Evidence map›Paper›PMID 39497739›Full record

ArticleFrontiers in bioinformatics2024

Quantification of muscle fiber malformations using edge detection to investigate chronic muscle pressure ulcers.

Charlene Z L Ong, N Jannah M Nasir, Roy E Welsch, Lisa Tucker-Kellogg, Jagath C Rajapakse

Abstract read
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Article in Frontiers in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Charlene Z L Ong *Health Informatics Lab, College of Computing and Data Science, Nanyang Technological University, Singapore, Singapore.
N Jannah M Nasir *Centre for Computational Biology and Programme in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore.
Roy E WelschSloan School of Management Operations Research and Statistics, Massachusetts Institute of Technology, Cambridge, MA, United States.
Lisa Tucker-KelloggCentre for Computational Biology and Programme in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore.
Jagath C RajapakseHealth Informatics Lab, College of Computing and Data Science, Nanyang Technological University, Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Microscopy of regenerated tissue shows different morphologies between the healing of acute wounds and chronic wounds. This difference can be seen manually by biologists, but computational methods are needed to automate the characterization of morphology and regenerative quality in regenerated muscle tissue. Results: From the detected edge segments, we computed several imaging biomarkers of interest, such as median tortuosity, number of edge segments normalized by area, median edge segment distance and interquartile range of orientation angles of edge segments of the microscope images of successful and unsuccessful muscle regeneration. We observed that muscle fibers in saline-treated pressure ulcers had a larger interquartile range of orientation angles of the edge segments (p = 0.05) and shorter edge segment distances (p = 0.003) compared to those of acute cardiotoxin injuries. Conclusion: Our edge detection method was able to identify statistically significant differences in some of the imaging biomarkers between saline-treated pressure ulcers and cardiotoxin injuries, suggesting that chronic pressure ulcers have increased muscle fiber malformations compared to cardiotoxin injuries.

Indexed as

deep learningedge detectionimaging biomarkersmuscle fiberspressure injuriestissue morphology

Identifiers

PMID39497739
PMCPMC11532102

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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 OpenQuestion graph.