Evidence mapPaperPMID 42145674Full record

ArticleBiomedical optics express2026

Whole-slide mapping of tumor tissue fiber architecture via computational scattered light imaging.

Hamed Abbasi, Loes Ettema, Rens van Elk, Meike Eskes, Michail Doukas, Sjors A Koppes, Stijn Keereweer, Miriam Menzel

Abstract read
In one paragraph

Article in Biomedical optics express, 2026. 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

8 authors.

Hamed AbbasiDepartment of Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands.ORCID https://orcid.org/0000-0003-0655-7187
Loes EttemaDepartment of Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands.ORCID https://orcid.org/0009-0003-3399-0047
Rens van ElkDepartment of Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands.ORCID https://orcid.org/0009-0003-9132-2004
Meike EskesDepartment of Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands.ORCID https://orcid.org/0009-0003-3807-1621
Michail DoukasDepartment of Pathology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Sjors A KoppesDepartment of Pathology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Stijn KeereweerDepartment of Otorhinolaryngology and Head and Neck Surgery, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Miriam MenzelDepartment of Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands.ORCID https://orcid.org/0000-0002-6042-7490

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mapping peritumoral collagen fiber directionality in solid tumors may assist in determining cancer progression and support more personalized prognoses. However, existing microscopy techniques are often limited by a restricted field of view, high cost, or incompatibility with paraffin-treated tissues. Computational scattered light imaging (ComSLI) is a cost-effective whole-slide microscopy technique that reveals fiber orientations independent of sample preparation. Using glioma, colorectal, and head and neck cancer samples, we show for the first time that ComSLI maps fiber orientations in paraffin-treated tumor tissues, visualizes tumor growth pathways and desmoplastic reactions, and allows the study of collagen orientations relative to tumor boundaries.

Identifiers

PMID42145674
PMCPMC13178623

What Socratic holds

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Registered trials

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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 Socratic graph.