Automated Morphological Analysis of Microglia After Stroke.
Automated Morphological Analysis of Microglia After Stroke.
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DOI：
10.3389/fncel.2018.00106
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发表时间：
2018
影响因子：
5.3
通讯作者：
Liesz A
中科院分区：
文献类型：
--
作者：
Heindl S;Gesierich B;Benakis C;Llovera G;Duering M;Liesz A
小胶质细胞是大脑的常驻免疫细胞，通过转录调节和形态改变对环境的变化做出快速反应。脑组织损伤如缺血性中风可引起局部炎症反应，包括小胶质细胞激活。小胶质细胞激活状态的变化反映在其从高度分枝细胞逐渐转变为较少分枝细胞或变形虫细胞形状。因此，小胶质细胞的形态学变化被广泛用于量化小胶质细胞的激活，并研究它们在几乎所有脑部疾病中的作用。然而，目前可用的方法，主要是基于免疫荧光显微图像的手动评级，往往是不准确的，评级偏差较大，并且非常耗时。为了解决这些问题，我们创建了一个全自动图像分析工具，该工具可以从共聚焦z堆叠中分析小胶质细胞形态，并提供多达59个形态学特征。我们在中风小鼠模型的小胶质细胞探索性数据集上开发了该算法，并在独立数据集上验证了研究结果。在这两个数据集中，我们可以证明该算法能够敏感地区分梗死周围和对侧未受影响皮质的小胶质细胞形态。通过主成分分析降低维数，可以为小胶质细胞形状分析生成高度敏感的复合评分。最后，我们测试了新的自动化分析工具和传统的人工分析结果之间的一致性，发现高度相关。综上所述，与传统的分析方法相比，我们的小胶质细胞形态学全自动分析方法具有较高的准确性和时效性。这个工具，我们公开提供，可以在广泛的脑疾病模型中使用荧光成像来研究小胶质细胞形态。
Microglia are the resident immune cells of the brain and react quickly to changes in their environment with transcriptional regulation and morphological changes. Brain tissue injury such as ischemic stroke induces a local inflammatory response encompassing microglial activation. The change in activation status of a microglia is reflected in its gradual morphological transformation from a highly ramified into a less ramified or amoeboid cell shape. For this reason, the morphological changes of microglia are widely utilized to quantify microglial activation and studying their involvement in virtually all brain diseases. However, the currently available methods, which are mainly based on manual rating of immunofluorescent microscopic images, are often inaccurate, rater biased, and highly time consuming. To address these issues, we created a fully automated image analysis tool, which enables the analysis of microglia morphology from a confocal Z-stack and providing up to 59 morphological features. We developed the algorithm on an exploratory dataset of microglial cells from a stroke mouse model and validated the findings on an independent data set. In both datasets, we could demonstrate the ability of the algorithm to sensitively discriminate between the microglia morphology in the peri-infarct and the contralateral, unaffected cortex. Dimensionality reduction by principal component analysis allowed to generate a highly sensitive compound score for microglial shape analysis. Finally, we tested for concordance of results between the novel automated analysis tool and the conventional manual analysis and found a high degree of correlation. In conclusion, our novel method for the fully automatized analysis of microglia morphology shows excellent accuracy and time efficacy compared to traditional analysis methods. This tool, which we make openly available, could find application to study microglia morphology using fluorescence imaging in a wide range of brain disease models.
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DOI：
10.1083/jcb.201004104
发表时间：
2010-05-31
期刊：
The Journal of cell biology
影响因子：
--
作者：
Linkert M;Rueden CT;Allan C;Burel JM;Moore W;Patterson A;Loranger B;Moore J;Neves C;Macdonald D;Tarkowska A;Sticco C;Hill E;Rossner M;Eliceiri KW;Swedlow JR
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10.1523/jneurosci.2102-11.2011
发表时间：
2011-09-07
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
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作者：
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影响因子：
5.3
作者：
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DOI：
10.1016/j.pnpbp.2016.07.003
发表时间：
2017-10-03
影响因子：
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作者：
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影响因子：
56.9
作者：
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