Designing patient-specific virtual phantoms for pediatric patients with congenital heart disease

Congenital Heart Disease (CHD) is the most common birth defect worldwide, affecting millions of newborns yearly. Pulmonary artery stenosis is a narrowing around the pulmonary valve that restricts blood flow to the lungs and can lead to heart failure if untreated. Current treatment uses stents to support blood flow, but this lacks long-term effectiveness for children and newborns. The purpose of our work is to leverage a comprehensive database of pediatric phantoms based on biomechanical simulation to simulate stent placement preoperatively. We segmented patient anatomies using TotalSegmentator with additional refinements, then reconstructed them using the RFTA algorithm. This approach reduced geometric error by 73% on average compared to Marching Cubes (measured by Chamfer distance and Hausdorff distance) while maintaining fine details. For non-rigid deformation, we used the SyN algorithm in ANTs, which achieved high normalized cross-correlation values of 91.89% to 95.09% as well as a mutual information score of 45.93% to 79.13%, showcasing strong alignment between the warped template and patient images. Our resulting library of patient-specific phantoms enables preoperative stent placement simulation. This framework supports personalized planning for pediatric CHD interventions, aiming to improve stent performance and reduce restenosis.