ArticleJMIR serious games2023
Advantages of a Training Course for Surgical Planning in Virtual Reality for Oral and Maxillofacial Surgery: Crossover Study.
Article in JMIR serious games, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06967090 (Accuracy of Guided Implant Placement Using Artificial Intelligence Segmentation Versus Conventional Technique), which is not on this map. Cited by 9 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Accuracy of Guided Implant Placement Using Artificial Intelligence Segmentation Versus Conventional Technique: A Randomized Clinical Trial
Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Augmented and virtual reality in dental and oral and maxillofacial surgery education: a systematic review with a taxonomy of training technologies.BMC medical education · 2026Pooled it
- Effectiveness of Mixed Reality in Oral Surgery Training: A Systematic Review.Sensors (Basel, Switzerland) · 2025Pooled it
- Development and validation of collaborative robot-assisted cutting method for iliac crest flap raising: Randomized crossover trial.Scientific reports · 2025Trial
- Evaluating Osteotomy Accuracy in Mandibular Reconstruction: A Preliminary Study Using Custom Cutting Guides and Virtual Reality.Diseases (Basel, Switzerland) · 2025Article
- Fetal heart segmentation in a virtual reality environment.The international journal of cardiovascular imaging · 2025Article
- Segmentation of the iliac crest from CT-data for virtual surgical planning of facial reconstruction surgery using deep learning.Scientific reports · 2025Article
- Virtual reality for preoperative patient education: Impact on satisfaction, usability, and burnout from the perspective of new nurses.World journal of clinical cases · 2024Article
- Characterizing the untapped potential of virtual reality in plastic and reconstructive surgical training: A systematic review on skill transferability.JPRAS open · 2024Review
- Application of artificial intelligence-assisted image diagnosis software based on volume data reconstruction technique in medical imaging practice teaching.BMC medical education · 2024Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAs an integral part of computer-assisted surgery, virtual surgical planning (VSP) leads to significantly better surgery results, such as for oral and maxillofacial reconstruction with microvascular grafts of the fibula or iliac crest. It is performed on a 2D computer desktop screen (DS) based on preoperative medical imaging. However, in this environment, VSP is associated with shortcomings, such as a time-consuming planning process and the requirement of a learning process. Therefore, a virtual reality (VR)-based VSP application has great potential to reduce or even overcome these shortcomings due to the benefits of visuospatial vision, bimanual interaction, and full immersion. However, the efficacy of such a VR environment has not yet been investigated.
objectiveThis study aimed to demonstrate the possible advantages of a VR environment through a substep of VSP, specifically the segmentation of the fibula (calf bone) and os coxae (hip bone), by conducting a training course in both DS and VR environments and comparing the results.
methodsDuring the training course, 6 novices were taught how to use a software application in a DS environment (3D Slicer) and in a VR environment (Elucis) for the segmentation of the fibula and os coxae, and they were asked to carry out the maneuvers as accurately and quickly as possible. Overall, 13 fibula and 13 os coxae were segmented for each participant in both methods (VR and DS), resulting in 156 different models (78 fibula and 78 os coxae) per method (VR and DS) and 312 models in total. The individual learning processes in both environments were compared using objective criteria (time and segmentation performance) and self-reported questionnaires. The models resulting from the segmentation were compared mathematically (Hausdorff distance and Dice coefficient) and evaluated by 2 experienced radiologists in a blinded manner.
resultsA much faster learning curve was observed for the VR environment than the DS environment (β=.86 vs β=.25). This nearly doubled the segmentation speed (cm
conclusionsThe more rapid learning process and the ability to work faster in the VR environment could save time and reduce the VSP workload, providing certain advantages over the DS environment.
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