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DOI: 10.1055/a-2405-2708
Single-Port da Vinci Robot–Assisted Cervical Esophagectomy: How to Do It
Abstract
Minimally invasive esophagectomies, including robot-assisted procedures, have demonstrated superiority over traditional open surgery. Despite the prevalence of transhiatal and transthoracic approaches, cervical access is less common in minimally invasive esophageal surgery. Advancements in robotic systems, such as the da Vinci Single Port (SP), enable controlled transcervical extrapleural mediastinoscopic access, potentially reducing pulmonary complications and extending surgical options to patients with comorbidities. The da Vinci SP robot-assisted cervical esophagectomy (SP-RACE) employs an SP and laparoscopic approach, demonstrating feasibility with comparable lymphadenectomy and recurrent nerve palsy rates to transthoracic methods. This technique, performed for the first time in Europe at the University Hospital Mainz, involves a transcervical SP phase that allows for effective mediastinal dissection and esophageal mobilization. Despite technical challenges due to limited space, robotic systems enhance controlled access and eliminate arm collision. The da Vinci SP platform's advantages include improved triangulation, fewer interferences, and better control of instruments in confined spaces. This novel approach shows promise for patients with high esophageal tumors and those unsuitable for transthoracic surgery, warranting further investigation into its clinical utility and reproducibility.
Authors' Contribution
E.H. and V.J.L. wrote the manuscript. E.H., V.J.L., E.V.G., L.B., H.L., and P.P.G. participated in conceptualization, methodology, supervision, and review of the final draft. All authors have read and agreed to the published version of the manuscript. E.H. and V.J.L. contributed equally to this manuscript.
* These authors contributed equally to this study.
Publication History
Received: 09 June 2024
Accepted: 05 August 2024
Accepted Manuscript online:
29 August 2024
Article published online:
29 September 2024
© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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