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IMPORTANCE: Digital breast tomosynthesis (DBT) is a breast cancer screening modality that has gained popularity in recent years. Although insurance coverage for DBT is not mandated under the Patient Protection and Affordable Care Act, several states have required coverage without cost sharing for private insurers. OBJECTIVE: To evaluate the association between state-level insurance coverage mandates for DBT and changes in DBT use, price, and out-of-pocket payments. DESIGN, SETTING, AND PARTICIPANTS: This cohort study used an event-study design with repeated cross-sectional observations of US states. Data were obtained from the Blue Cross Blue Shield Axis database for commercially insured women aged 40 to 64 years who underwent screening mammography between January 1, 2015, and June 30, 2019. Data were analyzed between January 14, 2021, and January 20, 2022. INTERVENTIONS: Passage of state-level legislation requiring insurance coverage of DBT. MAIN OUTCOMES AND MEASURES: Change in DBT use among women screened for breast cancer, overall DBT price, and out-of-pocket payments for DBT in states with mandates for coverage of DBT compared with states that did not pass legislation. RESULTS: This study included 9 604 084 screening mammograms from 5 754 123 women (mean [SD] age, of 53 [6.7] years). During the study period, 15 states enacted DBT coverage mandates and 34 states did not. In states with coverage mandates, DBT use increased by 9.0 percentage points (95% CI, 1.8-16.3 percentage points; P = .02) 2 years after the mandate compared with states without coverage mandates. Coverage mandates were also associated with a net $38.7 (95% CI, $13.4-$63.9; P = .003) decrease in the mean price of DBT compared with no coverage mandates. There was no association between coverage mandates and out-of-pocket payments 2 years after mandate passage ($–2.1; 95% CI, $–5.3 to $1.0; P = .18). CONCLUSIONS AND RELEVANCE: In this cohort study, DBT coverage mandates were associated with an increase in DBT use but not with any change in ...

Purpose Debate 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 Methods Adjunct 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 modality; these were compared using McNemar's test for paired binary data in a preplanned interim analysis.

This study contributes to social studies of imaging and visualization practices within scientific and medical settings. The focus is on practices in radiology, which are bound up with visual records known as radiographs. The study addresses work following the introduction of a new imaging technology, tomosynthesis. Since it was a novel technology, there was limited knowledge of how to correctly analyse tomosynthesis images. To address this problem, a collective review session was arranged. The purpose of the present study was to uncover the practical work that took place during that session and to show how, and on what basis, new methods, interpretations and understandings were being generated. The analysis displays how the diagnostic work on patients' bodies was grounded in two sets of technologically produced renderings. This shows how expertise is not simply a matter of providing correct explanations, but also involves discovery work in which visual renderings are made transparent. Furthermore, the results point to how the disciplinary knowledge is intertwined with timely actions, which in turn, partly rely on established practices of manipulating and comparing images. The embodied and situated reasoning that enabled radiologists to discern objects in the images thus display expertise as inherently practical and domain-specific.

Cover -- Title -- Copyright -- Contents -- Contributors -- Preface -- Share Handbook of Breast Cancer and Related Breast Disease -- Chapter 1: Breast Imaging: Breast Cancer Screening, Diagnosis, Staging, and Surveillance -- Introduction -- Indications for Breast Imaging -- Multimodality Breast Imaging -- Breast Imaging Reporting and Data System (BI-RADS) -- Breast Cancer Screening -- Mammography and Digital Breast Tomosynthesis -- Breast MRI -- Breast Ultrasound -- Diagnosis of Breast Diseases by Imaging -- Palpable Breast Lump -- Breast Pain -- Nipple Discharge -- Implant Abnormalities -- Image-Guided Breast Biopsies -- Type of Image-Guided Biopsy -- Type of Needle Biopsy -- Image-Guided Needle Localizations -- Radiologic-Pathologic Correlation -- Imaging Assessment After Breast Cancer Diagnosis -- Imaging Surveillance of Breast Cancer Survivors -- Management Pearls -- References -- Chapter 2: Management of High-Risk Breast Disease -- Introduction -- General Characteristics -- Workup -- Management -- Atypical Ductal Hyperplasia -- Histology -- Upgrade Rate -- Treatment -- Risk of Future Malignancy -- Atypical Lobular Hyperplasia -- Histology -- Upgrade Rate -- Treatment -- Risk of Future Malignancy -- Lobular Carcinoma In Situ -- Histology -- Upgrade Rate -- Treatment -- Risk of Future Malignancy -- Atypical Columnar Cell Change (Flat Epithelial Atypia) -- Histology -- Upgrade Rate -- Treatment -- Risk of Future Malignancy -- Intraductal Papillomas -- Histology -- Upgrade Rate -- Treatment -- Risk of Future Malignancy -- Chemoprevention -- Risk Reduction -- Selective Estrogen Receptor Modulators -- Aromatase Inhibitors -- Key Prevention Trials -- International Breast Cancer Intervention Study I (IBIS-I) -- National Surgical Adjuvant Breast and Bowel Project, Prevention-1 (NSABP P-1) -- Royal Marsden Trial

Virtual clinical trials (VCT) currently represent key tools for breast imaging optimisation, especially in two-dimensional planar mammography and digital breast tomosynthesis. Voxelised breast models are a crucial part of VCT as they allow the generation of synthetic image projections of breast tissue distribution. Therefore, realistic breast models containing an accurate representation of women breasts are needed. Current voxelised breast models show, in their compressed version, a very round contour which might not be representative of the entire population. This work pretends to develop an imaging framework, based on depth cameras, to investigate breast deformation during mammographic compression. Preliminary results show the feasibility of depth sensors for such task, however post-processing steps are needed to smooth the models. The proposed framework can be used in the future to produce more accurate compressed breast models, which will eventually generate more realistic images in VCT ; This work is part of the SCARtool project (H2020-MSCA-IF-2014, reference 657875), a research funded by the European Union within the Marie Sklodowska-Curie Innovative Training Networks. Also, some of the authors have been partially supported from the Ministry of Economy and Competitiveness of Spain, under project references TIN2012-37171-C02-01 and DPI2015-68442-R, and the FPI grant BES-2013-065314

Virtual clinical trials (VCT) currently represent key tools for breast imaging optimisation, especially in two-dimensional planar mammography and digital breast tomosynthesis. Voxelised breast models are a crucial part of VCT as they allow the generation of synthetic image projections of breast tissue distribution. Therefore, realistic breast models containing an accurate representation of women breasts are needed. Current voxelised breast models show, in their compressed version, a very round contour which might not be representative of the entire population. This work pretends to develop an imaging framework, based on depth cameras, to investigate breast deformation during mammographic compression. Preliminary results show the feasibility of depth sensors for such task, however post-processing steps are needed to smooth the models. The proposed framework can be used in the future to produce more accurate compressed breast models, which will eventually generate more realistic images in VCT ; This work is part of the SCARtool project (H2020-MSCA-IF-2014, reference 657875), a research funded by the European Union within the Marie Sklodowska-Curie Innovative Training Networks. Also, some of the authors have been partially supported from the Ministry of Economy and Competitiveness of Spain, under project references TIN2012-37171-C02-01 and DPI2015-68442-R, and the FPI grant BES-2013-065314

Virtual clinical trials (VCT) currently represent key tools for breast imaging optimisation, especially in two-dimensional planar mammography and digital breast tomosynthesis. Voxelised breast models are a crucial part of VCT as they allow the generation of synthetic image projections of breast tissue distribution. Therefore, realistic breast models containing an accurate representation of women breasts are needed. Current voxelised breast models show, in their compressed version, a very round contour which might not be representative of the entire population. This work pretends to develop an imaging framework, based on depth cameras, to investigate breast deformation during mammographic compression. Preliminary results show the feasibility of depth sensors for such task, however post-processing steps are needed to smooth the models. The proposed framework can be used in the future to produce more accurate compressed breast models, which will eventually generate more realistic images in VCT ; This work is part of the SCARtool project (H2020-MSCA-IF-2014, reference 657875), a research funded by the European Union within the Marie Sklodowska-Curie Innovative Training Networks. Also, some of the authors have been partially supported from the Ministry of Economy and Competitiveness of Spain, under project references TIN2012-37171-C02-01 and DPI2015-68442-R, and the FPI grant BES-2013-065314

Virtual clinical trials (VCT) currently represent key tools for breast imaging optimisation, especially in two-dimensional planar mammography and digital breast tomosynthesis. Voxelised breast models are a crucial part of VCT as they allow the generation of synthetic image projections of breast tissue distribution. Therefore, realistic breast models containing an accurate representation of women breasts are needed. Current voxelised breast models show, in their compressed version, a very round contour which might not be representative of the entire population. This work pretends to develop an imaging framework, based on depth cameras, to investigate breast deformation during mammographic compression. Preliminary results show the feasibility of depth sensors for such task, however post-processing steps are needed to smooth the models. The proposed framework can be used in the future to produce more accurate compressed breast models, which will eventually generate more realistic images in VCT ; This work is part of the SCARtool project (H2020-MSCA-IF-2014, reference 657875), a research funded by the European Union within the Marie Sklodowska-Curie Innovative Training Networks. Also, some of the authors have been partially supported from the Ministry of Economy and Competitiveness of Spain, under project references TIN2012-37171-C02-01 and DPI2015-68442-R, and the FPI grant BES-2013-065314

Virtual clinical trials (VCT) currently represent key tools for breast imaging optimisation, especially in two-dimensional planar mammography and digital breast tomosynthesis. Voxelised breast models are a crucial part of VCT as they allow the generation of synthetic image projections of breast tissue distribution. Therefore, realistic breast models containing an accurate representation of women breasts are needed. Current voxelised breast models show, in their compressed version, a very round contour which might not be representative of the entire population. This work pretends to develop an imaging framework, based on depth cameras, to investigate breast deformation during mammographic compression. Preliminary results show the feasibility of depth sensors for such task, however post-processing steps are needed to smooth the models. The proposed framework can be used in the future to produce more accurate compressed breast models, which will eventually generate more realistic images in VCT ; This work is part of the SCARtool project (H2020-MSCA-IF-2014, reference 657875), a research funded by the European Union within the Marie Sklodowska-Curie Innovative Training Networks. Also, some of the authors have been partially supported from the Ministry of Economy and Competitiveness of Spain, under project references TIN2012-37171-C02-01 and DPI2015-68442-R, and the FPI grant BES-2013-065314

Virtual clinical trials (VCT) currently represent key tools for breast imaging optimisation, especially in two-dimensional planar mammography and digital breast tomosynthesis. Voxelised breast models are a crucial part of VCT as they allow the generation of synthetic image projections of breast tissue distribution. Therefore, realistic breast models containing an accurate representation of women breasts are needed. Current voxelised breast models show, in their compressed version, a very round contour which might not be representative of the entire population. This work pretends to develop an imaging framework, based on depth cameras, to investigate breast deformation during mammographic compression. Preliminary results show the feasibility of depth sensors for such task, however post-processing steps are needed to smooth the models. The proposed framework can be used in the future to produce more accurate compressed breast models, which will eventually generate more realistic images in VCT ; This work is part of the SCARtool project (H2020-MSCA-IF-2014, reference 657875), a research funded by the European Union within the Marie Sklodowska-Curie Innovative Training Networks. Also, some of the authors have been partially supported from the Ministry of Economy and Competitiveness of Spain, under project references TIN2012-37171-C02-01 and DPI2015-68442-R, and the FPI grant BES-2013-065314

Front Cover -- Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images -- Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images -- Copyright -- Contents -- Contributors -- Preface -- 1 - Mammogram data analysis: Trends, challenges, and future directions -- 1. Introduction -- 1.1 Theoretical background -- 1.1.1 "Sick lobe" model -- 1.1.2 Neoductgenesis -- 1.2 Technical knowledge -- 1.3 BC diagnosis using several imaging modalities -- 1.3.1 Mammography -- 1.3.2 Ultrasound -- 1.3.3 MRI -- 1.3.4 Histopathology -- 1.3.5 Thermography -- 1.4 Risk factors -- 1.5 Advantages in mammography -- 2. Related works -- 2.1 Microcalcification detection -- 2.2 Classification of mass -- 2.3 Feature-based BC detection -- 2.4 Computer-aided mammography -- 2.5 Database for mammogram images -- 2.5.1 INbreast -- 2.5.2 CBIS-DDSM -- 2.5.3 Image retrieval in medical applications -- 2.5.4 Mammographic Image Analysis Society -- 2.5.5 Breast cancer digital repository -- 2.5.6 BancoWeb LAPIMO -- 2.5.7 UCHC DigiMammo -- 3. Current trends in mammography analysis -- 3.1 Full field digital mammography -- 3.2 Digital mammography -- 3.2.1 Computed tomography electro-optical tomographic laser mammography -- 3.3 Scintimammography -- 3.4 Optical mammography -- 3.5 Digital breast tomosynthesis -- 3.6 Future of DBT imaging -- 4. Challenges in mammogram data analysis -- 4.1 General challenges in BC measurement and analysis -- 4.1.1 Shortcomings in primary care -- 4.1.2 Public secondary healthcare clinic mammography concerns -- 4.1.3 A gap between the BC detection strategy for primary care and secondary -- 4.1.4 Potential risks of mammography -- 4.1.5 Physical and mental suffering -- 4.1.6 Biopsies -- 4.2 Obstacles to data analytics in BC -- 4.2.1 Personal encounters and obstacles to obtaining assistance.

OBJECTIVE: Breast density notification laws are increasingly common, but little is known of how they affect supplemental screening use. We investigated supplemental screening before and after density notification in North Carolina, where notification has been required since 2014. METHODS: We evaluated breast screening data from Carolina Mammography Registry participants aged 40-79 years with no personal history of breast cancer or breast implants. Supplemental screening was defined as a non-diagnostic digital breast tomosynthesis (DBT), whole breast ultrasound, or breast magnetic resonance imaging examination performed within three months of a negative or benign screening mammogram (2-D or DBT). Supplemental screening before (2012-2013) and after (2014-2016) the notification law was compared using logistic regression. RESULTS: During the study period, 78,967 women received 145,279 index screening mammograms. Supplemental screening use was similar before and after the notification law, regardless of breast density (dense breasts, adjusted odds ratio [aOR] 1.01, 95% confidence interval [CI] 0.58, 1.75; non-dense breasts, aOR 0.63, 95% CI 0.38, 1.04). Though there was no change in supplemental screening, new use of any screening DBT in 2014-2016 was greater for women with dense breasts (vs. non-dense breasts, aOR 1.15, 95% CI 1.08, 1.23). DISCUSSION: Data suggest that supplemental screening use in North Carolina did not change after enactment of a breast density notification law, though the increase in new use of any screening DBT was greater for women with dense breasts. The short-term lack of change in supplemental screening should be considered as additional notification laws are developed.

Objective: Despite the lack of evidence that supplemental screening in women with dense breasts reduces breast cancer mortality, 38 states have passed breast density legislation, with some including recommendations for supplemental screening. The objective of this study is to compare the availability versus use of supplemental breast cancer screening modalities and determine factors driving use of supplemental screening in rural versus urban settings. Methods: A 50-item mailed survey using the Tailored Design Method was sent to American College of Radiology mammography-accredited facilities in North Carolina in 2017. Respondents included 94 facilities (48 rural and 46 urban locations). Survey questions focused on breast cancer and supplemental screening services, breast density, risk factors/assessment, and facility demographics. Results: The survey response rate was 60.3% (94/156). Among the 94 respondents, 64.0% (n = 60) reported availability of any type of supplemental screening (digital breast tomosynthesis [DBT], ultrasound, or magnetic resonance imaging [MRI]). In facilities where supplemental screening modalities were available, the most commonly utilized supplemental screening modality was DBT (96.4%), compared with ultrasound (35.7%) and MRI (46.7%). Facilities reported using supplemental screening based on patient breast density (48.3%), referring physician recommendation (63.3%), reading radiologist recommendation (63.3%), breast cancer risk factors (48.3%), and patient request (40.0%). Urban facilities were more likely than rural facilities to base supplemental screening on breast cancer risk factors (62.5% vs. 32.1%; p-value = 0.019), referring physician (75.0% vs. 50.0%; p-value = 0.045), and reading radiologist (78.1% vs. 46.4%; p-value = 0.011). Conclusion: In our study, supplemental screening modalities were widely available, with facilities more likely to use DBT for supplemental screening compared to other modalities.