AI assistance enhances radiologists' breast cancer detection performance and directs attention to critical regions in mammograms.
Key Details
- 1Study included 12 breast imaging radiologists with 4–32 years’ experience from 10 institutions.
- 2150 mammography exams were analyzed (75 positive for cancer, 75 negative).
- 3With AI, average AUC improved from 0.93 to 0.97 (p<0.001); sensitivity increased from 81.7% to 87.2%.
- 4Radiologists spent more fixation time on lesion regions (5.4s with AI vs 4.4s) and covered less of the whole breast (9.5% vs 11.1%).
- 5No significant increase in reading time was found with AI support (30.8s with AI vs 29.4s).
- 6The study used Transpara (ScreenPoint Medical) as the AI tool; further research underway on timing and selective use of AI in practice.
Why It Matters
This research demonstrates how AI decision support can improve interpretive accuracy and efficiency in breast imaging, validating the role of AI as an effective adjunct in screening mammography workflows. Ongoing work aims to optimize AI presentation to avoid automation bias and maximize benefit.
Source
AuntMinnie
Related News
•AuntMinnie
AI Enables Safe 75% Gadolinium Reduction in Breast MRI Without Losing Sensitivity
AI-enhanced breast MRI with a 75% reduced gadolinium dose maintained diagnostic sensitivity comparable to full-dose protocols.
•Cardiovascular Business
Deep Learning AI Model Detects Coronary Microvascular Dysfunction Via ECG
A new AI algorithm rapidly detects coronary microvascular dysfunction using ECGs, with validation incorporating PET imaging.
•AuntMinnie
Study: Patients Prefer AI in Radiology as Assistive, Not Standalone Tool
Survey finds patients support AI-assisted radiology but not AI-only interpretations.