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Dual-Channel NIR Fluorescence Imaging for Precise Delineation of Gastric Tumor Margins

  • Yuanyuan Ji
  • , Kai Bao
  • , Lin Mei
  • , Yuanhao Su
  • , Yongke Wu
  • , Cheng Li
  • , Yongshen Wu
  • , Zhishen Ge
  • , Sangkee Choi
  • , Zhidong Wang
  • , Hak Soo Choi
  • The Second Affiliated Hospital of Xi'an Jiaotong University
  • Massachusetts General Hospital
  • Xi'an Jiaotong University
  • Japan Advanced Institute of Science and Technology

Research output: Contribution to journalArticlepeer-review

Abstract

Fluorescence imaging is a promising intraoperative technique for gastric cancer surgery, enabling clear visualization of surgical margins and detection of occult lesions. However, the lack of near-infrared (NIR) fluorescent probes specifically targeting gastric tumors and normal tissues remains a limitation. To address this, we developed a dual-channel imaging strategy using IR-780 (800 nm) for tumor detection and ESS65-Cl (700 nm) for normal gastric tissue identification. We evaluated their specificity in human gastric epithelial (GES-1) and cancer (SGC-7901) cells, confirming selective uptake: ESS65-Cl in normal gastric cells and IR-780 in tumor cells. In subcutaneous and orthotopic xenograft models, dual-channel imaging allowed simultaneous visualization of tumors and surrounding tissues in distinct colors. Pharmacokinetic analysis revealed that ESS65-Cl achieved a stomach signal-to-background ratio of 3.3 by 48 h, while IR-780 exhibited a tumor-to-background ratio of 4.0, demonstrating high targetability. Moreover, biodistribution studies confirmed efficient clearance of both agents. When combined, these fluorophores enabled precise intraoperative differentiation between gastric tissues and tumors. This approach holds substantial potential for improving surgical accuracy in gastric cancer resection, particularly in defining proximal esophageal margins and gastrectomy boundaries. By enhancing real-time tissue discrimination, dual-channel NIR imaging may increase surgical success rates and improve patient outcomes.

Original languageEnglish
Article number0275
JournalBiomaterials Research
Volume29
DOIs
StatePublished - 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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