RESUMEN
Artificial intelligence (AI) has been implemented in multiple fields of medicine to assist in the diagnosis and treatment of patients. AI implementation in radiology, more specifically for breast imaging, has advanced considerably. Breast cancer is one of the most important causes of cancer mortality among women, and there has been increased attention towards creating more efficacious methods for breast cancer detection utilizing AI to improve radiologist accuracy and efficiency to meet the increasing demand of our patients. AI can be applied to imaging studies to improve image quality, increase interpretation accuracy, and improve time efficiency and cost efficiency. AI applied to mammography, ultrasound, and MRI allows for improved cancer detection and diagnosis while decreasing intra- and interobserver variability. The synergistic effect between a radiologist and AI has the potential to improve patient care in underserved populations with the intention of providing quality and equitable care for all. Additionally, AI has allowed for improved risk stratification. Further, AI application can have treatment implications as well by identifying upstage risk of ductal carcinoma in situ (DCIS) to invasive carcinoma and by better predicting individualized patient response to neoadjuvant chemotherapy. AI has potential for advancement in pre-operative 3-dimensional models of the breast as well as improved viability of reconstructive grafts.
RESUMEN
BACKGROUND: The decision to pursue bilateral mastectomy without pathological confirmation of additional preoperative MRI lesions is likely multifactorial. We investigated the association of demographic factors and biopsy compliance following preoperative breast MRI with changes in surgical management in patients with newly diagnosed breast cancer. METHODS: A retrospective review of BI-RADS 4 and 5 MRIs performed across a health system from March 2018 to November 2021 for assessment of disease extent and preoperative planning. Patient characteristics, including demographics, Tyrer-Cuzick risk score, pathology from index cancer and biopsy of MRI findings, and pre- and post-MRI surgical plans were recorded. Analysis compared patients who underwent biopsy with those who did not. RESULTS: The final cohort included 323 patients who underwent a biopsy and 89 who did not. Of patients who underwent a biopsy, 144/323 (44.6%) had additional cancer diagnoses. MRI did not change management in 179/323 patients (55.4%) who underwent biopsy and in 44/89 patients (51.7%) who did not. Patients with a biopsy were more likely to have additional breast conservation surgery (P < .001) and patients without a biopsy were more likely to have a change in management to bilateral mastectomy P = .009). Patients without a biopsy who underwent a management change to bilateral mastectomy were significantly younger (47.2 vs 58.6; P < .001) and more likely to be white (P = .02) compared to those choosing bilateral mastectomy after biopsy. DISCUSSION: Biopsy compliance is associated with changes in surgical decisions, and younger, white women are more likely to pursue aggressive surgical management without definitive pathologic diagnoses.