3D Printing in Surgical Management of Double Outlet Right Ventricle.

Shi-Joon Yoo,Glen S Van Arsdell

doi:10.3389/fped.2017.00289

Shi-Joon Yoo, Glen S Van Arsdell

Open Access

https://doi.org/10.3389/fped.2017.00289

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Abstract

Double outlet right ventricle (DORV) is a heterogeneous group of congenital heart diseases that require individualized surgical approach based on precise understanding of the complex cardiovascular anatomy. Physical 3-dimensional (3D) print models not only allow fast and unequivocal perception of the complex anatomy but also eliminate misunderstanding or miscommunication among imagers and surgeons. Except for those cases showing well-recognized classic surgical anatomy of DORV such as in cases with a typical subaortic or subpulmonary ventricular septal defect, 3D print models are of enormous value in surgical decision and planning. Furthermore, 3D print models can also be used for rehearsal of the intended procedure before the actual surgery on the patient so that the outcome of the procedure is precisely predicted and the procedure can be optimally tailored for the patient’s specific anatomy. 3D print models are invaluable resource for hands-on surgical training of congenital heart surgeons.

Highlights

Double outlet right ventricle (DORV) has long been a contentious topic in congenital heart pathology and surgery [1]
DORV is defined as a type of ventriculoarterial connection in which both great arteries arise either entirely or predominantly from the right ventricle [1, 2]
We review the utility and future of 3D reconstruction and printing in surgical management of the patients with DORV based on our experience in the last 10 years and literature review [7,8,9,10]

Summary

Introduction

Double outlet right ventricle (DORV) has long been a contentious topic in congenital heart pathology and surgery [1]. There has been increasing utilization of computed tomography (CT) and magnetic resonance (MR) for clear demonstration of the surgical anatomy as both imaging modalities provide 3-dimensional (3D) volume data of the cardiovascular system with relatively high spatial and temporal resolutions.

Results

Conclusion