Multiphoton imaging-based quantifiable collagen signatures for predicting outcomes in patients with pancreatic ductal adenocarcinoma.

ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) presents a clinical challenge due to its poor prognosis and high mortality rate. Here, we aimed to enhance the prognostic prediction of patients with PDAC by studying collagen features in tumor microenvironment using multiphoton microscopy (MPM) combining with image processing technique. We identified eight distinct tumor-associated collagen signatures (TACS1-8) from multiphoton images of PDAC tissues and developed an optical biomarker, TACS-score, based on the TACS1-8 using ridge regression analysis. Additionally, we also extracted 142 microscopic TACS (M-TACS) from second-harmonic generation (SHG) images and constructed a new robust biomarker, M-TACS-score, using the least absolute shrinkage and selection operator (LASSO) regression analysis. Our s

SUBMITTER: Chen X 

PROVIDER: S-EPMC11799447 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature