ArticleJTCVS techniques2022
State-of-the-art silicone molded models for simulation of arterial switch operation: Innovation with parting-and-assembly strategy.
Article in JTCVS techniques, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Patient-specific silicone aortic model using 3D printing for Coselli graft planning in open thoracoabdominal aortic aneurysm repair.Journal of vascular surgery cases and innovative techniques · 2026Article
- Expanding the use of 3D printing in congenital heart surgery.Translational pediatrics · 2025Review
- The Pocket Strabismus Surgical Skills Trainer: design and validation.Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus · 2025Article
- Congenital cardiac surgical simulation: bridging global workforce gaps and optimizing outcomes.Future cardiology · 2025Review
- Evaluation of the Efficacy and Accuracy of Super-Flexible Three-Dimensional Heart Models of Congenital Heart Disease Made via Stereolithography Printing and Vacuum Casting: A Multicenter Clinical Trial.Journal of cardiovascular development and disease · 2024Article
- Longitudinal Evaluation of Congenital Cardiovascular Surgical Performance and Skills Retention Using Silicone-Molded Heart Models.World journal for pediatric & congenital heart surgery · 2024Article
- Partial heart transplantation of atrioventricular valves in complete atrioventricular septal defect-simulation of techniques using silicone-molded heart models.JTCVS techniques · 2023Article
- New operations for truncus arteriosus repair using partial heart transplantation: Exploring the surgical design space with 3-dimensional printed heart models.JTCVS techniques · 2023Article
- Patient-Specific 3D-Printed Models in Pediatric Congenital Heart Disease.Children (Basel, Switzerland) · 2023Review
- Congenital Heart Surgery Skill Training Using Simulation Models: Not an Option but a Necessity.Journal of Korean medical science · 2022Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Three-dimensional (3D) printed models are widely accepted for use in training of various surgical procedures for congenital heart disease; however, their physical properties have been considered suboptimum for procedures. We created silicone molded models produced using a novel "parting and assembly" strategy and compared their suitability for hands-on training with that of conventional 3D printed models. Methods: Computed tomography imaging data from 2 patients with transposition of the great arteries were used. The heart was divided into multiple parts (atria, ventricles, great arteries, coronary arteries, and valves), and molds of each part were created. The parts reproduced by silicone molding were assembled using an adhesive agent. In an online course, 2 silicone molded models and 1 3D printed model were used for training of 34 surgeons. A questionnaire was distributed to these surgeons aimed at assessing the suitability of the models for the arterial switch operation (ASO). Results: The silicone molded models showed excellent anatomic detail, high elasticity, and high resistance to tearing. The cost per model, based on the production of 50 models, was slightly higher for the silicone molded models compared with the 3D printed models. All 26 surgeons who completed the questionnaire reported that the silicone molded models provided sufficient anatomic information, but only 19% said the same for the 3D printed models. All surgeons also considered the silicone models to be realistic when passing a needle, cutting vessels, suturing, and excision of the coronary buttons, as opposed to <46% for the 3D printed models. Conclusions: Silicone molding of models for the ASO is feasible by applying a "parting and assembly" strategy. Silicone molded models provide excellent physical properties that are far superior to those of 3D printed models for surgical simulation.
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