RESUMO
PURPOSE: Firstly, to validate automatically and visually scored coronary artery calcium (CAC) on low dose CT (LDCT) scans with a dedicated calcium scoring CT (CSCT) scan. Secondly, to assess the added value of CAC scored from LDCT scans acquired during [15O]-water-PET myocardial perfusion imaging (MPI) on prediction of major adverse cardiac events (MACE). METHODS: 572 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, nonfatal myocardial infarction, coronary revascularization, and unstable angina. RESULTS: The agreement in risk group classification between reference CSCT manual scoring and visual/automatic LDCT scoring from LDCT was 0.66 (95% 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 ischemic information from the [15O]-water-PET scan. CONCLUSIONS: 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.
RESUMO
BACKGROUND: We present an automatic method for coronary artery calcium (CAC) quantification and cardiovascular risk categorization in CT attenuation correction (CTAC) scans acquired at rest and stress during cardiac PET/CT. The method segments CAC according to visual assessment rather than the commonly used CT-number threshold. METHODS: The method decomposes an image containing CAC into a synthetic image without CAC and an image showing only CAC. Extensive evaluation was performed in a set of 98 patients, each having rest and stress CTAC scans and a dedicated calcium scoring CT (CSCT). Standard manual calcium scoring in CSCT provided the reference standard. RESULTS: The interscan reproducibility of CAC quantification computed as average absolute relative differences between CTAC and CSCT scan pairs was 75% and 85% at rest and stress using the automatic method compared to 121% and 114% using clinical calcium scoring. Agreement between automatic risk assessment in CTAC and clinical risk categorization in CSCT resulted in linearly weighted kappa of 0.65 compared to 0.40 between CTAC and CSCT using clinically used calcium scoring. CONCLUSION: The increased interscan reproducibility achieved by our method may allow routine cardiovascular risk assessment in CTAC, potentially relieving the need for dedicated CSCT.
