AI-Guided Breast MRI Protocols Cut Scan Times Without Compromising Cancer Detection
June 3, 2025
AI triaging halved breast MRI scan times while preserving diagnostic performance, enabling efficient, adaptive imaging workflows.
Key Details
- Simulation study analyzed retrospective data from 863 women (1,423 MRI exams); 51 breast cancers diagnosed within 12 months.
- AI-directed triaging assigned about 50% of exams to an abbreviated protocol based on real-time suspicion scoring.
- Diagnostic performance: Sensitivity (AI triage 88.2%, conventional 86.3%); specificity (AI triage 80.8%, conventional 81.4%).
- Cancer detection rates were nearly identical (31.6 vs 30.9 per 1,000 exams); interval cancer rates slightly improved with AI triaging (4.2 vs 4.9 per 1,000).
- No cases were missed by abbreviated MRI that would have been detected by the full protocol.
- Study highlights potential for workflow efficiency and personalized MRI acquisition.
Why It Matters
This approach could make high-volume breast MRI screenings more efficient, reducing scan and patient time without sacrificing cancer detection. It marks a step toward adaptive, AI-driven imaging protocols and improved resource utilization in breast imaging.