Deep learning AI improves interreader agreement in CAD-RADS assessments on coronary CT angiography.
Key Details
- 1Study published in Radiology: Cardiothoracic Imaging (Oct 9).
- 2623 patients (11,214 coronary segments) who underwent CCTA were included.
- 3AI-assisted CAD-RADS readings showed higher agreement: 1 vs. 2 readers (manual: 73.7%, AI-assisted: 81.8%); 1 vs. 3 (manual: 77.9%, AI-assisted: 84.5%).
- 4AI algorithm evaluated lesion, segment, and patient levels for CAD-RADS and classified stenosis grades with visual outputs.
- 5Authors call for further research with larger datasets and diverse settings.
Why It Matters
Standardizing CAD-RADS assessments using AI has the potential to reduce variability and errors in coronary CT reporting, which could improve patient management and facilitate training for less experienced readers.

Source
AuntMinnie
Related News

•AuntMinnie
AI Tool Mirai Shows Robust Performance for Interval Breast Cancer Detection
The Mirai AI model significantly improves detection of interval breast cancers in negative screening mammograms.

•Radiology Business
AI Tool Predicts Interval Breast Cancer Risk from Negative Mammograms
AI can predict interval breast cancer risk up to three years after a negative mammogram.

•Radiology Business
AI Outperforms Radiologists in Predicting Lung Cancer Treatment Response
AI tools demonstrate higher accuracy than radiologists in predicting lung cancer treatment response from imaging studies.