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Skelet Muscle. 2019 Jan 8;9(1):2. doi: 10.1186/s13395-018-0186-6.

Open-CSAM, a new tool for semi-automated analysis of myofiber cross-sectional area in regenerating adult skeletal muscle.

Author information

1
Institut NeuroMyoGène, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5310, INSERM U1217, 8 Avenue Rockfeller, F-69008, Lyon, France.
2
CREATIS, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5220, INSERM U1206, INSA Lyon, 69100, Villeurbanne, France.
3
CIQLE, Lyon Bio Image, Univ Lyon, Université Claude Bernard Lyon 1, Structure Fédérative de Recherche santé Lyon-Est CNRS UMS3453/INSERM US7, 69008, Lyon, France.
4
Institut NeuroMyoGène, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5310, INSERM U1217, 8 Avenue Rockfeller, F-69008, Lyon, France. benedicte.chazaud@inserm.fr.
5
Institut NeuroMyoGène, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5310, INSERM U1217, 8 Avenue Rockfeller, F-69008, Lyon, France. gaetan.juban@univ-lyon1.fr.

Abstract

Adult skeletal muscle is capable of complete regeneration after an acute injury. The main parameter studied to assess muscle regeneration efficacy is the cross-sectional area (CSA) of the myofibers as myofiber size correlates with muscle force. CSA analysis can be time-consuming and may trigger variability in the results when performed manually. This is why programs were developed to completely automate the analysis of the CSA, such as SMASH, MyoVision, or MuscleJ softwares. Although these softwares are efficient to measure CSA on normal or hypertrophic/atrophic muscle, they fail to efficiently measure CSA on regenerating muscles. We developed Open-CSAM, an ImageJ macro, to perform a high throughput semi-automated analysis of CSA on skeletal muscle from various experimental conditions. The macro allows the experimenter to adjust the analysis and correct the mistakes done by the automation, which is not possible with fully automated programs. We showed that Open-CSAM was more accurate to measure CSA in regenerating and dystrophic muscles as compared with SMASH, MyoVision, and MuscleJ softwares and that the inter-experimenter variability was negligible. We also showed that, to obtain a representative CSA measurement, it was necessary to analyze the whole muscle section and not randomly selected pictures, a process that was easily and accurately be performed using Open-CSAM. To conclude, we show here an easy and experimenter-controlled tool to measure CSA in muscles from any experimental condition, including regenerating muscle.

PMID:
30621783
PMCID:
PMC6323738
DOI:
10.1186/s13395-018-0186-6
[Indexed for MEDLINE]
Free PMC Article

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