Label-free assessment of pathological changes in pancreatic intraepithelial neoplasia by biomedical multiphoton microscopy

Pancreatic intraepithelial neoplasia (PanIN) is the most common precursor lesion that has the potential to progress to invasive pancreatic cancer, and early and rapid detection may offer patients a chance for treatment before the development of invasive carcinoma. Therefore, the identification of PanIN holds significant clinical importance. In this study, we first used multiphoton microscopy (MPM) combining two-photon excitation fluorescence and second-harmonic generation imaging to label-free detect PanIN and attempted to differentiate between normal pancreatic ducts and different grades of PanIN. Then, we also developed an automatic image processing strategy to extract eight morphological features of collagen fibers from MPM images to quantify the changes in collagen fibers surrounding the ducts. Experimental results demonstrate that the combination of MPM and quantitative information can accurately identify normal pancreatic ducts and different grades of PanIN. This study may contribute to the rapid diagnosis of pancreatic diseases and may lay the foundation for further clinical application of MPM. In this study, we attempted to distinguish between normal pancreatic ducts and different grades of pancreatic intraepithelial neoplasia (PanIN) using label-free multiphoton microscopy (MPM), and developed an automated image-processing program to quantify periductal collagen fibers. Results show that MPM combined with quantitative information can accurately differentiate normal ducts and different grades of PanIN. MPM may play an important role in helping clinicians to achieve accurate diagnosis of premalignant lesions, and this work may provide a foundation for further clinical applications of MPM.image