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
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