A deep-learning model predicts coronary artery calcium (CAC) scores from chest x-rays, improving risk assessment for coronary artery disease.
Key Details
- 1Researchers developed and validated an AI model to predict CAC scores from chest x-rays.
- 2The study analyzed data from 10,230 patients with paired chest x-rays and CAC scores.
- 3Models were trained to classify risk based on CAC thresholds of 0, 100, and 400.
- 4Best performance AUCs were 0.74–0.79 (x-ray only), improving to 0.77–0.82 with clinical variables.
- 5External validation resulted in consistent AUCs of 0.78–0.81, supporting robustness.
Why It Matters
This research demonstrates AI's potential to estimate coronary risk from routine chest x-rays, reducing reliance on CT, lowering costs, and minimizing radiation exposure for cardiovascular risk assessment.

Source
AuntMinnie
Related News

•AuntMinnie
Deep Learning AI Outperforms Radiologists in Detecting ENE on CT
A deep learning tool, DeepENE, exceeded radiologist performance in identifying lymph node extranodal extension in head and neck cancers using preoperative CT scans.

•Radiology Business
Patients Favor AI in Imaging Diagnostics, Hesitate on Triage Use
Survey finds most patients support AI in diagnostic imaging but are reluctant about its use in triage decisions.

•Radiology Business
FDA Clears Multi-Disease AI Screening Platform for CT Imaging
HeartLung Corporation's AI-CVD platform receives FDA clearance to detect multiple diseases from a single CT scan.