A Virtual Reality Environment to Visualize Three-Dimensional Patient-Specific Models by a Mobile Head-Mounted Display. (June 2019)

• Record Type: Journal Article
• Authors: Vertemati, Maurizio; Cassin, Simone; Rizzetto, Francesco; Vanzulli, Angelo; Elli, Marco; Sampogna, Gianluca; Gallieni, Maurizio
• Is Part Of: Surgical innovation. Volume 26:Number 3(2019)
• Page Start: 359
• Page End: 370
• Publication Date: 2019-06
• Subjects: virtual reality -- anatomy -- training -- mobile -- head-mounted display; Surgery, Operative -- Periodicals; Endoscopic surgery -- Periodicals; Laparoscopic surgery -- Periodicals; Surgical Procedures, Operative -- Periodicals; Surgical Procedures, Minimally Invasive -- Periodicals; Diffusion of Innovation -- Periodicals; Chirurgie opératoire -- Périodiques; Chirurgie endoscopique -- Périodiques; Chirurgie laparoscopique -- Périodiques; 617.91
• DOI: 10.1177/1553350618822860
• Languages: English
• ISSNs: 1553-3506

Abstract

Introduction . With the availability of low-cost head-mounted displays (HMDs), virtual reality environments (VREs) are increasingly being used in medicine for teaching and clinical purposes. Our aim was to develop an interactive, user-friendly VRE for tridimensional visualization of patient-specific organs, establishing a workflow to transfer 3-dimensional (3D) models from imaging datasets to our immersive VRE. Materials and Methods . This original VRE model was built using open-source software and a mobile HMD, Samsung Gear VR. For its validation, we enrolled 33 volunteers: morphologists (n = 11), trainee surgeons (n = 15), and expert surgeons (n = 7). They tried our VRE and then filled in an original 5-point Likert-type scale 6-item questionnaire, considering the following parameters: ease of use, anatomy comprehension compared with 2D radiological imaging, explanation of anatomical variations, explanation of surgical procedures, preoperative planning, and experience of gastrointestinal/neurological disorders. Results in the 3 groups were statistically compared using analysis of variance. Results . Using cross-sectional medical imaging, the developed VRE allowed to visualize a 3D patient-specific abdominal scene in 1 hour. Overall, the 6 items were evaluated positively by all groups; only anatomy comprehension was statistically significant different among the 3 groups. Conclusions . Our approach, based on open-source software and mobile hardware, proved to be a valid and well-appreciated system to visualize 3D patient-specific models, paving the way for a potential new tool for teaching and preoperative planning.