First Japanese Experience of Robotic-Assisted Low Anterior Resection Using the da Vinci 5: Incorporating Force Feedback and Case Insights in Rectal Cancer Surgery

日本首例使用达芬奇5机器人辅助低位直肠前切除术的经验:将力反馈和病例分析应用于直肠癌手术

阅读:1

Abstract

INTRODUCTION: Colorectal cancer outcomes depend not only on disease stage but also on surgical quality, particularly in locally advanced rectal cancer. Robot-assisted surgery offers advantages over laparoscopy but lacks haptic feedback. The da Vinci 5 Surgical System introduces Force Feedback (FFB) technology, which transmits kinesthetic sensations to the surgeon and quantifies forces, as well as Case Insights, an artificial intelligence-based intraoperative data platform. To the best of our knowledge, this report describes the first case of robot-assisted low anterior resection for rectal cancer performed in Japan using da Vinci 5. CASE PRESENTATION: A woman in her 50s presented with constipation and was diagnosed with rectal cancer (cT3N0M0). She underwent robot-assisted low anterior resection using da Vinci 5. Console time was 131 min with minimal blood loss. The patient recovered uneventfully without leakage or urinary dysfunction and was discharged on POD 7. Case Insights revealed an instrument active time of 82% and average FFB forces of 2.1-2.7 N, with forces >6.5 N applied during only 4.3%-6.4% of the procedure, mainly during rectal mobilization. A complete total mesorectal excision and negative circumferential resection margins were achieved. CONCLUSIONS: Surgical skills have long remained tacit expert knowledge. FFB and Case Insights provide numeric metrics synchronized with intraoperative procedures, which may help convert tacit skills into explicit, quantifiable information. This enables experts to better understand their operative technique and help novices learn through objective, verbalized information that facilitates procedural understanding.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。