Patient-specific computational simulation of coronary artery bifurcation stenting

Abstract

Patient-specific and lesion-specific computational simulation of bifurcation stenting is an attractive approach to achieve individualized pre-procedural planning that could improve outcomes. The objectives of this work were to describe and validate a novel platform for fully computational patient-specific coronary bifurcation stenting. Our computational stent simulation platform was trained using n = 4 patient-specific bench bifurcation models (n = 17 simulations), and n = 5 clinical bifurcation cases (training group, n = 23 simulations). The platform was blindly tested in n = 5 clinical bifurcation cases (testing group, n = 29 simulations). A variety of stent platforms and stent techniques with 1- or 2-stents was used. Post-stenting imaging with micro-computed tomography (μCT) for bench group and optical coherence tomography (OCT) for clinical groups were used as reference for the training and testing of computational coronary bifurcation stenting. There was a very high agreement for mean lumen diameter (MLD) between stent simulations and post-stenting μCT in bench cases yielding an overall bias of 0.03 (− 0.28 to 0.34) mm. Similarly, there was a high agreement for MLD between stent simulation and OCT in clinical training group [bias 0.08 (− 0.24 to 0.41) mm], and clinical testing group [bias 0.08 (− 0.29 to 0.46) mm]. Quantitatively and qualitatively stent size and shape in computational stenting was in high agreement with clinical cases, yielding an overall bias of < 0.15 mm. Patient-specific computational stenting of coronary bifurcations is a feasible and accurate approach. Future clinical studies are warranted to investigate the ability of computational stenting simulations to guide decision-making in the cardiac catheterization laboratory and improve clinical outcomes.

First-in-Human Computational Preprocedural Planning of Left Main Interventions Using a New Everolimus-Eluting Stent

“… For the first time, a well-validated patient-specific computational stent simulations platform 4 was used for preprocedural planning of coronary interventions. This platform could help interventional cardiologists familiarize themselves with anatomically complex cases (eg, LM, bifurcations) and optimize the equipment selection (eg, stents, balloons) and procedural steps (eg, lesion preparation, 1-stent vs 2-stent technique, postdilatation technique) in a safe, radiation- and contrast-free environment.…”

“…Detailed description of the methods used for stent simulations and computational fluid dynamics (CFD) is provided in Supplemental Table 1 . 4 Initially, we 3D reconstructed patient-specific LM anatomies on the basis of angiography and HD IVUS ( Figures 4A, 4B , 5A, 5B , 6A, and 6B ). 3 , 4 , 5 , 6 The 3D reconstructed LM anatomies were meshed and assigned realistic plaque stiffness properties considering the longitudinal and circumferential plaque heterogeneity derived from HD IVUS ( Figures 4C , 5C , and 6C ).…”

“… 4 Initially, we 3D reconstructed patient-specific LM anatomies on the basis of angiography and HD IVUS ( Figures 4A, 4B , 5A, 5B , 6A, and 6B ). 3 , 4 , 5 , 6 The 3D reconstructed LM anatomies were meshed and assigned realistic plaque stiffness properties considering the longitudinal and circumferential plaque heterogeneity derived from HD IVUS ( Figures 4C , 5C , and 6C ). 3 , 4 After performing computational stent simulations and CFD analyses ( Figures 4D, 4E , 5D, 5E , 6D, and 6E , Videos 1 , 2 , and 3 ), we selected the optimal stent positioning, sizing (length, diameter, inflation pressures), and strategy for each individual patient ( Figure 7 ).…”

“… 3 , 4 , 5 , 6 The 3D reconstructed LM anatomies were meshed and assigned realistic plaque stiffness properties considering the longitudinal and circumferential plaque heterogeneity derived from HD IVUS ( Figures 4C , 5C , and 6C ). 3 , 4 After performing computational stent simulations and CFD analyses ( Figures 4D, 4E , 5D, 5E , 6D, and 6E , Videos 1 , 2 , and 3 ), we selected the optimal stent positioning, sizing (length, diameter, inflation pressures), and strategy for each individual patient ( Figure 7 ). In these computational simulations, we used the new everolimus-eluting stent design provided by the manufacturer (Boston Scientific).…”

Introduction of a Novel Image-Based and Non-Invasive Method for the Estimation of Local Elastic Properties of Great Vessels

“…Over recent decades, the use of patient-specific numerical models has continued to grow for an increasing range of applications [1][2][3]. Recent technological advances in medical imaging and computational power have enabled the increased use of numerical patient-specific modeling, providing a reliable tool for the study of cardiovascular problems in a highly accurate way.…”