Abstract
OBJECTIVES: To evaluate abdominal aortic calcification parameters derived from 3D volumetric analysis using photon-counting CT (PCCT) angiography-based virtual non-calcium (VNCa) algorithm as an imaging biomarker for high-risk cardiovascular disease (CVD) patients. METHODS: This retrospective study included patients who underwent abdominal PCCT angiography and non-contrast-enhanced chest CT (nCE-CCT, including CT scanners other than PCCT) between March 2023 and June 2024. Abdominal aortic calcification maps were generated by subtracting VNCa from the corresponding CTA images to calculate the abdominal calcification volume (ACV) and aortic wall volume (AWV). Percentage calcification volume (PCV) was calculated as ACV/AWV. Agatston scores from nCE-CCT classified patients into low- (≤ 100) and high-risk (> 100) CVD groups. Correlations between Agatston score, ACV, and PCV were analyzed using Spearman's rank correlation, and receiver operating characteristic analysis was used to determine the performance and cutoff values of ACV and PCV, with McNemar's test comparing sensitivities and specificities. RESULTS: The study included 200 patients, 163 low- and 37 high-risk patients. Agatston score correlations with ACV and PCV were 0.75 and 0.78, respectively (p < 0.0001). PCV showed a superior AUC (0.94) than ACV (0.90, p = 0.0002). Cutoff values were 5.74 mL for ACV (75.7% sensitivity, 89.0% specificity) and 14.81% for PCV (73.0% sensitivity, 99.4% specificity), and PCV specificity was significantly higher than ACV specificity (p < 0.0001). CONCLUSION: PCV > 14.81% indicates an increased CVD risk, suggesting that PCV is a potential imaging biomarker for high-risk patients with CVD. Abdominal CTA alone may identify high-risk patients with CVD, warranting further cardiovascular screening.