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Background: Patients with cT1-2 colon cancer (CC) have a 10-20% risk of lymph node metastases. Sentinel lymph node identification (SLNi) could improve staging and reduce morbidity in future organ-preserving CC surgery. This pilot study aimed to assess safety and feasibility of robot-assisted fluorescence-guided SLNi using submucosally injected indocyanine green (ICG) in patients with cT1-2N0M0 CC.
Methods: Ten consecutive patients with cT1-2N0M0 CC were included in this prospective feasibility study. Intraoperative submucosal, peritumoral injection of ICG was performed during a colonoscopy. Subsequently, the near-infrared fluorescence 'Firefly' mode of the da Vinci Xi robotic surgical system was used for SLNi. SLNs were marked with a suture, after which a segmental colectomy was performed. The SLN was postoperatively ultrastaged using serial slicing and immunohistochemistry, in addition to the standard pathological examination of the specimen. Colonoscopy time, detection time (time from ICG injection to first SLNi), and total SLNi time were measured (time from the start of colonoscopy to start of segmental resection). Intraoperative, postoperative, and pathological outcomes were registered.
Results: In all patients, at least one SLN was identified (mean 2.3 SLNs, SLN diameter range 1-13 mm). No tracer-related adverse events were noted. Median colonoscopy time was 12 min, detection time was 6 min, and total SLNi time was 30.5 min. Two patients had lymph node metastases present in the SLN, and there were no patients with false negative SLNs. No patient was upstaged due to ultrastaging of the SLN after an initial negative standard pathological examination. Half of the patients unexpectedly had pT3 tumours.
Conclusions: Robot-assisted fluorescence-guided SLNi using submucosally injected ICG in ten patients with cT1-2N0M0 CC was safe and feasible. SLNi was performed in an acceptable timespan and SLNs down to 1 mm were detected. All lymph node metastases would have been detected if SLN biopsy had been performed.
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http://dx.doi.org/10.1007/s00464-023-10394-2 | DOI Listing |
J Bras Pneumol
September 2025
. Universidade Federal do Rio de Janeiro, Rio de Janeiro (RJ) Brasil.
Anticancer Drugs
September 2025
Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College.
Nonsmall cell lung cancer (NSCLC) with SMARCA4 deficiency represents a rare subset of lung tumors characterized by early metastasis, poor response to chemotherapy, and unfavorable prognosis. Established therapy strategies for SMARCA4-deficient NSCLC remain elusive. While immune checkpoint inhibitors have been proposed as a potential solution, their efficacy remains uncertain.
View Article and Find Full Text PDFInt J Surg
September 2025
Guangxi Medical University, Nanning, Guangxi, China.
Ann Nucl Med
September 2025
Department of Nuclear Medicine, Marmara University School of Medicine, Istanbul, Turkey.
Objective: This study aims to systematically evaluate the inter- and intra-observer agreement regarding lesions with uncertain malignancy potential in Ga-68 PSMA PET/CT imaging of prostate cancer patients, utilizing the PSMA-RADS 2.0 classification system, and to emphasize the malignancy evidence associated with these lesions.
Methods: We retrospectively reviewed Ga-68 PSMA PET/CT images of patients diagnosed with prostate cancer via histopathology between December 2016 and November 2023.
Ann Surg Oncol
September 2025
Cancer Center, Renmin Hospital of Wuhan University, Wuhan, China.
Background: The optimal number of examined lymph nodes (ELN) for accurate staging and prognosis for esophageal cancer patients receiving neoadjuvant therapy remains controversial. This study aimed to evaluate the impact of ELN count on pathologic staging and survival outcomes and to develop a predictive model for lymph node positivity in this patient population.
Methods: Data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and a multicenter cohort.