(Tuesday, 7/31/2018) 4:30 PM - 5:30 PM
Room: Exhibit Hall | Forum 2
Purpose: To develop and evaluate the utility of a virtual reality (VR)-based radiotherapy treatment planning platform for planning and plan evaluation activities.
Methods: A VR-based 3-dimensional (3D) image and contour viewing platform was developed for the HTC Vive using the Unity game engine. The process for extracting and preprocessing treatment planning CT images and structures from the host treatment planning system (TPS) for import into the Unity application was automated with in-house software. Using handheld Vive controllers, users manipulate 3D wire-frame contours and, with a virtual 2D image plane that can be repositioned in any arbitrary orientation, sample the 3D space containing scan set and color-filled structure volumes.Four medical physicists with varying levels of clinical experience sequentially assessed individual structure contours for six contoured scan sets in both VR and the TPS. The structure sets were duplicated between the platforms with a single, unambiguous error added to one structure in each version. The time to correctly assess the error-free subset of structures common between the duplicated sets was measured. Users were also asked to rate their familiarity with each platform on a scale of 0 to 10.
Results: The time to assess the error-free subset of structures for each scan set varied between users and between platforms, with some users performing faster in VR and others in our main TPS. Across users, as the difference in rated familiarity approached zero, relative performance in VR increased with the most familiar user being twice as fast, on average, in VR compared to the planning system.
Conclusion: The relationship between timing and familiarity suggests that for users equally familiar with both platforms, radiotherapy scan and structure sets may be more intuitively viewed in VR, suggesting that VR platforms may improve radiotherapy treatment planning activities.
Keywords
3D, Computer Software, Image Visualization
Taxonomy
IM/TH- image segmentation: General (Most aspects)
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