Aims: The study aimed, firstly, to validate automatically and visually scored coronary artery calcium (CAC) on low-dose computed tomography (CT) (LDCT) scans with a dedicated calcium scoring CT (CSCT) scan and, secondly, to assess the added value of CAC scored from LDCT scans acquired during [15O]-water-positron emission tomography (PET) myocardial perfusion imaging (MPI) on prediction of major adverse cardiac events (MACE). Methods and results: Five hundred seventy-Two consecutive patients with suspected coronary artery disease, who underwent [15O]-water-PET MPI with LDCT and a dedicated CSCT scan were included. In the reference CSCT scans, manual CAC scoring was performed, while LDCT scans were scored visually and automatically using deep learning approach. Subsequently, based on CAC score results from CSCT and LDCT scans, each patient's scan was assigned to one out of five cardiovascular risk groups (0, 1-100, 101-400, 401-1000, >1000), and the agreement in risk group classification between CSCT and LDCT scans was investigated. MACE was defined as a composite of all-cause death, non-fatal myocardial infarction, coronary revascularization, and unstable angina. The agreement in risk group classification between reference CSCT manual scoring and visual/automatic LDCT scoring from LDCT was 0.66 [95% confidence interval (CI): 0.62-0.70] and 0.58 (95% CI: 0.53-0.62), respectively. Based on visual and automatic CAC scoring from LDCT scans, patients with CAC > 100 and CAC > 400, respectively, were at increased risk of MACE, independently of ischaemic information from the [15O]-water-PET scan. Conclusion: There is a moderate agreement in risk classification between visual and automatic CAC scoring from LDCT and reference CSCT scans. Visual and automatic CAC scoring from LDCT scans improve identification of patients at higher risk of MACE
