Quantifying aortic valve calcification is critical for assessing the severity of aortic stenosis, predicting cardiovascular risk, and guiding treatment decisions. This study evaluated the feasibility of a deep learning-based automatic quantification of aortic valve calcification using contrast-enhanced coronary CT angiography and compared the results with manual calcium scoring. A retrospective analysis of 177 patients undergoing aortic stenosis evaluation was conducted, divided into a development set (n = 97) and an internal validation set (n = 80).
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