Novel risk score for predicting acute cardiovascular and cerebrovascular events after chest radiotherapy in patients with breast or lung cancer

Abu Rmilah et al. developed a risk score to predict major adverse cardiovascular and cerebrovascular events (MACCE) in breast and lung cancer patients post-chest radiotherapy (RT). This retrospective study analyzed cohorts from the Mayo Clinic, incorporating factors such as coronary artery calcification (CAC), age ≥74, diabetes, prior MACCE history, and heart radiation dose. **AVIEW CAC software** was used to automatically calculate CAC scores on non-gated CT planning scans, applying a deep-learning algorithm to identify and quantify coronary calcifications. This method generated a modified Agatston score, allowing CAC to be a key variable in the risk prediction models. The resulting models, C2AD2 (including heart dose) and C2AD (excluding heart dose), stratified patients into low, intermediate, and high-risk groups, with AUCs of 0.738 and 0.783, respectively. These findings suggest that CAC quantification with AVIEW CAC, combined with clinical data, can enhance cardiovascular risk assessment for patients undergoing chest RT.