Letter, Haley P

Abstract Objective Current clinical risk models were developed for longer-term breast cancer risk stratification and therefore have limited utility for predicting short-term (1-year) breast cancer risk. This study evaluates the performance of a mammogram-based artificial intelligence (MB-AI) risk model for predicting breast cancer diagnosis within 1 year in high-risk women. Methods This retrospective case-control study included 340 women who underwent supplemental MRI screening within 1 year following a negative mammogram, of whom 101 (29.7%) developed breast cancer and 239 (70.3%) remained cancer-free during the same interval. Artificial-intelligence–assigned absolute 1-year risk scores, Tyrer–Cuzick (TC) lifetime and 10-year scores, and Gail lifetime and 5-year scores were analyzed. Model discrimination was evaluated using receiver operating characteristic (ROC) curves. Sensitivity, specificity, and predictive values were estimated at optimal cutoffs. Subgroup analyses examined model performance across genetic, menopausal, reproductive, and tumor-based strata. Results The MB-AI model demonstrated the highest overall discriminative ability (area under the curve [AUC] = 0.812), with strong performance in extremely dense breasts (AUC = 0.976). By comparison, TC lifetime (AUC = 0.625) and Gail lifetime (AUC = 0.668) models showed modest discrimination, while TC 10-year and Gail 5-year models did not discriminate (AUCs ≤0.49). Subgroup analyses showed consistent performance across clinical and pathological categories. The MB-AI model also showed an AUC comparable to that of previously developed AI models. Conclusions A mammogram-based AI model demonstrated improved performance compared with traditional clinical risk models for predicting breast cancer diagnosis within 1 year in women undergoing supplemental screening. These findings support that AI-based approaches may reflect both short-term risk and early imaging features of occult disease and suggest further investigation of AI as a complement to existing risk stratification strategies.

Breast size changes are common, but the underlying cause may be challenging to diagnose and requires a structured approach combining patient history, physical examination, and multimodality imaging to differentiate benign from malignant causes and improve patient outcomes.

Abstract Women with a personal history of breast cancer (PHBC) remain at risk for ipsilateral breast tumor recurrence or a second primary tumor, with a cumulative incidence of 14.3% and reported annual risk of approximately 1–2%. Post-treatment changes can obscure imaging findings, making early recognition of recurrence a challenging, but critical skill for breast radiologists. Detection of early breast cancer recurrence, before it becomes symptomatic, is linked to improved survival, highlighting the need for multimodality surveillance imaging. This review summarizes key prognostic factors that influence recurrence risk and should inform imaging interpretation. Incorporating these prognostic factors into practice can aid imaging interpretation by heightening the attention to subtle changes that may reflect early recurrence. Illustrative cases are used to demonstrate the imaging spectrum of locoregional recurrence in post-lumpectomy and post-mastectomy patients. Recurrences often resemble the imaging features of the primary tumor but may also present subtly. The distinction between recurrence and benign post-treatment change is emphasized, with attention to imaging findings that warrant further evaluation. Finally, emerging evidence-based recommendations for risk-adapted surveillance incorporating tumor biology, receptor status, and stage are reviewed to support early detection and improved outcomes

Abstract The practice of formally documenting radiologic and pathologic concordance after percutaneous breast biopsies was instituted more than 20 years ago. There are several ways in which this can be done, but in many practices the performing radiologist independently compares the imaging findings with the pathology report to determine concordance. However, some studies show that a multidisciplinary review of breast biopsy results can maximize cancer detection, identify discordant cases in a timely manner, decrease imaging follow-up, and avoid unnecessary surgical intervention. This article will propose a practical method to establish a formal radiology-pathology conference in which percutaneous breast biopsies are reviewed with multidisciplinary input to increase efficiency and improve patient care. With the wide implementation of digital radiologic imaging and digital pathology evaluation plus the recent adoption of virtual meeting platforms, a successful radiology-pathology conference can be implemented in nearly any practice setting. Case examples will be presented demonstrating the utility of such a conference.

Abstract Objective Peri-implant enhancement can be seen on contrast-enhanced breast MRI, but its association with malignancy has not been described, leading to considerable variability in assessment and recommendations by radiologists. This study evaluated imaging features, management, and outcomes of implant-related enhancement. Methods This multisite IRB-approved retrospective review queried all breast MRI reports for keywords describing peri-implant enhancement, fluid, and/or masses (plus synonymous descriptions) and implant-associated malignancies, with subsequent imaging and chart review. Peri-implant enhancement and implant features were characterized. Assessments and outcomes were evaluated via clinical and imaging follow-up, aspiration/biopsy, and/or capsulectomy to evaluate for association of peri-implant enhancement with implant-related malignancy. Results A total of 100 patients had peri-implant enhancement. Uniform thin peripheral enhancement was most common (79/100, 79%). Capsulectomy was performed in 31/100 (31%), with benign capsular fibrosis/inflammation discovered in 26/31 (83.9%). Breast implant–associated anaplastic large cell lymphoma was present in 2/100 (2%), both with textured implants, while 98/100 (98%) had no implant-related malignancy. MRI recommendations varied: resume routine imaging (26/100, 26%), clinical management (18/100, 18%), follow-up MRI (17/100, 17%), MRI-directed US (17/100, 17%), aspiration/biopsy (11/100, 11%), and surgical consultation (10/100, 10%). Conclusion Peri-implant enhancement is a nonspecific imaging finding with a low malignant association, especially when seen in isolation (no associated effusion, mass, or adenopathy). Implant surface texture should be considered in management recommendations; diagnostic capsulectomy is not recommended in patients with smooth implants. Additional studies are encouraged to validate nonoperative management recommendations.

Abstract Unlike many other subspecialties in radiology, breast radiologists practice in a patient-facing and interdisciplinary environment where team building, communication, and leadership skills are critical. Although breast radiologists can improve these skills over time, strong mentorship can accelerate this process, leading to a more successful and satisfying career. In addition to providing advice, insight, feedback, and encouragement to mentees, mentors help advance the field of breast radiology by contributing to the development of the next generation of leaders. During the mentorship process, mentors continue to hone their listening, problem-solving, and networking skills, which in turn creates a more supportive and nurturing work environment for the entire breast care team. This article reviews important mentorship skills that are essential for all breast radiologists. Although some of the principles apply to all mentoring relationships, ensuring that every breast radiologist has the skills to be both an effective mentor and mentee is key to the future of the profession.

Abstract Objective Molecular breast imaging (MBI) is a supplemental screening modality consistently demonstrating incremental cancer detection over mammography alone; however, its lengthy duration may limit widespread utilization. The study purpose was to assess feasibility of an abbreviated MBI protocol, providing readers with mediolateral oblique (MLO) projections only and assessing performance in lesion detection and localization. Methods Retrospective IRB-exempt blinded reader study administered to 5 fellowship-trained breast imaging radiologists. Independent reads performed for 124 screening MBI cases, half abnormal and half negative/normal. Readers determined whether an abnormality was present, side of abnormality, and location of abnormality (medial/lateral). Abnormal cases had confirmatory biopsy or surgical pathology; normal cases had imaging follow-up ensuring true negative results. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to assess performance. A false negative result indicated that a reader failed to detect abnormal uptake; a false positive result indicated a reader incorrectly called an abnormality for a negative case. Tests for association included chi-square, Fisher-exact, and analysis of variance. Results Mean reader performance for detecting abnormal uptake: sensitivity 96.8%, specificity 98.7%, PPV 98.8%, and NPV 96.9%. Accuracy in localizing lesions to the medial or lateral breast was 100%. There were no associations in reader performance with reader experience, reader technique, lesion morphology, or lesion pathology. Median lesion size was 1.0 cm (range: 0.4–8.0 cm). All readers correctly identified 97.7% (42/43) of lesions with malignant or elevated risk pathology. Conclusion An abbreviated MBI protocol (MLO images only) maintained high accuracy in lesion detection and localization.