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
•Radiology Business
Real-World Study: Radiology AI Best in Emergency and Inpatient Settings
A commercial AI tool for intracranial aneurysm detection outperformed in inpatient and emergency settings but yielded limited benefits for outpatients in a major health system study.
•Radiology Business
New Rubric Enhances Safety of AI-Generated Radiology Summaries
Researchers developed a five-factor rubric to assess the safety and quality of AI-generated, patient-friendly radiology report summaries.
•Radiology Business
Healthcare Leader Warns AI Will Dominate Diagnostic Radiology
A leading oncologist urges future radiologists to specialize in interventional procedures due to AI advances in image interpretation.