Framework for Successful Integration of Health Services Research Into a Breast Imaging Career.

Health services research (HSR) is a multidisciplinary field of inquiry that examines how health care is structured, providing valuable data on health care outcomes and delivery. Over the past few decades, a shift in the U.S.

Incidence, Timing, and Long-Term Outcomes of COVID-19 Vaccine-Related Lymphadenopathy on Screening Mammography.

Objective: To determine the incidence, timing, and long-term outcomes of unilateral axillary lymphadenopathy ipsilateral to vaccine site (UIAL) on screening mammography after COVID-19 vaccination.

Methods: This retrospective, multisite study included consecutive patients undergoing screening mammography February 8, 2021, to January 31, 2022, with at least 1 year of follow-up. UIAL was typically considered benign (BI-RADS 1 or 2) in the setting of recent (≤6 weeks) vaccination or BI-RADS 0 (ultrasound recommended) when accompanied by a breast finding or identified >6 weeks postvaccination.

Comparison of the Diagnostic Accuracy of Mammogram-based Deep Learning and Traditional Breast Cancer Risk Models in Patients Who Underwent Supplemental Screening with MRI.

Background Access to supplemental screening breast MRI is determined using traditional risk models, which are limited by modest predictive accuracy. Purpose To compare the diagnostic accuracy of a mammogram-based deep learning (DL) risk assessment model to that of traditional breast cancer risk models in patients who underwent supplemental screening with MRI. Materials and Methods This retrospective study included consecutive patients undergoing breast cancer screening MRI from September 2017 to September 2020 at four facilities.

Predicting ipsilateral recurrence in women treated for ductal carcinoma in situ using machine learning and multivariable logistic regression models.

Purpose: To develop machine learning (ML) and multivariable regression models to predict ipsilateral breast event (IBE) risk after ductal carcinoma in situ (DCIS) treatment.

Methods: A retrospective investigation was conducted of patients diagnosed with DCIS from 2007 to 2014 who were followed for a minimum of five years after treatment. Data about each patient were extracted from the medical records.

Deep Learning vs Traditional Breast Cancer Risk Models to Support Risk-Based Mammography Screening.

Background: Deep learning breast cancer risk models demonstrate improved accuracy compared with traditional risk models but have not been prospectively tested. We compared the accuracy of a deep learning risk score derived from the patient's prior mammogram to traditional risk scores to prospectively identify patients with cancer in a cohort due for screening.

Methods: We collected data on 119 139 bilateral screening mammograms in 57 617 consecutive patients screened at 5 facilities between September 18, 2017, and February 1, 2021.

Impact of a Deep Learning Model for Predicting Mammographic Breast Density in Routine Clinical Practice.

Objective: Legislation in 38 states requires patient notification of dense mammographic breast tissue because increased density is a marker of breast cancer risk and can limit mammographic sensitivity. Because radiologist density assessments vary widely, our objective was to implement and measure the impact of a deep learning (DL) model on mammographic breast density assessments in clinical practice.

Methods: This institutional review board-approved prospective study identified consecutive screening mammograms performed across three clinical sites over two periods: 2017 period (January 1, 2017, through September 30, 2017) and 2019 period (January 1, 2019, through September 30, 2019).

Magnetic Seeds: An Alternative to Wire Localization for Nonpalpable Breast Lesions.

Introduction: Magnetic seeds have emerged as an alternative to wires for localization of nonpalpable breast lesions. The purpose of this study was to evaluate the utility of magnetic seeds compared to wires for preoperative localization.

Materials And Methods: A retrospective cohort analysis of magnetic seed localization (MSL) and wire localization (WL) excisional biopsies and lumpectomies performed at a single institution was conducted.

Artificial Intelligence (AI) for Screening Mammography, From the Special Series on AI Applications.

Artificial intelligence (AI) applications for screening mammography are being marketed for clinical use in the interpretative domains of lesion detection and diagnosis, triage, and breast density assessment and in the noninterpretive domains of breast cancer risk assessment, image quality control, image acquisition, and dose reduction. Evidence in support of these nascent applications, particularly for lesion detection and diagnosis, is largely based on multireader studies with cancer-enriched datasets rather than rigorous clinical evaluation aligned with the application's specific intended clinical use. This article reviews commercial AI algorithms for screening mammography that are currently available for clinical practice, their use, and evidence supporting their performance.

Are English-language online patient education materials related to breast cancer risk assessment understandable, readable, and actionable?

Purpose: To evaluate the readability, understandability, and actionability of online patient education materials (OPEM) related to breast cancer risk assessment.

Material And Methods: We queried seven English-language search terms related to breast cancer risk assessment: breast cancer high-risk, breast cancer risk factors, breast cancer family history, BRCA, breast cancer risk assessment, Tyrer-Cuzick, and Gail model. Websites were categorized as: academic/hospital-based, commercial, government, non-profit or academic based on the organization hosting the site.

Screening Mammography Recovery After COVID-19 Pandemic Facility Closures: Associations of Facility Access and Racial and Ethnic Screening Disparities.

Screening mammography facilities closed during the COVID-19 pandemic in spring 2020. Recovery of screening volumes has varied across patient subgroups and facilities. We compared screening mammography volumes and patient and facility characteristics between periods before COVID-19 and early and later postclosure recovery periods.

Imaging Evaluation of the Axilla-A National Survey of Clinical Practice Among Radiologists.

Objective: To assess awareness and implementation of the American College of Surgeons Oncology Group Z0011 trial findings, approaches to axillary nodal imaging, and to identify differences in practice based on respondent characteristics.

Methods: An online survey was distributed to members of the Society of Breast Imaging. Questions regarded demographics, evaluation approaches, and impact of the Z0011 trial.

A Multimetric Evaluation of Online Patient Educational Materials for Breast Implant-associated Anaplastic Large Cell Lymphoma.

Objective: To assess understandability, actionability, and readability of online patient educational materials (OPEM) related to breast implant-associated anaplastic large cell lymphoma (BIA-ALCL).

Methods: Search volumes for query terms related to BIA-ALCL including "breast implant associated lymphoma," "breast implant associated anaplastic large cell lymphoma," and "BIA-ALCL" were analyzed in one-week increments and normalized to total Google search volume. The same terms were then queried using an online search engine to identify commonly accessed OPEM on this topic.

Disparities in Same-Day Diagnostic Imaging in Breast Cancer Screening: Impact of an Immediate-Read Screening Mammography Program Implemented During the COVID-19 Pandemic.

The need for second visits between screening mammography and diagnostic imaging contributes to disparities in the time to breast cancer diagnosis. During the COVID-19 pandemic, an immediate-read screening mammography program was implemented to reduce patient visits and decrease time to diagnostic imaging. The purpose of this study was to measure the impact of an immediate-read screening program with focus on disparities in same-day diagnostic imaging after abnormal findings are made at screening mammography.

Evidence-Based Pragmatic Approach to the Management of Borderline or High-Risk Breast Lesions.

The management of borderline or high-risk breast lesions (HRLs) remains controversial. We propose a pragmatic evidence-based approach based on lesion type. For lobular carcinoma in situ with pleomorphism, papilloma with atypia, atypical ductal hyperplasia, and fibroepithelial lesions, surgical consultation and excision are recommended.

An Algorithm for Management of Cosmetic and Reconstructive Patients with Textured Implants: An Institutional Experience.

Textured anatomic silicone gel breast implants have advantages of gel cohesivity and a natural slope between the upper and lower poles of the breast; however, they have fallen out of favor secondary to their risk of breast implant-associated anaplastic large cell lymphoma. For patients who choose to keep their textured devices, there remains controversy over the best long-term follow-up. This article presents an algorithm from plastic surgery, surgical oncology, and radiology at the Massachusetts General Hospital for management of these patients.

Unilateral Lymphadenopathy After COVID-19 Vaccination: A Practical Management Plan for Radiologists Across Specialties.

Reports are rising of patients with unilateral axillary lymphadenopathy, visible on diverse imaging examinations, after recent coronavirus disease 2019 vaccination. With less than 10% of the US population fully vaccinated, we can prepare now for informed care of patients imaged after recent vaccination. The authors recommend documenting vaccination information (date[s] of vaccination[s], injection site [left or right, arm or thigh], type of vaccine) on intake forms and having this information available to the radiologist at the time of examination interpretation.

Mitigating the Impact of Coronavirus Disease (COVID-19) Vaccinations on Patients Undergoing Breast Imaging Examinations: A Pragmatic Approach.

Reports of patients with axillary adenopathy identified on breast imaging after coronavirus disease (COVID-19) vaccination are rising. We propose a pragmatic management approach based on clinical presentation, vaccination delivery, and imaging findings. In the settings of screening mammography, screening MRI, and diagnostic imaging workup of breast symptoms, with no imaging findings beyond unilateral axillary adenopathy ipsilateral to recent (within the past 6 weeks) vaccination, we report the adenopathy as benign with no further imaging indicated if no nodes are palpable 6 weeks after the last dose.

Toward robust mammography-based models for breast cancer risk.

Improved breast cancer risk models enable targeted screening strategies that achieve earlier detection and less screening harm than existing guidelines. To bring deep learning risk models to clinical practice, we need to further refine their accuracy, validate them across diverse populations, and demonstrate their potential to improve clinical workflows. We developed Mirai, a mammography-based deep learning model designed to predict risk at multiple timepoints, leverage potentially missing risk factor information, and produce predictions that are consistent across mammography machines.

Retrospective Review of Preoperative Radiofrequency Tag Localization of Breast Lesions in 848 Patients.

Advantages of radiofrequency tags for preoperative breast lesion localization include decoupling of tag placement from surgical schedules and improved patient comfort. The purpose of this study was to evaluate the feasibility of a preoperative localization radiofrequency tag system for breast lesions requiring surgical excision. The cohort for this retrospective study included consecutive patients who underwent image-guided needle localization with radiofrequency tags before surgical excision from July 12, 2018, to July 31, 2019.

Opportunities for Radiology Trainee Education Amid the COVID-19 Pandemic: Lessons From an Academic Breast Imaging Program.

The COVID-19 pandemic required restructuring of Radiology trainee education across US institutions. While reduced clinical imaging volume and mandates to maintain physical distancing presented new challenges to traditional medical education during this period, new opportunities developed to support our division in providing high-quality training for residents and fellows. The Accreditation Council for Graduate Medical Education (ACGME) Core Competencies for Diagnostic Radiology helped guide division leadership in restructuring and reframing breast imaging education during this time of drastic change and persistent uncertainty.

Predictors of Reexcision following Breast-Conserving Surgery for Ductal Carcinoma In Situ.

Background: Reexcision following breast-conserving surgery (BCS) in women with ductal carcinoma in situ (DCIS) results in adjuvant treatment delays, higher health care costs, and undesirable cosmetic outcomes. The purpose of this study is to determine patient, imaging, pathological, and surgical predictors of reexcision following BCS for DCIS.

Patients And Methods: A retrospective review of women with DCIS who had BCS from 2007 to 2016 was conducted.