Utility of Multimodality Intravascular Imaging and the Local Hemodynamic Forces to Predict Atherosclerotic Disease Progression.

MedStar author(s):
Citation: Jacc: Cardiovascular Imaging. 13(4):1021-1032, 2020 04.PMID: 31202749Institution: MedStar Heart & Vascular InstituteForm of publication: Journal ArticleMedline article type(s): Journal ArticleSubject headings: *Coronary Angiography | *Coronary Artery Disease/dg [Diagnostic Imaging] | *Coronary Circulation | *Coronary Vessels/dg [Diagnostic Imaging] | *Hemodynamics | *Multimodal Imaging | *Plaque, Atherosclerotic | *Tomography, Optical Coherence | *Ultrasonography, Interventional | Aged | Coronary Artery Disease/pp [Physiopathology] | Coronary Artery Disease/th [Therapy] | Coronary Vessels/pp [Physiopathology] | Disease Progression | Female | Humans | Longitudinal Studies | Male | Middle Aged | Predictive Value of Tests | Prospective Studies | Time FactorsYear: 2020ISSN:
  • 1876-7591
Name of journal: JACC. Cardiovascular imagingAbstract: 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.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). Copyright (c) 2019 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.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.OBJECTIVES: This study sought to examine the utility of multimodality intravascular imaging and of the endothelial shear stress (ESS) distribution to predict atherosclerotic evolution.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.All authors: Bourantas CV, Fotiadis DI, Garcia-Garcia HM, Heg D, Kalatzis F, Karagiannis A, Koskinas KC, Mathur A, Michalis LK, Naka KK, Papafaklis MI, Raber L, Radu MD, Sakellarios A, Serruys PW, Taniwaki M, Ueki Y, Windecker S, Yamaji K, Zanchin TOriginally published: Jacc: Cardiovascular Imaging. 2019 Jun 12Fiscal year: FY2020Digital Object Identifier: Date added to catalog: 2019-10-10
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Journal Article MedStar Authors Catalog Article 31202749 Available 31202749

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.

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). Copyright (c) 2019 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

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.

OBJECTIVES: This study sought to examine the utility of multimodality intravascular imaging and of the endothelial shear stress (ESS) distribution to predict atherosclerotic evolution.

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.

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