screening in this cohort of women after excision of a high-risk lesion has not been previously established. The objective of this study was to investigate outcomes of breast MRI surveillance in this subgroup of high-risk patients. We performed a retrospective review of women who required excision of an atypical lesion or LCIS who underwent at least one screening breast MRI from April 2005-December 2011. We collected information on demographics, number of second-look imaging studies recommended, number of biopsies performed and pathologic outcomes. A total of 179 patients met the inclusion criteria, including 131 (73%) with atypical lesions and 48 (27%) with LCIS. Second-look imaging was recommended for 31 of 131 (23.7%) patients with atypical lesions and 8 of 48 (16.7%) with LCIS. Ten biopsies were performed in the atypical cohort (7.6%) with two revealing a malignancy (Positive Predictive Value [PPV] of 20%). In the LCIS cohort, five biopsies were performed (10.4%) with one revealing a malignancy (PPV of 20%). The benefit of breast MRI surveillance in patients after excision of atypical lesions or LCIS has not been clearly delineated previously. Our data demonstrate that the use of screening breast MRI in this cohort results in additional work-up in one-fifth of patients, but a PPV of only 20%. Large, prospective studies would be needed to determine whether breast cancer outcomes differ between patients undergoing conventional breast screening and those undergoing conventional breast screening plus breast MRI surveillance. Copyright © 2015 Elsevier Inc. All rights reserved.

Ex vivo MRI evaluation of breast tumors: a novel tool for verifying resection of nonpalpable only MRI detected lesions.

PubMed

Agresti, Roberto; Trecate, Giovanna; Ferraris, Cristina; Valeri, Barbara; Maugeri, Ilaria; Pellitteri, Cristina; Martelli, Gabriele; Migliavacca, Silvana; Carcangiu, Maria Luisa; Bohm, Silvia; Maffioli, Lorenzo; Vergnaghi, Daniele; Panizza, Pietro

2013-01-01

A fundamental question in surgery of only magnetic resonance imaging (MRI)-detected breast lesions is to ensure their removal when they are not palpable by clinical examination and surgical exploration. This is especially relevant in the case of small tumors, carcinoma in situ or lobular carcinoma. Thirty-nine patients were enrolled in the study, 21 patients with breast lesions detected by both conventional imaging and breast MRI (bMRI) and 18 patients with bMRI findings only. Preoperative bMRI allowed staging the disease and localizing the lesion. In the operating theater, contrast medium was injected 1 minute before skin incision. After removal, surgical specimens were submitted to ex vivo MRI, performed using a dedicated surface coil and Spair inversion recovery sequences for suppression of fat signal intensity. All MRI enhancing lesions were completely included within the surgical specimen and visualized by ex vivo MRI. In the first 21 patients, bMRI was able to visualize branching margins or satellite nodules around the core lesion, and allowed for better staging of the surrounding in situ carcinoma; in the last 18 patients, eight of whom were breast cancer type 1 susceptibility protein (BRCA) mutation carriers, bMRI identified 12 malignant tumors, otherwise undetectable, that were all visualized by ex vivo MRI. This is the first description of a procedure that re-enhances breast lesions within a surgical specimen, demonstrating the surgical removal of nonpalpable breast lesions diagnosed only with bMRI. This new strategy reproduces the morphology and the entire extension of the primary lesion on the specimen, with potentially better local surgical control, reducing additional unplanned surgery. © 2013 Wiley Periodicals, Inc.

Comparison of transducers with different frequencies in breast contrast-enhanced ultrasound (CEUS) using SonoVue as contrast agent.

PubMed

Wang, Yong-Mei; Fan, Wei; Zhang, Kai; Zhang, Li; Tan, Zhen; Ma, Rong

2016-07-01

To explore the effectiveness of different transducers in breast contrast-enhanced ultrasound (CEUS) using SonoVue(®) (Bracco, Plan-Les-Ouates, Switzerland) as the contrast agent. Breast CEUS was performed in 51 patients with 51 breast lesions using a low-frequency transducer (probe C5-1) and a high-frequency transducer (probe L12-5) separately. All image processes were reviewed for the presence of local blood perfusion defects and surrounding vessels. McNemar's test was conducted to compare the detection effectiveness between these two transducers. Pathological results revealed 38 malignant and 13 benign lesions. The two transducers showed no difference in detecting benign lesions. Among malignant lesions, CEUS conducted by probe C5-1 (frequency range from 1 to 5 MHz) presented 23 (60.5%) lesions with local blood perfusion defects and 26 (68.4%) lesions with surrounding vessels. Meanwhile, probe L12-5 (frequency range from 5 to 12 MHz) showed only 12 (31.6%) lesions with local blood perfusion defects and 12 (31.6%) lesions with surrounding vessel. Probe C5-1 was more sensitive than probe L12-5 in detecting malignant CEUS characteristics (p-value < 0.05). The low-frequency transducer was more sensitive than the high-frequency transducer in breast CEUS using SonoVue as the contrast agent. A new contrast agent with a higher resonance frequency, specially designed for high-frequency transducers, may be helpful in improving the clinical value of breast CEUS. The first study comparing different frequency transducers in breast CEUS of the same patient lesions. We brought out the requirement for CEUS contrast agents which are more suitable for high-frequency examinations.

Use of shear wave elastography to differentiate benign and malignant breast lesions

PubMed Central

Olgun, Deniz Çebi; Korkmazer, Bora; Kılıç, Fahrettin; Dikici, Atilla Süleyman; Velidedeoğlu, Mehmet; Aydoğan, Fatih; Kantarcı, Fatih; Yılmaz, Mehmet Halit

2014-01-01

PURPOSE We aimed to determine the correlations between the elasticity values of solid breast masses and histopathological findings to define cutoff elasticity values differentiating malignant from benign lesions. MATERIALS and METHODS A total of 115 solid breast lesions of 109 consecutive patients were evaluated prospectively using shear wave elastography (SWE). Two orthogonal elastographic images of each lesion were obtained. Minimum, mean, and maximum elasticity values were calculated in regions of interest placed over the stiffest areas on the two images; we also calculated mass/fat elasticity ratios. Correlation of elastographic measurements with histopathological results were studied. RESULTS Eighty-three benign and thirty-two malignant lesions were histopathologically diagnosed. The minimum, mean, and maximum elasticity values, and the mass/fat elasticity ratios of malignant lesions, were significantly higher than those of benign lesions. The cutoff value was 45.7 kPa for mean elasticity (sensitivity, 96%; specificity, 95%), 54.3 kPa for maximum elasticity (sensitivity, 95%; specificity, 94%), 37.1 kPa for minimum elasticity (sensitivity, 96%; specificity, 95%), and 4.6 for the mass/fat elasticity ratio (sensitivity, 97%; specificity, 95%). CONCLUSION SWE yields additional valuable quantitative data to ultrasonographic examination on solid breast lesions. SWE may serve as a complementary tool for diagnosis of breast lesions. Long-term clinical studies are required to accurately select lesions requiring biopsy. PMID:24509183

Cytomorphologic features of papillary lesions of the male breast: a study of 11 cases.

PubMed

Reid-Nicholson, Michelle D; Tong, Guoxia; Cangiarella, Joan F; Moreira, Andre L

2006-08-25

Breast masses occur in men far less commonly than women and are infrequently subjected to fine-needle aspiration (FNA) biopsy. Papillary lesions of the male breast are rare and are comprised of a spectrum of lesions ranging from papillary hyperplasia in gynecomastia to invasive papillary carcinoma. The following study describes the cytomorphology of papillary breast lesions in 11 men. The patients ranged in age from 23 to 78 years old and each presented with an unilateral subareolar or periareolar breast mass that varied in size from 0.5 to 3 cm. Two patients presented with bloody nipple discharge. Archival material (8-year period) from FNA biopsies of papillary lesions of the male breast was reviewed. The reviewed cases were correlated with appropriate clinicopathologic follow-up. The smears had variable cellularity but all showed papillary clusters of mammary epithelial cells with and without fibrovascular cores. Single epithelial cells with a high nuclear-to-cytoplasmic ratio and eccentric nuclei were seen in all smears; however, these were more numerous in cases of adenocarcinoma. Hemosiderin-laden macrophages were present in all cases. Nipple discharge was seen only in the 2 benign lesions. All adenocarcinomas occurred in older men. The only cytologic criteria that differentiated benign from malignant papillary lesions were marked cellularity and the presence of abundant 3-dimensional clusters. To the best of the authors' knowledge, the current series is the largest in the English literature to date that examines the cytomorphologic features of papillary breast lesions in men. Copyright 2006 American Cancer Society.

A new background distribution-based active contour model for three-dimensional lesion segmentation in breast DCE-MRI

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

Liu, Hui; Liu, Yiping; Qiu, Tianshuang

2014-08-15

Purpose: To develop and evaluate a computerized semiautomatic segmentation method for accurate extraction of three-dimensional lesions from dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) of the breast. Methods: The authors propose a new background distribution-based active contour model using level set (BDACMLS) to segment lesions in breast DCE-MRIs. The method starts with manual selection of a region of interest (ROI) that contains the entire lesion in a single slice where the lesion is enhanced. Then the lesion volume from the volume data of interest, which is captured automatically, is separated. The core idea of BDACMLS is a new signed pressure functionmore » which is based solely on the intensity distribution combined with pathophysiological basis. To compare the algorithm results, two experienced radiologists delineated all lesions jointly to obtain the ground truth. In addition, results generated by other different methods based on level set (LS) are also compared with the authors’ method. Finally, the performance of the proposed method is evaluated by several region-based metrics such as the overlap ratio. Results: Forty-two studies with 46 lesions that contain 29 benign and 17 malignant lesions are evaluated. The dataset includes various typical pathologies of the breast such as invasive ductal carcinoma, ductal carcinomain situ, scar carcinoma, phyllodes tumor, breast cysts, fibroadenoma, etc. The overlap ratio for BDACMLS with respect to manual segmentation is 79.55% ± 12.60% (mean ± s.d.). Conclusions: A new active contour model method has been developed and shown to successfully segment breast DCE-MRI three-dimensional lesions. The results from this model correspond more closely to manual segmentation, solve the weak-edge-passed problem, and improve the robustness in segmenting different lesions.« less

Diagnostic performance of qualitative shear-wave elastography according to different color map opacities for breast masses.

PubMed

Kim, Hana; Youk, Ji Hyun; Gweon, Hye Mi; Kim, Jeong-Ah; Son, Eun Ju

2013-08-01

To compare the diagnostic performance of qualitative shear-wave elastography (SWE) according to three different color map opacities for breast masses 101 patients aged 21-77 years with 113 breast masses underwent B-mode US and SWE under three different color map opacities (50%, 19% and 100%) before biopsy or surgery. Following SWE features were reviewed: visual pattern classification (pattern 1-4), color homogeneity (Ehomo) and six-point color score of maximum elasticity (Ecol). Combined with B-mode US and SWE, the likelihood of malignancy (LOM) was also scored. The area under the curve (AUC) was obtained by ROC curve analysis to assess the diagnostic performance under each color opacity. A visual color pattern, Ehomo, Ecol and LOM scoring were significantly different between benign and malignant lesions under all color opacities (P<0.001). For 50% opacity, AUCs of visual color pattern, Ecol, Ehomo and LOM scoring were 0.902, 0.951, 0.835 and 0.975. But, for each SWE feature, there was no significant difference in the AUC among three different color opacities. For all color opacities, visual color pattern and Ecol showed significantly higher AUC than Ehomo. In addition, a combined set of B-mode US and SWE showed significantly higher AUC than SWE alone for color patterns, Ehomo, but no significant difference was found in Ecol. Qualitative SWE was useful to differentiate benign from malignant breast lesion under all color opacities. The difference in color map opacity did not significantly influence diagnostic performance of SWE. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Breast mass segmentation in mammography using plane fitting and dynamic programming.

PubMed

Song, Enmin; Jiang, Luan; Jin, Renchao; Zhang, Lin; Yuan, Yuan; Li, Qiang

2009-07-01

Segmentation is an important and challenging task in a computer-aided diagnosis (CAD) system. Accurate segmentation could improve the accuracy in lesion detection and characterization. The objective of this study is to develop and test a new segmentation method that aims at improving the performance level of breast mass segmentation in mammography, which could be used to provide accurate features for classification. This automated segmentation method consists of two main steps and combines the edge gradient, the pixel intensity, as well as the shape characteristics of the lesions to achieve good segmentation results. First, a plane fitting method was applied to a background-trend corrected region-of-interest (ROI) of a mass to obtain the edge candidate points. Second, dynamic programming technique was used to find the "optimal" contour of the mass from the edge candidate points. Area-based similarity measures based on the radiologist's manually marked annotation and the segmented region were employed as criteria to evaluate the performance level of the segmentation method. With the evaluation criteria, the new method was compared with 1) the dynamic programming method developed by Timp and Karssemeijer, and 2) the normalized cut segmentation method, based on 337 ROIs extracted from a publicly available image database. The experimental results indicate that our segmentation method can achieve a higher performance level than the other two methods, and the improvements in segmentation performance level were statistically significant. For instance, the mean overlap percentage for the new algorithm was 0.71, whereas those for Timp's dynamic programming method and the normalized cut segmentation method were 0.63 (P < .001) and 0.61 (P < .001), respectively. We developed a new segmentation method by use of plane fitting and dynamic programming, which achieved a relatively high performance level. The new segmentation method would be useful for improving the accuracy of computerized detection and classification of breast cancer in mammography.

The influence of family history on breast cancer risk in women with biopsy-confirmed benign breast disease: results from the Nurses' Health Study.

PubMed

Collins, Laura C; Baer, Heather J; Tamimi, Rulla M; Connolly, James L; Colditz, Graham A; Schnitt, Stuart J

2006-09-15

An association between histologic category of benign breast disease (BBD) and breast cancer risk has been well documented. However, the influence of a positive family history (FH) on breast cancer risk among women with biopsy-confirmed BBD is less certain. The authors conducted a nested case-control study of BBD and breast cancer risk among 2005 women who were enrolled in the Nurses' Health Study. Cases were women with breast cancer who had a previous benign breast biopsy (n = 395 women). Controls were women who also had previous biopsy-confirmed BBD but were free from breast cancer at the time the corresponding case was diagnosed (n = 1610 women). BBD slides were reviewed and categorized as either nonproliferative lesions, proliferative lesions without atypia, or atypical hyperplasia (AH). Compared with women who had nonproliferative lesions and no FH, women who had proliferative lesions without atypia and a positive FH had a higher breast cancer risk (odds ratio [OR], 2.45; 95% confidence interval [95% CI], 1.61-3.70) than women with no FH (OR, 1.51; 95% CI, 1.12-2.06; P = .07). Among women who had AH, the OR for the development of breast cancer was 4.38 (95% CI, 2.93-6.55) for those with no FH and 5.37 (95% CI, 3.01-9.58) for those with a positive FH (P = .57). There was no significant interaction between the type of BBD and FH (P = .74). A positive FH of breast cancer slightly increased the breast cancer risk among women who had proliferative lesions without atypia. The increase in risk of breast cancer associated with FH was not significant among women who had AH. (c) 2006 American Cancer Society.

Added value of semi-quantitative breast-specific gamma imaging in the work-up of suspicious breast lesions compared to mammography, ultrasound and 3-T MRI

PubMed Central

Seymer, A; Keinrath, P; Holzmannhofer, J; Pirich, C; Hergan, K; Meissnitzer, M W

2015-01-01

Objective: To prospectively analyse the diagnostic value of semi-quantitative breast-specific gamma imaging (BSGI) in the work-up of suspicious breast lesions compared with that of mammography (MG), breast ultrasound and MRI of the breast. Methods: Within a 15-month period, 67 patients with 92 breast lesions rated as Category IV or V according to the breast imaging reporting and data system detected with MG and/or ultrasound were included into the study. After the injection of 740–1110 MBq of Technetium-99m (99mTc) SestaMIBI intravenously, scintigrams were obtained in two projections comparable to MG. The BSGI was analysed visually and semi-quantitatively by calculating a relative uptake factor (X). With the exception of two patients with cardiac pacemakers, all patients underwent 3-T breast MRI. Biopsy results were obtained as the reference standard in all patients. Sensitivity, specificity, positive- and negative-predictive values, accuracy and area under the curve were calculated for each modality. Results: Among the 92 lesions, 67 (72.8%) were malignant. 60 of the 67 cancers of any size were detected by BSGI with an overall sensitivity of 90%, only exceeded by ultrasound with a sensitivity of 99%. The sensitivity of BSGI for lesions <1 cm declined significantly to 60%. Overall specificity of ultrasound was only 20%. Specificity, accuracy and positive-predictive value were the highest for BSGI (56%, 80% and 85%, respectively). X was significantly higher for malignant lesions (mean, 4.27) and differed significantly between ductal types (mean, 4.53) and the other histopathological entities (mean, 3.12). Conclusion: Semi-quantitative BSGI with calculation of the relative uptake factor (X) can help to characterize breast lesions. BSGI negativity may obviate the need for biopsy of breast lesions >1 cm with low or intermediate prevalence for malignancy. Advances in knowledge: Compared with morphological imaging modalities, specificity, positive-predictive value for malignancy and accuracy were the highest for BSGI in our study. BSGI negativity may support the decision not to biopsy in selected lesions with a low or low-to-moderate pre-test probability for malignancy. PMID:25882690

Proton magnetic resonance spectroscopy of tubercular breast abscess: report of a case.

PubMed

Das, Chandan Jyoti; Medhi, Kunjahari

2008-01-01

In vivo proton magnetic resonance spectroscopy (H-MRS) is a functional imaging modality. When magnetic resonance imaging is coupled with H-MRS, it results in accurate metabolic characterization of various lesions. Proton magnetic resonance spectroscopy has an established role in evaluating malignant breast lesions, and the increasing number of published literature supports the role of H-MRS in patients with breast cancer. However, H-MRS can be of help in evaluating benign breast disease. We present a case of tubercular breast abscess, initial diagnosis of which was suggested based on characteristic lipid pick on H-MRS and was subsequently confirmed by fine needle aspiration biopsy of the breast lesion.

A large epidermoid cyst of breast mimicking carcinoma: A case report and review of literature

PubMed Central

Debnath, Debasish; Taribagil, Savita; Al-Janabi, Khalid J.S.; Inwang, Reggie

2012-01-01

INTRODUCTION Triple assessment of a suspicious breast lesion may not always provide a definite diagnosis. We report a case of epidermoid cyst of breast, which caused diagnostic dilemma in spite of a thorough triple assessment and entailed mastectomy. PRESENTATION OF CASE A 69-year-old woman presented with a large painful retroareolar left breast mass. Clinical examination, ultrasound and mammography were highly suspicious of malignancy. However, core biopsy suggested a benign lesion. Due to size of the lesion and diagnostic uncertainty, various options were discussed with the patient. She opted for a simple mastectomy. The histology confirmed a large epidermoid cyst. DISCUSSION It is rare for an epidermoid cyst to present as such an advanced lesion, mimicking carcinoma. Excision of such a large retroareolar ‘benign’ lesion, however, may sometime entail mastectomy. This is the first reported case of an epidermoid cyst of breast necessitating mastectomy. CONCLUSION Diagnostic dilemma while dealing with a suspected breast cancer is not rare. Involvement of multidisciplinary team as well as patient is important in the decision-making. The report illustrates a rare presentation of a deep seated large epidermoid cyst of breast, which mimicked carcinoma, caused diagnostic confusion and entailed mastectomy. We strongly advocate the option of breast reconstruction in such cases. PMID:22705938

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.

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

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

Pike, Robert; Sechopoulos, Ioannis; Fei, Baowei, E-mail: bfei@emory.edu

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

Flat Epithelial Atypia of the Breast.

PubMed

Collins, Laura C

2009-06-01

Lesions of the breast characterized by enlarged terminal duct lobular units lined by columnar epithelial cells are being encountered increasingly in breast biopsy specimens. Some of these lesions feature cuboidal to columnar epithelial cells in which the lining cells exhibit cytologic atypia. The role of these lesions (recently designated "flat epithelial atypia" [FEA]) in breast tumor progression is still emerging. FEA commonly coexists with well-developed examples of atypical ductal hyperplasia, low-grade ductal carcinoma in situ, lobular neoplasia, and tubular carcinoma. These findings and those of recent genetic studies suggest that FEA is a neoplastic lesion that may represent a precursor to or the earliest morphologic manifestation of ductal carcinoma in situ. Additional studies are needed to better understand the biologic nature and clinical significance of these lesions. Copyright © 2009 Elsevier Inc. All rights reserved.

Molecular breast tomosynthesis with scanning focus multi-pinhole cameras

NASA Astrophysics Data System (ADS)

van Roosmalen, Jarno; Goorden, Marlies C.; Beekman, Freek J.

2016-08-01

Planar molecular breast imaging (MBI) is rapidly gaining in popularity in diagnostic oncology. To add 3D capabilities, we introduce a novel molecular breast tomosynthesis (MBT) scanner concept based on multi-pinhole collimation. In our design, the patient lies prone with the pendant breast lightly compressed between transparent plates. Integrated webcams view the breast through these plates and allow the operator to designate the scan volume (e.g. a whole breast or a suspected region). The breast is then scanned by translating focusing multi-pinhole plates and NaI(Tl) gamma detectors together in a sequence that optimizes count yield from the volume-of-interest. With simulations, we compared MBT with existing planar MBI. In a breast phantom containing different lesions, MBT improved tumour-to-background contrast-to-noise ratio (CNR) over planar MBI by 12% and 111% for 4.0 and 6.0 mm lesions respectively in case of whole breast scanning. For the same lesions, much larger CNR improvements of 92% and 241% over planar MBI were found in a scan that focused on a breast region containing several lesions. MBT resolved 3.0 mm rods in a Derenzo resolution phantom in the transverse plane compared to 2.5 mm rods distinguished by planar MBI. While planar MBI cannot provide depth information, MBT offered 4.0 mm depth resolution. Our simulations indicate that besides offering 3D localization of increased tracer uptake, multi-pinhole MBT can significantly increase tumour-to-background CNR compared to planar MBI. These properties could be promising for better estimating the position, extend and shape of lesions and distinguishing between single and multiple lesions.

Positron emission mammography in the diagnosis of breast cancer. Is maximum PEM uptake value a valuable threshold for malignant breast cancer detection?

PubMed

Müller, F H H; Farahati, J; Müller, A G; Gillman, E; Hentschel, M

2016-01-01

To evaluate the diagnostic value (sensitivity, specificity) of positron emission mammography (PEM) in a single site non-interventional study using the maximum PEM uptake value (PUVmax). In a singlesite, non-interventional study, 108 patients (107 women, 1 man) with a total of 151 suspected lesions were scanned with a PEM Flex Solo II (Naviscan) at 90 min p.i. with 3.5 MBq 18F-FDG per kg of body weight. In this ROI(region of interest)-based analysis, maximum PEM uptake value (PUV) was determined in lesions, tumours (PUVmaxtumour), benign lesions (PUVmaxnormal breast) and also in healthy tissues on the contralateral side (PUVmaxcontralateral breast). These values were compared and contrasted. In addition, the ratios of PUVmaxtumour / PUVmaxcontralateral breast and PUVmaxnormal breast / PUVmaxcontralateral breast were compared. The image data were interpreted independently by two experienced nuclear medicine physicians and compared with histology in cases of suspected carcinoma. Based on a criteria of PUV>1.9, 31 out of 151 lesions in the patient cohort were found to be malignant (21%). A mean PUVmaxtumour of 3.78 ± 2.47 was identified in malignant tumours, while a mean PUVmaxnormal breast of 1.17 ± 0.37 was reported in the glandular tissue of the healthy breast, with the difference being statistically significant (p < 0.001). Similarly, the mean ratio between tumour and healthy glandular tissue in breast cancer patients (3.15 ± 1.58) was found to be significantly higher than the ratio for benign lesions (1.17 ± 0.41, p < 0.001). PEM is capable of differentiating breast tumours from benign lesions with 100% sensitivity along with a high specificity of 96%, when a threshold of PUVmax >1.9 is applied.

The utility of breast cone-beam computed tomography, ultrasound, and digital mammography for detecting malignant breast tumors: A prospective study with 212 patients.

PubMed

He, Ni; Wu, Yao-Pan; Kong, Yanan; Lv, Ning; Huang, Zhi-Mei; Li, Sheng; Wang, Yue; Geng, Zhi-Jun; Wu, Pei-Hong; Wei, Wei-Dong

2016-02-01

Breast cone-beam computed tomography (BCBCT) is a flat-panel detector (FPD)-based X-ray imaging system that provides high-quality images of the breast. The purpose of this study was to investigate the ability to detect breast abnormalities using non-contrast BCBCT and contrast-enhanced BCBCT (BCBCT and CE-BCBCT) compared to ultrasound (US) and digital mammography (MG). A prospective study was performed from May 2012 to August 2014. Ninety-two patients (172 lesions) underwent BCBCT alone, and 120 patients (270 lesions) underwent BCBCT and CE-BCBCT, all the patients underwent US and MG. Cancer diagnosis was confirmed pathologically in 102 patients (110 lesions). BCBCT identified 97 of 110 malignant lesions, whereas 93 malignant lesions were identified using MG and US. The areas under the receiver operating curves (AUCs) for breast cancer diagnosis were 0.861 (BCBCT), 0.856 (US), and 0.829 (MG). CE-BCBCT improved cancer diagnostic sensitivity by 20.3% (78.4-98.7%). The AUC values were 0.869 (CE-BCBCT), 0.846 (BCBCT), 0.834 (US), and 0.782 (MG). In this preliminary study, BCBCT was found to accurately identify malignant breast lesions in a diagnostic setting. CE-BCBCT provided additional information and improved cancer diagnosis in style c or d breasts compared to the use of BCBCT, US, or MG alone. Copyright © 2015. Published by Elsevier Ireland Ltd.

Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis

PubMed Central

Galván-Tejada, Carlos E.; Zanella-Calzada, Laura A.; Galván-Tejada, Jorge I.; Celaya-Padilla, José M.; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L.

2017-01-01

Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions. PMID:28216571

Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis.

PubMed

Galván-Tejada, Carlos E; Zanella-Calzada, Laura A; Galván-Tejada, Jorge I; Celaya-Padilla, José M; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L

2017-02-14

Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions.

Size assessment of breast lesions by means of a computer-aided detection (CAD) system for magnetic resonance mammography.

PubMed

Levrini, G; Sghedoni, R; Mori, C; Botti, A; Vacondio, R; Nitrosi, A; Iori, M; Nicoli, F

2011-10-01

The aim of this study was to investigate the efficacy of a dedicated software tool for automated volume measurement of breast lesions in contrast-enhanced (CE) magnetic resonance mammography (MRM). The size of 52 breast lesions with a known histopathological diagnosis (three benign, 49 malignant) was automatically evaluated using different techniques. The volume of all lesions was measured automatically (AVM) from CE 3D MRM examinations by means of a computer-aided detection (CAD) system and compared with the size estimates based on maximum diameter measurement (MDM) on MRM, ultrasonography (US), mammography and histopathology. Compared with histopathology as the reference method, AVM understimated lesion size by 4% on average. This result was similar to MDM (3% understimation, not significantly different) but significantly better than US and mammographic lesion measurements (24% and 33% size underestimation, respectively). AVM is as accurate as MDM but faster. Both methods are more accurate for size assessment of breast lesions compared with US and mammography.

Breast MRI in nonpalpable breast lesions: a randomized trial with diagnostic and therapeutic outcome - MONET - study.

PubMed

Peters, Nicky H G M; Borel Rinkes, Inne H M; Mali, Willem P T M; van den Bosch, Maurice A A J; Storm, Remmert K; Plaisier, Peter W; de Boer, Erwin; van Overbeeke, Adriaan J; Peeters, Petra H M

2007-11-28

In recent years there has been an increasing interest in MRI as a non-invasive diagnostic modality for the work-up of suspicious breast lesions. The additional value of Breast MRI lies mainly in its capacity to detect multicentric and multifocal disease, to detect invasive components in ductal carcinoma in situ lesions and to depict the tumor in a 3-dimensional image. Breast MRI therefore has the potential to improve the diagnosis and provide better preoperative staging and possibly surgical care in patients with breast cancer. The aim of our study is to assess whether performing contrast enhanced Breast MRI can reduce the number of surgical procedures due to better preoperative staging and whether a subgroup of women with suspicious nonpalpable breast lesions can be identified in which the combination of mammography, ultrasound and state-of-the-art contrast-enhanced Breast MRI can provide a definite diagnosis. The MONET - study (MR mammography Of Nonpalpable BrEast Tumors) is a randomized controlled trial with diagnostic and therapeutic endpoints. We aim to include 500 patients with nonpalpable suspicious breast lesions who are referred for biopsy. With this number of patients, the expected 12% reduction in surgical procedures due to more accurate preoperative staging with Breast MRI can be detected with a high power (90%). The secondary outcome is the positive and negative predictive value of contrast enhanced Breast MRI. If the predictive values are deemed sufficiently close to those for large core biopsy then the latter, invasive, procedure could possibly be avoided in some women. The rationale, study design and the baseline characteristics of the first 100 included patients are described. Study protocol number NCT00302120.

Breast MRI in nonpalpable breast lesions: a randomized trial with diagnostic and therapeutic outcome – MONET – study

PubMed Central

Peters, Nicky HGM; Borel Rinkes, Inne HM; Mali, Willem PTM; van den Bosch, Maurice AAJ; Storm, Remmert K; Plaisier, Peter W; de Boer, Erwin; van Overbeeke, Adriaan J; Peeters, Petra HM

2007-01-01

Background In recent years there has been an increasing interest in MRI as a non-invasive diagnostic modality for the work-up of suspicious breast lesions. The additional value of Breast MRI lies mainly in its capacity to detect multicentric and multifocal disease, to detect invasive components in ductal carcinoma in situ lesions and to depict the tumor in a 3-dimensional image. Breast MRI therefore has the potential to improve the diagnosis and provide better preoperative staging and possibly surgical care in patients with breast cancer. The aim of our study is to assess whether performing contrast enhanced Breast MRI can reduce the number of surgical procedures due to better preoperative staging and whether a subgroup of women with suspicious nonpalpable breast lesions can be identified in which the combination of mammography, ultrasound and state-of-the-art contrast-enhanced Breast MRI can provide a definite diagnosis. Methods/Design The MONET – study (MR mammography Of Nonpalpable BrEast Tumors) is a randomized controlled trial with diagnostic and therapeutic endpoints. We aim to include 500 patients with nonpalpable suspicious breast lesions who are referred for biopsy. With this number of patients, the expected 12% reduction in surgical procedures due to more accurate preoperative staging with Breast MRI can be detected with a high power (90%). The secondary outcome is the positive and negative predictive value of contrast enhanced Breast MRI. If the predictive values are deemed sufficiently close to those for large core biopsy then the latter, invasive, procedure could possibly be avoided in some women. The rationale, study design and the baseline characteristics of the first 100 included patients are described. Trial registration Study protocol number NCT00302120 PMID:18045470

Improved characterization of molecular phenotypes in breast lesions using 18F-FDG PET image homogeneity

NASA Astrophysics Data System (ADS)

Cao, Kunlin; Bhagalia, Roshni; Sood, Anup; Brogi, Edi; Mellinghoff, Ingo K.; Larson, Steven M.

2015-03-01

Positron emission tomography (PET) using uorodeoxyglucose (18F-FDG) is commonly used in the assessment of breast lesions by computing voxel-wise standardized uptake value (SUV) maps. Simple metrics derived from ensemble properties of SUVs within each identified breast lesion are routinely used for disease diagnosis. The maximum SUV within the lesion (SUVmax) is the most popular of these metrics. However these simple metrics are known to be error-prone and are susceptible to image noise. Finding reliable SUV map-based features that correlate to established molecular phenotypes of breast cancer (viz. estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) expression) will enable non-invasive disease management. This study investigated 36 SUV features based on first and second order statistics, local histograms and texture of segmented lesions to predict ER and PR expression in 51 breast cancer patients. True ER and PR expression was obtained via immunohistochemistry (IHC) of tissue samples from each lesion. A supervised learning, adaptive boosting-support vector machine (AdaBoost-SVM), framework was used to select a subset of features to classify breast lesions into distinct phenotypes. Performance of the trained multi-feature classifier was compared against the baseline single-feature SUVmax classifier using receiver operating characteristic (ROC) curves. Results show that texture features encoding local lesion homogeneity extracted from gray-level co-occurrence matrices are the strongest discriminator of lesion ER expression. In particular, classifiers including these features increased prediction accuracy from 0.75 (baseline) to 0.82 and the area under the ROC curve from 0.64 (baseline) to 0.75.

Differential diagnosis of breast masses in South Korean premenopausal women using diffuse optical spectroscopic imaging

NASA Astrophysics Data System (ADS)

Leproux, Anaïs; Kim, You Me; Min, Jun Won; McLaren, Christine E.; Chen, Wen-Pin; O'Sullivan, Thomas D.; Lee, Seung-ha; Chung, Phil-Sang; Tromberg, Bruce J.

2016-07-01

Young patients with dense breasts have a relatively low-positive biopsy rate for breast cancer (˜1 in 7). South Korean women have higher breast density than Westerners. We investigated the benefit of using a functional and metabolic imaging technique, diffuse optical spectroscopic imaging (DOSI), to help the standard of care imaging tools to distinguish benign from malignant lesions in premenopausal Korean women. DOSI uses near-infrared light to measure breast tissue composition by quantifying tissue concentrations of water (ctH2O), bulk lipid (ctLipid), deoxygenated (ctHHb), and oxygenated (ctHbO2) hemoglobin. DOSI spectral signatures specific to abnormal tissue and absent in healthy tissue were also used to form a malignancy index. This study included 19 premenopausal subjects (average age 41±9), corresponding to 11 benign and 10 malignant lesions. Elevated lesion to normal ratio of ctH2O, ctHHb, ctHbO2, total hemoglobin (THb=ctHHb+ctHbO2), and tissue optical index (ctHHb×ctH2O/ctLipid) were observed in the malignant lesions compared to the benign lesions (p<0.02). THb and malignancy index were the two best single predictors of malignancy, with >90% sensitivity and specificity. Malignant lesions showed significantly higher metabolism and perfusion than benign lesions. DOSI spectral features showed high discriminatory power for distinguishing malignant and benign lesions in dense breasts of the Korean population.

Role of multidetector computed tomography in evaluating incidentally detected breast lesions.

PubMed

Moschetta, Marco; Scardapane, Arnaldo; Lorusso, Valentina; Rella, Leonarda; Telegrafo, Michele; Serio, Gabriella; Angelelli, Giuseppe; Ianora, Amato Antonio Stabile

2015-01-01

Computed tomography (CT) does not represent the primary method for the evaluation of breast lesions; however, it can detect breast abnormalities, even when performed for other reasons related to thoracic structures. The aim of this study is to evaluate the potential benefits of 320-row multidetector CT (MDCT) in evaluating and differentiating incidentally detected breast lesions by using vessel probe and 3D analysis software with net enhancement value. Sixty-two breast lesions in 46 patients who underwent 320-row chest CT examination were retrospectively evaluated. CT scans were assessed searching for the presence, location, number, morphological features, and density of breast nodules. Net enhancement was calculated by subtracting precontrast density from the density obtained by postcontrast values. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of CT were calculated for morphological features and net enhancement. Thirty of 62 lesions were found to be malignant at histological examination and 32 were found to be benign. When morphological features were considered, the sensitivity, specificity, accuracy, PPV, and NPV of CT were 87%, 100%, 88%, 100%, and 50%, respectively. Based on net enhancement, CT reached a sensitivity, specificity, accuracy, PPV, and NPV of 100%, 94%, 97%, 94%, and 100%, respectively. MDCT allows to recognize and characterize breast lesions based on morphological features. Net enhancement can be proposed as an additional accurate feature of CT.

[Correlations between apparent diffusion coefficient in diffusion?weighted magnetic resonance imaging and molecular subtypes of invasive breast cancer masses].

PubMed

Shang, Liu-Tong; Yang, Jia-Fei; Lu, Jing; Wang, Ting-Ting; Zhou, Ying; Xing, Xin-Bo; Wang, Xin-Kun; Yang, Shu-Hui; Hu, Ming-Yan

2017-10-20

To study the correlation of apparent diffusion coefficient (ADC) measured by diffusion-weighted magnetic resonance imaging (MRI) with the molecular subtypes and biological prognostic factors of invasive breast cancer masses. Breast MRI data (including dynamic enhanced and diffusion-weighted imaging) were collected from 64 patients with pathologically confirmed invasive breast cancer masses (a total of 69 lesions). The mean ADC values of the lesions were calculated and their correlations were analyzed with the 5 molecular subtypes of invasive breast cancer and the biological prognostic factors including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2 (HER2), and Ki-67 index. The ADC values did not differ significantly among the 5 molecular subtypes of invasive breast cancer masses (P>0.05) or among lesions with different ER, PR, or HER2 status (P>0.05). The mean ADC values were significantly higher in Ki-67-positive lesions than in the negative lesions (P=0.023 and negatively correlated with the expressions of Ki-67 (r=-0.249). ADC value can not be used to identify the molecular subtypes of invasive breast cancer masses or to evaluate the biological prognosis of the lesions, but its correlation with Ki-67 expression may help in prognostic evaluation and guiding clinical therapy of the tumors.

High-Resolution Scintimammography: A Pilot Study

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

Rachel F. Brem; Joelle M. Schoonjans; Douglas A. Kieper

2002-07-01

This study evaluated a novel high-resolution breast-specific gamma camera (HRBGC) for the detection of suggestive breast lesions. Methods: Fifty patients (with 58 breast lesions) for whom a scintimammogram was clinically indicated were prospectively evaluated with a general-purpose gamma camera and a novel HRBGC prototype. The results of conventional and high-resolution nuclear studies were prospectively classified as negative (normal or benign) or positive (suggestive or malignant) by 2 radiologists who were unaware of the mammographic and histologic results. All of the included lesions were confirmed by pathology. Results: There were 30 benign and 28 malignant lesions. The sensitivity for detection ofmore » breast cancer was 64.3% (18/28) with the conventional camera and 78.6% (22/28) with the HRBGC. The specificity with both systems was 93.3% (28/30). For the 18 nonpalpable lesions, sensitivity was 55.5% (10/18) and 72.2% (13/18) with the general-purpose camera and the HRBGC, respectively. For lesions 1 cm, 7 of 15 were detected with the general-purpose camera and 10 of 15 with the HRBGC. Four lesions (median size, 8.5 mm) were detected only with the HRBGC and were missed by the conventional camera. Conclusion: Evaluation of indeterminate breast lesions with an HRBGC results in improved sensitivity for the detection of cancer, with greater improvement shown for nonpalpable and 1-cm lesions.« less

Initial results of the FUSION-X-US prototype combining 3D automated breast ultrasound and digital breast tomosynthesis.

PubMed

Schaefgen, Benedikt; Heil, Joerg; Barr, Richard G; Radicke, Marcus; Harcos, Aba; Gomez, Christina; Stieber, Anne; Hennigs, André; von Au, Alexandra; Spratte, Julia; Rauch, Geraldine; Rom, Joachim; Schütz, Florian; Sohn, Christof; Golatta, Michael

2018-06-01

To determine the feasibility of a prototype device combining 3D-automated breast ultrasound (ABVS) and digital breast tomosynthesis in a single device to detect and characterize breast lesions. In this prospective feasibility study, the FUSION-X-US prototype was used to perform digital breast tomosynthesis and ABVS in 23 patients with an indication for tomosynthesis based on current guidelines after clinical examination and standard imaging. The ABVS and tomosynthesis images of the prototype were interpreted separately by two blinded experts. The study compares the detection and BI-RADS® scores of breast lesions using only the tomosynthesis and ABVS data from the FUSION-X-US prototype to the results of the complete diagnostic workup. Image acquisition and processing by the prototype was fast and accurate, with some limitations in ultrasound coverage and image quality. In the diagnostic workup, 29 solid lesions (23 benign, including three cases with microcalcifications, and six malignant lesions) were identified. Using the prototype, all malignant lesions were detected and classified as malignant or suspicious by both investigators. Solid breast lesions can be localized accurately and fast by the Fusion-X-US system. Technical improvements of the ultrasound image quality and ultrasound coverage are needed to further study this new device. The prototype combines tomosynthesis and automated 3D-ultrasound (ABVS) in one device. It allows accurate detection of malignant lesions, directly correlating tomosynthesis and ABVS data. The diagnostic evaluation of the prototype-acquired data was interpreter-independent. The prototype provides a time-efficient and technically reliable diagnostic procedure. The combination of tomosynthesis and ABVS is a promising diagnostic approach.

Computerized analysis of sonograms for the detection of breast lesions

NASA Astrophysics Data System (ADS)

Drukker, Karen; Giger, Maryellen L.; Horsch, Karla; Vyborny, Carl J.

2002-05-01

With a renewed interest in using non-ionizing radiation for the screening of high risk women, there is a clear role for a computerized detection aid in ultrasound. Thus, we are developing a computerized detection method for the localization of lesions on breast ultrasound images. The computerized detection scheme utilizes two methods. Firstly, a radial gradient index analysis is used to distinguish potential lesions from normal parenchyma. Secondly, an image skewness analysis is performed to identify posterior acoustic shadowing. We analyzed 400 cases (757 images) consisting of complex cysts, solid benign lesions, and malignant lesions. The detection method yielded an overall sensitivity of 95% by image, and 99% by case at a false-positive rate of 0.94 per image. In 51% of all images, only the lesion itself was detected, while in 5% of the images only the shadowing was identified. For malignant lesions these numbers were 37% and 9%, respectively. In summary, we have developed a computer detection method for lesions on ultrasound images of the breast, which may ultimately aid in breast cancer screening.

21 CFR 884.2990 - Breast lesion documentation system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... system is a device for use in producing a surface map of the breast as an aid to document palpable breast... Lesion Documentation System.” See § 884.1(e) for the availability of this guidance document. [68 FR 44415...

Contrast enhanced dual energy spectral mammogram, an emerging addendum in breast imaging.

PubMed

Kariyappa, Kalpana D; Gnanaprakasam, Francis; Anand, Subhapradha; Krishnaswami, Murali; Ramachandran, Madan

2016-11-01

To assess the role of contrast-enhanced dual-energy spectral mammogram (CEDM) as a problem-solving tool in equivocal cases. 44 consenting females with equivocal findings on full-field digital mammogram underwent CEDM. All the images were interpreted by two radiologists independently. Confidence of presence was plotted on a three-point Likert scale and probability of cancer was assigned on Breast Imaging Reporting and Data System scoring. Histopathology was taken as the gold standard. Statistical analyses of all variables were performed. 44 breast lesions were included in the study, among which 77.3% lesions were malignant or precancerous and 22.7% lesions were benign or inconclusive. 20% of lesions were identified only on CEDM. True extent of the lesion was made out in 15.9% of cases, multifocality was established in 9.1% of cases and ductal extension was demonstrated in 6.8% of cases. Statistical significance for CEDM was p-value <0.05. Interobserver kappa value was 0.837. CEDM has a useful role in identifying occult lesions in dense breasts and in triaging lesions. In a mammographically visible lesion, CEDM characterizes the lesion, affirms the finding and better demonstrates response to treatment. Hence, we conclude that CEDM is a useful complementary tool to standard mammogram. Advances in knowledge: CEDM can detect and demonstrate lesions even in dense breasts with the advantage of feasibility of stereotactic biopsy in the same setting. Hence, it has the potential to be a screening modality with need for further studies and validation.

Finding lesion correspondences in different views of automated 3D breast ultrasound

NASA Astrophysics Data System (ADS)

Tan, Tao; Platel, Bram; Hicks, Michael; Mann, Ritse M.; Karssemeijer, Nico

2013-02-01

Screening with automated 3D breast ultrasound (ABUS) is gaining popularity. However, the acquisition of multiple views required to cover an entire breast makes radiologic reading time-consuming. Linking lesions across views can facilitate the reading process. In this paper, we propose a method to automatically predict the position of a lesion in the target ABUS views, given the location of the lesion in a source ABUS view. We combine features describing the lesion location with respect to the nipple, the transducer and the chestwall, with features describing lesion properties such as intensity, spiculation, blobness, contrast and lesion likelihood. By using a grid search strategy, the location of the lesion was predicted in the target view. Our method achieved an error of 15.64 mm+/-16.13 mm. The error is small enough to help locate the lesion with minor additional interaction.

Fibroadenomatoid mastopathy: another distractive breast lesion?

PubMed

Tan, P E; Looi, L M

1991-12-01

Although most anatomical pathologists have encountered breast lesions with the composite histological features of fibroadenoma (FA) and fibrocystic change (FC), referred to as fibroadenomatosis or fibroadenomatoid mastopathy (FAM), little is known about its prevalence or clinico-pathological significance. In a retrospective histological review of 400 consecutive breast lesions, among both East and West Malaysians, coded either as FA or FC in the files of the Department of Pathology, University of Malaya, we found 45 (11.3%) cases of FAM. Typically, FAM lesions showed fibroadenomatoid foci in a background of fibrocystic change. The finding of FAM among lesions coded as FC was higher (18.5%) than among FA (4%). The mean age of patients with FAM (32.1 years) was similar to FC (35.1 years) but significantly older than that of FA (26.1 years). The notion that FA and FC are lesions at two ends of a spectrum of growth disorder of breast related to oestrogen-progesterone interplay, and that FAM occupies a position intermediate between the two, may explain its morphological and age patterns, but remains speculative. It is hoped that increasing awareness of this condition will lead to better understanding of breast pathophysiology. Nevertheless, until its biological nature, histogenesis and malignant potential are more clearly understood, defining FAM as a distinct form of breast disease may not be meaningful to patient management.

Fully automatic lesion segmentation in breast MRI using mean-shift and graph-cuts on a region adjacency graph.

PubMed

McClymont, Darryl; Mehnert, Andrew; Trakic, Adnan; Kennedy, Dominic; Crozier, Stuart

2014-04-01

To present and evaluate a fully automatic method for segmentation (i.e., detection and delineation) of suspicious tissue in breast MRI. The method, based on mean-shift clustering and graph-cuts on a region adjacency graph, was developed and its parameters tuned using multimodal (T1, T2, DCE-MRI) clinical breast MRI data from 35 subjects (training data). It was then tested using two data sets. Test set 1 comprises data for 85 subjects (93 lesions) acquired using the same protocol and scanner system used to acquire the training data. Test set 2 comprises data for eight subjects (nine lesions) acquired using a similar protocol but a different vendor's scanner system. Each lesion was manually delineated in three-dimensions by an experienced breast radiographer to establish segmentation ground truth. The regions of interest identified by the method were compared with the ground truth and the detection and delineation accuracies quantitatively evaluated. One hundred percent of the lesions were detected with a mean of 4.5 ± 1.2 false positives per subject. This false-positive rate is nearly 50% better than previously reported for a fully automatic breast lesion detection system. The median Dice coefficient for Test set 1 was 0.76 (interquartile range, 0.17), and 0.75 (interquartile range, 0.16) for Test set 2. The results demonstrate the efficacy and accuracy of the proposed method as well as its potential for direct application across different MRI systems. It is (to the authors' knowledge) the first fully automatic method for breast lesion detection and delineation in breast MRI.

First International Consensus Conference on lesions of uncertain malignant potential in the breast (B3 lesions).

PubMed

Rageth, Christoph J; O'Flynn, Elizabeth Am; Comstock, Christopher; Kurtz, Claudia; Kubik, Rahel; Madjar, Helmut; Lepori, Domenico; Kampmann, Gert; Mundinger, Alexander; Baege, Astrid; Decker, Thomas; Hosch, Stefanie; Tausch, Christoph; Delaloye, Jean-François; Morris, Elisabeth; Varga, Zsuzsanna

2016-09-01

The purpose of this study is to obtain a consensus for the therapy of B3 lesions. The first International Consensus Conference on lesions of uncertain malignant potential in the breast (B3 lesions) including atypical ductal hyperplasia (ADH), flat epithelial atypia (FEA), classical lobular neoplasia (LN), papillary lesions (PL), benign phyllodes tumors (PT), and radial scars (RS) took place in January 2016 in Zurich, Switzerland organized by the International Breast Ultrasound School and the Swiss Minimally Invasive Breast Biopsy group-a subgroup of the Swiss Society of Senology. Consensus recommendations for the management and follow-up surveillance of these B3 lesions were developed and areas of research priorities were identified. The consensus recommendation for FEA, LN, PL, and RS diagnosed on core needle biopsy or vacuum-assisted biopsy (VAB) is to therapeutically excise the lesion seen on imaging by VAB and no longer by open surgery, with follow-up surveillance imaging for 5 years. The consensus recommendation for ADH and PT is, with some exceptions, therapeutic first-line open surgical excision. Minimally invasive management of selected B3 lesions with therapeutic VAB is acceptable as an alternative to first-line surgical excision.

Characterization of spatiotemporal changes for the classification of dynamic contrast-enhanced magnetic-resonance breast lesions.

PubMed

Milenković, Jana; Hertl, Kristijana; Košir, Andrej; Zibert, Janez; Tasič, Jurij Franc

2013-06-01

The early detection of breast cancer is one of the most important predictors in determining the prognosis for women with malignant tumours. Dynamic contrast-enhanced magnetic-resonance imaging (DCE-MRI) is an important imaging modality for detecting and interpreting the different breast lesions from a time sequence of images and has proved to be a very sensitive modality for breast-cancer diagnosis. However, DCE-MRI exhibits only a moderate specificity, thus leading to a high rate of false positives, resulting in unnecessary biopsies that are stressful and physically painful for the patient and lead to an increase in the cost of treatment. There is a strong medical need for a DCE-MRI computer-aided diagnosis tool that would offer a reliable support to the physician's decision providing a high level of sensitivity and specificity. In our study we investigated the possibility of increasing differentiation between the malignant and the benign lesions with respect to the spatial variation of the temporal enhancements of three parametric maps, i.e., the initial enhancement (IE) map, the post-initial enhancement (PIE) map and the signal enhancement ratio (SER) map, by introducing additional methods along with the grey-level co-occurrence matrix, i.e., a second-order statistical method already applied for quantifying the spatiotemporal variations. We introduced the grey-level run-length matrix and the grey-level difference matrix, representing two additional, second-order statistical methods, and the circular Gabor as a frequency-domain-based method. Each of the additional methods is for the first time applied to the DCE-MRI data to differentiate between the malignant and the benign breast lesions. We applied the least-square minimum-distance classifier (LSMD), logistic regression and least-squares support vector machine (LS-SVM) classifiers on a total of 115 (78 malignant and 37 benign) breast DCE-MRI cases. The performances were evaluated using ten experiments of a ten-fold cross-validation. Our experimental analysis revealed the PIE map, together with the feature subset in which the discriminating ability of the co-occurrence features was increased by adding the newly introduced features, to be the most significant for differentiation between the malignant and the benign lesions. That diagnostic test - the aforementioned combination of parametric map and the feature subset achieved the sensitivity of 0.9193 which is statistically significantly higher compared to other diagnostic tests after ten-experiments of a ten-fold cross-validation and gave a statistically significantly higher specificity of 0.7819 for the fixed 95% sensitivity after the receiver operating characteristic (ROC) curve analysis. Combining the information from all the three parametric maps significantly increased the area under the ROC curve (AUC) of the aforementioned diagnostic test for the LSMD and logistic regression; however, not for the LS-SVM. The LSMD classifier yielded the highest area under the ROC curve when using the combined information, increasing the AUC from 0.9651 to 0.9755. Introducing new features to those of the grey-level co-occurrence matrix significantly increased the differentiation between the malignant and the benign breast lesions, thus resulting in a high sensitivity and improved specificity. Copyright © 2013 Elsevier B.V. All rights reserved.

Evaluation of tumour markers as differential diagnostic tool in patients with suspicion of liver metastases from breast cancer.

PubMed

Liska, Vaclav; Holubec, Lubos; Treska, Vladislav; Vrzalova, Jindra; Skalicky, Tomas; Sutnar, Alan; Kormunda, Stanislav; Bruha, Jan; Vycital, Ondrej; Finek, Jindrich; Pesta, Martin; Pecen, Ladislav; Topolcan, Ondrej

2011-04-01

The liver is the site of breast cancer metastasis in 50% of patients with advanced disease. Tumour markers have been demonstrated as being useful in follow-up of patients with breast cancer, in early detection of recurrence of breast cancer after radical surgical treatments, and in assessing oncologic therapy effect, but no study has been carried out on their usefullness in distinguishing benign liver lesions from breast cancer metastases. The aim of this study was therefore to evaluate the importance of tumour markers carcinoembryonic antigen (CEA), carbohydrate antigen CA19-9 (CA19-9), thymidine kinase (TK), tissue polypeptide antigen (TPA), tissue polypeptide-specific antigen (TPS) and cytokeratin 19 fragment (CYFRA 21-1) in differential diagnosis between benign liver lesions and liver metastases of breast cancer. The study includes 3 groups: 22 patients with liver metastases of breast cancer; 39 patients with benign liver lesions (hemangioma, focal nodular hyperplasia, liver cyst, hepatocellular adenoma); and 21 patients without any liver disease or lesion that were operated on for benign extrahepatic diseases (groin hernia, varices of lower limbs) as a control group. The serum levels of tumour markers were assessed by means of immunoanalytical methods. Preoperative serum levels of CYFRA 21-1, TPA, TPS and CEA were significantly higher in patients with liver metastases of breast cancer in contrast to healthy controls and patients with benign liver lesions (p-value<0.05). Serum levels of CA19-9 and TK were higher in patients with malignancy in comparison with benign liver disease and healthy controls but these differences were not statistically significant. Tumour markers CEA, CYFRA 21-1, TPA and TPS can be recommended as a good tool for differential diagnosis between liver metastases of breast cancer and benign liver lesions.

Variability of non-Gaussian diffusion MRI and intravoxel incoherent motion (IVIM) measurements in the breast.

PubMed

Iima, Mami; Kataoka, Masako; Kanao, Shotaro; Kawai, Makiko; Onishi, Natsuko; Koyasu, Sho; Murata, Katsutoshi; Ohashi, Akane; Sakaguchi, Rena; Togashi, Kaori

2018-01-01

We prospectively examined the variability of non-Gaussian diffusion magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) measurements with different numbers of b-values and excitations in normal breast tissue and breast lesions. Thirteen volunteers and fourteen patients with breast lesions (seven malignant, eight benign; one patient had bilateral lesions) were recruited in this prospective study (approved by the Internal Review Board). Diffusion-weighted MRI was performed with 16 b-values (0-2500 s/mm2 with one number of excitations [NEX]) and five b-values (0-2500 s/mm2, 3 NEX), using a 3T breast MRI. Intravoxel incoherent motion (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm2 [ADC0] and kurtosis [K]) parameters were estimated from IVIM and Kurtosis models using 16 b-values, and synthetic apparent diffusion coefficient (sADC) values were obtained from two key b-values. The variabilities between and within subjects and between different diffusion acquisition methods were estimated. There were no statistical differences in ADC0, K, or sADC values between the different b-values or NEX. A good agreement of diffusion parameters was observed between 16 b-values (one NEX), five b-values (one NEX), and five b-values (three NEX) in normal breast tissue or breast lesions. Insufficient agreement was observed for IVIM parameters. There were no statistical differences in the non-Gaussian diffusion MRI estimated values obtained from a different number of b-values or excitations in normal breast tissue or breast lesions. These data suggest that a limited MRI protocol using a few b-values might be relevant in a clinical setting for the estimation of non-Gaussian diffusion MRI parameters in normal breast tissue and breast lesions.

Variability of non-Gaussian diffusion MRI and intravoxel incoherent motion (IVIM) measurements in the breast

PubMed Central

Kataoka, Masako; Kanao, Shotaro; Kawai, Makiko; Onishi, Natsuko; Koyasu, Sho; Murata, Katsutoshi; Ohashi, Akane; Sakaguchi, Rena; Togashi, Kaori

2018-01-01

We prospectively examined the variability of non-Gaussian diffusion magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) measurements with different numbers of b-values and excitations in normal breast tissue and breast lesions. Thirteen volunteers and fourteen patients with breast lesions (seven malignant, eight benign; one patient had bilateral lesions) were recruited in this prospective study (approved by the Internal Review Board). Diffusion-weighted MRI was performed with 16 b-values (0–2500 s/mm2 with one number of excitations [NEX]) and five b-values (0–2500 s/mm2, 3 NEX), using a 3T breast MRI. Intravoxel incoherent motion (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm2 [ADC0] and kurtosis [K]) parameters were estimated from IVIM and Kurtosis models using 16 b-values, and synthetic apparent diffusion coefficient (sADC) values were obtained from two key b-values. The variabilities between and within subjects and between different diffusion acquisition methods were estimated. There were no statistical differences in ADC0, K, or sADC values between the different b-values or NEX. A good agreement of diffusion parameters was observed between 16 b-values (one NEX), five b-values (one NEX), and five b-values (three NEX) in normal breast tissue or breast lesions. Insufficient agreement was observed for IVIM parameters. There were no statistical differences in the non-Gaussian diffusion MRI estimated values obtained from a different number of b-values or excitations in normal breast tissue or breast lesions. These data suggest that a limited MRI protocol using a few b-values might be relevant in a clinical setting for the estimation of non-Gaussian diffusion MRI parameters in normal breast tissue and breast lesions. PMID:29494639

Does pre-operative breast magnetic resonance imaging in addition to mammography and breast ultrasonography change the operative management of breast carcinoma?

PubMed

Lim, Hye In; Choi, Jae Hyuck; Yang, Jung-Hyun; Han, Boo-Kyung; Lee, Jeong Eon; Lee, Se-Kyung; Kim, Wan Wook; Kim, Sangmin; Kim, Jee Soo; Kim, Jung-Han; Choe, Jun-Ho; Cho, Eun Yoon; Kang, Seok Seon; Shin, Jung Hee; Ko, Eun Young; Kim, Sang Wook; Nam, Seok Jin

2010-01-01

Magnetic resonance imaging (MRI) has been used for the local staging of breast cancer, especially to determine the extent of multiple lesions and to identify occult malignancies. The aim of this study was to evaluate the effect of pre-operative MRI on the surgical treatment of breast cancer. Between January 2006 and May 2007, 535 newly diagnosed breast cancer patients who planned to undergo breast conserving surgery had clinical examinations, bilateral mammography, breast ultrasonography, and breast MRI. The radiologic findings and clinicopathologic data were reviewed retrospectively. Ninety-eight (18.3%) patients had additional lesions, shown as suspicious lesions on breast MRI, but not detected with conventional methods. Eighty-four (15.7%) of these patients had a change in surgical treatment plans based on the MRI results. Forty-seven (8.8%) of the 84 patients had additional malignancies;the other 37 patients (6.9%) had benign lesions. The positive predictive value for MRI-based surgery was 56.0% (47 of 84 patients). During the period of study, the use of pre-operative MRI was increased with time (OR 1.20; 95% CI 1.16-1.23; P < 0.001), but the mastectomy rate did not change significantly (OR 0.98; 95% CI 0.95-1.00; P = 0.059). Multiple factors were analyzed to identify the patients more likely to undergo appropriate and complete surgery based on the additional findings of the pre-operative MRI, but the results were not statistically significant. This research suggests that a pre-operative MRI can potentially lower the rate of incompletely excised malignancies by identifying additional occult cancer prior to surgery and does not lead to an increase in the mastectomy rate; however, because some benign lesions are indistinguishable from suspicious or malignant lesions, excessive surgical procedures are unnecessarily performed in a significant portion of patients. In the future, the criteria for the use of MRI in local staging of breast cancer should be established.

Mucocele-Like Lesions of the Breast: Clinical Outcome and Histological Analysis of 102 Cases

PubMed Central

Meares, Annie L.; Frank, Ryan D.; Degnim, Amy C.; Vierkant, Robert A.; Frost, Marlene H.; Hartmann, Lynn C.; Winham, Stacey J.; Visscher, Daniel W.

2016-01-01

Mucocele-like lesions (MLL) of the breast are characterized by cystic architecture with stromal mucin and frequent atypia, but it is unknown whether they convey long term breast cancer risk. We evaluated 102MLL that were derived from a single institution benign breast disease (BBD) cohort of 13412 women who underwent biopsy from 1967–2001.MLL were histologically characterized by type of lining epithelium, architecture of the lesion, associated atypical hyperplasia (AH) and for incidence of breast cancer (14.8 years median follow-up). A relatively large proportion of MLL (42%) were diagnosed in women >55 years of age AH was significantly more frequent in MML patient compared to the cohort overall (27% vs 5%, p<0.001). Breast cancer has developed in 13 patients with MLL.. This frequency is only slightly higher than population expected rates overall (Standardized incidence ratio (SIR) 2.28, 95% CI 1.21–3.91), and not significantly different from women in the cohort with (non atypical) proliferative breast lesions. Younger women (<45) with MLL had a non-significant increase in risk of cancer compared to the general population (SIR 5.16, 95% CI 1.41–13.23). We conclude MLL is an uncommon breast lesion that is often associated with co-existing AH. However, in women over age 45, MLL do not convey additional risk of breast cancer beyond that associated with the presence of proliferative disease. PMID:26826407

Is the performance of MRI in preoperative staging of breast cancer independent of clinical and histological factors? A subgroup analysis.

PubMed

Carreira Gómez, C; Zamora Romero, J; Gil de Miguel, A; Chiva de Agustín, M; Plana Farrás, M N; Martínez González, J

2015-01-01

To determine whether preoperative breast MRI is more useful in patients according to their breast density, age, menopausal status, and biopsy findings of carcinoma in situ. We retrospectively studied 264 patients treated for breast cancer who had undergone mammography, ultrasonography, and MRI. We compared the size of the tumor on the three techniques and the sensitivity of the techniques for detecting additional lesions both in the overall group and in subgroups of patients classified according to their breast density, age, menopausal status, and histological findings of intraductal carcinoma. The definitive histological diagnosis was used as the gold standard. MRI was the technique that was most concordant with the histological findings for the size of the lesion, and it was also the technique that detected the most additional lesions. With MRI, we observed no differences in lesion size between the overall group and the subgroups in which MRI provided added value. Likewise, we observed no differences in the number of additional lesions detected in the overall group except for multicentric lesions, which was larger in older patients (P=.02). In the subgroup of patients in which MRI provided added value, the sensitivity for bilateral lesions was higher in patients with fatty breasts (P=.04). Multifocal lesions were detected significantly better in premenopausal patients (P=.03). MRI is better than mammography and better than ultrasonography for establishing the size of the tumor and for detecting additional lesions. Our results did not identify any subgroups in which the technique was more useful. Copyright © 2013 SERAM. Published by Elsevier España, S.L.U. All rights reserved.

Diagnostic performance of shear wave elastography of the breast according to scanning orientation.

PubMed

Kim, Solip; Choi, SeonHyeong; Choi, Yoonjung; Kook, Shin-Ho; Park, Hee Jin; Chung, Eun Chul

2014-10-01

To evaluate the influence of the scanning orientation on diagnostic performance measured by the mean elasticity, maximum elasticity, and fat-to-lesion elasticity ratio on ultrasound-based shear wave elastography in differentiating breast cancers from benign lesions. In this study, a total of 260 breast masses from 235 consecutive patients were observed from March 2012 to November 2012. For each lesion, the mean elasticity value, maximum elasticity value, and fat-to-lesion ratio were measured along two orthogonal directions, and all values were compared with pathologic results. There were 59 malignant and 201 benign lesions. Malignant masses showed higher mean elasticity, maximum elasticity, and fat-to-lesion ratio values than benign lesions (P < .0001). The areas under the receiver operating characteristic curves were as follows: average mean elasticity on both views, 0.870; mean elasticity on the transverse view, 0.866; maximum elasticity on both views, 0.865; maximum elasticity on the transverse view, 0.864; mean elasticity on the longitudinal view, 0.849; fat-to-lesion ratio on both views, 0.849; maximum elasticity on the longitudinal view, 0.845; fat-to-lesion ratio on the transverse view, 0.841; and fat-to-lesion ratio on the longitudinal view, 0.814. Intraclass correlation coefficients for agreement between the scanning directions were as follows: mean elasticity, 0.852; maximum elasticity, 0.842; fat-to-lesion ratio, 0.746, for masses; and mean elasticity, 0.392, for anterior mammary fat. Mean elasticity, maximum elasticity, and fat-to-lesion elasticity ratio values were helpful in differentiating benign and malignant breast masses. The scanning orientation did not significantly affect the diagnostic performance of shear wave elastography for breast masses. © 2014 by the American Institute of Ultrasound in Medicine.

Diagnostic features of quantitative comb-push shear elastography for breast lesion differentiation

PubMed Central

Denis, Max; Gregory, Adriana; Mehrmohammadi, Mohammad; Kumar, Viksit; Meixner, Duane; Fazzio, Robert T.; Fatemi, Mostafa

2017-01-01

Background Lesion stiffness measured by shear wave elastography has shown to effectively separate benign from malignant breast masses. The aim of this study was to evaluate different aspects of Comb-push Ultrasound Shear Elastography (CUSE) performance in differentiating breast masses. Methods With written signed informed consent, this HIPAA- compliant, IRB approved prospective study included patients from April 2014 through August 2016 with breast masses identified on conventional imaging. Data from 223 patients (19–85 years, mean 59.93±14.96 years) with 227 suspicious breast masses identifiable by ultrasound (mean size 1.83±2.45cm) were analyzed. CUSE was performed on all patients. Three regions of interest (ROI), 3 mm in diameter each, were selected inside the lesion on the B-mode ultrasound which also appeared in the corresponding shear wave map. Lesion elasticity values were measured in terms of the Young’s modulus. In correlation to pathology results, statistical analyses were performed. Results Pathology revealed 108 lesions as malignant and 115 lesions as benign. Additionally, 4 lesions (BI-RADS 2 and 3) were considered benign and were not biopsied. Average lesion stiffness measured by CUSE resulted in 84.26% sensitivity (91 of 108), 89.92% specificity (107 of 119), 85.6% positive predictive value, 89% negative predictive value and 0.91 area under the curve (P<0.0001). Stiffness maps showed spatial continuity such that maximum and average elasticity did not have significantly different results (P > 0.21). Conclusion CUSE was able to distinguish between benign and malignant breast masses with high sensitivity and specificity. Continuity of stiffness maps allowed for choosing multiple quantification ROIs which covered large areas of lesions and resulted in similar diagnostic performance based on average and maximum elasticity. The overall results of this study, highlights the clinical value of CUSE in differentiation of breast masses based on their stiffness. PMID:28257467

Diagnostic features of quantitative comb-push shear elastography for breast lesion differentiation.

PubMed

Bayat, Mahdi; Denis, Max; Gregory, Adriana; Mehrmohammadi, Mohammad; Kumar, Viksit; Meixner, Duane; Fazzio, Robert T; Fatemi, Mostafa; Alizad, Azra

2017-01-01

Lesion stiffness measured by shear wave elastography has shown to effectively separate benign from malignant breast masses. The aim of this study was to evaluate different aspects of Comb-push Ultrasound Shear Elastography (CUSE) performance in differentiating breast masses. With written signed informed consent, this HIPAA- compliant, IRB approved prospective study included patients from April 2014 through August 2016 with breast masses identified on conventional imaging. Data from 223 patients (19-85 years, mean 59.93±14.96 years) with 227 suspicious breast masses identifiable by ultrasound (mean size 1.83±2.45cm) were analyzed. CUSE was performed on all patients. Three regions of interest (ROI), 3 mm in diameter each, were selected inside the lesion on the B-mode ultrasound which also appeared in the corresponding shear wave map. Lesion elasticity values were measured in terms of the Young's modulus. In correlation to pathology results, statistical analyses were performed. Pathology revealed 108 lesions as malignant and 115 lesions as benign. Additionally, 4 lesions (BI-RADS 2 and 3) were considered benign and were not biopsied. Average lesion stiffness measured by CUSE resulted in 84.26% sensitivity (91 of 108), 89.92% specificity (107 of 119), 85.6% positive predictive value, 89% negative predictive value and 0.91 area under the curve (P<0.0001). Stiffness maps showed spatial continuity such that maximum and average elasticity did not have significantly different results (P > 0.21). CUSE was able to distinguish between benign and malignant breast masses with high sensitivity and specificity. Continuity of stiffness maps allowed for choosing multiple quantification ROIs which covered large areas of lesions and resulted in similar diagnostic performance based on average and maximum elasticity. The overall results of this study, highlights the clinical value of CUSE in differentiation of breast masses based on their stiffness.

Technical Note: Development of a combined molecular breast imaging/ultrasound system for diagnostic evaluation of MBI-detected lesions.

PubMed

O'Connor, Michael K; Morrow, Melissa M; Tran, Thuy; Hruska, Carrie B; Conners, Amy L; Hunt, Katie N

2017-02-01

The purpose of this study was to perform a pilot evaluation of an integrated molecular breast imaging/ultrasound (MBI/US) system designed to enable, in real-time, the registration of US to MBI and diagnostic evaluation of breast lesions detected on MBI. The MBI/US system was constructed by modifying an existing dual-head cadmium zinc telluride (CZT)-based MBI gamma camera. The upper MBI detector head was replaced with a mesh panel, which allowed an ultrasound probe to access the breast. An optical tracking system was used to monitor the location of the ultrasound transducer, referenced to the MBI detector. The lesion depth at which ultrasound was targeted was estimated from analysis of previously acquired dual-head MBI datasets. A software tool was developed to project the US field of view onto the current MBI image. Correlation of lesion location between both modalities with real-time MBI/US scanning was confirmed in a breast phantom model and assessed in 12 patients with a breast lesion detected on MBI. Combined MBI/US scanning allowed for registration of lesions detected on US and MBI as validated in phantom experiments. In patient studies, successful registration was achieved in 8 of 12 (67%) patients, with complete registration achieved in seven and partial registration achieved in one patient. In 4 of 12 (37%) patients, lesion registration was not achieved, partially attributed to uncertainty in lesion depth estimates from MBI. The MBI/US system enabled successful registration of US to MBI in over half of patients studied in this pilot evaluation. Future studies are needed to determine if real-time, registered US imaging of MBI-detected lesions may obviate the need to proceed to more expensive procedures such as contrast-enhanced breast MRI for diagnostic workup or biopsy of MBI findings. © 2016 American Association of Physicists in Medicine.

MR evaluation of breast lesions obtained by diffusion-weighted imaging with background body signal suppression (DWIBS) and correlations with histological findings.

PubMed

Moschetta, Marco; Telegrafo, Michele; Rella, Leonarda; Capolongo, Arcangela; Stabile Ianora, Amato Antonio; Angelelli, Giuseppe

2014-07-01

Diffusion imaging represents a new imaging tool for the diagnosis of breast cancer. This study aims to investigate the role of diffusion-weighted MRI with background body signal suppression (DWIBS) for evaluating breast lesions. 90 patients were prospectively evaluated by MRI with STIR, TSE-T2, contrast enhanced THRIVE-T1 and DWIBS sequences. DWIBS were analyzed searching for the presence of breast lesions and calculating the ADC value. ADC values of ≤1.44×10(-3)mm(2)/s were considered suspicious for malignancy. This analysis was then compared with the histological findings. Sensitivity, specificity, diagnostic accuracy (DA), positive predictive value (PPV) and negative (NPV) were calculated. In 53/90 (59%) patients, DWIBS indicated the presence of breast lesions, 16 (30%) with ADC values of >1.44 and 37 (70%) with ADC≤1.44. The comparison with histology showed 25 malignant and 28 benign lesions. DWIBS sequences obtained sensitivity, specificity, DA, PPV and NPV values of 100, 82, 87, 68 and 100%, respectively. DWIBS can be proposed in the MRI breast protocol representing an accurate diagnostic complement. Copyright © 2014 Elsevier Inc. All rights reserved.

Basal Cell Carcinoma Arising in a Breast Augmentation Scar.

PubMed

Edwards, Lisa R; Cresce, Nicole D; Russell, Mark A

2017-04-01

We report a case of a 46-year-old female who presented with a persistent lesion on the inferior right breast. The lesion was located within the scar from a breast augmentation procedure 12 years ago. The lesion had been treated as several conditions with no improvement. Biopsy revealed a superficial and nodular basal cell carcinoma, and the lesion was successfully removed with Mohs micrographic surgery. Basal cell carcinoma arising in a surgical scar is exceedingly rare with only 13 reported cases to date. This is the first reported case of basal cell carcinoma arising in a breast augmentation scar. We emphasize the importance of biopsy for suspicious lesions or those refractory to treatment, particularly those lesions that form within a scar. 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 .

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

PubMed

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

2015-01-01

Full-field digital mammography (FFDM) with dense breasts has a high rate of missed diagnosis, and digital breast tomosynthesis (DBT) could reduce organization overlapping and provide more reliable images for BI-RADS classification. This study aims to explore application of COMBO (FFDM+DBT) for effect and significance of BI-RADS classification of breast cancer. In this study, we selected 832 patients who had been treated from May 2013 to November 2013. Classify FFDM and COMBO examination according to BI-RADS separately and compare the differences for glands in the image of the same patient in judgment, mass characteristics display and indirect signs. Employ Paired Wilcoxon rank sum test was used in 79 breast cancer patients to find differences between two examine methods. The results indicated that COMBO pattern is able to observe more details in distribution of glands when estimating content. Paired Wilcoxon rank sum test showed that overall classification level of COMBO is higher significantly compared to FFDM to BI-RADS diagnosis and classification of breast (P<0.05). The area under FFDM ROC curve is 0.805, while that is 0.941 in COMBO pattern. COMBO shows relation of mass with the surrounding tissues, the calcification in the mass, and multiple foci clearly in breast cancer tissues. The optimal sensitivity of cut-off value in COMBO pattern is 82.9%, which is higher than that in FFDM (60%). They share the same specificity which is both 93.2%. Digital Breast Tomosynthesis (DBT) could be used for the BI-RADS classification in breast cancer in clinical.

[Diagnostic value of quantitative pharmacokinetic parameters and relative quantitative pharmacokinetic parameters in breast lesions with dynamic contrast-enhanced MRI].

PubMed

Sun, T T; Liu, W H; Zhang, Y Q; Li, L H; Wang, R; Ye, Y Y

2017-08-01

Objective: To explore the differential between the value of dynamic contrast-enhanced MRI quantitative pharmacokinetic parameters and relative pharmacokinetic quantitative parameters in breast lesions. Methods: Retrospective analysis of 255 patients(262 breast lesions) who was obtained by clinical palpation , ultrasound or full-field digital mammography , and then all lessions were pathologically confirmed in Zhongda Hospital, Southeast University from May 2012 to May 2016. A 3.0 T MRI scanner was used to obtain the quantitative MR pharmacokinetic parameters: volume transfer constant (K(trans)), exchange rate constant (k(ep))and extravascular extracellular volume fraction (V(e)). And measured the quantitative pharmacokinetic parameters of normal glands tissues which on the same side of the same level of the lesions; and then calculated the value of relative pharmacokinetic parameters: rK(rans)、rk(ep) and rV(e).To explore the diagnostic value of two pharmacokinetic parameters in differential diagnosis of benign and malignant breast lesions using receiver operating curves and model of logistic regression. Results: (1)There were significant differences between benign lesions and malignant lesions in K(trans) and k(ep) ( t =15.489, 15.022, respectively, P <0.05), there were no significant differences between benign lesions and malignant lesions in V(e)( t =-2.346, P >0.05). The areas under the ROC curve(AUC)of K(trans), k(ep) and V(e) between malignant and benign lesions were 0.933, 0.948 and 0.387, the sensitivity of K(trans), k(ep) and V(e) were 77.1%, 85.0%, 51.0% , and the specificity of K(trans), k(ep) and V(e) were 96.3%, 93.6%, 60.8% for the differential diagnosis of breast lesions if taken the maximum Youden's index as cut-off. (2)There were significant differences between benign lesions and malignant lesions in rK(trans), rk(ep) and rV(e) ( t =14.177, 11.726, 2.477, respectively, P <0.05). The AUC of rK(trans), rk(ep) and rV(e) between malignant and benign lesions were 0.963, 0.903 and 0.575, the sensitivity of rK(trans), rk(ep) and rV(e) were 85.6%, 71.9%, 52.9% , and the specificity of rK(trans), rk(ep) and rV(e) were 94.5%, 92.7%, 60.6% for the differential diagnosis of breast lesions.(3)There was no significant difference in the area under the ROC curve between the predictive probability of quantitative pharmacokinetic parameters and the prediction probability of relative quantitative pharmacokinetic parameters( Z =0.867, P =0.195). Conclusion: There was no significant difference between the quantitative parameter values (K(trans,) k(ep)) and the relative quantitative parameter values (rK(trans,) rk(ep)) in diagnosis of breast lesions, which were important parameters in differential diagnosis of benign and malignant breast lesions.

A Review of Inflammatory Processes of the Breast with a Focus on Diagnosis in Core Biopsy Samples

PubMed Central

D’Alfonso, Timothy M.; Ginter, Paula S.; Shin, Sandra J.

2015-01-01

Inflammatory and reactive lesions of the breast are relatively uncommon among benign breast lesions and can be the source of an abnormality on imaging. Such lesions can simulate a malignant process, based on both clinical and radiographic findings, and core biopsy is often performed to rule out malignancy. Furthermore, some inflammatory processes can mimic carcinoma or other malignancy microscopically, and vice versa. Diagnostic difficulty may arise due to the small and fragmented sample of a core biopsy. This review will focus on the pertinent clinical, radiographic, and histopathologic features of the more commonly encountered inflammatory lesions of the breast that can be characterized in a core biopsy sample. These include fat necrosis, mammary duct ectasia, granulomatous lobular mastitis, diabetic mastopathy, and abscess. The microscopic differential diagnoses for these lesions when seen in a core biopsy sample will be discussed. PMID:26095437

A Review of Inflammatory Processes of the Breast with a Focus on Diagnosis in Core Biopsy Samples.

PubMed

D'Alfonso, Timothy M; Ginter, Paula S; Shin, Sandra J

2015-07-01

Inflammatory and reactive lesions of the breast are relatively uncommon among benign breast lesions and can be the source of an abnormality on imaging. Such lesions can simulate a malignant process, based on both clinical and radiographic findings, and core biopsy is often performed to rule out malignancy. Furthermore, some inflammatory processes can mimic carcinoma or other malignancy microscopically, and vice versa. Diagnostic difficulty may arise due to the small and fragmented sample of a core biopsy. This review will focus on the pertinent clinical, radiographic, and histopathologic features of the more commonly encountered inflammatory lesions of the breast that can be characterized in a core biopsy sample. These include fat necrosis, mammary duct ectasia, granulomatous lobular mastitis, diabetic mastopathy, and abscess. The microscopic differential diagnoses for these lesions when seen in a core biopsy sample will be discussed.

Fibroadenomatosis (fibroadenomatoid mastopathy): a benign breast lesion with composite pathologic features.

PubMed

Hanson, C A; Snover, D C; Dehner, L P

1987-10-01

A benign breast lesion with the composite histologic features of a fibroadenoma and fibrocystic changes has been referred to previously as fibroadenomatosis or fibroadenomatoid mastopathy; this lesion is distinct from the typical well circumscribed fibroadenoma that may have fibrocystic changes. The purpose of our study was to ascertain the frequency of this change among 200 consecutive breast biopsies and excisions with a coded pathologic diagnosis of fibroadenoma and/or "fibrocystic disease"; we identified these changes in 23 (11.5%) specimens. The lesion was characterized by microscopic fibroadenomatoid foci intermingled with dilated ducts, epitheliosis, and adenosis. It is suggested that fibroadenomatosis is yet another pattern in the complex morphologic spectrum known as benign proliferative breast disease. From our experience, this particular lesion was often appreciated as a unique finding, but the appropriate diagnostic designation was in question. The natural history of fibroadenomatosis is essentially unknown. It may represent a morphologic stage in the development of fibroadenoma(s).

Contrast enhanced dual energy spectral mammogram, an emerging addendum in breast imaging

PubMed Central

Gnanaprakasam, Francis; Anand, Subhapradha; Krishnaswami, Murali; Ramachandran, Madan

2016-01-01

Objective: To assess the role of contrast-enhanced dual-energy spectral mammogram (CEDM) as a problem-solving tool in equivocal cases. Methods: 44 consenting females with equivocal findings on full-field digital mammogram underwent CEDM. All the images were interpreted by two radiologists independently. Confidence of presence was plotted on a three-point Likert scale and probability of cancer was assigned on Breast Imaging Reporting and Data System scoring. Histopathology was taken as the gold standard. Statistical analyses of all variables were performed. Results: 44 breast lesions were included in the study, among which 77.3% lesions were malignant or precancerous and 22.7% lesions were benign or inconclusive. 20% of lesions were identified only on CEDM. True extent of the lesion was made out in 15.9% of cases, multifocality was established in 9.1% of cases and ductal extension was demonstrated in 6.8% of cases. Statistical significance for CEDM was p-value <0.05. Interobserver kappa value was 0.837. Conclusion: CEDM has a useful role in identifying occult lesions in dense breasts and in triaging lesions. In a mammographically visible lesion, CEDM characterizes the lesion, affirms the finding and better demonstrates response to treatment. Hence, we conclude that CEDM is a useful complementary tool to standard mammogram. Advances in knowledge: CEDM can detect and demonstrate lesions even in dense breasts with the advantage of feasibility of stereotactic biopsy in the same setting. Hence, it has the potential to be a screening modality with need for further studies and validation. PMID:27610475

PREDICTION OF MALIGNANT BREAST LESIONS FROM MRI FEATURES: A COMPARISON OF ARTIFICIAL NEURAL NETWORK AND LOGISTIC REGRESSION TECHNIQUES

PubMed Central

McLaren, Christine E.; Chen, Wen-Pin; Nie, Ke; Su, Min-Ying

2009-01-01

Rationale and Objectives Dynamic contrast enhanced MRI (DCE-MRI) is a clinical imaging modality for detection and diagnosis of breast lesions. Analytical methods were compared for diagnostic feature selection and performance of lesion classification to differentiate between malignant and benign lesions in patients. Materials and Methods The study included 43 malignant and 28 benign histologically-proven lesions. Eight morphological parameters, ten gray level co-occurrence matrices (GLCM) texture features, and fourteen Laws’ texture features were obtained using automated lesion segmentation and quantitative feature extraction. Artificial neural network (ANN) and logistic regression analysis were compared for selection of the best predictors of malignant lesions among the normalized features. Results Using ANN, the final four selected features were compactness, energy, homogeneity, and Law_LS, with area under the receiver operating characteristic curve (AUC) = 0.82, and accuracy = 0.76. The diagnostic performance of these 4-features computed on the basis of logistic regression yielded AUC = 0.80 (95% CI, 0.688 to 0.905), similar to that of ANN. The analysis also shows that the odds of a malignant lesion decreased by 48% (95% CI, 25% to 92%) for every increase of 1 SD in the Law_LS feature, adjusted for differences in compactness, energy, and homogeneity. Using logistic regression with z-score transformation, a model comprised of compactness, NRL entropy, and gray level sum average was selected, and it had the highest overall accuracy of 0.75 among all models, with AUC = 0.77 (95% CI, 0.660 to 0.880). When logistic modeling of transformations using the Box-Cox method was performed, the most parsimonious model with predictors, compactness and Law_LS, had an AUC of 0.79 (95% CI, 0.672 to 0.898). Conclusion The diagnostic performance of models selected by ANN and logistic regression was similar. The analytic methods were found to be roughly equivalent in terms of predictive ability when a small number of variables were chosen. The robust ANN methodology utilizes a sophisticated non-linear model, while logistic regression analysis provides insightful information to enhance interpretation of the model features. PMID:19409817

Magnetic resonance mammography in comparison with mammography in the discovery of multifocal, multicentric and bilateral lesions of breast cancer.

PubMed

Bakhtavar, Khadijeh; Saran, Maryam; Behzadifar, Masoud; Farsi, Maryam

2017-08-01

Breast cancer is one of the health system problems and important diseases that is rising in developing and advanced countries. This study aimed to determine the difference of Magnetic Resonance Mammography (MRM) findings versus mammography in detecting multifocal, multi-centric and malignant bilateral lesions in patients with known breast cancer in Tehran. This cross-sectional study was conducted in Iran and Tehran among breast cancer patients between January 2015 and February 2016. Patients were included in the study prior to surgery, at the request of a surgeon with the aim of detecting multifocal, multi-centric and bilateral lesions. Demographic information was also collected from patients. The results for quantitative variables were expressed as mean and standard deviations, and for qualitative variables, were expressed as relative and absolute frequency. Chi-square test was used to compare the two methods. SPSS Ver.24 (IBM) software was used to analyze the data. Thirty-nine patients were enrolled in the study. The mean age of patients in this study was 48.46±6.836. In mammography, 13 (33.3%) had Composition C and 26 (66.7%) had Composition D according to the type of Composition. In total, 25 patients (89.3%) had one lesion and 3 patients (10.7%) had more than two lesions. In MRM, all lesions observed were mass (54 masses). The number of lesions found in MRM was 27 patients with one lesion (58.9%), 6 patients with two lesions (20.5%) and 5 patients with three lesions (20.6%). MRM detected more lesions compared to mammography (p<0.0001). The value of Chi-square test with a degree of freedom and error level of 0.05 was 3.71 and p<0.0001 that showed a significant relationship between the number of MRM findings in comparison with mammography. The results of our study showed that two or more lesions and bilateral lesions in MRM were more than mammography in women with B Breast Composition C, D; the findings showed that MRM has a better ability to detect breast masses, and can affect the patient's surgical procedure.

Computerized Analysis of MR and Ultrasound Images of Breast Lesions

DTIC Science & Technology

2001-07-01

Although general rules for the differentiation between benign and malignant mammographically identified breast lesions exist, considerable...round-robin runs yielded A(sub z) values of 0.94 and 0.87 in the task of distinguishing between benign and malignant lesions in the entire database

Computerized Analysis of MR and Ultrasound Images of Breast Lesions

DTIC Science & Technology

2000-07-01

Although general rules for the differentiation between benign and malignant mammographically identified breast lesions exist, considerable...round-robin runs yielded Az values of 0.94 and 0.87 in the task of distinguishing between benign and malignant lesions in the entire database and the

Breast screening: What can the interval cancer review teach us? Are we perhaps being a bit too hard on ourselves?

PubMed

Lekanidi, Katerina; Dilks, Phil; Suaris, Tamara; Kennett, Steffan; Purushothaman, Hema

2017-09-01

The aim of this study was to determine the features that make interval cancers apparent on the preceding screening mammogram and determine whether changes in the ways of performing the interval cancer review will affect the true interval cancer rate. This study was approved by the clinical governance committee. Mammograms of women diagnosed with an interval cancer were included in the study if they had been allocated to either the "suspicious signs" group or "subtle signs" group, during the historic interval cancer review. Three radiologists, individually and blinded to the site of interval cancer, reviewed the mammograms and documented the presence, site, characteristics and classification of any abnormality. Findings were compared with the appearances of the abnormality at the site of subsequent cancer development by a different breast radiologist. The chi-squared test was used in the analysis of the results, seeking associations between recall concordance and cancer mammographic or histological characteristics. 111/590 interval cancers fulfilled the study inclusion criteria. In 17% of the cases none of the readers identified the relevant abnormality on the screening mammogram. 1/3 readers identified the relevant lesion in 22% of the cases, 2/3 readers in 28% of cases and all 3 readers in 33% of cases. The commonest unanimously recalled abnormality was microcalcification and the most challenging mammographic abnormality to detect was asymmetric density. We did not find any statistically significant association between recall concordance and time to interval cancer, position of lesion in the breast, breast density or cancer grade. Even the simple step of performing an independent blinded review of interval cancers reduces the rate of interval cancers classified as missed by up to 39%. Copyright © 2017 Elsevier B.V. All rights reserved.

1H-MRS evaluation of breast lesions by using total choline signal-to-noise ratio as an indicator of malignancy: a meta-analysis.

PubMed

Wang, Xin; Wang, Xiang Jiang; Song, Hui Sheng; Chen, Long Hua

2015-05-01

The aim of this study was to evaluate the diagnostic performance of the use of total choline signal-to-noise ratio (tCho SNR) criteria in MRS studies for benign/malignant discrimination of focal breast lesions. We conducted (1) a meta-analysis based on 10 studies including 480 malignant breast lesions and 312 benign breast lesions and (2) a subgroup meta-analysis of tCho SNR ≥ 2 as cutoff for malignancy based on 7 studies including 371 malignant breast lesions and 239 benign breast lesions. (1) The pooled sensitivity and specificity of proton MRS with tCho SNR were 0.74 (95 % CI 0.69-0.77) and 0.76 (95 % CI 0.71-0.81), respectively. The PLR and NLR were 3.67 (95 % CI 2.30-5.83) and 0.25 (95 % CI 0.14-0.42), respectively. From the fitted SROC, the AUC and Q* index were 0.89 and 0.82. Publication bias was present (t = 2.46, P = 0.039). (2) Meta-regression analysis suggested that neither threshold effect nor evaluated covariates including strength of field, pulse sequence, TR and TE were sources of heterogeneity (all P value >0.05). (3) Subgroup meta-analysis: The pooled sensitivity and specificity were 0.79 and 0.72, respectively. The PLR and NLR were 3.49 and 0.20, respectively. The AUC and Q* index were 0.92 and 0.85. The use of tCho SNR criteria in MRS studies was helpful for differentiation between malignant and benign breast lesions. However, pooled diagnostic measures might be overestimated due to publication bias. A tCho SNR ≥ 2 as cutoff for malignancy resulted in higher diagnostic accuracy.

High-Spatial- and High-Temporal-Resolution Dynamic Contrast-enhanced MR Breast Imaging with Sweep Imaging with Fourier Transformation: A Pilot Study

PubMed Central

Benson, John C.; Idiyatullin, Djaudat; Snyder, Angela L.; Snyder, Carl J.; Hutter, Diane; Everson, Lenore I.; Eberly, Lynn E.; Nelson, Michael T.; Garwood, Michael

2015-01-01

Purpose To report the results of sweep imaging with Fourier transformation (SWIFT) magnetic resonance (MR) imaging for diagnostic breast imaging. Materials and Methods Informed consent was obtained from all participants under one of two institutional review board–approved, HIPAA-compliant protocols. Twelve female patients (age range, 19–54 years; mean age, 41.2 years) and eight normal control subjects (age range, 22–56 years; mean age, 43.2 years) enrolled and completed the study from January 28, 2011, to March 5, 2013. Patients had previous lesions that were Breast Imaging Reporting and Data System 4 and 5 based on mammography and/or ultrasonographic imaging. Contrast-enhanced SWIFT imaging was completed by using a 4-T research MR imaging system. Noncontrast studies were completed in the normal control subjects. One of two sized single-breast SWIFT-compatible transceiver coils was used for nine patients and five controls. Three patients and five control subjects used a SWIFT-compatible dual breast coil. Temporal resolution was 5.9–7.5 seconds. Spatial resolution was 1.00 mm isotropic, with later examinations at 0.67 mm isotropic, and dual breast at 1.00 mm or 0.75 mm isotropic resolution. Results Two nonblinded breast radiologists reported SWIFT image findings of normal breast tissue, benign fibroadenomas (six of six lesions), and malignant lesions (10 of 12 lesions) concordant with other imaging modalities and pathologic reports. Two lesions in two patients were not visualized because of coil field of view. The images yielded by SWIFT showed the presence and extent of known breast lesions. Conclusion The SWIFT technique could become an important addition to breast imaging modalities because it provides high spatial resolution at all points during the dynamic contrast-enhanced examination. © RSNA, 2014 PMID:25247405

Newly Diagnosed Breast Cancer: Comparison of Contrast-enhanced Spectral Mammography and Breast MR Imaging in the Evaluation of Extent of Disease.

PubMed

Lee-Felker, Stephanie A; Tekchandani, Leena; Thomas, Mariam; Gupta, Esha; Andrews-Tang, Denise; Roth, Antoinette; Sayre, James; Rahbar, Guita

2017-11-01

Purpose To compare the diagnostic performances of contrast material-enhanced spectral mammography and breast magnetic resonance (MR) imaging in the detection of index and secondary cancers in women with newly diagnosed breast cancer by using histologic or imaging follow-up as the standard of reference. Materials and Methods This institutional review board-approved, HIPAA-compliant, retrospective study included 52 women who underwent breast MR imaging and contrast-enhanced spectral mammography for newly diagnosed unilateral breast cancer between March 2014 and October 2015. Of those 52 patients, 46 were referred for contrast-enhanced spectral mammography and targeted ultrasonography because they had additional suspicious lesions at MR imaging. In six of the 52 patients, breast cancer had been diagnosed at an outside institution. These patients were referred for contrast-enhanced spectral mammography and targeted US as part of diagnostic imaging. Images from contrast-enhanced spectral mammography were analyzed by two fellowship-trained breast imagers with 2.5 years of experience with contrast-enhanced spectral mammography. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value were calculated for both imaging modalities and compared by using the Bennett statistic. Results Fifty-two women with 120 breast lesions were included for analysis (mean age, 50 years; range, 29-73 years). Contrast-enhanced spectral mammography had similar sensitivity to MR imaging (94% [66 of 70 lesions] vs 99% [69 of 70 lesions]), a significantly higher PPV than MR imaging (93% [66 of 71 lesions] vs 60% [69 of 115 lesions]), and fewer false-positive findings than MR imaging (five vs 45) (P < .001 for all results). In addition, contrast-enhanced spectral mammography depicted 11 of the 11 secondary cancers (100%) and MR imaging depicted 10 (91%). Conclusion Contrast-enhanced spectral mammography is potentially as sensitive as MR imaging in the evaluation of extent of disease in newly diagnosed breast cancer, with a higher PPV. © RSNA, 2017.

A simple and robust classification tree for differentiation between benign and malignant lesions in MR-mammography.

PubMed

Baltzer, Pascal A T; Dietzel, Matthias; Kaiser, Werner A

2013-08-01

In the face of multiple available diagnostic criteria in MR-mammography (MRM), a practical algorithm for lesion classification is needed. Such an algorithm should be as simple as possible and include only important independent lesion features to differentiate benign from malignant lesions. This investigation aimed to develop a simple classification tree for differential diagnosis in MRM. A total of 1,084 lesions in standardised MRM with subsequent histological verification (648 malignant, 436 benign) were investigated. Seventeen lesion criteria were assessed by 2 readers in consensus. Classification analysis was performed using the chi-squared automatic interaction detection (CHAID) method. Results include the probability for malignancy for every descriptor combination in the classification tree. A classification tree incorporating 5 lesion descriptors with a depth of 3 ramifications (1, root sign; 2, delayed enhancement pattern; 3, border, internal enhancement and oedema) was calculated. Of all 1,084 lesions, 262 (40.4 %) and 106 (24.3 %) could be classified as malignant and benign with an accuracy above 95 %, respectively. Overall diagnostic accuracy was 88.4 %. The classification algorithm reduced the number of categorical descriptors from 17 to 5 (29.4 %), resulting in a high classification accuracy. More than one third of all lesions could be classified with accuracy above 95 %. • A practical algorithm has been developed to classify lesions found in MR-mammography. • A simple decision tree consisting of five criteria reaches high accuracy of 88.4 %. • Unique to this approach, each classification is associated with a diagnostic certainty. • Diagnostic certainty of greater than 95 % is achieved in 34 % of all cases.

Spectrum of the Breast Lesions With Increased 18F-FDG Uptake on PET/CT

PubMed Central

Dong, Aisheng; Wang, Yang; Lu, Jianping; Zuo, Changjing

2016-01-01

Abstract Interpretation of 18F-FDG PET/CT studies in breast is challenging owing to nonspecific FDG uptake in various benign and malignant conditions. Benign conditions include breast changes in pregnancy and lactation, gynecomastia, mastitis, fat necrosis, fibroadenoma, intraductal papilloma, and atypical ductal hyperplasia. Among malignancies, invasive ductal carcinoma and invasive lobular carcinoma are common histological types of breast carcinoma. Rarely, other unusual histological types of breast carcinomas (eg, intraductal papillary carcinoma, invasive micropapillary carcinoma, medullary carcinoma, mucinous carcinoma, and metaplastic carcinoma), lymphoma, and metastasis can be the causes. Knowledge of a wide spectrum of hypermetabolic breast lesions on FDG PET/CT is essential in accurate reading of FDG PET/CT. The purpose of this atlas article is to demonstrate features of various breast lesions encountered at our institution, both benign and malignant, which can result in hypermetabolism on FDG PET/CT imaging. PMID:26975010

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

PubMed

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

2018-03-01

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

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.

Positron emission tomography using [18F]fluorotamoxifen to evaluate therapeutic responses in patients with breast cancer: preliminary study.

PubMed

Inoue, T; Kim, E E; Wallace, S; Yang, D J; Wong, F C; Bassa, P; Cherif, A; Delpassand, E; Buzdar, A; Podoloff, D A

1996-08-01

Positron emission tomography (PET) was used to assess the biodistribution and clinical usefulness of [18F]fluorotamoxifen (FTX) in 10 patients with estrogen-receptor(ER)-positive breast tumors. Ten patients with ER-positive breast cancer were prospectively studied, and the consecutive PET imagings (each takes 15 or 20 min) were obtained for 60 or 80 min after the injection of 88.8-392.2 MBq (2.4-10.6 mCi) of [18F]FTX. Twenty three suspected primary or metastatic lesions in 10 patients were evaluated and the tumor uptakes of [18F]FTX in nineteen tumor lesions were correlated to the response of tamoxifen therapy. Three lesions in three patients were considered to be truly negative for breast cancer on the bases of biopsy specimens and/or clinical course. Five (71.4%) of seven patients and 16 (80.0%) of 20 lesions were interpreted to be truly positive for breast cancer. The mean standardized uptake value (SUV) of the radiotracer in tumor was 3.0 on delayed images. There was no significant correlation between the standardized uptake values of [18F]FTX and the ER concentrations in primary lesions. Nineteen tumor lesions in six patients were evaluable to compare the [18F]FTX uptake with responses to tamoxifen therapy after the PET study. Three patients who had a good response to tamoxifen therapy showed positive lesions on PET images, whereas two of three patients who had a poor response showed negative lesions and one showed mixed results. There was no significant difference of [18F]FTX uptake in bone lesions between good and poor responders. However, when bone lesions were excluded, [18F]FTX uptakes in tumors with good responses were significantly higher than those with poor responses (mean and standard deviation of SUV: 2.46 +/- 0.62 vs 1.37 +/- 0.59, P < 0.05). PET imaging using [18F]FTX provides useful information in predicting the effect of tamoxifen therapy in patients with ER-positive breast cancer. Further study is warranted to confirm the clinical utility of PET using [18F]FTX in breast cancer patients.

Expression of Antigen Processing and Presenting Molecules in Brain Metastasis of Breast Cancer

PubMed Central

Liu, Yan; Komohara, Yoshihiro; Domenick, Natalie; Ohno, Masasuke; Ikeura, Maki; Hamilton, Ronald L.; Horbinski, Craig; Wang, Xinhui; Ferrone, Soldano; Okada, Hideho

2012-01-01

Defects in human leukocyte antigen (HLA) class I antigen processing machinery (APM) component expression can have a negative impact on the clinical course of tumors and the response to T-cell-based immunotherapy. Since brain metastases of breast cancer are of increasing clinical significance, the APM component expression levels and CD8+ T-cell infiltration patterns were analyzed in primary breast and metastatic brain lesions of breast cancer by immunohistochemistry. Comparison of unpaired 50 primary and 33 brain metastases showed lower expression of β2-microgloblin, transporter associated with antigen processing (TAP) 1, TAP2 and calnexin in the brain lesions. Although no significant differences were found in APM component scores between primary breast and brain lesions in 15 paired cases, primary breast lesions of which patients eventually developed brain metastases showed lower levels of β2-microgloblin, TAP1 and calnexin compared with breast lesions without known brain metastases. The extent of CD8+ T cell infiltration was significantly higher in the lesions without metastasis compared with the ones with brain metastases, and was positively associated with the expression of TAP1 and calnexin. Furthermore, mouse tumor cells stably transfected with silencing hairpin (sh)RNA for TAP1 demonstrated a decreased susceptibility to cytotoxic T lymphocytes (CTL) in vitro and enhanced spontaneous brain metastasis in vivo. These data support the functional significance of TAP1 expression in tumor cells. Taken together, our data suggest that patients with low or defective TAP1 or calnexin in primary breast cancers may be at higher risks for developing brain metastasis due to the defects in T cell-based immunosurveillance. PMID:22065046

Plasma DNA integrity index as a potential molecular diagnostic marker for breast cancer.

PubMed

Kamel, Azza M; Teama, Salwa; Fawzy, Amal; El Deftar, Mervat

2016-06-01

Plasma DNA integrity index is increased in various malignancies including breast cancer, the most common cancer in women worldwide; early detection is crucial for successful treatment. Current screening methods fail to detect many cases of breast cancer at an early stage. In this study, we evaluated the level of plasma DNA integrity index in 260 females (95 with breast cancer, 95 with benign breast lesions, and 70 healthy controls) to verify its potential value in discriminating malignant from benign breast lesions. The criteria of the American Joint Committee on Cancer were used for staging of breast cancer patients. DNA integrity index was measured by real-time PCR. DNA integrity index was significantly higher in breast cancer than in benign breast patients and healthy subjects (P = <0.001). DNA integrity index is correlated with TNM stage. Given 100 % specificity, the highest sensitivity achieved in detecting cancer group was 85.3 % at 0.55 DNA integrity index cutoff. In conclusion, the plasma DNA integrity index may be a promising molecular diagnostic marker of malignancy in breast lesions.

Targeting Premalignant Lesions: Implications for Early Breast Cancer Detection and Intervention

DTIC Science & Technology

2016-04-01

prostate, lung, colon and pancreas and have been also reported in the premalignant lesions. This peptide could provide us with an opportunity to...including those of the breast, prostate, lung, colon and pancreas and have been also reported in the premalignant lesions (Erez N, et. al Cancer Cell

Role of exponential apparent diffusion coefficient in characterizing breast lesions by 3.0 Tesla diffusion-weighted magnetic resonance imaging

PubMed Central

Kothari, Shweta; Singh, Archana; Das, Utpalendu; Sarkar, Diptendra K; Datta, Chhanda; Hazra, Avijit

2017-01-01

Objective: To evaluate the role of exponential apparent diffusion coefficient (ADC) as a tool for differentiating benign and malignant breast lesions. Patients and Methods: This prospective observational study included 88 breast lesions in 77 patients (between 18 and 85 years of age) who underwent 3T breast magnetic resonance imaging (MRI) including diffusion-weighted imaging (DWI) using b-values of 0 and 800 s/mm2 before biopsy. Mean exponential ADC and ADC of benign and malignant lesions obtained from DWI were compared. Receiver operating characteristics (ROC) curve analysis was undertaken to identify any cut-off for exponential ADC and ADC to predict malignancy. P value of <0.05 was considered statistically significant. Histopathology was taken as the gold standard. Results: According to histopathology, 65 lesions were malignant and 23 were benign. The mean ADC and exponential ADC values of malignant lesions were 0.9526 ± 0.203 × 10−3 mm2/s and 0.4774 ± 0.071, respectively, and for benign lesions were 1.48 ± 0.4903 × 10−3 mm2/s and 0.317 ± 0.1152, respectively. For both the parameters, differences were highly significant (P < 0.001). Cut-off value of ≤0.0011 mm2/s (P < 0.0001) for ADC provided 92.3% sensitivity and 73.9% specificity, whereas with an exponential ADC cut-off value of >0.4 (P < 0.0001) for malignant lesions, 93.9% sensitivity and 82.6% specificity was obtained. The performance of ADC and exponential ADC in distinguishing benign and malignant breast lesions based on respective cut-offs was comparable (P = 0.109). Conclusion: Exponential ADC can be used as a quantitative adjunct tool for characterizing breast lesions with comparable sensitivity and specificity as that of ADC. PMID:28744085

Analysis of routine cytopathologic reports in 1,598 histologically verified benign breast lesions.

PubMed

Pogacnik, A; Us-Krasovec, M

2004-02-01

This retrospective study was designed to evaluate the accuracy of cytopathologic diagnosis and of correct classification of benign breast diseases. A total of 1,598 FNABs were identified to have met the study criteria; of these, 1,258 (78.7%) cases were cytologically benign, 88 (5.5%) suspicious, 3 (0.18%) false-positive, and in 249 (15.6%) cases an inadequate sample was obtained. A specific diagnosis was made in 847/1,258 (67.3%) cases; the other 411 were diagnosed as benign NOS. Out of 847 specific FNABs diagnoses, 451 were fibroadenomas, 27 phyllodes tumors, 289 fibrocystic diseases, 4 proliferative fibrocystic diseases, 38 papillomas, 22 fat necrosis, 9 mastitis, 1 pseudolymphoma, 2 lipomas, 2 duct ecstasies, and 2 atheromas. In our study group the cytopathologic diagnosis of benign breast diseases excluding unsatisfactory aspirates was correct in 93%. Specific diagnosis was correct on average in 50% of cases, only in FA was its accuracy over 60%; in adequately sampled tumor, the predictive value of FA was 86.2%. Copyright 2004 Wiley-Liss, Inc.

Diagnostic efficacy of contrast-enhanced sonography by combined qualitative and quantitative analysis in breast lesions: a comparative study with magnetic resonance imaging.

PubMed

Wang, Lin; Du, Jing; Li, Feng-Hua; Fang, Hua; Hua, Jia; Wan, Cai-Feng

2013-10-01

The purpose of this study was to evaluate the diagnostic efficacy of contrast-enhanced sonography for differentiation of breast lesions by combined qualitative and quantitative analyses in comparison to magnetic resonance imaging (MRI). Fifty-six patients with American College of Radiology Breast Imaging Reporting and Data System category 3 to 5 breast lesions on conventional sonography were evaluated by contrast-enhanced sonography and MRI. A comparative analysis of diagnostic results between contrast-enhanced sonography and MRI was conducted in light of the pathologic findings. Pathologic analysis showed 26 benign and 30 malignant lesions. The predominant enhancement patterns of the benign lesions on contrast-enhanced sonography were homogeneous, centrifugal, and isoenhancement or hypoenhancement, whereas the patterns of the malignant lesions were mainly heterogeneous, centripetal, and hyperenhancement. The detection rates for perfusion defects and peripheral radial vessels in the malignant group were much higher than those in the benign group (P < .05). As to quantitative analysis, statistically significant differences were found in peak and time-to-peak values between the groups (P < .05). With pathologic findings as the reference standard, the sensitivity, specificity, and accuracy of contrast-enhanced sonography and MRI were 90.0%, 92.3%, 91.1% and 96.7%, 88.5%, and 92.9%, respectively. The two methods had a concordant rate of 87.5% (49 of 56), and the concordance test gave a value of κ = 0.75, indicating that there was high concordance in breast lesion assessment between the two diagnostic modalities. Contrast-enhanced sonography provided typical enhancement patterns and valuable quantitative parameters, which showed good agreement with MRI in diagnostic efficacy and may potentially improve characterization of breast lesions.

Characterization of breast lesion using T1-perfusion magnetic resonance imaging: Qualitative vs. quantitative analysis.

PubMed

Thakran, S; Gupta, P K; Kabra, V; Saha, I; Jain, P; Gupta, R K; Singh, A

2018-06-14

The objective of this study was to quantify the hemodynamic parameters using first pass analysis of T 1 -perfusion magnetic resonance imaging (MRI) data of human breast and to compare these parameters with the existing tracer kinetic parameters, semi-quantitative and qualitative T 1 -perfusion analysis in terms of lesion characterization. MRI of the breast was performed in 50 women (mean age, 44±11 [SD] years; range: 26-75) years with a total of 15 benign and 35 malignant breast lesions. After pre-processing, T 1 -perfusion MRI data was analyzed using qualitative approach by two radiologists (visual inspection of the kinetic curve into types I, II or III), semi-quantitative (characterization of kinetic curve types using empirical parameters), generalized-tracer-kinetic-model (tracer kinetic parameters) and first pass analysis (hemodynamic-parameters). Chi-squared test, t-test, one-way analysis-of-variance (ANOVA) using Bonferroni post-hoc test and receiver-operating-characteristic (ROC) curve were used for statistical analysis. All quantitative parameters except leakage volume (Ve), qualitative (type-I and III) and semi-quantitative curves (type-I and III) provided significant differences (P<0.05) between benign and malignant lesions. Kinetic parameters, particularly volume transfer coefficient (K trans ) provided a significant difference (P<0.05) between all grades except grade-II vs III. The hemodynamic parameter (relative-leakage-corrected-breast-blood-volume [rBBVcorr) provided a statistically significant difference (P<0.05) between all grades. It also provided highest sensitivity and specificity among all parameters in differentiation between different grades of malignant breast lesions. Quantitative parameters, particularly rBBVcorr and K trans provided similar sensitivity and specificity in differentiating benign from malignant breast lesions for this cohort. Moreover, rBBVcorr provided better differentiation between different grades of malignant breast lesions among all the parameters. Copyright © 2018. Published by Elsevier Masson SAS.

Clinical application of qualitative assessment for breast masses in shear-wave elastography.

PubMed

Gweon, Hye Mi; Youk, Ji Hyun; Son, Eun Ju; Kim, Jeong-Ah

2013-11-01

To evaluate the interobserver agreement and the diagnostic performance of various qualitative features in shear-wave elastography (SWE) for breast masses. A total of 153 breast lesions in 152 women who underwent B-mode ultrasound and SWE before biopsy were included. Qualitative analysis in SWE was performed using two different classifications: E values (Ecol; 6-point color score, Ehomo; homogeneity score and Esha; shape score) and a four-color pattern classification. Two radiologists reviewed five data sets: B-mode ultrasound, SWE, and combination of both for E values and four-color pattern. The BI-RADS categories were assessed B-mode and combined sets. Interobserver agreement was assessed using weighted κ statistics. Areas under the receiver operating characteristic curve (AUC), sensitivity, and specificity were analyzed. Interobserver agreement was substantial for Ecol (κ=0.79), Ehomo (κ=0.77) and four-color pattern (κ=0.64), and moderate for Esha (κ=0.56). Better-performing qualitative features were Ecol and four-color pattern (AUCs, 0.932 and 0.925) compared with Ehomo and Esha (AUCs, 0.857 and 0.864; P<0.05). The diagnostic performance of B-mode ultrasound (AUC, 0.950) was not significantly different from combined sets with E value and with four color pattern (AUCs, 0.962 and 0.954). When all qualitative values were negative, leading to downgrade the BI-RADS category, the specificity increased significantly from 16.5% to 56.1% (E value) and 57.0% (four-color pattern) (P<0.001) without improvement in sensitivity. The qualitative SWE features were highly reproducible and showed good diagnostic performance in suspicious breast masses. Adding qualitative SWE to B-mode ultrasound increased specificity in decision making for biopsy recommendation. Copyright © 2013 Elsevier Ireland 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.

Intraductal location of the sclerosing adenosis of the breast.

PubMed

Unal, Bulent; Gur, A Serhat; Bhargava, Rohit; Edington, Howard; Ahrendt, Gretchen; Soran, Atilla

2009-01-01

Sclerosing adenosis is a benign breast disease with non-specific images on ultrasound or mammogram. It can mimic infiltrating carcinoma when the above mentioned imaging techniques are used. Herein we present a patient with breast cancer who received neoadjuvant chemotherapy and subsequently underwent mastectomy. Ductoscopy was performed to the mastectomised breast specimen as per the ductoscopy research protocol. Ductoscopy revealed several nodular lesions in the duct with no additional demonstrable intraductal pathology. The lesions were reported as sclerosing adenosis by pathologist. As to our knowledge, this is the first case in literature that demonstrates the use of ductoscopy in diagnosing the sclerosing adenosis in the breast tissue. Ductoscopy and development of ductoscopy guided biopsy techniques may be used as an early diagnostic method for the ductal breast lesions (Fig. 2, Ref. 10). Full Text (Free, PDF) www.bmj.sk.

Ultrasonography of the male breast.

PubMed

Draghi, F; Tarantino, C C; Madonia, L; Ferrozzi, G

2011-09-01

The male breast has been insufficiently explored in the medical literature, particularly that dealing with ultrasonography, although this topic is almost as vast and varied as that of the female breast. The purpose of this article is to provide a schematic review of the most frequent breast lesions encountered in males and their sonographic appearances. After a brief introduction on the anatomy of the male breast, the authors review the non-neoplastic (gynecomastia, pseudogynecomastia, cysts, inflammatory diseases, and Mondor disease) and neoplastic (benign and malignant) lesions encountered in this organ.

Unenhanced breast MRI (STIR, T2-weighted TSE, DWIBS): An accurate and alternative strategy for detecting and differentiating breast lesions.

PubMed

Telegrafo, Michele; Rella, Leonarda; Stabile Ianora, Amato Antonio; Angelelli, Giuseppe; Moschetta, Marco

2015-10-01

To assess the role of STIR, T2-weighted TSE and DWIBS sequences for detecting and characterizing breast lesions and to compare unenhanced (UE)-MRI results with contrast-enhanced (CE)-MRI and histological findings, having the latter as the reference standard. Two hundred eighty consecutive patients (age range, 27-73 years; mean age±standard deviation (SD), 48.8±9.8years) underwent MR examination with a diagnostic protocol including STIR, T2-weighted TSE, THRIVE and DWIBS sequences. Two radiologists blinded to both dynamic sequences and histological findings evaluated in consensus STIR, T2-weighted TSE and DWIBS sequences and after two weeks CE-MRI images searching for breast lesions. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for UE-MRI and CE-MRI were calculated. UE-MRI results were also compared with CE- MRI. UE-MRI sequences obtained sensitivity, specificity, diagnostic accuracy, PPV and NPV values of 94%, 79%, 86%, 79% and 94%, respectively. CE-MRI sequences obtained sensitivity, specificity, diagnostic accuracy, PPV and NPV values of 98%, 83%, 90%, 84% and 98%, respectively. No statistically significant difference between UE-MRI and CE-MRI was found. Breast UE-MRI could represent an accurate diagnostic tool and a valid alternative to CE-MRI for evaluating breast lesions. STIR and DWIBS sequences allow to detect breast lesions while T2-weighted TSE sequences and ADC values could be useful for lesion characterization. Copyright © 2015 Elsevier Inc. All rights reserved.

Comparison of strain and acoustic radiation force impulse elastography of breast lesions by qualitative evaluation.

PubMed

Zhao, Qing; Wang, Xiao-Lei; Sun, Jia-Wei; Jiang, Zhao-Peng; Tao, Lin; Zhou, Xian-Li

2018-04-13

To compare the diagnostic performance of conventional strain elastography (CSE) and acoustic radiation force impulse (ARFI) induced SE for qualitative assessment of breast lesions and evaluate the additional value of the two techniques combined with Breast Imaging Reporting and Data System (BI-RADS) respectively for the differentiation of benign and malignant breast lesions. In a cohort of 110 women, the conventional ultrasound (US) features and the elasticity scores of CSE and ARFI induced SE were recorded. The diagnostic performances of BI-RADS, elastography and BI-RADS plus elastography were evaluated, including the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity and accuracy. Pathologically, there were forty-eight malignant and sixty-two benign breast lesions in the final analysis. The AUCs for CSE and ARFI induced SE are similar (CSE, 0.807; ARFI induced SE, 0.846; p > 0.05), however, the specificity of the latter method was significantly higher than that of CSE (83.9% vs. 58.1%, p = 0.004) in differentiating breast lesions. The accuracy and specificity of BI-RADS plus ARFI induced SE (84.5%, 80.6%, respectively) were significantly higher than BI-RADS alone (73.6%, 54.8%, respectively) and BI-RADS plus conventional SE (72.7%, 56.5%, respectively), respectively (p < 0.05) without loss of sensitivity. Our study showed that BI-RADS plus ARFI induced SE had a better diagnostic performance in the diagnosis of breast lesions in comparison with BI-RADS alone or BI-RADS plus CSE.

Incremental cancer detection using breast ultrasonography versus breast magnetic resonance imaging in the evaluation of newly diagnosed breast cancer patients.

PubMed

He, Hongying; Plaxco, Jeri S; Wei, Wei; Huo, Lei; Candelaria, Rosalind P; Kuerer, Henry M; Yang, Wei T

2016-09-01

To compare the incremental cancer detection rate (ICDR) using bilateral whole-breast ultrasonography (BWBUS) vs dynamic contrast-enhanced MRI in patients with primary breast cancer. A retrospective database search in a single institution identified 259 patients with breast cancer diagnosed from January 2011 to August 2014 who underwent mammography, BWBUS and MRI before surgery. Patient characteristics, tumour characteristics and lesions seen on each imaging modality were recorded. The sensitivity, specificity and accuracy for each modality were calculated. ICDRs according to index tumour histology and receptor status were also evaluated. The effect of additional cancer detection on surgical planning was obtained from the medical records. A total of 266 additional lesions beyond 273 index malignancies were seen on at least 1 modality, of which 121 (45%) lesions were malignant and 145 (55%) lesions were benign. MRI was significantly more sensitive than BWBUS (p = 0.01), while BWBUS was significantly more accurate and specific than MRI (p < 0.0001). Compared with mammography, the ICDRs using BWBUS and MRI were significantly higher for oestrogen receptor-positive and triple-negative cancers, but not for human epidermal growth factor receptor 2-positive cancers. 22 additional malignant lesions in 18 patients were seen on MRI only. Surgical planning remained unchanged in 8 (44%) of those 18 patients. MRI was more sensitive than BWBUS, while BWBUS was more accurate and specific than MRI. MRI-detected additional malignant lesions did not change surgical planning in almost half of these patients. BWBUS may be a cost-effective and practical tool in breast cancer staging.

Value of shear wave arrival time contour display in shear wave elastography for breast masses diagnosis.

PubMed

Zhou, Bang-Guo; Wang, Dan; Ren, Wei-Wei; Li, Xiao-Long; He, Ya-Ping; Liu, Bo-Ji; Wang, Qiao; Chen, Shi-Gao; Alizad, Azra; Xu, Hui-Xiong

2017-08-01

To evaluate the diagnostic performance of shear wave arrival time contour (SWATC) display for the diagnosis of breast lesions and to identify factors associated with the quality of shear wave propagation (QSWP) in breast lesions. This study included 277 pathologically confirmed breast lesions. Conventional B-mode ultrasound characteristics and shear wave elastography parameters were computed. Using the SWATC display, the QSWP of each lesion was assigned to a two-point scale: score 1 (low quality) and score 2 (high quality). Binary logistic regression analysis was performed to identify factors associated with QSWP. The area under the receiver operating characteristic curve (AUROC) for QSWP to differentiate benign from malignant lesions was 0.913, with a sensitivity of 91.9%, a specificity of 90.7%, a positive predictive value (PPV) of 74.0%, and a negative predictive value (NPV) of 97.5%. Compared with using the standard deviation of shear wave speed (SWS SD ) alone, SWS SD combined with QSWP increased the sensitivity from 75.8% to 93.5%, but decreased the specificity from 95.8% to 89.3% (P < 0.05). SWS SD was identified to be the strongest factor associated with the QSWP, followed by tumor malignancy and the depth of the lesion. In conclusion, SWATC display may be useful for characterization of breast lesions.

Sonographically-guided vacuum-assisted biopsy with digital mammography-guided skin marking of suspicious breast microcalcifications: comparison of outcomes with stereotactic biopsy in Asian women.

PubMed

Hahn, Soo Yeon; Shin, Jung Hee; Han, Boo-Kyung; Ko, Eun Young

2011-02-01

Management of suspicious microcalcifications in very thin breasts is problematic. To evaluate whether sonographically-guided vacuum-assisted biopsy (USVAB) with digital mammography-guided skin marking (DM) for the diagnosis of breast microcalcifications is comparable to stereotactic-guided vacuum-assisted biopsy (SVAB) in Asian women with thin breasts. Retrospective review was performed for 263 consecutive suspicious microcalcification lesions in 261 women who underwent USVAB with DM or SVAB using a prone table between January 2004 and December 2007. SVAB was performed for 190 lesions and USVAB for 73 lesions. Biopsy results were correlated with surgical pathology or followed up for at least 12 months. The diagnostic outcomes of SVAB and USVAB to diagnose microcalcifications were compared. Of 263 lesions, 104 (40%) underwent surgery and 159 (60%) were followed up. SVAB and USVAB groups showed similar final categories or the extent of microcalcifications. US visible lesions were 57 (78%) of 73 at USVAB and 14 (10%) of 140 at SVAB. Of 57 US visible lesions at USVAB, 29 (51%) were not found in initial US but were detectable with the help of DM. Specimen radiographs were negative in 2.1% of lesions at SVAB and in 4.1% at USVAB (p=0.4008). The under-estimation rate and false-negative rate were similar in SVAB and USVAB. US with DM facilitates US visibility of microcalcifications. USVAB with DM can produce acceptable biopsy results, as can SVAB, to diagnose breast microcalcifications in patients with thin breasts.

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.

Diffusion weighted imaging reflects variable cellularity and stromal density present in breast fibroadenomas

PubMed Central

Parsian, Sana; Giannakopoulos, Nadia V.; Rahbar, Habib; Rendi, Mara H.; Chai, Xiaoyu

2016-01-01

OBJECTIVE To determine the underlying histopathologic features influencing apparent diffusion coefficient (ADC) values of breast fibroadenomas. MATERIALS AND METHODS Biopsy proven fibroadenomas (n=26) initially identified as suspicious on breast MRI were retrospectively evaluated. Histopathological assessments of lesion cellularity and stromal type were compared with ADC measures on diffusion-weighted MRI. RESULTS Presence of epithelial hyperplasia (increased cellularity) and dense collagenous stroma were both significantly associated with lower lesion ADC values (p=0.02 and 0.004, respectively. CONCLUSION Variations in epithelial cellularity and stromal type influence breast lesion ADC values and may explain the wide range of ADC measures observed in benign fibroadenomas. PMID:27379441

The role of chemoprevention in modifying the risk of breast cancer in women with atypical breast lesions.

PubMed

Coopey, Suzanne B; Mazzola, Emanuele; Buckley, Julliette M; Sharko, John; Belli, Ahmet K; Kim, Elizabeth M H; Polubriaginof, Fernanda; Parmigiani, Giovanni; Garber, Judy E; Smith, Barbara L; Gadd, Michele A; Specht, Michelle C; Guidi, Anthony J; Roche, Constance A; Hughes, Kevin S

2012-12-01

Women with atypical ductal hyperplasia (ADH), atypical lobular hyperplasia (ALH), lobular carcinoma in situ (LCIS), and severe ADH are at increased risk of breast cancer, but a systematic quantification of this risk and the efficacy of chemoprevention in the clinical setting is still lacking. The objective of this study is to evaluate a woman's risk of breast cancer based on atypia type and to determine the effect of chemoprevention in decreasing this risk. Review of 76,333 breast pathology reports from three institutions within Partners Healthcare System, Boston, from 1987 to 2010 using natural language processing was carried out. This approach identified 2,938 women diagnosed with atypical breast lesions. The main outcome of this study is breast cancer occurrence. Of the 2,938 patients with atypical breast lesions, 1,658 were documented to have received no chemoprevention, and 184/1,658 (11.1 %) developed breast cancer at a mean follow-up of 68 months. Estimated 10-year cancer risks were 17.3 % with ADH, 20.7 % with ALH, 23.7 % with LCIS, and 26.0 % with severe ADH. In a subset of patients treated from 1999 on (the chemoprevention era), those who received no chemoprevention had an estimated 10-year breast cancer risk of 21.3 %, whereas those treated with chemoprevention had a 10-year risk of 7.5 % (p < 0.001). Chemoprevention use significantly reduced breast cancer risk for all atypia types (p < 0.05). The risk of breast cancer with atypical breast lesions is substantial. Physicians should counsel patients with ADH, ALH, LCIS, and severe ADH about the benefit of chemoprevention in decreasing their breast cancer risk.

A modified Seeded Region Growing algorithm for vessel segmentation in breast MRI images for investigating the nature of potential lesions

NASA Astrophysics Data System (ADS)

Glotsos, D.; Vassiou, K.; Kostopoulos, S.; Lavdas, El; Kalatzis, I.; Asvestas, P.; Arvanitis, D. L.; Fezoulidis, I. V.; Cavouras, D.

2014-03-01

The role of Magnetic Resonance Imaging (MRI) as an alternative protocol for screening of breast cancer has been intensively investigated during the past decade. Preliminary research results have indicated that gadolinium-agent administrative MRI scans may reveal the nature of breast lesions by analyzing the contrast-agent's uptake time. In this study, we attempt to deduce the same conclusion, however, from a different perspective by investigating, using image processing, the vascular network of the breast at two different time intervals following the administration of gadolinium. Twenty cases obtained from a 3.0-T MRI system (SIGNA HDx; GE Healthcare) were included in the study. A new modification of the Seeded Region Growing (SRG) algorithm was used to segment vessels from surrounding background. Delineated vessels were investigated by means of their topology, morphology and texture. Results have shown that it is possible to estimate the nature of the lesions with approximately 94.4% accuracy, thus, it may be claimed that the breast vascular network does encodes useful, patterned, information, which can be used for characterizing breast lesions.

Speckle tracking and speckle content based composite strain imaging for solid and fluid filled lesions.

PubMed

Rabbi, Md Shifat-E; Hasan, Md Kamrul

2017-02-01

Strain imaging though for solid lesions provides an effective way for determining their pathologic condition by displaying the tissue stiffness contrast, for fluid filled lesions such an imaging is yet an open problem. In this paper, we propose a novel speckle content based strain imaging technique for visualization and classification of fluid filled lesions in elastography after automatic identification of the presence of fluid filled lesions. Speckle content based strain, defined as a function of speckle density based on the relationship between strain and speckle density, gives an indirect strain value for fluid filled lesions. To measure the speckle density of the fluid filled lesions, two new criteria based on oscillation count of the windowed radio frequency signal and local variance of the normalized B-mode image are used. An improved speckle tracking technique is also proposed for strain imaging of the solid lesions and background. A wavelet-based integration technique is then proposed for combining the strain images from these two techniques for visualizing both the solid and fluid filled lesions from a common framework. The final output of our algorithm is a high quality composite strain image which can effectively visualize both solid and fluid filled breast lesions in addition to the speckle content of the fluid filled lesions for their discrimination. The performance of our algorithm is evaluated using the in vivo patient data and compared with recently reported techniques. The results show that both the solid and fluid filled lesions can be better visualized using our technique and the fluid filled lesions can be classified with good accuracy. Copyright © 2016 Elsevier B.V. All rights reserved.

Random forest learning of ultrasonic statistical physics and object spaces for lesion detection in 2D sonomammography

NASA Astrophysics Data System (ADS)

Sheet, Debdoot; Karamalis, Athanasios; Kraft, Silvan; Noël, Peter B.; Vag, Tibor; Sadhu, Anup; Katouzian, Amin; Navab, Nassir; Chatterjee, Jyotirmoy; Ray, Ajoy K.

2013-03-01

Breast cancer is the most common form of cancer in women. Early diagnosis can significantly improve lifeexpectancy and allow different treatment options. Clinicians favor 2D ultrasonography for breast tissue abnormality screening due to high sensitivity and specificity compared to competing technologies. However, inter- and intra-observer variability in visual assessment and reporting of lesions often handicaps its performance. Existing Computer Assisted Diagnosis (CAD) systems though being able to detect solid lesions are often restricted in performance. These restrictions are inability to (1) detect lesion of multiple sizes and shapes, and (2) differentiate between hypo-echoic lesions from their posterior acoustic shadowing. In this work we present a completely automatic system for detection and segmentation of breast lesions in 2D ultrasound images. We employ random forests for learning of tissue specific primal to discriminate breast lesions from surrounding normal tissues. This enables it to detect lesions of multiple shapes and sizes, as well as discriminate between hypo-echoic lesion from associated posterior acoustic shadowing. The primal comprises of (i) multiscale estimated ultrasonic statistical physics and (ii) scale-space characteristics. The random forest learns lesion vs. background primal from a database of 2D ultrasound images with labeled lesions. For segmentation, the posterior probabilities of lesion pixels estimated by the learnt random forest are hard thresholded to provide a random walks segmentation stage with starting seeds. Our method achieves detection with 99.19% accuracy and segmentation with mean contour-to-contour error < 3 pixels on a set of 40 images with 49 lesions.

Radioguided localisation of non-palpable lesions of the breast in Costa Rica: review of results of our first 800 patients in private practice.

PubMed

Aguilar, Marisel; Alfaro, Sabrina; Aguilar, Ricardo

2017-01-01

Surgical treatment of non-palpable breast lesions is controversial. At the European Institute of Oncology in Milan, Italy, Prof Umberto Veronesi introduced a new technique called the radioguided occult lesion localisation (ROLL) in 1996 to replace conventional methods and their disadvantages (Zurrida S, Galimberti V, and Monti S et al (1998) Radioguided localization of occult breast lesions Breast 7 11-13 https://doi.org/10.1016/S0960-9776(98)90044-3). Given the success experienced in that institution, the method became the technique of choice for the early diagnosis of breast cancer. In this paper, we will examine the technical aspects of ROLL and the results from a large series of patients treated in our private practice in Costa Rica. We analysed the first 816 patients with different non-palpable breast lesions detected by ultrasound or mammography within our private practice in Costa Rica. In 774 patients, technetium 99m labelled with human serum albumin (7-10 MBq) in 0.2 ml of saline solution was injected into the lesion under mammographic or ultrasound guidance. The excisional biopsy was done by means of a gamma-probe and complete excision of the lesion was verified by X-ray on the specimen in lesions that were visible by mammography and ultrasound 4 months after surgery. In the remaining 42 patients, the localisation of the lesion was carried out by wire. The tracer was correctly positioned in the first attempt in 772/816 (94.6%) of cases and in the second attempt in two other cases. In 42/816 (5.1%) cases, the localisation of the lesion had to be performed with the traditional method. X-rays showed that the lesion was entirely removed in 770/772 (99.74%) of cases. The ROLL is a simple and excellent option for the removal of hidden breast lesions in clinical practice. It offers the advantage of making resections safer and with tumour-free margins, in addition to reducing the number of reinterventions. Since it makes it possible to specify to the pathologist the exact site where the lesion is located, we can guarantee a better diagnosis. The rate of success with the use of this technique corresponds to the available scientific data, so we conclude that it is a procedure that we can routinely perform in private practice in Costa Rica.

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.

Computer-aided detection of breast lesions in DCE-MRI using region growing based on fuzzy C-means clustering and vesselness filter

NASA Astrophysics Data System (ADS)

B. Shokouhi, Shahriar; Fooladivanda, Aida; Ahmadinejad, Nasrin

2017-12-01

A computer-aided detection (CAD) system is introduced in this paper for detection of breast lesions in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). The proposed CAD system firstly compensates motion artifacts and segments the breast region. Then, the potential lesion voxels are detected and used as the initial seed points for the seeded region-growing algorithm. A new and robust region-growing algorithm incorporating with Fuzzy C-means (FCM) clustering and vesselness filter is proposed to segment any potential lesion regions. Subsequently, the false positive detections are reduced by applying a discrimination step. This is based on 3D morphological characteristics of the potential lesion regions and kinetic features which are fed to the support vector machine (SVM) classifier. The performance of the proposed CAD system is evaluated using the free-response operating characteristic (FROC) curve. We introduce our collected dataset that includes 76 DCE-MRI studies, 63 malignant and 107 benign lesions. The prepared dataset has been used to verify the accuracy of the proposed CAD system. At 5.29 false positives per case, the CAD system accurately detects 94% of the breast lesions.

Upgrade of high-risk breast lesions detected on mammography in the Breast Cancer Surveillance Consortium

PubMed Central

Menes, Tehillah S.; Rosenberg, Robert; Balch, Steven; Jaffer, Shabnam; Kerlikowske, Karla; Miglioretti, Diana L.

2013-01-01

Background Upgrade rates of high-risk breast lesions after screening mammography were examined. Study design The Breast Cancer Surveillance Consortium registry was used to identify all BI-RADS 4 assessments followed by needle biopsies with high-risk lesions. Follow-up was performed for all women. Results High-risk lesions were found in 957 needle biopsies, with excision documented in 53%. Most (N=685) were atypical ductal hyperplasia (ADH), 173 were lobular neoplasia, and 99 were papillary lesions. Upgrade to cancer varied with type of lesion (18% in ADH, 10% in lobular neoplasia and 2% in papillary). In premenopausal women with ADH, upgrade was associated with family history. Cancers associated with ADH were mostly (82%) ductal carcinoma in situ, those associated with lobular neoplasia were mostly (56%) invasive. During further 2 years of follow-up, cancer was documented in 1% of women with follow-up surgery and in 3% with no surgery. Conclusion Despite low rates of surgery, low rates of cancer were documented during follow-up. Benign papillary lesions diagnosed on BI-RADS 4 mammograms among asymptomatic women do not justify surgical excision. PMID:24112677

A new idea for visualization of lesions distribution in mammogram based on CPD registration method.

PubMed

Pan, Xiaoguang; Qi, Buer; Yu, Hongfei; Wei, Haiping; Kang, Yan

2017-07-20

Mammography is currently the most effective technique for breast cancer. Lesions distribution can provide support for clinical diagnosis and epidemiological studies. We presented a new idea to help radiologists study breast lesions distribution conveniently. We also developed an automatic tool based on this idea which could show visualization of lesions distribution in a standard mammogram. Firstly, establishing a lesion database to study; then, extracting breast contours and match different women's mammograms to a standard mammogram; finally, showing the lesion distribution in the standard mammogram, and providing the distribution statistics. The crucial process of developing this tool was matching different women's mammograms correctly. We used a hybrid breast contour extraction method combined with coherent point drift method to match different women's mammograms. We tested our automatic tool by four mass datasets of 641 images. The distribution results shown by the tool were consistent with the results counted according to their reports and mammograms by manual. We also discussed the registration error that was less than 3.3 mm in average distance. The new idea is effective and the automatic tool can provide lesions distribution results which are consistent with radiologists simply and conveniently.

Diffusion-weighted magnetic resonance imaging combined with T2-weighted images in the detection of small breast cancer: a single-center multi-observer study.

PubMed

Wu, Lian-Ming; Chen, Jie; Hu, Jiani; Gu, Hai-Yan; Xu, Jian-Rong; Hua, Jia

2014-02-01

Breast cancer is the most common cancer in women worldwide. However, it remains a difficult diagnosis problem to differentiate between benign and malignant breast lesions, especially in small early breast lesions. To assess the diagnostic value of diffusion-weighted imaging (DWI) combined with T2-weighted imaging (T2WI) for small breast cancer characterization. Fifty-eight patients (65 lesions) with a lesion <2 cm in diameter underwent 3.0 Tesla breast magnetic resonance imaging (MRI) including DWI and histological analysis. Three observers with varying experience levels reviewed MRI. The probability of breast cancer in each lesion on MR images was recorded with a 5-point scale. Areas under the receiver-operating characteristic curve (AUCs) were compared by using the Z test; sensitivity and specificity were determined with the Z test after adjusting for data clustering. AUC of T2WI and DWI (Observer 1, 0.95; Observer 2, 0.91; Observer 3, 0.83) was greater than that of T2WI (Observer 1, 0.80; Observer 2, 0.74; Observer 3, 0.70) for all observers (P < 0.0001 in all comparisons). Sensitivity of T2WI and DWI (Observer 1, 90%; Observer 2, 93%; and Observer 3, 86%) was greater than that of T2WI alone (Observer 1, 76%; Observer 2, 83%; Observer 3, 79%) for all observers (P < 0.0001 in all comparisons). Specificity of T2WI and DWI was greater than that of T2WI alone for observer 1 (89% vs. 72%, P < 0.01) and observer 2 (94% vs. 78%, P < 0.001). DWI combined with T2WI can improve the diagnostic performance of MRI in small breast cancer characterization. It should be considered selectively in the preoperative evaluation of patients with small lesions of the breast.

Evaluation of T1/T2 ratios in a pilot study as a potential biomarker of biopsy: proven benign and malignant breast lesions in correlation with histopathological disease stage.

PubMed

Malikova, Marina A; Tkacz, Jaroslaw N; Slanetz, Priscilla J; Guo, Chao-Yu; Aakil, Adam; Jara, Hernan

2017-08-01

Early breast cancer detection is important for intervention and prognosis. Advances in treatment and outcome require diagnostic tools with highly positive predictive value. To study the potential role of quantitative MRI (qMRI) using T1/T2 ratios to differentiate benign from malignant breast lesions. A cross-sectional study of 69 women with 69 known or suspicious breast lesions were scanned with mixed-turbo spin echo pulse sequence. Patients were grouped according to histopathological assessment of disease stage: untreated malignant tumor, treated malignancy and benign disease. Elevated T1/T2 means were observed for biopsy-proven malignant lesions and for malignant lesions treated prior to qMRI with chemotherapy and/or radiation, as compared with benign lesions. The qMRI-obtained T1/T2 ratios correlated with histopathology. Analysis revealed correlation between elevated T1/T2 ratio and disease stage. This could provide valuable complementary information on tissue properties as an additional diagnostic tool.

Can continuous scans in orthogonal planes improve diagnostic performance of shear wave elastography for breast lesions?

PubMed

Yang, Pan; Peng, Yulan; Zhao, Haina; Luo, Honghao; Jin, Ya; He, Yushuang

2015-01-01

Static shear wave elastography (SWE) is used to detect breast lesions, but slice and plane selections result in discrepancies. To evaluate the intraobserver reproducibility of continuous SWE, and whether quantitative elasticities in orthogonal planes perform better in the differential diagnosis of breast lesions. One hundred and twenty-two breast lesions scheduled for ultrasound-guided biopsy were recruited. Continuous SWE scans were conducted in orthogonal planes separately. Quantitative elasticities and histopathology results were collected. Reproducibility in the same plane and diagnostic performance in different planes were evaluated. The maximum and mean elasticities of the hardest portion, and standard deviation of whole lesion, had high inter-class correlation coefficients (0.87 to 0.95) and large areas under receiver operation characteristic curve (0.887 to 0.899). Without loss of accuracy, sensitivities had increased in orthogonal planes compared with single plane (from 73.17% up to 82.93% at most). Mean elasticity of whole lesion and lesion-to-parenchyma ratio were significantly less reproducible and less accurate. Continuous SWE is highly reproducible for the same observer. The maximum and mean elasticities of the hardest portion and standard deviation of whole lesion are most reliable. Furthermore, the sensitivities of the three parameters are improved in orthogonal planes without loss of accuracies.

Combination of elastography and tissue quantification using the acoustic radiation force impulse (ARFI) technology for differential diagnosis of breast masses.

PubMed

Tozaki, Mitsuhiro; Isobe, Sachiko; Sakamoto, Masaaki

2012-10-01

We evaluated the diagnostic performance of elastography and tissue quantification using acoustic radiation force impulse (ARFI) technology for differential diagnosis of breast masses. There were 161 mass lesions. First, lesion correspondence on ARFI elastographic images to those on the B-mode images was evaluated: no findings on ARFI images (pattern 1), lesions that were bright inside (pattern 2), lesions that were dark inside (pattern 4), lesions that contained both bright and dark areas (pattern 3). In addition, pattern 4 was subdivided into 4a (dark area same as B-mode lesion) and 4b (dark area larger than lesion). Next, shear wave velocity (SWV) was measured using virtual touch tissue quantification. There were 13 pattern 1 lesions and five pattern 2 lesions; all of these lesions were benign, whereas all pattern 4b lesions (n = 43) were malignant. When the value of 3.59 m/s was chosen as the cutoff value, the combination of elastography and tissue quantification showed 91 % (83-91) sensitivity, 93 % (65-70) specificity, and 92 % (148-161) accuracy. The combination of elastography and tissue quantification is thought to be a promising ultrasound technique for differential diagnosis of breast-mass lesions.

ICADx: interpretable computer aided diagnosis of breast masses

NASA Astrophysics Data System (ADS)

Kim, Seong Tae; Lee, Hakmin; Kim, Hak Gu; Ro, Yong Man

2018-02-01

In this study, a novel computer aided diagnosis (CADx) framework is devised to investigate interpretability for classifying breast masses. Recently, a deep learning technology has been successfully applied to medical image analysis including CADx. Existing deep learning based CADx approaches, however, have a limitation in explaining the diagnostic decision. In real clinical practice, clinical decisions could be made with reasonable explanation. So current deep learning approaches in CADx are limited in real world deployment. In this paper, we investigate interpretability in CADx with the proposed interpretable CADx (ICADx) framework. The proposed framework is devised with a generative adversarial network, which consists of interpretable diagnosis network and synthetic lesion generative network to learn the relationship between malignancy and a standardized description (BI-RADS). The lesion generative network and the interpretable diagnosis network compete in an adversarial learning so that the two networks are improved. The effectiveness of the proposed method was validated on public mammogram database. Experimental results showed that the proposed ICADx framework could provide the interpretability of mass as well as mass classification. It was mainly attributed to the fact that the proposed method was effectively trained to find the relationship between malignancy and interpretations via the adversarial learning. These results imply that the proposed ICADx framework could be a promising approach to develop the CADx system.

Model–Free Visualization of Suspicious Lesions in Breast MRI Based on Supervised and Unsupervised Learning

PubMed Central

Twellmann, Thorsten; Meyer-Baese, Anke; Lange, Oliver; Foo, Simon; Nattkemper, Tim W.

2008-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has become an important tool in breast cancer diagnosis, but evaluation of multitemporal 3D image data holds new challenges for human observers. To aid the image analysis process, we apply supervised and unsupervised pattern recognition techniques for computing enhanced visualizations of suspicious lesions in breast MRI data. These techniques represent an important component of future sophisticated computer-aided diagnosis (CAD) systems and support the visual exploration of spatial and temporal features of DCE-MRI data stemming from patients with confirmed lesion diagnosis. By taking into account the heterogeneity of cancerous tissue, these techniques reveal signals with malignant, benign and normal kinetics. They also provide a regional subclassification of pathological breast tissue, which is the basis for pseudo-color presentations of the image data. 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. PMID:19255616

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Magnetic resonance imaging-radioguided occult lesion localization (ROLL) in breast cancer using Tc-99m macro-aggregated albumin and distilled water control.

PubMed

Philadelpho Arantes Pereira, Fernanda; Martins, Gabriela; Gregorio Calas, Maria Julia; Fonseca Torres de Oliveira, Maria Veronica; Gasparetto, Emerson Leandro; Barbosa da Fonseca, Lea Mirian

2013-09-18

Magnetic resonance imaging (MRI) guided wire localization presents several challenges apart from the technical difficulties. An alternative to this conventional localization method using a wire is the radio-guided occult lesion localization (ROLL), more related to safe surgical margins and reductions in excision volume. The purpose of this study was to establish a safe and reliable magnetic resonance imaging-radioguided occult lesion localization (MRI-ROLL) technique and to report our initial experience with the localization of nonpalpable breast lesions only observed on MRI. Sixteen women (mean age 53.2 years) with 17 occult breast lesions underwent radio-guided localization in a 1.5-T MR system using a grid-localizing system. All patients had a diagnostic MRI performed prior to the procedure. An intralesional injection of Technetium-99m macro-aggregated albumin followed by distilled water was performed. After the procedure, scintigraphy was obtained. Surgical resection was performed with the help of a gamma detector probe. The lesion histopathology and imaging concordance; the procedure's positive predictive value (PPV), duration time, complications, and accuracy; and the rate of exactly excised lesions evaluated with MRI six months after the surgery were assessed. One lesion in one patient had to be excluded because the radioactive substance came back after the injection, requiring a wire placement. Of the remaining cases, there were four malignant lesions, nine benign lesions, and three high-risk lesions. Surgical histopathology and imaging findings were considered concordant in all benign and high-risk cases. The PPV of MRI-ROLL was greater if the indication for the initial MR examination was active breast cancer. The median procedure duration time was 26 minutes, and all included procedures were defined as accurate. The exact and complete lesion removal was confirmed in all (100%) patients who underwent six-month postoperative MRI (50%). MRI-ROLL offers a precise, technically feasible, safe, and rapid means for performing preoperative MRI localizations in the breast.

Computerized detection of breast lesions in multi-centre and multi-instrument DCE-MR data using 3D principal component maps and template matching

NASA Astrophysics Data System (ADS)

Ertas, Gokhan; Doran, Simon; Leach, Martin O.

2011-12-01

In this study, we introduce a novel, robust and accurate computerized algorithm based on volumetric principal component maps and template matching that facilitates lesion detection on dynamic contrast-enhanced MR. The study dataset comprises 24 204 contrast-enhanced breast MR images corresponding to 4034 axial slices from 47 women in the UK multi-centre study of MRI screening for breast cancer and categorized as high risk. The scans analysed here were performed on six different models of scanner from three commercial vendors, sited in 13 clinics around the UK. 1952 slices from this dataset, containing 15 benign and 13 malignant lesions, were used for training. The remaining 2082 slices, with 14 benign and 12 malignant lesions, were used for test purposes. To prevent false positives being detected from other tissues and regions of the body, breast volumes are segmented from pre-contrast images using a fast semi-automated algorithm. Principal component analysis is applied to the centred intensity vectors formed from the dynamic contrast-enhanced T1-weighted images of the segmented breasts, followed by automatic thresholding to eliminate fatty tissues and slowly enhancing normal parenchyma and a convolution and filtering process to minimize artefacts from moderately enhanced normal parenchyma and blood vessels. Finally, suspicious lesions are identified through a volumetric sixfold neighbourhood connectivity search and calculation of two morphological features: volume and volumetric eccentricity, to exclude highly enhanced blood vessels, nipples and normal parenchyma and to localize lesions. This provides satisfactory lesion localization. For a detection sensitivity of 100%, the overall false-positive detection rate of the system is 1.02/lesion, 1.17/case and 0.08/slice, comparing favourably with previous studies. This approach may facilitate detection of lesions in multi-centre and multi-instrument dynamic contrast-enhanced breast MR data.

Objective breast tissue image classification using Quantitative Transmission ultrasound tomography

NASA Astrophysics Data System (ADS)

Malik, Bilal; Klock, John; Wiskin, James; Lenox, Mark

2016-12-01

Quantitative Transmission Ultrasound (QT) is a powerful and emerging imaging paradigm which has the potential to perform true three-dimensional image reconstruction of biological tissue. Breast imaging is an important application of QT and allows non-invasive, non-ionizing imaging of whole breasts in vivo. Here, we report the first demonstration of breast tissue image classification in QT imaging. We systematically assess the ability of the QT images’ features to differentiate between normal breast tissue types. The three QT features were used in Support Vector Machines (SVM) classifiers, and classification of breast tissue as either skin, fat, glands, ducts or connective tissue was demonstrated with an overall accuracy of greater than 90%. Finally, the classifier was validated on whole breast image volumes to provide a color-coded breast tissue volume. This study serves as a first step towards a computer-aided detection/diagnosis platform for QT.

Design, Implementation, and Characterization of a Dedicated Breast Computed Mammotomography System for Enhanced Lesion Imaging

DTIC Science & Technology

2006-03-01

Evaluation of fully 3D emission mammotomography with a compact cadmium zinc telluride detector,” IEEE Trans. Med. Imag. (Submitted) 2005. [16] M.P...times over a few months, and the degradation due to compromised adipose tissue boundaries as well as other physical breast features are becoming...breast lesions, especially in radiographically dense breasts,2,11-13 through the removal of contrast-reducing overlying tissue ; (2) uncompressed

The p27Kip1 Tumor Suppressor and Multi-Step Tumorigenesis

DTIC Science & Technology

2001-08-01

Breast Cancer , Cell cycle, tumor suppressor 33 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20...in many cancers , including carcinomas of the breast , colon, lung and prostate, and lymphoma. Although these studies of p27 expression in primary...of DMBA-induced pituitary tumors in p27-/- mice precluded determination of breast cancer risk in these mice. Nevertheless, the extensive mammary tissue

Neutrosophic segmentation of breast lesions for dedicated breast CT

NASA Astrophysics Data System (ADS)

Lee, Juhun; Nishikawa, Robert M.; Reiser, Ingrid; Boone, John M.

2017-03-01

We proposed the neutrosophic approach for segmenting breast lesions in breast Computer Tomography (bCT) images. The neutrosophic set (NS) considers the nature and properties of neutrality (or indeterminacy), which is neither true nor false. We considered the image noise as an indeterminate component, while treating the breast lesion and other breast areas as true and false components. We first transformed the image into the NS domain. Each voxel in the image can be described as its membership in True, Indeterminate, and False sets. Operations α-mean, β-enhancement, and γ-plateau iteratively smooth and contrast-enhance the image to reduce the noise level of the true set. Once the true image no longer changes, we applied one existing algorithm for bCT images, the RGI segmentation, on the resulting image to segment the breast lesions. We compared the segmentation performance of the proposed method (named as NS-RGI) to that of the regular RGI segmentation. We used a total of 122 breast lesions (44 benign, 78 malignant) of 123 non-contrasted bCT cases. We measured the segmentation performances of the NS-RGI and the RGI using the DICE coefficient. The average DICE value of the NS-RGI was 0.82 (STD: 0.09), while that of the RGI was 0.8 (STD: 0.12). The difference between the two DICE values was statistically significant (paired t test, p-value = 0.0007). We conducted a subsequent feature analysis on the resulting segmentations. The classifier performance for the NS-RGI (AUC = 0.8) improved over that of the RGI (AUC = 0.69, p-value = 0.006).

Preoperative MRI and surgical management in patients with nonpalpable breast cancer: the MONET - randomised controlled trial.

PubMed

Peters, N H G M; van Esser, S; van den Bosch, M A A J; Storm, R K; Plaisier, P W; van Dalen, T; Diepstraten, S C E; Weits, T; Westenend, P J; Stapper, G; Fernandez-Gallardo, M A; Borel Rinkes, I H M; van Hillegersberg, R; Mali, W P Th M; Peeters, P H M

2011-04-01

We evaluated whether performing contrast-enhanced breast MRI in addition to mammography and/or ultrasound in patients with nonpalpable suspicious breast lesions improves breast cancer management. The MONET - study (MR mammography of nonpalpable breast tumours) is a randomised controlled trial in patients with a nonpalpable BIRADS 3-5 lesion. Patients were randomly assigned to receive routine medical care, including mammography, ultrasound and lesion sampling by large core needle biopsy or additional MRI preceding biopsy. Patients with cancer were referred for surgery. Primary end-point was the rate of additional surgical procedures (re-excisions and conversion to mastectomy) in patients with a nonpalpable breast cancer. Four hundred and eighteen patients were randomised, 207 patients were allocated to MRI, and 211 patients to the control group. In the MRI group 74 patients had 83 malignant lesions, compared to 75 patients with 80 malignant lesions in the control group. The primary breast conserving surgery (BCS) rate was similar in both groups; 68% in the MRI group versus 66% in the control group. The number of re-excisions performed because of positive resection margins after primary BCS was increased in the MRI group; 18/53 (34%) patients in the MRI group versus 6/50 (12%) in the control group (p=0.008). The number of conversions to mastectomy did not differ significantly between groups. Overall, the rate of an additional surgical intervention (BCS and mastectomy combined) after initial breast conserving surgery was 24/53 (45%) in the MRI group versus 14/50 (28%) in the control group (p=0.069). Addition of MRI to routine clinical care in patients with nonpalpable breast cancer was paradoxically associated with an increased re-excision rate. Breast MRI should not be used routinely for preoperative work-up of patients with nonpalpable breast cancer. Copyright © 2010 Elsevier Ltd. All rights reserved.

Application of Eshelby's Solution to Elastography for Diagnosis of Breast Cancer.

PubMed

Shin, Bonghun; Gopaul, Darindra; Fienberg, Samantha; Kwon, Hyock Ju

2016-03-01

Eshelby's solution is the analytical method that can derive the elastic field within and around an ellipsoidal inclusion embedded in a matrix. Since breast tumor can be regarded as an elastic inclusion with different elastic properties from those of surrounding matrix when the deformation is small, we applied Eshelby's solution to predict the stress and strain fields in the breast containing a suspicious lesion. The results were used to investigate the effectiveness of strain ratio (SR) from elastography in representing modulus ratio (MR) that may be the meaningful indicator of the malignancy of the lesion. This study showed that SR significantly underestimates MR and is varied with the shape and the modulus of the lesion. Based on the results from Eshelby's solution and finite element analysis (FEA), we proposed a surface regression model as a polynomial function that can predict the MR of the lesion to the matrix. The model has been applied to gelatin-based phantoms and clinical ultrasound images of human breasts containing different types of lesions. The results suggest the potential of the proposed method to improve the diagnostic performance of breast cancer using elastography. © The Author(s) 2015.

Ideal-observer analysis of lesion detectability in planar, conventional SPECT, and dedicated SPECT scintimammography using effective multi-dimensional smoothing

NASA Astrophysics Data System (ADS)

La Riviere, P. J.; Pan, X.; Penney, B. C.

1998-06-01

Scintimammography, a nuclear-medicine imaging technique that relies on the preferential uptake of Tc-99m-sestamibi and other radionuclides in breast malignancies, has the potential to provide differentiation of mammographically suspicious lesions, as well as outright detection of malignancies in women with radiographically dense breasts. In this work we use the ideal-observer framework to quantify the detectability of a 1-cm lesion using three different imaging geometries: the planar technique that is the current clinical standard, conventional single-photon emission computed tomography (SPECT), in which the scintillation cameras rotate around the entire torso, and dedicated breast SPECT, in which the cameras rotate around the breast alone. We also introduce an adaptive smoothing technique for the processing of planar images and of sinograms that exploits Fourier transforms to achieve effective multidimensional smoothing at a reasonable computational cost. For the detection of a 1-cm lesion with a clinically typical 6:1 tumor-background ratio, we find ideal-observer signal-to-noise ratios (SNR) that suggest that the dedicated breast SPECT geometry is the most effective of the three, and that the adaptive, two-dimensional smoothing technique should enhance lesion detectability in the tomographic reconstructions.

Reducing breast biopsies by ultrasonographic analysis and a modified self-organizing map

NASA Astrophysics Data System (ADS)

Zheng, Yi; Greenleaf, James F.; Gisvold, John J.

1997-05-01

Recent studies suggest that visual evaluation of ultrasound images could decrease negative biopsies of breast cancer diagnosis. However, visual evaluation requires highly experienced breast sonographers. The objective of this study is to develop computerized radiologist assistant to reduce breast biopsies needed for evaluating suspected breast cancer. The approach of this study utilizes a neural network and tissue features extracted from digital sonographic breast images. The features include texture parameters of breast images: characteristics of echoes within and around breast lesions, and geometrical information of breast tumors. Clusters containing only benign lesions in the feature space are then identified by a modified self- organizing map. This newly developed neural network objectively segments population distributions of lesions and accurately establishes benign and equivocal regions.t eh method was applied to high quality breast sonograms of a large number of patients collected with a controlled procedure at Mayo Clinic. The study showed that the number of biopsies in this group of women could be decreased by 40 percent to 59 percent with high confidence and that no malignancies would have been included in the nonbiopsied group. The advantages of this approach are that it is robust, simple, and effective and does not require highly experienced sonographers.

Color-coded automated signal intensity curves for detection and characterization of breast lesions: preliminary evaluation of a new software package for integrated magnetic resonance-based breast imaging.

PubMed

Pediconi, Federica; Catalano, Carlo; Venditti, Fiammetta; Ercolani, Mauro; Carotenuto, Luigi; Padula, Simona; Moriconi, Enrica; Roselli, Antonella; Giacomelli, Laura; Kirchin, Miles A; Passariello, Roberto

2005-07-01

The objective of this study was to evaluate the value of a color-coded automated signal intensity curve software package for contrast-enhanced magnetic resonance mammography (CE-MRM) in patients with suspected breast cancer. Thirty-six women with suspected breast cancer based on mammographic and sonographic examinations were preoperatively evaluated on CE-MRM. CE-MRM was performed on a 1.5-T magnet using a 2D Flash dynamic T1-weighted sequence. A dosage of 0.1 mmol/kg of Gd-BOPTA was administered at a flow rate of 2 mL/s followed by 10 mL of saline. Images were analyzed with the new software package and separately with a standard display method. Statistical comparison was performed of the confidence for lesion detection and characterization with the 2 methods and of the diagnostic accuracy for characterization compared with histopathologic findings. At pathology, 54 malignant lesions and 14 benign lesions were evaluated. All 68 (100%) lesions were detected with both methods and good correlation with histopathologic specimens was obtained. Confidence for both detection and characterization was significantly (P < or = 0.025) better with the color-coded method, although no difference (P > 0.05) between the methods was noted in terms of the sensitivity, specificity, and overall accuracy for lesion characterization. Excellent agreement between the 2 methods was noted for both the determination of lesion size (kappa = 0.77) and determination of SI/T curves (kappa = 0.85). The novel color-coded signal intensity curve software allows lesions to be visualized as false color maps that correspond to conventional signal intensity time curves. Detection and characterization of breast lesions with this method is quick and easily interpretable.

Parametric imaging using subharmonic signals from ultrasound contrast agents in patients with breast lesions.

PubMed

Eisenbrey, John R; Dave, Jaydev K; Merton, Daniel A; Palazzo, Juan P; Hall, Anne L; Forsberg, Flemming

2011-01-01

Parametric maps showing perfusion of contrast media can be useful tools for characterizing lesions in breast tissue. In this study we show the feasibility of parametric subharmonic imaging (SHI), which allows imaging of a vascular marker (the ultrasound contrast agent) while providing near complete tissue suppression. Digital SHI clips of 16 breast lesions from 14 women were acquired. Patients were scanned using a modified LOGIQ 9 scanner (GE Healthcare, Waukesha, WI) transmitting/receiving at 4.4/2.2 MHz. Using motion-compensated cumulative maximum intensity (CMI) sequences, parametric maps were generated for each lesion showing the time to peak (TTP), estimated perfusion (EP), and area under the time-intensity curve (AUC). Findings were grouped and compared according to biopsy results as benign lesions (n = 12, including 5 fibroadenomas and 3 cysts) and carcinomas (n = 4). For each lesion CMI, TTP, EP, and AUC parametric images were generated. No significant variations were detected with CMI (P = .80), TTP (P = .35), or AUC (P = .65). A statistically significant variation was detected for the average pixel EP (P = .002). Especially, differences were seen between carcinoma and benign lesions (mean ± SD, 0.10 ± 0.03 versus 0.05 ± 0.02 intensity units [IU]/s; P = .0014) and between carcinoma and fibroadenoma (0.10 ± 0.03 versus 0.04 ± 0.01 IU/s; P = .0044), whereas differences between carcinomas and cysts were found to be nonsignificant. In conclusion, a parametric imaging method for characterization of breast lesions using the high contrast to tissue signal provided by SHI has been developed. While the preliminary sample size was limited, results show potential for breast lesion characterization based on perfusion flow parameters.

Overdiagnosis and overtreatment of breast cancer.

PubMed

Alvarado, Michael; Ozanne, Elissa; Esserman, Laura

2012-01-01

Breast cancer is the most common cancer in women. Through greater awareness, mammographic screening, and aggressive biopsy of calcifications, the proportion of low-grade, early stage cancers and in situ lesions among all breast cancers has risen substantially. The introduction of molecular testing has increased the recognition of lower risk subtypes, and less aggressive treatments are more commonly recommended for these subtypes. Mammographically detected breast cancers are much more likely to have low-risk biology than symptomatic tumors found between screenings (interval cancers) or that present as clinical masses. Recognizing the lower risk associated with these lesions and the ability to confirm the risk with molecular tests should safely enable the use of less aggressive treatments. Importantly, ductal carcinoma in situ (DCIS) lesions, or what have been called stage I cancers, in and of themselves are not life-threatening. In situ lesions have been treated in a manner similar to that of invasive cancer, but there is little evidence to support that this practice has improved mortality. It is also being recognized that DCIS lesions are heterogeneous, and a substantial proportion of them may in fact be precursors of more indolent invasive cancers. Increasing evidence suggests that these lesions are being overtreated. The introduction of molecular tests should be able to help usher in a change in approach to these lesions. Reclassifying these lesions as part of the spectrum of high-risk lesions enables the use of a prevention approach. Learning from the experience with active surveillance in prostate cancer should empower the introduction of new approaches, with a focus on preventing invasive cancer, especially given that there are effective, United States Food and Drug Administration (FDA)-approved breast cancer preventive interventions.

Ultrasound-guided cable-free 13-gauge vacuum-assisted biopsy of non-mass breast lesions

PubMed Central

Seo, Jiwoon; Jang, Mijung; Yun, Bo La; Lee, Soo Hyun; Kim, Eun-Kyu; Kang, Eunyoung; Park, So Yeon; Moon, Woo Kyung; Choi, Hye Young; Kim, Bohyoung

2017-01-01

Purpose To compare the outcomes of ultrasound-guided core biopsy for non-mass breast lesions by the novel 13-gauge cable-free vacuum-assisted biopsy (VAB) and by the conventional 14-gauge semi-automated core needle biopsy (CCNB). Materials and methods Our institutional review board approved this prospective study, and all patients provided written informed consent. Among 1840 ultrasound-guided percutaneous biopsies performed from August 2013 to December 2014, 145 non-mass breast lesions with suspicious microcalcifications on mammography or corresponding magnetic resonance imaging finding were subjected to 13-gauge VAB or 14-gauge CCNB. We evaluated the technical success rates, average specimen numbers, and tissue sampling time. We also compared the results of percutaneous biopsy and final surgical pathologic diagnosis to analyze the rates of diagnostic upgrade or downgrade. Results Ultrasound-guided VAB successfully targeted and sampled all lesions, whereas CCNB failed to demonstrate calcification in four (10.3%) breast lesions with microcalcification on specimen mammography. The mean sampling time were 238.6 and 170.6 seconds for VAB and CCNB, respectively. No major complications were observed with either method. Ductal carcinoma in situ (DCIS) and atypical ductal hyperplasia (ADH) lesions were more frequently upgraded after CCNB (8/23 and 3/5, respectively) than after VAB (2/26 and 0/4, respectively P = 0.028). Conclusion Non-mass breast lesions were successfully and accurately biopsied using cable-free VAB. The underestimation rate of ultrasound-detected non-mass lesion was significantly lower with VAB than with CCNB. Trial registration CRiS KCT0002267. PMID:28628656

Ultrasonography of the male breast

PubMed Central

Draghi, F.; Tarantino, C.C.; Madonia, L.; Ferrozzi, G.

2011-01-01

The male breast has been insufficiently explored in the medical literature, particularly that dealing with ultrasonography, although this topic is almost as vast and varied as that of the female breast. The purpose of this article is to provide a schematic review of the most frequent breast lesions encountered in males and their sonographic appearances. After a brief introduction on the anatomy of the male breast, the authors review the non-neoplastic (gynecomastia, pseudogynecomastia, cysts, inflammatory diseases, and Mondor disease) and neoplastic (benign and malignant) lesions encountered in this organ. PMID:23397020

Breast epithelium procurement from stereotactic core biopsy washings: flow cytometry-sorted cell count analysis.

PubMed

Stoler, Daniel L; Stewart, Carleton C; Stomper, Paul C

2002-02-01

Molecular studies of breast lesions have been constrained by difficulties in procuring adequate tissues for analyses. Standard procedures are restricted to larger, palpable masses or the use of paraffin-embedded materials, precluding facile procurement of fresh specimens of early lesions. We describe a study to determine the yield and characteristics of sorted cell populations retrieved in core needle biopsy specimen rinses from a spectrum of breast lesions. Cells from 114 consecutive stereotactic core biopsies of mammographic lesions released into saline washes were submitted for flow cytometric analysis. For each specimen, epithelial cells were separated from stromal and blood tissue based on the presence of cytokeratin 8 and 18 markers. Epithelial cell yields based on pathological diagnoses of the biopsy specimen, patient age, and mammographic appearance of the lesion were determined. Biopsies containing malignant lesions yielded significantly higher numbers of cells than were obtained from benign lesion biopsies. Significantly greater cell counts were observed from lesions from women age 50 or above compared with those of younger women. Mammographic density surrounding the biopsy site, the mammographic appearance of the lesion, and the number of cores taken at the time of biopsy appeared to have little effect on the yield of epithelial cells. We demonstrate the use of flow cytometric sorting of stereotactic core needle biopsy washes from lesions spanning the spectrum of breast pathology to obtain epithelial cells in sufficient numbers to meet the requirements of a variety of molecular and genetic analyses.

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.

Interobserver variability of ultrasound elastography and the ultrasound BI-RADS lexicon of breast lesions.

PubMed

Park, Chang Suk; Kim, Sung Hun; Jung, Na Young; Choi, Jae Jung; Kang, Bong Joo; Jung, Hyun Seouk

2015-03-01

Elastographpy is a newly developed noninvasive imaging technique that uses ultrasound (US) to evaluate tissue stiffness. The interpretation of the same elastographic images may be variable according to reviewers. Because breast lesions are usually reported according to American College of Radiology Breast Imaging and Data System (ACR BI-RADS) lexicons and final category, we tried to compare observer variability between lexicons and final categorization of US BI-RADS and the elasticity score of US elastography. From April 2009 to February 2010, 1356 breast lesions in 1330 patients underwent ultrasound-guided core biopsy. Among them, 63 breast lesions in 55 patients (mean age, 45.7 years; range, 21-79 years) underwent both conventional ultrasound and elastography and were included in this study. Two radiologists independently performed conventional ultrasound and elastography, and another three observers reviewed conventional ultrasound images and elastography videos. Observers independently recorded the elasticity score for a 5-point scoring system proposed by Itoh et al., BI-RADS lexicons and final category using ultrasound BI-RADS. The histopathologic results were obtained and used as the reference standard. Interobserver variability was evaluated. Of the 63 lesions, 42 (66.7 %) were benign, and 21 (33.3 %) were malignant. The highest value of concordance among all variables was achieved for the elasticity score (k = 0.59), followed by shape (k = 0.54), final category (k = 0.48), posterior acoustic features (k = 0.44), echogenecity and orientation (k = 0.43). The least concordances were margin (k = 0.26), lesion boundary (k = 0.29) and calcification (k = 0.3). Elasticity score showed a higher level of interobserver agreement for the diagnosis of breast lesions than BI-RADS lexicons and final category.

Quantification of breast lesion compositions using low-dose spectral mammography: A feasibility study

PubMed Central

Ding, Huanjun; Sennung, David; Cho, Hyo-Min; Molloi, Sabee

2016-01-01

Purpose: The positive predictive power for malignancy can potentially be improved, if the chemical compositions of suspicious breast lesions can be reliably measured in screening mammography. The purpose of this study is to investigate the feasibility of quantifying breast lesion composition, in terms of water and lipid contents, with spectral mammography. Methods: Phantom and tissue samples were imaged with a spectral mammography system based on silicon-strip photon-counting detectors. Dual-energy calibration was performed for material decomposition, using plastic water and adipose-equivalent phantoms as the basis materials. The step wedge calibration phantom consisted of 20 calibration configurations, which ranged from 2 to 8 cm in thickness and from 0% to 100% in plastic water density. A nonlinear rational fitting function was used in dual-energy calibration of the imaging system. Breast lesion phantoms, made from various combinations of plastic water and adipose-equivalent disks, were embedded in a breast mammography phantom with a heterogeneous background pattern. Lesion phantoms with water densities ranging from 0% to 100% were placed at different locations of the heterogeneous background phantom. The water density in the lesion phantoms was measured using dual-energy material decomposition. The thickness and density of the background phantom were varied to test the accuracy of the decomposition technique in different configurations. In addition, an in vitro study was also performed using mixtures of lean and fat bovine tissue of 25%, 50%, and 80% lean weight percentages as the background. Lesions were simulated by using breast lesion phantoms, as well as small bovine tissue samples, composed of carefully weighed lean and fat bovine tissues. The water densities in tissue samples were measured using spectral mammography and compared to measurement using chemical decomposition of the tissue. Results: The thickness of measured and known water contents was compared for various lesion configurations. There was a good linear correlation between the measured and the known values. The root-mean-square errors in water thickness measurements were 0.3 and 0.2 mm for the plastic phantom and bovine tissue backgrounds, respectively. Conclusions: The results indicate that spectral mammography can be used to accurately characterize breast lesion composition in terms of their equivalent water and lipid contents. PMID:27782705

MR-guided fine needle aspiration of breast lesions: Initial experience

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

Wald, D.S.; Weinreb, J.C.; Newstead, G.

1996-01-01

Fine needle aspiration (FNA) is a minimally invasive procedure that is used to obtain cytologic specimens of suspicious lesions in the breast. The goal of this study was to evaluate the logistics and limitations of MR-guided FNA using a prototype breast localization coil. MR-guided FNAs were attempted on 18 lesions (detected on mammography and/or palpation) in 16 patients. Patients were prone with their compressed mediolaterally between two plates in a circularly polarized RF coil. Lesion position was determined by reference to fiducial makers that corresponded to a grid of holes placed at 5 mm intervals in compression plate. FNA wasmore » performed with a 22G non-ferromagnetic needle. FNA was successful for 11 of 18 lesions (61%). Of the seven unsuccessful cases, there were four in which the lesions were too posteriorly placed to be accessed through the compression plate by the needle. Three cases were too anteriorly placed to be effectively immobilized and, although successfully localized, were insufficiently sampled by the FNA technique. MR-guided FNA is possible using a prototype breast localization device in a select group of patients. Current coil design limits its use in performing MR-guided FNA on the most anteriorly and posteriorly placed breast lesions. Unique requirements of FNA under MR guidance as compared to needle localization and biopsy have been identified. Modifications in localization hardware and cytology aspiration needles should overcome these restrictions. 15 refs., 3 figs.« less

[Contrast enhanced power Doppler and color Doppler ultrasound in breast masses: Efficiency in diagnosis and contributions to differential diagnosis].

PubMed

Algül, Ali; Balci, Pinar; Seçil, Mustafa; Canda, Tülay

2003-06-01

To compare ability of detection of vascular structures by utilizing ultrasonographic contrast agent (Levovist) prior to and following power Doppler ultrasound (PDUS) and colour Doppler ultrasound (CDUS) and to determine useful parameters in the differentiation of malignant and benign breast masses by means of verified data. Vascularisation characteristics of 38 breast masses (22 malignant, 16 benign) which were confirmed by mammography and B-mode sonography were evaluated by both CDUS and PDUS following and prior to intravenous contrast application. In addition, Vmax and RI values of vascular structures were calculated by Doppler spectral evaluation. Malignant lesions showed more vascularity than benign lesions both with and without contrast enhancement. With both methods, by utilizing contrast agent, central, penetrating and tortuous vascular structures became more significant in malignant lesions when compared with benign lesions. PDUS was able to detect vascular structures better than CDUS; however, the difference was not statistically significant. Presence of peripheral vascularity was not useful in differentiating malignant from benign lesions. Vmax and RI values were higher in malignant lesions and the difference was statistically significant. In both methods, Vmax > 15 cm/sec and RI > 0.80 (CDUS), and RI > 0.70 (PDUS) were accepted as malignancy parameters. Vascular patterns of breast masses as determined with PDUS and CDUS with contrast enhancement and Doppler spectral examinations enabled differentiation of malignant and benign breast lesions. Thus, it is possible to decrease the number of unnecessary surgical interventions.

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.

Incidence of inflammatory breast cancer in patients with clinical inflammatory breast symptoms

PubMed Central

Pons, Kelly; Mabille, Mylène; Abd alsamad, Issam; Mitri, Rana; Skalli, Dounia; Haddad, Bassam

2017-01-01

Background To describe a large cohort of women with non-puerperal inflammatory breast and to identify characteristics of inflammatory breast cancer. Methods All patients consulting for inflammatory breast syndrome in the breast unit of our tertiary University hospital between September 2013 and December 2015 were prospectively included. We excluded women who were pregnant or in the postpartum period. Patients underwent systematic clinical examination and imaging (breast ultrasonography and mammography). A biopsy was performed if the clinician suspected a malignant lesion of the breast. Clinicopathologic and radiologic data were registered. Statistics were performed using R (3.0.2 version) software. Results Among the 76 patients screened and included, 38 (50%) had a malignant lesion at final diagnosis, 21 (27.6%) were diagnosed with infectious disease and 17 (22.4%) with inflammatory disease of the breast. When compared to patients with benign disease, patients with a malignant lesion were significantly older (p = 0.022, CI95% 1.78–14.7), had a significantly bigger palpable mass (p<0.001, CI 95% 22.8–58.9), were more likely to have skin thickening (p = 0.05) and had more suspicious lymph nodes at clinical examination (p<0.001, CI 95% 2.72–65.3). Precise limits on ultrasonography were significantly associated with benign lesions. The presence of a mass (p = 0.04), micro calcifications (p = 0.04) or of focal asymmetry (p<0.001, CI95% 1.3–618) on mammography was significantly associated with malignant disease. Conclusion Inflammatory breast cancer was common in our cohort of women consulting for inflammatory breast syndrome. Identifying these patients with high-risk malignancy is crucial in the management of an inflammatory breast. PMID:29261724

Comparison of conventional DCE-MRI and a novel golden-angle radial multicoil compressed sensing method for the evaluation of breast lesion conspicuity.

PubMed

Heacock, Laura; Gao, Yiming; Heller, Samantha L; Melsaether, Amy N; Babb, James S; Block, Tobias K; Otazo, Ricardo; Kim, Sungheon G; Moy, Linda

2017-06-01

To compare a novel multicoil compressed sensing technique with flexible temporal resolution, golden-angle radial sparse parallel (GRASP), to conventional fat-suppressed spoiled three-dimensional (3D) gradient-echo (volumetric interpolated breath-hold examination, VIBE) MRI in evaluating the conspicuity of benign and malignant breast lesions. Between March and August 2015, 121 women (24-84 years; mean, 49.7 years) with 180 biopsy-proven benign and malignant lesions were imaged consecutively at 3.0 Tesla in a dynamic contrast-enhanced (DCE) MRI exam using sagittal T1-weighted fat-suppressed 3D VIBE in this Health Insurance Portability and Accountability Act-compliant, retrospective study. Subjects underwent MRI-guided breast biopsy (mean, 13 days [1-95 days]) using GRASP DCE-MRI, a fat-suppressed radial "stack-of-stars" 3D FLASH sequence with golden-angle ordering. Three readers independently evaluated breast lesions on both sequences. Statistical analysis included mixed models with generalized estimating equations, kappa-weighted coefficients and Fisher's exact test. All lesions demonstrated good conspicuity on VIBE and GRASP sequences (4.28 ± 0.81 versus 3.65 ± 1.22), with no significant difference in lesion detection (P = 0.248). VIBE had slightly higher lesion conspicuity than GRASP for all lesions, with VIBE 12.6% (0.63/5.0) more conspicuous (P < 0.001). Masses and nonmass enhancement (NME) were more conspicuous on VIBE (P < 0.001), with a larger difference for NME (14.2% versus 9.4% more conspicuous). Malignant lesions were more conspicuous than benign lesions (P < 0.001) on both sequences. GRASP DCE-MRI, a multicoil compressed sensing technique with high spatial resolution and flexible temporal resolution, has near-comparable performance to conventional VIBE imaging for breast lesion evaluation. 3 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;45:1746-1752. © 2016 International Society for Magnetic Resonance in Medicine.

Nummular Eczema of Breast: A Potential Dermatologic Complication after Mastectomy and Subsequent Breast Reconstruction

PubMed Central

Iwahira, Yoshiko; Nagasao, Tomohisa; Shimizu, Yusuke; Kuwata, Kumiko; Tanaka, Yoshio

2015-01-01

Purposes. The present paper reports clinical cases where nummular eczema developed during the course of breast reconstruction by means of implantation and evaluates the occurrence patterns and ratios of this complication. Methods. 1662 patients undergoing breast reconstruction were reviewed. Patients who developed nummular eczema during the treatment were selected, and a survey was conducted on these patients regarding three items: (1) the stage of the treatment at which nummular eczema developed; (2) time required for the lesion to heal; (3) location of the lesion on the reconstructed breast(s). Furthermore, histopathological examination was conducted to elucidate the etiology of the lesion. Results. 48 patients (2.89%) developed nummular eczema. The timing of onset varied among these patients, with lesions developing after the placement of tissue expanders for 22 patients (45.8%); after the tissue expanders were replaced with silicone implants for 12 patients (25%); and after nipple-areola complex reconstruction for 14 patients (29.2%). Nummular eczema developed both in periwound regions (20 cases: 41.7%) and in nonperiwound regions (32 cases: 66.7%). Histopathological examination showed epidermal acanthosis, psoriasiform patterns, and reduction of sebaceous glands. Conclusions. Surgeons should recognize that nummular eczema is a potential complication of breast reconstruction with tissue expanders and silicone implants. PMID:26380109

3 Tesla breast MR imaging as a problem-solving tool: Diagnostic performance and incidental lesions

PubMed Central

Spick, Claudio; Szolar, Dieter H. M.; Preidler, Klaus W.; Reittner, Pia; Rauch, Katharina; Brader, Peter; Tillich, Manfred

2018-01-01

Purpose To investigate the diagnostic performance and incidental lesion yield of 3T breast MRI if used as a problem-solving tool. Methods This retrospective, IRB-approved, cross-sectional, single-center study comprised 302 consecutive women (mean: 50±12 years; range: 20–79 years) who were undergoing 3T breast MRI between 03/2013-12/2014 for further workup of conventional and clinical breast findings. Images were read by experienced, board-certified radiologists. The reference standard was histopathology or follow-up ≥ two years. Sensitivity, specificity, PPV, and NPV were calculated. Results were stratified by conventional and clinical breast findings. Results The reference standard revealed 53 true-positive, 243 true-negative, 20 false-positive, and two false-negative breast MRI findings, resulting in a sensitivity, specificity, PPV, and NPV of 96.4% (53/55), 92.4% (243/263), 72.6% (53/73), and 99.2% (243/245), respectively. In 5.3% (16/302) of all patients, incidental MRI lesions classified BI-RADS 3–5 were detected, 37.5% (6/16) of which were malignant. Breast composition and the imaging findings that had led to referral had no significant influence on the diagnostic performance of breast MR imaging (p>0.05). Conclusion 3T breast MRI yields excellent diagnostic results if used as a problem-solving tool independent of referral reasons. The number of suspicious incidental lesions detected by MRI is low, but is associated with a substantial malignancy rate. PMID:29293582

Efficiency of Imaging Modalities in Male Breast Disease: Can Ultrasound Give Additional Information for Assessment of Gynecomastia Evolution?

PubMed Central

Sarıca, Özgür; Kahraman, A. Nedim; Öztürk, Enis; Teke, Memik

2018-01-01

Objective The purpose of this study is to present mammography and ultrasound findings of male breast lesions and to investigate the ability of diagnostic modalities in estimating the evolution of gynecomastia. Materials and Methods Sixty-nine male patients who admitted to Taksim and Bakirkoy Education and Research Hospitals and underwent mammography (MG) and ultrasonography (US) imaging were retrospectively evaluated. Duration of symptoms and mammographic types of gynecomastia according to Appelbaum’s classifications were evaluated, besides the sonographic findings in mammographic types of gynecomastia. Results The distribution of 69 cases were as follows: gynecomastia 47 (68.11%), pseudogynecomastia 6 (8.69%) primary breast carcinoma 7 (10.14%), metastatic carcinoma 1 (1.4%), epidermal inclusion cyst 2 (2.8%), abscess 2 (2.8%), lipoma 2 (2.8%), pyogenic granuloma 1 (1.4%), and granulomatous lobular mastitis 1 (1.4%). Gynecomastia patients who had symptoms less than 1 year had nodular gynecomastia (34.6%) as opposed to dendritic gynecomastia (61.5%) (p<0.01) based on mammography results according to Appelbaum’s classifications. In patients having symptoms for 1 to 2 years, diffuse gynecomastia (70%) had a higher rate than the dendritic type (20%). Patients having the symptoms more than 2 years had diffuse gynecomastia (57.1%) while 42.9% had dendritic gynecomastia (p<0.001). With sonographic examination patients who had symptoms less than 1 year had higher rates of dendritic gynecomastia (92.3%) than noduler type (1.9 %). Patients having symptoms for 1 to 2 years had more dentritic gynecomastia (70%) than diffuse type (30%). Patients having symptoms more than 2 years had diffuse gynecomastia (57.1%) comparable to dendritic gynecomastia (42.9 %). Conclusion Diagnostic imaging modalities are efficient tools for estimation of gynecomastia evolution as well as the diagnosis of other male breast diseases. There seems to be an incongruity between duration of clinical complaints and diagnostic imaging classification of gynecomastia. The use of these high resolution US findings may demonstrate an early phase fibrosis especially in patients visualized by mammography as with nodular phase. PMID:29322116

Efficiency of Imaging Modalities in Male Breast Disease: Can Ultrasound Give Additional Information for Assessment of Gynecomastia Evolution?

PubMed

Sarıca, Özgür; Kahraman, A Nedim; Öztürk, Enis; Teke, Memik

2018-01-01

The purpose of this study is to present mammography and ultrasound findings of male breast lesions and to investigate the ability of diagnostic modalities in estimating the evolution of gynecomastia. Sixty-nine male patients who admitted to Taksim and Bakirkoy Education and Research Hospitals and underwent mammography (MG) and ultrasonography (US) imaging were retrospectively evaluated. Duration of symptoms and mammographic types of gynecomastia according to Appelbaum's classifications were evaluated, besides the sonographic findings in mammographic types of gynecomastia. The distribution of 69 cases were as follows: gynecomastia 47 (68.11%), pseudogynecomastia 6 (8.69%) primary breast carcinoma 7 (10.14%), metastatic carcinoma 1 (1.4%), epidermal inclusion cyst 2 (2.8%), abscess 2 (2.8%), lipoma 2 (2.8%), pyogenic granuloma 1 (1.4%), and granulomatous lobular mastitis 1 (1.4%). Gynecomastia patients who had symptoms less than 1 year had nodular gynecomastia (34.6%) as opposed to dendritic gynecomastia (61.5%) (p<0.01) based on mammography results according to Appelbaum's classifications. In patients having symptoms for 1 to 2 years, diffuse gynecomastia (70%) had a higher rate than the dendritic type (20%). Patients having the symptoms more than 2 years had diffuse gynecomastia (57.1%) while 42.9% had dendritic gynecomastia (p<0.001). With sonographic examination patients who had symptoms less than 1 year had higher rates of dendritic gynecomastia (92.3%) than noduler type (1.9 %). Patients having symptoms for 1 to 2 years had more dentritic gynecomastia (70%) than diffuse type (30%). Patients having symptoms more than 2 years had diffuse gynecomastia (57.1%) comparable to dendritic gynecomastia (42.9 %). Diagnostic imaging modalities are efficient tools for estimation of gynecomastia evolution as well as the diagnosis of other male breast diseases. There seems to be an incongruity between duration of clinical complaints and diagnostic imaging classification of gynecomastia. The use of these high resolution US findings may demonstrate an early phase fibrosis especially in patients visualized by mammography as with nodular phase.

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

Comparison and Optimization of 3.0 T Breast Images Quality of Diffusion-Weighted Imaging with Multiple B-Values.

PubMed

Han, Xiaowei; Li, Junfeng; Wang, Xiaoyi

2017-04-01

Breast 3.0 T magnetic resonance diffusion-weighted imaging (MR-DWI) of benign and malignant lesions were obtained to measure and calculate the signal-to-noise ratio (SNR), signal intensity ratio (SIR), and contrast-to-noise ratio (CNR) of lesions at different b-values. The variation patterns of SNR and SIR were analyzed with different b-values and the images of DWI were compared at four different b-values with higher image quality. The effect of SIR on the differential diagnostic efficiency of benign and malignant lesions was compared using receiver operating characteristic curves to provide a reference for selecting the optimal b-value. A total of 96 qualified patients with 112 lesions and 14 patients with their contralateral 14 normal breasts were included in this study. The single-shot echo planar imaging sequence was used to perform the DWI and a total of 13 b-values were used: 0, 50, 100, 200, 400, 600, 800, 1000, 1200, 1500, 1800, 2000, and 2500 s/mm 2 . On DWI, the suitable regions of interest were selected. The SNRs of normal breasts (SNR normal ), SNR lesions , SIR, and CNR of benign and malignant lesions were measured on DWI with different b-values and calculated. The variation patterns of SNR, SIR, and CNR values on DWI for normal breasts, benign lesions, and malignant lesions with different b-values were analyzed by using Pearson correlation analysis. The SNR and SIR of benign and malignant lesions with the same b-values were compared using t-tests. The diagnostic efficiencies of SIR with different b-values for benign and malignant lesions were evaluated using receiver operating characteristic curves. Breast DWI had higher CNR for b-values ranging from 600 to 1200 s/mm 2 . It had the best CNR at b = 1000 s/mm 2 for the benign lesions and at b = 1200 s/mm 2 for the malignant lesions. The signal intensity and SNR values of normal breasts decreased with increasing b-values, with a negative correlation (r = -0.945, P < 0.01). The mean SNR values of benign and malignant lesions were negatively correlated (r = -0.982 and -0.947, respectively, and P < 0.01), gradually decreasing with increasing b-values. The mean SIR value of benign lesions gradually decreased with increasing b-values, a negative correlation (r = -0.991, P < 0.01). The mean SIR values of malignant lesions gradually increased with increasing b-values between 0 and 1200 s/mm 2 , and gradually decreased with increasing b-values ≥ 1500 s/mm 2 . For b-values of 600, 800, 1000, and 1200 s/mm 2 , the sensitivity and specificity of SIR in identifying benign and malignant lesions gradually increased with increasing b-values, peaking at 1200 s/mm 2 . Breast DWI had higher image quality for b-values ranging from 600 to 1200 s/mm 2 , and was best for b-values ranging from 1000 to 1200 s/mm 2 . The SIR had the highest diagnostic efficiency in differentiating benign and malignant lesions for a b-value of 1200 s/mm 2 . Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Value of the BI-RADS classification in MR-Mammography for diagnosis of benign and malignant breast tumors.

PubMed

Sohns, Christian; Scherrer, Martin; Staab, Wieland; Obenauer, Silvia

2011-12-01

To assess whether the BI-RADS classification in MR-Mammography (MRM) can distinguish between benign and malignant lesions. 207 MRM investigations were categorised according to BI-RADS. The results were compared to histology. All MRM studies were interpreted by two examiners. Statistical significance for the accuracy of MRM was calculated. A significant correlation between specific histology and MRM-tumour-morphology could not be reported. Mass (68%) was significant for malignancy. Significance raised with irregular shape (88%), spiculated margin (97%), rim enhancement (98%), fast initial increase (90%), post initial plateau (65%), and intermediate T2 result (82%). Highly significant for benignity was an oval mass (79%), slow initial increase (94%) and a hyperintense T2 result (77%), also an inconspicuous MRM result (77%) was often seen in benign histology. Symmetry (90%) and further post initial increase (90%) were significant, whereas a regional distribution (74%) was lowly significant for benignity. On basis of the BI-RADS classification an objective comparability and statement of diagnosis could be made highly significant. Due to the fact of false-negative and false-positive MRM-results, histology is necessary.

iROLL: does 3-D radioguided occult lesion localization improve surgical management in early-stage breast cancer?

PubMed

Bluemel, Christina; Cramer, Andreas; Grossmann, Christoph; Kajdi, Georg W; Malzahn, Uwe; Lamp, Nora; Langen, Heinz-Jakob; Schmid, Jan; Buck, Andreas K; Grimminger, Hanns-Jörg; Herrmann, Ken

2015-10-01

To prospectively evaluate the feasibility of 3-D radioguided occult lesion localization (iROLL) and to compare iROLL with wire-guided localization (WGL) in patients with early-stage breast cancer undergoing breast-conserving surgery and sentinel lymph node biopsy (SLNB). WGL (standard procedure) and iROLL in combination with SLNB were performed in 31 women (mean age 65.1 ± 11.2 years) with early-stage breast cancer and clinically negative axillae. Patient comfort in respect of both methods was assessed using a ten point scale. SLNB and iROLL were guided by freehand SPECT (fhSPECT). The results of the novel 3-D image-based method were compared with those of WGL, ultrasound-based lesion localization, and histopathology. iROLL successfully detected the malignant primary and at least one sentinel lymph node in 97% of patients. In a single patient (3%), only iROLL, and not WGL, enabled lesion localization. The variability between fhSPECT and ultrasound-based depth localization of breast lesions was low (1.2 ± 1.4 mm). Clear margins were achieved in 81% of the patients; however, precise prediction of clear histopathological surgical margins was not feasible using iROLL. Patients rated iROLL as less painful than WGL with a pain score 0.8 ± 1.2 points (p < 0.01) lower than the score for iROLL. iROLL is a well-tolerated and feasible technique for localizing early-stage breast cancer in the course of breast-conserving surgery, and is a suitable replacement for WGL. As a single image-based procedure for localization of breast lesions and sentinel nodes, iROLL may improve the entire surgical procedure. However, no advantages of the image-guided procedure were found with regard to prediction of complete tumour resection.

3.0 Tesla breast magnetic resonance imaging in patients with nipple discharge when mammography and ultrasound fail.

PubMed

Lubina, Nóra; Schedelbeck, Ulla; Roth, Anne; Weng, Andreas Max; Geissinger, Eva; Hönig, Arnd; Hahn, Dietbert; Bley, Thorsten Alexander

2015-05-01

To compare 3.0 Tesla breast magnetic resonance imaging (MRI) with galactography for detection of benign and malignant causes of nipple discharge in patients with negative mammography and ultrasound. We prospectively evaluated 56 breasts of 50 consecutive patients with nipple discharge who had inconspicuous mammography and ultrasound, using 3.0 Tesla breast MRI with a dedicated 16-channel breast coil, and then compared the results with galactography. Histopathological diagnoses and follow-ups were used as reference standard. Lesion size estimated on MRI was compared with the size at histopathology. Sensitivity and specificity of MRI vs. galactography for detecting pathologic findings were 95.7 % vs. 85.7 % and 69.7 % vs. 33.3 %, respectively. For the supposed concrete pathology based on MRI findings, the specificity was 67.6 % and the sensitivity 77.3 % (PPV 60.7 %, NPV 82.1 %). Eight malignant lesions were detected (14.8 %). The estimated size at breast MRI showed excellent correlation with the size at histopathology (Pearson's correlation coefficient 0.95, p < 0.0001). MRI of the breast at 3.0 Tesla is an accurate imaging test and can replace galactography in the workup of nipple discharge in patients with inconspicuous mammography and ultrasound. • Breast MRI is an excellent diagnostic tool for patients with nipple discharge. • MRI of the breast reveals malignant lesions despite inconspicuous mammography and ultrasound. • MRI of the breast has greater sensitivity and specificity than galactography. • Excellent correlation of lesion size measured at MRI and histopathology was found.

[Atypical epithelial hyperplasia of the breast: current state of knowledge and clinical practice].

PubMed

Lavoué, V; Bertel, C; Tas, P; Bendavid, C; Rouquette, S; Foucher, F; Audrain, O; Bouriel, C; Levêque, J

2010-02-01

The diagnosis of atypical epithelial hyperplasia (AEH) increases with breast cancer screening. AEH is divided in three groups: atypical ductal hyperplasia, columnar cell lesions with atypia, lobular neoplasia. The management of women with AEH is not consensual because of uncertainty about their diagnosis related to the type of the biopsy sampling (core needle biopsy or surgical excision) and their controversial clinical signification between risk marker and true precursor of breast cancer. A systematic review of published studies was performed. Medline baseline interrogation was performed with the following keywords: atypical ductal hyperplasia, columnar cell lesions with atypia, lobular neoplasia, core needle biopsy, breast cancer, precursor lesion, hormonal replacement therapy. For each breast lesion, identified publications (English or French) were assessed for clinical practise in epidemiology, diagnosis and patient management. With immunohistochemistry and molecular studies, AEH seems to be precursor of breast cancer. But, epidemiological studies show low rate of breast cancer in women with AEH. AEH were still classified as risk factor of breast cancer. Because of high rate of breast cancer underestimation, surgical excision is necessary after the diagnosis of AEH at core needle biopsy. Surgical oncology rules and collaboration with radiologist are required for this surgery. A second operation was not required due to involved margins by AEH (except with pleiomorphic lobular neoplasia) because local control of breast cancer seems to be unchanged. Besides, hormonal replacement therapy for patient with AEH is not recommended because of lack of studies about this subject. Copyright 2009 Elsevier Masson SAS. All rights reserved.

Novel Breast Imaging and Machine Learning: Predicting Breast Lesion Malignancy at Cone-Beam CT Using Machine Learning Techniques.

PubMed

Uhlig, Johannes; Uhlig, Annemarie; Kunze, Meike; Beissbarth, Tim; Fischer, Uwe; Lotz, Joachim; Wienbeck, Susanne

2018-05-24

The purpose of this study is to evaluate the diagnostic performance of machine learning techniques for malignancy prediction at breast cone-beam CT (CBCT) and to compare them to human readers. Five machine learning techniques, including random forests, back propagation neural networks (BPN), extreme learning machines, support vector machines, and K-nearest neighbors, were used to train diagnostic models on a clinical breast CBCT dataset with internal validation by repeated 10-fold cross-validation. Two independent blinded human readers with profound experience in breast imaging and breast CBCT analyzed the same CBCT dataset. Diagnostic performance was compared using AUC, sensitivity, and specificity. The clinical dataset comprised 35 patients (American College of Radiology density type C and D breasts) with 81 suspicious breast lesions examined with contrast-enhanced breast CBCT. Forty-five lesions were histopathologically proven to be malignant. Among the machine learning techniques, BPNs provided the best diagnostic performance, with AUC of 0.91, sensitivity of 0.85, and specificity of 0.82. The diagnostic performance of the human readers was AUC of 0.84, sensitivity of 0.89, and specificity of 0.72 for reader 1 and AUC of 0.72, sensitivity of 0.71, and specificity of 0.67 for reader 2. AUC was significantly higher for BPN when compared with both reader 1 (p = 0.01) and reader 2 (p < 0.001). Machine learning techniques provide a high and robust diagnostic performance in the prediction of malignancy in breast lesions identified at CBCT. BPNs showed the best diagnostic performance, surpassing human readers in terms of AUC and specificity.

Clinical and ultrasonographic features of male breast tumors: A retrospective analysis.

PubMed

Yuan, Wei-Hsin; Li, Anna Fen-Yau; Chou, Yi-Hong; Hsu, Hui-Chen; Chen, Ying-Yuan

2018-01-01

The purpose of this study was to determine clinical and ultrasonographic characteristics of male breast tumors. The medical records of male patients with breast lesions were retrieved from an electronic medical record database and a pathology database and retrospectively reviewed. A total of 112 men (125 breast masses) with preoperative breast ultrasonography (US) were included (median age, 59.50 years; age range, 15-96 years). Data extracted included patient age, if the lesions were bilateral, palpable, and tender, and the presence of nipple discharge. Breast lesion features on static US images were reviewed by three experienced radiologists without knowledge of physical examination or pathology results, original breast US image interpretations, or surgical outcomes. The US features were documented according to the BI-RADS (Breast Imaging-Reporting and Data System) US lexicons. A forth radiologist compiled the data for analysis. Of the 125 breast masses, palpable tender lumps and bilateral synchronous masses were more likely to be benign than malignant (both, 100% vs 0%, P < 0.05). Advanced age and bloody discharge from nipples were common in malignant lesions (P <0.05). A mass eccentric to a nipple, irregular shape, the presence of an echogenic halo, predominantly internal vascularity, and rich color flow signal on color Doppler ultrasound were significantly related to malignancy (all, P < 0.05). An echogenic halo and the presence of rich color flow signal were independent predictors of malignancy. Specific clinical and US characteristics of male breast tumors may help guide treatment, and determine if surgery or conservative treatment is preferable.

Clinical and ultrasonographic features of male breast tumors: A retrospective analysis

PubMed Central

Li, Anna Fen-Yau; Chou, Yi-Hong; Hsu, Hui-Chen; Chen, Ying-Yuan

2018-01-01

Objective The purpose of this study was to determine clinical and ultrasonographic characteristics of male breast tumors. Methods The medical records of male patients with breast lesions were retrieved from an electronic medical record database and a pathology database and retrospectively reviewed. A total of 112 men (125 breast masses) with preoperative breast ultrasonography (US) were included (median age, 59.50 years; age range, 15–96 years). Data extracted included patient age, if the lesions were bilateral, palpable, and tender, and the presence of nipple discharge. Breast lesion features on static US images were reviewed by three experienced radiologists without knowledge of physical examination or pathology results, original breast US image interpretations, or surgical outcomes. The US features were documented according to the BI-RADS (Breast Imaging-Reporting and Data System) US lexicons. A forth radiologist compiled the data for analysis. Results Of the 125 breast masses, palpable tender lumps and bilateral synchronous masses were more likely to be benign than malignant (both, 100% vs 0%, P < 0.05). Advanced age and bloody discharge from nipples were common in malignant lesions (P <0.05). A mass eccentric to a nipple, irregular shape, the presence of an echogenic halo, predominantly internal vascularity, and rich color flow signal on color Doppler ultrasound were significantly related to malignancy (all, P < 0.05). An echogenic halo and the presence of rich color flow signal were independent predictors of malignancy. Conclusion Specific clinical and US characteristics of male breast tumors may help guide treatment, and determine if surgery or conservative treatment is preferable. PMID:29558507

Is the necrosis/wall ADC ratio useful for the differentiation of benign and malignant breast lesions?

PubMed

Durur-Subasi, Irmak; Durur-Karakaya, Afak; Karaman, Adem; Seker, Mehmet; Demirci, Elif; Alper, Fatih

2017-05-01

To determine whether the necrosis/wall apparent diffusion coefficient (ADC) ratio is useful for the malignant-benign differentiation of necrotic breast lesions. Breast MRI was performed using a 3-T system. In this retrospective study, calculation of the necrosis/wall ADC ratio was based on ADC values measured from the necrosis and from the wall of malignant and benign breast lesions by diffusion-weighted imaging (DWI). By synchronizing post-contrast T 1 weighted images, the separate parts of wall and necrosis were maintained. All the diagnoses were pathologically confirmed. Statistical analyses were conducted using an independent sample t-test and receiver operating characteristic analysis. The intraclass and interclass correlations were evaluated. A total of 66 female patients were enrolled, 38 of whom had necrotic breast carcinomas and 28 of whom had breast abscesses. The ADC values were obtained from both the wall and necrosis. The mean necrosis/wall ADC ratio (± standard deviation) was 1.61 ± 0.51 in carcinomas, and it was 0.65 ± 0.33 in abscesses. The area under the curve values for necrosis ADC, wall ADC and the necrosis/wall ADC ratio were 0.680, 0.068 and 0.942, respectively. A wall/necrosis ADC ratio cut-off value of 1.18 demonstrated a sensitivity of 97%, specificity of 93%, a positive-predictive value of 95%, a negative-predictive value of 96% and an accuracy of 95% in determining the malignant nature of necrotic breast lesions. There was a good intra- and interclass reliability for the ADC values of both necrosis and wall. The necrosis/wall ADC ratio appears to be a reliable and promising tool for discriminating breast carcinomas from abscesses using DWI. Advances in knowledge: ADC values of the necrosis obtained by DWI are valuable for malignant-benign differentiation in necrotic breast lesions. The necrosis/wall ADC ratio appears to be a reliable and promising tool in the breast imaging field.

A simple working classification proposed for the latrogenic lesions of teeth and associated structures in the oral cavity.

PubMed

Shamim, Thorakkal

2013-09-01

Iatrogenic lesions can affect both hard and soft tissues in the oral cavity, induced by the dentist's activity, manner or therapy. There is no approved simple working classification for the iatrogenic lesions of teeth and associated structures in the oral cavity in the literature. A simple working classification is proposed here for iatrogenic lesions of teeth and associated structures in the oral cavity based on its relation with dental specialities. The dental specialities considered in this classification are conservative dentistry and endodontics, orthodontics, oral and maxillofacial surgery and prosthodontics. This classification will be useful for the dental clinician who is dealing with diseases of oral cavity.

Shear-wave elastography in breast ultrasonography: the state of the art

PubMed Central

2017-01-01

Shear-wave elastography (SWE) is a recently developed ultrasound technique that can visualize and measure tissue elasticity. In breast ultrasonography, SWE has been shown to be useful for differentiating benign breast lesions from malignant breast lesions, and it has been suggested that SWE enhances the diagnostic performance of ultrasonography, potentially improving the specificity of conventional ultrasonography using the Breast Imaging Reporting and Data System criteria. More recently, not only has SWE been proven useful for the diagnosis of breast cancer, but has also been shown to provide valuable information that can be used as a preoperative predictor of the prognosis or response to chemotherapy. PMID:28513127

Minimal invasive complete excision of benign breast tumors using a three-dimensional ultrasound-guided mammotome vacuum device.

PubMed

Baez, E; Huber, A; Vetter, M; Hackelöer, B-J

2003-03-01

The aim of this study was to evaluate the use of three-dimensional (3D) ultrasonography in the complete excision of benign breast tumors using ultrasound-guided vacuum-assisted core-needle biopsy (Mammotome). A protocol for the management of benign breast tumors is proposed. Twenty consecutive patients with sonographically benign breast lesions underwent 3D ultrasound-guided mammotome biopsy under local anesthesia. The indication for surgical biopsy was a solid lesion with benign characteristics on both two-dimensional (2D) and 3D ultrasound imaging, increasing in size over time or causing pain or irritation. Preoperatively, the size of the lesion was assessed using 2D and 3D volumetry. During vacuum biopsy the needle was visualized sonographically in all three dimensions, including the coronal plane. Excisional biopsy was considered complete when no residual tumor tissue could be seen sonographically. Ultrasonographic follow-up examinations were performed on the following day and 3-6 months later to assess residual tissue and scarring. All lesions were histologically benign. Follow-up examinations revealed complete excision of all lesions of < 1.5 mL in volume as assessed by 3D volumetry. 3D ultrasonographic volume assessment was more accurate than 2D using the ellipsoid formula or assessment of the maximum diameter for the prediction of complete excision of the tumor. No bleeding or infections occurred postoperatively and no scarring was seen ultrasonographically on follow-up examinations. Ultrasound-guided vacuum-assisted biopsy allows complete excision of benign breast lesions that are

A support vector machine designed to identify breasts at high risk using multi-probe generated REIS signals: a preliminary assessment

NASA Astrophysics Data System (ADS)

Gur, David; Zheng, Bin; Lederman, Dror; Dhurjaty, Sreeram; Sumkin, Jules; Zuley, Margarita

2010-02-01

A new resonance-frequency based electronic impedance spectroscopy (REIS) system with multi-probes, including one central probe and six external probes that are designed to contact the breast skin in a circular form with a radius of 60 millimeters to the central ("nipple") probe, has been assembled and installed in our breast imaging facility. We are conducting a prospective clinical study to test the performance of this REIS system in identifying younger women (< 50 years old) at higher risk for having or developing breast cancer. In this preliminary analysis, we selected a subset of 100 examinations. Among these, 50 examinations were recommended for a biopsy due to detection of a highly suspicious breast lesion and 50 were determined negative during mammography screening. REIS output signal sweeps that we used to compute an initial feature included both amplitude and phase information representing differences between corresponding (matched) EIS signal values acquired from the left and right breasts. A genetic algorithm was applied to reduce the feature set and optimize a support vector machine (SVM) to classify the REIS examinations into "biopsy recommended" and "non-biopsy" recommended groups. Using the leave-one-case-out testing method, the classification performance as measured by the area under the receiver operating characteristic (ROC) curve was 0.816 +/- 0.042. This pilot analysis suggests that the new multi-probe-based REIS system could potentially be used as a risk stratification tool to identify pre-screened young women who are at higher risk of having or developing breast cancer.

Diagnostic value of virtual touch tissue imaging quantification for benign and malignant breast lesions with different sizes

PubMed Central

Liu, Hui; Zhao, Li-Xia; Xu, Guang; Yao, Ming-Hua; Zhang, Ai-Hong; Xu, Hui-Xiong; Wu, Rong

2015-01-01

The study was to explore diagnostic value of the virtual touch tissue imaging quantification (VTIQ) in distinguishing benign and malignant breast lesions of variable sizes. We performed conventional ultrasound and VTIQ in 139 breast lesions. The lesions were categorized into three groups according to size (group 1, ≤ 10 mm; group 2, 10-20 mm; and group 3, > 20 mm), and their mean, min, and max shear wave velocities (SWVs) were measured. Diagnoses were confirmed by pathological examination after surgery or needle biopsy. Receiver-operating characteristic curves (ROC) were constructed to determine the optimum cut-off values, calculate the area under curve (AUC), the sensitivity, specificity and accuracy for each velocity. For all groups, the mean, min, and max SWVs of malignant lesions were significantly higher than those of benign lesions (P < 0.05). The cut-off values of mean, min, and max SWVs were not significantly different among the three groups. In addition, the diagnostic performance of mean, min, and max SWV values is analogous, regardless of lesion size. In conclusion, VTIQ is a strong complement to conventional ultrasound, which is a promising method in the differential diagnosis of the breast lesions with different sizes. Further studies validate our results as well as reduce the number of unnecessary biopsies, regardless of size is warranted. PMID:26550234

[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.

Study of nuclear morphometry on cytology specimens of benign and malignant breast lesions: A study of 122 cases

PubMed Central

Kashyap, Anamika; Jain, Manjula; Shukla, Shailaja; Andley, Manoj

2017-01-01

Background: Breast cancer has emerged as a leading site of cancer among women in India. Fine needle aspiration cytology (FNAC) has been routinely applied in assessment of breast lesions. Cytological evaluation in breast lesions is subjective with a “gray zone” of 6.9–20%. Quantitative evaluation of nuclear size, shape, texture, and density parameters by morphometry can be of diagnostic help in breast tumor. Aims: To apply nuclear morphometry on cytological breast aspirates and assess its role in differentiating between benign and malignant breast lesions with derivation of suitable cut-off values between the two groups. Settings and Designs: The present study was a descriptive cross-sectional hospital-based study of nuclear morphometric parameters of benign and malignant cases. Materials and Methods: The study included 50 benign breast disease (BBD), 8 atypical ductal hyperplasia (ADH), and 64 carcinoma cases. Image analysis was performed on Papanicolaou-stained FNAC slides by Nikon Imaging Software (NIS)–Elements Advanced Research software (Version 4.00). Nuclear morphometric parameters analyzed included 5 nuclear size, 2 shape, 4 texture, and 2 density parameters. Results: Nuclear morphometry could differentiate between benign and malignant aspirates with a gradually increasing nuclear size parameters from BBD to ADH to carcinoma. Cut-off values of 31.93 μm2, 6.325 μm, 5.865 μm, 7.855 μm, and 21.55 μm for mean nuclear area, equivalent diameter, minimum feret, maximum ferret, and perimeter, respectively, were derived between benign and malignant cases, which could correctly classify 7 out of 8 ADH cases. Conclusion: Nuclear morphometry is a highly objective tool that could be used to supplement FNAC in differentiating benign from malignant lesions, with an important role in cases with diagnostic dilemma. PMID:28182052

Study of nuclear morphometry on cytology specimens of benign and malignant breast lesions: A study of 122 cases.

PubMed

Kashyap, Anamika; Jain, Manjula; Shukla, Shailaja; Andley, Manoj

2017-01-01

Breast cancer has emerged as a leading site of cancer among women in India. Fine needle aspiration cytology (FNAC) has been routinely applied in assessment of breast lesions. Cytological evaluation in breast lesions is subjective with a "gray zone" of 6.9-20%. Quantitative evaluation of nuclear size, shape, texture, and density parameters by morphometry can be of diagnostic help in breast tumor. To apply nuclear morphometry on cytological breast aspirates and assess its role in differentiating between benign and malignant breast lesions with derivation of suitable cut-off values between the two groups. The present study was a descriptive cross-sectional hospital-based study of nuclear morphometric parameters of benign and malignant cases. The study included 50 benign breast disease (BBD), 8 atypical ductal hyperplasia (ADH), and 64 carcinoma cases. Image analysis was performed on Papanicolaou-stained FNAC slides by Nikon Imaging Software (NIS)-Elements Advanced Research software (Version 4.00). Nuclear morphometric parameters analyzed included 5 nuclear size, 2 shape, 4 texture, and 2 density parameters. Nuclear morphometry could differentiate between benign and malignant aspirates with a gradually increasing nuclear size parameters from BBD to ADH to carcinoma. Cut-off values of 31.93 μm 2 , 6.325 μm, 5.865 μm, 7.855 μm, and 21.55 μm for mean nuclear area, equivalent diameter, minimum feret, maximum ferret, and perimeter, respectively, were derived between benign and malignant cases, which could correctly classify 7 out of 8 ADH cases. Nuclear morphometry is a highly objective tool that could be used to supplement FNAC in differentiating benign from malignant lesions, with an important role in cases with diagnostic dilemma.

Combination of two-dimensional shear wave elastography with ultrasound breast imaging reporting and data system in the diagnosis of breast lesions: a new method to increase the diagnostic performance.

PubMed

Li, Dan-Dan; Xu, Hui-Xiong; Guo, Le-Hang; Bo, Xiao-Wan; Li, Xiao-Long; Wu, Rong; Xu, Jun-Mei; Zhang, Yi-Feng; Zhang, Kun

2016-09-01

To evaluate the diagnostic performance of a new method of combined two-dimensional shear wave elastography (i.e. virtual touch imaging quantification, VTIQ) and ultrasound (US) Breast Imaging Reporting and Data System (BI-RADS) in the differential diagnosis of breast lesions. From September 2014 to December 2014, 276 patients with 296 pathologically proven breast lesions were enrolled in this study. The conventional US images were interpreted by two independent readers. The diagnosis performances of BI-RADS and combined BI-RADS and VTIQ were evaluated, including the area under the receiver operating characteristic curve (AUROC), sensitivity and specificity. Observer consistency was also evaluated. Pathologically, 212 breast lesions were benign and 84 were malignant. Compared with BI-RADS alone, the AUROCs and specificities of the combined method for both readers increased significantly (AUROC: 0.862 vs. 0.693 in reader 1, 0.861 vs. 0.730 in reader 2; specificity: 91.5 % vs. 38.7 % in reader 1, 94.8 % vs. 47.2 % in reader 2; all P < .05). The Kappa value between the two readers for BI-RADS assessment was 0.614, and 0.796 for the combined method. The combined VTIQ and BI-RADS had a better diagnostic performance in the diagnosis of breast lesions in comparison with BI-RADS alone. • Combination of conventional ultrasound and elastography distinguishes breast cancers more effectively. • Combination of conventional ultrasound and elastography increases observer consistency. • BI-RADS weights more than the 2D-SWE with an increase in malignancy probability.

A Computer-Aided Diagnosis System for Breast Cancer Combining Digital Mammography and Genomics

DTIC Science & Technology

2006-05-01

Huang, "Breast cancer diagnosis using self-organizing map for sonography." Ultrasound Med. Biol. 26, 405 (2000). 20 K. Horsch, M.L. Giger, L.A. Venta ...L.A. Venta , "Performance of computer-aided diagnosis in the interpretation of lesions on breast sonography." Acad Radiol 11, 272 (2004). 22 W. Chen...418. 27. Horsch K, Giger ML, Vyborny CJ, Venta LA. Performance of computer-aided diagnosis in the interpretation of lesions on breast sonography

[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.

Primary epidermoid carcinoma of the breast presenting as a breast abscess and sepsis.

PubMed

Damin, Andrea Pires; Nascimento, Fernanda Costa; Andreola, João Batista; Cerutti, Talita Haubert; Roehe, Adriana; Damin, Daniel Carvalho

2011-12-01

Squamous cell carcinoma (SCC) of the breast is an extremely rare form of cancer, accounting for approximately 0.04% of all malignant breast tumors. To date, only a limited number of cases of SCC of the breast have been reported, and most of them presented like the usual breast carcinomas. A 39-year-old woman presented with a large breast abscess and signs of sepsis. After surgical debridement of the lesion, histopathological examination of the abscess capsule revealed the presence of SCC of the breast. The definitive treatment for the tumor consisted of modified radical mastectomy with resection of the residual lesion in the right breast. This unusual case illustrates how an apparently benign disorder such as a breast abscess might be related to a clinically occult malignancy. A review of the literature on SCC of the breast is presented.

Strategies to Increase Cancer Detection: Review of True-Positive and False-Negative Results at Digital Breast Tomosynthesis Screening

PubMed Central

Weinstein, Susan P.; McDonald, Elizabeth S.; Conant, Emily F.

2016-01-01

Digital breast tomosynthesis (DBT) represents a valuable addition to breast cancer screening by decreasing recall rates while increasing cancer detection rates. The increased accuracy achieved with DBT is due to the quasi–three-dimensional format of the reconstructed images and the ability to “scroll through” breast tissue in the reconstructed images, thereby reducing the effect of tissue superimposition found with conventional planar digital mammography. The margins of both benign and malignant lesions are more conspicuous at DBT, which allows improved lesion characterization, increased reader confidence, and improved screening outcomes. However, even with the improvements in accuracy achieved with DBT, there remain differences in breast cancer conspicuity by mammographic view. Early data suggest that breast cancers may be more conspicuous on craniocaudal (CC) views than on mediolateral oblique (MLO) views. While some very laterally located breast cancers may be visualized on only the MLO view, the increased conspicuity of cancers on the CC view compared with the MLO view suggests that DBT screening should be performed with two-view imaging. Even with the improved conspicuity of lesions at DBT, there may still be false-negative studies. Subtle lesions seen on only one view may be discounted, and dense and/or complex tissue patterns may make some cancers occult or extremely difficult to detect. Therefore, radiologists should be cognizant of both perceptual and cognitive errors to avoid potential pitfalls in lesion detection and characterization. ©RSNA, 2016 Online supplemental material is available for this article. PMID:27715711

Safety and feasibility of breast lesion localization using magnetic seeds (Magseed): a multi-centre, open-label cohort study.

PubMed

Harvey, James R; Lim, Yit; Murphy, John; Howe, Miles; Morris, Julie; Goyal, Amit; Maxwell, Anthony J

2018-06-01

Wire localization has several disadvantages, notably wire migration and difficulty scheduling the procedure close to surgery. Radioactive seed localization overcomes these disadvantages, but implementation is limited due to radiation safety requirements. Magnetic seeds potentially offer the logistical benefits and transcutaneous detection equivalence of a radioactive seed, with easier implementation. This study was designed to evaluate the feasibility and safety of using magnetic seeds for breast lesion localization. A two-centre open-label cohort study to assess the feasibility and safety of magnetic seed (Magseed) localization of breast lesions. Magseeds were placed under radiological guidance into women having total mastectomy surgery. The primary outcome measure was seed migration distance. Secondary outcome measures included accuracy of placement, ease of transcutaneous detection, seed integrity and safety. Twenty-nine Magseeds were placed into the breasts of 28 patients under ultrasound guidance. There was no migration of the seeds between placement and surgery. Twenty-seven seeds were placed directly in the target lesion with the other seeds being 2 and 3 mm away. All seeds were detectable transcutaneously in all breast sizes and at all depths. There were no complications or safety issues. Magnetic seeds are a feasible and safe method of breast lesion localization. They can be accurately placed, demonstrate no migration in this feasibility study and are detectable in all sizes and depths of breast tissue. Now that safety and feasibility have been demonstrated, further clinical studies are required to evaluate the seed's effectiveness in wide local excision surgery.

Non-invasive optical estimate of tissue composition to differentiate malignant from benign breast lesions: A pilot study

NASA Astrophysics Data System (ADS)

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

2017-01-01

Several techniques are being investigated as a complement to screening mammography, to reduce its false-positive rate, but results are still insufficient to draw conclusions. This initial study explores time domain diffuse optical imaging as an adjunct method to classify non-invasively malignant vs benign breast lesions. We estimated differences in tissue composition (oxy- and deoxyhemoglobin, lipid, water, collagen) and absorption properties between lesion and average healthy tissue in the same breast applying a perturbative approach to optical images collected at 7 red-near infrared wavelengths (635-1060 nm) from subjects bearing breast lesions. The Discrete AdaBoost procedure, a machine-learning algorithm, was then exploited to classify lesions based on optically derived information (either tissue composition or absorption) and risk factors obtained from patient’s anamnesis (age, body mass index, familiarity, parity, use of oral contraceptives, and use of Tamoxifen). Collagen content, in particular, turned out to be the most important parameter for discrimination. Based on the initial results of this study the proposed method deserves further investigation.

Angiosonography in suspicious breast lesions with non-diagnostic FNAC: comparison with power Doppler US.

PubMed

Caumo, F; Carbognin, G; Casarin, A; Pinali, L; Vasori, S; D'Onofrio, M; Pozzi Mucelli, R

2006-02-01

The purpose of this study was to evaluate the accuracy of angiosonography in comparison with colour Doppler ultrasound (US) in the discrimination of suspicious breast lesions with nondiagnostic fine-needle aspiration cytology (FNAC). Pre-operative Power Doppler US and angiosonography were prospectively performed in 20 suspicious breast lesions with non-diagnostic FNAC. A second-generation US contrast agent was utilised with a high-frequency transducer and a contrast-specific algorithm (low acoustic pressure CnTI). The enhancement characteristics of all lesions were analysed using qualitative and quantitative parameters obtained from time-intensity curves with the different imaging modalities. The final diagnosis was confirmed at pathology in all cases. Microvessel density (MVD) was assessed in the surgical specimen using CD34. The correct assessment of biological behaviour was achieved in all cases by angiosonography (sensitivity of 100%; specificity of 91%) and colour Doppler US (45% sensitivity; 78% specificity). MVD correlated with the biological behaviour. Angiosonography is more accurate than colour Doppler US in the correct assessment of biological behaviour of suspicious breast lesions.

Sampling probability distributions of lesions in mammograms

NASA Astrophysics Data System (ADS)

Looney, P.; Warren, L. M.; Dance, D. R.; Young, K. C.

2015-03-01

One approach to image perception studies in mammography using virtual clinical trials involves the insertion of simulated lesions into normal mammograms. To facilitate this, a method has been developed that allows for sampling of lesion positions across the cranio-caudal and medio-lateral radiographic projections in accordance with measured distributions of real lesion locations. 6825 mammograms from our mammography image database were segmented to find the breast outline. The outlines were averaged and smoothed to produce an average outline for each laterality and radiographic projection. Lesions in 3304 mammograms with malignant findings were mapped on to a standardised breast image corresponding to the average breast outline using piecewise affine transforms. A four dimensional probability distribution function was found from the lesion locations in the cranio-caudal and medio-lateral radiographic projections for calcification and noncalcification lesions. Lesion locations sampled from this probability distribution function were mapped on to individual mammograms using a piecewise affine transform which transforms the average outline to the outline of the breast in the mammogram. The four dimensional probability distribution function was validated by comparing it to the two dimensional distributions found by considering each radiographic projection and laterality independently. The correlation of the location of the lesions sampled from the four dimensional probability distribution function across radiographic projections was shown to match the correlation of the locations of the original mapped lesion locations. The current system has been implemented as a web-service on a server using the Python Django framework. The server performs the sampling, performs the mapping and returns the results in a javascript object notation format.

Relationship between ultrasound elastography and myofibroblast distribution in breast cancer and its clinical significance

PubMed Central

Hao, Yi; Guo, Xia; Ma, Binlin; Zhu, Lin; Liu, Lisha

2016-01-01

The study investigated the relationship between ultrasound elastography (USE) scoring and myofibroblast distribution with expression features of α-SMA + /CD34− in patients of Uyghur and Han ethnicities with breast masses in Xinjiang, China. The data was used to evaluate its clinical significance in the early diagnosis of breast cancer. A total of 300 patients with breast masses were included in the study, which involved conventional sonography and USE, with histopathologic diagnosis as the reference standard. Myofibroblast distribution was investigated by detecting the expression levels of α-SMA and CD34 in lesions using immunohistochemistry and real-time PCR. Out of 300 lesions, 185 were histologically malignant and 115 benign. The mean elasticity score for malignant lesions was significantly higher than for benign lesions. The expression level of α-SMA was elevated while the expression level of CD34 was lower in malignancies, compared with benign lesions. The expression of α-SMA was positively associated with the USE scores, while a negative relationship was observed between CD34 expression and USE scoring. The combination of USE and molecular diagnosis provides a promising modality for the early diagnosis and evaluation of the risks in particular types of breast cancer. PMID:26846996

Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study.

PubMed

Ortiz-Ramón, Rafael; Larroza, Andrés; Ruiz-España, Silvia; Arana, Estanislao; Moratal, David

2018-05-14

To examine the capability of MRI texture analysis to differentiate the primary site of origin of brain metastases following a radiomics approach. Sixty-seven untreated brain metastases (BM) were found in 3D T1-weighted MRI of 38 patients with cancer: 27 from lung cancer, 23 from melanoma and 17 from breast cancer. These lesions were segmented in 2D and 3D to compare the discriminative power of 2D and 3D texture features. The images were quantized using different number of gray-levels to test the influence of quantization. Forty-three rotation-invariant texture features were examined. Feature selection and random forest classification were implemented within a nested cross-validation structure. Classification was evaluated with the area under receiver operating characteristic curve (AUC) considering two strategies: multiclass and one-versus-one. In the multiclass approach, 3D texture features were more discriminative than 2D features. The best results were achieved for images quantized with 32 gray-levels (AUC = 0.873 ± 0.064) using the top four features provided by the feature selection method based on the p-value. In the one-versus-one approach, high accuracy was obtained when differentiating lung cancer BM from breast cancer BM (four features, AUC = 0.963 ± 0.054) and melanoma BM (eight features, AUC = 0.936 ± 0.070) using the optimal dataset (3D features, 32 gray-levels). Classification of breast cancer and melanoma BM was unsatisfactory (AUC = 0.607 ± 0.180). Volumetric MRI texture features can be useful to differentiate brain metastases from different primary cancers after quantizing the images with the proper number of gray-levels. • Texture analysis is a promising source of biomarkers for classifying brain neoplasms. • MRI texture features of brain metastases could help identifying the primary cancer. • Volumetric texture features are more discriminative than traditional 2D texture features.

Fine needle aspiration cytology of radiation-induced changes in nonneoplastic breast lesions. Possible pitfalls in cytodiagnosis

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

Peterse, J.L.; Thunnissen, F.B.; van Heerde, P.

1989-03-01

The range of radiation-induced changes in fine needle aspiration (FNA) smears of the breast is described. In 41 of more than 800 patients who underwent breast-conserving treatment, a palpable breast lesion developed, and FNA was performed. In six cases, a recurrent carcinoma was present. In the remaining cases, three patterns of nonneoplastic lesions could be discerned: epithelial atypia (14 cases), fat necrosis (10 cases) and poorly cellular smears without epithelial atypia or fat necrosis (13 cases). It is important to be familiar with the patterns of radiation-induced epithelial atypia, since such atypia may lead to a misdiagnosis of recurrent carcinoma.more » These atypical cells may show impressive anisocytosis and anisonucleosis; however, the nuclear/cytoplasmic ratio remains normal and an admixture of bipolar cells is present. Cell dissociation and necrotic cell debris, as often seen in breast cancer smears, were never encountered in FNA smears from radiated nonneoplastic breasts.« less

Association between power law coefficients of the anatomical noise power spectrum and lesion detectability in breast imaging modalities

NASA Astrophysics Data System (ADS)

Chen, Lin; Abbey, Craig K.; Boone, John M.

2013-03-01

Previous research has demonstrated that a parameter extracted from a power function fit to the anatomical noise power spectrum, β, may be predictive of breast mass lesion detectability in x-ray based medical images of the breast. In this investigation, the value of β was compared with a number of other more widely used parameters, in order to determine the relationship between β and these other parameters. This study made use of breast CT data sets, acquired on two breast CT systems developed in our laboratory. A total of 185 breast data sets in 183 women were used, and only the unaffected breast was used (where no lesion was suspected). The anatomical noise power spectrum computed from two-dimensional region of interests (ROIs), was fit to a power function (NPS(f) = α f-β), and the exponent parameter (β) was determined using log/log linear regression. Breast density for each of the volume data sets was characterized in previous work. The breast CT data sets analyzed in this study were part of a previous study which evaluated the receiver operating characteristic (ROC) curve performance using simulated spherical lesions and a pre-whitened matched filter computer observer. This ROC information was used to compute the detectability index as well as the sensitivity at 95% specificity. The fractal dimension was computed from the same ROIs which were used for the assessment of β. The value of β was compared to breast density, detectability index, sensitivity, and fractal dimension, and the slope of these relationships was investigated to assess statistical significance from zero slope. A statistically significant non-zero slope was considered to be a positive association in this investigation. All comparisons between β and breast density, detectability index, sensitivity at 95% specificity, and fractal dimension demonstrated statistically significant association with p < 0.001 in all cases. The value of β was also found to be associated with patient age and breast diameter, parameters both related to breast density. In all associations between other parameters, lower values of β were associated with increased breast cancer detection performance. Specifically, lower values of β were associated with lower breast density, higher detectability index, higher sensitivity, and lower fractal dimension values. While causality was not and probably cannot be demonstrated, the strong, statistically significant association between the β metric and the other more widely used parameters suggest that β may be considered as a surrogate measure for breast cancer detection performance. These findings are specific to breast parenchymal patterns and mass lesions only.

Classification of full-thickness rotator cuff lesions: a review

PubMed Central

Lädermann, Alexandre; Burkhart, Stephen S.; Hoffmeyer, Pierre; Neyton, Lionel; Collin, Philippe; Yates, Evan; Denard, Patrick J.

2016-01-01

Rotator cuff lesions (RCL) have considerable variability in location, tear pattern, functional impairment, and repairability. Historical classifications for differentiating these lesions have been based upon factors such as the size and shape of the tear, and the degree of atrophy and fatty infiltration. Additional recent descriptions include bipolar rotator cuff insufficiency, ‘Fosbury flop tears’, and musculotendinous lesions. Recommended treatment is based on the location of the lesion, patient factors and associated pathology, and often includes personal experience and data from case series. Development of a more comprehensive classification which integrates historical and newer descriptions of RCLs may help to guide treatment further. Cite this article: Lädermann A, Burkhart SS, Hoffmeyer P, et al. Classification of full thickness rotator cuff lesions: a review. EFORT Open Rev 2016;1:420-430. DOI: 10.1302/2058-5241.1.160005. PMID:28461921

Shear-wave elastography quantitative assessment of the male breast: added value to distinguish benign and malignant palpable masses.

PubMed

Crombé, Amandine; Hurtevent-Labrot, Gabrielle; Asad-Syed, Maryam; Palussière, Jean; MacGrogan, Gaetan; Kind, Michèle; Ferron, Stéphane

2018-02-01

To evaluate the ability of shear-wave elastography (SWE) to distinguish between benign and malignant palpable masses of the adult male breast. Clinical examination, mammography, B-mode and Doppler ultrasound findings and SWE quantitative parameters were compared in 50 benign lesions (including 40 gynaecomastias) and 15 malignant lesions (invasive ductal carcinomas) from 65 patients who were consecutively addressed for specialized advice at our comprehensive cancer centre. Mean elasticity (El mean), maximum elasticity (El max), El mean of the surrounding fatty tissue and lesion to fat ratio (El ratio) were reported for each patient. Malignant masses displayed significantly higher El mean (p < 0.0001), El max (p < 0.0001) and El ratio (p < 0.0001) compared to benign masses without overlap of values between the two groups. By adding SWE to clinical examination, mammography and ultrasound, all the lesions would have been retrospectively correctly diagnosed as benign or malignant. One false positive could have been downstaged, 14/65 undetermined masses could have been correctly reclassified as 4 malignant and 10 benign lesions, for which biopsies could have consequently been avoided. Evaluation of male breast palpable masses by SWE demonstrates that malignant masses are significantly stiffer lesions and may improve diagnostic management when clinical examination, mammography and conventional ultrasound are doubtful. Advances in knowledge: Quantitative SWE is feasible in male breast and could be of great interest to help classify doubtful lesions after classical clinical and radiological evaluations, probably because of different anatomy and different tumours epidemiology compared with female breast.

Automatic breast tissue density estimation scheme in digital mammography images

NASA Astrophysics Data System (ADS)

Menechelli, Renan C.; Pacheco, Ana Luisa V.; Schiabel, Homero

2017-03-01

Cases of breast cancer have increased substantially each year. However, radiologists are subject to subjectivity and failures of interpretation which may affect the final diagnosis in this examination. The high density features in breast tissue are important factors related to these failures. Thus, among many functions some CADx (Computer-Aided Diagnosis) schemes are classifying breasts according to the predominant density. In order to aid in such a procedure, this work attempts to describe automated software for classification and statistical information on the percentage change in breast tissue density, through analysis of sub regions (ROIs) from the whole mammography image. Once the breast is segmented, the image is divided into regions from which texture features are extracted. Then an artificial neural network MLP was used to categorize ROIs. Experienced radiologists have previously determined the ROIs density classification, which was the reference to the software evaluation. From tests results its average accuracy was 88.7% in ROIs classification, and 83.25% in the classification of the whole breast density in the 4 BI-RADS density classes - taking into account a set of 400 images. Furthermore, when considering only a simplified two classes division (high and low densities) the classifier accuracy reached 93.5%, with AUC = 0.95.

Giant fibroadenomatoid hyperplasia of the breast: a case report.

PubMed

Zhang, Hao; Wang, Xin-Lu; Ren, Wei-Dong; Shi, Tie-Mei

2014-01-01

Fibroadenomatoid hyperplasia of the breast (FAHB) is a rare benign breast lesion and its clinical features are similar to fibroadenoma and fibrocystic changes. FAHB has been previously termed sclerosing lobular hyperplasia, fibroadenomatosis, fibroadenomatoid change, or fibroadenomatoid mastopathy. Typically, FAHB is derived from stroma and epithelia. The pathologic characteristics of FAHB are microfocal lobulocentric proliferation of stroma accompanied by epithelial and myoepithelial components resembling similar histological changes, as found in fibroadenoma, apocrine hyperplasia, intraductal hyperplasia, and lobular hyperplasia. FAHB could be present as a localized or diffused pattern in pathology. Most cases show no well-circumscribed mass lesions and no apparent capsules; it is usually identified as an incidental finding in other benign lesions or in random sampling in cancerous breast tissues. FAHB is categorized as a benign proliferative breast disease and it has previously been reported; however, the authors believe this study may be the first case with two giant masses reported. Fiber adenoma hyperplasia is a rare cystic hyperplasia of breast pathology and its ultrasonographic manifestations are easily confused with breast cancer. Comparative MRI ultrasound analysis will help make the differential diagnosis. © 2014 S. Karger AG, Basel.

Image patch-based method for automated classification and detection of focal liver lesions on CT

NASA Astrophysics Data System (ADS)

Safdari, Mustafa; Pasari, Raghav; Rubin, Daniel; Greenspan, Hayit

2013-03-01

We developed a method for automated classification and detection of liver lesions in CT images based on image patch representation and bag-of-visual-words (BoVW). BoVW analysis has been extensively used in the computer vision domain to analyze scenery images. In the current work we discuss how it can be used for liver lesion classification and detection. The methodology includes building a dictionary for a training set using local descriptors and representing a region in the image using a visual word histogram. Two tasks are described: a classification task, for lesion characterization, and a detection task in which a scan window moves across the image and is determined to be normal liver tissue or a lesion. Data: In the classification task 73 CT images of liver lesions were used, 25 images having cysts, 24 having metastasis and 24 having hemangiomas. A radiologist circumscribed the lesions, creating a region of interest (ROI), in each of the images. He then provided the diagnosis, which was established either by biopsy or clinical follow-up. Thus our data set comprises 73 images and 73 ROIs. In the detection task, a radiologist drew ROIs around each liver lesion and two regions of normal liver, for a total of 159 liver lesion ROIs and 146 normal liver ROIs. The radiologist also demarcated the liver boundary. Results: Classification results of more than 95% were obtained. In the detection task, F1 results obtained is 0.76. Recall is 84%, with precision of 73%. Results show the ability to detect lesions, regardless of shape.

Magnetic resonance imaging-radioguided occult lesion localization (ROLL) in breast cancer using Tc-99m macro-aggregated albumin and distilled water control

PubMed Central

2013-01-01

Background Magnetic resonance imaging (MRI) guided wire localization presents several challenges apart from the technical difficulties. An alternative to this conventional localization method using a wire is the radio-guided occult lesion localization (ROLL), more related to safe surgical margins and reductions in excision volume. The purpose of this study was to establish a safe and reliable magnetic resonance imaging-radioguided occult lesion localization (MRI-ROLL) technique and to report our initial experience with the localization of nonpalpable breast lesions only observed on MRI. Methods Sixteen women (mean age 53.2 years) with 17 occult breast lesions underwent radio-guided localization in a 1.5-T MR system using a grid-localizing system. All patients had a diagnostic MRI performed prior to the procedure. An intralesional injection of Technetium-99m macro-aggregated albumin followed by distilled water was performed. After the procedure, scintigraphy was obtained. Surgical resection was performed with the help of a gamma detector probe. The lesion histopathology and imaging concordance; the procedure’s positive predictive value (PPV), duration time, complications, and accuracy; and the rate of exactly excised lesions evaluated with MRI six months after the surgery were assessed. Results One lesion in one patient had to be excluded because the radioactive substance came back after the injection, requiring a wire placement. Of the remaining cases, there were four malignant lesions, nine benign lesions, and three high-risk lesions. Surgical histopathology and imaging findings were considered concordant in all benign and high-risk cases. The PPV of MRI-ROLL was greater if the indication for the initial MR examination was active breast cancer. The median procedure duration time was 26 minutes, and all included procedures were defined as accurate. The exact and complete lesion removal was confirmed in all (100%) patients who underwent six-month postoperative MRI (50%). Conclusions MRI-ROLL offers a precise, technically feasible, safe, and rapid means for performing preoperative MRI localizations in the breast. PMID:24044428

Nonpalpable breast tumors: diagnosis with stereotaxic localization and fine-needle aspiration

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

Dowlatshahi, K.; Gent, H.J.; Schmidt, R.

1989-02-01

Modern mammography is the most effective means of detecting nonpalpable breast cancers, but correct diagnosis for malignancy is made in only 20%-30% of the cases. The conventional method of lesion localization usually results in approximate placement of the hookwire in the breast. The authors report the results of stereotaxic localization, combined with fine-needle aspiration and cytologic study, performed in 528 cases. Clinically occult breast lesions were localized precisely (within 2 mm 96% of the time), sampled by means of a 23-gauge needle, and marked with either methylene blue or a hookwire for subsequent open excisional biopsy. The results indicate amore » sensitivity of 95%, specificity of 91%, and accuracy of 92% for the fine-needle aspiration procedure. This technique offers a significantly improved preoperative method of diagnosing small breast lesions with minimal pain, no complications, reduced cost, and no disfigurement or scar interfering with subsequent mammographic follow-up.« less

Whole breast tissue characterization with ultrasound tomography

NASA Astrophysics Data System (ADS)

Duric, Neb; Littrup, Peter; Li, Cuiping; Roy, Olivier; Schmidt, Steve; Seamans, John; Wallen, Andrea; Bey-Knight, Lisa

2015-03-01

A number of clinical trials have shown that screening ultrasound, supplemental to mammography, detects additional cancers in women with dense breasts. However, labor intensity, operator dependence and high recall rates have limited adoption. This paper describes the use of ultrasound tomography for whole-breast tissue stiffness measurements as a first step toward addressing the issue of high recall rates. The validation of the technique using an anthropomorphic phantom is described. In-vivo applications are demonstrated on 13 breast masses, indicating that lesion stiffness correlates with lesion type as expected. Comparison of lesion stiffness measurements with standard elastography was available for 11 masses and showed a strong correlation between the 2 measures. It is concluded that ultrasound tomography can map out the 3 dimensional distribution of tissue stiffness over the whole breast. Such a capability is well suited for screening where additional characterization may improve the specificity of screening ultrasound, thereby lowering barriers to acceptance.

Targeting Premalignant Lesions - Implications for Early Breast Cancer Detection and Intervention

DTIC Science & Technology

2017-04-01

lesions. Peptide conjugated AgNP were injected intravenously in mice and mammary glands were isolated and analyzed for nanoparticle accumulation by silver ...Furthermore, these probes will be used to develop targeted therapeutic nanoparticles for early intervention in breast cancer. 2. KEYWORDS...cancer (Months 18-24) (To be done) Specific Aim 3: Target premalignant lesions utilizing peptide-conjugated nanoparticles to prevent/delay

Classification of multiple sclerosis lesions using adaptive dictionary learning.

PubMed

Deshpande, Hrishikesh; Maurel, Pierre; Barillot, Christian

2015-12-01

This paper presents a sparse representation and an adaptive dictionary learning based method for automated classification of multiple sclerosis (MS) lesions in magnetic resonance (MR) images. Manual delineation of MS lesions is a time-consuming task, requiring neuroradiology experts to analyze huge volume of MR data. This, in addition to the high intra- and inter-observer variability necessitates the requirement of automated MS lesion classification methods. Among many image representation models and classification methods that can be used for such purpose, we investigate the use of sparse modeling. In the recent years, sparse representation has evolved as a tool in modeling data using a few basis elements of an over-complete dictionary and has found applications in many image processing tasks including classification. We propose a supervised classification approach by learning dictionaries specific to the lesions and individual healthy brain tissues, which include white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). The size of the dictionaries learned for each class plays a major role in data representation but it is an even more crucial element in the case of competitive classification. Our approach adapts the size of the dictionary for each class, depending on the complexity of the underlying data. The algorithm is validated using 52 multi-sequence MR images acquired from 13 MS patients. The results demonstrate the effectiveness of our approach in MS lesion classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

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%.

Breast MRI at Very Short TE (minTE): Image Analysis of minTE Sequences on Non-Fat-Saturated, Subtracted T1-Weighted Images.

PubMed

Wenkel, Evelyn; Janka, Rolf; Geppert, Christian; Kaemmerer, Nadine; Hartmann, Arndt; Uder, Michael; Hammon, Matthias; Brand, Michael

2017-02-01

Purpose  The aim was to evaluate a minimum echo time (minTE) protocol for breast magnetic resonance imaging (MRI) in patients with breast lesions compared to a standard TE (nTE) time protocol. Methods  Breasts of 144 women were examined with a 1.5 Tesla MRI scanner. Additionally to the standard gradient-echo sequence with nTE (4.8 ms), a variant with minimum TE (1.2 ms) was used in an interleaved fashion which leads to a better temporal resolution and should reduce the scan time by approximately 50 %. Lesion sizes were measured and the signal-to-noise ratio (SNR) as well as the contrast-to-noise ratio (CNR) were calculated. Subjective confidence was evaluated using a 3-point scale before looking at the nTE sequences (1 = very sure that I can identify a lesion and classify it, 2 = quite sure that I can identify a lesion and classify it, 3 = definitely want to see nTE for final assessment) and the subjective image quality of all examinations was evaluated using a four-grade scale (1 = sharp, 2 = slight blur, 3 = moderate blur and 4 = severe blur/not evaluable) for lesion and skin sharpness. Lesion morphology and contrast enhancement were also evaluated. Results  With minTE sequences, no lesion was rated with "definitely want to see nTE sequences for final assessment". The difference of the longitudinal and transverse diameter did not differ significantly (p > 0.05). With minTE, lesions and skin were rated to be significantly more blurry (p < 0.01 for lesions and p < 0.05 for skin). There was no difference between both sequences with respect to SNR, CNR, lesion morphology, contrast enhancement and detection of multifocal disease. Conclusion  Dynamic breast MRI with a minTE protocol is feasible without a major loss of information (SNR, CNR, lesion morphology, contrast enhancement and lesion sizes) and the temporal resolution can be increased by a factor of 2 using minTE sequences. Key points   · Increase of temporal resolution for a better in-flow curve.. · Dynamic breast MRI with a shorter TE time is possible without relevant loss of information.. · Possible decrease of the overall scan time.. Citation Format · Wenkel E, Janka R, Geppert C et al. Breast MRI at Very Short TE (minTE): Image Analysis of minTE Sequences on Non-Fat-Saturated, Subtracted T1-Weighted Images. Fortschr Röntgenstr 2017; 189: 137 - 145. © Georg Thieme Verlag KG Stuttgart · New York.

CFS-SMO based classification of breast density using multiple texture models.

PubMed

Sharma, Vipul; Singh, Sukhwinder

2014-06-01

It is highly acknowledged in the medical profession that density of breast tissue is a major cause for the growth of breast cancer. Increased breast density was found to be linked with an increased risk of breast cancer growth, as high density makes it difficult for radiologists to see an abnormality which leads to false negative results. Therefore, there is need for the development of highly efficient techniques for breast tissue classification based on density. This paper presents a hybrid scheme for classification of fatty and dense mammograms using correlation-based feature selection (CFS) and sequential minimal optimization (SMO). In this work, texture analysis is done on a region of interest selected from the mammogram. Various texture models have been used to quantify the texture of parenchymal patterns of breast. To reduce the dimensionality and to identify the features which differentiate between breast tissue densities, CFS is used. Finally, classification is performed using SMO. The performance is evaluated using 322 images of mini-MIAS database. Highest accuracy of 96.46% is obtained for two-class problem (fatty and dense) using proposed approach. Performance of selected features by CFS is also evaluated by Naïve Bayes, Multilayer Perceptron, RBF Network, J48 and kNN classifier. The proposed CFS-SMO method outperforms all other classifiers giving a sensitivity of 100%. This makes it suitable to be taken as a second opinion in classifying breast tissue density.

Whole-lesion histogram analysis metrics of the apparent diffusion coefficient as a marker of breast lesions characterization at 1.5 T.

PubMed

Bougias, H; Ghiatas, A; Priovolos, D; Veliou, K; Christou, A

2017-05-01

To retrospectively assess the role of whole-lesion apparent diffusion coefficient (ADC) in the characterization of breast tumors by comparing different histogram metrics. 49 patients with 53 breast lesions underwent magnetic resonance imaging (MRI). ADC histogram parameters, including the mean, mode, 10th/50th/90th percentile, skewness, kurtosis, and entropy ADCs, were derived for the whole-lesion volume in each patient. Mann-Whitney U-test, area under the receiver-operating characteristic curve (AUC) were used for statistical analysis. The mean, mode and 10th/50th/90th percentile ADC values were significantly lower in malignant lesions compared with benign ones (all P < 0.0001), while skewness was significantly higher in malignant lesions P = 0.02. However, no significant difference was found between entropy and kurtosis values in malignant lesions compared with benign ones (P = 0.06 and P = 1.00, respectively). Univariate logistic regression showed that 10th and 50th percentile ADC yielded the highest AUC (0.985; 95% confidence interval [CI]: 0.902, 1.000 and 0.982; 95% confidence interval [CI]: 0.896, 1.000 respectively), whereas kurtosis value yielded the lowest AUC (0.500; 95% CI: 0.355, 0.645), indicating that 10th and 50th percentile ADC values may be more accurate for lesion discrimination. Whole-lesion ADC histogram analysis could be a helpful index in the characterization and differentiation between benign and malignant breast lesions with the 10th and 50th percentile ADC be the most accurate discriminators. Copyright © 2017 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

SU-C-207B-04: Automated Segmentation of Pectoral Muscle in MR Images of Dense Breasts

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

Verburg, E; Waard, SN de; Veldhuis, WB

Purpose: To develop and evaluate a fully automated method for segmentation of the pectoral muscle boundary in Magnetic Resonance Imaging (MRI) of dense breasts. Methods: Segmentation of the pectoral muscle is an important part of automatic breast image analysis methods. Current methods for segmenting the pectoral muscle in breast MRI have difficulties delineating the muscle border correctly in breasts with a large proportion of fibroglandular tissue (i.e., dense breasts). Hence, an automated method based on dynamic programming was developed, incorporating heuristics aimed at shape, location and gradient features.To assess the method, the pectoral muscle was segmented in 91 randomly selectedmore » participants (mean age 56.6 years, range 49.5–75.2 years) from a large MRI screening trial in women with dense breasts (ACR BI-RADS category 4). Each MR dataset consisted of 178 or 179 T1-weighted images with voxel size 0.64 × 0.64 × 1.00 mm3. All images (n=16,287) were reviewed and scored by a radiologist. In contrast to volume overlap coefficients, such as DICE, the radiologist detected deviations in the segmented muscle border and determined whether the result would impact the ability to accurately determine the volume of fibroglandular tissue and detection of breast lesions. Results: According to the radiologist’s scores, 95.5% of the slices did not mask breast tissue in such way that it could affect detection of breast lesions or volume measurements. In 13.1% of the slices a deviation in the segmented muscle border was present which would not impact breast lesion detection. In 70 datasets (78%) at least 95% of the slices were segmented in such a way it would not affect detection of breast lesions, and in 60 (66%) datasets this was 100%. Conclusion: Dynamic programming with dedicated heuristics shows promising potential to segment the pectoral muscle in women with dense breasts.« less

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.

An evaluation of bone scans as screening procedures for occult metastases in primary breast cancer.

PubMed Central

Baker, R R; Holmes, E R; Alderson, P O; Khouri, N F; Wagner, H N

1977-01-01

Preoperative bone scans were obtained in 104 patients with operable breast cancer. Areas of increased radioactivity detected by the bone scan were correlated with appropriate radiographs. One of 64 patients (1.5%) with clinical Stage I and Stage II breast cancer had a metastatic lesion detected by the preoperative bone scan. In contrast, 10 of 41 patients (24%) with Stage III breast cancer had occult metastatic lesions detected by the preoperative bone scan. The majority of patients with abnormal bone scans and no radiographic evidence of a benign lesion to explain the cause of the increased radioactivity proved to have metastatic breast cancer on follow-examination. Even though 20% of patients with operable breast cancer will eventually develop bone metastases, our results indicate that preoperative bone scans are not an effective means of predicting which patients with Stage I and Stage II disease will develop metastatic breast cancer. Because of the considerably increased frequency of detection of occult metastases in patients with Stage III breast cancer, bone scans should be obtained routinely in the preoperative assessment of these patients. Images Figs. 1a and b. Figs. 2a and b. Figs. 3a-d. PMID:889378

Clinical practice guidelines from the French College of Gynecologists and Obstetricians (CNGOF): benign breast tumors - short text.

PubMed

Lavoué, Vincent; Fritel, Xavier; Antoine, Martine; Beltjens, Françoise; Bendifallah, Sofiane; Boisserie-Lacroix, Martine; Boulanger, Loic; Canlorbe, Geoffroy; Catteau-Jonard, Sophie; Chabbert-Buffet, Nathalie; Chamming's, Foucauld; Chéreau, Elisabeth; Chopier, Jocelyne; Coutant, Charles; Demetz, Julie; Guilhen, Nicolas; Fauvet, Raffaele; Kerdraon, Olivier; Laas, Enora; Legendre, Guillaume; Mathelin, Carole; Nadeau, Cédric; Naggara, Isabelle Thomassin; Ngô, Charlotte; Ouldamer, Lobna; Rafii, Arash; Roedlich, Marie-Noelle; Seror, Jérémy; Séror, Jean-Yves; Touboul, Cyril; Uzan, Catherine; Daraï, Emile

2016-05-01

Screening with breast ultrasound in combination with mammography is needed to investigate a clinical breast mass (Grade B), colored single-pore breast nipple discharge (Grade C), or mastitis (Grade C). The BI-RADS system is recommended for describing and classifying abnormal breast imaging findings. For a breast abscess, a percutaneous biopsy is recommended in the case of a mass or persistent symptoms (Grade C). For mastalgia, when breast imaging is normal, no MRI or breast biopsy is recommended (Grade C). Percutaneous biopsy is recommended for a BI-RADS category 4-5 mass (Grade B). For persistent erythematous nipple or atypical eczema lesions, a nipple biopsy is recommended (Grade C). For distortion and asymmetry, a vacuum core-needle biopsy is recommended due to the risk of underestimation by simple core-needle biopsy (Grade C). For BI-RADS category 4-5 microcalcifications without any ultrasound signal, a minimum 11-G vacuum core-needle biopsy is recommended (Grade B). In the absence of microcalcifications on radiography cores additional samples are recommended (Grade B). For atypical ductal hyperplasia, atypical lobular hyperplasia, lobular carcinoma in situ, flat epithelial atypia, radial scar and mucocele with atypia, surgical excision is commonly recommended (Grade C). Expectant management is feasible after multidisciplinary consensus. For these lesions, when excision margins are not clear, no new excision is recommended except for LCIS characterized as pleomorphic or with necrosis (Grade C). For grade 1 phyllodes tumor, surgical resection with clear margins is recommended. For grade 2 phyllodes tumor, 10mm margins are recommended (Grade C). For papillary breast lesions without atypia, complete disappearance of the radiological signal is recommended (Grade C). For papillary breast lesions with atypia, complete surgical excision is recommended (Grade C). Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

Prediction of occult invasive disease in ductal carcinoma in situ using computer-extracted mammographic features

NASA Astrophysics Data System (ADS)

Shi, Bibo; Grimm, Lars J.; Mazurowski, Maciej A.; Marks, Jeffrey R.; King, Lorraine M.; Maley, Carlo C.; Hwang, E. Shelley; Lo, Joseph Y.

2017-03-01

Predicting the risk of occult invasive disease in ductal carcinoma in situ (DCIS) is an important task to help address the overdiagnosis and overtreatment problems associated with breast cancer. In this work, we investigated the feasibility of using computer-extracted mammographic features to predict occult invasive disease in patients with biopsy proven DCIS. We proposed a computer-vision algorithm based approach to extract mammographic features from magnification views of full field digital mammography (FFDM) for patients with DCIS. After an expert breast radiologist provided a region of interest (ROI) mask for the DCIS lesion, the proposed approach is able to segment individual microcalcifications (MCs), detect the boundary of the MC cluster (MCC), and extract 113 mammographic features from MCs and MCC within the ROI. In this study, we extracted mammographic features from 99 patients with DCIS (74 pure DCIS; 25 DCIS plus invasive disease). The predictive power of the mammographic features was demonstrated through binary classifications between pure DCIS and DCIS with invasive disease using linear discriminant analysis (LDA). Before classification, the minimum redundancy Maximum Relevance (mRMR) feature selection method was first applied to choose subsets of useful features. The generalization performance was assessed using Leave-One-Out Cross-Validation and Receiver Operating Characteristic (ROC) curve analysis. Using the computer-extracted mammographic features, the proposed model was able to distinguish DCIS with invasive disease from pure DCIS, with an average classification performance of AUC = 0.61 +/- 0.05. Overall, the proposed computer-extracted mammographic features are promising for predicting occult invasive disease in DCIS.

Large palpable ductal carcinoma in situ is Her-2 positive with high nuclear grade.

PubMed

Monabati, Ahmad; Sokouti, Ali-Reza; Noori, Sadat Noori; Safaei, Akbar; Talei, Abd-Rasul; Omidvari, Shapoor; Azarpira, Negar

2015-01-01

Ductal carcinoma in situ (DCIS) of the breast is a heterogeneous group with variable clinical presentation. The exact molecular mechanism is not known why some ductal carcinomas may reach to such a large size but still remains in situ. Although, molecular classification of DCIS lesions and nuclear grading are important for identification of more aggressive lesions but it is not sufficient. Our aim was to examine the expression pattern of immunohistochemical (IHC) markers of ER, PR, HER-2 in palpable DCIS lesions and compare with clinicopathological findings. Our center is referral hospital from South of Iran. Samples were obtained from fifty four patients with a diagnosis of palpable DCIS. Equivocal (2+) case in HER-2 IHC testing was more characterized by chromogenic in situ hybridization. The positive frequency of HER2, ER, and PR was 92%, 48%, and 37% respectively. Palpable DCIS lesions were significantly more HER-2 positive (92%). The DCIS cases were more likely to be of high nuclear grade (grade III) and Her-2 positive cases were more likely to be of high nuclear grade than intermediate grade. All ER negative tumors had high nuclear grade. The Her-2 positivity is suggested as the most important factor responsible for marked in situ proliferation and production of palpable mass.

Large palpable ductal carcinoma in situ is Her-2 positive with high nuclear grade

PubMed Central

Monabati, Ahmad; Sokouti, Ali-Reza; Noori, Sadat Noori; Safaei, Akbar; Talei, Abd-Rasul; Omidvari, Shapoor; Azarpira, Negar

2015-01-01

Ductal carcinoma in situ (DCIS) of the breast is a heterogeneous group with variable clinical presentation. The exact molecular mechanism is not known why some ductal carcinomas may reach to such a large size but still remains in situ. Although, molecular classification of DCIS lesions and nuclear grading are important for identification of more aggressive lesions but it is not sufficient. Our aim was to examine the expression pattern of immunohistochemical (IHC) markers of ER, PR, HER-2 in palpable DCIS lesions and compare with clinicopathological findings. Our center is referral hospital from South of Iran. Samples were obtained from fifty four patients with a diagnosis of palpable DCIS. Equivocal (2+) case in HER-2 IHC testing was more characterized by chromogenic in situ hybridization. The positive frequency of HER2, ER, and PR was 92%, 48%, and 37% respectively. Palpable DCIS lesions were significantly more HER-2 positive (92%). The DCIS cases were more likely to be of high nuclear grade (grade III) and Her-2 positive cases were more likely to be of high nuclear grade than intermediate grade. All ER negative tumors had high nuclear grade. The Her-2 positivity is suggested as the most important factor responsible for marked in situ proliferation and production of palpable mass. PMID:26097582

Investigation of optimal parameters for penalized maximum-likelihood reconstruction applied to iodinated contrast-enhanced breast CT

NASA Astrophysics Data System (ADS)

Makeev, Andrey; Ikejimba, Lynda; Lo, Joseph Y.; Glick, Stephen J.

2016-03-01

Although digital mammography has reduced breast cancer mortality by approximately 30%, sensitivity and specificity are still far from perfect. In particular, the performance of mammography is especially limited for women with dense breast tissue. Two out of every three biopsies performed in the U.S. are unnecessary, thereby resulting in increased patient anxiety, pain, and possible complications. One promising tomographic breast imaging method that has recently been approved by the FDA is dedicated breast computed tomography (BCT). However, visualizing lesions with BCT can still be challenging for women with dense breast tissue due to the minimal contrast for lesions surrounded by fibroglandular tissue. In recent years there has been renewed interest in improving lesion conspicuity in x-ray breast imaging by administration of an iodinated contrast agent. Due to the fully 3-D imaging nature of BCT, as well as sub-optimal contrast enhancement while the breast is under compression with mammography and breast tomosynthesis, dedicated BCT of the uncompressed breast is likely to offer the best solution for injected contrast-enhanced x-ray breast imaging. It is well known that use of statistically-based iterative reconstruction in CT results in improved image quality at lower radiation dose. Here we investigate possible improvements in image reconstruction for BCT, by optimizing free regularization parameter in method of maximum likelihood and comparing its performance with clinical cone-beam filtered backprojection (FBP) algorithm.

[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.

Diagnosis of sub-centimetre breast lesions: combining BI-RADS-US with strain elastography and contrast-enhanced ultrasound-a preliminary study in China.

PubMed

Xiao, Xiaoyun; Jiang, Qiongchao; Wu, Huan; Guan, Xiaofeng; Qin, Wei; Luo, Baoming

2017-06-01

To compare the diagnostic efficacies of B-mode ultrasound (US), strain elastography (SE), contrast-enhanced ultrasound (CEUS) and the combination of these modalities for breast lesions <1 cm in size. Between January 2013 and October 2015, 203 inpatients with 209 sub-centimetre breast lesions categorised as BI-RADS-US (Breast Imaging Reporting and Data System for Ultrasound) 3-5 were included. US, SE and CEUS were performed to evaluate each lesion. The diagnostic performances of different ultrasonic modalities were compared. The diagnostic efficacies of BI-RADS-US and our re-rating systems were also compared. The pathology findings were used as the reference standard. The specificities of US, SE and CEUS for tumour differentiation were 17.4 %, 56.2 % and 86.0 %, respectively (P < 0.05); and the sensitivities were 100 %, 93.2 % and 93.2 % for US, SE and CEUS, respectively (P < 0.05). The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was 0.867 for original BI-RADS-US, 0.882 for BI-RADS-US combined with only SE, 0.953 for BI-RADS-US combined with only CEUS and 0.924 for BI-RADS-US combined with both SE and CEUS. The best combination was BI-RADS-US combined with only CEUS. Evaluating sub-centimetre breast lesions with SE and CEUS could increase the diagnostic specificity while retaining high sensitivity compared with B-mode ultrasound. • Evaluating breast lesions with SE and CEUS could increase the diagnostic specificity • SE and CEUS offer alternatives to biopsy and possibly allow shorter-interval follow-ups • BI-RADS-US combined with CEUS exhibited the best diagnostic performance.

Evaluation of a simulation procedure designed to recognize shape and contour of suspicious masses in mammography

NASA Astrophysics Data System (ADS)

Sousa, Maria A. Z.; Siqueira, Paula N.; Schiabel, Homero

2015-03-01

A large number of breast phantoms have been developed for conducting quality tests, characterization of imaging systems and computer aided diagnosis schemes, dosimetry and image perception. The realism of these phantoms is important for ensuring the accuracy of results and a greater range of applications. In this work, a developed phantom is considered proposing the use of PVC films for simulation of nodules inserted in the breast parenchyma designed for classification between malignant and benign signals according to the BI-RADS® standard. The investigation includes analysis of radiographic density, mass shape and its corresponding contour outlined by experienced radiologists. The material was cut based on lesions margins found in 44 clinical cases, which were divided between circumscribed and spiculated structures. Tests were performed to check the ability of the specialists in distinguishing the contour compared to actual cases while the shapes accuracy was determined quantitatively by evaluation metrics. Results showed the applicability of the chosen material creating image radiological patterns very similar to the actual ones.

MO-A-BRD-01: An Investigation of the Dynamic Response of a Novel Acousto-Optic Liquid Crystal Detector for Full-Field Transmission Ultrasound Breast Imaging

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

Rosenfield, J.R.; La Riviere, P.J.; Sandhu, J.S.

Purpose: To characterize the dynamic response of a novel acousto-optic (AO) liquid crystal detector for high-resolution transmission ultrasound breast imaging. Transient and steady-state lesion contrast were investigated to identify optimal transducer settings for our prototype imaging system consistent with the FDA limits of 1 W/cm{sup 2} and 50 J/cm{sup 2} on the incident acoustic intensity and the transmitted acoustic energy flux density. Methods: We have developed a full-field transmission ultrasound breast imaging system that uses monochromatic plane-wave illumination to acquire projection images of the compressed breast. The acoustic intensity transmitted through the breast is converted into a visual image bymore » a proprietary liquid crystal detector operating on the basis of the AO effect. The dynamic response of the AO detector in the absence of an imaged breast was recorded by a CCD camera as a function of the acoustic field intensity and the detector exposure time. Additionally, a stereotactic needle biopsy breast phantom was used to investigate the change in opaque lesion contrast with increasing exposure time for a range of incident acoustic field intensities. Results: Using transducer voltages between 0.3 V and 0.8 V and exposure times of 3 minutes, a unique one-to-one mapping of incident acoustic intensity to steady-state optical brightness in the AO detector was observed. A transfer curve mapping acoustic intensity to steady-state optical brightness shows a high-contrast region analogous to the linear portion of the Hurter-Driffield curves of radiography. Using transducer voltages between 1 V and 1.75 V and exposure times of 90 s, the lesion contrast study demonstrated increasing lesion contrast with increasing breast exposure time and acoustic field intensity. Lesion-to-background contrast on the order of 0.80 was observed. Conclusion: Maximal lesion contrast in our prototype system can be obtained using the highest acoustic field intensity and the longest breast exposure time allowable under FDA standards. Department of Defense (DOD) Breast Cancer Research Program IDEA Award W81XWH-11-1-0332; National Institutes of Health (NIH) Grant T32 EB002103-21 from the National Institute of Biomedical Imaging and Bioengineering (NIBIB)« less

Development and Translation of Hybrid Optoacoustic/Ultrasonic Tomography for Early Breast Cancer Detection

DTIC Science & Technology

2015-09-01

OAT) and laser-induced ultrasound tomography (LUT) to obtain coregistered maps of tissue optical absorption and speed of sound , displayed within the...computed tomography (UST) can provide high-resolution anatomical images of breast lesions based on three complementary acoustic properties (speed-of- sound ...tomography (UST) can provide high-resolution anatomical images of breast lesions based on three complementary acoustic properties (speed-of- sound

Do breast columnar cell lesions with atypia need to be excised?

PubMed

Datrice, Nicole; Narula, Navneet; Maggard, Melinda; Butler, John; Hsiang, David; Baick, Choong; Lane, Karen

2007-10-01

Columnar cell lesion with atypia (CCLA) is a newly recognized pathologic entity seen in breast specimens. The breast cancer risk associated with this finding is unclear, although CCLA had been found adjacent to both in situ and invasive carcinomas, but the incidence is unknown. Breast specimens from patients with a columnar cell lesion were reviewed by a pathologist for atypia. Twenty-one specimens with CCLA were identified [core biopsy (8), excisional biopsy (11), and simple mastectomy (2)]. Six of eight specimens with CCLA on core had adjacent abnormal pathology: infiltrating ductal carcinoma (IDC)/lobular carcinoma in situ (LCIS) (1), ductal carcinoma in situ (DCIS)/LCIS (1), DCIS (1), LCIS (1), and papillomatosis (2). Five of 11 specimens with CCLA on excisional biopsy had adjacent abnormal pathology: IDC (3), DCIS/LCIS (1), and atypical ductal hyperplasia/papilloma (1). Two of two simple mastectomy specimens had CCLA associated with IDC (1) and DCIS (1). Overall, abnormal pathology was found adjacent to CCLA in 62 per cent of specimens (13/21). Breast pathologic specimens containing a columnar cell lesion should be carefully examined for atypia. Surgical excision is warranted for CCLA found on core biopsy. The future risk of breast cancer based on the finding of CCLA alone requires further investigation.

A prospective clinical study to evaluate the safety and performance of wireless localization of nonpalpable breast lesions using radiofrequency identification technology.

PubMed

Dauphine, Christine; Reicher, Joshua J; Reicher, Murray A; Gondusky, Christina; Khalkhali, Iraj; Kim, Michelle

2015-06-01

The purpose of this study was to evaluate the safety and performance of localizing nonpalpable breast lesions using radiofrequency identification technology. Twenty consecutive women requiring preoperative localization of a breast lesion were recruited. Subjects underwent placement of both a hook wire and a radiofrequency identification tag immediately before surgery. The radiofrequency identification tag was the primary method used by the operating surgeon to localize each lesion during excision, with the hook wire serving as backup in case of tag migration or failed localization. Successful localization with removal of the intended lesion was the primary outcome measured. Tag migration and postoperative infection were also noted to assess safety. Twenty patients underwent placement of a radiofrequency identification tag, 12 under ultrasound guidance and eight with stereotactic guidance. In all cases, the radiofrequency identification tag was successfully localized by the reader at the level of the skin before incision, and the intended lesion was removed along with the radiofrequency identification tag. There were no localization failures and no postoperative infections. Tag migration did not occur before incision, but in three cases, occurred as the lesion was being retracted with fingers to make the final cut along the deep surface of the specimen. In this initial clinical study, radiofrequency tags were safe and able to successfully localize nonpalpable breast lesions. Radiofrequency identification technology may represent an alternative method to hook wire localization.

Influence of region of interest size and ultrasound lesion size on the performance of 2D shear wave elastography (SWE) in solid breast masses.

PubMed

Skerl, K; Vinnicombe, S; Giannotti, E; Thomson, K; Evans, A

2015-12-01

To evaluate the influence of the region of interest (ROI) size and lesion diameter on the diagnostic performance of 2D shear wave elastography (SWE) of solid breast lesions. A study group of 206 consecutive patients (age range 21-92 years) with 210 solid breast lesions (70 benign, 140 malignant) who underwent core biopsy or surgical excision was evaluated. Lesions were divided into small (diameter <15 mm, n=112) and large lesions (diameter ≥15 mm, n=98). An ROI with a diameter of 1, 2, and 3 mm was positioned over the stiffest part of the lesion. The maximum elasticity (Emax), mean elasticity (Emean) and standard deviation (SD) for each ROI size were compared to the pathological outcome. Statistical analysis was undertaken using the chi-square test and receiver operating characteristic (ROC) analysis. The ROI size used has a significant impact on the performance of Emean and SD but not on Emax. Youden's indices show a correlation with the ROI size and lesion size: generally, the benign/malignant threshold is lower with increasing ROI size but higher with increasing lesion size. No single SWE parameter has superior performance. Lesion size and ROI size influence diagnostic performance. Copyright © 2015. Published by Elsevier Ltd.

A Comprehensive Repository of Normal and Tumor Human Breast Tissues and Cells

DTIC Science & Technology

1999-07-01

mother was reported to have had cancer of the uterine cervix at the age of 22. Both maternal grandparents had died of colon cancer in their sixties...1 mutation). The repository also includes breast epithelial and stromal cell strains derived from non cancerous breast tissue as well as peripheral...tissue banks. 14. SUBJECT TERMS Breast Cancer 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF THIS PAGE

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

PubMed

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

2005-05-01

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

Recent Changes of Classification for Squamous Intraepithelial Lesions of the Head and Neck.

PubMed

Cho, Kyung-Ja; Song, Joon Seon

2018-05-18

- Interpretation of atypical squamous lesions of the head and neck has always been a nettlesome task for pathologists. Moreover, many different grading systems for squamous intraepithelial lesions have been proposed in past decades. The recent World Health Organization 2017 classification presents 2 types of 2-tier systems for laryngeal and oral precursor lesions. - To review the recent changes in classification and the clinical significance for squamous intraepithelial lesions of the head and neck. - Personal experience and data from the literature. - The 2-tier grading system for laryngeal dysplasia, presented by World Health Organization in 2017, is expected to improve diagnostic reproducibility and clinical implication. However, the diagnostic criteria for low-grade dysplasia do not distinguish it clearly from basal cell hyperplasia. The World Health Organization 2017 classification of oral epithelial dysplasia remains unclear, and complicated and variable grading systems still make head and neck intraepithelial lesions difficult to interpret.

Flat epithelial atypia is a common subtype of B3 breast lesions and is associated with noninvasive cancer but not with invasive cancer in final excision histology.

PubMed

Noske, Aurelia; Pahl, Stefan; Fallenberg, Eva; Richter-Ehrenstein, Christiane; Buckendahl, Ann-Christin; Weichert, Wilko; Schneider, Achim; Dietel, Manfred; Denkert, Carsten

2010-04-01

The biological behavior and the optimal management of benign breast lesions with uncertain malignant potential, the so-called B3 lesions, found in breast needle core biopsies is still under debate. We addressed this study to compare histologic findings in B3 needle core biopsies with final excision specimens to determine associated rates of malignancy. Consecutive needle core biopsies were performed in a 3-year period (January 1, 2006-December 31, 2008). Biopsies were image-guided (31 by ultrasound, 85 stereotactic vacuum-assisted, 6 unknown) for evaluation of breast abnormalities. We reviewed 122 needle core biopsies with B3 lesions of 91 symptomatic patients and 31 screen-detected women and compared the B3 histologic subtypes with the final excision histology. A total of 1845 needle core biopsies were performed and B3 lesions comprised 6.6% of all B categories. The most common histologic subtype in biopsies was flat epithelia atypia in 35.2%, followed by papillary lesions in 21% and atypical ductal hyperplasia in 20%. Reports on excision specimens were available in 66% (81 patients). Final excision histology was benign in 73 (90.2%) and malignant in 8 (9.8%) patients (2 invasive cancer, 6 ductal carcinoma in situ). Of all B3 subtypes, atypical ductal hyperplasia and flat epithelial atypia were associated with malignancy, whereas only atypical ductal hyperplasia was accompanied by invasive cancer. Of all lesions, flat epithelial atypia was most frequently found in excision specimens (18%). In our study, flat epithelial atypia and atypical ductal hyperplasia are common lesions of the B3 category in needle core biopsies of the breast. Both lesions are associated with malignancy, whereas only atypical ductal hyperplasia was related to invasive cancer. We conclude that an excision biopsy after diagnosis of flat epithelial atypia is recommended depending on clinical and radiologic findings. Copyright 2010 Elsevier Inc.

The value of ultrasounds exam correlated with frozen section diagnosis in the breast tumors.

PubMed

Venter, Alina; Roşca, Elena; Muţiu, Gabriela; Pirte, Adriana; Roşca, D M

2010-01-01

The paper represents a parallel study regarding the harmony between the ultrasounds and the frozen section diagnosis in the breast cancer. We examined at an ultrasounds machine a group of 146 women aged between 16-73-year-old, which came presenting palpable formations at the level of breasts, in the Pelican Medical Centre from Oradea. The suspect lesions were subject to excisional biopsy or surgical intervention. The elements followed at the ultrasounds exam were: echogenicity, echostructure, contour, presence and absence of posterior shadowing, microcalcifiation, orientation of lesion, compressibility, aspect of adjacent structures. Histopathological diagnosis of suspect lesions emphasized malignant lesions in a percentage of 64.86% of cases; the frozen section exam diagnosed invasive ductal carcinoma in 86% of the cases, invasive lobular carcinoma 8%, medullar carcinoma 2%, and benign lesions 4%. The clinical-anatomopathological collaboration is absolutely compulsory for a correct microscopic diagnosis. The ultrasounds modifications separated after the criteria taken into account allow the orientation of diagnosis to malignant-benign. At 14% of the women examined, additional lesions were identified in comparison to those palpated, the ultrasounds having a role in detecting the multifocality and muticentricity of lesions. At 29.05% from the identified lesions, malignant lesions were histopathologically identified. The frozen section diagnosis in the breast cancer allows a rapid diagnosis, correct in high percentage of cases, allowing taking an intra-surgery therapeutic attitude in only one surgical intervention, thus reducing the costs. The anatomopathologist's experience reduces the diagnosis risk in excess and÷or in minus.

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

Research on the lesion segmentation of breast tumor MR images based on FCM-DS theory

NASA Astrophysics Data System (ADS)

Zhang, Liangbin; Ma, Wenjun; Shen, Xing; Li, Yuehua; Zhu, Yuemin; Chen, Li; Zhang, Su

2017-03-01

Magnetic resonance imaging (MRI) plays an important role in the treatment of breast tumor by high intensity focused ultrasound (HIFU). The doctors evaluate the scale, distribution and the statement of benign or malignancy of breast tumor by analyzing variety modalities of MRI, such as the T2, DWI and DCE images for making accurate preoperative treatment plan and evaluating the effect of the operation. This paper presents a method of lesion segmentation of breast tumor based on FCM-DS theory. Fuzzy c-means clustering (FCM) algorithm combined with Dempster-Shafer (DS) theory is used to process the uncertainty of information, segmenting the lesion areas on DWI and DCE modalities of MRI and reducing the scale of the uncertain parts. Experiment results show that FCM-DS can fuse the DWI and DCE images to achieve accurate segmentation and display the statement of benign or malignancy of lesion area by Time-Intensity Curve (TIC), which could be beneficial in making preoperative treatment plan and evaluating the effect of the therapy.

Practical application of contrast-enhanced magnetic resonance mammography [CE-MRM] by an algorithm combining morphological and enhancement patterns.

PubMed

Potente, Giuseppe; Messineo, Daniela; Maggi, Claudia; Savelli, Sara

2009-03-01

The purpose of this article is to report our practical utilization of dynamic contrast-enhanced magnetic resonance mammography [DCE-MRM] in the diagnosis of breast lesions. In many European centers, was preferred a high-temporal acquisition of both breasts simultaneously in a large FOV. We preferred to scan single breasts, with the aim to combine the analysis of the contrast intake and washout with the morphological evaluation of breast lesions. We followed an interpretation model, based upon a diagnostic algorithm, which combined contrast enhancement with morphological evaluation, in order to increase our confidence in diagnosis. DCE-MRM with our diagnostic algorithm has identified 179 malignant and 41 benign lesions; final outcome has identified 178 malignant and 42 benign lesions, 3 false positives and 2 false negatives. Sensitivity of CE-MRM was 98.3%; specificity, 95.1%; positive predictive value, 98.9%; negative predictive value, 92.8% and accuracy, 97.7%.

Use of a Volume Navigation Technique for Combining Real-Time Ultrasound and Contrast-Enhanced MRI: Accuracy and Feasibility of a Novel Technique for Locating Breast Lesions.

PubMed

Kucukkaya, Fikret; Aribal, Erkin; Tureli, Derya; Altas, Hilal; Kaya, Handan

2016-01-01

The objective of this study was to evaluate the accuracy of the volume navigation technique for combining real-time ultrasound and contrast-enhanced MRI (CE-MRI) of breast lesions. Thirty-eight women with single breast lesions underwent 3-T MRI. A 3.5-minute CE-MRI sequence was used, as was a flexible body coil. Patients underwent imaging in the supine position, with three markers placed on their breasts. Real-time sonographic images were coregistered to the preloaded breast CE-MRI volume by coupling skin markers, with the use of an electromagnetic transmitter positioned next to the subjects. The transmitter detected the spatial positions of the two electromagnetic sensors mounted on the transducer bracket. After this fusion process in 3D space was completed, divergences in the location of the center of each lesion on CE-MRI and ultrasound images were analyzed. The mean lesion size was 17.4 mm on ultrasound and 17.9 mm on MRI, whereas the mean (± SD) misalignment of the lesion centers on CE-MRI and ultrasound was 3.9 ± 2.5 mm on the x-axis (mediolateral view), 3.6 ± 2.7 mm on the y-axis (anteroposterior view), and 4.3 ± 2.6 mm on the z-axis (craniocaudal view). No lesion had a misalignment greater than 10 mm on any of three axes. The accuracy of volume navigation was independent of patient age and the lesion size, location, and histopathologic findings (p > 0.05). Intermediate lesions, which had a depth of center of 11-20 mm on ultrasound had a mean misalignment of 2.6 ± 1.9 mm, compared with 5.5 ± 2.2 mm for deep lesions, which had a depth of center greater than 20 mm (p = 0.049). The volume navigation technique is an accurate method for coregistration of CE-MRI and sonographic images, enabling lesion localization within a limited volume.

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 multi-image approach to CADx of breast cancer with integration into PACS

NASA Astrophysics Data System (ADS)

Elter, Matthias; Wittenberg, Thomas; Schulz-Wendtland, Rüdiger; Deserno, Thomas M.

2009-02-01

While screening mammography is accepted as the most adequate technique for the early detection of breast cancer, its low positive predictive value leads to many breast biopsies performed on benign lesions. Therefore, we have previously developed a knowledge-based system for computer-aided diagnosis (CADx) of mammographic lesions. It supports the radiologist in the discrimination of benign and malignant lesions. So far, our approach operates on the lesion level and employs the paradigm of content-based image retrieval (CBIR). Similar lesions with known diagnosis are retrieved automatically from a library of references. However, radiologists base their diagnostic decisions on additional resources, such as related mammographic projections, other modalities (e.g. ultrasound, MRI), and clinical data. Nonetheless, most CADx systems disregard the relation between the craniocaudal (CC) and mediolateral-oblique (MLO) views of conventional mammography. Therefore, we extend our approach to the full case level: (i) Multi-frame features are developed that jointly describe a lesion in different views of mammography. Taking into account the geometric relation between different images, these features can also be extracted from multi-modal data; (ii) the CADx system architecture is extended appropriately; (iii) the CADx system is integrated into the radiology information system (RIS) and the picture archiving and communication system (PACS). Here, the framework for image retrieval in medical applications (IRMA) is used to support access to the patient's health care record. Of particular interest is the application of the proposed CADx system to digital breast tomosynthesis (DBT), which has the potential to succeed digital mammography as the standard technique for breast cancer screening. The proposed system is a natural extension of CADx approaches that integrate only two modalities. However, we are still collecting a large enough database of breast lesions with images from multiple modalities to evaluate the benefits of the proposed approach on.

Benign breast lesions at risk of developing cancer--a challenging problem in breast cancer screening programs: five years' experience of the Breast Cancer Screening Program in Verona (1999-2004).

PubMed

Manfrin, Erminia; Mariotto, Renata; Remo, Andrea; Reghellin, Daniela; Falsirollo, Francesca; Dalfior, Daniela; Bricolo, Paola; Piazzola, Elena; Bonetti, Franco

2009-02-01

Cytology and core-needle biopsies are not always sufficient to exclude malignancy in benign breast lesions (BBL) that are at risk of developing cancer, and open biopsy often is mandatory. In screening programs, open biopsies performed for lesions that are at risk of developing malignancy are considered benign. The authors of this report evaluated the impact of the screen-detected BBL at risk of developing cancer that were counted in the quota of benign breast open biopsies in the Breast Cancer Screening Program of Verona. Benign open biopsies were subdivided into 4 groups according to their risk of developing cancer: Histo1, normal histology; Histo2, 'pure' BBL (fibroadenoma, fibrocystic disease, mastitis, adenosis); Histo3, BBL with a low risk of developing cancer (radial scar, papilloma, papillomatosis, phyllodes tumor, mucocele-like lesion); and Histo4, BBL with a high risk of developing cancer (atypical columnar cell hyperplasia, atypical ductal hyperplasia, atypical lobular hyperplasia). Of 510 open biopsies, 83 biopsies were benign, and the ratio of benign to malignant biopsies was 1:5. Histo1 was observed in 4.8% of all benign open biopsies, Histo2 was observed in 37.4%, Histo3 was observed in 31.3%, and Histo4 was observed 26.5%. BBL at risk of developing cancer may be numerous in screening programs. It is inappropriate to include BBL at risk of developing cancer in the overall benign open biopsy rate. The authors propose separating pure BBL from lesions at higher risk of developing cancer. To date, there is no evidence to support the premise that detecting high-risk proliferative lesions leads to benefits in terms of reduced mortality; however, these lesions need to be counted separately for future evaluations. (c) 2008 American Cancer Society.

Fibromatosis of the breast mimicking an abscess: case report of unusual sonographic features.

PubMed

Lee, So Min; Lee, Ji Young; Lee, Byung Hoon; Kim, Su Young; Joo, Mee; Kim, Jae Il

2015-01-01

Fibromatosis of the breast, also known as a desmoid tumor, is extremely rare and most often appears as an aggressive lesion mimicking breast carcinoma. It lacks metastatic potential but can grow aggressively in a localized area. Ultrasonography often shows an irregular spiculated hypoechoic mass with posterior acoustic shadowing. We discuss a case of breast fibromatosis that presented as a painful palpable breast mass in a 32-year-old woman and mimicked an abscess in the sonogram. We found that this lesion displayed atypical sonographic features such as a heterogeneous echoic mass with an internal anechoic area. Copyright © 2015 Elsevier Inc. All rights reserved.

Relationship of Terminal Duct Lobular Unit Involution of the Breast with Area and Volume Mammographic Densities

PubMed Central

Gierach, Gretchen L.; Patel, Deesha A.; Pfeiffer, Ruth M.; Figueroa, Jonine D.; Linville, Laura; Papathomas, Daphne; Johnson, Jason M.; Chicoine, Rachael E.; Herschorn, Sally D.; Shepherd, John A.; Wang, Jeff; Malkov, Serghei; Vacek, Pamela M.; Weaver, Donald L.; Fan, Bo; Mahmoudzadeh, Amir Pasha; Palakal, Maya; Xiang, Jackie; Oh, Hannah; Horne, Hisani N.; Sprague, Brian L.; Hewitt, Stephen M.; Brinton, Louise A.; Sherman, Mark E.

2016-01-01

Elevated mammographic density (MD) is an established breast cancer risk factor. Reduced involution of terminal duct lobular units (TDLUs), the histologic source of most breast cancers, has been associated with higher MD and breast cancer risk. We investigated relationships of TDLU involution with area and volumetric MD, measured throughout the breast and surrounding biopsy targets (peri-lesional). Three measures inversely related to TDLU involution (TDLU count/mm2, median TDLU span, median acini count/TDLU) assessed in benign diagnostic biopsies from 348 women, ages 40–65, were related to MD area (quantified with thresholding software) and volume (assessed with a density phantom) by analysis of covariance, stratified by menopausal status and adjusted for confounders. Among premenopausal women, TDLU count was directly associated with percent peri-lesional MD (P-trend=0.03), but not with absolute dense area/volume. Greater TDLU span was associated with elevated percent dense area/volume (P-trend<0.05) and absolute peri-lesional MD (P=0.003). Acini count was directly associated with absolute peri-lesional MD (P=0.02). Greater TDLU involution (all metrics) was associated with increased nondense area/volume (P-trend≤0.04). Among postmenopausal women, TDLU measures were not significantly associated with MD. Among premenopausal women, reduced TDLU involution was associated with higher area and volumetric MD, particularly in peri-lesional parenchyma. Data indicating that TDLU involution and MD are correlated markers of breast cancer risk suggest that associations of MD with breast cancer may partly reflect amounts of at-risk epithelium. If confirmed, these results could suggest a prevention paradigm based on enhancing TDLU involution and monitoring efficacy by assessing MD reduction. PMID:26645278

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.

Segmentation of malignant lesions in 3D breast ultrasound using a depth-dependent model.

PubMed

Tan, Tao; Gubern-Mérida, Albert; Borelli, Cristina; Manniesing, Rashindra; van Zelst, Jan; Wang, Lei; Zhang, Wei; Platel, Bram; Mann, Ritse M; Karssemeijer, Nico

2016-07-01

Automated 3D breast ultrasound (ABUS) has been proposed as a complementary screening modality to mammography for early detection of breast cancers. To facilitate the interpretation of ABUS images, automated diagnosis and detection techniques are being developed, in which malignant lesion segmentation plays an important role. However, automated segmentation of cancer in ABUS is challenging since lesion edges might not be well defined. In this study, the authors aim at developing an automated segmentation method for malignant lesions in ABUS that is robust to ill-defined cancer edges and posterior shadowing. A segmentation method using depth-guided dynamic programming based on spiral scanning is proposed. The method automatically adjusts aggressiveness of the segmentation according to the position of the voxels relative to the lesion center. Segmentation is more aggressive in the upper part of the lesion (close to the transducer) than at the bottom (far away from the transducer), where posterior shadowing is usually visible. The authors used Dice similarity coefficient (Dice) for evaluation. The proposed method is compared to existing state of the art approaches such as graph cut, level set, and smart opening and an existing dynamic programming method without depth dependence. In a dataset of 78 cancers, our proposed segmentation method achieved a mean Dice of 0.73 ± 0.14. The method outperforms an existing dynamic programming method (0.70 ± 0.16) on this task (p = 0.03) and it is also significantly (p < 0.001) better than graph cut (0.66 ± 0.18), level set based approach (0.63 ± 0.20) and smart opening (0.65 ± 0.12). The proposed depth-guided dynamic programming method achieves accurate breast malignant lesion segmentation results in automated breast ultrasound.

Added value of Virtual Touch IQ shear wave elastography in the ultrasound assessment of breast lesions.

PubMed

Ianculescu, Victor; Ciolovan, Laura Maria; Dunant, Ariane; Vielh, Philippe; Mazouni, Chafika; Delaloge, Suzette; Dromain, Clarisse; Blidaru, Alexandru; Balleyguier, Corinne

2014-05-01

To determine the diagnostic performance of Acoustic Radiation Force Impulse (ARFI) Virtual Touch IQ shear wave elastography in the discrimination of benign and malignant breast lesions. Conventional B-mode and elasticity imaging were used to evaluate 110 breast lesions. Elastographic assessment of breast tissue abnormalities was done using a shear wave based technique, Virtual Touch IQ (VTIQ), implemented on a Siemens Acuson S3000 ultrasound machine. Tissue mechanical properties were interpreted as two-dimensional qualitative and quantitative colour maps displaying relative shear wave velocity. Wave speed measurements in m/s were possible at operator defined regions of interest. The pathologic diagnosis was established on samples obtained by ultrasound guided core biopsy or fine needle aspiration. BIRADS based B-mode evaluation of the 48 benign and 62 malignant lesions achieved 92% sensitivity and 62.5% specificity. Subsequently performed VTIQ elastography relying on visual interpretation of the colour overlay displaying relative shear wave velocities managed similar standalone diagnostic performance with 92% sensitivity and 64.6% specificity. Lesion and surrounding tissue shear wave speed values were calculated and a significant difference was found between the benign and malignant populations (Mann-Whitney U test, p<0.0001). By selecting a lesion cut-off value of 3.31m/s we achieved 80.4% sensitivity and 73% specificity. Applying this threshold only to BIRADS 4a masses, we reached overall levels of 92% sensitivity and 72.9% specificity. VTIQ qualitative and quantitative elastography has the potential to further characterise B-mode detected breast lesions, increasing specificity and reducing the number of unnecessary biopsies. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Real-Time Palpation Imaging for Improved Detection and Discrimination of Breast Abnormalities

DTIC Science & Technology

2001-10-01

useful tool for improving the discrimination between benign and malignant breast tumors. The scope of the effort in our first year of funding was to...lesion area measured in B-mode versus strain images we find complete discrimination between benign and malignant lesions.

Technetium-99m sestamibi scintimammography complements mammography in the detection of breast cancer.

PubMed

Krishnaiah, Gayathri; Sher-Ahmed, Arifa; Ugwu-Dike, Martins; Regan, Patricia; Singer, John; Totoonchie, Adil; Spiegler, Ethan; Sardi, Armando

2003-01-01

Mammography remains the technique of choice for the detection of early breast cancer. The sensitivity of mammography is 85%, but is decreased in patients with dense breasts. Sestamibi scintimammography (SCM) has been suggested as an adjunctive modality to improve the detection of breast cancer. We conducted a study to determine the impact of SCM in patient management. A prospective study was conducted in 95 patients presenting with palpable masses and/or abnormal mammography scheduled for biopsy. Injection of 20-30 mCi of technetium-99m (Tc-99m) sestamibi into a pedal vein was performed. Ten-minute images of the breast and axilla were obtained in multiple projections. The mammography and SCM were correlated with pathology and clinical findings. The median age was 44 years (range 28-86 years). The total number of lesions was 104, as eight patients had bilateral lesions and one patient had two lesions in the same breast. Fifty-nine patients presented with palpable lesions and 45 patients with nonpalpable lesions (42 with abnormal mammography only and 3 with nipple discharge). A comparison of sensitivity, specificity, positive and negative predictive values, and overall accuracy of SCM and mammography were performed. The sensitivity and specificity for SCM were 83% and 83%, respectively, and for mammography were 65%, and 72%, respectively. The sensitivity and specificity for combined SCM and mammography were 87% and 94%, respectively. The p-value for mammography versus combined SCM and mammography was 0.0003 and that for SCM versus SCM and mammography was 0.0098. There were 80 (77%) benign and 24 (23%) malignant lesions. Of the 24 malignancies, SCM missed six (25%), versus eight (33%) by mammography. In two patients (9%) SCM detected malignancy in the breast that was not visualized by mammography or found on clinical examination. Sestamibi SCM improves the sensitivity of mammography and it detects up to 9% of malignancies not detected by mammography or clinical examination. This testing could impact the management of 16,500 patients in the United States every year. More studies are needed to better define its role in breast cancer detection.

Is the necrosis/wall ADC ratio useful for the differentiation of benign and malignant breast lesions?

PubMed Central

Durur-Karakaya, Afak; Karaman, Adem; Seker, Mehmet; Demirci, Elif; Alper, Fatih

2017-01-01

Objective: To determine whether the necrosis/wall apparent diffusion coefficient (ADC) ratio is useful for the malignant–benign differentiation of necrotic breast lesions. Methods: Breast MRI was performed using a 3-T system. In this retrospective study, calculation of the necrosis/wall ADC ratio was based on ADC values measured from the necrosis and from the wall of malignant and benign breast lesions by diffusion-weighted imaging (DWI). By synchronizing post-contrast T1 weighted images, the separate parts of wall and necrosis were maintained. All the diagnoses were pathologically confirmed. Statistical analyses were conducted using an independent sample t-test and receiver operating characteristic analysis. The intraclass and interclass correlations were evaluated. Results: A total of 66 female patients were enrolled, 38 of whom had necrotic breast carcinomas and 28 of whom had breast abscesses. The ADC values were obtained from both the wall and necrosis. The mean necrosis/wall ADC ratio (± standard deviation) was 1.61 ± 0.51 in carcinomas, and it was 0.65 ± 0.33 in abscesses. The area under the curve values for necrosis ADC, wall ADC and the necrosis/wall ADC ratio were 0.680, 0.068 and 0.942, respectively. A wall/necrosis ADC ratio cut-off value of 1.18 demonstrated a sensitivity of 97%, specificity of 93%, a positive-predictive value of 95%, a negative-predictive value of 96% and an accuracy of 95% in determining the malignant nature of necrotic breast lesions. There was a good intra- and interclass reliability for the ADC values of both necrosis and wall. Conclusion: The necrosis/wall ADC ratio appears to be a reliable and promising tool for discriminating breast carcinomas from abscesses using DWI. Advances in knowledge: ADC values of the necrosis obtained by DWI are valuable for malignant-benign differentiation in necrotic breast lesions. The necrosis/wall ADC ratio appears to be a reliable and promising tool in the breast imaging field. PMID:28339285

Consistency of histopathological reporting of breast lesions detected by screening: findings of the U.K. National External Quality Assessment (EQA) Scheme. U. K. National Coordinating Group for Breast Screening Pathology.

PubMed

Sloane, J P; Ellman, R; Anderson, T J; Brown, C L; Coyne, J; Dallimore, N S; Davies, J D; Eakins, D; Ellis, I O; Elston, C W

1994-01-01

The aim of the scheme was to determine consistency of histopathological reporting in the United Kingdom National Breast Screening Programme. This external quality assessment scheme involved 51 sets of 12 slides which were circulated to 186-251 pathologists at intervals of 6 months for 3 years. Participants recorded their diagnoses on standard reporting forms, which were submitted to the U.K. National Cancer Screening Evaluation Unit for analysis. A high level of consistency was achieved in diagnosing major categories of breast disease including invasive carcinoma and the important borderline lesions, radial scar and ductal carcinoma in situ (DCIS), the latter exceeding a national target set prior to the onset of the scheme. Atypical hyperplasia (AH) was reported with much less consistency although, where it was the majority opinion, over 86% of diagnoses were of benign disorders and only 14% were of DCIS. Inconsistency was encountered in subtyping and measuring DCIS, the former apparently due to current uncertainties about classification and the latter to poor circumscription, variation in size in different sections and merging with zones of AH. Reporting prognostic features of invasive carcinomas was variable. Measurement of size was achieved with adequate consistency except in a small number of very poorly circumscribed tumours. Grading and subtyping were inconsistent although the latter was not specifically tested and will be the subject of future study. Members of the National Coordinating Group achieved greater uniformity than the remainder of the participants in all diagnostic categories, but both groups experienced similar types of problem. Our findings suggest that participation in the scheme improves diagnostic consistency. In conclusion, consistency in diagnosing invasive carcinoma and radial scar is excellent, and good in DCIS, but improvements are desirable in diagnosing atypical hyperplasia, classifying DCIS and reporting certain prognostic features of invasive tumours. Such improvements will require further research, the development of improved diagnostic criteria and the dissemination of clearer guidelines.

Evaluation of aldehyde dehydrogenase 1 and transcription factors in both primary breast cancer and axillary lymph node metastases as a prognostic factor.

PubMed

Ito, Maiko; Shien, Tadahiko; Omori, Masako; Mizoo, Taeko; Iwamoto, Takayuki; Nogami, Tomohiro; Motoki, Takayuki; Taira, Naruto; Doihara, Hiroyoshi; Miyoshi, Shinichiro

2016-05-01

Aldehyde dehydrogenase 1 (ALDH1) is a marker of breast cancer stem cells, and the expression of ALDH1 may be a prognostic factor of poor clinical outcome. The epithelial-mesenchymal transition may produce cells with stem-cell-like properties promoted by transcription factors. We investigated the expression of ALDH1 and transcription factors in both primary and metastatic lesions, and prognostic value of them in breast cancer patients with axillary lymph node metastasis (ALNM). Forty-seven breast cancer patients with ALNM who underwent surgery at Okayama University Hospital from 2002 to 2008 were enrolled. We retrospectively evaluated the levels of ALDH1 and transcription factors, such as Snail, Slug and Twist, in both primary and metastatic lesions by immunohistochemistry. In primary lesions, the positive rate of ALDH1, Snail, Slug and Twist was 19, 49, 40 and 26%, respectively. In lymph nodes, that of ALDH1, Snail, Slug and Twist was 21, 32, 13 and 23%, respectively. The expression of ALDH1 or transcription factors alone was not significantly associated with a poor prognosis. However, co-expression of ALDH1 and Slug in primary lesions was associated with a shorter DFS (P = 0.009). The evaluation of the co-expression of ALDH1 and transcription factors in primary lesions may be useful in prognosis of node-positive breast cancers.

Depth profiling of calcifications in breast tissue using picosecond Kerr-gated Raman spectroscopy.

PubMed

Baker, Rebecca; Matousek, Pavel; Ronayne, Kate Louise; Parker, Anthony William; Rogers, Keith; Stone, Nicholas

2007-01-01

Breast calcifications are found in both benign and malignant lesions and their composition can indicate the disease state. Calcium oxalate (dihydrate) (COD) is associated with benign lesions, however calcium hydroxyapatite (HAP) is found mainly in proliferative lesions including carcinoma. The diagnostic practices of mammography and histopathology examine the morphology of the specimen. They can not reliably distinguish between the two types of calcification, which may indicate the presence of a cancerous lesion during mammography. We demonstrate for the first time that Kerr-gated Raman spectroscopy is capable of non-destructive probing of sufficient biochemical information from calcifications buried within tissue, and this information can potentially be used as a first step in identifying the type of lesion. The method uses a picosecond pulsed laser combined with fast temporal gating of Raman scattered light to enable spectra to be collected from a specific depth within scattering media by collecting signals emerging from the sample at a given time delay following the laser pulse. Spectra characteristic of both HAP and COD were obtained at depths of up to 0.96 mm, in both chicken breast and fatty tissue; and normal and cancerous human breast by utilising different time delays. This presents great potential for the use of Raman spectroscopy as an adjunct to mammography in the early diagnosis of breast cancer.

Clinical application of spectral electromagnetic interaction in breast cancer: diagnostic results of a pilot study.

PubMed

De Cicco, Concetta; Mariani, Luigi; Vedruccio, Clarbruno; Ricci, Carla; Balma, Massimo; Rotmensz, Nicole; Ferrari, Mahila Esmeralda; Autino, Elena; Trifirò, Giuseppe; Sacchini, Virgilio; Viale, Giuseppe; Paganelli, Giovanni

2006-01-01

There is a need for a cost-effective method to safely reduce the number of diagnostic procedures women undergo for breast cancer. We tested a new procedure for breast cancer diagnosis based on breast tissue response to low level electromagnetic incident waves. We tested 101 patients with suspicious palpable breast lesions detected by mammography or ultrasonography, who were scheduled to undergo an open biopsy. Using an electromagnetic field generator (tissue resonance interaction method probe [TRIMprob]), we passed the TRIMprob over the breast area and recorded the signal variation of one or more spectral lines (dB1, dB2, dB3). The results were compared with those of a control group as well as with pathology data obtained from excisional biopsy. No adverse effects of the test were observed. Pathology revealed 86 malignant breast cancers (72 invasive, 14 in situ) and 15 benign conditions. We achieved the best discrimination between normal breasts and lesions using dB1 (dB1 AUC-ROC = 0.8; dB2 AUC-ROC = 0.61; dB3 AUC-ROC = 0.76). With a specificity of 75% to 95%, the sensitivity ranged from 49% to 84%. Tumor or patient variables did not influence the results. The TRIMprob test was able to provide some degree of discrimination between normal breast tissue and lesions but not between benign and malignant lesions. The lack of influence of patient age and tumor size on test results might be advantageous in terms of early diagnosis in young women. These preliminary results need to be verified and extended in a preclinical-stage disease setting before clinical applicability can be envisaged.

Probabilistic multiple sclerosis lesion classification based on modeling regional intensity variability and local neighborhood information.

PubMed

Harmouche, Rola; Subbanna, Nagesh K; Collins, D Louis; Arnold, Douglas L; Arbel, Tal

2015-05-01

In this paper, a fully automatic probabilistic method for multiple sclerosis (MS) lesion classification is presented, whereby the posterior probability density function over healthy tissues and two types of lesions (T1-hypointense and T2-hyperintense) is generated at every voxel. During training, the system explicitly models the spatial variability of the intensity distributions throughout the brain by first segmenting it into distinct anatomical regions and then building regional likelihood distributions for each tissue class based on multimodal magnetic resonance image (MRI) intensities. Local class smoothness is ensured by incorporating neighboring voxel information in the prior probability through Markov random fields. The system is tested on two datasets from real multisite clinical trials consisting of multimodal MRIs from a total of 100 patients with MS. Lesion classification results based on the framework are compared with and without the regional information, as well as with other state-of-the-art methods against the labels from expert manual raters. The metrics for comparison include Dice overlap, sensitivity, and positive predictive rates for both voxel and lesion classifications. Statistically significant improvements in Dice values ( ), for voxel-based and lesion-based sensitivity values ( ), and positive predictive rates ( and respectively) are shown when the proposed method is compared to the method without regional information, and to a widely used method [1]. This holds particularly true in the posterior fossa, an area where classification is very challenging. The proposed method allows us to provide clinicians with accurate tissue labels for T1-hypointense and T2-hyperintense lesions, two types of lesions that differ in appearance and clinical ramifications, and with a confidence level in the classification, which helps clinicians assess the classification results.

Histopathological Image Classification using Discriminative Feature-oriented Dictionary Learning

PubMed Central

Vu, Tiep Huu; Mousavi, Hojjat Seyed; Monga, Vishal; Rao, Ganesh; Rao, UK Arvind

2016-01-01

In histopathological image analysis, feature extraction for classification is a challenging task due to the diversity of histology features suitable for each problem as well as presence of rich geometrical structures. In this paper, we propose an automatic feature discovery framework via learning class-specific dictionaries and present a low-complexity method for classification and disease grading in histopathology. Essentially, our Discriminative Feature-oriented Dictionary Learning (DFDL) method learns class-specific dictionaries such that under a sparsity constraint, the learned dictionaries allow representing a new image sample parsimoniously via the dictionary corresponding to the class identity of the sample. At the same time, the dictionary is designed to be poorly capable of representing samples from other classes. Experiments on three challenging real-world image databases: 1) histopathological images of intraductal breast lesions, 2) mammalian kidney, lung and spleen images provided by the Animal Diagnostics Lab (ADL) at Pennsylvania State University, and 3) brain tumor images from The Cancer Genome Atlas (TCGA) database, reveal the merits of our proposal over state-of-the-art alternatives. Moreover, we demonstrate that DFDL exhibits a more graceful decay in classification accuracy against the number of training images which is highly desirable in practice where generous training is often not available. PMID:26513781

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.

Differentiating benign from malignant solid breast masses: value of shear wave elastography according to lesion stiffness combined with greyscale ultrasound according to BI-RADS classification.

PubMed

Evans, A; Whelehan, P; Thomson, K; Brauer, K; Jordan, L; Purdie, C; McLean, D; Baker, L; Vinnicombe, S; Thompson, A

2012-07-10

The aim of this study was to assess the performance of shear wave elastography combined with BI-RADS classification of greyscale ultrasound images for benign/malignant differentiation in a large group of patients. One hundred and seventy-five consecutive patients with solid breast masses on routine ultrasonography undergoing percutaneous biopsy had the greyscale findings classified according to the American College of Radiology BI-RADS. The mean elasticity values from four shear wave images were obtained. For mean elasticity vs greyscale BI-RADS, the performance results against histology were sensitivity: 95% vs 95%, specificity: 77% vs 69%, Positive Predictive Value (PPV): 88% vs 84%, Negative Predictive Value (NPV): 90% vs 91%, and accuracy: 89% vs 86% (all P>0.05). The results for the combination (positive result from either modality counted as malignant) were sensitivity 100%, specificity 61%, PPV 82%, NPV 100%, and accuracy 86%. The combination of BI-RADS greyscale and shear wave elastography yielded superior sensitivity to BI-RADS alone (P=0.03) or shear wave alone (P=0.03). The NPV was superior in combination compared with either alone (BI-RADS P=0.01 and shear wave P=0.02). Together, BI-RADS assessment of greyscale ultrasound images and shear wave ultrasound elastography are extremely sensitive for detection of malignancy.

Differentiating benign from malignant solid breast masses: value of shear wave elastography according to lesion stiffness combined with greyscale ultrasound according to BI-RADS classification

PubMed Central

Evans, A; Whelehan, P; Thomson, K; Brauer, K; Jordan, L; Purdie, C; McLean, D; Baker, L; Vinnicombe, S; Thompson, A

2012-01-01

Background: The aim of this study was to assess the performance of shear wave elastography combined with BI-RADS classification of greyscale ultrasound images for benign/malignant differentiation in a large group of patients. Methods: One hundred and seventy-five consecutive patients with solid breast masses on routine ultrasonography undergoing percutaneous biopsy had the greyscale findings classified according to the American College of Radiology BI-RADS. The mean elasticity values from four shear wave images were obtained. Results: For mean elasticity vs greyscale BI-RADS, the performance results against histology were sensitivity: 95% vs 95%, specificity: 77% vs 69%, Positive Predictive Value (PPV): 88% vs 84%, Negative Predictive Value (NPV): 90% vs 91%, and accuracy: 89% vs 86% (all P>0.05). The results for the combination (positive result from either modality counted as malignant) were sensitivity 100%, specificity 61%, PPV 82%, NPV 100%, and accuracy 86%. The combination of BI-RADS greyscale and shear wave elastography yielded superior sensitivity to BI-RADS alone (P=0.03) or shear wave alone (P=0.03). The NPV was superior in combination compared with either alone (BI-RADS P=0.01 and shear wave P=0.02). Conclusion: Together, BI-RADS assessment of greyscale ultrasound images and shear wave ultrasound elastography are extremely sensitive for detection of malignancy. PMID:22691969

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

Breast cancer metastasis to the stomach resembling early gastric cancer.

PubMed

Eo, Wan Kyu

2008-12-01

Breast cancer metastases to the stomach are infrequent, with an estimated incidence rate of approximately 0.3%. Gastric metastases usually are derived from lobular rather than from ductal breast cancer. The most frequent type of a breast cancer metastasis as seen on endoscopy to the stomach is linitis plastica; features of a metastatic lesion that resemble early gastric cancer (EGC) are extremely rare. In this report, we present a case of a breast cancer metastasis to the stomach from an infiltrating ductal carcinoma (IDC) of the breast in a 48-year-old woman. The patient had undergone a left modified radical mastectomy with axillary dissection nine years prior. A gastric endoscopy performed for evaluation of nausea and anorexia showed the presence of a slightly elevated mucosal lesion in the cardia, suggestive of a type IIa EGC. A histological examination revealed nests of a carcinoma in the subepithelial lymphatics, and immunohistochemical staining for estrogen receptor was positive. This is an extremely rare case with features of type IIa EGC, but the lesion was finally identified as a cancer metastasis to the cardia of the stomach from an IDC of the breast.

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.

Evaluation of expert criteria for preoperative magnetic resonance imaging of newly diagnosed breast cancer.

PubMed

Behrendt, Carolyn E; Tumyan, Lusine; Gonser, Laura; Shaw, Sara L; Vora, Lalit; Paz, I Benjamin; Ellenhorn, Joshua D I; Yim, John H

2014-08-01

Despite 2 randomized trials reporting no reduction in operations or local recurrence at 1 year, preoperative magnetic resonance imaging (MRI) is increasingly used in diagnostic workup of breast cancer. We evaluated 5 utilization criteria recently proposed by experts. Of women (n = 340) newly diagnosed with unilateral breast cancer who underwent bilateral MRI, most (69.4%) met at least 1 criterion before MRI: mammographic density (44.4%), under consideration for partial breast irradiation (PBI) (19.7%), genetic-familial risk (12.9%), invasive lobular carcinoma (11.8%), and multifocal/multicentric disease (10.6%). MRI detected occult malignant lesion or extension of index lesion in 21.2% of index, 3.3% of contralateral, breasts. No expert criterion was associated with MRI-detected malignant lesion, which associated instead with pre-MRI plan of lumpectomy without PBI (48.2% of subjects): Odds Ratio 3.05, 95% CI 1.57-5.91 (p adjusted for multiple hypothesis testing = 0.007, adjusted for index-vs-contralateral breast and covariates). The expert guidelines were not confirmed by clinical evidence. Copyright © 2014 Elsevier Ltd. All rights reserved.

Phantom experiments using soft-prior regularization EIT for breast cancer imaging.

PubMed

Murphy, Ethan K; Mahara, Aditya; Wu, Xiaotian; Halter, Ryan J

2017-06-01

A soft-prior regularization (SR) electrical impedance tomography (EIT) technique for breast cancer imaging is described, which shows an ability to accurately reconstruct tumor/inclusion conductivity values within a dense breast model investigated using a cylindrical and a breast-shaped tank. The SR-EIT method relies on knowing the spatial location of a suspicious lesion initially detected from a second imaging modality. Standard approaches (using Laplace smoothing and total variation regularization) without prior structural information are unable to accurately reconstruct or detect the tumors. The soft-prior approach represents a very significant improvement to these standard approaches, and has the potential to improve conventional imaging techniques, such as automated whole breast ultrasound (AWB-US), by providing electrical property information of suspicious lesions to improve AWB-US's ability to discriminate benign from cancerous lesions. Specifically, the best soft-regularization technique found average absolute tumor/inclusion errors of 0.015 S m -1 for the cylindrical test and 0.055 S m -1 and 0.080 S m -1 for the breast-shaped tank for 1.8 cm and 2.5 cm inclusions, respectively. The standard approaches were statistically unable to distinguish the tumor from the mammary gland tissue. An analysis of false tumors (benign suspicious lesions) provides extra insight into the potential and challenges EIT has for providing clinically relevant information. The ability to obtain accurate conductivity values of a suspicious lesion (>1.8 cm) detected from another modality (e.g. AWB-US) could significantly reduce false positives and result in a clinically important technology.

A Prospective, Single Arm, Multi-site, Clinical Evaluation of a Nonradioactive Surgical Guidance Technology for the Location of Nonpalpable Breast Lesions during Excision.

PubMed

Cox, Charles E; Russell, Scott; Prowler, Vanessa; Carter, Ebonie; Beard, Abby; Mehindru, Ankur; Blumencranz, Peter; Allen, Kathleen; Portillo, Michael; Whitworth, Pat; Funk, Kristi; Barone, Julie; Norton, Denise; Schroeder, Jerome; Police, Alice; Lin, Erin; Combs, Freddie; Schnabel, Freya; Toth, Hildegard; Lee, Jiyon; Anglin, Beth; Nguyen, Minh; Canavan, Lynn; Laidley, Alison; Warden, Mary Jane; Prati, Ronald; King, Jeff; Shivers, Steven C

2016-10-01

This study was a multicenter evaluation of the SAVI SCOUT(®) breast localization and surgical guidance system using micro-impulse radar technology for the removal of nonpalpable breast lesions. The study was designed to validate the results of a recent 50-patient pilot study in a larger multi-institution trial. The primary endpoints were the rates of successful reflector placement, localization, and removal. This multicenter, prospective trial enrolled patients scheduled to have excisional biopsy or breast-conserving surgery of a nonpalpable breast lesion. From March to November 2015, 154 patients were consented and evaluated by 20 radiologists and 16 surgeons at 11 participating centers. Patients had SCOUT(®) reflectors placed up to 7 days before surgery, and placement was confirmed by mammography or ultrasonography. Implanted reflectors were detected by the SCOUT(®) handpiece and console. Presence of the reflector in the excised surgical specimen was confirmed radiographically, and specimens were sent for routine pathology. SCOUT(®) reflectors were successfully placed in 153 of 154 patients. In one case, the reflector was placed at a distance from the target that required a wire to be placed. All 154 lesions and reflectors were successfully removed during surgery. For 101 patients with a preoperative diagnosis of cancer, 86 (85.1 %) had clear margins, and 17 (16.8 %) patients required margin reexcision. SCOUT(®) provides a reliable and effective alternative method for the localization and surgical excision of nonpalpable breast lesions using no wires or radioactive materials, with excellent patient, radiologist, and surgeon acceptance.

Pre-Operative Planning Using Real-Time Virtual Sonography, an MRI/Ultrasound Image Fusion Technique, for Breast-Conserving Surgery in Patients with Non-Mass Enhancement on Breast MRI: A Preliminary Study.

PubMed

Ando, Takahito; Ito, Yukie; Ido, Mirai; Osawa, Manami; Kousaka, Junko; Mouri, Yukako; Fujii, Kimihito; Nakano, Shogo; Kimura, Junko; Ishiguchi, Tsuneo; Watanebe, Rie; Imai, Tsuneo; Fukutomi, Takashi

2018-07-01

The purpose of this retrospective study was to evaluate the effect of pre-operative planning using real-time virtual sonography (RVS), a magnetic resonance imaging (MRI)/ultrasound (US) image fusion technique on breast-conserving surgery (BCS) in patients with non-mass enhancement (NME) on breast MRI. Between 2011 and 2015, we enrolled 12 consecutive patients who had lesions with NME that exceeded the US hypo-echoic area, in which it was particularly difficult to evaluate the tumor margin. During pre-operative planning before breast-conserving surgery, RVS was used to delineate the enhancing area on the breast surface after additional supine breast MRI was performed. We analyzed both the surgical margin positivity rate and the re-operation rate. All NME lesions corresponded to the index cancer. In all patients, the diameter of the NME lesion was greater than that of the hypo-echoic lesion. The median diameters of the NME and hypo-echoic lesions were 24 mm (range: 12-39 mm) and 8.0 mm (range: 4.9-18 mm), respectively (p = 0.0002). After RVS-derived skin marking was performed on the surface of the affected breast, lumpectomy and quadrantectomy were conducted in 7 and 5 patients, respectively. The surgical margins were negative in 10 (83%) patients. Two patients with positive margins were found to have ductal carcinoma in situ in 1 duct each, 2.4 and 3.2 mm from the resection margin, respectively. None of the patients required additional resection. Although further prospective studies are required, the findings of our preliminary study suggest that it is very well possible that the use of RVS-derived skin marking during pre-operative planning for BCS in patients with NME would have resulted in surgical outcomes similar to or better than those obtained without the use of such marking. Copyright © 2018. Published by Elsevier Inc.

Wavelet-based 3D reconstruction of microcalcification clusters from two mammographic views: new evidence that fractal tumors are malignant and Euclidean tumors are benign.

PubMed

Batchelder, Kendra A; Tanenbaum, Aaron B; Albert, Seth; Guimond, Lyne; Kestener, Pierre; Arneodo, Alain; Khalil, Andre

2014-01-01

The 2D Wavelet-Transform Modulus Maxima (WTMM) method was used to detect microcalcifications (MC) in human breast tissue seen in mammograms and to characterize the fractal geometry of benign and malignant MC clusters. This was done in the context of a preliminary analysis of a small dataset, via a novel way to partition the wavelet-transform space-scale skeleton. For the first time, the estimated 3D fractal structure of a breast lesion was inferred by pairing the information from two separate 2D projected mammographic views of the same breast, i.e. the cranial-caudal (CC) and mediolateral-oblique (MLO) views. As a novelty, we define the "CC-MLO fractal dimension plot", where a "fractal zone" and "Euclidean zones" (non-fractal) are defined. 118 images (59 cases, 25 malignant and 34 benign) obtained from a digital databank of mammograms with known radiologist diagnostics were analyzed to determine which cases would be plotted in the fractal zone and which cases would fall in the Euclidean zones. 92% of malignant breast lesions studied (23 out of 25 cases) were in the fractal zone while 88% of the benign lesions were in the Euclidean zones (30 out of 34 cases). Furthermore, a Bayesian statistical analysis shows that, with 95% credibility, the probability that fractal breast lesions are malignant is between 74% and 98%. Alternatively, with 95% credibility, the probability that Euclidean breast lesions are benign is between 76% and 96%. These results support the notion that the fractal structure of malignant tumors is more likely to be associated with an invasive behavior into the surrounding tissue compared to the less invasive, Euclidean structure of benign tumors. Finally, based on indirect 3D reconstructions from the 2D views, we conjecture that all breast tumors considered in this study, benign and malignant, fractal or Euclidean, restrict their growth to 2-dimensional manifolds within the breast tissue.

Gastric metastasis from invasive lobular breast cancer, mimicking primary gastric cancer: A case report.

PubMed

Kim, Dae Hoon; Son, Seung-Myoung; Choi, Young Jin

2018-03-01

Gastric metastasis from invasive lobular breast cancer is relatively rare, commonly presented among multiple metastases, several years after primary diagnosis of breast cancer. Importantly, gastric cancer that is synchronously presented with lobular breast cancer can be misdiagnosed as primary gastric cancer; therefore, accurate differential diagnosis is required. A 39-year-old woman was visited to our hospital because of right breast mass and progressive dyspepsia. Invasive lobular carcinoma of breast was diagnosed on core needle biopsy. Gastroscopy revealed a diffuse scirrhous mass at the prepyloric antrum and diagnosed as poorly differentiated adenocarcinoma on biopsy. Synchronous double primary breast and gastric cancers were considered. Detailed pathological analysis focused on immunohistochemical studies of selected antibodies, including those of estrogen receptors, gross cystic disease fluid protein-15, and caudal-type homeobox transcription factor 2, were studied. As a result, gastric lesion was diagnosed as metastatic gastric cancer originating from breast. Right breast conserving surgery was performed, and duodenal stent was inserted under endoscopic guidance to relieve the patient's symptoms. Systemic chemotherapy with combined administration of paclitaxel and trastuzumab was initiated. Forty-one months after the diagnosis, the patient is still undergoing the same therapy. No recurrent lesion has been identified in the breast and evidence of a partial remission of gastric wall thickening has been observed on follow-up studies without new metastatic lesions. Clinical suspicion, repeat endoscopic biopsy, and detailed histological analysis, including immunohistochemistry, are necessary for diagnosis of metastatic gastric cancer from the breast.

Fatal Neonatal Herpes Simplex Infection Likely from Unrecognized Breast Lesions.

PubMed

Field, Scott S

2016-02-01

Type 1 herpes simplex virus (HSV-1) is very prevalent yet in rare circumstances can lead to fatal neonatal disease. Genital acquisition of type 2 HSV is the usual mode for neonatal herpes, but HSV-1 transmission by genital or extragenital means may result in greater mortality rates. A very rare scenario is presented in which the mode of transmission was likely through breast lesions. The lesions were seen by nurses as well as the lactation consultant and obstetrician in the hospital after delivery of the affected baby but not recognized as possibly being caused by herpes. The baby died 9 days after birth with hepatic failure and disseminated intravascular coagulation. Peripartum health care workers need to be aware of potential nongenital (including from the breast[s]) neonatal herpes acquisition, which can be lethal. © The Author(s) 2015.

Differential diagnosis of benign and malignant breast masses using diffusion-weighted magnetic resonance imaging.

PubMed

Min, Qinghua; Shao, Kangwei; Zhai, Lulan; Liu, Wei; Zhu, Caisong; Yuan, Lixin; Yang, Jun

2015-02-07

Diffusion-weighted magnetic resonance imaging (DW-MRI) is different from conventional diagnostic methods and has the potential to delineate the microscopic anatomy of a target tissue or organ. The purpose of our study was to evaluate the value of DW-MRI in the diagnosis of benign and malignant breast masses, which would help the clinical surgeon to decide the scope and pattern of operation. A total of 52 female patients with palpable solid breast masses received breast MRI scans using routine sequences, dynamic contrast-enhanced imaging, and diffusion-weighted echo-planar imaging at b values of 400, 600, and 800 s/mm(2), respectively. Two regions of interest (ROIs) were plotted, with a smaller ROI for the highest signal and a larger ROI for the overall lesion. Apparent diffusion coefficient (ADC) values were calculated at three different b values for all detectable lesions and from two different ROIs. The sensitivity, specificity, positive predictive value, and positive likelihood ratio of DW-MRI were determined for comparison with histological results. A total of 49 (49/52, 94.2%) lesions were detected using DW-MRI, including 20 benign lesions (two lesions detected in the same patient) and 29 malignant lesions. Benign lesion had a higher mean ADC value than their malignant counterparts, regardless of b value. According to the receiver operating characteristic (ROC) curve, the smaller-range ROI was more effective in differentiation between benign and malignant lesions. The area under the ROC curve was the largest at a b value of 800 s/mm(2). With a threshold ADC value at 1.23 × 10(-3) mm(2)/s, DW-MRI achieved a sensitivity of 82.8%, specificity of 90.0%, positive predictive value of 92.3%, and positive likelihood ratio of 8.3 for differentiating benign and malignant lesions. DW-MRI is an accurate diagnostic tool for differentiation between benign and malignant breast lesions, with an optimal b value of 800 s/mm(2). A smaller-range ROI focusing on the highest signal has a better differential value.

Accuracy of determining preoperative cancer extent measured by automated breast ultrasonography.

PubMed

Tozaki, Mitsuhiro; Fukuma, Eisuke

2010-12-01

The aim of this study was to determine the accuracy of measuring preoperative cancer extent using automated breast ultrasonography (US). This retrospective study consisted of 40 patients with histopathologically confirmed breast cancer. All of the patients underwent automated breast US (ABVS; Siemens Medical Solutions, Mountain View, CA, USA) on the day before the surgery. The sizes of the lesions on US were measured on coronal multiplanar reconstruction images using the ABVS workstation. Histopathological measurement of tumor size included not only the invasive foci but also any in situ component and was used as the gold standard. The discrepancy of the tumor extent between automated breast US and the histological examination was calculated. Automated breast US enabled visualization of the breast carcinomas in all patients. The mean size of the lesions on US was 12 mm (range 4-62 mm). The histopathological diagnosis was ductal carcinoma in situ (DCIS) in seven patients and invasive ductal carcinoma in 33 patients (18 without an intraductal component, 15 with an intraductal component). Lesions ranged in diameter from 4 to 65 mm (mean 16 mm). The accuracy of determination of the tumor extent with a deviation in length of <2 cm was 98% (39/40). Automated breast US is thought to be useful for evaluating tumor extent preoperatively.

Columnar cell change with atypia (flat epithelial atypia) on breast core biopsy-outcomes following open excision.

PubMed

Biggar, Magdalena A; Kerr, Kris M; Erzetich, Lisa M; Bennett, Ian C

2012-01-01

Columnar cell change with atypia (CCCA) is a relatively recently recognized pathologic breast entity considered to be a risk factor for subsequent development of breast carcinoma. The aim of this study was to investigate the significance of finding CCCA on breast core biopsy, by establishing the frequency of other breast pathology on subsequently performed surgical excision specimens. All cases with CCCA as the most advanced lesion on core biopsy were reviewed. After excision, another advanced proliferative lesion was identified in 17 (33%) patients, including three patients (6%) with in situ or invasive carcinoma. An additional five patients (10%) were concurrently diagnosed with primary breast carcinoma at other sites. These findings indicate that when CCCA is found on core biopsy, open surgical biopsy of the relevant area should be performed and that workup of both breasts should be undertaken to exclude coexistent breast carcinoma at alternative sites. © 2012 Wiley Periodicals, Inc.

Pathological criteria and practical issues in papillary lesions of the breast - a review.

PubMed

Ni, Yun-Bi; Tse, Gary M

2016-01-01

Papillary lesions of the breast include a broad spectrum of lesions, ranging from benign papilloma, papilloma with atypical ductal hyperplasia (ADH) or ductal carcinoma in situ (DCIS) to papillary carcinoma. The accurate diagnosis of mammary papillary lesions is a challenge for pathologists, owing to the overlapping features among these lesions. In this review, some of the diagnostic criteria of papillary lesions are discussed, with special emphasis on some key morphological features, namely fibrovascular cores, epithelial proliferation in a solid pattern, intraductal papilloma complicated by ADH or DCIS, and invasion and its mimics. The roles of immunohistochemistry, and the interpretation of myoepithelial cell markers, hormone receptors, and high molecular weight cytokeratin, are addressed. Finally, novel biomarkers and genetic aberrations in papillary lesions are summarized. © 2015 John Wiley & Sons Ltd.

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.

Characteristics of metastasis in the breast from extramammary malignancies.

PubMed

Lee, Se Kyung; Kim, Wan Wook; Kim, Sung Hoon; Hur, Sung Mo; Kim, Sangmin; Choi, Jae Hyuck; Cho, Eun Yoon; Han, Soo Yeon; Hahn, Boo-Kyung; Choe, Jun-Ho; Kim, Jung-Han; Kim, Jee Soo; Lee, Jeong Eon; Nam, Seok Jin; Yang, Jung-Hyun

2010-02-01

Breast metastasis from extramammary neoplasm is rare. We present the cases of metastasis to the breast after review of results in one institute and we want to show the difference of previous report. The surgical and pathology databases of Samsung Medical Center from November 1994 to March 2009 were investigated to identify all patients with a diagnosis of metastasis to the breast. Thirty-three patients with breast metastases from extramammary neoplasm were studied. Gastric carcinoma was most common metastatic origin in this study. There were four cases with microcalcifications in their metastatic lesions. This is the first report of microcalcification of metastatic lesions to the breast from hepatocellular carcinoma and gastric cancer. Pathologic examination and considering known clinical history may be helpful to differentiate the primary breast cancer and metastatic cancer. Metastasis to the breast from an extramammary neoplasm usually indicates disseminated metastatic disease and a poor prognosis. An accurate diagnosis of breast metastases, differentiating primary from metastatic breast carcinoma, is important for proper management.

Modified Core Wash Cytology: A reliable same day biopsy result for breast clinics.

PubMed

Bulte, J P; Wauters, C A P; Duijm, L E M; de Wilt, J H W; Strobbe, L J A

2016-12-01

Fine Needle Aspiration Biopsy (FNAB), Core Needle biopsy (CNB) and hybrid techniques including Core Wash Cytology (CWC) are available for same-day diagnosis in breast lesions. In CWC a washing of the biopsy core is processed for a provisional cytological diagnosis, after which the core is processed like a regular CNB. This study focuses on the reliability of CWC in daily practice. All consecutive CWC procedures performed in a referral breast centre between May 2009 and May 2012 were reviewed, correlating CWC results with the CNB result, definitive diagnosis after surgical resection and/or follow-up. Symptomatic as well as screen-detected lesions, undergoing CNB were included. 1253 CWC procedures were performed. Definitive histology showed 849 (68%) malignant and 404 (32%) benign lesions. 80% of CWC procedures yielded a conclusive diagnosis: this percentage was higher amongst malignant lesions and lower for benign lesions: 89% and 62% respectively. Sensitivity and specificity of a conclusive CWC result were respectively 98.3% and 90.4%. The eventual incidence of malignancy in the cytological 'atypical' group (5%) was similar to the cytological 'benign' group (6%). CWC can be used to make a reliable provisional diagnosis of breast lesions within the hour. The high probability of conclusive results in malignant lesions makes CWC well suited for high risk populations. Copyright © 2016 Elsevier Ltd, BASO ~ the Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Contrast-enhanced digital mammography (CEDM): imaging modeling, computer simulations, and phantom study

NASA Astrophysics Data System (ADS)

Chen, Biao; Jing, Zhenxue; Smith, Andrew

2005-04-01

Contrast enhanced digital mammography (CEDM), which is based upon the analysis of a series of x-ray projection images acquired before/after the administration of contrast agents, may provide physicians critical physiologic and morphologic information of breast lesions to determine the malignancy of lesions. This paper proposes to combine the kinetic analysis (KA) of contrast agent uptake/washout process and the dual-energy (DE) contrast enhancement together to formulate a hybrid contrast enhanced breast-imaging framework. The quantitative characteristics of materials and imaging components in the x-ray imaging chain, including x-ray tube (tungsten) spectrum, filter, breast tissues/lesions, contrast agents (non-ionized iodine solution), and selenium detector, were systematically modeled. The contrast-noise-ration (CNR) of iodinated lesions and mean absorbed glandular dose were estimated mathematically. The x-ray techniques optimization was conducted through a series of computer simulations to find the optimal tube voltage, filter thickness, and exposure levels for various breast thicknesses, breast density, and detectable contrast agent concentration levels in terms of detection efficiency (CNR2/dose). A phantom study was performed on a modified Selenia full field digital mammography system to verify the simulated results. The dose level was comparable to the dose in diagnostic mode (less than 4 mGy for an average 4.2 cm compressed breast). The results from the computer simulations and phantom study are being used to optimize an ongoing clinical study.

[Caries patterns and diet in early childhood caries].

PubMed

Faye, M; Ba, A A; Yam, A A; Ba, I

2006-01-01

Early childhood caries (EEC) are multiple carious lesions affecting the primary teeth of infants and preschool children. They are related to a prolonged and night bottle-feeding rich in fermentable carbohydrates. The carious lesions characterised by their patterns and the rapidity of their process can lead to a widespread tooth destruction. The aim of this study was to evaluate the patterns of the carious lesions and their relationship to the diet. This prospective study was carried out in Dakar in public heath structures that have a dental office. It has included 68 children of both sex aged from two to 6 years consisted of 35 boys (51% of the sample) and 33 girls (49%) with the predominance of the 5-year-old children. These children were examined using a plan mouth mirror and probes and their mothers were interviewed. The observed carious lesions were distributed on all tooth surfaces but the complete coronal destruction was the most common lesions observed and represented 25 of the lesions, followed by lesions in three faces of the tooth (17%). The most frequently affected tooth was the association maxillar incisors and molars and the mandibular molars (32.4%). The incisor alone represented 22.1% of the affected teeth. The children were breast-fed associated with either pap or with hard food (52.9%). The bottle was added to this association in 32.4% of the cases and 10% of the children were exclusively breast-fed. The carious lesions were more severe and more frequent in children fed with breast associated with pap and hard food and in those fed with breast associated with the bottle pap and food than to children exclusively breast-fed. These differences were not statistically significant (p = 0.73 > 0.05). Early childhood caries are related to a diet rich in carbon hydrate. They lead to severe tooth destruction. The treatments cost are very high thus prevention by information on the bad effects of sugar on diet and the baby bottle are of great interest.

Lesion stiffness measured by shear-wave elastography: Preoperative predictor of the histologic underestimation of US-guided core needle breast biopsy.

PubMed

Park, Ah Young; Son, Eun Ju; Kim, Jeong-Ah; Han, Kyunghwa; Youk, Ji Hyun

2015-12-01

To determine whether lesion stiffness measured by shear-wave elastography (SWE) can be used to predict the histologic underestimation of ultrasound (US)-guided 14-gauge core needle biopsy (CNB) for breast masses. This retrospective study enrolled 99 breast masses from 93 patients, including 40 high-risk lesions and 59 ductal carcinoma in situ (DCIS), which were diagnosed by US-guided 14-gauge CNB. SWE was performed for all breast masses to measure quantitative elasticity values before US-guided CNB. To identify the preoperative factors associated with histologic underestimation, patients' age, symptoms, lesion size, B-mode US findings, and quantitative SWE parameters were compared according to the histologic upgrade after surgery using the chi-square test, Fisher's exact test, or independent t-test. The independent factors for predicting histologic upgrade were evaluated using multivariate logistic regression analysis. The underestimation rate was 28.3% (28/99) in total, 25.0% (10/40) in high-risk lesions, and 30.5% (18/59) in DCIS. All elasticity values of the upgrade group were significantly higher than those of the non-upgrade group (P<0.001). On multivariate analysis, the mean (Odds ratio [OR]=1.021, P=0.001), maximum (OR=1.015, P=0.008), and minimum (OR=1.028, P=0.001) elasticity values were independently associated with histologic underestimation. The patients' age, lesion size, and final assessment category on US of the upgrade group were higher than those of the non-upgrade group (P=0.046 for age; P=0.021 for lesion size; P=0.030 for US category), but these were not independent predictors of histologic underestimation on multivariate analysis. Breast lesion stiffness quantitatively measured by SWE could be helpful to predict the underestimation of malignancy in US-guided 14-gauge CNB. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Comparison of dynamic contrast-enhanced MRI parameters of breast lesions at 1.5 and 3.0 T: a pilot study

PubMed Central

Pineda, F D; Medved, M; Fan, X; Ivancevic, M K; Abe, H; Shimauchi, A; Newstead, G M

2015-01-01

Objective: To compare dynamic contrast-enhanced (DCE) MRI parameters from scans of breast lesions at 1.5 and 3.0 T. Methods: 11 patients underwent paired MRI examinations in both Philips 1.5 and 3.0 T systems (Best, Netherlands) using a standard clinical fat-suppressed, T1 weighted DCE-MRI protocol, with 70–76 s temporal resolution. Signal intensity vs time curves were fit with an empirical mathematical model to obtain semi-quantitative measures of uptake and washout rates as well as time-to-peak enhancement (TTP). Maximum percent enhancement and signal enhancement ratio (SER) were also measured for each lesion. Percent differences between parameters measured at the two field strengths were compared. Results: TTP and SER parameters measured at 1.5 and 3.0 T were similar; with mean absolute differences of 19% and 22%, respectively. Maximum percent signal enhancement was significantly higher at 3 T than at 1.5 T (p = 0.006). Qualitative assessment showed that image quality was significantly higher at 3 T (p = 0.005). Conclusion: Our results suggest that TTP and SER are more robust to field strength change than other measured kinetic parameters, and therefore measurements of these parameters can be more easily standardized than measurements of other parameters derived from DCE-MRI. Semi-quantitative measures of overall kinetic curve shape showed higher reproducibility than do discrete classification of kinetic curve early and delayed phases in a majority of the cases studied. Advances in knowledge: Qualitative measures of curve shape are not consistent across field strength even when acquisition parameters are standardized. Quantitative measures of overall kinetic curve shape, by contrast, have higher reproducibility. PMID:25785918

Colorectal breast carcinoma metastasis diagnosed as an obstructive colonic primary tumor. A case report and review of the literature.

PubMed

Théraux, J; Bretagnol, F; Guedj, N; Cazals-Hatem, D; Panis, Y

2009-12-01

Common sites of colorectal breast carcinoma metastasis are bones, lungs, the central nervous system and the liver. Metastases in the gastrointestinal (GI) tract are rare and especially involve the stomach rather than the colon. Clinical or radiological features usually cannot differentiate them from a primary colorectal tumor, resulting in inappropriate treatment. In some cases, this lesion suggests multifocal spread of breast cancer with peritoneal carcinomatosis. Colorectal breast cancer metastasis is a rare finding and there is no consensus on the management of these lesions. The present case report describes a 69-year-old female with metastatic breast cancer presenting as an obstructive tumor of the transverse colon.

[Elastography as an additional tool in breast sonography. Technical principles and clinical applications].

PubMed

Rjosk-Dendorfer, D; Reichelt, A; Clevert, D-A

2014-03-01

In recent years the use of elastography in addition to sonography has become a routine clinical tool for the characterization of breast masses. Whereas free hand compression elastography results in qualitative imaging of tissue stiffness due to induced compression, shear wave elastography displays quantitative information of tissue displacement. Recent studies have investigated the use of elastography in addition to sonography and improvement of specificity in differentiating benign from malignant breast masses could be shown. Therefore, additional use of elastography could help to reduce the number of unnecessary biopsies in benign breast lesions especially in category IV lesions of the ultrasound breast imaging reporting data system (US-BI-RADS).

Hematolymphoid lesions of the breast.

PubMed

Hoffmann, Jenny; Ohgami, Robert S

2017-09-01

Hematolymphoid malignancies of the breast are most commonly neoplasms of mature B-lymphocytes, and may arise as a primary disease or by secondary involvement of a systemic disease. Primary breast lymphomas (PBL) account for 0.04-0.5% of breast malignancies, less than 1% of all non-Hodgkin's lymphomas (NHL), and less than 5% of extranodal lymphomas (Lakhani et al., 2012; Swerdlow et al., 2008; Joks et al., 2011; Barişta et al., 2000; Giardini et al., 1992; Brogi and Harris, 1999; Topalovski et al., 1999). 1-7 Secondary breast lymphomas (SBL) are also rare, with an estimated annual incidence of 0.07% (Domchek et al., 2002; Talwalkar et al., 2008). 8,9 Recognition of breast lesions as hematolymphoid is critical to distinguish them from other entities that can occur in the breast. Copyright © 2017. Published by Elsevier Inc.

Comparative performance of multiview stereoscopic and mammographic display modalities for breast lesion detection

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

Webb, Lincoln J.; Samei, Ehsan; Lo, Joseph Y.

2011-04-15

Purpose: Mammography is known to be one of the most difficult radiographic exams to interpret. Mammography has important limitations, including the superposition of normal tissue that can obscure a mass, chance alignment of normal tissue to mimic a true lesion and the inability to derive volumetric information. It has been shown that stereomammography can overcome these deficiencies by showing that layers of normal tissue lay at different depths. If standard stereomammography (i.e., a single stereoscopic pair consisting of two projection images) can significantly improve lesion detection, how will multiview stereoscopy (MVS), where many projection images are used, compare to mammography?more » The aim of this study was to assess the relative performance of MVS compared to mammography for breast mass detection. Methods: The MVS image sets consisted of the 25 raw projection images acquired over an arc of approximately 45 deg. using a Siemens prototype breast tomosynthesis system. The mammograms were acquired using a commercial Siemens FFDM system. The raw data were taken from both of these systems for 27 cases and realistic simulated mass lesions were added to duplicates of the 27 images at the same local contrast. The images with lesions (27 mammography and 27 MVS) and the images without lesions (27 mammography and 27 MVS) were then postprocessed to provide comparable and representative image appearance across the two modalities. All 108 image sets were shown to five full-time breast imaging radiologists in random order on a state-of-the-art stereoscopic display. The observers were asked to give a confidence rating for each image (0 for lesion definitely not present, 100 for lesion definitely present). The ratings were then compiled and processed using ROC and variance analysis. Results: The mean AUC for the five observers was 0.614{+-}0.055 for mammography and 0.778{+-}0.052 for multiview stereoscopy. The difference of 0.164{+-}0.065 was statistically significant with a p-value of 0.0148. Conclusions: The differences in the AUCs and the p-value suggest that multiview stereoscopy has a statistically significant advantage over mammography in the detection of simulated breast masses. This highlights the dominance of anatomical noise compared to quantum noise for breast mass detection. It also shows that significant lesion detection can be achieved with MVS without any of the artifacts associated with tomosynthesis.« less

Posterior medial meniscus root ligament lesions: MRI classification and associated findings.

PubMed

Choi, Ja-Young; Chang, Eric Y; Cunha, Guilherme M; Tafur, Monica; Statum, Sheronda; Chung, Christine B

2014-12-01

The purposes of this study were to determine the prevalence of altered MRI appearances of "posterior medial meniscus root ligament (PMMRL)" lesions, introduce a classification of lesion types, and report associated findings. We retrospectively reviewed 419 knee MRI studies to identify the presence of PMMRL lesions. Classification was established on the basis of lesions encountered. The medial compartment was assessed for medial meniscal tears in the meniscus proper, medial meniscal extrusion, insertional PMMRL osseous changes, regional synovitis, osteoarthritis, insufficiency fracture, and cruciate ligament abnormality. PMMRL abnormalities occurred in 28.6% (120/419) of the studies: degeneration, 14.3% (60/419) and tear, 14.3% (60/419). Our classification system included degeneration and tearing. Tearing was categorized as partial or complete with delineation of the point of failure as entheseal, midsubstance, or junction to meniscus. Of all tears, 93.3% (56/60) occurred at the meniscal junction. Univariate analysis revealed significant differences between the knees with and without PMMRL lesions in age, medial meniscal tear, medial meniscal extrusion, insertional PMMRL osseous change, regional synovitis, osteoarthritis, insufficiency fracture (p=0.017), and cruciate ligament degeneration (p<0.001). PMMRL lesions are commonly detected in symptomatic patients. We have introduced an MRI classification system. PMMRL lesions are significantly associated with age, medial meniscal tears, medial meniscal extrusion, insertional PMMRL osseous change, regional synovitis, osteoarthritis, insufficiency fracture, and cruciate ligament degeneration.

Influence of Texture and Colour in Breast TMA Classification

PubMed Central

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

2015-01-01

Breast cancer diagnosis is still done by observation of biopsies under the microscope. The development of automated methods for breast TMA classification would reduce diagnostic time. This paper is a step towards the solution for this problem and shows a complete study of breast TMA classification based on colour models and texture descriptors. The TMA images were divided into four classes: i) benign stromal tissue with cellularity, ii) adipose tissue, iii) benign and benign anomalous structures, and iv) ductal and lobular carcinomas. A relevant set of features was obtained on eight different colour models from first and second order Haralick statistical descriptors obtained from the intensity image, Fourier, Wavelets, Multiresolution Gabor, M-LBP and textons descriptors. Furthermore, four types of classification experiments were performed using six different classifiers: (1) classification per colour model individually, (2) classification by combination of colour models, (3) classification by combination of colour models and descriptors, and (4) classification by combination of colour models and descriptors with a previous feature set reduction. The best result shows an average of 99.05% accuracy and 98.34% positive predictive value. These results have been obtained by means of a bagging tree classifier with combination of six colour models and the use of 1719 non-correlated (correlation threshold of 97%) textural features based on Statistical, M-LBP, Gabor and Spatial textons descriptors. PMID:26513238

Automated analysis of non-mass-enhancing lesions in breast MRI based on morphological, kinetic, and spatio-temporal moments and joint segmentation-motion compensation technique

NASA Astrophysics Data System (ADS)

Hoffmann, Sebastian; Shutler, Jamie D.; Lobbes, Marc; Burgeth, Bernhard; Meyer-Bäse, Anke

2013-12-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) represents an established method for the detection and diagnosis of breast lesions. While mass-like enhancing lesions can be easily categorized according to the Breast Imaging Reporting and Data System (BI-RADS) MRI lexicon, a majority of diagnostically challenging lesions, the so called non-mass-like enhancing lesions, remain both qualitatively as well as quantitatively difficult to analyze. Thus, the evaluation of kinetic and/or morphological characteristics of non-masses represents a challenging task for an automated analysis and is of crucial importance for advancing current computer-aided diagnosis (CAD) systems. Compared to the well-characterized mass-enhancing lesions, non-masses have no well-defined and blurred tumor borders and a kinetic behavior that is not easily generalizable and thus discriminative for malignant and benign non-masses. To overcome these difficulties and pave the way for novel CAD systems for non-masses, we will evaluate several kinetic and morphological descriptors separately and a novel technique, the Zernike velocity moments, to capture the joint spatio-temporal behavior of these lesions, and additionally consider the impact of non-rigid motion compensation on a correct diagnosis.

Automatic ultrasound image enhancement for 2D semi-automatic breast-lesion segmentation

NASA Astrophysics Data System (ADS)

Lu, Kongkuo; Hall, Christopher S.

2014-03-01

Breast cancer is the fastest growing cancer, accounting for 29%, of new cases in 2012, and second leading cause of cancer death among women in the United States and worldwide. Ultrasound (US) has been used as an indispensable tool for breast cancer detection/diagnosis and treatment. In computer-aided assistance, lesion segmentation is a preliminary but vital step, but the task is quite challenging in US images, due to imaging artifacts that complicate detection and measurement of the suspect lesions. The lesions usually present with poor boundary features and vary significantly in size, shape, and intensity distribution between cases. Automatic methods are highly application dependent while manual tracing methods are extremely time consuming and have a great deal of intra- and inter- observer variability. Semi-automatic approaches are designed to counterbalance the advantage and drawbacks of the automatic and manual methods. However, considerable user interaction might be necessary to ensure reasonable segmentation for a wide range of lesions. This work proposes an automatic enhancement approach to improve the boundary searching ability of the live wire method to reduce necessary user interaction while keeping the segmentation performance. Based on the results of segmentation of 50 2D breast lesions in US images, less user interaction is required to achieve desired accuracy, i.e. < 80%, when auto-enhancement is applied for live-wire segmentation.

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.

Risks of Being Malignant or High Risk and Their Characteristics in Breast Lesions 20 mm or Larger After Benign Results on Ultrasonography-Guided 14-Gauge Core Needle Biopsy.

PubMed

Moon, Hee Jung; Kim, Min Jung; Yoon, Jung Hyun; Kim, Eun-Kyung

2016-06-01

The malignancy risk, risk of being high-risk lesions after benign results on ultrasonography-guided 14-gauge core needle biopsies (US-CNBs), and their characteristics in breast lesions of 20 mm or greater were investigated. Eight hundred forty-seven breast lesions with benign results on US-CNB were classified as benign, high risk, and malignant through excision and clinical follow-up. The risks of being malignant or high risk were analyzed in all lesions, lesions 20 to 29 mm, and lesions 30 mm or greater. Their clinicopathological characteristics were evaluated. Of 847, 18 (2.1%) were malignant, 53 (6.3%) were high-risk lesions, and 776 (91.6%) were benign. Of 18 malignancies, 6 (33.3%) were malignant phyllodes tumors and 12 (66.7%) were carcinomas. In benign lesions 20 to 29 mm, risks of being malignant or high risk were 1.6% (9 of 566) and 4.4% (25 of 566). In 281 lesions 30 mm or greater, the risks of being malignant or high risk were 3.2% and 10%. The risk of being high risk in lesions 30 mm or greater was 10%, significantly higher than 4.4% of lesions 20 to 29 mm (P = 0.002). Excision can be considered in lesions measuring 20 mm or larger because of the 2.1% malignancy risk and the 6.3% risk of being high-risk lesions despite benign results on US-CNB. Excision should be considered in lesions measuring 30 mm or larger because of the 3.2% malignancy risk and the 10% risk of being high-risk lesions.

Reading the lesson: eliciting requirements for a mammography training application

NASA Astrophysics Data System (ADS)

Hartswood, M.; Blot, L.; Taylor, P.; Anderson, S.; Procter, R.; Wilkinson, L.; Smart, L.

2009-02-01

Demonstrations of a prototype training tool were used to elicit requirements for an intelligent training system for screening mammography. The prototype allowed senior radiologists (mentors) to select cases from a distributed database of images to meet the specific training requirements of junior colleagues (trainees) and then provided automated feedback in response to trainees' attempts at interpretation. The tool was demonstrated to radiologists and radiographers working in the breast screening service at four evaluation sessions. Participants highlighted ease of selecting cases that can deliver specific learning objectives as important for delivering effective training. To usefully structure a large data set of training images we undertook a classification exercise of mentor authored free text 'learning points' attached to training case obtained from two screening centres (n=333, n=129 respectively). We were able to adduce a hierarchy of abstract categories representing classes of lesson that groups of cases were intended to convey (e.g. Temporal change, Misleading juxtapositions, Position of lesion, Typical/Atypical presentation, and so on). In this paper we present the method used to devise this classification, the classification scheme itself, initial user-feedback, and our plans to incorporated it into a software tool to aid case selection.

An approach to the diagnosis of flat intraepithelial lesions of the urinary bladder using the World Health Organization/ International Society of Urological Pathology consensus classification system.

PubMed

Amin, Mahul B; McKenney, Jesse K

2002-07-01

The classification of flat urothelial (transitional cell) lesions with atypia has historically varied in its application from institution to institution with no fewer than six major nomenclature systems proposed in the past 25 years. In 1998, the World Health Organization/ International Society of Urological Pathology (WHO/ISUP) published a consensus classification that included the following categories for flat urinary bladder lesions: reactive atypia, atypia of unknown significance, dysplasia (low-grade intraepithelial neoplasia), and carcinoma in situ (high-grade intraepithelial neoplasia). This classification expands the definition traditionally used for urothelial carcinoma in situ, basing its diagnosis primarily on the severity of cytologic changes. In proposing the classification system for flat lesions of the bladder with atypia, it was hoped that consistent use of uniform diagnostic terminology would ultimately aid in a better understanding of the biology of these lesions. In this review, the authors discuss the history of the concept of flat urothelial neoplasia, the rationale and histologic criteria for the WHO/ISUP diagnostic categories, an approach to the diagnosis of flat lesions, and problems and pitfalls associated with their recognition in routine surgical pathology specimens.

Significance of resistive index in color Doppler ultrasonogram: differentiation between benign and malignant breast masses.

PubMed

Choi, H Y; Kim, H Y; Baek, S Y; Kang, B C; Lee, S W

1999-01-01

The objective of this article is to evaluate the significance of resistive index in differentiation between benign and malignant breast lesions on duplex ultrasonographic examination. Resistive indices obtained in 106 breast lesions of 104 patients were included. Sixty-four were benign (mean age: 32.4 +/- 11.1 years), and 42 were malignant lesions (mean age: 47.8 +/- 11.4 years). The resistive index was classified as follows: below 0.49, from 0.5 to 0.59, 0.6 to 0.69, 0.7 to 0.79, and above 0.8. We analyzed and defined the optimal threshold value of RI between benign and malignant lesions. The mean values of the RI of benign and malignant lesions were 0.62 +/- 0.095 (range 0.44-0.86) and 0.74 +/- 0.097 (range, 0.50-0.92), respectively. The resistive index exceeded 0.7 in 80% of malignant lesions. The difference of the RI between malignant and benign lesions was statistically significant when the threshold value was 0.7 (P < 0.001). A resistive index over 0.7 may suggest malignant lesions. Due to the considerable overlap of the range of the RI, it may not be diagnostic in any single patient; however, it may be helpful in conjunct with gray-scale image.

Analysis of 3D Subharmonic Ultrasound Signals from Patients with Known Breast Masses for Lesion Differentiation

DTIC Science & Technology

2012-10-01

separate image processing course were attended and this programming language will be used for the research component of this project. Subharmonic...4 5 BODY ...lesions. 5 BODY 5.1 Training Component The training component of this research has been split into breast imaging and image processing arms

Computed tomography guided localization of clinically occult breast carcinoma-the ''N'' skin guide

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

Kopans, D.B.; Meyer, J.E.

1982-10-01

Standard computed tomography (CT) can be used for the three-dimensional localization of clinically occult suspicious breast lesions whose exact position cannot be determined by standard mammographic views. A method is described that facilitates accurate preoperative needle localization using CT guidance, once the position of these lesions is defined.

Extraction of breast lesions from ultrasound imagery: Bhattacharyya gradient flow approach

NASA Astrophysics Data System (ADS)

Torkaman, Mahsa; Sandhu, Romeil; Tannenbaum, Allen

2018-03-01

Breast cancer is one of the most commonly diagnosed neoplasms among American women and the second leading cause of death among women all over the world. In order to reduce the mortality rate and cost of treatment, early diagnosis and treatment are essential. Accurate and reliable diagnosis is required in order to ensure the most effective treatment and a second opinion is often advisable. In this paper, we address the problem of breast lesion detection from ultrasound imagery by means of active contours, whose evolution is driven by maximizing the Bhattacharyya distance1 between the probability density functions (PDFs). The proposed method was applied to ultrasound breast imagery, and the lesion boundary was obtained by maximizing the distance-based energy functional such that the maximum (optimal contour) is attained at the boundary of the potential lesion. We compared the results of the proposed method quantitatively using the Dice coefficient (similarity index)2 to well-known GrowCut segmentation method3 and demonstrated that Bhattacharyya approach outperforms GrowCut in most of the cases.

Initial Experience with a Wireless Ultrasound-Guided Vacuum-Assisted Breast Biopsy Device

PubMed Central

Choi, E-Ryung; Han, Boo-Kyung; Ko, Eun Sook; Ko, Eun Young; Choi, Ji Soo; Cho, Eun Yoon; Nam, Seok Jin

2015-01-01

Objective To determine the imaging characteristic of frequent target lesions of wireless ultrasound (US)-guided, vacuum-assisted breast biopsy (Wi-UVAB) and to evaluate diagnostic yield, accuracy and complication of the device in indeterminate breast lesions. Materials and Methods From March 2013 to October 2014, 114 women (age range, 29–76 years; mean age, 50.0 years) underwent Wi-UVAB using a 13-gauge needle (Mammotome Elite®; Devicor Medical Products, Cincinnati, OH, USA). In 103 lesions of 96 women with surgical (n = 81) or follow-up (n = 22) data, complications, biopsy procedure, imaging findings of biopsy targets and histologic results were reviewed. Results Mean number of biopsy cores was 10 (range 4–25). Nine patients developed moderate bleeding. All lesions were suspicious on US, and included non-mass lesions (67.0%) and mass lesions (33.0%). Visible calcifications on US were evident in 57.3% of the target lesions. Most of the lesions (93.2%) were nonpalpable. Sixty-six (64.1%) were malignant [ductal carcinoma in situ (DCIS) rate, 61%] and 12 were high-risk lesions (11.7%). Histologic underestimation was identified in 11 of 40 (27.5%). DCIS cases and in 3 of 9 (33.3%) high-risk lesions necessitating surgery. There was no false-negative case. Conclusion Wi-UVAB is very handy and advantageous for US-unapparent non-mass lesions to diagnose DCIS, especially for calcification cases. Histologic underestimation is unavoidable; still, Wi-UVAB is safe and accurate to diagnose a malignancy. PMID:26630136

Diagnostic value of 99mTc-bombesin scintigraphy for differentiation of malignant from benign breast lesions.

PubMed

Shariati, Farzaneh; Aryana, Kamran; Fattahi, Asiehsadat; Forghani, Mohammad N; Azarian, Azita; Zakavi, Seyed R; Sadeghi, Ramin; Ayati, Narjes; Sadri, Keyvan

2014-06-01

In this study, we evaluated the diagnostic accuracy of (99m)Tc-bombesin scintigraphy for differentiation of benign from malignant palpable breast lesions. (99m)Tc-Bombesin is a tracer with high affinity for gastrin-releasing peptide receptor, which is overexpressed on a variety of human tumors including breast carcinoma. We examined 33 consecutive women who were referred to our center with suspicious palpable breast lesions but had no definitive diagnosis in other imaging procedures. A volume of 370-444 MBq of (99m)Tc-bombesin was injected and dynamic 1-min images were taken for 20 min immediately after injection in anterior view. Thereafter, two static images in anterior and prone-lateral views were taken for 5 min. Finally, single-photon emission computed tomography images were taken for each patient. Definitive diagnosis was based on biopsy and histopathological evaluation. The scan findings were positive in 19 patients and negative in 11 on visual assessment of the planar and single-photon emission computed tomography images. Pathologic examination confirmed breast carcinoma in 12 patients with positive scans and benign pathology for 18 patients. The overall sensitivity, specificity, negative and positive predictive values, and accuracy of this radiotracer for diagnosis of breast cancer were 100, 66.1, 100, 63, and 76%, respectively. Semiquantitative analysis improved the specificity of the visual assessment from 66 to 84%. Our study showed that (99m)Tc-bombesin scintigraphy has a high sensitivity and negative predictive value for detecting malignant breast lesions, but the specificity and positive predictive value of this radiotracer for differentiation of malignant breast abnormalities from benign ones are relatively low.

FNAC: its role, limitations and perspective in the preoperative diagnosis of breast cancer.

PubMed

Zagorianakou, P; Fiaccavento, S; Zagorianakou, N; Makrydimas, G; Stefanou, D; Agnantis, N J

2005-01-01

Fine-needle aspiration cytology (FNAC) was first described and performed in 1930. Thirty years later, it gained acceptance first in Europe and about a decade later in North America. The method is generally considered as a rapid, reliable, safe diagnostic tool to distinguish non-neoplastic from neoplastic breast lesions. In developed countries, in the last 20 years, mammographic screening programmes, which have been used extensively, are designed to detect the earliest possible breast cancer. The FNAC report is extremely important because it gives the necessary information for the management of patients, in order to proceed with more invasive diagnostic methods or surgical treatment, and to decide what kind of operation to perform. In the preoperative phase, FNAC has taken a fundamental role of both palpable and nonpalpable lesions, using ultrasound or stereotactic guidance. New developed techniques, breast biopsy instrumentation (ABBI) and mammotome have the advantage of complete removal of breast lesions, but this is not possible in all the examined cases. In developing countries, economical restrictions, low budget for health care and screening programmes put the patients at a disadvantage because of the high cost of sophisticated diagnostic methods, thus we recommend that FNAC be used as a routine diagnostic method because of its low cost compared with the others and this policy maximizes the availability of health care to women with breast cancer. We conclude that FNAC plays an important and essential role in the management of patients with breast lesions and also offers a great potential for prediction of patient outcome, disease response to therapy and assessment of risk of developing breast cancer. The reliability and efficiency of the method depends on the quality of the samples and the experience of the medical staff that performs the aspiration.

Radiation-induced sarcoma of the breast in a female adolescent. Case report with histologic and therapeutic considerations

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

Squire, R.; Bianchi, A.; Jakate, S.M.

A 14-year-old girl developed a radiation-induced sarcoma of the left breast after successful combined surgical and radiation therapy of a left adrenal carcinoma when she was 9 months old. The breast lesion was histologically described as a stromal sarcoma with fibrosarcomatous and myxosarcomatous areas. The second primary lesion and local recurrence of this was treated with surgery. At each recurrence the tumor became more aggressive both clinically and histologically, and eventually proved fatal.

Raman spectroscopic sensing of carbonate intercalation in breast microcalcifications at stereotactic biopsy

PubMed Central

Sathyavathi, R.; Saha, Anushree; Soares, Jaqueline S.; Spegazzini, Nicolas; McGee, Sasha; Rao Dasari, Ramachandra; Fitzmaurice, Maryann; Barman, Ishan

2015-01-01

Microcalcifications are an early mammographic sign of breast cancer and frequent target for stereotactic biopsy. Despite their indisputable value, microcalcifications, particularly of the type II variety that are comprised of calcium hydroxyapatite deposits, remain one of the least understood disease markers. Here we employed Raman spectroscopy to elucidate the relationship between pathogenicity of breast lesions in fresh biopsy cores and composition of type II microcalcifications. Using a chemometric model of chemical-morphological constituents, acquired Raman spectra were translated to characterize chemical makeup of the lesions. We find that increase in carbonate intercalation in the hydroxyapatite lattice can be reliably employed to differentiate benign from malignant lesions, with algorithms based only on carbonate and cytoplasmic protein content exhibiting excellent negative predictive value (93–98%). Our findings highlight the importance of calcium carbonate, an underrated constituent of microcalcifications, as a spectroscopic marker in breast pathology evaluation and pave the way for improved biopsy guidance. PMID:25927331

Raman spectroscopic sensing of carbonate intercalation in breast microcalcifications at stereotactic biopsy

NASA Astrophysics Data System (ADS)

Sathyavathi, R.; Saha, Anushree; Soares, Jaqueline S.; Spegazzini, Nicolas; McGee, Sasha; Rao Dasari, Ramachandra; Fitzmaurice, Maryann; Barman, Ishan

2015-04-01

Microcalcifications are an early mammographic sign of breast cancer and frequent target for stereotactic biopsy. Despite their indisputable value, microcalcifications, particularly of the type II variety that are comprised of calcium hydroxyapatite deposits, remain one of the least understood disease markers. Here we employed Raman spectroscopy to elucidate the relationship between pathogenicity of breast lesions in fresh biopsy cores and composition of type II microcalcifications. Using a chemometric model of chemical-morphological constituents, acquired Raman spectra were translated to characterize chemical makeup of the lesions. We find that increase in carbonate intercalation in the hydroxyapatite lattice can be reliably employed to differentiate benign from malignant lesions, with algorithms based only on carbonate and cytoplasmic protein content exhibiting excellent negative predictive value (93-98%). Our findings highlight the importance of calcium carbonate, an underrated constituent of microcalcifications, as a spectroscopic marker in breast pathology evaluation and pave the way for improved biopsy guidance.

Raman spectroscopic sensing of carbonate intercalation in breast microcalcifications at stereotactic biopsy.

PubMed

Sathyavathi, R; Saha, Anushree; Soares, Jaqueline S; Spegazzini, Nicolas; McGee, Sasha; Rao Dasari, Ramachandra; Fitzmaurice, Maryann; Barman, Ishan

2015-04-30

Microcalcifications are an early mammographic sign of breast cancer and frequent target for stereotactic biopsy. Despite their indisputable value, microcalcifications, particularly of the type II variety that are comprised of calcium hydroxyapatite deposits, remain one of the least understood disease markers. Here we employed Raman spectroscopy to elucidate the relationship between pathogenicity of breast lesions in fresh biopsy cores and composition of type II microcalcifications. Using a chemometric model of chemical-morphological constituents, acquired Raman spectra were translated to characterize chemical makeup of the lesions. We find that increase in carbonate intercalation in the hydroxyapatite lattice can be reliably employed to differentiate benign from malignant lesions, with algorithms based only on carbonate and cytoplasmic protein content exhibiting excellent negative predictive value (93-98%). Our findings highlight the importance of calcium carbonate, an underrated constituent of microcalcifications, as a spectroscopic marker in breast pathology evaluation and pave the way for improved biopsy guidance.

Aggravation of atopic dermatitis in breast-fed infants by tree nut-related foods and fermented foods in breast milk.

PubMed

Uenishi, Toshiaki; Sugiura, Hisashi; Tanaka, Toshihiro; Uehara, Masami

2011-02-01

Ninety-two exclusively breast-fed Japanese infants with atopic dermatitis were studied to see whether tree nut-related foods (chocolate and coffee) and fermented foods (cheese, yogurt, bread, soy sauce, miso soup and fermented soy beans) eaten by their mothers affected their skin condition. Of the 92 infants, 67 (73%) showed improvement of skin lesions when their mothers avoided these foods and showed aggravation of skin lesions when these foods were reintroduced. The predominant offending foods were chocolate, yogurt, soy sauce and miso soup. A long-term maternal exclusion of the trigger foods brought about progressive improvement of skin lesions in the majority of the infants. These findings suggest that tree nut-related foods and fermented foods are important offending foods of atopic dermatitis in breast-fed infants. © 2010 Japanese Dermatological Association.

The diagnostic value of diffusion-weighted imaging and the apparent diffusion coefficient values in the differentiation of benign and malignant breast lesions.

PubMed

Çabuk, Gonca; Nass Duce, Meltem; Özgür, Anıl; Apaydın, Feramuz Demir; Polat, Ayşe; Orekici, Gülhan

2015-04-01

The goal of our study was to evaluate the diagnostic efficacy of diffusion-weighted imaging (DWI) in the differentiation of benign and malignant breast lesions. Between June 2012 and March 2013, 60 patients with 63 lesions (age range 29-70 years, mean age 48.6 years) were included in our study. All lesions, except complicated cysts and intra-mammary lymph nodes, were confirmed histopathologically. The patients were evaluated with a 1.5 Tesla MR scanner using dedicated bilateral breast coil. DWI images were obtained by echo planar imaging sequence and 'b' values were selected as 200, 600 and 1000 s/mm(2). Apparent diffusion coefficient (ADC) values of both breast lesions and the normal fibroglandular tissue of the contralateral breast were calculated and statistically compared using Shapiro-Wilk test, Student's t-test, Mann-Whitney U test, chi-square test and the receiver operating curve. Of 63 lesions, 22 were malignant and 41 were benign. In malignant lesions, the mean ADC values were 1.40 ± 0.41 × 10(-3) mm(2)/s for b = 200, 1.05 ± 0.28 × 10(-3) mm(2)/s for b = 600 and 0.91 ± 0.20 × 10(-3) mm(2)/s for b = 1000 and in benign lesions, the mean ADC values were 2.13 ± 0.85 × 10(-3) mm(2)/s for b = 200, 1.64 ± 0.47 × 10(-3) mm(2)/s for b = 600 and 1.40 ± 0.43 × 10(-3) mm(2)/s for b = 1000. The success of ADC values in differentiation of benign and malignant lesions was statistically significant (P = 0.0001). The threshold values were determined to be 1.50 × 10(-3) mm(2)/s for b = 200, 1.22 × 10(-3) mm(2)/s for b = 600 and 0.98 × 10(-3) mm(2)/s for b = 1000 (P < 0.05). DWI can be an effective radiological method in the differentiation of benign and malignant breast lesions. © 2015 The Royal Australian and New Zealand College of Radiologists.

Breast mass as the initial presentation of esophageal carcinoma: a case report

PubMed Central

Norooz, Mohammad Tayefeh; Ahmadi, Hamed; Zavarei, Mansour Jamali; Daryaei, Parviz

2009-01-01

Introduction Esophageal cancer is considered as a fatal malignancy. It mostly metastasizes to lung, liver, and bone while breast metastasis has been rarely reported. This is the fifth report of metastatic breast cancer from esophageal cancer, which differs from previous reported cases in terms of initial presentation with metastatic breast mass and no metastatic involvement of other organs. Case presentation We present a 35-year-old Caucasian woman who initially complained of a painful breast mass. Squamous pearls on cytologic evaluation suggested a metastatic lesion. Two months history of dysphagia was extracted through detailed interview with patient and further investigation revealed a stage IV esophageal squamous cell carcinoma. Conclusion In this case, breast lesion as an unusual presentation of esophageal carcinoma emphasizes the great role of thorough medical history taking and cytologic study in evaluating an accidentally detected breast mass. The increasing reports of breast metastasis in patients with esophageal carcinoma necessitate the careful breast examination in visits after treatment of the primary tumor. PMID:19829901

Effectiveness of computer-aided diagnosis (CADx) of breast pathology using immunohistochemistry results of core needle biopsy samples for synaptophysin, oestrogen receptor and CK14/p63 for classification of epithelial proliferative lesions of the breast.

PubMed

Maeda, Ichiro; Kubota, Manabu; Ohta, Jiro; Shinno, Kimika; Tajima, Shinya; Ariizumi, Yasushi; Doi, Masatomo; Oana, Yoshiyasu; Kanemaki, Yoshihide; Tsugawa, Koichiro; Ueno, Takahiko; Takagi, Masayuki

2017-12-01

The aim of this study was to develop a computer-aided diagnosis (CADx) system for identifying breast pathology. Two sets of 100 consecutive core needle biopsy (CNB) specimens were collected for test and validation studies. All 200 CNB specimens were stained with antibodies targeting oestrogen receptor (ER), synaptophysin and CK14/p63. All stained slides were scanned in a whole-slide imaging system and photographed. The photographs were analysed using software to identify the proportions of tumour cells that were positive and negative for each marker. In the test study, the cut-off values for synaptophysin (negative and positive) and CK14/p63 (negative and positive) were decided using receiver operating characteristic (ROC) analysis. For ER analysis, samples were divided into groups with <10% positive or >10% positive cells and decided using receiver operating characteristic (ROC) analysis. Finally, these two groups categorised as ER-low, ER-intermediate (non-low and non-high) and ER-high groups. In the validation study, the second set of immunohistochemical slides were analysed using these cut-off values. The cut-off values for synaptophysin, <10% ER positive, >10% ER positive and CK14/p63 were 0.14%, 2.17%, 77.93% and 18.66%, respectively. The positive predictive value for malignancy (PPV) was 100% for synaptophysin-positive/ER-high/(CK14/p63)-any or synaptophysin-positive/ER-low/(CK14/p63)-any. The PPV was 25% for synaptophysin-positive/ER-intermediate/(CK14/p63)-positive. For synaptophysin-negative/(CK14/p63)-negative, the PPVs for ER-low, ER-intermediate and ER-high were 100%, 80.0% and 95.8%, respectively. The PPV was 4.5% for synaptophysin-negative/ER-intermediate/(CK14/p63)-positive. The CADx system was able to analyse sufficient data for all types of epithelial proliferative lesions of the breast including invasive breast cancer. This system may be useful for pathological diagnosis of breast CNB in routine investigations. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Polyvinyl chloride plastisol breast phantoms for ultrasound imaging.

PubMed

de Carvalho, Isabela Miller; De Matheo, Lucas Lobianco; Costa Júnior, José Francisco Silva; Borba, Cecília de Melo; von Krüger, Marco Antonio; Infantosi, Antonio Fernando Catelli; Pereira, Wagner Coelho de Albuquerque

2016-08-01

Ultrasonic phantoms are objects that mimic some features of biological tissues, allowing the study of their interactions with ultrasound (US). In the diagnostic-imaging field, breast phantoms are an important tool for testing performance and optimizing US systems, as well as for training medical professionals. This paper describes the design and manufacture of breast lesions by using polyvinyl chloride plastisol (PVCP) as the base material. Among the materials available for this study, PVCP was shown to be stable, durable, and easy to handle. Furthermore, it is a nontoxic, nonpolluting, and low-cost material. The breast's glandular tissue (image background) was simulated by adding graphite powder with a concentration of 1% to the base material. Mixing PVCP and graphite powder in differing concentrations allows one to simulate lesions with different echogenicity patterns (anechoic, hypoechoic, and hyperechoic). From this mixture, phantom materials were obtained with speed of sound varying from 1379.3 to 1397.9ms(-1) and an attenuation coefficient having values between 0.29 and 0.94dBcm(-1) for a frequency of 1MHz at 24°C. A single layer of carnauba wax was added to the lesion surface in order to evaluate its applicability for imaging. The images of the phantoms were acquired using commercial ultrasound equipment; a specialist rated the images, elaborating diagnoses representative of both benign and malignant lesions. The results indicated that it was possible to easily create a phantom by using low-cost materials, readily available in the market and stable at room temperature, as the basis of ultrasonic phantoms that reproduce the image characteristics of fatty breast tissue and typical lesions of the breast. Copyright © 2016 Elsevier B.V. All rights reserved.

Detectability of BI-RADS category 3 or higher breast lesions and reading time on mammography: comparison between 5-MP and 8-MP LCD monitors.

PubMed

Yabuuchi, Hidetake; Kawanami, Satoshi; Kamitani, Takeshi; Matsumura, Tomomi; Yamasaki, Yuzo; Morishita, Junji; Honda, Hiroshi

2017-04-01

Background Five-megapixel (MP) displays are recommended as soft copy devices for digital mammogram. An 8-MP liquid crystal display (LCD) (two 4-MP displays within one display) might offer the advantage of being able to view biplane mammography more easily than the dual planes of 5-MP LCDs. Purpose To compare detectability of Breast Imaging Reporting and Data System (BI-RADS) category 3 or higher lesions and reading time on mammography between 5- MP and 8-MP LCDs. Material and Methods The mammograms of 240 breasts of 120 patients including 60 breasts with BI-RADS category 3 or higher lesions and 180 breasts with normal or category 2 lesions were enrolled. All bilateral mammograms were displayed on bifacial 5-MP LCDs or an 8-MP LCD (two 4-MP displays within one display). Six radiologists assessed 240 breasts on each display. The observations were analyzed using receiver operating characteristic (ROC) analysis. A jack-knife method was used for statistical analysis. We employed a paired t-test to determine whether any significant differences existed in the reading time between two different displays. A P value < 0.05 was considered significant. Results The mean areas under the ROC curve obtained using 5-MP and 8-MP LCDs were 0.925 and 0.915, respectively, and there was no significant difference ( P = 0.46). There was also no significant difference in the reading time between two types of displays (57.8 min. vs. 51.5 min, P = 0.39). Conclusion The detectability of BI-RADS category 3 or higher lesions and reading time using an 8-MP LCD were comparable to those using a 5-MP LCD.

Towards an in-plane methodology to track breast lesions using mammograms and patient-specific finite-element simulations

NASA Astrophysics Data System (ADS)

Lapuebla-Ferri, Andrés; Cegoñino-Banzo, José; Jiménez-Mocholí, Antonio-José; Pérez del Palomar, Amaya

2017-11-01

In breast cancer screening or diagnosis, it is usual to combine different images in order to locate a lesion as accurately as possible. These images are generated using a single or several imaging techniques. As x-ray-based mammography is widely used, a breast lesion is located in the same plane of the image (mammogram), but tracking it across mammograms corresponding to different views is a challenging task for medical physicians. Accordingly, simulation tools and methodologies that use patient-specific numerical models can facilitate the task of fusing information from different images. Additionally, these tools need to be as straightforward as possible to facilitate their translation to the clinical area. This paper presents a patient-specific, finite-element-based and semi-automated simulation methodology to track breast lesions across mammograms. A realistic three-dimensional computer model of a patient’s breast was generated from magnetic resonance imaging to simulate mammographic compressions in cranio-caudal (CC, head-to-toe) and medio-lateral oblique (MLO, shoulder-to-opposite hip) directions. For each compression being simulated, a virtual mammogram was obtained and posteriorly superimposed to the corresponding real mammogram, by sharing the nipple as a common feature. Two-dimensional rigid-body transformations were applied, and the error distance measured between the centroids of the tumors previously located on each image was 3.84 mm and 2.41 mm for CC and MLO compression, respectively. Considering that the scope of this work is to conceive a methodology translatable to clinical practice, the results indicate that it could be helpful in supporting the tracking of breast lesions.

The role of cone-beam breast-CT for breast cancer detection relative to breast density.

PubMed

Wienbeck, Susanne; Uhlig, Johannes; Luftner-Nagel, Susanne; Zapf, Antonia; Surov, Alexey; von Fintel, Eva; Stahnke, Vera; Lotz, Joachim; Fischer, Uwe

2017-12-01

To evaluate the impact of breast density on the diagnostic accuracy of non-contrast cone-beam breast computed tomography (CBBCT) in comparison to mammography for the detection of breast masses. A retrospective study was conducted from August 2015 to July 2016. Fifty-nine patients (65 breasts, 112 lesions) with BI-RADS, 5th edition 4 or 5 assessment in mammography and/or ultrasound of the breast received an additional non-contrast CBBCT. Independent double blind reading by two radiologists was performed for mammography and CBBCT imaging. Sensitivity, specificity and AUC were compared between the modalities. Breast lesions were histologically examined in 85 of 112 lesions (76%). The overall sensitivity for CBBCT (reader 1: 91%, reader 2: 88%) was higher than in mammography (both: 68%, p<0.001), and also for the high-density group (p<0.05). The specificity and AUC was higher for mammography in comparison to CBBCT (p<0.05 and p<0.001). The interobserver agreement (ICC) between the readers was 90% (95% CI: 86-93%) for mammography and 87% (95% CI: 82-91%) for CBBCT. Compared with two-view mammography, non-contrast CBBCT has higher sensitivity, lower specificity, and lower AUC for breast mass detection in both high and low density breasts. • Overall sensitivity for non-contrast CBBCT ranged between 88%-91%. • Sensitivity was higher for CBBCT than mammography in both density types (p<0.001). • Specificity was higher for mammography than CBBCT in both density types (p<0.05). • AUC was larger for mammography than CBBCT in both density types (p<0.001).

Metastatic trichilemmal carcinoma in a patient with breast cancer.

PubMed

Sofianos, Chrysis; Chauke, Nkhensani Y; Grubnik, Alexandra

2016-11-21

Trichilemmal carcinoma (TC) is described as a very rare cancer of the skin adnexa. 1 2 Ninety per cent of the lesions present on the scalp. Prognostic factors in TC are limited to lymph node status and surgical margins, with no statistical significance observed for age or gender of the patient, size of tumour or locoregional recurrence. We present a 46-year-old black patient who developed TC during treatment for breast cancer. Postoperative histology of the scalp lesion excision confirmed no involved margins. At the three monthly appointment, the patient was reviewed and multiple, new scalp lesions were noted. A CT scan of the head, neck found multiple lesions on the scalp, limited to the soft tissue, not involving the outer table of the skull. There was bilateral invasion of the parotid glands. To the best of our knowledge, no syndromes or associations between breast cancer and adnexal skin tumours exist. 2016 BMJ Publishing Group Ltd.

Digital breast tomosynthesis for detecting multifocal and multicentric breast cancer: influence of acquisition geometry on model observer performance in breast phantom images

NASA Astrophysics Data System (ADS)

Wen, Gezheng; Park, Subok; Markey, Mia K.

2017-03-01

Multifocal and multicentric breast cancer (MFMC), i.e., the presence of two or more tumor foci within the same breast, has an immense clinical impact on treatment planning and survival outcomes. Detecting multiple breast tumors is challenging as MFMC breast cancer is relatively uncommon, and human observers do not know the number or locations of tumors a priori. Digital breast tomosynthesis (DBT), in which an x-ray beam sweeps over a limited angular range across the breast, has the potential to improve the detection of multiple tumors.1, 2 However, prior efforts to optimize DBT image quality only considered unifocal breast cancers (e.g.,3-9), so the recommended geometries may not necessarily yield images that are informative for the task of detecting MFMC. Hence, the goal of this study is to employ a 3D multi-lesion (ml) channelized-Hotelling observer (CHO) to identify optimal DBT acquisition geometries for MFMC. Digital breast phantoms and simulated DBT scanners of different geometries (e.g., wide or narrow arc scans, different number of projections in each scan) were used to generate image data for the simulation study. Multiple 3D synthetic lesions were inserted into different breast regions to simulate MF cases and MC cases. 3D partial least squares (PLS) channels, and 3D Laguerre-Gauss (LG) channels were estimated to capture discriminant information and correlations among signals in locally varying anatomical backgrounds, enabling the model observer to make both image-level and location-specific detection decisions. The 3D ml-CHO with PLS channels outperformed that with LG channels in this study. The simulated MC cases and MC cases were not equally difficult for the ml-CHO to detect across the different simulated DBT geometries considered in this analysis. Also, the results suggest that the optimal design of DBT may vary as the task of clinical interest changes, e.g., a geometry that is better for finding at least one lesion may be worse for counting the number of lesions.

Comparison between fine needle aspiration cytology (FNAC) and core needle biopsy (CNB) in the diagnosis of breast lesions.

PubMed

Moschetta, M; Telegrafo, M; Carluccio, D A; Jablonska, J P; Rella, L; Serio, Gabriella; Carrozzo, M; Stabile Ianora, A A; Angelelli, G

2014-01-01

To compare the diagnostic accuracy of fine-needle aspiration cytology (FNAC) and core needle biopsy (CNB) in patients with USdetected breast lesions. Between September 2011 and May 2013, 3469 consecutive breast US examinations were performed. 400 breast nodules were detected in 398 patients. 210 FNACs and 190 CNBs were performed. 183 out of 400 (46%) lesions were surgically removed within 30 days form diagnosis; in the remaining cases, a six month follow up US examination was performed. Sensitivity, specificity, diagnostic accuracy, positive predictive (PPV) and negative predictive (NPV) values were calculated for FNAC and CNB. 174 out of 400 (43%) malignant lesions were found while the remaining 226 resulted to be benign lesions. 166 out of 210 (79%) FNACs and 154 out of 190 (81%) CNBs provided diagnostic specimens. Sensitivity, specificity, diagnostic accuracy, PPV and NPV of 97%, 94%, 95%, 91% and 98% were found for FNAC, and values of 92%, 82%, 89%, 92% and 82% were obtained for CNB. Sensitivity, specificity, diagnostic accuracy, PPV and NPV of 97%, 96%, 96%, 97% and 96% were found for FNAC, and values of 97%, 96%, 96%, 97% and 96% were obtained for CNB. FNAC and CNB provide similar values of diagnostic accuracy.

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps.

PubMed

Sadeghi-Naini, Ali; Suraweera, Harini; Tran, William Tyler; Hadizad, Farnoosh; Bruni, Giancarlo; Rastegar, Rashin Fallah; Curpen, Belinda; Czarnota, Gregory J

2017-10-20

This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic.

Rethinking Skin Lesion Segmentation in a Convolutional Classifier.

PubMed

Burdick, Jack; Marques, Oge; Weinthal, Janet; Furht, Borko

2017-10-18

Melanoma is a fatal form of skin cancer when left undiagnosed. Computer-aided diagnosis systems powered by convolutional neural networks (CNNs) can improve diagnostic accuracy and save lives. CNNs have been successfully used in both skin lesion segmentation and classification. For reasons heretofore unclear, previous works have found image segmentation to be, conflictingly, both detrimental and beneficial to skin lesion classification. We investigate the effect of expanding the segmentation border to include pixels surrounding the target lesion. Ostensibly, segmenting a target skin lesion will remove inessential information, non-lesion skin, and artifacts to aid in classification. Our results indicate that segmentation border enlargement produces, to a certain degree, better results across all metrics of interest when using a convolutional based classifier built using the transfer learning paradigm. Consequently, preprocessing methods which produce borders larger than the actual lesion can potentially improve classifier performance, more than both perfect segmentation, using dermatologist created ground truth masks, and no segmentation altogether.

Demonstration of an algorithm to overcome health system-related barriers to timely diagnosis of breast diseases in rural Zambia

PubMed Central

Nzayisenga, Jean-Baptiste; Shibemba, Aaron; Kusweje, Victor; Chiboola, Hector; Amuyunzu-Nyamongo, Mary; Kapambwe, Sharon; Mwaba, Catherine; Lermontov, Pavlo; Mumba, Chibamba; Henry-Tillman, Ronda; Parham, Groesbeck P.

2018-01-01

Background Long delays to diagnosis is a major cause of late presentation of breast diseases in sub-Saharan Africa. Aims We designed and implemented a single-visit breast care algorithm that overcomes health system-related barriers to timely diagnosis of breast diseases. Methods A multidisciplinary team of Zambian healthcare experts trained a team of mid- and high-level Zambian healthcare practitioners how to evaluate women for breast diseases, and train trainers to do likewise. Working collaboratively, the two teams then designed a clinical platform that provides multiple breast care services within a single visit. The service platform was implemented using a breast outreach camp format, during which breast self-awareness, psychosocial counseling, clinical breast examination, breast ultrasound, ultrasound-guided biopsy, imprint cytology of biopsy specimens and surgical treatment or referral, were offered within a single visit. Results Eleven hundred and twenty-nine (1129) women attended the camps for breast care. Mean age was 35.9 years. The majority were multiparous (79.4%), breast-fed (76.0%), and reported hormone use (50.4%). Abnormalities were detected on clinical breast examination in 122 (10.8%) women, 114 of whom required ultrasound. Of the 114 who underwent ultrasound, 48 had identifiable lesions and were evaluated with ultrasound-guided core needle biopsy (39) or fine-needle aspiration (9). The concordance between imprint cytology and histopathology was 100%, when breast specimens were classified as either benign or malignant. However, when specimens were classified by histopathologic subtype, the concordance between imprint cytology and histology was 85.7% for benign and 100% for malignant lesions. Six (6) women were diagnosed with invasive cancer. Eighteen (18) women with symptomatic breast lesions had next-day surgery. Significance Similar to its impact on cervical cancer prevention services, a single visit breast care algorithm has the potential to overcome health system-related barriers to timely diagnosis of breast diseases, including cancer, in rural African settings. PMID:29746541

Abdominal Sarcoidosis Mimicking Peritoneal Carcinomatosis.

PubMed

Roh, Won Seok; Lee, Seungho; Park, Ji Hyun; Kang, Jeonghyun

2018-04-01

We present a patient diagnosed with skin sarcoidosis, breast cancer, pulmonary tuberculosis, and peritoneal sarcoidosis with a past history of colorectal cancer. During stage work up for breast cancer, suspicious lesions on peritoneum were observed in imaging studies. Considering our patient's history and imaging findings, we initially suspected peritoneal carcinomatosis. However, the peritoneal lesion was diagnosed as sarcoidosis in laparoscopic biopsy. This case demonstrates that abdominal sarcoidosis might be considered as a differential diagnosis when there is a lesion suspected of being peritoneal carcinomatosis with nontypical clinical presentations.

Breast Metastatic Localization of Signet-Ring Cell Gastric Carcinoma

PubMed Central

Parrell Soler, C.; Palacios Marqués, A.; Saco López, L.; Bermejo De las Heras, R.; Pertusa Martínez, S.

2011-01-01

Metastatic tumors in the breast are quite rare and constitute 0,5 to 6% of all breast malignancies. They often occur in a polymetastatic context. Gastrointestinal lesions rarely metastasize to the breast. The first case of a metastasis deposit to the breast and ovary from gastric signet-ring cell carcinoma was reported in the literature in 1999. Since this report, only 5 cases have been reported. We present a case report of a 37-year-old woman who complained of a lump in the left breast. Two months earlier, the woman underwent a subtotal gastrectomy and a total hysterectomy with double anexectomy, which histologically was diagnosed of gastric signet-ring carcinoma, disseminated with Krukenberg's tumor. In those days, the patient was following a chemotherapy treatment. A core needle biopsy of the lesion in left breast revealed cells with signet-ring features, with probably gastric origin. PMID:21637360

Comparison of Tc-99m maraciclatide and Tc-99m sestamibi molecular breast imaging in patients with suspected breast cancer.

PubMed

O'Connor, Michael K; Morrow, Melissa M B; Hunt, Katie N; Boughey, Judy C; Wahner-Roedler, Dietlind L; Conners, Amy Lynn; Rhodes, Deborah J; Hruska, Carrie B

2017-12-01

Molecular breast imaging (MBI) performed with 99m Tc sestamibi has been shown to be a valuable technique for the detection of breast cancer. Alternative radiotracers such as 99m Tc maraciclatide may offer improved uptake in breast lesions. The purpose of this study was to compare relative performance of 99m Tc sestamibi and 99m Tc maraciclatide in patients with suspected breast cancer, using a high-resolution dedicated gamma camera for MBI. Women with breast lesions suspicious for malignancy were recruited to undergo two MBI examinations-one with 99m Tc sestamibi and one with 99m Tc maraciclatide. A radiologist interpreted MBI studies in a randomized, blinded fashion to assign an assessment score (1-5) and measured lesion size. Lesion-to-background (L/B) ratio was measured with region-of-interest analysis. Among 39 analyzable patients, 21 malignant tumors were identified in 21 patients. Eighteen of 21 tumors (86%) were seen on 99m Tc sestamibi MBI and 19 of 21 (90%) were seen on 99m Tc maraciclatide MBI (p = 1). Tumor extent measured with both radiopharmaceuticals correlated strongly with pathologic size ( 99m Tc sestamibi, r = 0.84; 99m Tc maraciclatide, r = 0.81). The L/B ratio in detected breast cancers was similar for the two radiopharmaceuticals: 1.55 ± 0.36 (mean ± S.D.) for 99m Tc sestamibi and 1.62 ± 0.37 (mean ± S.D.) for 99m Tc maraciclatide (p = 0.53). No correlation was found between the L/B ratio and molecular subtype for 99m Tc sestamibi (r s  = 0.12, p = 0.63) or 99m Tc maraciclatide (r s  = -0.12, p = 0.64). Of 20 benign lesions, 10 (50%) were seen on 99m Tc sestamibi and 9 of 20 (45%) were seen on 99m Tc maraciclatide images (p = 0.1). The average L/B ratio for benign lesions was 1.34 ±0.40 (mean ±S.D.) for 99m Tc sestamibi and 1.41 ±0.52 (mean ±S.D.) for 99m Tc maraciclatide (p = 0.75). Overall diagnostic performance was similar for both radiopharmaceuticals. AUC from ROC analysis was 0.83 for 99m Tc sestamibi and 0.87 for 99m Tc maraciclatide (p = 0.64). 99m Tc maraciclatide offered comparable lesion uptake to 99m Tc sestamibi, in both malignant and benign lesions. There was good correlation between lesion extent and uptake measured from both radiopharmaceuticals. 99m Tc maraciclatide offered a marginal (but not significant) improvement in sensitivity over 99m Tc sestamibi. Our findings did not support an association between the uptake of either radiopharmaceutical and tumor molecular subtype. ClinicalTrials.gov, NCT00888589.

TU-CD-207-02: Quantification of Breast Lesion Compositions Using Low-Dose Spectral Mammography: A Feasibility Study

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

Cho, H; Ding, H; Sennung, D

2015-06-15

Purpose: To investigate the feasibility of measuring breast lesion composition with spectral mammography using physical phantoms and bovine tissue. Methods: Phantom images were acquired with a spectral mammography system with a silicon-strip based photon-counting detector. Plastic water and adipose-equivalent phantoms were used to calibrate the system for dual-energy material decomposition. The calibration phantom was constructed in range of 2–8 cm thickness and water densities in the range of 0% to 100%. A non-linear rational fitting function was used to calibrate the imaging system. The phantom studies were performed with uniform background phantom and non-uniform background phantom. The breast lesion phantomsmore » (2 cm in diameter and 0.5 cm in thickness) were made with water densities ranging from 0 to 100%. The lesion phantoms were placed in different positions and depths on the phantoms to investigate the accuracy of the measurement under various conditions. The plastic water content of the lesion was measured by subtracting the total decomposed plastic water signal from a surrounding 2.5 mm thick border outside the lesion. In addition, bovine tissue samples composed of 80 % lean were imaged as background for the simulated lesion phantoms. Results: The thickness of measured and known water contents was compared. The rootmean-square (RMS) errors in water thickness measurements were 0.01 cm for the uniform background phantom, 0.04 cm for non-uniform background phantom, and 0.03 cm for 80% lean bovine tissue background. Conclusion: The results indicate that the proposed technique using spectral mammography can be used to accurately characterize breast lesion compositions.« less

Positron emission mammography in breast cancer presurgical planning: comparisons with magnetic resonance imaging

PubMed Central

Narayanan, Deepa; Kalinyak, Judith E.; The, Juliette; Velasquez, Maria Victoria; Kahn, Simone; Saady, Matthew; Mahal, Ravinder; Chrystal, Larraine

2010-01-01

Purpose The objective of this study was to compare the performance characteristics of 18F-fluorodeoxyglucose (FDG) positron emission mammography (PEM) with breast magnetic resonance imaging (MRI) as a presurgical imaging and planning option for index and ipsilateral lesions in patients with newly diagnosed, biopsy-proven breast cancer. Methods Two hundred and eight women >25 years of age (median age = 59.7 ± 14.1 years) with biopsy-proven primary breast cancer enrolled in this prospective, single-site study. MRI, PEM, and whole-body positron emission tomography (WBPET) were conducted on each patient within 7 business days. PEM and WBPET images were acquired on the same day after intravenous administration of 370 MBq of FDG (median = 432.9 MBq). PEM and MRI images were blindly evaluated, compared with final surgical histopathology, and the sensitivity determined. Substudy analysis compared the sensitivity of PEM versus MRI in patients with different menopausal status, breast density, and use of hormone replacement therapy (HRT) as well as determination of performance characteristics for additional ipsilateral lesion detection. Results Two hundred and eight patients enrolled in the study of which 87% (182/208) were analyzable. Of these analyzable patients, 26.4% (48/182), 7.1% (13/182), and 64.2% (120/182) were pre-, peri-, and postmenopausal, respectively, and 48.4% (88/182) had extremely or heterogeneously dense breast tissue, while 33.5% (61/182) had a history of HRT use. Ninety-two percent (167/182) underwent core biopsy for index lesion diagnosis. Invasive cancer was found in 77.5% (141/182), while ductal carcinoma in situ (DCIS) and/or Paget’s disease were found in 22.5% (41/182) of patients. Both PEM and MRI had index lesion depiction sensitivity of 92.8% and both were significantly better than WBPET (67.9%, p < 0.001, McNemar’s test). For index lesions, PEM and MRI had equivalent sensitivity of various tumors, categorized by tumor stage as well as similar invasive tumor size predictions with Spearman's correlation coefficient of 0.61 for both PEM and MRI compared to surgical pathology. Menopausal status, breast density, and HRT did not influence the sensitivity of PEM or MRI. For 67 additional unsuspected ipsilateral lesions or multifocal lesions, PEM had sensitivity of 85% (34/40) and specificity of 74%, (20/27) compared to MRI's sensitivity of 98% (39/40) and specificity of 48% (13/27) [p = 0.074, for sensitivity; p = 0.096 for specificity] Conclusion PEM is a good alternative to MRI as a presurgical breast imaging option and its performance characteristics are not affected by patient menopausal/hormonal status or breast density. PMID:20871992

Positron emission mammography in breast cancer presurgical planning: comparisons with magnetic resonance imaging.

PubMed

Schilling, Kathy; Narayanan, Deepa; Kalinyak, Judith E; The, Juliette; Velasquez, Maria Victoria; Kahn, Simone; Saady, Matthew; Mahal, Ravinder; Chrystal, Larraine

2011-01-01

The objective of this study was to compare the performance characteristics of (18)F-fluorodeoxyglucose (FDG) positron emission mammography (PEM) with breast magnetic resonance imaging (MRI) as a presurgical imaging and planning option for index and ipsilateral lesions in patients with newly diagnosed, biopsy-proven breast cancer. Two hundred and eight women >25 years of age (median age = 59.7 ± 14.1 years) with biopsy-proven primary breast cancer enrolled in this prospective, single-site study. MRI, PEM, and whole-body positron emission tomography (WBPET) were conducted on each patient within 7 business days. PEM and WBPET images were acquired on the same day after intravenous administration of 370 MBq of FDG (median = 432.9 MBq). PEM and MRI images were blindly evaluated, compared with final surgical histopathology, and the sensitivity determined. Substudy analysis compared the sensitivity of PEM versus MRI in patients with different menopausal status, breast density, and use of hormone replacement therapy (HRT) as well as determination of performance characteristics for additional ipsilateral lesion detection. Two hundred and eight patients enrolled in the study of which 87% (182/208) were analyzable. Of these analyzable patients, 26.4% (48/182), 7.1% (13/182), and 64.2% (120/182) were pre-, peri-, and postmenopausal, respectively, and 48.4% (88/182) had extremely or heterogeneously dense breast tissue, while 33.5% (61/182) had a history of HRT use. Ninety-two percent (167/182) underwent core biopsy for index lesion diagnosis. Invasive cancer was found in 77.5% (141/182), while ductal carcinoma in situ (DCIS) and/or Paget's disease were found in 22.5% (41/182) of patients. Both PEM and MRI had index lesion depiction sensitivity of 92.8% and both were significantly better than WBPET (67.9%, p < 0.001, McNemar's test). For index lesions, PEM and MRI had equivalent sensitivity of various tumors, categorized by tumor stage as well as similar invasive tumor size predictions with Spearman's correlation coefficient of 0.61 for both PEM and MRI compared to surgical pathology. Menopausal status, breast density, and HRT did not influence the sensitivity of PEM or MRI. For 67 additional unsuspected ipsilateral lesions or multifocal lesions, PEM had sensitivity of 85% (34/40) and specificity of 74%, (20/27) compared to MRI's sensitivity of 98% (39/40) and specificity of 48% (13/27) [p = 0.074, for sensitivity; p = 0.096 for specificity] PEM is a good alternative to MRI as a presurgical breast imaging option and its performance characteristics are not affected by patient menopausal/hormonal status or breast density.

[Examination of Stereotactic Mammotome Biopsy for Microcalcification in Our Hospital].

PubMed

Sueoka, Noriko; Ishizuka, Mariko; Yoshikawa, Katsuhiro; Tsubota, Yu; Yamamoto, Daigo; Kon, Masanori

2017-11-01

We introduced stereotactic mammotome biopsy(ST-MMT)for the purpose of screening and other institutions. There are many benign cases to be diagnosed by pathological findings, so it is thought to be necessary to examine the adaptation of STMMT again. We examined the performance of ST-MMT in a case of a non-palpating calcification lesion. Between August 2013 and December 2016, ST-MMT biopsies were performed for 247 microcalcified lesions revealed by mammography(in both breasts in 9 patients; twice in the ipsilateral breast in 2 patients). The mean age of all patients was 46 years(range, 24- 89 years). We found 39 cases(15.8%)of breast cancer. A final diagnosis of breast cancer was made in 39 patients, who comprised 0% of those with Category 2, 53.8% of those with Category 3, 35.9% of those with Category 4, and 10.3% of those with Category 5. Regarding the morphology and distribution of microcalcifications, breast cancer accounted for 46.2%, 5.1%, 2.6%, 35.9%, 7.7%, and 2.6% of the cases with small round/clustered, amorphous/clustered, pleomorphic/clus- tered, pleomorphic/linear segmental, and fine linear/clustered patterns, respectively. Also, we examined each of the patients, (1) who underwent mammography for medical examinations, (2) who underwent mammography performed at other institutions, (3) who underwent follow-up for microcalcifications and postoperative follow-up mammography. The proportions of breast cancer diagnoses were (1) 11.4%, (2) 20.6%, and (3) 7.1%. Proportions of Category 3 breast cancer were (1) 10.3%, (2) 38.5%, and (3) 5.1%. Among the cases in which ST-MMT was performed in this study, Category 3 accounted for more than half. However, 10.9%(21/192 lesions)were diagnosed as malignant in Category 3. The diagnosis of breast cancer in pa- tients who underwent mammography performed at other institutions was not observed in 79.4%(104/131 lesions), and among the 104 lesions, as a result of reassessment of calcification in our hospital, Category 2 was also included. Calcification in Category 2 lesions was benign in all cases. It was suggested that the indication for ST-MMT biopsy could be further narrowed down by being careful not to over-diagnose.

Quantitative differentiation of breast lesions at 3T diffusion-weighted imaging (DWI) using the ratio of distributed diffusion coefficient (DDC).

PubMed

Ertas, Gokhan; Onaygil, Can; Akin, Yasin; Kaya, Handan; Aribal, Erkin

2016-12-01

To investigate the accuracy of diffusion coefficients and diffusion coefficient ratios of breast lesions and of glandular breast tissue from mono- and stretched-exponential models for quantitative diagnosis in diffusion-weighted magnetic resonance imaging (MRI). We analyzed pathologically confirmed 170 lesions (85 benign and 85 malignant) imaged using a 3.0T MR scanner. Small regions of interest (ROIs) focusing on the highest signal intensity for lesions and also for glandular tissue of contralateral breast were obtained. Apparent diffusion coefficient (ADC) and distributed diffusion coefficient (DDC) were estimated by performing nonlinear fittings using mono- and stretched-exponential models, respectively. Coefficient ratios were calculated by dividing the lesion coefficient by the glandular tissue coefficient. A stretched exponential model provides significantly better fits then the monoexponential model (P < 0.001): 65% of the better fits for glandular tissue and 71% of the better fits for lesion. High correlation was found in diffusion coefficients (0.99-0.81 and coefficient ratios (0.94) between the models. The highest diagnostic accuracy was found by the DDC ratio (area under the curve [AUC] = 0.93) when compared with lesion DDC, ADC ratio, and lesion ADC (AUC = 0.91, 0.90, 0.90) but with no statistically significant difference (P > 0.05). At optimal thresholds, the DDC ratio achieves 93% sensitivity, 80% specificity, and 87% overall diagnostic accuracy, while ADC ratio leads to 89% sensitivity, 78% specificity, and 83% overall diagnostic accuracy. The stretched exponential model fits better with signal intensity measurements from both lesion and glandular tissue ROIs. Although the DDC ratio estimated by using the model shows a higher diagnostic accuracy than the ADC ratio, lesion DDC, and ADC, it is not statistically significant. J. Magn. Reson. Imaging 2016;44:1633-1641. © 2016 International Society for Magnetic Resonance in Medicine.

Model observer for assessing digital breast tomosynthesis for multi-lesion detection in the presence of anatomical noise

NASA Astrophysics Data System (ADS)

Wen, Gezheng; Markey, Mia K.; Miner Haygood, Tamara; Park, Subok

2018-02-01

Model observers are widely used in task-based assessments of medical image quality. The presence of multiple abnormalities in a single set of images, such as in multifocal multicentric breast cancer (MFMC), has an immense clinical impact on treatment planning and survival outcomes. Detecting multiple breast tumors is challenging as MFMC is relatively uncommon, and human observers do not know the number or locations of tumors a priori. Digital breast tomosynthesis (DBT), in which an x-ray beam sweeps over a limited angular range across the breast, has the potential to improve the detection of multiple tumors. However, prior studies of DBT image quality all focus on unifocal breast cancers. In this study, we extended our 2D multi-lesion (ML) channelized Hotelling observer (CHO) into a 3D ML-CHO that detects multiple lesions from volumetric imaging data. Then we employed the 3D ML-CHO to identify optimal DBT acquisition geometries for detection of MFMC. Digital breast phantoms with multiple embedded synthetic lesions were scanned by simulated DBT scanners of different geometries (wide/narrow angular span, different number of projections per scan) to simulate MFMC cases. With new implementations of 3D partial least squares (PLS) and modified Laguerre-Gauss (LG) channels, the 3D ML-CHO made detection decisions based upon the overall information from individual DBT slices and their correlations. Our evaluation results show that: (1) the 3D ML-CHO could achieve good detection performance with a small number of channels, and 3D PLS channels on average outperform the counterpart LG channels; (2) incorporating locally varying anatomical backgrounds and their correlations as in the 3D ML-CHO is essential for multi-lesion detection; (3) the most effective DBT geometry for detection of MFMC may vary when the task of clinical interest changes, and a given DBT geometry may not yield images that are equally informative for detecting MF, MC, and unifocal cancers.

Accuracy of lesion boundary tracking in navigated breast tumor excision

NASA Astrophysics Data System (ADS)

Heffernan, Emily; Ungi, Tamas; Vaughan, Thomas; Pezeshki, Padina; Lasso, Andras; Gauvin, Gabrielle; Rudan, John; Engel, C. Jay; Morin, Evelyn; Fichtinger, Gabor

2016-03-01

PURPOSE: An electromagnetic navigation system for tumor excision in breast conserving surgery has recently been developed. Preoperatively, a hooked needle is positioned in the tumor and the tumor boundaries are defined in the needle coordinate system. The needle is tracked electromagnetically throughout the procedure to localize the tumor. However, the needle may move and the tissue may deform, leading to errors in maintaining a correct excision boundary. It is imperative to quantify these errors so the surgeon can choose an appropriate resection margin. METHODS: A commercial breast biopsy phantom with several inclusions was used. Location and shape of a lesion before and after mechanical deformation were determined using 3D ultrasound volumes. Tumor location and shape were estimated from initial contours and tracking data. The difference in estimated and actual location and shape of the lesion after deformation was quantified using the Hausdorff distance. Data collection and analysis were done using our 3D Slicer software application and PLUS toolkit. RESULTS: The deformation of the breast resulted in 3.72 mm (STD 0.67 mm) average boundary displacement for an isoelastic lesion and 3.88 mm (STD 0.43 mm) for a hyperelastic lesion. The difference between the actual and estimated tracked tumor boundary was 0.88 mm (STD 0.20 mm) for the isoelastic and 1.78 mm (STD 0.18 mm) for the hyperelastic lesion. CONCLUSION: The average lesion boundary tracking error was below 2mm, which is clinically acceptable. We suspect that stiffness of the phantom tissue affected the error measurements. Results will be validated in patient studies.

Modern classification and outcome predictors of surgery in patients with brain arteriovenous malformations.

PubMed

Tayebi Meybodi, Ali; Lawton, Michael T

2018-02-23

Brain arteriovenous malformations (bAVM) are challenging lesions. Part of this challenge stems from the infinite diversity of these lesions regarding shape, location, anatomy, and physiology. This diversity has called on a variety of treatment modalities for these lesions, of which microsurgical resection prevails as the mainstay of treatment. As such, outcome prediction and managing strategy mainly rely on unraveling the nature of these complex tangles and ways each lesion responds to various therapeutic modalities. This strategy needs the ability to decipher each lesion through accurate and efficient categorization. Therefore, classification schemes are essential parts of treatment planning and outcome prediction. This article summarizes different surgical classification schemes and outcome predictors proposed for bAVMs.

Preclinical study of diagnostic performances of contrast-enhanced spectral mammography versus MRI for breast diseases in China.

PubMed

Wang, Qingguo; Li, Kangan; Wang, Lihui; Zhang, Jianbing; Zhou, Zhiguo; Feng, Yan

2016-01-01

To evaluate diagnostic performances of CESM for breast diseases with comparison to breast MRI in China. Sixty-eight patients with 77 breast lesions underwent MR and CESM. Two radiologists interpreted either MRI or CESM images, separately and independently. BI-RADS 1-3 and BI-RADS 4-5 were classified into the suspicious benign and suspicious malignant groups. Diagnostic accuracy parameters were calculated. Receiver operating characteristic (ROC) curves were constructed for the two modalities. The agreement and correlation between maximum lesion diameter based on CESM and MRI, or CESM and pathology were analyzed. Diagnostic accuracy parameters for CESM were sensitivity 95.8 %, specificity 65.5 %, PPV 82.1 %, NPV 90.5 % and accuracy 84.4 %. The diagnostic accuracy parameters for breast MRI were sensitivity 93.8 %, specificity 82.8 %, PPV 88.2 %, NPV 92.3 %and accuracy 89.6 %. Area under the curve (AUC) of ROC was 0.96 for breast MRI and 0.88 for CESM. The Bland-Altman plots showed a mean difference of 0.7 mm with 95 % limits of agreement of 11.4 mm in tumor diameter measured using CESM and breast MRI. The differences of size measurement between CESM and breast MRI were significant, whereas no difference was observed between CESM and pathology as well as between breast MRI and pathology. The better correlation with pathological results was found in CESM than breast MRI. Our study demonstrates that CESM possesses better diagnostic performances than breast MRI in terms of diagnostic sensitivity and lesion size assessment. And CESM is a good alternative method of screening breast cancer in high-risk people.

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.

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

Weinmann, Amanda L.; Hruska, Carrie B.; Conners, Amy L.

Purpose: Molecular breast imaging (MBI) is a dedicated nuclear medicine breast imaging modality that employs dual-head cadmium zinc telluride (CZT) gamma cameras to functionally detect breast cancer. MBI has been shown to detect breast cancers otherwise occult on mammography and ultrasound. Currently, a MBI-guided biopsy system does not exist to biopsy such lesions. Our objective was to consider the utility of a novel conical slant-hole (CSH) collimator for rapid (<1 min) and accurate monitoring of lesion position to serve as part of a MBI-guided biopsy system. Methods: An initial CSH collimator design was derived from the dimensions of a parallel-holemore » collimator optimized for MBI performed with dual-head CZT gamma cameras. The parameters of the CSH collimator included the collimator height, cone slant angle, thickness of septa and cones of the collimator, and the annular areas exposed at the base of the cones. These parameters were varied within the geometric constraints of the MBI system to create several potential CSH collimator designs. The CSH collimator designs were evaluated using Monte Carlo simulations. The model included a breast compressed to a thickness of 6 cm with a 1-cm diameter lesion located 3 cm from the collimator face. The number of particles simulated was chosen to represent the count density of a low-dose, screening MBI study acquired with the parallel-hole collimator for 10 min after a {approx}150 MBq (4 mCi) injection of Tc-99m sestamibi. The same number of particles was used for the CSH collimator simulations. In the resulting simulated images, the count sensitivity, spatial resolution, and accuracy of the lesion depth determined from the lesion profile width were evaluated. Results: The CSH collimator design with default parameters derived from the optimal parallel-hole collimator provided 1-min images with error in the lesion depth estimation of 1.1 {+-} 0.7 mm and over 21 times the lesion count sensitivity relative to 1-min images acquired with the current parallel-hole collimator. Sensitivity was increased via more vertical cone slant angles, larger annular areas, thinner cone walls, shorter cone heights, and thinner radiating septa. Full width at half maximum trended in the opposite direction as sensitivity for all parameters. There was less error in the depth estimates for less vertical slant angles, smaller annular areas, thinner cone walls, cone heights near 1 cm, and generally thinner radiating septa. Conclusions: A Monte Carlo model was used to demonstrate the feasibility of a CSH collimator design for rapid biopsy application in molecular breast imaging. Specifically, lesion depth of a 1-cm diameter lesion positioned in the center of a typical breast can be estimated with error of less than 2 mm using circumferential count profiles of images acquired in 1 min.« less

Comparison of the time taken for localised breast surgery pre- and post-introduction of intra-operative digital specimen mammography.

PubMed

Carraro do Nascimento, Vinicius; Bourke, Anita G

2018-02-01

More than half of the patients with an impalpable malignant breast lesion have a mammographically detected and imaged-guided localisation, which can be technically challenging for the breast surgeon. Specimen imaging is used to confirm successful excision of the localised index lesion and has improved the operating list efficiency resulting in a higher number of excisions per surgical list. The aim of this study was to evaluate whether introducing IDSM (intra-operative digital specimen mammography) saved operation time for localised breast surgery. A single-centre retrospective review was undertaken to compare the operation time (from incision to wound closure) taken for excision of 114 consecutive image-guided localised impalpable breast lesions, performed using departmental specimen radiography (DSR), 6 months prior to the introduction of IDSM (Hologic, Trident ® ) in March 2013, with the theatre time taken for excision of 121 consecutive image-guided localised impalpable breast lesions in the 6 months following introduction of IDSM. There was no significant difference in mean surgical time, which were 47.8 (±27.3) minutes in the CSR group and 48.8 (±25.7) minutes in the IDSM group. We were expecting to confirm a reduction in theatre time with the introduction of IDSM. Surprisingly, no difference in operating times was demonstrated. Factors that influenced the impact of IDSM included the proximity of the imaging department to the operating theatre. © 2017 The Royal Australian and New Zealand College of Radiologists.

Role of specimen US for predicting resection margin status in breast conserving therapy.

PubMed

Moschetta, M; Telegrafo, M; Introna, T; Coi, L; Rella, L; Ranieri, V; Cirili, A; Stabile Ianora, A A; Angelelli, G

2015-01-01

To assess the diagnostic accuracy of specimen ultrasound (US) for predicting resection margin status in women undergoing breast conserving therapy for US-detected cancer, having the histological findings as the reference standard. A total of 132 consecutive patients (age range, 34-87 years; mean, 51 years) underwent breast-conserving surgery for US-detected invasive breast cancer. All surgical specimens underwent US examination. The presence of lesion within the specimen and its distance from the specimen margins were assessed considering a threshold distance between the lesion and specimen margins of 10 mm. US findings were then compared with the pathological ones and specimen US. Sensitivity, specificity, diagnostic accuracy, positive (PPV) and negative predictive values (NPV) for predicting histological margin status were evaluated, having the histological findings as the reference standard. The histological examination detected invasive ductal carcinoma in 96/132 (73%) cases, invasive lobular carcinoma in 32/132 (24%), mucinous carcinoma in 4/132 (3%). The pathological margin analysis revealed 96/132 (73%) negative margins and 36 (27%) close/positive margins. US examination detected all 132 breast lesions within the surgical specimens. 110 (83%) negative margins and 22 (17%) positive margins were found on US. Sensitivity, specificity, diagnostic accuracy, PPV and NPV of 44%, 94%, 80%, 73% and 82%, respectively, were found for specimen US. Specimen US represents a time and cost saving imaging tool for evaluating the presence of US detected-breast lesion within surgical specimen and for predicting the histological margin status.

Quantification of FDG-PET/CT with delayed imaging in patients with newly diagnosed recurrent breast cancer.

PubMed

Baun, Christina; Falch, Kirsten; Gerke, Oke; Hansen, Jeanette; Nguyen, Tram; Alavi, Abass; Høilund-Carlsen, Poul-Flemming; Hildebrandt, Malene G

2018-05-09

Several studies have shown the advantage of delayed-time-point imaging with 18F-FDG-PET/CT to distinguish malignant from benign uptake. This may be relevant in cancer diseases with low metabolism, such as breast cancer. We aimed at examining the change in SUV from 1 h (1h) to 3 h (3h) time-point imaging in local and distant lesions in patients with recurrent breast cancer. Furthermore, we investigated the effect of partial volume correction in the different types of metastases, using semi-automatic quantitative software (ROVER™). One-hundred and two patients with suspected breast cancer recurrence underwent whole-body PET/CT scans 1h and 3h after FDG injection. Semi-quantitative standardised uptake values (SUVmax, SUVmean) and partial volume corrected SUVmean (cSUVmean), were estimated in malignant lesions, and as reference in healthy liver tissue. The change in quantitative measures from 1h to 3h was calculated, and SUVmean was compared to cSUVmean. Metastases were verified by biopsy. Of the 102 included patients, 41 had verified recurrent disease with in median 15 lesions (range 1-70) amounting to a total of 337 malignant lesions included in the analysis. SUVmax of malignant lesions increased from 6.4 ± 3.4 [0.9-19.7] (mean ± SD, min and max) at 1h to 8.1 ± 4.4 [0.7-29.7] at 3h. SUVmax in breast, lung, lymph node and bone lesions increased significantly (p < 0.0001) between 1h and 3h by on average 25, 40, 33, and 27%, respectively. A similar pattern was observed with (uncorrected) SUVmean. Partial volume correction increased SUVmean significantly, by 63 and 71% at 1h and 3h imaging, respectively. The highest impact was in breast lesions at 3h, where cSUVmean increased by 87% compared to SUVmean. SUVs increased from 1h to 3h in malignant lesions, SUVs of distant recurrence were in general about twice as high as those of local recurrence. Partial volume correction caused significant increases in these values. However, it is questionable, if these relatively modest quantitative advances of 3h imaging are sufficient to warrant delayed imaging in this patient group. ClinicalTrails.gov NCT01552655 . Registered 28 February 2012, partly retrospectively registered.

Breast Cancer: Diffusion Kurtosis MR Imaging-Diagnostic Accuracy and Correlation with Clinical-Pathologic Factors.

PubMed

Sun, Kun; Chen, Xiaosong; Chai, Weimin; Fei, Xiaochun; Fu, Caixia; Yan, Xu; Zhan, Ying; Chen, Kemin; Shen, Kunwei; Yan, Fuhua

2015-10-01

To assess diagnostic accuracy with diffusion kurtosis imaging (DKI) in patients with breast lesions and to evaluate the potential association between DKI-derived parameters and breast cancer clinical-pathologic factors. Institutional review board approval and written informed consent were obtained. Data from 97 patients (mean age ± standard deviation, 45.7 years ± 13.1; range, 19-70 years) with 98 lesions (57 malignant and 41 benign) who were treated between January 2014 and April 2014 were retrospectively analyzed. DKI (with b values of 0-2800 sec/mm(2)) and conventional diffusion-weighted imaging data were acquired. Kurtosis and diffusion coefficients from DKI and apparent diffusion coefficients from diffusion-weighted imaging were measured by two radiologists. Student t test, Wilcoxon signed-rank test, Jonckheere-Terpstra test, receiver operating characteristic curves, and Spearman correlation were used for statistical analysis. Kurtosis coefficients were significantly higher in the malignant lesions than in the benign lesions (1.05 ± 0.22 vs 0.65 ± 0.11, respectively; P < .0001). Diffusivity and apparent diffusion coefficients in the malignant lesions were significantly lower than those in the benign lesions (1.13 ± 0.27 vs 1.97 ± 0.33 and 1.02 ± 0.18 vs 1.48 ± 0.33, respectively; P < .0001). Significantly higher specificity for differentiation of malignant from benign lesions was shown with the use of kurtosis and diffusivity coefficients than with the use of apparent diffusion coefficients (83% [34 of 41] and 83% [34 of 41] vs 76% [31 of 41], respectively; P < .0001) with equal sensitivity (95% [54 of 57]). In patients with invasive breast cancer, kurtosis was positively correlated with tumor histologic grade (r = 0.75) and expression of the Ki-67 protein (r = 0.55). Diffusivity was negatively correlated with tumor histologic grades (r = -0.44) and Ki-67 expression (r = -0.46). DKI showed higher specificity than did conventional diffusion-weighted imaging for assessment of benign and malignant breast lesions. Patients with grade 3 breast cancer or tumors with high expression of Ki-67 were associated with higher kurtosis and lower diffusivity coefficients; however, this association must be confirmed in prospective studies. (©) RSNA, 2015 Online supplemental material is available for this article.

National program of breast cancer early detection in Brod-Posavina County (East Croatia).

PubMed

Jurišić, Irena; Kolovrat, Ana; Mitrečić, Drago; Cvitković, Ante

2014-09-01

Results of the National Program of Breast Cancer Early Detection in Brod-Posavina County during the 2006-2012 period are presented. Response rate in two National Program cycles, cancers detected according to factors such as first and last menstruation, age at cancer detection, deliveries and mammography findings according to the Breast Imaging Reporting and Data System (BI-RADS) before diagnosis verification were analyzed. Data were obtained from the software connecting Public Health Institutes via Ministry of Health server and questionnaires filled out by the women presenting for screening and processed by the method of descriptive statistics. Mammography findings were classified according to the BI-RADS classification. In two National Program cycles during the 2006-2012 period, women aged 50-69 were called for mammography screening. In the first cycle, the response rate in Brod-Posavina County was 53.2%, with 71 cancers detected at a mean age of 61.3 years. In the second cycle, the response rate was 57.0%, with 44 cancers detected at a mean age of 62.5 years. In the first and second cycles, there were 21.1% and 14.3% of mammography findings requiring additional work-up (BI-RADS 0), respectively. Particular risk factors such as early menarche, late menopause, parity, positive family history and presence of benign breast lesions were not demonstrated in women with verified cancer. There was no increase in the incidence of breast cancer per 100,000 inhabitants in the Brod-Posavina County following implementation of the National Program. In conclusion, efforts should be focused on increasing public health awareness, ensuring appropriate professional staff engaged in screening, and improving medical care in order to reduce the time elapsed from establishing suspicion to confirming the diagnosis of breast cancer.

Systemic treatment after whole-brain radiotherapy may improve survival in RPA class II/III breast cancer patients with brain metastasis.

PubMed

Zhang, Qian; Chen, Jian; Yu, Xiaoli; Ma, Jinli; Cai, Gang; Yang, Zhaozhi; Cao, Lu; Chen, Xingxing; Guo, Xiaomao; Chen, Jiayi

2013-09-01

Whole brain radiotherapy (WBRT) is the most widely used treatment for brain metastasis (BM), especially for patients with multiple intracranial lesions. The purpose of this study was to examine the efficacy of systemic treatments following WBRT in breast cancer patients with BM who had different clinical characteristics, based on the classification of the Radiation Therapy Oncology Group recursive partitioning analysis (RPA) and the breast cancer-specific Graded Prognostic Assessment (Breast-GPA). One hundred and one breast cancer patients with BM treated between 2006 and 2010 were analyzed. The median interval between breast cancer diagnosis and identification of BM in the triple-negative patients was shorter than in the luminal A subtype (26 vs. 36 months, respectively; P = 0.021). Univariate analysis indicated that age at BM diagnosis, Karnofsky performance status/recursive partitioning analysis (KPS/RPA) classes, number of BMs, primary tumor control, extracranial metastases and systemic treatment following WBRT were significant prognostic factors for overall survival (OS) (P < 0.05). Multivariate analysis revealed that KPS/RPA classes and systemic treatments following WBRT remained the significant prognostic factors for OS. For RPA class I, the median survival with and without systemic treatments following WBRT was 25 and 22 months, respectively (P = 0.819), while for RPA class II/III systemic treatments significantly improved OS from 7 and 2 months to 11 and 5 months, respectively (P < 0.05). Our results suggested that triple-negative patients had a shorter interval between initial diagnosis and the development of BM than luminal A patients. Systemic treatments following WBRT improved the survival of RPA class II/III patients.

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.

Analysis of metaplastic breast carcinoma: FNAC; histopathology and immunohistochemistry are complementary for diagnosis.

PubMed

Abd El Hafez, Amal; Shawky, Abd El-Aty

2013-01-01

Metaplastic breast carcinoma (MBC) is a rare malignancy comprised of ductal, squamous and/or mesenchymal elements with problematic diagnosis. This study analyses MBC identifying its cytologic and histologic features and emphasizing the combined role of FNAC, histopathology and immunohistochemistry (IHC) in its diagnosis. Cytology and histopathology files search yielded 21 cases identified as MBC from January 2005 to December 2010. FNAC and the histopathology slides were re-examined for the presence and frequency of various elements. Cytological and histopathological diagnoses were made and the cases subtyped according to WHO classification. Cytokeratin and vimenten IHC were used to confirm diagnosis when required. On FNAC, 52.4% were diagnosed as malignant, 9.5% as suspicious for malignancy and 38.1% as benign lesions. Most frequent cytologic findings were squamous and spindle cell elements (52.4% each). Histopathology revealed 76.2% pure epithelial tumors and 23.8% mixed epithelial-mesenchymal tumors. Squamous cell carcinoma was the most frequent histological subtype (33.3%). Carcinosarcomas were dimorphic on IHC& spindle cell carcinomas were positive for both cytokeratin and vimentin. Presence of dual components, squamous, spindle elements, mesenchymal fragments and necrosis in moderate to high cellularity breast FNAC provides clues for the diagnosis of MBC. FNAC; histopathology and IHC complement for diagnosis.

[Benign proliferative breast disease with and without atypia].

PubMed

Coutant, C; Canlorbe, G; Bendifallah, S; Beltjens, F

2015-12-01

In the last few years, diagnostics of high-risk breast lesions (atypical ductal hyperplasia [ADH], flat epithelial atypia [FEA], lobular neoplasia: atypical lobular hyperplasia [ALH], lobular carcinoma in situ [LCIS], radial scar [RS], usual ductal hyperplasia [UDH], adenosis, sclerosing adenosis [SA], papillary breast lesions, mucocele-like lesion [MLL]) have increased with the growing number of breast percutaneous biopsies. The management of these lesions is highly conditioned by the enlarged risk of breast cancer combined with either an increased probability of finding cancer after surgery, either a possible malignant transformation (in situ or invasive cancer), or an increased probability of developing cancer on the long range. An overview of the literature reports grade C recommendations concerning the management and follow-up of these lesions: in case of ADH, FEA, ALH, LCIS, RS, MLL with atypia, diagnosed on percutaneous biopsies: surgical excision is recommended; in case of a diagnostic based on vacuum-assisted core biopsy with complete disappearance of radiological signal for FEA or RS without atypia: surgical abstention is a valid alternative approved by multidisciplinary meeting. In case of ALH (incidental finding) associated with benign lesion responsible of radiological signal: abstention may be proposed; in case of UDH, adenosis, MLL without atypia, diagnosed on percutaneous biopsies: the concordance of radiology and histopathology findings must be ensured. No data is available to recommend surgery; in case of non-in sano resection for ADH, FEA, ALH, LCIS (except pleomorphic type), RS, MLL: surgery does not seem to be necessary; in case of previous ADH, ALH, LCIS: a specific follow-up is recommended in accordance with HAS's recommendations. In case of FEA and RS or MLL combined with atypia, little data are yet available to differ the management from others lesions with atypia; in case of UDH, usual sclerosing adenosis, RS without atypia, fibro cystic disease: no specific follow-up is recommended in agreement with HAS's recommendations. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Pure squamous cell carcinoma of the breast presenting as a pyogenic abscess: a case report.

PubMed

Nair, Vimoj J; Kaushal, Vivek; Atri, Rajeev

2007-08-01

The field of oncology is studded with fascinating case reports of rarities, and management of breast cancer by the oncologist has, at times, resulted in the surfacing of such instances of rarities. Pure squamous cell carcinoma (SCC) of the breast is such an example of a rare and generally aggressive malignancy constituting < 0.1% of invasive breast cancers. To the best of our knowledge, until 2006, only 5 patients of primary SCC of the breast, which presented clinically as breast abscess, have been reported in medical literature. We report the sixth worldwide case of pure primary SCC of the breast presenting as an abscess. In this report, we highlight the fact that a benign lesion like breast abscess can harbor such a rare malignancy. Clinicians should be aware of that fact, and adequate investigations should be done to rule out that possibility. Extensive literature review has been done to discuss the clinical and radiologic features as well as management of this rare lesion.

Impact of compressed breast thickness and dose on lesion detectability in digital mammography: FROC study with simulated lesions in real mammograms

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

Salvagnini, Elena, E-mail: elena.salvagnini@gmail.

Purpose: The aim of this work was twofold: (1) to examine whether, with standard automatic exposure control (AEC) settings that maintain pixel values in the detector constant, lesion detectability in clinical images decreases as a function of breast thickness and (2) to verify whether a new AEC setup can increase lesion detectability at larger breast thicknesses. Methods: Screening patient images, acquired on two identical digital mammography systems, were collected over a period of 2 yr. Mammograms were acquired under standard AEC conditions (part 1) and subsequently with a new AEC setup (part 2), programmed to use the standard AEC settingsmore » for compressed breast thicknesses ≤49 mm, while a relative dose increase was applied above this thickness. The images were divided into four thickness groups: T1 ≤ 29 mm, T2 = 30–49 mm, T3 = 50–69 mm, and T4 ≥ 70 mm, with each thickness group containing 130 randomly selected craniocaudal lesion-free images. Two measures of density were obtained for every image: a BI-RADS score and a map of volumetric breast density created with a software application (VolparaDensity, Matakina, NZ). This information was used to select subsets of four images, containing one image from each thickness group, matched to a (global) BI-RADS score and containing a region with the same (local) VOLPARA volumetric density value. One selected lesion (a microcalcification cluster or a mass) was simulated into each of the four images. This process was repeated so that, for a given thickness group, half the images contained a single lesion and half were lesion-free. The lesion templates created and inserted in groups T3 and T4 for the first part of the study were then inserted into the images of thickness groups T3 and T4 acquired with higher dose settings. Finally, all images were visualized using the ViewDEX software and scored by four radiologists performing a free search study. A statistical jackknife-alternative free-response receiver operating characteristic analysis was applied. Results: For part 1, the alternative free-response receiver operating characteristic curves for the four readers were 0.80, 0.65, 0.55 and 0.56 in going from T1 to T4, indicating a decrease in detectability with increasing breast thickness. P-values and the 95% confidence interval showed no significant difference for the T3-T4 comparison (p = 0.78) while all the other differences were significant (p < 0.05). Separate analysis of microcalcification clusters presented the same results while for mass detection, the only significant difference came when comparing T1 to the other thickness groups. Comparing the scores of part 1 and part 2, results for the T3 group acquired with the new AEC setup and T3 group at standard AEC doses were significantly different (p = 0.0004), indicating improved detection. For this group a subanalysis for microcalcification detection gave the same results while no significant difference was found for mass detection. Conclusions: These data using clinical images confirm results found in simple QA tests for many mammography systems that detectability falls as breast thickness increases. Results obtained with the AEC setup for constant detectability above 49 mm showed an increase in lesion detection with compressed breast thickness, bringing detectability of lesions to the same level.« less

Dual modality surgical guidance of non-palpable breast lesions

NASA Astrophysics Data System (ADS)

Judy, Patricia Goodale

Although breast conserving therapy has some advantages over the traditional mastectomy procedure, the biggest disadvantage is the chance of local re-occurrence in which a second surgery is often required. Adequate surgical removal of breast tumors requires accurate tumor localization in order to ensure a balance between optimal cosmetic results and minimization of the risk for local re-occurrence. These challenges have motivated the search for alternative, more accurate methods for intraoperative localization of non-palpable breast lesions. The overall goal of this project was to develop an innovative technique for radioguided localization of non-palpable breast lesions that is more accurate, easier for the breast surgeon, and more comfortable for the patient than the current practice of wire localization. The technique uses a dual modality breast imaging system to place a marker composed of radiolabeled albumin (99mTc-MAA or 111ln-MAA) into the lesion. Preliminary studies were made to evaluate the localization accuracy of the system, which showed that the dual modality breast scanner is capable of accurate 3-dimensional localization using either X-ray or gamma ray imaging. A 3-axis needle positioning system was built and integrated into the dual modality breast scanner and its accuracy tested. A pilot clinical trial to evaluate the dual-modality surgical guidance technique was designed and preliminary clinical data collected. Detailed results were presented on the first three subjects; although a total of seven subjects have been recruited to the study to date. So far, it has been demonstrated that the radioguided surgery technique can be performed with approximately 10 times less radiomarker activity than is currently being used by other researchers employing 99mTc-MAA as a radiomarker, while maintaining comparable localization accuracy. Although the DMSG technique has not been tested in a large cohort of subjects, the preliminary data on the first few are encouraging. Feedback on the technique from the surgeons, for this limited population, has been positive. Recruitment to the study is ongoing.

Efficacy and cost-effectiveness of stereotactic vacuum-assisted core biopsy of nonpalpable breast lesions: analysis of 602 biopsies performed over 5 years.

PubMed

Luparia, A; Durando, M; Campanino, P; Regini, E; Lucarelli, D; Talenti, A; Mattone, G; Mariscotti, G; Sapino, A; Gandini, G

2011-04-01

The authors sought to evaluate the diagnostic accuracy and cost-effectiveness of vacuum-assisted core biopsy (VACB) in comparison with diagnostic surgical excision for characterisation of nonpalpable breast lesions classified as Breast Imaging Reporting and Data System (BI-RADS) categories R3 and R4. From January 2004 to December 2008, we conducted 602 stereotactic, 11-gauge, VACB procedures on 243 nonpalpable breast lesions categorised as BI-RADS R3, 346 categorised as BI-RADS R4 and 13 categorised as BI-RADS R5. We calculated the diagnostic accuracy and cost savings of VACB by subtracting the cost of the stereotactic biopsy from that of the diagnostic surgical procedure. A total of 56% of the lesions were benign and required no further assessment. Lesions of uncertain malignant potential (B3) (23.6%) were debated at multidisciplinary meetings, and diagnostic surgical biopsy was recommended for 83.1% of them. All malignant lesions (B4 and B5) underwent surgical excision. VACB had a sensitivity of 94.9%, specificity of 98.3% and diagnostic accuracy of 97.7%. The cost savings per VACB procedure were 464.00 euro; by obviating 335 surgical biopsies, the overall cost savings was 155,440.00 euro over 5 years. VACB proved to have high diagnostic accuracy for characterising abnormalities at low to intermediate risk of malignancy and obviated surgical excision in about half of the cases, allowing for considerable cost savings.

Contrast-Enhanced Spectral Mammography: Comparison with Conventional Mammography and Histopathology in 152 Women

PubMed Central

Luczyńska, Elzbieta; Heinze-Paluchowska, Sylwia; Dyczek, Sonia; Rys, Janusz; Reinfuss, Marian

2014-01-01

Objective The goal of the study was to compare conventional mammography (MG) and contrast-enhanced spectral mammography (CESM) in preoperative women. Materials and Methods The study was approved by the local Ethics Committee and all participants provided informed consent. The study included 152 consecutive patients with 173 breast lesions diagnosed on MG or CESM. All MG examinations and consults were conducted in one oncology centre. Non-ionic contrast agent, at a total dose of 1.5 mL/kg body weight, was injected intravenous. Subsequently, CESM exams were performed with a mammography device, allowing dual-energy acquisitions. The entire procedure was done within the oncology centre. Images from low and high energy exposures were processed together and the combination provided an "iodine" image which outlined contrast up-take in the breast. Results MG detected 157 lesions in 150 patients, including 92 infiltrating cancers, 12 non-infiltrating cancers, and 53 benign lesions. CESM detected 149 lesions in 128 patients, including 101 infiltrating cancers, 13 non-infiltrating cancers, and 35 benign lesions. CESM sensitivity was 100% (vs. 91% for MG), specificity was 41% (vs. 15% for MG), area under the receiver operating characteristic curve was 0.86 (vs. 0.67 for MG), and accuracy was 80% (vs. 65% for MG) for the diagnosis of breast cancer. Both MG and CESM overestimated lesion sizes compared to histopathology (p < 0.001). Conclusion CESM may provide higher sensitivity for breast cancer detection and greater diagnostic accuracy than conventional mammography. PMID:25469079

Contrast-enhanced spectral mammography: comparison with conventional mammography and histopathology in 152 women.

PubMed

Luczyńska, Elzbieta; Heinze-Paluchowska, Sylwia; Dyczek, Sonia; Blecharz, Pawel; Rys, Janusz; Reinfuss, Marian

2014-01-01

The goal of the study was to compare conventional mammography (MG) and contrast-enhanced spectral mammography (CESM) in preoperative women. The study was approved by the local Ethics Committee and all participants provided informed consent. The study included 152 consecutive patients with 173 breast lesions diagnosed on MG or CESM. All MG examinations and consults were conducted in one oncology centre. Non-ionic contrast agent, at a total dose of 1.5 mL/kg body weight, was injected intravenous. Subsequently, CESM exams were performed with a mammography device, allowing dual-energy acquisitions. The entire procedure was done within the oncology centre. Images from low and high energy exposures were processed together and the combination provided an "iodine" image which outlined contrast up-take in the breast. MG detected 157 lesions in 150 patients, including 92 infiltrating cancers, 12 non-infiltrating cancers, and 53 benign lesions. CESM detected 149 lesions in 128 patients, including 101 infiltrating cancers, 13 non-infiltrating cancers, and 35 benign lesions. CESM sensitivity was 100% (vs. 91% for MG), specificity was 41% (vs. 15% for MG), area under the receiver operating characteristic curve was 0.86 (vs. 0.67 for MG), and accuracy was 80% (vs. 65% for MG) for the diagnosis of breast cancer. Both MG and CESM overestimated lesion sizes compared to histopathology (p < 0.001). CESM may provide higher sensitivity for breast cancer detection and greater diagnostic accuracy than conventional mammography.

Role of shear wave sonoelastography in differentiation between focal breast lesions.

PubMed

Dobruch-Sobczak, Katarzyna; Nowicki, Andrzej

2015-02-01

Our goal in this study was to evaluate the relevance of shear wave sonoelastography (SWE) in the differential diagnosis of masses in the breast with respect to ultrasound (US). US and SWE were performed (Aixplorer System, SuperSonic Imagine, Aix en Provence, France) in 76 women (aged 24 to 85) with 84 lesions (43 malignant, 41 benign). The study included BI-RADS-US (Breast Imaging Reporting and Data System for Ultrsound) category 3-5 lesions. In elastograms, the following values were calculated: mean elasticity in lesions (E(av.l)) and in fat tissue (E(av.f.)) and maximal (E(max.adj.)) and mean (E(av.adj.)) elasticity in lesions and adjacent tissues. The sensitivity and specificity of the BI-RADS category 4a/4b cutoff value were 97.7% and 90.2%. For an E(av.adj.) of 68.5 kPa, the cutoff sensitivity was 86.1% and the specificity was 87.8%, and for an E(max.adj.) of 124.1 kPa, 74.4% and 92.7%, respectively. For BI-RADS-US category 3 lesions, E(av.l), E(max.adj.) and E(av.adj.) were below cutoff levels. On the basis of our findings, E(av.adj.) had lower sensitivity and specificity compared with US. Emax.adj. improved the specificity of breast US with loss of sensitivity. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

[Clinical features and treatment of choroidal metastasis].

PubMed

Wang, Guang-lu; Wang, Ming-yang; Wei, Wen-bin

2009-03-01

To assess the clinical features and management of choroidal metastasis. Fundus examination was performed in 49 patients (66 eyes) with choroidal metastasis. Fundus fluorescein angiography (FFA) was performed in 44 cases, combined with indocyanine green angiography (ICGA) examination in 12 cases. B-scan ultrasound examination was performed in 8 cases. Transpupillary thermotherapy (TTT) was performed in 24 eyes, combined with photo-dynamic therapy in one eye. Plaque radio-therapy was used in one eye. The parameters of treatment for TTT were 1.2 - 3 mm spot size, 450 - 1000 mV, 60 s; 2 sessions of TTT in 2 eyes and 3 sessions in 3 eyes. Fourteen cases were male and 35 cases were female. Both eyes were affected in 17 cases (34.7%). Age ranged from 23 - 74 years old with an average of 47 years. The visual acuity was 0.05 or less in 13 eyes; 0.06 - 0.2 in 22 eyes and 0.3 or more in 31 eyes. Primary tumours were found in 40 cases (81.6%) (surgical excision in 25 cases), consisting of breast carcinoma in 16 cases (32.7%), lung carcinoma in 14 cases (28.6%), hepatoma and cholangiocarcinoma in 3 cases, colon and stomach carcinomas in 3 cases, gynecologic appendix carcinoma (including 1 case of ovarian mucous cyst adenocarcinoma) in 2 cases, nasopharyngeal adenocarcinoma in 1 case, vertebra tumor in 1 case, undetected in 5 cases (10.2%) and under detection in 4 cases (8.2%). The fundus had 1 lesion in 58 eyes (58/66 = 87.8%), 2 lesions in 4 eyes (4/66 = 6.0%), 3 or more lesions in 2 eyes (including 7 lesions in 1 eye). According to the location and development status of the lesions, they could be divided into solitary type, 39 eyes (39/66 = 59.1%); diffuse type, 19 eyes (19/66 = 28.8%); and early type, 8 eyes (8/66 = 12.1%). FFA examination: early stage lesions showed hypofluorescence and later stage lesions showed moderate to strong hyperfluorescence. In 8 cases of solitary lesions, the size of the lesion measured by B-scan averaged 11.5 mm x 10.5 mm x 3.6 mm with the maximal height at 4.9 mm. The tumor became flattened and vision remained stable at 3 months after plaque radiotherapy in 1 case. Three cases were followed-up for 2, 3, and 4 months after TTT treatment. The lesions remained stable with vision unchanged or slightly decreased. The choroidal metastasis has specific clinical features. The classification of metastatic lesions into solitary, diffuse and early types is helpful for the evaluation of the disease process. The primary tumor can be found in 80% of cases. The most common primary cancer is breast carcinoma, followed by lung carcinoma. These two cancers account for 75% of primary tumors. In solitary type and early type lesions, TTT combines with systemic treatment could result in regression of lesions, saving of vision and improvement of the life quality.

[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.

Accuracy of MRI volume measurements of breast lesions: comparison between automated, semiautomated and manual assessment.

PubMed

Rominger, Marga B; Fournell, Daphne; Nadar, Beenarose Thanka; Behrens, Sarah N M; Figiel, Jens H; Keil, Boris; Heverhagen, Johannes T

2009-05-01

The aim of this study was to investigate the efficacy of a dedicated software tool for automated and semiautomated volume measurement in contrast-enhanced (CE) magnetic resonance mammography (MRM). Ninety-six breast lesions with histopathological workup (27 benign, 69 malignant) were re-evaluated by different volume measurement techniques. Volumes of all lesions were extracted automatically (AVM) and semiautomatically (SAVM) from CE 3D MRM and compared with manual 3D contour segmentation (manual volume measurement, MVM, reference measurement technique) and volume estimates based on maximum diameter measurement (MDM). Compared with MVM as reference method MDM, AVM and SAVM underestimated lesion volumes by 63.8%, 30.9% and 21.5%, respectively, with significantly different accuracy for benign (102.4%, 18.4% and 11.4%) and malignant (54.9%, 33.0% and 23.1%) lesions (p < 0.05). Inter- and intraobserver reproducibility was best for AVM (mean difference +/- 2SD, 1.0 +/- 9.7% and 1.8 +/- 12.1%) followed by SAVM (4.3 +/- 25.7% and 4.3 +/- 7.9%), MVM (2.3 +/- 38.2% and 8.6 +/- 31.8%) and MDM (33.9 +/- 128.4% and 9.3 +/- 55.9%). SAVM is more accurate for volume assessment of breast lesions than MDM and AVM. Volume measurement is less accurate for malignant than benign lesions.

Bayesian Inference on Malignant Breast Cancer in Nigeria: A Diagnosis of MCMC Convergence

PubMed Central

Ogunsakin, Ropo Ebenezer; Siaka, Lougue

2017-01-01

Background: There has been no previous study to classify malignant breast tumor in details based on Markov Chain Monte Carlo (MCMC) convergence in Western, Nigeria. This study therefore aims to profile patients living with benign and malignant breast tumor in two different hospitals among women of Western Nigeria, with a focus on prognostic factors and MCMC convergence. Materials and Methods: A hospital-based record was used to identify prognostic factors for malignant breast cancer among women of Western Nigeria. This paper describes Bayesian inference and demonstrates its usage to estimation of parameters of the logistic regression via Markov Chain Monte Carlo (MCMC) algorithm. The result of the Bayesian approach is compared with the classical statistics. Results: The mean age of the respondents was 42.2 ±16.6 years with 52% of the women aged between 35-49 years. The results of both techniques suggest that age and women with at least high school education have a significantly higher risk of being diagnosed with malignant breast tumors than benign breast tumors. The results also indicate a reduction of standard errors is associated with the coefficients obtained from the Bayesian approach. In addition, simulation result reveal that women with at least high school are 1.3 times more at risk of having malignant breast lesion in western Nigeria compared to benign breast lesion. Conclusion: We concluded that more efforts are required towards creating awareness and advocacy campaigns on how the prevalence of malignant breast lesions can be reduced, especially among women. The application of Bayesian produces precise estimates for modeling malignant breast cancer. PMID:29072396

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

Quantitative analysis of enhanced malignant and benign lesions on contrast-enhanced spectral mammography.

PubMed

Deng, Chih-Ying; Juan, Yu-Hsiang; Cheung, Yun-Chung; Lin, Yu-Ching; Lo, Yung-Feng; Lin, GiGin; Chen, Shin-Cheh; Ng, Shu-Hang

2018-02-27

To retrospectively analyze the quantitative measurement and kinetic enhancement among pathologically proven benign and malignant lesions using contrast-enhanced spectral mammography (CESM). We investigated the differences in enhancement between 44 benign and 108 malignant breast lesions in CESM, quantifying the extent of enhancements and the relative enhancements between early (between 2-3 min after contrast medium injection) and late (3-6 min) phases. The enhancement was statistically stronger in malignancies compared to benign lesions, with good performance by the receiver operating characteristic curve [0.877, 95% confidence interval (0.813-0.941)]. Using optimal cut-off value at 220.94 according to Youden index, the sensitivity was 75.9%, specificity 88.6%, positive likelihood ratio 6.681, negative likelihood ratio 0.272 and accuracy 82.3%. The relative enhancement patterns of benign and malignant lesions, showing 29.92 vs 73.08% in the elevated pattern, 7.14 vs 92.86% in the steady pattern, 5.71 vs 94.29% in the depressed pattern, and 80.00 vs 20.00% in non-enhanced lesions (p < 0.0001), respectively. Despite variations in the degree of tumour angiogenesis, quantitative analysis of the breast lesions on CESM documented the malignancies had distinctive stronger enhancement and depressed relative enhancement patterns than benign lesions. Advances in knowledge: To our knowledge, this is the first study evaluating the feasibility of quantifying lesion enhancement on CESM. The quantities of enhancement were informative for assessing breast lesions in which the malignancies had stronger enhancement and more relative depressed enhancement than the benign lesions.

Radioactive Seed Localization Versus Wire Localization for Nonpalpable Breast Lesions: A Two-Year Initial Experience at a Large Community Hospital.

PubMed

Stelle, Lacey; Schoenheit, Taylor; Brubaker, Allison; Tang, Xiwei; Qu, Peiyong; Cradock, Kimberly; Higham, Anna

2018-01-01

Radioactive seed localization (RSL) is a safe and effective alternative to wire localization (WL) for nonpalpable breast lesions. While several large academic institutions currently utilize RSL, few community hospitals have adopted this technique. The aim of this study was to examine the experience of RSL versus WL at a large community hospital. A retrospective chart review of patients who underwent RSL or WL for breast-conserving surgery from 1 November 2013 to 31 November 2015. The total number of lesions examined was 382. RSL was utilized in 205 (54%) lesions, with 187 undergoing single RSL, while WL was used in 155 (40%) lesions, with 109 undergoing single WL; both techniques were used in 22 (6%) lesions. Pathology was benign in 142 (48%) lesions, with 93 RSLs and 49 WLs. For malignant lesions, mean specimen size was 36.3 g for single RSL and 35.9 g for single WL (p = 0.904). Re-excision for margin clearance was required for 16 (17%) malignant lesions in the RSL group and 10 (17%) in the WL group (p = 0.954). For malignant lesions, mean operating room time was 86 min for single RSL versus 70 min for single WL (p = 0.014). The use of RSL is a viable option in the community setting, with several benefits over WL. While operative times were slightly longer with RSL, there was no difference in specimen size or re-excision rate for malignant lesions.

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.

Clinical Application of Six Current Classification Systems for Iatrogenic Bile Duct Injuries after Cholecystectomy.

PubMed

Velidedeoglu, Mehmet; Arikan, Akif Enes; Uludag, Sezgin Server; Olgun, Deniz Cebi; Kilic, Fahrettin; Kapan, Metin

2015-05-01

Due to being a severe complication, iatrogenic bile duct injury is still a challenging issue for surgeons in gallbladder surgery. However, a commonly accepted classification describing the type of injury has not been available yet. This study aims to evaluate ability of six current classification systems to discriminate bile duct injury patterns. Twelve patients, who were referred to our clinic because of iatrogenic bile duct injury after laparoscopic cholecystectomy were reviewed retrospectively. We described type of injury for each patient according to current six different classifications. 9 patients underwent definitive biliary reconstruction. Bismuth, Strasberg-Bismuth, Stewart-Way and Neuhaus classifications do not consider vascular involvement, Siewert system does, but only for the tangential lesions without structural loss of duct and lesion with a structural defect of hepatic or common bile duct. Siewert, Neuhaus and Stewart-Way systems do not discriminate between lesions at or above bifurcation of the hepatic duct. The Hannover classification may resolve the missing aspects of other systems by describing additional vascular involvement and location of the lesion at or above bifurcation.

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

Classification of large-scale fundus image data sets: a cloud-computing framework.

PubMed

Roychowdhury, Sohini

2016-08-01

Large medical image data sets with high dimensionality require substantial amount of computation time for data creation and data processing. This paper presents a novel generalized method that finds optimal image-based feature sets that reduce computational time complexity while maximizing overall classification accuracy for detection of diabetic retinopathy (DR). First, region-based and pixel-based features are extracted from fundus images for classification of DR lesions and vessel-like structures. Next, feature ranking strategies are used to distinguish the optimal classification feature sets. DR lesion and vessel classification accuracies are computed using the boosted decision tree and decision forest classifiers in the Microsoft Azure Machine Learning Studio platform, respectively. For images from the DIARETDB1 data set, 40 of its highest-ranked features are used to classify four DR lesion types with an average classification accuracy of 90.1% in 792 seconds. Also, for classification of red lesion regions and hemorrhages from microaneurysms, accuracies of 85% and 72% are observed, respectively. For images from STARE data set, 40 high-ranked features can classify minor blood vessels with an accuracy of 83.5% in 326 seconds. Such cloud-based fundus image analysis systems can significantly enhance the borderline classification performances in automated screening systems.

Evaluation of shear wave elastography for differential diagnosis of breast lesions: A new qualitative analysis versus conventional quantitative analysis.

PubMed

Ren, Wei-Wei; Li, Xiao-Long; Wang, Dan; Liu, Bo-Ji; Zhao, Chong-Ke; Xu, Hui-Xiong

2018-04-13

To evaluate a special kind of ultrasound (US) shear wave elastography for differential diagnosis of breast lesions, using a new qualitative analysis (i.e. the elasticity score in the travel time map) compared with conventional quantitative analysis. From June 2014 to July 2015, 266 pathologically proven breast lesions were enrolled in this study. The maximum, mean, median, minimum, and standard deviation of shear wave speed (SWS) values (m/s) were assessed. The elasticity score, a new qualitative feature, was evaluated in the travel time map. The area under the receiver operating characteristic (AUROC) curves were plotted to evaluate the diagnostic performance of both qualitative and quantitative analyses for differentiation of breast lesions. Among all quantitative parameters, SWS-max showed the highest AUROC (0.805; 95% CI: 0.752, 0.851) compared with SWS-mean (0.786; 95% CI:0.732, 0.834; P = 0.094), SWS-median (0.775; 95% CI:0.720, 0.824; P = 0.046), SWS-min (0.675; 95% CI:0.615, 0.731; P = 0.000), and SWS-SD (0.768; 95% CI:0.712, 0.817; P = 0.074). The AUROC of qualitative analysis in this study obtained the best diagnostic performance (0.871; 95% CI: 0.825, 0.909, compared with the best parameter of SWS-max in quantitative analysis, P = 0.011). The new qualitative analysis of shear wave travel time showed the superior diagnostic performance in the differentiation of breast lesions in comparison with conventional quantitative analysis.

Cystic brain metastasis is associated with poor prognosis in patients with advanced breast cancer.

PubMed

Sun, Bing; Huang, Zhou; Wu, Shikai; Ding, Lijuan; Shen, Ge; Cha, Lei; Wang, Junliang; Song, Santai

2016-11-08

Brain metastasis (BM) with a cystic component from breast cancer is rare and largely uncharacterized. The purpose of this study was to identify the characteristics of cystic BM in a large cohort of breast cancer patients. A total of 35 eligible patients with cystic BM and 255 patients with solid BM were analyzed. Three factors were significantly associated with an increased probability of developing cystic lesions: age at diagnosis ≤ 40 years, age at BM ≤ 45 years, and poor histological grade (p < 0.05). Patients with cystic metastasis were also characterized by a larger metastasis volume, a shorter progression-free survival (PFS) following their first treatment for BM, and poor overall survival after BM (p < 0.05). Multivariate analysis further demonstrated that local control of cystic BM was only potentially achieved for HER2-negative primary tumors (p = 0.084). Breast cancer patients with parenchymal BM were reviewed from consecutive cases treated at our institution. Cystic BM was defined when the volume of a cystic lesion was greater than 50% of the aggregated volume of all lesions present. Clinicopathologic and radiographic variables were correlated with development of cystic lesions and with prognosis of cystic BM. This study shows that cystic BM from breast cancer, a special morphological type of BM, had worse prognosis than the more commonly observed solid BM. Younger age and low tumor grade were associated with the development of cystic lesions. Further comprehensive research and management of cystic BM are warranted to improve its poor prognosis.

Adaptable Near-Infrared Spectroscopy Fiber Array for Improved Coupling to Different Breast Sizes During Clinical MRI

PubMed Central

Mastanduno, Michael A.; El-Ghussein, Fadi; Jiang, Shudong; DiFlorio-Alexander, Roberta; Junqing, Xu; Hong, Yin; Pogue, Brian W.; Paulsen, Keith D.

2016-01-01

Rationale and Objectives Near-infrared spectroscopy (NIRS) of breast can provide functional information on the vascular and structural compartments of tissues in regions identified during simultaneous magnetic resonance imaging (MRI). NIRS can be acquired during dynamic contrast-enhanced MRI (DCE-MRI) to accomplish image-guided spectroscopy of the enhancing regions, potentially increasing the diagnostic specificity of the examination and reducing the number of biopsies performed as a result of inconclusive MRI breast imaging studies. Materials and Methods We combine synergistic attributes of concurrent DCE-MRI and NIRS with a new design of the clinical NIRS breast interface that couples to a standard MR breast coil and allows imaging of variable breast sizes. Spectral information from healthy volunteers and cancer patients is recovered, providing molecular information in regions defined by the segmented MR image volume. Results The new coupling system significantly improves examination utility by allowing improved coupling of the NIR fibers to breasts of all cup sizes and lesion locations. This improvement is demonstrated over a range of breast sizes (cup size A through D) and normal tissue heterogeneity using a group of eight healthy volunteers and two cancer patients. Lesions located in the axillary region and medial-posterior breast are now accessible to NIRS optodes. Reconstructed images were found to have biologically plausible hemoglobin content, oxygen saturation, and water and lipid fractions. Conclusions In summary, a new NIRS/MRI breast interface was developed to accommodate the variation in breast sizes and lesion locations that can be expected in clinical practice. DCE-MRI–guided NIRS quantifies total hemoglobin, oxygenation, and scattering in MR-enhancing regions, increasing the diagnostic information acquired from MR examinations. PMID:24439327

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.

Plasmacytoma of the Breast: A Report of a Rare Disease.

PubMed

Gabriel, Ugare; Joseph, Udosen; Bassey, Ima-Abasi; Joshua, Ayodele; Emmanuel, Djunda

2015-10-01

Extramedullary plasma cells tumours are rare. Much more rarer is their occurance in the breast tissue. Our aim is to report a single case of this very rare lesion (at least from an African perspective) that we incidentally diagnosed histopathologically as a primary extramedullary lesion in a 53 year old woman. Clinical records of a 53 year old postmenopausal woman was referred from a secondary health centre to our clinic with a three weeks' history of right breast lump were reviewed. There was no associated pain, nipple discharge, weight loss or systemic symptoms nor was there a previous history of trauma or surgery to the breast. On examination: two discrete lumps measuring 3x2 and 2 x 1.5cm in the upper medial quadrant of the right breast were identified. The lumps were firm, irregular in shape, not attached to the skin or underlying tissues. Tentative diagnosis of adenocarcinoma of the breast was made, with a differential as fat necrosis. A wide excision biopsy was done four days later for histology, after an inconclusive cytological examination of smear of which the result revealed plasmacytosis. The liver function test, Plasma proteins electrophoresis, electrolytes, urea, creatinine, bicarbonate and pelvic X-rays, and abdomino-pelvic ultrasonography were normal. Bence Jones proteins were negative in urine. Histology of bone marrow aspirate revealed scanty plasma cells. She received 20mg dexamethasone, 20mg adramycin, and 2mg vincristine intravenously and 200mg of alloperinol daily by mouth for three days before leaving by the 4th treatment day against medical advice for personal reasons. This rare lesion should sometimes be considered as a differential diagnosis of a breast lump, as it does not differ from the common lesions clinically, especially in older women.

What are the characteristics of breast cancers misclassified as benign by quantitative ultrasound shear wave elastography?

PubMed

Vinnicombe, S J; Whelehan, P; Thomson, K; McLean, D; Purdie, C A; Jordan, L B; Hubbard, S; Evans, A J

2014-04-01

Shear wave elastography (SWE) is a promising adjunct to greyscale ultrasound in differentiating benign from malignant breast masses. The purpose of this study was to characterise breast cancers which are not stiff on quantitative SWE, to elucidate potential sources of error in clinical application of SWE to evaluation of breast masses. Three hundred and two consecutive patients examined by SWE who underwent immediate surgery for breast cancer were included. Characteristics of 280 lesions with suspicious SWE values (mean stiffness >50 kPa) were compared with 22 lesions with benign SWE values (<50 kPa). Statistical significance of the differences was assessed using non-parametric goodness-of-fit tests. Pure ductal carcinoma in situ (DCIS) masses were more often soft on SWE than masses representing invasive breast cancer. Invasive cancers that were soft were more frequently: histological grade 1, tubular subtype, ≤10 mm invasive size and detected at screening mammography. No significant differences were found with respect to the presence of invasive lobular cancer, vascular invasion, hormone and HER-2 receptor status. Lymph node positivity was less common in soft cancers. Malignant breast masses classified as benign by quantitative SWE tend to have better prognostic features than those correctly classified as malignant. • Over 90 % of cancers assessable with ultrasound have a mean stiffness >50 kPa. • 'Soft' invasive cancers are frequently small (≤10 mm), low grade and screen-detected. • Pure DCIS masses are more often soft than invasive cancers (>40 %). • Large symptomatic masses are better evaluated with SWE than small clinically occult lesions. • When assessing small lesions, 'softness' should not raise the threshold for biopsy.

Retrospective analysis of the utility of multiparametric MRI for differentiating between benign and malignant breast lesions in women in China

PubMed Central

Fan, Wei Xiong; Chen, Xiao Feng; Cheng, Feng Yan; Cheng, Ya Bao; Xu, Tai; Zhu, Wen Biao; Zhu, Xiao Lei; Li, Gui Jin; Li, Shuai

2018-01-01

Abstract We explored the utility of time-resolved angiography with interleaved stochastic trajectories dynamic contrast-enhanced magnetic resonance imaging (TWIST DCE-MRI), readout segmentation of long variable echo-trains diffusion-weighted magnetic resonance imaging- diffusion-weighted magnetic resonance imaging (RESOLVE-DWI), and echo-planar imaging- diffusion-weighted magnetic resonance imaging (EPI-DWI) for distinguishing between malignant and benign breast lesions. This retrospective analysis included female patients with breast lesions seen at a single center in China between January 2016 and April 2016. Patients were allocated to a benign or malignant group based on pathologic diagnosis. All patients received routine MRI, RESOLVE-DWI, EPI-DWI, and TWIST DCE-T1WI. Variables measured included quantitative parameters (Ktrans, Kep, and Ve), semiquantitative parameters (rate of contrast enhancement for contrast agent inflow [W-in], rate of contrast decay for contrast agent outflow [W-out], and time-to-peak enhancement after contrast agent injection [TTP]) and apparent diffusion coefficient (ADC) values for RESOLVE-DWI (ADCr) and EPI-DWI (ADCe). Receiver-operating characteristic (ROC) curve analysis was used to evaluate the diagnostic utility of each parameter for differentiating malignant from benign breast lesions. A total of 87 patients were included (benign, n = 20; malignant, n = 67). Compared with the benign group, the malignant group had significantly higher Ktrans, Kep and W-in and significantly lower W-out, TTP, ADCe, and ADCr (all P < .05); Ve was not significantly different between groups. RESOLVE-DWI was superior to conventional EPI-DWI at illustrating lesion boundary and morphology, while ADCr was significantly lower than ADCe in all patients. Kep, W-out, ADCr, and ADCe showed the highest diagnostic efficiency (based on AUC value) for differentiating between benign and malignant lesions. Combining 3 parameters (Kep, W-out, and ADCr) had a higher diagnostic efficiency (AUC, 0.965) than any individual parameter and distinguished between benign and malignant lesions with high sensitivity (91.0%), specificity (95.0%), and accuracy (91.9%). An index combining Kep, W-out, and ADCr could potentially be used for the differential diagnosis of breast lesions. PMID:29369183

Retrospective analysis of the utility of multiparametric MRI for differentiating between benign and malignant breast lesions in women in China.

PubMed

Fan, Wei Xiong; Chen, Xiao Feng; Cheng, Feng Yan; Cheng, Ya Bao; Xu, Tai; Zhu, Wen Biao; Zhu, Xiao Lei; Li, Gui Jin; Li, Shuai

2018-01-01

We explored the utility of time-resolved angiography with interleaved stochastic trajectories dynamic contrast-enhanced magnetic resonance imaging (TWIST DCE-MRI), readout segmentation of long variable echo-trains diffusion-weighted magnetic resonance imaging- diffusion-weighted magnetic resonance imaging (RESOLVE-DWI), and echo-planar imaging- diffusion-weighted magnetic resonance imaging (EPI-DWI) for distinguishing between malignant and benign breast lesions.This retrospective analysis included female patients with breast lesions seen at a single center in China between January 2016 and April 2016. Patients were allocated to a benign or malignant group based on pathologic diagnosis. All patients received routine MRI, RESOLVE-DWI, EPI-DWI, and TWIST DCE-T1WI. Variables measured included quantitative parameters (K, Kep, and Ve), semiquantitative parameters (rate of contrast enhancement for contrast agent inflow [W-in], rate of contrast decay for contrast agent outflow [W-out], and time-to-peak enhancement after contrast agent injection [TTP]) and apparent diffusion coefficient (ADC) values for RESOLVE-DWI (ADCr) and EPI-DWI (ADCe). Receiver-operating characteristic (ROC) curve analysis was used to evaluate the diagnostic utility of each parameter for differentiating malignant from benign breast lesions.A total of 87 patients were included (benign, n = 20; malignant, n = 67). Compared with the benign group, the malignant group had significantly higher K, Kep and W-in and significantly lower W-out, TTP, ADCe, and ADCr (all P < .05); Ve was not significantly different between groups. RESOLVE-DWI was superior to conventional EPI-DWI at illustrating lesion boundary and morphology, while ADCr was significantly lower than ADCe in all patients. Kep, W-out, ADCr, and ADCe showed the highest diagnostic efficiency (based on AUC value) for differentiating between benign and malignant lesions. Combining 3 parameters (Kep, W-out, and ADCr) had a higher diagnostic efficiency (AUC, 0.965) than any individual parameter and distinguished between benign and malignant lesions with high sensitivity (91.0%), specificity (95.0%), and accuracy (91.9%).An index combining Kep, W-out, and ADCr could potentially be used for the differential diagnosis of breast lesions.

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.

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.

Improving breast cancer diagnosis by reducing chest wall effect in diffuse optical tomography

NASA Astrophysics Data System (ADS)

Zhou, Feifei; Mostafa, Atahar; Zhu, Quing

2017-03-01

We have developed the ultrasound (US)-guided diffuse optical tomography technique to assist US diagnosis of breast cancer and to predict neoadjuvant chemotherapy response of patients with breast cancer. The technique was implemented using a hand-held hybrid probe consisting of a coregistered US transducer and optical source and detector fibers which couple the light illumination from laser diodes and photon detection to the photomultiplier tube detectors. With the US guidance, diffused light measurements were made at the breast lesion site and the normal contralateral reference site which was used to estimate the background tissue optical properties for imaging reconstruction. However, background optical properties were affected by the chest wall underneath the breast tissue. We have analyzed data from 297 female patients, and results have shown statistically significant correlation between the fitted optical properties (μa and μs‧) and the chest wall depth. After subtracting the background μa at each wavelength, the difference of computed total hemoglobin (tHb) between malignant and benign lesion groups has improved. For early stage malignant lesions, the area-under-the-receiver operator characteristic curve (AUC) has improved from 88.5% to 91.5%. For all malignant lesions, the AUC has improved from 85.3% to 88.1%. Statistical test has revealed the significant difference of the AUC improvements after subtracting background tHb values.

Reliability and Validity of the Arthroscopic International Cartilage Repair Society Classification System: Correlation With Histological Assessment of Depth.

PubMed

Dwyer, Tim; Martin, C Ryan; Kendra, Rita; Sermer, Corey; Chahal, Jaskarndip; Ogilvie-Harris, Darrell; Whelan, Daniel; Murnaghan, Lucas; Nauth, Aaron; Theodoropoulos, John

2017-06-01

To determine the interobserver reliability of the International Cartilage Repair Society (ICRS) grading system of chondral lesions in cadavers, to determine the intraobserver reliability of the ICRS grading system comparing arthroscopy and video assessment, and to compare the arthroscopic ICRS grading system with histological grading of lesion depth. Eighteen lesions in 5 cadaveric knee specimens were arthroscopically graded by 7 fellowship-trained arthroscopic surgeons using the ICRS classification system. The arthroscopic video of each lesion was sent to the surgeons 6 weeks later for repeat grading and determination of intraobserver reliability. Lesions were biopsied, and the depth of the cartilage lesion was assessed. Reliability was calculated using intraclass correlations. The interobserver reliability was 0.67 (95% confidence interval, 0.5-0.89) for the arthroscopic grading, and the intraobserver reliability with the video grading was 0.8 (95% confidence interval, 0.67-0.9). A high correlation was seen between the arthroscopic grading of depth and the histological grading of depth (0.91); on average, surgeons graded lesions using arthroscopy a mean of 0.37 (range, 0-0.86) deeper than the histological grade. The arthroscopic ICRS classification system has good interobserver and intraobserver reliability. A high correlation with histological assessment of depth provides evidence of validity for this classification system. As cartilage lesions are treated on the basis of the arthroscopic ICRS classification, it is important to ascertain the reliability and validity of this method. Copyright © 2016 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

[Differentiation between moisture lesions and pressure ulcers using photographs in a critical area].

PubMed

Valls-Matarín, Josefa; Del Cotillo-Fuente, Mercedes; Pujol-Vila, María; Ribal-Prior, Rosa; Sandalinas-Mulero, Inmaculada

2016-01-01

To identify difficulties for nurses in differentiating between moisture lesions and pressure ulcers, proper classification of pressure ulcers to assess the adequate classification of the Grupo Nacional para el Estudio y Asesoramiento de Úlceras por Presión y Heridas Crónicas (GNEAUPP) and the degree of agreement in the correct assessment by type and category of injury. Cross-sectional study in a critical area during 2014. All nurses who agreed to participate were included. They performed a questionnaire with 14 photographs validated by experts of moisture lesions or pressure ulcers in the sacral area and buttocks, with 6 possible answers: Pressure ulcer category I, II, III, IV, moisture lesions and unknown. Demographics and knowledge of the classification system of the pressure ulcers were collected according to GNEAUPP. It involved 98% of the population (n=56); 98.2% knew the classification system of the GNEAUPP; 35.2% of moisture lesions were considered as pressure ulcers, most of them as a category II (18.9%). The 14.8% of the pressure ulcers photographs were identified as moisture lesions and 16.1% were classified in another category. The agreement between nurses earned a global Kappa index of .38 (95% CI: .29-.57). There are difficulties differentiating between pressure ulcers and moisture lesions, especially within initial categories. Nurses have the perception they know the pressure ulcers classification, but they do not classify them correctly. The degree of concordance in the diagnosis of skin lesions was low. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

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.