Evidence map›Paper›PMID 37591987›Full record

ArticleScientific reports2023

Mueller matrix polarization parameters correlate with local recurrence in patients with stage III colorectal cancer.

Kseniia Tumanova, Stefano Serra, Anamitra Majumdar, Jigar Lad, Fayez Quereshy, Mohammadali Khorasani, Alex Vitkin

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 19% of its field
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

7 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
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  4. Polarimetry terahertz imaging of human breast cancer surgical specimens.Journal of medical imaging (Bellingham, Wash.) · 2024
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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

7 authors at 3 institutions in 1 country.

Kseniia TumanovaDepartment of Medical Biophysics, University of Toronto, Toronto, Canada. k.tumanova@mail.utoronto.ca.
Stefano SerraDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada.
Anamitra MajumdarDepartment of Medical Biophysics, University of Toronto, Toronto, Canada.
Jigar LadDepartment of Medical Biophysics, University of Toronto, Toronto, Canada.
Fayez QuereshyDepartment of Surgery, University of Toronto, Toronto, Canada.
Mohammadali KhorasaniDepartment of Surgery, University of British Columbia, Victoria, Canada.
Alex VitkinDepartment of Medical Biophysics, University of Toronto, Toronto, Canada.
University of Toronto · CAUniversity Health Network · CAUniversity of British Columbia · CA

Funding

CIHR PJT-156110
6 · The paper itself

Abstract

The peri-tumoural stroma has been explored as a useful source of prognostic information in colorectal cancer. Using Mueller matrix (MM) polarized light microscopy for quantification of unstained histology slides, the current study assesses the prognostic potential of polarimetric characteristics of peri-tumoural collagenous stroma architecture in 38 human stage III colorectal cancer (CRC) patient samples. Specifically, Mueller matrix transformation and polar decomposition parameters were tested for association with 5-year patient local recurrence outcomes. The results show that some of these polarimetric parameters were significantly different (p value < 0.05) for the recurrence versus the no-recurrence patient cohorts (Mann-Whitney U test). MM parameters may thus be prognostically valuable towards improving clinical management/treatment stratification in CRC patients.

Indexed as

Colorectal NeoplasmsHistological TechniquesHumansMicroscopy, PolarizationPatientsRefraction, Ocular

Identifiers

PMID37591987
PMCPMC10435541
OpenAlexW4385945367

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.