Robot-assisted laparoendoscopic single-site retroperitoneal nephroureterectomy with bladder cuff excision for upper tract urothelial carcinoma: Preliminary experience

机器人辅助腹腔镜单孔后腹膜肾输尿管切除术联合膀胱袖套切除术治疗上尿路尿路上皮癌:初步经验

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Abstract

OBJECTIVE: To present a modified technique for robot-assisted laparoendoscopic single-site retroperitoneal nephroureterectomy (RLESS-RNU) with bladder cuff excision and evaluate its effectiveness as a minimally invasive approach for managing upper tract urothelial carcinoma (UTUC). METHODS: Fifteen patients who underwent RLESS-RNU for UTUC between April 2020 and June 2021 were reviewed at our medical institution (The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China), from our prospectively maintained institutional database. The da Vinci® Xi system (Intuitive Surgical, Sunnyvale, CA, USA) was utilized for surgical procedures in all patients. An in-depth analysis was conducted on their baseline demographic characteristics, pathological factors, and perioperative details. The complete surgical process and details are elaborated. RESULTS: The median age of 15 patients was 67 years. The final pathology demonstrated 47% (7/15) patients with pT1 or lower and 47% (7/15) with pT3; one patient could not undergo pathological staging because of preoperative chemotherapy. The perioperative outcomes revealed that the mean operative time was 185 (standard deviation [SD] 23.05) min. The mean times of the trocar placement for primary and second docking were 15.00 (SD 0.85) min and 8.00 (SD 0.52) min, respectively. The median estimated blood loss was 55 mL. The mean drainage tube duration and postoperative hospital stay were 7.50 days and 11.00 days, respectively. After a mean follow-up period of 24.20 months, the relapse-free survival rate was 87%. Two patients experienced disease progression: one patient exhibited multifocal evidence of non-muscle invasive bladder cancer, and the other patient developed systemic recurrence. CONCLUSION: This study demonstrates that the modified technique for RLESS-RNU is safe and satisfactory for UTUC.

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