Sentinel lymph node (SLN) imaging and biopsy has been advocated as an important technique to evaluate the metastatic status of regional lymph nodes and determine subsequent surgical procedure for many cancers, yet there is no reliable means to provide accurate and rapid diagnosis of metastatic SLN during surgery. Here we develop a new approach, named “Ratiometric Raman dual-nanotag strategy”, that using folic acid functionalized targeted and nontargeted gap-enhanced Raman tags (FA-GERTs and Nt-GERTs) to detect metastatic SLN based on Raman imaging combined with classical least square data processing methods. By using this strategy, with built-in self-calibration for signal correction, rather than absolute intensity-dependent signal readout, we realize the visualization and prompt intraoperative diagnosis of metastatic SLN with a high accuracy of 87.5 % when the cut-off value of ratio (FA-GERTs/Nt-GERTs) set at 1.255. This approach may outperform the existing histopathological assessment in diagnosing SLN metastasis and is promising for guiding surgical procedure in the future.

前哨淋巴结 (SLN) 成像和活检一直被认为是评估区域淋巴结转移状态和确定许多癌症后续手术程序的重要技术，但目前还没有可靠的方法来准确、快速地诊断转移性 SLN外科手术。在这里，我们开发了一种名为“比率拉曼双纳米标签策略”的新方法，该方法使用叶酸功能化的靶向和非靶向间隙增强拉曼标签（FA-GERT 和 Nt-GERT）基于拉曼成像结合经典的拉曼成像检测转移性前哨淋巴结。最小二乘数据处理方法。通过使用这种策略，内置信号校正自校准，而不是绝对强度相关的信号读数，当比值 (FA-GERTs/Nt-GERTs) 的临界值设置为 1.255 时，我们实现了转移性 SLN 的可视化和术中诊断，准确率高达 87.5%。这种方法在诊断 SLN 转移方面可能优于现有的组织病理学评估，并有望指导未来的手术过程。