Raman Spectroscopy

Diagnosis of extrahepatic cholangiocarcinoma is challenging because the yield of imaging and tissue sampling is limited. Raman spectroscopy is an optical method based on the analysis of scattered monochromatic light. Raman spectroscopy is able to provide a molecular 'fingerprint' of the tissue to determine its type. The aim of this pilot study was to develop a methodology for in vivo Raman spectroscopy in bile ducts to improve the current diagnostic capabilities of extrahepatic cholangiocarcinoma.

The goal of this observational study is to explore whether a Raman-based, deep learning-assisted approach can be used to develop an effective method for early pan-cancer screening. The study includes healthy individuals, patients at risk of cancer, and patients with diagnosed cancers. The main questions it aims to answer are: * Evaluating the deep-learning model's accuracy and specificity in identifying cancer-specific features in Raman spectral data and determining whether this method can accurately classify patients based on risk. * Identifying which model is more adaptable to the Raman spectrum * Providing an interpretable analysis of the model-generated diagnosis Participants are already being diagnosed and follow-up to determine the type of cancer.