Cargando…
Automated muscle histopathology analysis using CellProfiler
BACKGROUND: Histological assessment of skeletal muscle sections is important for the research of muscle physiology and diseases. Quantifiable measures of skeletal muscle often include mean fiber diameter, fiber size distribution, and centrally nucleated muscle fibers. These parameters offer insights...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6193305/ https://www.ncbi.nlm.nih.gov/pubmed/30336774 http://dx.doi.org/10.1186/s13395-018-0178-6 |
_version_ | 1783364048741466112 |
---|---|
author | Lau, Yeh Siang Xu, Li Gao, Yandi Han, Renzhi |
author_facet | Lau, Yeh Siang Xu, Li Gao, Yandi Han, Renzhi |
author_sort | Lau, Yeh Siang |
collection | PubMed |
description | BACKGROUND: Histological assessment of skeletal muscle sections is important for the research of muscle physiology and diseases. Quantifiable measures of skeletal muscle often include mean fiber diameter, fiber size distribution, and centrally nucleated muscle fibers. These parameters offer insights into the dynamic adaptation of skeletal muscle cells during repeated cycles of degeneration and regeneration associated with many muscle diseases and injuries. Computational programs designed to obtain these parameters would greatly facilitate such efforts and offer significant advantage over manual image analysis, which is very labor-intensive and often subjective. Here, we describe a customized pipeline termed MuscleAnalyzer for muscle histology analysis based upon CellProfiler, a free, open-source software for measuring and analyzing cell images. RESULTS: The MuscleAnalyzer pipeline consists of loading, adjusting, and running a series of image-processing modules provided by CellProfiler. This pipeline was evaluated using wild-type and mdx muscle sections co-stained with laminin (to demarcate the muscle fiber boundaries) and 4′,6-diamidino-2-phenylindole (DAPI, to label the nuclei). The immunofluorescence images analyzed using the MuscleAnalyzer pipeline or manually yielded similar results in the number of muscle fibers per image (p = 0.42) and central nucleated fiber (CNF) percentage (p = 0.29) in mdx mice. However, for a total of 67 images, CellProfiler completed the analysis in ~ 10 min on a regular PC while it took an investigator ~ 3 h using the manual approach in order to quantify the number of muscle fibers and CNF. Moreover, the MuscleAnalyzer pipeline also provided the measurement of the cross-sectional area (CSA) and minimal Feret’s diameter (MFD) of muscle fibers, and thus fiber size distribution can be plotted. CONCLUSIONS: Our data indicate that the MuscleAnalyzer pipeline can efficiently and accurately analyze laminin and DAPI co-stained muscle images in a batch format and provide quantitative measurements for muscle histological properties such as muscle fiber diameters, fiber size distribution, and CNF percentage. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13395-018-0178-6) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6193305 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61933052018-10-22 Automated muscle histopathology analysis using CellProfiler Lau, Yeh Siang Xu, Li Gao, Yandi Han, Renzhi Skelet Muscle Software BACKGROUND: Histological assessment of skeletal muscle sections is important for the research of muscle physiology and diseases. Quantifiable measures of skeletal muscle often include mean fiber diameter, fiber size distribution, and centrally nucleated muscle fibers. These parameters offer insights into the dynamic adaptation of skeletal muscle cells during repeated cycles of degeneration and regeneration associated with many muscle diseases and injuries. Computational programs designed to obtain these parameters would greatly facilitate such efforts and offer significant advantage over manual image analysis, which is very labor-intensive and often subjective. Here, we describe a customized pipeline termed MuscleAnalyzer for muscle histology analysis based upon CellProfiler, a free, open-source software for measuring and analyzing cell images. RESULTS: The MuscleAnalyzer pipeline consists of loading, adjusting, and running a series of image-processing modules provided by CellProfiler. This pipeline was evaluated using wild-type and mdx muscle sections co-stained with laminin (to demarcate the muscle fiber boundaries) and 4′,6-diamidino-2-phenylindole (DAPI, to label the nuclei). The immunofluorescence images analyzed using the MuscleAnalyzer pipeline or manually yielded similar results in the number of muscle fibers per image (p = 0.42) and central nucleated fiber (CNF) percentage (p = 0.29) in mdx mice. However, for a total of 67 images, CellProfiler completed the analysis in ~ 10 min on a regular PC while it took an investigator ~ 3 h using the manual approach in order to quantify the number of muscle fibers and CNF. Moreover, the MuscleAnalyzer pipeline also provided the measurement of the cross-sectional area (CSA) and minimal Feret’s diameter (MFD) of muscle fibers, and thus fiber size distribution can be plotted. CONCLUSIONS: Our data indicate that the MuscleAnalyzer pipeline can efficiently and accurately analyze laminin and DAPI co-stained muscle images in a batch format and provide quantitative measurements for muscle histological properties such as muscle fiber diameters, fiber size distribution, and CNF percentage. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13395-018-0178-6) contains supplementary material, which is available to authorized users. BioMed Central 2018-10-18 /pmc/articles/PMC6193305/ /pubmed/30336774 http://dx.doi.org/10.1186/s13395-018-0178-6 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Lau, Yeh Siang Xu, Li Gao, Yandi Han, Renzhi Automated muscle histopathology analysis using CellProfiler |
title | Automated muscle histopathology analysis using CellProfiler |
title_full | Automated muscle histopathology analysis using CellProfiler |
title_fullStr | Automated muscle histopathology analysis using CellProfiler |
title_full_unstemmed | Automated muscle histopathology analysis using CellProfiler |
title_short | Automated muscle histopathology analysis using CellProfiler |
title_sort | automated muscle histopathology analysis using cellprofiler |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6193305/ https://www.ncbi.nlm.nih.gov/pubmed/30336774 http://dx.doi.org/10.1186/s13395-018-0178-6 |
work_keys_str_mv | AT lauyehsiang automatedmusclehistopathologyanalysisusingcellprofiler AT xuli automatedmusclehistopathologyanalysisusingcellprofiler AT gaoyandi automatedmusclehistopathologyanalysisusingcellprofiler AT hanrenzhi automatedmusclehistopathologyanalysisusingcellprofiler |