Open Access

ARTICLE

A New Three-Dimensional (3D) Printing Prepress Algorithm for Simulation of Planned Surgery for Congenital Heart Disease

Vitaliy Suvorov^1,2,*, Olga Loboda², Maria Balakina¹, Igor Kulczycki²

1 Department of Surgical Diseases of Children, Saint Petersburg State Pediatric Medical University, Saint Petersburg, Russia
2 Higher School of Theoretical Mechanics, Peter the Great Saint Petersburg Polytechnic University, Saint Petersburg, Russia

* Corresponding Author: Vitaliy Suvorov. Email:

Congenital Heart Disease 2023, 18(5), 491-505. https://doi.org/10.32604/chd.2023.030583

Received 13 April 2023; Accepted 16 June 2023; Issue published 10 November 2023

Abstract

Background: Three-dimensional printing technology may become a key factor in transforming clinical practice and in significant improvement of treatment outcomes. The introduction of this technique into pediatric cardiac surgery will allow us to study features of the anatomy and spatial relations of a defect and to simulate the optimal surgical repair on a printed model in every individual case. Methods: We performed the prospective cohort study which included 29 children with congenital heart defects. The hearts and the great vessels were modeled and printed out. Measurements of the same cardiac areas were taken in the same planes and points at multislice computed tomography images (group 1) and on printed 3D models of the hearts (group 2). Pre-printing treatment of the multislice computed tomography data and 3D model preparation were performed according to a newly developed algorithm. Results: The measurements taken on the 3D-printed cardiac models and the tomographic images did not differ significantly, which allowed us to conclude that the models were highly accurate and informative. The new algorithm greatly simplifies and speeds up the preparation of a 3D model for printing, while maintaining high accuracy and level of detail. Conclusions: The 3D-printed models provide an accurate preoperative assessment of the anatomy of a defect in each case. The new algorithm has several important advantages over other available programs. They enable the development of customized preliminary plans for surgical repair of each specific complex congenital heart disease, predict possible issues, determine the optimal surgical tactics, and significantly improve surgical outcomes.

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Graphical Abstract

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