Evidence map›Paper›PMID 25937889›Full record

ArticleSkeletal muscle2014

SMASH - semi-automatic muscle analysis using segmentation of histology: a MATLAB application.

Lucas R Smith, Elisabeth R Barton

Abstract read
In one paragraph

Article in Skeletal muscle, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 160 papers.

0numbers the graph read from it
0cells of the map it votes in
160citing 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

160 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Trial
  4. Trial
  5. Trial
  6. Trial
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Heme Metabolism-Derived Carbon Monoxide Regulates Skeletal Muscle Function.Journal of cachexia, sarcopenia and muscle · 2026
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

100 more citing papers are in PubMed but not listed here.

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

2 authors.

Lucas R SmithDepartment of Anatomy and Cell Biology, School of Dental Medicine, University of Pennsylvania, Philadelphia, PA USA ; Pennsylvania Muscle Institute, University of Pennsylvania, Philadelphia, PA USA.
Elisabeth R BartonDepartment of Anatomy and Cell Biology, School of Dental Medicine, University of Pennsylvania, Philadelphia, PA USA ; Pennsylvania Muscle Institute, University of Pennsylvania, Philadelphia, PA USA.

Funding

Training and education CoreU54AR052646 · NIAMS · UNIVERSITY OF PENNSYLVANIA · PI MCNALLY, ELIZABETH M, SWEENEY, H LEE · 2005 to 2020
$24.1M
Training in Muscle Biology and Muscle DiseaseT32AR053461 · NIAMS · UNIVERSITY OF PENNSYLVANIA · PI OSTAP, E. MICHAEL · 2006 to 2025
$4.9M
Modulation of Muscle Regenerationby Growth FactorsR01AR057363 · NIAMS · UNIVERSITY OF PENNSYLVANIA · PI BARTON, ELISABETH R · 2010 to 2014
$1.4M
NIAMS NIH HHS R01 AR057363NIAMS NIH HHS T32 AR053461NIAMS NIH HHS U54 AR052646
6 · The paper itself

Abstract

backgroundHistological assessment of skeletal muscle tissue is commonly applied to many areas of skeletal muscle physiological research. Histological parameters including fiber distribution, fiber type, centrally nucleated fibers, and capillary density are all frequently quantified measures of skeletal muscle. These parameters reflect functional properties of muscle and undergo adaptation in many muscle diseases and injuries. While standard operating procedures have been developed to guide analysis of many of these parameters, the software to freely, efficiently, and consistently analyze them is not readily available. In order to provide this service to the muscle research community we developed an open source MATLAB script to analyze immunofluorescent muscle sections incorporating user controls for muscle histological analysis.

resultsThe software consists of multiple functions designed to provide tools for the analysis selected. Initial segmentation and fiber filter functions segment the image and remove non-fiber elements based on user-defined parameters to create a fiber mask. Establishing parameters set by the user, the software outputs data on fiber size and type, centrally nucleated fibers, and other structures. These functions were evaluated on stained soleus muscle sections from 1-year-old wild-type and mdx mice, a model of Duchenne muscular dystrophy. In accordance with previously published data, fiber size was not different between groups, but mdx muscles had much higher fiber size variability. The mdx muscle had a significantly greater proportion of type I fibers, but type I fibers did not change in size relative to type II fibers. Centrally nucleated fibers were highly prevalent in mdx muscle and were significantly larger than peripherally nucleated fibers.

conclusionsThe MATLAB code described and provided along with this manuscript is designed for image processing of skeletal muscle immunofluorescent histological sections. The program allows for semi-automated fiber detection along with user correction. The output of the code provides data in accordance with established standards of practice. The results of the program have been validated using a small set of wild-type and mdx muscle sections. This program is the first freely available and open source image processing program designed to automate analysis of skeletal muscle histological sections.

Indexed as

Histological muscle analysisImage segmentationmdx mouseStandardized quantitative analysis

Identifiers

PMID25937889
PMCPMC4417508

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.