Image-driven, patient specific, direct numerical simulations of the right ventricle in congenital heart diseases

Analyzing intracardiac flow dynamics is vital for diagnosing and managing congenital heart defects, as flow patterns reveal disease progression and help guide treatment. While 4D flow MRI allows non-invasive assessment, its limited spatial and temporal resolution hinders capturing fine-scale flow features and derived metrics such as vorticity. These limitations are especially critical in pediatric patients, where small structures require higher resolution. To address this, high-fidelity computational models integrating electrophysiology, tissue mechanics, and hemodynamics have been developed. However, including multi-physics interactions significantly increases computational cost and relies on material parameters that may not reflect patient-specific conditions. A more practical alternative involves prescribing kinematics directly from patient-specific imaging data, replacing the need for full multi-physics modeling. This approach preserves flow fidelity while substantially reducing computational cost, enabling faster and individualized analysis. Despite these advances, accurately reconstructing thin, dynamic structures such as the tricuspid valve (TV) remains a major challenge, as they are often poorly resolved in conventional imaging. Most existing models rely on generalized material properties, limiting applicability to individual patients. In this study, we present a novel, patient-specific kinematic framework for the right heart, where TV motion and boundary conditions are derived from 4D-MRI data. The right ventricle (RV) and right atrium (RA) were segmented and registered using 3D Slicer, and kinematics was prescribed using the Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework. We conducted direct numerical simulations (DNS) using an in-house solver based on the Immersed Boundary Method (IBM) to solve the incompressible Navier–Stokes equations. DNS results for healthy cases showed strong agreement with 4D-MRI in both the qualitative comparison of diastolic filling and the quantitative metrics. The workflow was also extended to Tetralogy of Fallot (TOF) cases.