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

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 density (VBD) routinely. However, current available methods extrapolate VBD from two-dimensional (2D) images acquired using DBT and/or depend on the existence of raw DBT data, which is rarely archived by clinical centers because of storage constraints.

Feasibility and Accuracy of Ultrasound-Guided Core Needle Biopsy for Nipple Lesions: A Pilot Study.

Background: Due to the superficial location, suspicious findings of the nipple-areolar complex (NAC) are not amenable to stereotactic or MRI-guided sampling and have historically necessitated surgical biopsy or skin-punch biopsy. There are limited reports of US-guided core biopsy of the nipple (US-CBN).

Objective: We report our nearly 3-year pilot experience with US-CBN at an academic breast imaging center.

Feasibility of risk assessment for breast cancer molecular subtypes.

Purpose: Few breast cancer risk assessment models account for the risk profiles of different tumor subtypes. This study evaluated whether a subtype-specific approach improves discrimination.

Methods: Among 3389 women who had a screening mammogram and were later diagnosed with invasive breast cancer we performed multinomial logistic regression with tumor subtype as the outcome and known breast cancer risk factors as predictors.

Racial Disparities and Strategies for Improving Equity in Diagnostic Follow-Up for Abnormal Screening Mammograms.

Purpose: Black and White women undergo screening mammography at similar rates, but racial disparities in breast cancer outcomes persist. To assess potential contributors, we investigated delays in follow-up after abnormal imaging by race/ethnicity.

Methods: Women who underwent screening mammography at our urban academic center from January 2015 to February 2018 and received a Breast Imaging Reporting and Data System 0 assessment were included.

Abbreviated Breast MRI for Supplemental Screening in Patients With Dense Breasts: Comparison of Baseline Versus Subsequent-Round Examinations.

Abbreviated breast MRI (AB-MRI) achieves a higher cancer detection rate (CDR) than digital breast tomosynthesis when applied for baseline (i.e., first-round) supplemental screening of individuals with dense breasts.

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

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 and specialized neonatal care units to provide immediate care at birth, resuscitation for asphyxiation, postnatal care, follow up for high-risk newborns, immunization, and referral for additional or complex healthcare services. Despite these efforts, neonatal mortality remains high, and measures taken to reduce mortality have been severely challenged by multiple problems caused by the Covid-19 pandemic.

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

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 subspecialized academic breast center.

Methods: Following IRB approval, mammography audit reports, as specified in the BI-RADS atlas, were retrospectively generated for five radiologists reading at three locations during a 12-month time frame. One location had the AI tool (iCAD ProFound AI v2.

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.

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 this exam, and screening is consistently lower among racially minoritized populations.

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

Objectives: A virtual clinical trial (VCT) method is proposed to determine the limit of calcification detection in tomosynthesis.

Methods: Breast anatomy, focal findings, image acquisition, and interpretation (n = 14 readers) were simulated using screening data (n = 660 patients). Calcifications (0.

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

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 investigated.

Methods: We performed a case-cohort study of 8110 women aged 40-74 randomly selected from a Swedish mammography screening cohort initiated in 2010 together with 1661 incident BCs diagnosed before January 2022.

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

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 calibration of models consisting of the Breast Cancer Risk Assessment Tool (BCRAT), Breast Imaging-Reporting and Data System density and quantitative density measures. Patients were followed up from the date of first screening mammogram until invasive breast cancer diagnosis or 5-year follow-up.

Pervasiveness of Open Journal Invitations Across Radiology Specialties.

This study examines the patterns of faculty solicitations by open-access (OA) publishers in radiology. The purpose of the research is to determine the factors that predict the likelihood of receiving such solicitations. We recruited 6 faculty members from 7 subspecialties in radiology to collect emails from OA journals for 2 weeks.

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

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-derived risk models has not been investigated.

Methods: We performed a case-cohort study of 8,604 randomly selected women within a mammography screening cohort initiated in 2010 in Sweden for women age 40-74 years.

Mammographic Screening in Routine Practice: Multisite Study of Digital Breast Tomosynthesis and Digital Mammography Screenings.

Background The use of digital breast tomosynthesis (DBT) is increasing over digital mammography (DM) following studies demonstrating lower recall rates (RRs) and higher cancer detection rates (CDRs). However, inconsistent interpretation of evidence on the risks and benefits of mammography has resulted in varying screening mammography recommendations. Purpose To evaluate screening outcomes among women in the United States who underwent routine DM or DBT mammographic screening.

Changes in mammographic density and risk of breast cancer among a diverse cohort of women undergoing mammography screening.

Purpose: Mammographic density (MD) is a strong breast cancer risk factor. MD may change over time, with potential implications for breast cancer risk. Few studies have assessed associations between MD change and breast cancer in racially diverse populations.

Mammographic Breast Density: Current Assessment Methods, Clinical Implications, and Future Directions.

Mammographic breast density is widely accepted as an independent risk factor for the development of breast cancer. In addition, because dense breast tissue may mask breast malignancies, breast density is inversely related to the sensitivity of screening mammography. Given the risks associated with breast density, as well as ongoing efforts to stratify individual risk and personalize breast cancer screening and prevention, numerous studies have sought to better understand the factors that impact breast density, and to develop and implement reproducible, quantitative methods to assess mammographic density.

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

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 Breast Imaging Reporting and Data System (5th edition as of November 2022). Epidemiologically based risk models, such as the Tyrer-Cuzick model (version 8), demonstrate superior modeling performance when mammographic density is incorporated.

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

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 magnetic resonance imaging.

Methods: Participants included 59 premenopausal women at high risk of breast cancer. Obesity was defined as BMI ≥ 30 kg/m .

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

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. Reduced nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) are autofluorescent biomarkers that lend insight into cell and tissue metabolism.

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

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 external validation on a U.S.

Opinions on the Assessment of Breast Density Among Members of the Society of Breast Imaging.

Objective: Dense breast decreases the sensitivity and specificity of mammography and is associated with an increased risk of breast cancer. We conducted a survey to assess the opinions of Society of Breast Imaging (SBI) members regarding density assessment.

Methods: An online survey was sent to SBI members twice in September 2020.

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

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 distribution to SBI membership in July and August 2021. Eighteen questions queried practice demographics and then abbreviated breast MRI practices regarding initial adoption, scheduling and finances, MRI protocols, and interpretations.