Utility of Multimodality Intravascular Imaging and the Local Hemodynamic Forces to Predict Atherosclerotic
Christos V Bourantas1, Lorenz Räber2, Antonis Sakellarios3
1Department of Cardiology, Barts Heart Centre, Barts Health NHS Trust, London, United Kingdom; Institute of Cardiovascular Sciences, University College London, London, United Kingdom; Barts and the London School of Medicine, Queen Mary University London, London, United Kingdom.
Objectives:
This study sought to examine the utility of multimodality intravascular imaging and of the endothelial shear stress (ESS) distribution to predict atherosclerotic evolution.
Background:
There is robust evidence that intravascular ultrasound (IVUS)-derived plaque characteristics and ESS distribution can predict, with however limited accuracy, atherosclerotic evolution; nevertheless, it is yet unclear whether multimodality imaging and ESS mapping enable more accurate prediction of coronary plaque progression.
Methods:
A total of 44 patients admitted with a myocardial infarction that had successful revascularization and 3-vessel IVUS and optical coherence tomography (OCT) imaging at baseline and 13-month follow-up were included in the study. The IVUS data acquired at baseline in the nonculprit vessels were fused with x-ray angiography to reconstruct coronary anatomy and in the obtained models blood flow simulation was performed and the ESS was estimated. The baseline plaque characteristics and ESS distribution were used to identify predictors of disease progression: defined as a lumen reduction and an increase in plaque burden at follow-up.
Results:
Seventy-three vessels were included in the final analysis. Baseline ESS and the IVUS-derived but not the OCT-derived plaque characteristics were independently associated with a decrease in lumen area and an increase in plaque burden. Low ESS (odds ratio: 0.45; 95% confidence interval: 0.28 to 0.71; p < 0.001) and plaque burden (odds ratio: 0.73; 95% confidence interval: 0.54 to 0.97; p = 0.030) were the only independent predictors of disease progression at follow-up. The accuracy of the IVUS-derived plaque characteristics in predicting disease progression did not improve when ESS (AUC: 0.824 vs. 0.847; p = 0.127) or when OCT variables and ESS (AUC: 0.842; p = 0.611) were added into the model.
Conclusions:
ESS and OCT-derived variables did not improve the efficacy of IVUS in predicting disease progression. Further research is required to investigate whether multimodality imaging combined with ESS mapping will allow more reliable vulnerable plaque detection. (Comparison of Biomatrix Versus Gazelle in ST-Elevation Myocardial Infarction [STEMI] [COMFORTABLE]; NCT00962416).
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