Explanipedia

Interplay of BMI and volumetric breast density measures and breast cancer risk for black and white women Open

Mattia A. Mahmoud, Stacey J. Winham, Christopher G. Scott, Sarah Ehsan, Aaron D. Norman , et al. · 2025

Background Black women have lower Breast Imaging Reporting and Data System (BI-RADS) breast density than White women, likely due to body mass index (BMI) differences. No studies have directly compared BMI, race, and volumetric breast densi…

Dynamic AI-assisted ipsilateral tissue matching for digital breast tomosynthesis Open

Stephen Morrell, Michael Hütel, Oeslle Lucena, Cristina Alfaro Vergara, Georgiana Zamfir , et al. · 2025

AI-assisted tissue matching significantly improved localization accuracy, especially for non- expert readers and in complex cases. The AI warning system effectively identified high-uncertainty cases. Errors were reduced to within typical t…

Racial Differences in Screening Eligibility by Breast Density After State-Level Insurance Expansion Open

Mattia A. Mahmoud, Sarah Ehsan, Sara P. Ginzberg, Susan M. Domchek, Katherine L. Nathanson , et al. · 2025

Importance Women with dense breasts have elevated risk of false-negative mammograms and may benefit from supplemental screening. Objective To assess potential outcomes of Pennsylvania’s law mandating insurance coverage for supplemental bre…

Comparison of Digital Breast Tomosynthesis and Mammography-based Radiomics for Breast Cancer Risk Assessment: Case-Control Study Open

Alex Nguyen, Eric A. Cohen, Omid Haji Maghsoudi, Raymond J. Acciavatti, Lauren Pantalone , et al. · 2025

Three-dimensional radiomic analysis of digital breast tomosynthesis outperformed two-dimensional measures in breast cancer risk assessment.

miRNA panel from HER2+ and CD24+ plasma extracellular vesicle subpopulations as biomarkers of early-stage breast cancer Open

Griffin B. Spychalski, Andrew A. Lin, Sheau‐Fang Yang, Hanfei Shen, J. Fernando del Rosario , et al. · 2025

Background Mammography screening has improved early breast cancer detection, leading to reduced mortality and lower rates of advanced breast cancer. However, mammography has a high false positive rate that results in over a million invasiv…

Dynamic AI-assisted Ipsilateral Tissue Matching for Digital Breast Tomosynthesis Open

Stephen Morrell, Michael Hütel, Oeslle Lucena, Cristina Alfaro Vergara, Georgiana Zamfir , et al. · 2024

Structured Abstract Purpose To compare Digital Breast Tomosynthesis (DBT) tissue matching errors with and without artificial intelligence (AI) assistance to typical screen-detected breast tumor sizes, evaluating whether AI ameliorates lesi…

Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep Learning Open

Vinayak S. Ahluwalia, Nehal Doiphode, Walter C. Mankowski, Eric A. Cohen, Sarthak Pati , et al. · 2024

PURPOSE Breast density is a widely established independent breast cancer risk factor. With the increasing utilization of digital breast tomosynthesis (DBT) in breast cancer screening, there is an opportunity to estimate volumetric breast d…

Feasibility of risk assessment for breast cancer molecular subtypes Open

Anne Marie McCarthy, Sarah Ehsan, Kevin S. Hughes, Constance D. Lehman, Emily F. Conant , et al. · 2024

Providing optimal care in the neonatal care units in India: How Covid-19 exacerbated existing barriers Open

Lisa J. Messersmith, Cherryl Kolhe, Alyana Z. Ladha, Prabir Das, Sowmya R. Rao , et al. · 2024

Nearly one quarter (600,000) of all neonatal deaths worldwide per year occur in India. To reduce neonatal mortality, the Indian Ministry of Health and Family Welfare established neonatal care units, including neonatal intensive care units …

Protocol for a pragmatic stepped wedge cluster randomized clinical trial testing behavioral economic implementation strategies to increase supplemental breast MRI screening among patients with extremely dense breasts Open

Anne Marie McCarthy, Claudia Fernandez Perez, Rinad S. Beidas, Justin E. Bekelman, Daniel Blumenthal , et al. · 2023

Background Increased breast density augments breast cancer risk and reduces mammography sensitivity. Supplemental breast MRI screening can significantly increase cancer detection among women with dense breasts. However, few women undergo t…

Can AI Reduce the Harms of Screening Mammography? Open

Elizabeth S. McDonald, Emily F. Conant · 2023

NCCN Guidelines® Insights: Breast Cancer Screening and Diagnosis, Version 1.2023 Open

Therese B. Bevers, Bethany L. Niell, Jennifer L. Baker, Debbie L. Bennett, Ermelinda Bonaccio , et al. · 2023

The NCCN Guidelines for Breast Cancer Screening and Diagnosis provide health care providers with a practical, consistent framework for screening and evaluating a spectrum of clinical presentations and breast lesions. The NCCN Breast Cancer…

Impact of super-resolution and image acquisition on the detection of calcifications in digital breast tomosynthesis Open

Bruno Barufaldi, Raymond J. Acciavatti, Emily F. Conant, Andrew D. A. Maidment · 2023

A Clinical Risk Model for Personalized Screening and Prevention of Breast Cancer Open

Mikael Eriksson, Kamila Czene, Celine M. Vachon, Emily F. Conant, Per Hall · 2023

Background: Image-derived artificial intelligence (AI) risk models have shown promise in identifying high-risk women in the short term. The long-term performance of image-derived risk models expanded with clinical factors has not been inve…

Breast density quantitative measures and breast cancer risk among screened Black women Open

Mattia A. Mahmoud, Sarah Ehsan, Lauren Pantalone, Walter C. Mankowski, Emily F. Conant , et al. · 2023

Mammographic density is a strong predictor of breast cancer but only slightly increased the discriminatory ability of existing risk prediction models in previous studies with limited racial diversity. We assessed discrimination and calibra…

Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis Open

Jung Hyun Yoon, Fredrik Strand, Pascal Baltzer, Emily F. Conant, Fiona J. Gilbert , et al. · 2023

Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used fo…

Supplementary Data from Imaging Phenotypes of Breast Cancer Heterogeneity in Preoperative Breast Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) Scans Predict 10-Year Recurrence Open

Rhea Chitalia, Jennifer Rowland, Elizabeth S. McDonald, Lauren Pantalone, Eric A. Cohen , et al. · 2023

Supplementary data includes appendix of extracted Radiomic features. Figure S1 shows a summary of patient characteristics. Figure S2 shows the radiomic analysis workflow. Figure S3 shows representative cases from heterogeneity phenotypes. …

Use of Artificial Intelligence for Digital Breast Tomosynthesis Screening: A Preliminary Real-world Experience Open

Haley Letter, Meridith Peratikos, Alicia Y. Toledano, Jeffrey W. Hoffmeister, Robert M. Nishikawa , et al. · 2023

Objective The purpose of this study is to assess the “real-world” impact of an artificial intelligence (AI) tool designed to detect breast cancer in digital breast tomosynthesis (DBT) screening exams following 12 months of utilization in a…

Data from Imaging Phenotypes of Breast Cancer Heterogeneity in Preoperative Breast Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) Scans Predict 10-Year Recurrence Open

Rhea Chitalia, Jennifer Rowland, Elizabeth S. McDonald, Lauren Pantalone, Eric A. Cohen , et al. · 2023

Purpose:Identifying imaging phenotypes and understanding their relationship with prognostic markers and patient outcomes can allow for a noninvasive assessment of cancer. The purpose of this study was to identify and validate intrinsic ima…

Supplementary Data from Imaging Phenotypes of Breast Cancer Heterogeneity in Preoperative Breast Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) Scans Predict 10-Year Recurrence Open

Rhea Chitalia, Jennifer Rowland, Elizabeth S. McDonald, Lauren Pantalone, Eric A. Cohen , et al. · 2023

Supplementary data includes appendix of extracted Radiomic features. Figure S1 shows a summary of patient characteristics. Figure S2 shows the radiomic analysis workflow. Figure S3 shows representative cases from heterogeneity phenotypes. …

Data from Imaging Phenotypes of Breast Cancer Heterogeneity in Preoperative Breast Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) Scans Predict 10-Year Recurrence Open

Rhea Chitalia, Jennifer Rowland, Elizabeth S. McDonald, Lauren Pantalone, Eric A. Cohen , et al. · 2023

Purpose:Identifying imaging phenotypes and understanding their relationship with prognostic markers and patient outcomes can allow for a noninvasive assessment of cancer. The purpose of this study was to identify and validate intrinsic ima…

Long-Term Performance of an Image-Based Short-Term Risk Model for Breast Cancer Open

Mikael Eriksson, Kamila Czene, Celine M. Vachon, Emily F. Conant, Per Hall · 2023

PURPOSE Image-derived artificial intelligence–based short-term risk models for breast cancer have shown high discriminatory performance compared with traditional lifestyle/familial-based risk models. The long-term performance of image-deri…

Beyond Breast Density: Risk Measures for Breast Cancer in Multiple Imaging Modalities Open

Raymond J. Acciavatti, Su Hyun Lee, Beatriu Reig, Linda Moy, Emily F. Conant , et al. · 2023

Breast density is an independent risk factor for breast cancer. In digital mammography and digital breast tomosynthesis, breast density is assessed visually using the four-category scale developed by the American College of Radiology Breas…

Obesity and metabolic dysfunction correlate with background parenchymal enhancement in premenopausal women Open

Justin C. Brown, Jennifer A. Ligibel, Tracy E. Crane, Despina Kontos, Shengping Yang , et al. · 2023

Objective This study tested the hypothesis that obesity and metabolic abnormalities correlate with background parenchymal enhancement (BPE), the volume and intensity of enhancing fibroglandular breast tissue on dynamic contrast‐enhanced ma…

Development of an Endoscopic Auto-Fluorescent Sensing Device to Aid in the Detection of Breast Cancer and Inform Photodynamic Therapy Open

Brandon Gaitan, Collin T. Inglut, Udayakumar Kanniyappan, He N. Xu, Emily F. Conant , et al. · 2022

Breast cancer is the most diagnosed cancer type in women, with it being the second most deadly cancer in terms of total yearly mortality. Due to the prevalence of this disease, better methods are needed for both detection and treatment. Re…

External Validation of a Mammography-Derived AI-Based Risk Model in a U.S. Breast Cancer Screening Cohort of White and Black Women Open

Aimilia Gastounioti, Mikael Eriksson, Eric A. Cohen, Walter C. Mankowski, Lauren Pantalone , et al. · 2022

Despite the demonstrated potential of artificial intelligence (AI) in breast cancer risk assessment for personalizing screening recommendations, further validation is required regarding AI model bias and generalizability. We performed exte…

Abbreviated Breast MRI Utilization: A Survey of the Society of Breast Imaging Open

Lars J. Grimm, Emily F. Conant, Vandana Dialani, Brian N. Dontchos, Jennifer A. Harvey , et al. · 2022

Objective To survey Society of Breast Imaging (SBI) membership on their use of abbreviated breast MRI to understand variability in practice patterns. Methods A survey was developed by the SBI Patient Care and Delivery committee for distrib…

Outcomes of COVID-19 Vaccination–Related Incidental Axillary Adenopathy in Women Undergoing Breast MRI Open

Samantha P. Zuckerman, Elizabeth S. McDonald, Susan P. Weinstein, J Birnbaum, Jennifer D. Tobey , et al. · 2022

Objective To assess the frequency, management, and early outcomes of COVID-19 vaccine–related adenopathy on breast MRI. Methods This IRB-exempt retrospective study reviewed patients who underwent breast MRI following COVID-19 vaccine appro…

MammoFL: Mammographic Breast Density Estimation using Federated Learning Open

Ramya Muthukrishnan, Angelina Heyler, Keshava Katti, Sarthak Pati, Walter C. Mankowski , et al. · 2022

In this study, we automate quantitative mammographic breast density estimation with neural networks and show that this tool is a strong use case for federated learning on multi-institutional datasets. Our dataset included bilateral CC-view…

A risk model for digital breast tomosynthesis to predict breast cancer and guide clinical care Open

Mikael Eriksson, Stamatia Destounis, Kamila Czene, Andrew Zeiberg, Robert W. Day , et al. · 2022

Screening with digital breast tomosynthesis (DBT) improves breast cancer detection and reduces false positives. However, currently, no breast cancer risk model takes advantage of the additional information generated by DBT imaging for brea…

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