Robotic-Assisted Pelvic Exenteration for Cervical Cancer: A Systematic Review and Novel Insights into Compartment-Based Imaging.
J Clin Med
; 13(13)2024 Jun 24.
Article
em En
| MEDLINE
| ID: mdl-38999239
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.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article