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Updated: Jun 2, 2025
Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
Published on: January 15, 2022
Can fast wall shear stress computation predict adverse cardiac events in patients with intermediate non-flow limiting
Vincenzo Tufaro1, Ryo Torii2, Jean-Paul Aben3
1Department of Cardiology, Barts Heart Centre, Barts Health NHS Trust, London, UK; Centre for Cardiovascular Medicine and Devices, William Harvey Research Institute, Queen Mary University of London, London, UK; Department of Biomedical Sciences, Humanitas University, Pieve Emanuele-Milan, Italy.
Background And Aims:
Coronary angiography-derived wall shear stress (WSS) may enable identification of vulnerable plaques and patients. A new recently introduced software allows seamless three-dimensional quantitative coronary angiography (3D-QCA) reconstruction and WSS computation within a single user-friendly platform carrying promise for clinical applications. This study examines for the first time the efficacy of this software in detecting vulnerable lesions in patients with intermediate non-flow limiting stenoses.
Methods:
This multicentre retrospective study included patients who had coronary angiography showing at least one lesion with borderline negative fractional flow reserve (FFR: 0.81-0.85). In these lesions, 3D-QCA reconstruction and blood flow simulation were performed using the CAAS Workstation WSS prototype (Pie Medical Imaging, Maastricht, Netherlands). Time averaged and multidirectional WSS were extracted across the lesion at every 3 mm segments. The primary endpoint of the study was lesion-oriented clinical events (LOCE), defined as the composite of cardiac death, target lesion related myocardial infarction (MI) or clinically indicated target lesion revascularization.
Results:
352 patients (355 lesions) were included in the analysis. Over a median follow-up of 4.1 years, 57 LOCE were recorded. Lesions causing events had a larger area stenosis (AS) [59.4 (54.6-67.7)% vs 52.8 (43.8-60.1)%, p < 0.001], maximum time averaged WSS (TAWSS) [11.56 (8.25-13.64)Pa vs 7.73 (5.41-11.51)Pa, p < 0.001], mean TAWSS at the minimum lumen area (MLA) [9.30 (5.44-11.94)Pa vs 6.19 (3.96-9.00)Pa, p < 0.001] and maximum transverse WSS [0.30 (0.21-0.45)Pa vs 0.23 (0.17-0.32)Pa, p=0.002] than those remaining quiescent. In multivariable models, AS was the only independent predictor of LOCE. Kaplan-Meier curves demonstrated that lesions with elevated maximum TAWSS and AS had a higher rate of LOCE than those with low TAWSS and AS values (26 % vs 7 %, p < 0.001).
Conclusions:
For non-flow limiting lesions with borderline negative FFR, fast WSS computation using a dedicated software is feasible and holds potential for cardiovascular risk stratification.
