Computational modeling and engineering in pediatric and congenital heart disease

Abstract

Purpose of review Recent methodological advances in computational simulations are enabling increasingly realistic simulations of hemodynamics and physiology, driving increased clinical utility. We review recent developments in the use of computational simulations in pediatric and congenital heart disease, describe the clinical impact in modeling in single ventricle patients, and provide an overview of emerging areas. Recent Findings Multiscale modeling combining patient specific hemodynamics with reduced order (i.e. mathematically and computationally simplified) circulatory models has become the defacto standard for modeling local hemodynamics and “global” circulatory physiology. We review recent advances that have enabled faster solutions, discuss new methods, (e.g. fluid structure interaction and uncertainty quantification), which lend realism both computationally and clinically to results, highlight novel computationally-derived surgical methods for single ventricle patients, and discuss areas in which modeling has begun to exert its influence including Kawasaki disease, fetal circulation, tetralogy of Fallot, (and pulmonary tree), and circulatory support. Summary Computational modeling is emerging as a crucial tool for clinical decision-making and evaluation of novel surgical methods and interventions in pediatric cardiology and beyond. Continued development of modeling methods, with an eye towards clinical needs, will enable clinical adoption in a wide range of pediatric and congenital heart diseases.

Computational modelling for congenital heart disease: how far are we from clinical translation?

“… 49 Nevertheless, it has been recently reiterated that it is essential to establish an impact on patients' outcomes if we are ultimately to demonstrate the usefulness of simulations for improved diagnostics, surgical planning or device implantation. 50 Despite colossal advances on the technical side since those first pioneering Fontan simulations, and despite the undeniable potential for simulations to enrich clinical practice with their predictive capabilities, questions still remain to be answered. Will the uptake of simulation improve clinical success in treating patients with CHD?…”

A Patient-Specific CFD Pipeline Using Doppler Echocardiography for Application in Coarctation of the Aorta in a Limited Resource Clinical Context

“…Hence, research in patientspecific computational hemodynamics has been directed toward identifying a link between flow metrics such as pressure, velocity and wall shear stress (WSS), and the development of other cardiac lesions and recoarctation. Computational fluid dynamics (CFD) is seen as an important tool in this regard due to its high resolution of flow detail, by providing the capability to conduct in silico studies of different repairs and through incorporating predictive mathematical models for vascular growth and remodeling (Marsden and Feinstein, 2015;Capelli et al, 2018).…”

Patient-specific simulations for planning treatment in congenital heart disease

“…Patient-specific computational tools which combine the advances in the field of clinical imaging and processing, and finite-element (FE) and computational fluid dynamics (CFD) analyses with individual patient data on anatomy and function have greatly supported not only the understanding of human cardiac physiology and pathology, but, by taking into account realistic conditions, also the development of novel interventions and treatments [ 2 , 3 ], thus fostering personalized and precision medicine [ 4 , 5 ]. Bespoke treatment approaches are particularly relevant in the context of congenital heart disease (CHD) as, compared to adult patients with acquired diseases, children born with cardiovascular defects typically present a wide range of different anatomies and conditions that are sometimes unique and extremely complex [ 6 ]. Furthermore, with an increasing number of devices available on the market, the choice of the optimal treatment is not always straightforward and the availability of additional predictive tools such as patient-specific computational simulations may become crucial.…”