Mapping the Lymphatic Drainage Pattern of Esophageal Cancer with Near-Infrared Fluorescent Imaging during Robotic Assisted Minimally Invasive Ivor Lewis Esophagectomy (RAMIE)—First Results of the Prospective ESOMAP Feasibility Trial

医学 食管癌 吲哚青绿 淋巴结 食管切除术 食管 淋巴系统 淋巴 放射科 外科 前哨淋巴结 癌症 病理 内科学 乳腺癌
作者
Dolores T. Müller,Leif Schiffmann,Alissa Reisewitz,Seung‐Hun Chon,Jennifer A. Eckhoff,Benjamin Babic,Thomas Schmidt,Wolfgang Schröder,Christiane Bruns,Hans Fuchs
出处
期刊:Cancers [MDPI AG]
卷期号:15 (8): 2247-2247 被引量:1
标识
DOI:10.3390/cancers15082247
摘要

While the sentinel lymph node concept is routinely applied in other surgical fields, no established and valid modality for lymph node mapping for esophageal cancer surgery currently exists. Near-infrared light fluorescence (NIR) using indocyanine green (ICG) has been recently proven to be a safe technology for peritumoral injection and consecutive lymph node mapping in small surgical cohorts, mostly without the usage of robotic technology. The aim of this study was to identify the lymphatic drainage pattern of esophageal cancer during highly standardized RAMIE and to correlate the intraoperative images with the histopathological dissemination of lymphatic metastases. Patients with clinically advanced stage squamous cell carcinoma or adenocarcinoma of the esophagus undergoing a RAMIE at our Center of Excellence for Surgery of the Upper Gastrointestinal Tract were prospectively included in this study. Patients were admitted on the day prior to surgery, and an additional EGD with endoscopic injection of the ICG solution around the tumor was performed. Intraoperative imaging procedures were performed using the Stryker 1688 or the FIREFLY fluorescence imaging system, and resected lymph nodes were sent to pathology. A total of 20 patients were included in the study, and feasibility and safety for the application of NIR using ICG during RAMIE were shown. NIR imaging to detect lymph node metastases can be safely performed during RAMIE. Further analyses in our center will focus on pathological analyses of ICG-positive tissue and quantification using artificial intelligence tools with a correlation of long-term follow-up data.

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