Prediction of atherosclerotic disease progression using LDL transport modelling: a serial computed tomographic coronary angiographic study

• Published in: European heart journal cardiovascular imaging 2017-01, Vol.18 (1), p.11-18
• Main Authors: Sakellarios, Antonis, Bourantas, Christos V., Papadopoulou, Stella-Lida, Tsirka, Zeta, de Vries, Ton, Kitslaar, Pieter H., Girasis, Chrysafios, Naka, Katerina K., Fotiadis, Dimitrios I., Veldhof, Susan, Stone, Greg W., Reiber, Johan H.C., Michalis, Lampros K., Serruys, Patrick W., de Feyter, Pim J., Garcia-Garcia, Hector M.
• Format: Article
• Language: English
• Subjects: Acute Coronary Syndrome - diagnostic imaging; Acute Coronary Syndrome - therapy; Aged; Analysis of Variance; Angioplasty, Balloon, Coronary - adverse effects; Angioplasty, Balloon, Coronary - methods; Cohort Studies; Computed Tomography Angiography - methods; Computer Simulation; Coronary Angiography - methods; Coronary Artery Disease - diagnostic imaging; Coronary Artery Disease - therapy; Disease Progression; Female; Humans; Image Processing, Computer-Assisted; Lipoproteins, LDL - blood; Logistic Models; Male; Middle Aged; Monitoring, Physiologic - methods; Multidetector Computed Tomography; Multivariate Analysis; Predictive Value of Tests; Retrospective Studies; ROC Curve; Sensitivity and Specificity
• ISSN: 2047-2404; 2047-2412
• DOI: 10.1093/ehjci/jew035

Aim To investigate the efficacy of low-density lipoprotein (LDL) transport simulation in reconstructed arteries derived from computed tomography coronary angiography (CTCA) to predict coronary segments that are prone to progress. Methods and results Thirty-two patients admitted with an acute coronary event who underwent 64-slice CTCA after percutaneous coronary intervention and at 3-year follow-up were included in the analysis. The CTCA data were used to reconstruct the coronary anatomy of the untreated vessels at baseline and follow-up, and LDL transport simulation was performed in the baseline models. The computed endothelial shear stress (ESS), LDL concentration, and CTCA-derived plaque characteristics were used to identify predictors of substantial disease progression (defined as an increase in the plaque burden at follow-up higher than two standard deviations of the intra-observer variability of the expert who performed the analysis). Fifty-eight vessels were analysed. High LDL concentration [odds ratio (OR): 2.16; 95% confidence interval (CI): 1.64–2.84; P = 0.0054], plaque burden (OR: 1.40; 95% CI: 1.13–1.72; P = 0.0017), and plaque area (OR: 3.46; 95% CI: 2.20–5.44; P≤ 0.0001) were independent predictors of a substantial disease progression at follow-up. The ESS appears as a predictor of disease progression in univariate analysis but was not an independent predictor when the LDL concentration was entered into the multivariate model. The accuracy of the model that included the LDL concentration was higher than the accuracy of the model that included the ESS (65.1 vs. 62.5%). Conclusions LDL transport modelling appears a better predictor of atherosclerotic disease progression than the ESS, and combined with the atheroma characteristics provided by CTCA is able to detect with a moderate accuracy segments that will exhibit a significant plaque burden increase at mid-term follow-up.