Semi-automated Generation and Hemodynamic Assessment of Surgical Baffle Geometry for Biventricular Repair

Patient-specific computational modeling has emerged as a powerful tool for surgical planning in complex congenital heart disease. One promising application is complex biventricular repair, which often requires construction of a custom intraventricular baffle to establish a physiologic left ventricle-to-aorta outflow pathway. In current practice, baffle geometry is designed and shaped intraoperatively. While existing preoperative modeling tools increasingly support visualization and virtual baffle design, the design process remains predominantly manual, and watertight models for quantitative hemodynamic assessment remain limited. We present a semi-automated computational framework for the design and assessment of patient-specific intraventricular baffles. The method constructs an explicit ventricular septal defect (VSD)-to-aorta flow pathway that preserves native right ventricular myocardial and VSD geometry while reshaping the baffle region to satisfy patient-specific, section-wise area constraints. We retrospectively applied this framework to four patients with double outlet right ventricle (DORV) who had previously undergone biventricular repair. Each generated pathway was evaluated with pulsatile computational fluid dynamics (CFD), producing peak-flow pressure differences of 1.58-5.94 mmHg under the prescribed flow conditions. All modeled pressure differences remained below the 10-mmHg planning benchmark across mesh resolutions and under elevated flow. The current implementation preserves the native VSD and does not model VSD enlargement or conal resection; however, it provides a computational framework through which these interventions could be evaluated in silico. By translating a surgeon-defined baffle boundary into a physiologically constrained, simulation-ready model, this approach enables quantitative preoperative design and CFD-based evaluation of candidate baffle geometries, advancing patient-specific computational planning for biventricular flow restoration in heterogeneous anatomies.