ArticleBMC cancer2024
Prognostic significance of collagen signatures in pancreatic ductal adenocarcinoma obtained from second-harmonic generation imaging.
Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Machine Learning-Assisted SHG Morphometry Reveals Distinct Collagen Microarchitectures of Trabecular Bone and Fibrosis in Bone Marrow Biopsies.International journal of molecular sciences · 2026Article
- Biofabrication and artificial intelligence strategies for investigating solid- and fluid-pressure mechanobiology in pancreatic ductal adenocarcinoma.Cancer metastasis reviews · 2026Review
- Differences in collagen structure and organization in primary and metastatic pancreatic cancer and the effects of FOLFIRINOX treatment.Matrix biology plus · 2026Article
- Features of the spatial organization and qualitative composition of the collagen matrix in prostate cancer.Journal of molecular histology · 2026Article
- Autofluorescence and deep learning in early disease detection: biological foundations, clinical applications, and future directions.Frontiers in artificial intelligence · 2026Review
- The Heterogeneity and Function of Stromal Cells in the Tumor Microenvironment.Research (Washington, D.C.) · 2026Review
- Deep learning-enabled multiphoton microscopy predicts colorectal cancer recurrence from routine FFPE specimens.NPJ digital medicine · 2025Article
- Multiphoton imaging-based quantifiable collagen signatures for predicting outcomes in patients with pancreatic ductal adenocarcinoma.Scientific reports · 2025Article
- Development and validation of a collagen signature to predict central lymph node metastasis in papillary thyroid cancer.Frontiers in endocrinology · 2025Article
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Authors and funding
9 authors.
Funding
Abstract
backgroundPancreatic ductal adenocarcinoma (PDAC) ranks among the deadliest types of cancer, and it will be meaningful to search for new biomarkers with prognostic value to help clinicians tailor therapeutic strategies.
methodsHere we tried to use an advanced optical imaging technique, multiphoton microscopy (MPM) combining second-harmonic generation (SHG) and two-photon excited fluorescence (TPEF) imaging, for the label-free detection of PDAC tissues from a cohort of 149 patients. An automated image processing method was used to extract collagen features from SHG images and the Kaplan-Meier survival analysis and Cox proportional hazards regression were used to assess the prognostic value of collagen signatures.
resultsSHG images clearly show the different characteristics of collagen fibers in tumor microenvironment. We gained eight collagen morphological features, and a Feature-score was derived for each patient by the combination of these features using ridge regression. Statistical analyses reveal that Feature-score is an independent factor, and can predict the overall survival of PDAC patients as well as provide well risk stratification.
conclusionsSHG imaging technique can potentially be a tool for the accurate diagnosis of PDAC, and this optical biomarker (Feature-score) may help clinicians make more approximate treatment decisions.
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