A Virtual Reality Environment to Visualize Three-Dimensional Patient-Specific Models by a Mobile Head-Mounted Display

• Published in: Surgical innovation 2019-06, Vol.26 (3), p.359-370
• Main Authors: Vertemati, Maurizio, Cassin, Simone, Rizzetto, Francesco, Vanzulli, Angelo, Elli, Marco, Sampogna, Gianluca, Gallieni, Maurizio
• Format: Article
• Language: English
• Subjects: Equipment Design; Humans; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Software; Surgery, Computer-Assisted - instrumentation; Surveys and Questionnaires; Tomography, X-Ray Computed; User-Computer Interface; Virtual Reality
• ISSN: 1553-3506; 1553-3514
• DOI: 10.1177/1553350618822860

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.