Abstract
Purpose: Profound endourological skills are required for optimal postoperative outcome parameters after transurethral resection of the prostate (TURP). We investigated the Karl Storz (Tuttlingen, Germany) UroTrainer for virtual simulation training of the TURP. Materials and Methods Twenty urologists underwent a virtual reality (VR) TURP training. After a needs analysis, performance scores and self-rated surgical skills were compared before and after the curriculum, the realism of the simulator was assessed, and the optimal level of experience for VR training was evaluated. Statistical testing was done with SPSS 25. Results: Forty percent of participants indicated frequent intraoperative overload during real-life TURP and 80% indicated that VR training might be beneficial for endourological skills development, underlining the need to advance classical endourological training. For the complete cohort, overall VR performance scores (P = 0.022) and completeness of resection (P < 0.001) significantly improved. Self-rated parameters including identification of anatomical structures (P = 0.046), sparing the sphincter (P = 0.002), and handling of the resectoscope (P = 0.033) became significantly better during the VR curriculum. Participants indicated progress regarding handling of the resectoscope (70%), bleeding control (55%), and finding the correct resection depth (50%). Although overall realism and handling of the resectoscope was good, virtual bleeding control and correct tissue feedback should be improved in future VR simulators. Seventy percent of participants indicated 10 to 50 virtual TURP cases to be optimal and 80% junior residents to be the key target group for VR TURP training. Conclusions: There is a need to improve training the TURP and VR simulators might be a valuable supplement, especially for urologists beginning with the endourological desobstruction of the prostate.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 1559-2332 |
Sprache: | Englisch |
Dokumenten ID: | 86591 |
Datum der Veröffentlichung auf Open Access LMU: | 25. Jan. 2022, 09:19 |
Letzte Änderungen: | 25. Jan. 2022, 09:19 |