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      A Novel Virtual Reality Medical Image Display System for Group Discussions of Congenital Heart Disease: Development and Usability Testing

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          Abstract

          Background

          The complex 3-dimensional (3D) nature of anatomical abnormalities in congenital heart disease (CHD) necessitates multidisciplinary group discussions centered around the review of medical images such as magnetic resonance imaging. Currently, group viewings of medical images are constrained to 2-dimensional (2D) cross-sectional displays of 3D scans. However, 2D display methods could introduce additional challenges since they require physicians to accurately reconstruct the images mentally into 3D anatomies for diagnosis, staging, and planning of surgery or other therapies. Virtual reality (VR) software may enhance diagnosis and care of CHD via 3D visualization of medical images. Yet, present-day VR developments for medicine lack the emphasis on multiuser collaborative environments, and the effect of displays and level of immersion for diagnosing CHDs have not been studied.

          Objective

          The objective of the study was to evaluate and compare the diagnostic accuracies and preferences of various display systems, including the conventional 2D display and a novel group VR software, in group discussions of CHD.

          Methods

          A total of 22 medical trainees consisting of 1 first-year, 10 second-year, 4 third-year, and 1 fourth-year residents and 6 medical students, who volunteered for the study, were formed into groups of 4 to 5 participants. Each group discussed three diagnostic cases of CHD with varying structural complexity using conventional 2D display and group VR software. A group VR software, Cardiac Review 3D, was developed by our team using the Unity engine. By using different display hardware, VR was classified into nonimmersive and full-immersive settings. The discussion time, diagnostic accuracy score, and peer assessment were collected to capture the group and individual diagnostic performances. The diagnostic accuracies for each participant were scored by two experienced cardiologists following a predetermined answer rubric. At the end of the study, all participants were provided a survey to rank their preferences of the display systems for performing group medical discussions.

          Results

          Diagnostic accuracies were highest when groups used the full-immersive VR compared with the conventional and nonimmersive VR (χ 2 2=9.0, P=.01) displays. Differences between the display systems were more prominent with increasing case complexity (χ 2 2=14.1, P<.001) where full-immersive VR had accuracy scores that were 54.49% and 146.82% higher than conventional and nonimmersive VR, respectively. The diagnostic accuracies provided by the two cardiologists for each participant did not statistically differ from each other ( t=–1.01, P=.31). The full-immersive VR was ranked as the most preferred display for performing group CHD discussions by 68% of the participants.

          Conclusions

          The most preferred display system among medical trainees for visualizing medical images during group diagnostic discussions is full-immersive VR, with a trend toward improved diagnostic accuracy in complex anatomical abnormalities. Immersion is a crucial feature of displays of medical images for diagnostic accuracy in collaborative discussions.

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          Most cited references48

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          Heart Disease and Stroke Statistics—2015 Update: A Report From the American Heart Association

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            Medical 3D Printing for the Radiologist.

            While use of advanced visualization in radiology is instrumental in diagnosis and communication with referring clinicians, there is an unmet need to render Digital Imaging and Communications in Medicine (DICOM) images as three-dimensional (3D) printed models capable of providing both tactile feedback and tangible depth information about anatomic and pathologic states. Three-dimensional printed models, already entrenched in the nonmedical sciences, are rapidly being embraced in medicine as well as in the lay community. Incorporating 3D printing from images generated and interpreted by radiologists presents particular challenges, including training, materials and equipment, and guidelines. The overall costs of a 3D printing laboratory must be balanced by the clinical benefits. It is expected that the number of 3D-printed models generated from DICOM images for planning interventions and fabricating implants will grow exponentially. Radiologists should at a minimum be familiar with 3D printing as it relates to their field, including types of 3D printing technologies and materials used to create 3D-printed anatomic models, published applications of models to date, and clinical benefits in radiology. Online supplemental material is available for this article.
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              Medical Applications for 3D Printing: Current and Projected Uses.

              3D printing is expected to revolutionize health care through uses in tissue and organ fabrication; creation of customized prosthetics, implants, and anatomical models; and pharmaceutical research regarding drug dosage forms, delivery, and discovery.
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                Author and article information

                Contributors
                Journal
                JMIR Cardio
                JMIR Cardio
                JCARD
                JMIR Cardio
                JMIR Publications (Toronto, Canada )
                2561-1011
                Jan-Dec 2020
                8 December 2020
                : 4
                : 1
                : e20633
                Affiliations
                [1 ] University of Maryland College Park, MD United States
                [2 ] Children's National Hospital Washington, DC United States
                [3 ] Indicated LLC New York City, NY United States
                Author notes
                Corresponding Author: Byeol Kim star@ 123456umd.edu
                Author information
                https://orcid.org/0000-0001-8289-9424
                https://orcid.org/0000-0003-1003-1903
                https://orcid.org/0000-0002-5778-9300
                https://orcid.org/0000-0003-0376-9918
                https://orcid.org/0000-0001-5948-0182
                https://orcid.org/0000-0002-3783-0783
                https://orcid.org/0000-0001-8169-075X
                Article
                v4i1e20633
                10.2196/20633
                7755535
                33289675
                02a4a4dd-f31b-4509-aec2-cafebc87b925
                ©Byeol Kim, Yue-Hin Loke, Paige Mass, Matthew R Irwin, Conrad Capeland, Laura Olivieri, Axel Krieger. Originally published in JMIR Cardio (http://cardio.jmir.org), 08.12.2020.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Cardio, is properly cited. The complete bibliographic information, a link to the original publication on http://cardio.jmir.org, as well as this copyright and license information must be included.

                History
                : 31 May 2020
                : 18 August 2020
                : 12 October 2020
                : 24 October 2020
                Categories
                Original Paper
                Original Paper

                virtual reality,cardiac diagnostics,usability study,congenital heart disease,group collaboration

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