The study aimed to evaluate the reliability and agreement of a commercial deep learning-based software (AVIEW CAC, Coreline Soft) for fully automated coronary artery calcium (CAC) scoring on non-ECG-gated low-dose CT (LDCT) with different slice thicknesses compared with manual ECG-gated calcium-scoring CT (CSCT). The results showed that both CSCT and LDCT using the fully automated CAC-scoring software demonstrated excellent reliability and agreement with manual CSCT scoring. LDCT with a 1.0-mm slice thickness yielded more accurate Agatston scoring than LDCT with a 2.5-mm slice thickness using the fully automated commercial software.
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