Parameter selection and optimization of a computational network model of blood flow in single-ventricle patients

TL;DR

This paper presents a computational framework combining imaging data and fluid dynamics to predict hemodynamic features in single-ventricle patients, revealing differences in vascular properties compared to control patients.

Contribution

It introduces a patient-specific modeling approach for predicting unmeasured hemodynamics in HLHS patients using parameter inference and CFD simulations.

Findings

HLHS patients exhibit higher vascular stiffness and lower compliance.

Predicted WSS and WI differ between HLHS and control patients.

Model accurately predicts pressure and flow features from limited imaging data.

Abstract

Hypoplastic left heart syndrome (HLHS) is a congenital heart disease responsible for 23% of infant cardiac deaths each year. HLHS patients are born with an underdeveloped left heart, requiring several surgeries to reconstruct the aorta and create a single ventricle circuit known as the Fontan circulation. While survival into early adulthood is becoming more common, Fontan patients suffer from reduced cardiac output, putting them at risk for a multitude of complications. These patients are monitored using chest and neck MRI imaging, but these scans do not capture energy loss, pressure, wave intensity, or hemodynamics beyond the imaged region. This study develops a framework for predicting these missing features by combining imaging data and computational fluid dynamics (CFD) models. Predicted features from models of HLHS patients are compared to those from control patients with a double outlet right ventricle (DORV). We use parameter inference to render the model patient-specific. In the calibrated model, we predict pressure, flow, wave-intensity (WI), and wall shear stress (WSS). Results reveal that HLHS patients have higher vascular stiffness and lower compliance than DORV patients, resulting in lower WSS and higher WI in the ascending aorta and increased WSS and decreased WI in the descending aorta.