Institut NeuroMyoGène, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5310, INSERM U1217, 8 Avenue Rockfeller, F-69008, Lyon, France.
CREATIS, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5220, INSERM U1206, INSA Lyon, 69100, Villeurbanne, France.
Skelet Muscle. 2019 Jan 8;9(1):2. doi: 10.1186/s13395-018-0186-6.
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.
成人骨骼肌在急性损伤后能够完全再生。评估肌肉再生效果的主要参数是肌纤维的横截面积(CSA),因为肌纤维大小与肌肉力量相关。CSA 分析可能很耗时,并且当手动执行时可能会导致结果的可变性。这就是为什么开发了程序来完全自动分析 CSA 的原因,例如 SMASH、MyoVision 或 MuscleJ 软件。尽管这些软件对于测量正常或肥大/萎缩肌肉的 CSA 非常有效,但它们无法有效地测量再生肌肉的 CSA。我们开发了 Open-CSAM,这是一种 ImageJ 宏,用于对来自各种实验条件的骨骼肌进行高通量半自动 CSA 分析。该宏允许实验者调整分析并纠正自动化过程中出现的错误,这是完全自动化程序所无法做到的。我们表明,与 SMASH、MyoVision 和 MuscleJ 软件相比,Open-CSAM 更能准确地测量再生和萎缩肌肉中的 CSA,并且实验者之间的可变性可以忽略不计。我们还表明,为了获得有代表性的 CSA 测量值,有必要分析整个肌肉切片,而不是随机选择的图片,使用 Open-CSAM 可以轻松准确地完成这一过程。总之,我们在这里展示了一种易于使用且可由实验者控制的工具,用于测量任何实验条件下的肌肉 CSA,包括再生肌肉。