Patient-specific simulations for planning treatment in congenital heart disease

Abstract

Patient-specific computational models have been extensively developed over the last decades and applied to investigate a wide range of cardiovascular problems. However, translation of these technologies into clinical applications, such as planning of medical procedures, has been limited to a few single case reports. Hence, the use of patient-specific models is still far from becoming a standard of care in clinical practice. The aim of this study is to describe our experience with a modelling framework that allows patient-specific simulations to be used for prediction of clinical outcomes. A cohort of 12 patients with congenital heart disease who were referred for percutaneous pulmonary valve implantation, stenting of aortic coarctation and surgical repair of double-outlet right ventricle was included in this study. Image data routinely acquired for clinical assessment were post-processed to set up patient-specific models and test device implantation and surgery. Finite-element and computational fluid dynamics analyses were run to assess feasibility of each intervention and provide some guidance. Results showed good agreement between simulations and clinical decision including feasibility, device choice and fluid-dynamic parameters. The promising results of this pilot study support translation of computer simulations as tools for personalization of cardiovascular treatments.

Use of 3D rotational angiography to perform computational fluid dynamics and virtual interventions in aortic coarctation

“…3DRA‐based cardiac CFD is the first step to perform virtual interventions real‐time in the CCL and to allow CFD to guide management decisions during cardiac catheterization. Previous cardiac predictive modeling has used pre‐procedural MRI or CTA . Our novel workflow could allow for CFD‐guided personalized management decisions even when pre‐procedural advanced imaging is not performed …”

“…Previous cardiac predictive modeling has used pre‐procedural MRI or CTA . Our novel workflow could allow for CFD‐guided personalized management decisions even when pre‐procedural advanced imaging is not performed …”

Putting machine learning into motion: applications in cardiovascular imaging

“…A recent application uses patient-specific segmentations of the heart and great vessels in children with congenital or acquired conditions prior to stenting or surgical repair. 26 For instance, this allows simulation of the deployment of stents, predicting stress distribution following implantation and confirmation of safe anchoring. A similar concept is being used to identify optimal lead placement in cardiac resynchronisation therapy using patient-specific in silico modelling of anatomy and physiology.…”

New Insights into Valve Hemodynamics

“…Suzuki et al 129 presented an in vitro experimental study of the hemodynamics in a polymeric pediatric pulmonary valve prosthesis. Capelli et al 130 used numerical models of patient-specific anatomies to predict the clinical outcomes of Melody valve implantation and found good agreement between their results and clinical fluid-dynamic parameters. Recently, Li et al 131 presented fluid-structure interaction models of pulmonary valve stenosis as a result of congenital bicuspid pulmonary valve.…”