ArticleEuropean radiology2026
Adapted foundation models for breast MRI triaging in contrast-enhanced and non-contrast-enhanced protocols.
Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesTo evaluate a DINOv2-based medical slice transformer (MST) for triaging abbreviated breast MRI by ruling out examinations with suspicious findings that are immediately actionable (Breast Imaging Reporting and Data System [BI-RADS] ≥ 4) across contrast-enhanced and non-contrast-enhanced protocols. MATERIALS AND
methodsThis institutional review board-approved retrospective study included 1847 single-breast MRI examinations (377 BI-RADS ≥ 4) from an in-house dataset and 924 from an external dataset (Duke). Four abbreviated protocols were tested: T1-weighted early subtraction (T1
resultsA total of 1448 female patients (mean age, 49 ± 12 years) were included. T1
conclusionAt 97.5% sensitivity, the MST framework triaged cases without BI-RADS ≥ 4, achieving 19% specificity for contrast-enhanced and 17% for non-contrast-enhanced MRI. These findings highlight the potential of foundation-model-based AI to support efficient triaging of abbreviated breast MRI protocols. KEY POINTS: Question Can an adapted DINOv2-based MST accurately stratify abbreviated breast MRI examinations to support triaging across contrast-enhanced and non-contrast-enhanced imaging protocols? Findings The model achieved 19% specificity for contrast-enhanced and 17% for non-contrast-enhanced MRI at 97.5% sensitivity; external validation of the T1sub protocol yielded an AUC of 0.77. Clinical relevance A foundation-model-based triage approach may reduce radiologist workload in breast MRI screening by identifying examinations unlikely to contain suspicious findings, including on non-contrast-enhanced protocols, thereby enabling prioritization of higher-risk studies.
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