CT-derived coronary artery calcium density is affected by regional lesion distribution and image reconstruction parameters
Borek Foldyna, Said Basmagi, Foroud Aghapour Zangeneh, Matthias Wagner, Kalin Doktorov, Anna Matveeva, Timm Denecke, Robin F Gohmann, Christian Lücke, Matthias Gutberlet, Lukas Lehmkuhl
Clin Imaging . 2023 Nov:103:109980. doi: 10.1016/j.clinimag.2023.109980. Epub 2023 Sep 1.
Purpose: The prognostic relevance of coronary artery calcium (CAC) density, assessed from cardiac CT scans, is established. However, the influence of CAC distribution, volume, image reconstruction, and clinical factors on CAC density warrants further examination.
Methods: In this study, 120 patients underwent non-contrast ECG-gated cardiac CT scans using a prospectively defined CAC scoring protocol with 1-, 3-, and 5-mm thick image reconstructions, both with and without a 20% image overlap. We segmented CAC in all reconstructions and assessed the relationship between CAC density, volume, and number of detected calcifications/patient.
Results: Overall, 75/120 (63%) patients (66% men, mean age 63 ± 11 years) presented CAC across 342 segments. CAC density, CAC volume, and the number of detected calcifications decreased with increasing slice thickness (p < 0.001 for all); these effects were slightly reduced by image overlap (p < 0.001 for all). Higher CAC density correlated with greater CAC volume (ρ = 0.62; p < 0.001) and more calcified segments per person (ρ = 0.32; p = 0.006). Higher CAC density was also associated with lower patient weight (beta: -0.6, 95%CI: -1.1--0.1, p = 0.022) and increased high-density lipoprotein (HDL) levels (beta: 0.7, 95%CI: 0.0-1.4, p = 0.046). In a multivariable analysis adjusted for clinical covariates, lower CAC density was associated with broader CAC distribution (i.e., a higher number of calcified segments at a given CAC volume; beta-coefficient: -58.9; 95%CI: -84.7 to -33.1; p < 0.001).
Conclusion: CAC density is significantly impacted by regional CAC distribution and image reconstruction, potentially confounding its prognostic value. Accounting for these factors may improve patient risk assessment, management, and cardiovascular health outcomes.