Robotic-Assisted Pelvic Exenteration for Cervical Cancer: A Systematic Review and Novel Insights into Compartment-Based Imaging

机器人辅助盆腔脏器切除术治疗宫颈癌:系统评价及基于分区成像的新见解

阅读:1

Abstract

Background: Patients with persistent or recurrent cervical cancer, following primary treatment with concurrent chemoradiation, represent a subgroup eligible for pelvic exenteration. In light of the substantial morbidity associated with open pelvic exenterations, minimally invasive surgical techniques have been introduced. This systematic review aims to analyze and discuss the current literature on robotic-assisted pelvic exenterations in cervical cancer. In addition, novel aspects of compartment-based magnetic resonance imaging (MRI) are highlighted. Methods: This systematic review followed the PRISMA guidelines, and a comprehensive literature search on robotic-assisted pelvic exenterations in cervical cancer was conducted to assess, as main objectives, early and late postoperative complications as well as oncological outcomes. Inclusion and exclusion criteria were applied to select eligible studies. Results: Among the reported cases of robotic-assisted pelvic exenterations in cervical cancer, 79.4% are anterior pelvic exenterations. Intraoperative complications are minimal and early/late major complications averaged between 30-35%, which is lower compared to open pelvic exenterations. Oncological outcomes are similar between robotic and open pelvic exenterations. Sensitivity for locoregional invasion increases up to 93% for compartment-based MRI in colorectal cancer. A refined delineation of the seven pelvic compartments for cervical cancer is proposed here. Conclusions: Robotic-assisted pelvic exenterations have demonstrated feasibility and safety, with reduced rates of major complications compared to open surgery, while maintaining surgical efficiency and oncological outcomes. Compartment-based MRI holds promise for standardizing the selection and categorization of pelvic exenteration procedures.

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。