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Evaluation of Interactive Virtual Reality as a Preoperative Aid in Localizing Renal Tumors
Shlomi Tapiero1, Rajiv Karani1, Luke Limfueco1
1Department of Urology, University of California, Irvine, Orange, California, USA.
Abstract:
A detailed understanding of renal tumor anatomy is required to perform partial nephrectomy. We evaluated the utility of a CT-based interactive virtual reality (iVR) display to assist surgeons' understanding of the precise location of the renal tumor. CT scans and iVR models of 11 patients with a mean R.E.N.A.L. nephrometry score of 6.9 were evaluated. Seven faculty urologists and six urology residents reviewed CT scans and positioned each tumor onto a digital three-dimensional model of the same kidney, although without the tumor present. A week later, participants repeated the session using both iVR models and CT scans. For both time points, the overlap between the surgeon-inserted tumor and the actual tumor location was calculated. Participants answered a 1 to 10 Likert scale survey to gauge their understanding of renal and tumor anatomy based on CT alone vs CT+iVR. Median tumor overlap for the entire cohort was 28% after CT review and 42% after CT+iVR (p = 0.05); among faculty urologists, for CT+iVR vs CT alone, percentage overlap improved (47% vs 33%, p = 0.033) and the incidence of 0% overlap decreased (19%-4%, p = 0.024), respectively. Among residents, there was no significant difference for either percentage overlap or 0% overlap for CT vs CT+iVR. The percentage overlap for the two tumors with high R.E.N.A.L. nephrometry scores (i.e., 10) increased from 51% to 67% after using CT+iVR (p = 0.039). The combination of CT+iVR was an independent predictor of improved overlap vs CT alone (odds ratio 2.22, 95% confidence interval 1.04-4.78, p = 0.039). Faculty surgeons' survey responses showed an improved understanding of the tumor location and shape with the addition of iVR (p < 0.05). The addition of patient-specific iVR models to standard CT imaging improved the ability of faculty urologists to accurately configure the location of a renal tumor, and improved their understanding of tumor anatomy.
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