Precision planning in congenital heart disease: the impact of 3D printing and virtual simulation.

Authors

Khadijah Maghrabi, Osman Al-Radi

Published in

3D printing in medicine. Jul 13, 2026. Epub Jul 13, 2026.

Abstract

Surgical planning in complex congenital heart disease (CHD) often involves challenging decisions between univentricular and biventricular repair. Traditional imaging modalities such as echocardiography, CT, MRI, and angiography provide detailed data but lack intuitive three-dimensional spatial visualization. This study aimed to establish a low-cost, scalable 3D modeling and surgical simulation approach for broader access to this technology in mid-sized or resource-limited pediatric cardiology centers.
We retrospectively studied 25 patients with complex CHD who underwent 3D modeling to assess suitability for biventricular repair. Patient-specific cardiac models were generated using open-source segmentation and post-processing software and fabricated using a desktop stereolithography (SLA) Formlabs 3D printer. Surgical baffles were simulated digitally and incorporated into the models to assess the feasibility of biventricular repair. Models were reviewed in multidisciplinary team meetings and shared online via a 3D viewing platform (Sketchfab) to allow remote consultation.
Of the 25 patients evaluated, 14 (56%) underwent a change in surgical strategy from univentricular to biventricular repair after review of the 3D models and simulated baffles. All patients who underwent revised biventricular repair had favorable short-term outcomes. The cost of model production ranged from USD 350 to 480 per patient, significantly lower than traditional outsourced workflows. The approach enabled improved spatial understanding of cardiac anatomy and facilitated collaborative decision-making across institutions.
Low-cost 3D printed models can significantly impact surgical planning in complex CHD, increasing the feasibility of biventricular repair and reducing reliance on univentricular pathways.

PMID:
42440200
Bibliographic data and abstract were imported from PubMed on 13 Jul 2026.

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