A Kaiser score > 5 with breast MRI demonstrated a 97 percent sensitivity and 87.9 percent specificity for predicting malignancy in patients with BI-RADS 0 or 4 presentations on mammography and breast ultrasound, according to a new study.
Feature|Articles|August 26, 2026
Emerging Research in Mammography, Breast MRI, Ultrasound and AI: A Summer Roundup of Key Breast Imaging Studies
Author(s)Diagnostic Imaging Staff
This summer's breast imaging research spanned digital breast tomosynthesis (DBT) efficiency gains, AI models that flag cancer risk years before diagnosis, a cautionary study on automation bias, and advances in ultrasound, MRI, and contrast-enhanced mammography (CEM). Here is a look back at the most well-viewed breast imaging content of the summer.
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Can artificial intelligence (AI) redefine risk stratification in mammography? Could deep learning reconstruction bolster breast MRI quality and significantly reduce scan time? Can automated breast ultrasound reduce BI-RADS 3 assessments? Our summer roundup of breast imaging research addresses these questions and more.
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Assessing breast MRI scans, pathology and clinical data, the AI-powered TumorSight Risk software reportedly provides five- and 10-year risk for breast cancer recurrence for women with HR+, HER2-negative stage I-IIIA breast cancer.
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