Opportunities and Challenges of Indocyanine Green in Gastrointestinal Cancers for Intraoperative and Nano-Medicine Application

The morbidity and mortality of gastrointestinal tumours remain high worldwide. Surgical resection is currently the most critical radical therapeutic schedule, while postoperative complications and sentinel lymph node (SLN) identification are closely related to the outcome. Indocyanine green (ICG)-mediated fluorescence imaging is increasingly being used in gastrointestinal surgery. It has been embraced by various surgical disciplines as a potential method to improve lymph node detection and enhance surgical field visualization. ICG can passively concentrate in SLN because of enhanced permeation and retention effects. After excitation by near-infrared light devices, SLN can display higher intensity fluorescence, helping visualization for better lymph node dissection. In addition, visual assessment of intestinal blood flow through ICG may reduce the incidence of anastomotic leakage. Although it has good clinical application, ICG-imaging still faces some problems, such as a higher false-negative rate, poorly targeted biodistribution, and lower fluorescence contrast, due to the lack of active tumour targeting. Thus, different ICG-coupled nanoparticles with inherent characteristics or functional modification-enhanced SLN identification features for gastrointestinal cancers bring benefit through active tumour targeting, superior tumour-background ratio, and high resolution. Nano-ICG combined with potential substances, including enhanced imaging contrast and/or combination therapy (chemotherapy, targeted therapy, immunotherapy, etc.), have been packaged and accumulated in the tumour area through active targeting for multimodal imaging and treatment. In this review, we outline the intraoperative application and possible future nanodirections of ICG in gastrointestinal cancer. The prospects and challenges of nano-ICG diagnostic and therapeutic methods in clinical applications are also discussed. Graphical Abstract