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You have accessJournal of UrologyImaging/Uroradiology II (MP30)1 May 2024MP30-11 IMMERSIVE VIRTUAL REALITY FOR PERCUTANEOUS NEPHROLITHOTOMY (PCNL): "THE MORE YOU KNOW, THE SAFER AND MORE EFFECTIVE THE OUTCOME" Andrei D. Cumpanas, Kalon L. Morgan, Mariah C. Hernandez, Amanda McCormac, Jacob C. Tsai, Jaime Altamirano Villaroel, Candice M. Tran, Bruce Gao, Zachary E. Tano, Roshan M. Patel, Pengbo Jiang, Jaime Landman, and Ralph V. Clayman Andrei D. CumpanasAndrei D. Cumpanas , Kalon L. MorganKalon L. Morgan , Mariah C. HernandezMariah C. Hernandez , Amanda McCormacAmanda McCormac , Jacob C. TsaiJacob C. Tsai , Jaime Altamirano VillaroelJaime Altamirano Villaroel , Candice M. TranCandice M. Tran , Bruce GaoBruce Gao , Zachary E. TanoZachary E. Tano , Roshan M. PatelRoshan M. Patel , Pengbo JiangPengbo Jiang , Jaime LandmanJaime Landman , and Ralph V. ClaymanRalph V. Clayman View All Author Informationhttps://doi.org/10.1097/01.JU.0001009416.90901.7b.11AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Understanding the CT-based renal anatomy and stone location are key for planning PCNL. Assimilating the nearly 2000 static images of the CT scan into a functional mental image to enable surgical planning is challenging. Herein, we assess whether viewing a pre-operative CT-based interactive immersive virtual reality (iVR) model would benefit PCNL surgical planning and outcome. METHODS: Between 2019-2022, 175 PCNL patients were pre-operatively randomized into a CT-only group (n=89) or a CT+iVR group (n=86). CT scans were rendered into iVR models using 3D Slicer. In the CT+iVR group, the surgeon was able to visualize and manipulate the relevant anatomy, as well as simulate the percutaneous approach to the proposed calyx of entry and its alignment with the stone (Figure 1). The four participating surgeons' understanding of the anatomy was compared using a Likert-scale survey. Post-operative 2-3 mm slice CT scans were defined as absolute stone-free, 2 mm remnants, 4 mm remnants. Post-operative complications were classified using the Clavien-Dindo system. RESULTS: Viewing the iVR model enhanced each surgeon's understanding of the peri-renal anatomy as well as the stone's location, size, and trans-calyceal access (all p<0.001). This resulted in a changed calyx of entry in 30% of cases. The CT+iVR patients had a significant improvement in absolute-stone-free rate (34% vs. 20%, p=0.043) and 4 mm remnant rate (62% vs. 48%, p=0.044) (Figure 2). Clavien II+IIIa post-operative complications significantly fell in the CT+iVR group (3.37% vs. 14.60%, p=0.009). There was a trend towards an increased volume of stone ablated per minute of surgery in the CT+iVR group (p=0.07). Multivariate analysis demonstrated that regardless of each surgeon's years of experience, iVR visualization improved their objective clinical outcomes. CONCLUSIONS: Pre-operative visualization of an iVR model resulted in a safer, more effective percutaneous stone removal procedure. The benefit was independent of the surgeon's years in practice. Download PPTDownload PPT Source of Funding: None © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e496 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Andrei D. Cumpanas More articles by this author Kalon L. Morgan More articles by this author Mariah C. Hernandez More articles by this author Amanda McCormac More articles by this author Jacob C. Tsai More articles by this author Jaime Altamirano Villaroel More articles by this author Candice M. Tran More articles by this author Bruce Gao More articles by this author Zachary E. Tano More articles by this author Roshan M. Patel More articles by this author Pengbo Jiang More articles by this author Jaime Landman More articles by this author Ralph V. Clayman More articles by this author Expand All Advertisement PDF downloadLoading ...
Cumpanas et al. (Mon,) studied this question.