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Local assessment of myelin health in a multiple sclerosis mouse model using a 2D Fourier transform approach

机译:使用2D傅立叶变换方法对多发性硬化症小鼠模型中的髓磷脂健康进行局部评估

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摘要

We present an automated two-dimensional Fourier transform (2D-FT) approach to analyze the local organization of myelinated axons in the spinal cord. Coherent anti-Stokes Raman scattering (CARS) microscopy was used to observe lesions in a commonly used animal model of multiple sclerosis (MS), experimental autoimmune encephalomyelitis (EAE). A 2D-FT was applied on the CARS images to find the average orientation and directional anisotropy of the fibers within contiguous image domains. We introduce the corrected correlation parameter (CCP), a measure of the correlation between orientations of adjacent domains. We show that in the EAE animal model of MS, the CCP can be used to quantify the degree of organization/disorganization in the myelin structure. This analysis was applied to a large image dataset from animals at different clinical scores and we show that some descriptors of the CCP probability density function are strongly correlated with the clinical scores. This procedure, compatible with live animal imaging, has been developed to perform local in situ evaluation of myelinated axons afflicted by EAE.
机译:我们提出了一种自动化的二维傅立叶变换(2D-FT)方法来分析脊髓中髓鞘轴突的局部组织。相干抗斯托克斯拉曼散射(CARS)显微镜用于观察多发性硬化症(MS),实验性自身免疫性脑脊髓炎(EAE)常用动物模型中的病变。将2D-FT应用于CARS图像,以找出连续图像域内纤维的平均方向和方向各向异性。我们介绍了校正的相关参数(CCP),它是相邻域方向之间相关性的一种度量。我们显示,在MS的EAE动物模型中,CCP可用于量化髓鞘结构中组织/无序的程度。这项分析被应用于来自具有不同临床评分的动物的大型图像数据集,并且我们显示了CCP概率密度函数的某些描述符与临床评分高度相关。已经开发了与活体动物成像兼容的程序,以对受EAE侵袭的髓鞘轴突进行本地原位评估。

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