Evidence map›Paper›PMID 41233492›Full record

ArticleScientific reports2025

Label-free histological identification of intraductal carcinoma of the prostate using texture analysis-based multimodal stimulated Raman scattering microscopy.

Justin R Gagnon, Christian H Allen, Mame-Kany Diop, Frédérick Dallaire, Frédéric Leblond, Dominique Trudel, Sangeeta Murugkar

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 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. Understanding and targeting the tumour matrisome.Nature reviews. Clinical oncology · 2026
    Review
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.

Justin R GagnonDepartment of Physics, Carleton University, 1125 Colonel By Drive, Ottawa, ON, K1S 5B6, Canada.
Christian H AllenDepartment of Physics, Carleton University, 1125 Colonel By Drive, Ottawa, ON, K1S 5B6, Canada.
Mame-Kany DiopCentre de recherche du Centre hospitalier de l'Université de Montréal, Montreal, QC, Canada.
Frédérick DallaireCentre de recherche du Centre hospitalier de l'Université de Montréal, Montreal, QC, Canada.
Frédéric LeblondCentre de recherche du Centre hospitalier de l'Université de Montréal, Montreal, QC, Canada.
Dominique Trudel *Centre de recherche du Centre hospitalier de l'Université de Montréal, Montreal, QC, Canada.
Sangeeta Murugkar *Department of Physics, Carleton University, 1125 Colonel By Drive, Ottawa, ON, K1S 5B6, Canada. smurugkar@physics.carleton.ca.

Funding

CIHR PJT-169164Natural Sciences and Engineering Research Council of Canada RGPIN-2022-04897
6 · The paper itself

Abstract

Intraductal carcinoma of the prostate (IDC-P) is a very aggressive histopathological subtype of prostate cancer (PCa) that is strongly associated with poor clinical outcomes but for which no accurate biomarkers exist. Here, we demonstrate a novel application of texture analysis-based machine learning alongside multimodal nonlinear optical imaging using second-harmonic generation (SHG) and stimulated Raman scattering (SRS) at 1450 cm

Indexed as

Nonlinear Optical MicroscopyProstatic NeoplasmsSpectrum Analysis, RamanHumansMachine LearningMaleProstateSupport Vector MachineIntraductal carcinoma of the prostateProstate cancerSecond-harmonic generationStimulated raman scatteringSupport vector machinesTexture analysis

Identifiers

PMID41233492
PMCPMC12615821

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.