Robot-assisted radical prostatectomy using the novel hinotori(TM) surgical robot system: initial experience and operation learning curve at a single institution

使用新型hinotori™手术机器人系统进行机器人辅助根治性前列腺切除术:单中心初步经验及手术学习曲线

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Abstract

BACKGROUND: The hinotori(TM) surgical robot system (HSRS) is the first made-in-Japan robotic system used for radical prostatectomy. Here, we report initial results and describe our learning curve (skill development) implementing robot-assisted radical prostatectomy using HSRS (h-RARP). METHODS: Between November 2021 and December 2022, 97 patients who underwent h-RARP at our institution were enrolled in this study. We retrospectively evaluated the surgical outcomes of the initial cases using h-RARP, comparing those of RARP using da Vinci surgical robot system (d-RARP) in our institution. Furthermore, the learning curves of two surgeons with the highest number of h-RARP were analyzed. Patients treated by each surgeon were categorized into two groups: 1-15 cases (earlier group) and >15 cases (later group). Preoperative patient characteristics, operation parameters, and complication rates were compared between the two groups. RESULTS: In terms of surgical outcome, h-RARP was comparable to d-RARP. The procedures performed by the HSRS were successfully completed in all cases. There was no complication of grade 3 or higher. Comparing the two surgeons, surgeon 1, who had performed 40 d-RARP procedures, had time using robot system of the later group that was significantly shorter than that of the earlier group. However, for surgeon 2 with more than 100 d-RARP procedures, there was no statistically significant difference in time using robot system between groups. Other parameters showed no difference between earlier and later groups for the two surgeons. CONCLUSIONS: Our results show that surgical outcomes of h-RARP are comparable to those of d-RARP during the initial experience of clinical application. In addition, the surgeons' learning curves for the total RARP experience suggest that the experience of d-RARP can carry over to performance using the novel HSRS.

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