Focal comparison of experimental and finite element derived strain fields in a 3D IVUS-based computational model of vascular tissue under loading

对基于三维血管内超声(IVUS)的血管组织加载计算模型中实验应变场和有限元计算应变场进行重点比较

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Abstract

Arterial tissues are subjected to mechanical loads that influence biological mechanisms in health and disease. Motivated by these observations, computational models to predict the vascular mechanical environment are increasingly being developed and applied. However, few computational vascular biomechanics studies are evaluated for accuracy. This study aimed to compare the transmural strain fields in healthy vascular tissue under physiologic loading between 3D intravascular ultrasound (IVUS)-based finite element (FE) models and image-based experimental measurements. IVUS image data were captured along a ∼ 15 mm segment in porcine carotid arteries (n = 3) in the reference configuration (∼10 mmHg) and at five axial positions under varied pressure loads. FE models were constructed from the full-length segment IVUS data, and model-predicted strains were determined using reported soft and stiff material properties for porcine tissue. Experimental strains were determined at each axial slice across the applied loads using a deformable image registration technique (Hyperelastic Warping). Both FE-predicted and experimental deformations exhibited non-linear behavior under loading, as observed in the material response curves. Following Warping parameter selection, results demonstrated that FE-predicted transmural strains with soft and stiff material properties bounded the experimentally-derived data at systolic pressures; however, sample variability was observed. At systolic pressure, Warping-derived and FE-predicted transmural strains showed good agreement, as RMSE values were < 0.09 and differences < 0.08. In conclusion, this study presents an experimental framework to assess accuracy in IVUS-based FE models, and results indicate that the computational framework can predict realistic deformations of arterial tissue; however, the accuracy strongly depends on tissue-specific material properties.

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