A deep learning algorithm accurately quantifies coronary artery calcium (CAC) on routine nongated chest CT scans, offering significant potential for opportunistic cardiovascular risk assessment.
Key Details
- 1The AI-CAC algorithm analyzes noncontrast, nongated chest CTs, typically not used for CAC scoring.
- 2Study used data from 98 VA medical centers, comparing results from 795 patients with paired gated CTs.
- 3AI-CAC had 89.4% accuracy at detecting CAC and 87.3% accuracy at categorizing CAC above or below the score of 100.
- 4CAC scores above 400 indicated a 3.49-fold higher risk of 10-year all-cause mortality compared to a score of 0.
- 5Nearly all patients flagged by the model for high CAC would benefit from lipid-lowering therapy per cardiologist review.
- 6Opportunistic screening tested on 8,052 low-dose CT scans and highlights value for population health.
Why It Matters

Source
AuntMinnie
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