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Raimondi F, Vida V, Godard C, et al. Fast-track virtual reality for cardiac imaging in congenital heart disease. J Card Surg. 2021;36(7):2598-2602doi: 10.1111/jocs.15508.
Raimondi, F., Vida, V., Godard, C., Bertelli, F., Reffo, E., Boddaert, N., El Beheiry, M., & Masson, J. B. (2021). Fast-track virtual reality for cardiac imaging in congenital heart disease. Journal of cardiac surgery, 36(7), 2598-2602. https://doi.org/10.1111/jocs.15508
Raimondi, Francesca, et al. "Fast-track virtual reality for cardiac imaging in congenital heart disease." Journal of cardiac surgery vol. 36,7 (2021): 2598-2602. doi: https://doi.org/10.1111/jocs.15508
Raimondi F, Vida V, Godard C, Bertelli F, Reffo E, Boddaert N, El Beheiry M, Masson JB. Fast-track virtual reality for cardiac imaging in congenital heart disease. J Card Surg. 2021 Jul;36(7):2598-2602. doi: 10.1111/jocs.15508. Epub 2021 Mar 24. PMID: 33760302.
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J Card Surg. 2021 Jul;36(7):2598-2602. doi: 10.1111/jocs.15508. Epub 2021 Mar 24.

Fast-track virtual reality for cardiac imaging in congenital heart disease.

Journal of cardiac surgery

Francesca Raimondi, Vladimiro Vida, Charlotte Godard, Francesco Bertelli, Elena Reffo, Nathalie Boddaert, Mohamed El Beheiry, Jean-Baptiste Masson

Affiliations

  1. Unité médico-chirurgicale de cardiologie congénitale et pédiatrique, centre de référence des maladies cardiaques congénitales complexes-M3C, Hôpital universitaire Necker-Enfants Malades, Université de Paris, France.
  2. Decision and Bayesian Computation, Computation Biology Department, CNRS, URS 3756, Neuroscience Department, CNRS UMR 3571, Institut Pasteur, Paris, France.
  3. Pediatric Radiology Unit, Hôpital universitaire Necker-Enfants Malades, Université de Paris, France.
  4. Pediatric and Congenital Cardiac Surgery Unit, University of Padua, Italy.
  5. Pediatric Cardiology Unit, University of Padua, Italy.

PMID: 33760302 DOI: 10.1111/jocs.15508

Abstract

BACKGROUND AND AIM OF THE STUDY: We sought to evaluate the appropriateness of cardiac anatomy renderings by a new virtual reality (VR) technology, entitled DIVA, directly applicable to raw magnetic resonance imaging (MRI) data without intermediate segmentation steps in comparison to standard three-dimensional (3D) rendering techniques (3D PDF and 3D printing). Differences in post-processing times were also evaluated.

METHODS: We reconstructed 3D (STL, 3D-PDF, and 3D printed ones) and VR models of three patients with different types of complex congenital heart disease (CHD). We then asked a senior pediatric heart surgeon to compare and grade the results obtained.

RESULTS: All anatomical structures were well visualized in both VR and 3D PDF/printed models. Ventricular-arterial connections and their relationship with the great vessels were better visualized with the VR model (Case 2); aortic arch anatomy and details were also better visualized by the VR model (Case 3). The median post-processing time to get VR models using DIVA was 5 min in comparison to 8 h (range 8-12 h including printing time) for 3D models (PDF/printed).

CONCLUSIONS: VR directly applied to non-segmented 3D-MRI data set is a promising technique for 3D advanced modeling in CHD. It is systematically more consistent and faster when compared to standard 3D-modeling techniques.

© 2021 Wiley Periodicals LLC.

Keywords: 3D reconstruction; congenital heart disease; surgical planning; virtual reality

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