Evidence map›Paper›PMID 40350060›Full record

ArticleThe American journal of pathology2025

Computationally Enabled Polychromatic Polarized Imaging Enables Mapping of Matrix Architectures that Promote Pancreatic Ductal Adenocarcinoma Dissemination.

Guhan Qian, Hongrong Zhang, Yuming Liu, Michael Shribak, Kevin W Eliceiri, Paolo P Provenzano

Abstract read
In one paragraph

Article in The American journal of pathology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Guhan QianDepartment of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota; Center for Multiparametric Imaging of Tumor Immune Microenvironments, University of Minnesota and University of Wisconsin-Madison, Minneapolis, Minnesota and Madison, Wisconsin.
Hongrong ZhangDepartment of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota; Center for Multiparametric Imaging of Tumor Immune Microenvironments, University of Minnesota and University of Wisconsin-Madison, Minneapolis, Minnesota and Madison, Wisconsin.
Yuming LiuCenter for Multiparametric Imaging of Tumor Immune Microenvironments, University of Minnesota and University of Wisconsin-Madison, Minneapolis, Minnesota and Madison, Wisconsin; Center for Quantitative Cell Imaging, University of Wisconsin-Madison, Madison, Wisconsin.
Michael ShribakMarine Biological Laboratory, University of Chicago, Woods Hole, Massachusetts.
Kevin W EliceiriCenter for Multiparametric Imaging of Tumor Immune Microenvironments, University of Minnesota and University of Wisconsin-Madison, Minneapolis, Minnesota and Madison, Wisconsin; Center for Quantitative Cell Imaging, University of Wisconsin-Madison, Madison, Wisconsin; Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin.
Paolo P ProvenzanoDepartment of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota; Center for Multiparametric Imaging of Tumor Immune Microenvironments, University of Minnesota and University of Wisconsin-Madison, Minneapolis, Minnesota and Madison, Wisconsin; Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota; Division of Hematology, Oncology, and Transplantation, Department of Medicine, University of Minnesota, Minneapolis, Minnesota; Institute for Engineering in Medicine, University of Minnesota, Minneapolis, Minnesota; Stem Cell Institute, University of Minnesota, Minneapolis, Minnesota. Electronic address: pprovenz@umn.edu.

Funding

The Center for Label-free Imagingand Multiscale Biophotonics (CLIMB)P41EB031772 · NIBIB · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI Stephen A Boppart · 2022 to 2026
$7.6M
NIBIB NIH HHS P41 EB031772
6 · The paper itself

Abstract

Pancreatic ductal adenocarcinoma (PDA) is a highly metastatic and lethal disease. In PDA, extracellular matrix (ECM) architectures, known as tumor-associated collagen signatures (TACSs), regulate invasion and metastatic spread in both early dissemination and late-stage disease. As such, TACS has been suggested as a biomarker to aid in pathologic assessment. However, despite its significance, approaches to quantitatively capture these ECM patterns currently require advanced optical systems with signaling processing analysis. Herein, an expansion of polychromatic polarized microscopy (PPM) with inherent angular information coupled with machine learning and computational pixel-wise analysis of TACS was used to accurately capture TACS architectures in hematoxylin and eosin-stained histology sections directly through PPM contrast. Moreover, PPM facilitated identification of transitions to dissemination architectures (ie, transitions from sequestration through expansion to dissemination from both pancreatic intraepithelial neoplasias and throughout PDA). Lastly, PPM evaluation of architectures in liver metastases, the most common metastatic site for PDA, demonstrated TACS-mediated focal and local invasion as well as identification of unique patterns anchoring aligned fibers into normal-adjacent tumor, suggesting that these patterns may be precursors to metastasis expansion and local spread from micrometastatic lesions. Combined, these findings demonstrate that PPM coupled to computational platforms is a powerful tool for analyzing ECM architecture that can be used to advance cancer microenvironment studies and provide clinically relevant diagnostic information.

Indexed as

Carcinoma, Pancreatic DuctalExtracellular MatrixImage Processing, Computer-AssistedPancreatic NeoplasmsCollagenHumansMicroscopy, PolarizationCollagen

Identifiers

PMID40350060
PMCPMC12264559

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.