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Proceedings Paper

Workflow for creation and evaluation of virtual nephrolithotomy training models
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Paper Abstract

PURPOSE: Virtual reality (VR) simulation is an effective training system for medical residents, allowing them to gain and improve upon surgical skills in a realistic environment while also receiving feedback on their performance. Percutaneous nephrolithotomy is the most common surgical treatment for the removal of renal stones. We propose a workflow to generate 3D soft tissue and bone models from computed tomography (CT) images, to be used and validated in a VR nephrolithotomy simulator. METHODS: Venous, delay, non-contrast, and full body CT scans were registered and segmented to generate 3D models of the abdominal organs, skin, and bone. These models were decimated and re-meshed into low-polygon versions while maintaining anatomical accuracy. The models were integrated into a nephrolithotomy simulator with haptic feedback and scoring metrics. Urology surgical experts assessed the simulator and its validity through a questionnaire based on a 5-point Likert scale. RESULTS: The workflow produced soft tissue and bone models from patient CT scans, which were integrated into the simulator. Surgeon responses indicated level 3 and above for face validity and level 4 and above for all other aspects of medical simulation validity: content, construct, and criterion. CONCLUSION: We designed an effective workflow to generate 3D models from CT scans using open source and modelling software. The low resolution of these models allowed integration in a VR simulator for visualization and haptic feedback, while anatomical accuracy was maintained.

Paper Details

Date Published: 16 March 2020
PDF: 7 pages
Proc. SPIE 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, 1131524 (16 March 2020); doi: 10.1117/12.2549354
Show Author Affiliations
Catherine O. Wu, Queen's Univ. (Canada)
Kyle Sunderland, Queen's Univ. (Canada)
Mihail Filippov, Marion Surgical (Canada)
Ben Sainsbury, Marion Surgical (Canada)
Gabor Fichtinger, Queen's Univ. (Canada)
Tamas Ungi, Queen's Univ. (Canada)


Published in SPIE Proceedings Vol. 11315:
Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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