scispace - formally typeset
Search or ask a question

Showing papers on "Mammography published in 2016"


Journal ArticleDOI
TL;DR: The USPSTF concludes that the current evidence is insufficient to assess the benefits and harms of digital breast tomosynthesis (DBT) as a primary screening method for breast cancer.
Abstract: This guideline from the USPSTF is based on current evidence on mammography, digital breast tomography, and supplemental screening for breast cancer. The recommendations apply to asymptomatic women ...

1,383 citations


Journal ArticleDOI
TL;DR: Although the rate of detection of large tumors fell after the introduction of screening mammography, the more favorable size distribution was primarily the result of the additional detection of small tumors.
Abstract: BackgroundThe goal of screening mammography is to detect small malignant tumors before they grow large enough to cause symptoms. Effective screening should therefore lead to the detection of a greater number of small tumors, followed by fewer large tumors over time. MethodsWe used data from the Surveillance, Epidemiology, and End Results (SEER) program, 1975 through 2012, to calculate the tumor-size distribution and size-specific incidence of breast cancer among women 40 years of age or older. We then calculated the size-specific cancer case fatality rate for two time periods: a baseline period before the implementation of widespread screening mammography (1975 through 1979) and a period encompassing the most recent years for which 10 years of follow-up data were available (2000 through 2002). ResultsAfter the advent of screening mammography, the proportion of detected breast tumors that were small (invasive tumors measuring <2 cm or in situ carcinomas) increased from 36% to 68%; the proportion of detecte...

458 citations


Journal ArticleDOI
TL;DR: An innovative representation learning framework for breast cancer diagnosis in mammography that integrates deep learning techniques to automatically learn discriminative features avoiding the design of specific hand-crafted image-based feature detectors is described.

366 citations



Journal ArticleDOI
15 Jul 2016
TL;DR: The conclusion of the current study was that the frequency of screening might be dependent on breast density and in such cases diagnostic techniques such as “digital mammography, ultra sonography and magnetic resonance imaging” may prove to be better detection tools.
Abstract: With the increase in breast cancer risk over the years, there are many factors estimated that lead to it. However, till date which factor is majorly involved in development of breast cancer or which factor accounts more is not clearly evident. Mammography technique accounting for 80-90% of cancer being detected is believed to be the best method of detection. While mammographic density is manifested by increased proliferation of fat, stoma, epithelium and connective tissue, it is considered to be a risk factor for development of breast cancer. The current study was thus conducted to find out whether the mammographic density is actually a risk factor for development of breast cancer and to find out the better detection tool available. For this, the methodology adopted was review of various journals and studies already published with respect to mammographic density and its risk on development of breast cancer. The conclusion of the current study as well as from another comparable study was that the frequency of screening might be dependent on breast density and in such cases diagnostic techniques such as “digital mammography, ultra sonography and magnetic resonance imaging” may prove to be better detection tools. Moreover, recent studies have also suggested that mammographic density as a marker for risk of developing breast cancer holds true however, this fact needs to be evaluated further. Article DOI: https://dx.doi.org/10.20319/lijhls.2016.22.4854 This work is licensed under the Creative Commons Attribution-Non-commercial 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.

317 citations


Journal ArticleDOI
TL;DR: The results suggest that one-view DBT might be feasible as a stand-alone screening modality for breast cancer screening, and the recall rate increased significantly but was still low.
Abstract: Objective To assess the performance of one-view digital breast tomosynthesis (DBT) in breast cancer screening.

250 citations


Journal ArticleDOI
TL;DR: In this paper, a systematic review was conducted to inform the new recommendation on breast cancer screening from the USPSTF, which addresses supplemental cancer screening in women with dense breasts.
Abstract: This systematic review, conducted to inform the new recommendation on breast cancer screening from the USPSTF, addresses supplemental breast cancer screening in women with dense breasts.

248 citations


Journal ArticleDOI
TL;DR: Overall, deep learning based on large datasets was superior to standard methods for the discrimination of microcalcifications, and was increased by adopting a combinatorial approach to detect microCalcifications and masses simultaneously.
Abstract: Microcalcification is an effective indicator of early breast cancer. To improve the diagnostic accuracy of microcalcifications, this study evaluates the performance of deep learning-based models on large datasets for its discrimination. A semi-automated segmentation method was used to characterize all microcalcifications. A discrimination classifier model was constructed to assess the accuracies of microcalcifications and breast masses, either in isolation or combination, for classifying breast lesions. Performances were compared to benchmark models. Our deep learning model achieved a discriminative accuracy of 87.3% if microcalcifications were characterized alone, compared to 85.8% with a support vector machine. The accuracies were 61.3% for both methods with masses alone and improved to 89.7% and 85.8% after the combined analysis with microcalcifications. Image segmentation with our deep learning model yielded 15, 26 and 41 features for the three scenarios, respectively. Overall, deep learning based on large datasets was superior to standard methods for the discrimination of microcalcifications. Accuracy was increased by adopting a combinatorial approach to detect microcalcifications and masses simultaneously. This may have clinical value for early detection and treatment of breast cancer.

230 citations


Journal ArticleDOI
TL;DR: Integration of 3D mammography (2D-3D or 2D synthetic-3d) detected more cases of breast cancer than 2D Mammography alone, but increased the percentage of false-positive recalls.
Abstract: Summary Background Breast tomosynthesis (pseudo-3D mammography) improves breast cancer detection when added to 2D mammography. In this study, we examined whether integrating 3D mammography with either standard 2D mammography acquisitions or with synthetic 2D images (reconstructed from 3D mammography) would detect more cases of breast cancer than 2D mammography alone, to potentially reduce the radiation burden from the combination of 2D plus 3D acquisitions. Methods The Screening with Tomosynthesis Or standard Mammography-2 (STORM-2) study was a prospective population-based screening study comparing integrated 3D mammography (dual-acquisition 2D–3D mammography or 2D synthetic–3D mammography) with 2D mammography alone. Asymptomatic women aged 49 years or older who attended population-based screening in Trento, Italy were recruited for the study. All participants underwent digital mammography with 2D and 3D mammography acquisitions, with the use of software that allowed synthetic 2D mammographic images to be reconstructed from 3D acquisitions. Mammography screen-reading was done in two parallel double-readings conducted sequentially for 2D acquisitions followed by integrated acquisitions. Recall based on a positive mammography result was defined as recall at any screen read. Primary outcome measures were a comparison between integrated (2D–3D or 2D synthetic–3D) mammography and 2D mammography alone of the number of cases of screen-detected breast cancer, the cancer detection rate per 1000 screens, the incremental cancer detection rate, and the number and percentage of false-positive recalls. Findings Between May 31, 2013, and May 29, 2015, 10 255 women were invited to participate, of whom 9672 agreed to participate and were screened. In these 9672 participants (median age 58 years [IQR 53–63]), screening detected 90 cases of breast cancer, including 74 invasive breast cancers, in 85 women (five women had bilateral breast cancer). To account for these bilateral cancers in cancer detection rate estimates, the number of screens used for analysis was 9677. Both 2D–3D mammography (cancer detection rate 8·5 per 1000 screens [82 cancers detected in 9677 screens]; 95% CI 6·7–10·5) and 2D synthetic–3D mammography (8·8 per 1000 [85 in 9677]; 7·0–10·8) had significantly higher rates of breast cancer detection than 2D mammography alone (6·3 per 1000 [61 in 9677], 4·8–8·1; p Interpretation Integration of 3D mammography (2D–3D or 2D synthetic–3D) detected more cases of breast cancer than 2D mammography alone, but increased the percentage of false-positive recalls in sequential screen-reading. These results should be considered in the context of the trade-off between benefits and harms inherent in population breast cancer screening, including that significantly increased breast cancer detection from integrating 3D mammography into screening has the potential to augment screening benefit and also possibly contribute to overdiagnosis. Funding None.

214 citations


Journal ArticleDOI
TL;DR: Cancer detection rate with US is comparable with mammography, with a greater proportion of invasive and node-negative cancers among US detections and False positives are more common with US screening.
Abstract: BACKGROUND Mammography is not widely available in all countries, and breast cancer incidence is increasing. We considered performance characteristics using ultrasound (US) instead of mammography to screen for breast cancer. METHODS Two thousand eight hundred nine participants were enrolled at 20 sites in the United States, Canada, and Argentina in American College of Radiology Imaging 6666. Two thousand six hundred sixty-two participants completed three annual screens (7473 examinations) with US and film-screen (n = 4351) or digital (n = 3122) mammography and had biopsy or 12-month follow-up. Cancer detection, recall, and positive predictive values were determined. All statistical tests were two-sided. RESULTS One hundred ten women had 111 breast cancer events: 89 (80.2%) invasive cancers, median size 12 mm. The number of US screens to detect one cancer was 129 (95% bootstrap confidence interval [CI] = 110 to 156), and for mammography 127 (95% CI = 109 to 152). Cancer detection was comparable for each of US and mammography at 58 of 111 (52.3%) vs 59 of 111 (53.2%, P = .90), with US-detected cancers more likely invasive (53/58, 91.4%, median size 12 mm, range = 2-40 mm), vs mammography at 41 of 59 (69.5%, median size 13 mm, range = 1-55 mm, P < .001). Invasive cancers detected by US were more frequently node-negative, 34 of 53 (64.2%) vs 18 of 41 (43.9%) by mammography (P = .003). For 4814 incidence screens (years 2 and 3), US had higher recall and biopsy rates and lower PPV of biopsy (PPV3) than mammography: The recall rate was 10.7% (n = 515) vs 9.4% (n = 453, P = .03), the biopsy rate was 5.5% (n = 266) vs 2.0% (n = 97, P < .001), and PPV3 was 11.7% (31/266) vs 38.1% (37/97, P < .001). CONCLUSIONS Cancer detection rate with US is comparable with mammography, with a greater proportion of invasive and node-negative cancers among US detections. False positives are more common with US screening.

191 citations


Journal ArticleDOI
TL;DR: Digital breast tomosynthesis screening outcomes are sustainable, with significant recall reduction, increasing cancer cases per recalled patients, and a decline in interval cancers.
Abstract: Importance Breast cancer screening with digital breast tomosynthesis (DBT) combined with digital mammography (DM) decreases false-positive examinations and increases cancer detection compared with screening with DM alone. However, the longitudinal performance of DBT screening is unknown. Objectives To determine whether the improved outcomes observed after initial implementation of DBT screening are sustainable over time at a population level and to evaluate the effect of more than 1 DBT screening at the individual level. Design, Setting, and Participants Retrospective analysis of screening mammography metrics was performed for all patients presenting for screening mammography in an urban, academic breast center during 4 consecutive years (DM, year 0; DBT, years, 1-3). The study was conducted from September 1, 2010, to September 30, 2014 (excluding September 2011, which was the transition period from DM to DBT), for a total of 44 468 screening events attributable to a total of 23 958 unique women. Differences in screening outcomes between each DBT year and the DM year, as well as between groups of women with only 1, 2, or 3 DBT screenings, were assessed, and the odds of recall adjusted for age, race/ethnicity, breast density, and prior mammograms were estimated. Data analysis was performed between February 16 and October 26, 2015. Exposure Digital mammography screening supplemented with DBT. Main Outcomes and Measures Recall rates, cancer cases per recalled patients, and biopsy and interval cancer rates were determined. Results Screening outcome metrics were evaluated for a total of 44 468 examinations attributable to 23 958 unique women (mean [SD] age, 56.8 [11.0] years) over a 4-year period: year 0 cohort (DM0), 10 728 women; year 1 cohort (DBT1), 11 007; year 2 cohort (DBT2), 11 157; and year 3 cohort (DBT3), 11 576. Recall rates rose slightly for years 1 to 3 of DBT (88, 90, and 92 per 1000 screened, respectively) but remained significantly reduced compared with the DM0 rate of 104 per 1000 screened. Reported as odds ratios (95% CIs), the findings were DM vs DBT1, 0.83 (0.76-0.91, P P P = .003). The cancer cases per recalled patients continued to rise from DM0 rate of 4.4% to 6.2% ( P = .06), 6.5% ( P = .03), and 6.7% ( P = .02) for years 1 to 3 of DBT, respectively. Outcomes assessed for the most recent screening for individual women undergoing only 1, 2, or 3 DBT screenings during the study period demonstrated decreasing recall rates of 130, 78, and 59 per 1000 screened, respectively ( P Conclusions and Relevance Digital breast tomosynthesis screening outcomes are sustainable, with significant recall reduction, increasing cancer cases per recalled patients, and a decline in interval cancers.

Journal ArticleDOI
TL;DR: The American Cancer Society (ACS) 2003 breast cancer screening guideline for women at average risk for breast cancer was updated by the American Medical Association (AMA) as discussed by the authors, and a supplemental analysis of mammography registry data was conducted to address questions related to the screening interval.
Abstract: Importance Breast cancer is a leading cause of premature mortality among US women. Early detection has been shown to be associated with reduced breast cancer morbidity and mortality. Objective To update the American Cancer Society (ACS) 2003 breast cancer screening guideline for women at average risk for breast cancer. Process The ACS commissioned a systematic evidence review of the breast cancer screening literature to inform the update and a supplemental analysis of mammography registry data to address questions related to the screening interval. Formulation of recommendations was based on the quality of the evidence and judgment (incorporating values and preferences) about the balance of benefits and harms. Evidence Synthesis Screening mammography in women aged 40 to 69 years is associated with a reduction in breast cancer deaths across a range of study designs, and inferential evidence supports breast cancer screening for women 70 years and older who are in good health. Estimates of the cumulative lifetime risk of false-positive examination results are greater if screening begins at younger ages because of the greater number of mammograms, as well as the higher recall rate in younger women. The quality of the evidence for overdiagnosis is not sufficient to estimate a lifetime risk with confidence. Analysis examining the screening interval demonstrates more favorable tumor characteristics when premenopausal women are screened annually vs biennially. Evidence does not support routine clinical breast examination as a screening method for women at average risk. Recommendations The ACS recommends that women with an average risk of breast cancer should undergo regular screening mammography starting at age 45 years (strong recommendation). Women aged 45 to 54 years should be screened annually (qualified recommendation). Women 55 years and older should transition to biennial screening or have the opportunity to continue screening annually (qualified recommendation). Women should have the opportunity to begin annual screening between the ages of 40 and 44 years (qualified recommendation). Women should continue screening mammography as long as their overall health is good and they have a life expectancy of 10 years or longer (qualified recommendation). The ACS does not recommend clinical breast examination for breast cancer screening among average-risk women at any age (qualified recommendation). Conclusions and Relevance These updated ACS guidelines provide evidence-based recommendations for breast cancer screening for women at average risk of breast cancer. These recommendations should be considered by physicians and women in discussions about breast cancer screening.

Journal ArticleDOI
TL;DR: The Adjunct Screening With Tomosynthesis or Ultrasound in Women With Mammography-Negative Dense Breasts' interim analysis shows that ultrasound has better incremental BC detection than tomosynthesis in mammography-negative dense breasts at a similar FP-recall rate.
Abstract: PurposeDebate on adjunct screening in women with dense breasts has followed legislation requiring that women be informed about their mammographic density and related adjunct imaging. Ultrasound or tomosynthesis can detect breast cancer (BC) in mammography-negative dense breasts, but these modalities have not been directly compared in prospective trials. We conducted a trial of adjunct screening to compare, within the same participants, incremental BC detection by tomosynthesis and ultrasound in mammography-negative dense breasts.Patients and MethodsAdjunct Screening With Tomosynthesis or Ultrasound in Women With Mammography-Negative Dense Breasts is a prospective multicenter study recruiting asymptomatic women with mammography-negative screens and dense breasts. Eligible women had tomosynthesis and physician-performed ultrasound with independent interpretation of adjunct imaging. Outcome measures included cancer detection rate (CDR), number of false-positive (FP) recalls, and incremental CDR for each moda...

Posted Content
TL;DR: This work presents how Convolutional Neural Networks can be used to directly classify pre-segmented breast masses in mammograms as benign or malignant, using a combination of transfer learning, careful pre-processing and data augmentation to overcome limited training data.
Abstract: Mammography is the most widely used method to screen breast cancer. Because of its mostly manual nature, variability in mass appearance, and low signal-to-noise ratio, a significant number of breast masses are missed or misdiagnosed. In this work, we present how Convolutional Neural Networks can be used to directly classify pre-segmented breast masses in mammograms as benign or malignant, using a combination of transfer learning, careful pre-processing and data augmentation to overcome limited training data. We achieve state-of-the-art results on the DDSM dataset, surpassing human performance, and show interpretability of our model.

Journal ArticleDOI
TL;DR: A microwave imaging system has been developed as a clinical diagnostic tool operating in the 3- to 8-GHz region using multistatic data collection, and images show the location of the strongest signal, and this corresponded in both older and younger women.
Abstract: A microwave imaging system has been developed as a clinical diagnostic tool operating in the 3- to 8-GHz region using multistatic data collection. A total of 86 patients recruited from a symptomatic breast care clinic were scanned with a prototype design. The resultant three-dimensional images have been compared "blind" with available ultrasound and mammogram images to determine the detection rate. Images show the location of the strongest signal, and this corresponded in both older and younger women, with sensitivity of [Formula: see text], which was found to be maintained in dense breasts. The pathway from clinical prototype to clinical evaluation is outlined.

Journal ArticleDOI
TL;DR: In this article, the authors used a logistic regression model to compare digital breast tomosynthesis (DBT) and digital mammography (DM) for breast cancer screening and found that DBT showed a statistically significant increase in cancer detection over DM (5.9 vs. 4.4 %, p < 0.0001) and no significant difference in false negative rates for DBT compared to DM.
Abstract: Digital breast tomosynthesis (DBT) is emerging as the new standard of care for breast cancer screening based on improved cancer detection coupled with reductions in recall compared to screening with digital mammography (DM) alone. However, many prior studies lack follow-up data to assess false negatives examinations. The purpose of this study is to assess if DBT is associated with improved screening outcomes based on follow-up data from tumor registries or pathology. Retrospective analysis of prospective cohort data from three research centers performing DBT screening in the PROSPR consortium from 2011 to 2014 was performed. Recall and biopsy rates were assessed from 198,881 women age 40-74 years undergoing screening (142,883 DM and 55,998 DBT examinations). Cancer, cancer detection, and false negative rates and positive predictive values were assessed on examinations with one year of follow-up. Logistic regression was used to compare DBT to DM adjusting for research center, age, prior breast imaging, and breast density. There was a reduction in recall with DBT compared to DM (8.7 vs. 10.4 %, p < 0.0001), with adjusted OR = 0.68 (95 % CI = 0.65-0.71). DBT demonstrated a statistically significant increase in cancer detection over DM (5.9 vs. 4.4/1000 screened, adjusted OR = 1.45, 95 % CI = 1.12-1.88), an improvement in PPV1 (6.4 % for DBT vs. 4.1 % for DM, adjusted OR = 2.02, 95 % CI = 1.54-2.65), and no significant difference in false negative rates for DBT compared to DM (0.46 vs. 0.60/1000 screened, p = 0.347). Our data support implementation of DBT screening based on increased cancer detection, reduced recall, and no difference in false negative screening examinations.

Journal ArticleDOI
TL;DR: In this paper, an analysis of registry data, conducted to inform the new recommendation on breast cancer screening from the USPSTF, describes rates of false positive and false negative results among U.S. women.
Abstract: This analysis of registry data, conducted to inform the new recommendation on breast cancer screening from the USPSTF, describes rates of false-positive and false-negative results among U.S. women ...

Journal ArticleDOI
TL;DR: The clinical results on functional properties of malignant and benign breast lesions compared to host tissue are reviewed and the various methods to improve contrast between healthy and diseased tissue are discussed, such as enhanced spectroscopic information, dynamic variations of functional properties, and pharmacokinetics of extrinsic contrast agents.
Abstract: Diffuse optical imaging and spectroscopy of the female breast is an area of active research. We review the present status of this field and discuss the broad range of methodologies and applications. Starting with a brief overview on breast physiology, the remodeling of vasculature and extracellular matrix caused by solid tumors is highlighted that is relevant for contrast in optical imaging. Then, the various instrumental techniques and the related methods of data analysis and image generation are described and compared including multimodality instrumentation, fluorescence mammography, broadband spectroscopy, and diffuse correlation spectroscopy. We review the clinical results on functional properties of malignant and benign breast lesions compared to host tissue and discuss the various methods to improve contrast between healthy and diseased tissue, such as enhanced spectroscopic information, dynamic variations of functional properties, pharmacokinetics of extrinsic contrast agents, including the enhanced permeability and retention effect. We discuss research on monitoring neoadjuvant chemotherapy and on breast cancer risk assessment as potential clinical applications of optical breast imaging and spectroscopy. Moreover, we consider new experimental approaches, such as photoacoustic imaging and long-wavelength tissue spectroscopy.

Journal ArticleDOI
TL;DR: The addition of 3D ABUS to FFDSM in women with ACR3 or ACR4 breast density significantly improved invasive breast cancer detection rate with an acceptable recall increase.

Journal ArticleDOI
TL;DR: 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, which could have substantial effects on clinical practice patterns.
Abstract: 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.

Journal ArticleDOI
TL;DR: A review of recent advances in microwave imaging for breast cancer detection is presented and new research on a microwave imaging system with time-domain measurement that achieves short measurement time and low system cost is introduced.
Abstract: Breast cancer is a disease that occurs most often in female cancer patients. Early detection can significantly reduce the mortality rate. Microwave breast imaging, which is noninvasive and harmless to human, offers a promising alternative method to mammography. This paper presents a review of recent advances in microwave imaging for breast cancer detection. We conclude by introducing new research on a microwave imaging system with time-domain measurement that achieves short measurement time and low system cost. In the time-domain measurement system, scan time would take less than 1 sec, and it does not require very expensive equipment such as VNA.

Book ChapterDOI
21 Oct 2016
TL;DR: Preliminary experimental results show the high accuracy and efficiency obtained by the suggested network structure, and as the volume and complexity of data in healthcare continues to accelerate generalizing such an approach may have a profound impact on patient care in many applications.
Abstract: This paper addresses the problem of detection and classification of tumors in breast mammograms. We introduce a novel system that integrates several modules including a breast segmentation module and a fibroglandular tissue segmentation module into a modified cascaded region-based convolutional network. The method is evaluated on a large multi-center clinical dataset and compared to ground truth annotated by expert radiologists. Preliminary experimental results show the high accuracy and efficiency obtained by the suggested network structure. As the volume and complexity of data in healthcare continues to accelerate generalizing such an approach may have a profound impact on patient care in many applications.

Journal ArticleDOI
TL;DR: Digital breast tomosynthesis has the potential to increase sensitivity and decrease false-positive recall rates, and there are issues with DBT as a screening tool including additional reading time, IT storage and connectivity, over-diagnosis, and cost effectiveness.

Journal ArticleDOI
TL;DR: The advancing role of mammographic texture analysis is reviewed as a potential novel approach to characterize the breast parenchymal tissue to augment conventional density assessment in breast cancer risk estimation.
Abstract: The assessment of a woman’s risk for developing breast cancer has become increasingly important for establishing personalized screening recommendations and forming preventive strategies. Studies have consistently shown a strong relationship between breast cancer risk and mammographic parenchymal patterns, typically assessed by percent mammographic density. This paper will review the advancing role of mammographic texture analysis as a potential novel approach to characterize the breast parenchymal tissue to augment conventional density assessment in breast cancer risk estimation. The analysis of mammographic texture provides refined, localized descriptors of parenchymal tissue complexity. Currently, there is growing evidence in support of textural features having the potential to augment the typically dichotomized descriptors (dense or not dense) of area or volumetric measures of breast density in breast cancer risk assessment. Therefore, a substantial research effort has been devoted to automate mammographic texture analysis, with the aim of ultimately incorporating such quantitative measures into breast cancer risk assessment models. In this paper, we review current and emerging approaches in this field, summarizing key methodological details and related studies using novel computerized approaches. We also discuss research challenges for advancing the role of parenchymal texture analysis in breast cancer risk stratification and accelerating its clinical translation. The objective is to provide a comprehensive reference for researchers in the field of parenchymal pattern analysis in breast cancer risk assessment, while indicating key directions for future research.

Journal ArticleDOI
TL;DR: Screening with s2D/ DBT in a large urban practice resulted in similar outcomes compared with digital mammography/DBT imaging, and allowed for the benefits of DBT with a decrease in radiation dose compared withdigital mammography /DBT.
Abstract: Purpose To evaluate the early implementation of synthesized two-dimensional (s2D) mammography in a population screened entirely with s2D and digital breast tomosynthesis (DBT) (referred to as s2D/DBT) and compare recall rates and cancer detection rates to historic outcomes of digital mammography combined with DBT (referred to as digital mammography/DBT) screening. Materials and Methods This was an institutional review board-approved and HIPAA-compliant retrospective interpretation of prospectively acquired data with waiver of informed consent. Compared were recall rates, biopsy rates, cancer detection rates, and radiation dose for 15 571 women screened with digital mammography/DBT from October 1, 2011, to February 28, 2013, and 5366 women screened with s2D/DBT from January 7, 2015, to June 30, 2015. Two-sample z tests of equal proportions were used to determine statistical significance. Results Recall rate for s2D/DBT versus digital mammography/DBT was 7.1% versus 8.8%, respectively (P < .001). Biopsy rate for s2D/DBT versus digital mammography/DBT decreased (1.3% vs 2.0%, respectively; P = .001). There was no significant difference in cancer detection rate for s2D/DBT versus digital mammography/DBT (5.03 of 1000 vs 5.45 of 1000, respectively; P = .72). The average glandular dose was 39% lower in s2D/DBT versus digital mammography/DBT (4.88 mGy vs 7.97 mGy, respectively; P < .001). Conclusion Screening with s2D/DBT in a large urban practice resulted in similar outcomes compared with digital mammography/DBT imaging. Screening with s2D/DBT allowed for the benefits of DBT with a decrease in radiation dose compared with digital mammography/DBT. © RSNA, 2016 An earlier incorrect version of this article appeared online. This article was corrected on August 11, 2016.

Journal ArticleDOI
TL;DR: Implementing DBT into a U.S. breast cancer screening program significantly decreased the screening RR overall and for certain patient subgroups, while significantly increasing the CDR.
Abstract: This prospective internally funded investigation demonstrates that the addition of digital breast tomosynthesis to a two-dimensional mammography screening program in a U.S. academic medical center resulted in a significant increase in the cancer detection rate, as well as a decrease in the screening recall rate overall and for patients with heterogeneous or extremely dense breasts and for patients in their 5th or 7th decades.

Journal ArticleDOI
TL;DR: The ACR Appropriateness Criteria as discussed by the authors are evidence-based guidelines for specific clinical conditions that are reviewed every 2 years by a multidisciplinary expert panel and used to recommend imaging or treatment.
Abstract: Mammography is the recommended method for breast cancer screening of women in the general population. However, mammography alone does not perform as well as mammography plus supplemental screening in high-risk women. Therefore, supplemental screening with MRI or ultrasound is recommended in selected high-risk populations. Screening breast MRI is recommended in women at high risk for breast cancer on the basis of family history or genetic predisposition. Ultrasound is an option for those high-risk women who cannot undergo MRI. Recent literature also supports the use of breast MRI in some women of intermediate risk, and ultrasound may be an option for intermediate-risk women with dense breasts. There is insufficient evidence to support the use of other imaging modalities, such as thermography, breast-specific gamma imaging, positron emission mammography, and optical imaging, for breast cancer screening. The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed every 2 years by a multidisciplinary expert panel. The guideline development and review includes an extensive analysis of current medical literature from peer-reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances in which evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.

Journal ArticleDOI
TL;DR: Unenhanced diagnostic MR imaging (DWIBS mammography), with an NPV of 0.92 and an acquisition time of less than 7 minutes, could help exclude malignancy in women with suspicious x-ray screening mammograms and has the potential to reduce unnecessary invasive procedures and emotional distress for breast cancer screening participants.
Abstract: Diagnostic MR imaging (diffusion-weighted imaging with background suppression) can reveal false-positive x-ray screening mammography findings before biopsy, yielding a negative predictive value of 0.92 (95% confidence interval: 0.75, 0.99) and, if used as a complement after x-ray mammography, could help reduce unnecessary invasive procedures and emotional distress for breast cancer screening participants.

Journal ArticleDOI
02 Aug 2016-PLOS ONE
TL;DR: In this paper, the authors performed a systematic review and meta-analysis of peer-reviewed studies in PubMed from 1/01/1986 until 06/15/2015, evaluating the performance of MRI for diagnosis of breast cancer in non-calcified equivocal breast findings.
Abstract: Objectives To evaluate the performance of MRI for diagnosis of breast cancer in non-calcified equivocal breast findings. Materials and Methods We performed a systematic review and meta-analysis of peer-reviewed studies in PubMed from 01/01/1986 until 06/15/2015. Eligible were studies applying dynamic contrast-enhanced breast MRI as an adjunct to conventional imaging (mammography, ultrasound) to clarify equivocal findings without microcalcifications. Reference standard for MRI findings had to be established by histopathological sampling or imaging follow-up of at least 12 months. Number of true or false positives and negatives and other characteristics were extracted, and possible bias was determined using the QUADAS-2 applet. Statistical analyses included data pooling and heterogeneity testing. Results Fourteen out of 514 studies comprising 2,316 lesions met our inclusion criteria. Pooled diagnostic parameters were: sensitivity (99%, 95%-CI: 93–100%), specificity (89%, 95%-CI: 85–92%), PPV (56%, 95%-CI: 42–70%) and NPV (100%, 95%-CI: 99–100%). These estimates displayed significant heterogeneity (P<0.001). Conclusions Breast MRI demonstrates an excellent diagnostic performance in case of non-calcified equivocal breast findings detected in conventional imaging. However, considering the substantial heterogeneity with regard to prevalence of malignancy, problem solving criteria need to be better defined.

Journal ArticleDOI
TL;DR: CESM has a high sensitivity but very low specificity and high-quality studies are required to assess the accuracy of CESM in unselected cases.