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首页> 外文期刊>BMC Neuroscience >AxonTracer: a novel ImageJ plugin for automated quantification of axon regeneration in spinal cord tissue
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AxonTracer: a novel ImageJ plugin for automated quantification of axon regeneration in spinal cord tissue

机译：AxonTracer：新颖的ImageJ插件，用于自动定量脊髓组织中轴突再生

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Quantification of axon regeneration in spinal cord tissue sections is a fundamental step to adequately determine if an applied treatment leads to an anatomical benefit following spinal cord injury. Recent advances have led to the development of therapies that can promote regeneration of thousands of injured axons in vivo. Axon labeling methods and in the application of regeneration-enabling stem cell grafts have increased the number of detectable regenerating axons by orders of magnitudes. Manual axon tracing in such cases is challenging and laborious, and as such there is a great need for automated algorithms that can perform accurate tracing and quantification in axon-dense tissue sections. We developed “AxonTracer”, a fully automated software algorithm that traces and quantifies regenerating axons in spinal cord tissue sections. AxonTracer is an open source plugin for the freely available image-processing program ImageJ. The plugin identifies transplanted cells grafts or other regions of interest (ROIs) based on immunohistological staining and quantifies regenerating axons within the ROIs. Individual images or groups of images (batch mode) can be analyzed sequentially. In batch mode, a unique algorithm identifies a reference image for normalization, as well as a suitable image for defining detection parameters. An interactive user interface allows for adjustment of parameters defining ROI size, axon detection sensitivity and debris cleanup. Automated quantification of regenerating axons by AxonTracer correlates strongly with semi-manual quantification by the widely-used ImageJ plugin NeuronJ. However, quantification with AxonTracer is automated and reduces the need for user input compared to alternative methods. AxonTracer is a freely available open-source tool for automated analysis of regenerating axons in the injured nervous system. An interactive user interface provides detection-parameter adjustment, and usage does not require prior image analysis experience. Raw data as well as normalized results are stored in spreadsheet format and axon tracings are superimposed on raw images allowing for subjective visual verification. This software allows for automated, unbiased analysis of hundreds of axon-dense images, thus providing a useful tool in enabling in vivo screens of axon regeneration following spinal cord injury.
机译：量化脊髓组织切片中的轴突再生是充分确定所应用的治疗是否在脊髓损伤后带来解剖学益处的基本步骤。最近的进展导致了可以促进体内数千个受损轴突再生的疗法。轴突标记方法和可再生干细胞移植的应用已将可检测到的再生轴突的数量增加了几个数量级。在这种情况下，手动轴突追踪是具有挑战性和费力的，因此，迫切需要能够在轴突密集的组织切片中进行精确追踪和定量的自动化算法。我们开发了“ AxonTracer”，这是一种自动化的软件算法，可以跟踪和量化脊髓组织切片中再生的轴突。 AxonTracer是免费提供的图像处理程序ImageJ的开源插件。该插件基于免疫组织学染色识别移植的细胞移植物或其他感兴趣的区域（ROI），并量化ROI中的再生轴突。可以顺序分析单个图像或图像组（批处理模式）。在批处理模式下，独特的算法可识别参考图像进行标准化，以及用于定义检测参数的合适图像。交互式用户界面允许调整定义ROI大小，轴突检测灵敏度和碎片清除的参数。 AxonTracer对再生轴突的自动定量与广泛使用的ImageJ插件NeuronJ的半手动定量密切相关。但是，与其他方法相比，使用AxonTracer进行定量是自动化的，并减少了用户输入的需求。 AxonTracer是免费提供的开放源代码工具，用于自动分析受伤的神经系统中再生的轴突。交互式用户界面可提供检测参数调整，并且不需要事先进行图像分析经验即可使用。原始数据和标准化结果均以电子表格格式存储，并且轴突跟踪叠加在原始图像上，从而可以进行主观视觉验证。该软件可对数百个轴突密集图像进行自动化，无偏见的分析，从而提供了一个有用的工具，可在体内对脊髓损伤后轴突再生的筛查。

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