Non-invasive characterization of complex coronary lesions

Madhurima Vardhan,Andrew M Kahn,S James Chen,Jane A Leopold,Amanda Randles,John Gounley,Eric C Chi

doi:10.1038/s41598-021-86360-6

Abstract

Conventional invasive diagnostic imaging techniques do not adequately resolve complex Type B and C coronary lesions, which present unique challenges, require personalized treatment and result in worsened patient outcomes. These lesions are often excluded from large-scale non-invasive clinical trials and there does not exist a validated approach to characterize hemodynamic quantities and guide percutaneous intervention for such lesions. This work identifies key biomarkers that differentiate complex Type B and C lesions from simple Type A lesions by introducing and validating a coronary angiography-based computational fluid dynamic (CFD-CA) framework for intracoronary assessment in complex lesions at ultrahigh resolution. Among 14 patients selected in this study, 7 patients with Type B and C lesions were included in the complex lesion group including ostial, bifurcation, serial lesions and lesion where flow was supplied by collateral bed. Simple lesion group included 7 patients with lesions that were discrete, <10hbox {mm} long and readily accessible. Intracoronary assessment was performed using CFD-CA framework and validated by comparing to clinically measured pressure-based index, such as FFR. Local pressure, endothelial shear stress (ESS) and velocity profiles were derived for all patients. We validates the accuracy of our CFD-CA framework and report excellent agreement with invasive measurements (n=14, R^2 = 0.6, p = 0.0013). Ultra-high resolution achieved by the model enable physiological assessment in complex lesions and quantify hemodynamic metrics in all vessels up to 1mm in diameter. Importantly, we demonstrate that in contrast to traditional pressure-based metrics, there is a significant difference in the intracoronary hemodynamic forces, such as ESS, in complex lesions compared to simple lesions at both resting and hyperemic physiological states [n = 14, p=0.03]. Higher ESS was observed in the complex lesion group (7.0pm 4.7 Pa) than in simple lesion group (4.8pm 3.6 Pa). Complex coronary lesions have higher ESS compared to simple lesions, such differential hemodynamic evaluation can provide much the needed insight into the increase in adverse outcomes for such patients and has incremental prognostic value over traditional pressure-based indices, such as FFR.

Highlights

C coronary lesions, which present unique challenges, require personalized treatment and result in worsened patient outcomes
The results show that endothelial shear stress (ESS) and average hyperemic velocity vary with changes LCA/RCA lesion anatomy but compared to fractional flow reserve (FFR) these metrics are more sensitive to fluid flow variables, for example cardiac output and hematocrit
Treatment of complex coronary lesions is involved in more than 20% of the total number of percutaneous coronary intervention (PCI) procedures performed and post-interventional complications such as in-stent restenosis occurs in 30% of the cases

Summary

Introduction

C coronary lesions, which present unique challenges, require personalized treatment and result in worsened patient outcomes. Complex coronary lesions have higher ESS compared to simple lesions, such differential hemodynamic evaluation can provide much the needed insight into the increase in adverse outcomes for such patients and has incremental prognostic value over traditional pressure-based indices, such as FFR Complex coronary lesions, such as bifurcation and ostial lesions, are found in more than 20% of patients suffering from coronary diseases who are at high risk of developing secondary major adverse cardiac events[1,2,3,4]. We present a computational fluid dynamic (CFD) framework that accurately determines coronary arterial tree physiology at ultra-high resolutions This method enables quantitative evaluation of intra-arterial hemodynamics in complex coronary diseases, such as ostial lesion, bifurcation lesion and serial lesion, with high accuracy and prediction reliability for the first time. The accuracy of our framework is determined by comparing derived diagnostic metrics to clinical measurements, such as fractional flow reserve (FFR) in both simple and complex coronary lesions

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Results

Conclusion