Shear Stress Estimated by Quantitative Coronary Angiography Predicts Plaques Prone to Progress and Cause Events.


Journal

JACC. Cardiovascular imaging
ISSN: 1876-7591
Titre abrégé: JACC Cardiovasc Imaging
Pays: United States
ID NLM: 101467978

Informations de publication

Date de publication:
10 2020
Historique:
received: 19 08 2019
revised: 05 02 2020
accepted: 14 02 2020
pubmed: 18 5 2020
medline: 12 8 2021
entrez: 18 5 2020
Statut: ppublish

Résumé

This study examined the value of endothelial shear stress (ESS) estimated in 3-dimensional quantitative coronary angiography (3D-QCA) models in detecting plaques that are likely to progress and cause events. Cumulative evidence has shown that plaque characteristics and ESS derived from intravascular ultrasound (IVUS)-based reconstructions enable prediction of lesions that will cause cardiovascular events. However, the prognostic value of ESS estimated by 3D-QCA in nonflow limiting lesions is yet unclear. This study analyzed baseline virtual histology (VH)-IVUS and angiographic data from 28 lipid-rich lesions (i.e., fibroatheromas) that caused major adverse cardiovascular events or required revascularization (MACE-R) at 5-year follow-up and 119 lipid-rich plaques from a control group that remained quiescent. The segments studied by VH-IVUS at baseline were reconstructed using 3D-QCA software. In the obtained geometries, blood flow simulation was performed, and the pressure gradient across the lipid-rich plaque and the mean ESS values in 3-mm segments were estimated. The additive value of these hemodynamic indexes in predicting MACE-R beyond plaque characteristics was examined. MACE-R lesions were longer, had smaller minimum lumen area, increased plaque burden (PB), were exposed to higher ESS, and exhibited a higher pressure gradient. In multivariable analysis, PB (hazard ratio: 1.08; p = 0.004) and the maximum 3-mm ESS value (hazard ratio: 1.11; p = 0.001) were independent predictors of MACE-R. Lesions exposed to high ESS (>4.95 Pa) with a high-risk anatomy (minimal lumen area <4 mm In the present study, 3D-QCA-derived local hemodynamic variables provided useful prognostic information, and, in combination with lesion anatomy, enabled more accurate identification of MACE-R lesions.

Sections du résumé

OBJECTIVES
This study examined the value of endothelial shear stress (ESS) estimated in 3-dimensional quantitative coronary angiography (3D-QCA) models in detecting plaques that are likely to progress and cause events.
BACKGROUND
Cumulative evidence has shown that plaque characteristics and ESS derived from intravascular ultrasound (IVUS)-based reconstructions enable prediction of lesions that will cause cardiovascular events. However, the prognostic value of ESS estimated by 3D-QCA in nonflow limiting lesions is yet unclear.
METHODS
This study analyzed baseline virtual histology (VH)-IVUS and angiographic data from 28 lipid-rich lesions (i.e., fibroatheromas) that caused major adverse cardiovascular events or required revascularization (MACE-R) at 5-year follow-up and 119 lipid-rich plaques from a control group that remained quiescent. The segments studied by VH-IVUS at baseline were reconstructed using 3D-QCA software. In the obtained geometries, blood flow simulation was performed, and the pressure gradient across the lipid-rich plaque and the mean ESS values in 3-mm segments were estimated. The additive value of these hemodynamic indexes in predicting MACE-R beyond plaque characteristics was examined.
RESULTS
MACE-R lesions were longer, had smaller minimum lumen area, increased plaque burden (PB), were exposed to higher ESS, and exhibited a higher pressure gradient. In multivariable analysis, PB (hazard ratio: 1.08; p = 0.004) and the maximum 3-mm ESS value (hazard ratio: 1.11; p = 0.001) were independent predictors of MACE-R. Lesions exposed to high ESS (>4.95 Pa) with a high-risk anatomy (minimal lumen area <4 mm
CONCLUSIONS
In the present study, 3D-QCA-derived local hemodynamic variables provided useful prognostic information, and, in combination with lesion anatomy, enabled more accurate identification of MACE-R lesions.

Identifiants

pubmed: 32417338
pii: S1936-878X(20)30258-8
doi: 10.1016/j.jcmg.2020.02.028
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2206-2219

Subventions

Organisme : British Heart Foundation
ID : PG/17/18/32883
Pays : United Kingdom

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2020 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Auteurs

Christos V Bourantas (CV)

Department of Cardiology, Barts Heart Centre, Barts Health NHS, London, United Kingdom; Institute of Cardiovascular Sciences, University College London, London, United Kingdom; Centre for Cardiovascular Medicine and Device Innovation, Queen Mary University London, London, United Kingdom. Electronic address: cbourantas@gmail.com.

Thomas Zanchin (T)

Department of Cardiology, Barts Heart Centre, Barts Health NHS, London, United Kingdom; Department of Cardiology, Bern University Hospital, Bern, Switzerland; Department of Mechanical Engineering, University College London, London, United Kingdom.

Ryo Torii (R)

Department of Mechanical Engineering, University College London, London, United Kingdom.

Patrick W Serruys (PW)

Faculty of Medicine, National Heart & Lung Institute, Imperial College London, United Kingdom.

Alexios Karagiannis (A)

CTU Bern, Institute of Social and Preventive Medicine, Bern University, Bern, Switzerland.

Anantharaman Ramasamy (A)

Department of Cardiology, Barts Heart Centre, Barts Health NHS, London, United Kingdom; Centre for Cardiovascular Medicine and Device Innovation, Queen Mary University London, London, United Kingdom.

Hannah Safi (H)

Institute of Cardiovascular Sciences, University College London, London, United Kingdom.

Ahmet Umit Coskun (AU)

Mechanical and Industrial Engineering, Northeastern University, Boston, Massachusetts.

Gerhard Koning (G)

Medis medical imaging systems bv, Leiden, the Netherlands.

Yoshinobu Onuma (Y)

Department of Interventional Cardiology, Thoraxcenter, Erasmus Medical Center, Rotterdam, the Netherlands.

Christian Zanchin (C)

Department of Cardiology, Bern University Hospital, Bern, Switzerland.

Rob Krams (R)

Department of Molecular Bioengineering Engineering and Material Sciences, Queen Mary University London, London, United Kingdom.

Anthony Mathur (A)

Department of Cardiology, Barts Heart Centre, Barts Health NHS, London, United Kingdom; Centre for Cardiovascular Medicine and Device Innovation, Queen Mary University London, London, United Kingdom.

Andreas Baumbach (A)

Department of Cardiology, Barts Heart Centre, Barts Health NHS, London, United Kingdom; Centre for Cardiovascular Medicine and Device Innovation, Queen Mary University London, London, United Kingdom.

Gary Mintz (G)

Department of Cardiology, Columbia University Medical Center and the Cardiovascular Research Foundation, New York, New York.

Stephan Windecker (S)

Department of Cardiology, Bern University Hospital, Bern, Switzerland.

Alexandra Lansky (A)

Institute of Cardiovascular Sciences, University College London, London, United Kingdom; Division of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.

Akiko Maehara (A)

Department of Cardiology, Columbia University Medical Center and the Cardiovascular Research Foundation, New York, New York.

Peter H Stone (PH)

Cardiovascular Division, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts.

Lorenz Raber (L)

Department of Cardiology, Bern University Hospital, Bern, Switzerland.

Gregg W Stone (GW)

Division of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.

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