A Novel Virtual Reality Medical Image Display System for Group Discussions of Congenital Heart Disease: Development and Usability Testing
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Résumé
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: =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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Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle