Illuminating the future of precision cancer surgery with fluorescence imaging and artificial intelligence convergence

作者：Han Cheng, Hong-Tao Xu, Boyang Peng, Xiaojuan Huang, Yongjie Hu, Chongyang Zheng, Zhiyuan Zhang · 发表于：npj Precision Oncology · 年份：2024 · DOI：10.1038/s41698-024-00699-3 · 被引用次数：69 · 研究领域：Nanoplatforms for cancer theranostics、Artificial Intelligence in Healthcare and Education、Radiomics and Machine Learning in Medical Imaging

Real-time and accurate guidance for tumor resection has long been anticipated by surgeons. In the past decade, the flourishing material science has made impressive progress in near-infrared fluorophores that may fulfill this purpose. Fluorescence imaging-guided surgery shows great promise for clinical application and has undergone widespread evaluations, though it still requires continuous improvements to transition this technique from bench to bedside. Concurrently, the rapid progress of artificial intelligence (AI) has revolutionized medicine, aiding in the screening, diagnosis, and treatment of human doctors. Incorporating AI helps enhance fluorescence imaging and is poised to bring major innovations to surgical guidance, thereby realizing precision cancer surgery. This review provides an overview of the principles and clinical evaluations of fluorescence-guided surgery. Furthermore, recent endeavors to synergize AI with fluorescence imaging were presented, and the benefits of this interdisciplinary convergence were discussed. Finally, several implementation strategies to overcome technical hurdles were proposed to encourage and inspire future research to expedite the clinical application of these revolutionary technologies.