Computational modeling of vascular growth in patient-specific pulmonary arterial patch reconstructions

Abstract

Recent progress in vascular growth mechanics has involved the use of computational algorithms to address clinical problems with the use of three-dimensional patient specific geometries. The objective of this study is to establish a predictive computational model for the volumetric growth of pulmonary arterial (PA) tissue following complex cardiovascular patch reconstructive surgeries for congenital heart disease patients. For the first time in the literature, the growth mechanics and performance of artificial cardiovascular patches in contact with the growing PA tissue domain is established. An elastic growing material model was developed in the open source FEBio software suite to first examine the surgical patch reconstruction process for an idealized main PA anatomy as a benchmark model and then for the patient-specific PA of a newborn. Following patch reconstruction, high levels of stress and strain are compensated by growth on the arterial tissue. As this growth progresses, the arterial tissue is predicted to stiffen to limit elastic deformations. We simulated this arterial growth up to the age of 18 years, when somatic growth plateaus. Our research findings show that the non-growing patch material remains in a low strain state throughout the simulation timeline, while experiencing high stress hot-spots. Arterial tissue growth along the surgical stitch lines is triggered mainly due to PA geometry and blood pressure, rather than due to material property differences in the artificial and native tissue. Thus, nonuniform growth patterns are observed along the arterial tissue proximal to the sutured boundaries. This computational approach is effective for the pre-surgical planning of complex patch surgeries to quantify the unbalanced growth of native arteries and artificial non-growing materials to develop optimal patch biomechanics for improved postoperative outcomes. (c) 2021 Published by Elsevier Ltd.