Abstract
Background: In cancer surgery, resection of the primary tumor and regional lymph nodes (LNs) is critical. Adequate LN examination is essential to detect metastasis, which determines the cancer stage. Fluorescence emission allows for visual differentiation and rapid monitoring of LNs. Methods: Cancer tissue is stained with a fluorescent dye (indocyanine green, ICG) to identify LNs. Fluorescence is induced from the stained LNs using LED light, and a photosensor coupled with a speaker detects the fluorescence signal and triggers an audible alarm. Filters are applied to prevent false alarms. Results: Upon LN detection, an alarm is emitted from the speaker, and the results are recorded using the LED and a digital multimeter (DMM). In clinical trials, ICG is injected to induce LN fluorescence staining, followed by LED irradiation to induce the fluorescent wavelength and verify LN imaging. Discussion: In clinical trials, ICG stains both LNs and blood vessels, which may lead to false positives. To address this limitation, artificial intelligence algorithms can be trained to specifically identify LNs. Conclusions: Detection of fluorescence wavelengths via photosensors allows for rapid identification of LNs, confirmed through an audible alarm, thereby reducing surgical time. This method shows potential for broad application in cancer surgery.