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Grey matter volume in healthy and epileptic beagles using voxel-based morphometry – a pilot study

机译:基于体素形态学的健康和癫痫小猎犬的灰质体积–一项初步研究

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摘要

BackgroundOne of the most common chronic neurological disorders in dogs is idiopathic epilepsy (IE) diagnosed as epilepsy without structural changes in the brain. In the current study the hypothesis should be proven that subtle grey matter changes occur in epileptic dogs. Therefore, magnetic resonance (MR) images of one dog breed (Beagles) were used to obtain an approximately uniform brain shape. Local differences in grey matter volume (GMV) were compared between 5 healthy Beagles and 10 Beagles with spontaneously recurrent seizures (5 dogs with IE and 5 dogs with structural epilepsy (SE)), using voxel-based morphometry (VBM). T1W images of all dogs were prepared using Amira 6.3.0 for brain extraction, FSL 4.1.8 for registration and SPM12 for realignment. After creation of tissue probability maps of cerebrospinal fluid, grey and white matter from control images to segment all extracted brains, GM templates for each group were constructed to normalize brain images for parametric statistical analysis, which was achieved using SPM12.
机译:背景技术犬中最常见的慢性神经系统疾病之一是特发性癫痫病(IE),被诊断为癫痫病,大脑中没有结构性变化。在当前的研究中,应该证明这一假设,即癫痫犬会发生细微的灰质变化。因此,一种犬种(比格犬)的磁共振(MR)图像用于获得近似均匀的大脑形状。使用基于体素的形态计量学(VBM)比较了5例健康小猎犬和10例自发反复发作的小猎犬(5例IE犬和5例结构性癫痫(SE)狗)的灰质体积(GMV)的局部差异。使用Amira 6.3.0进行脑部提取,FSL 4.1.8进行配准,SPM12进行重新排列,准备所有狗的T1W图像。从对照图像创建脑脊液,灰质和白质的组织概率图以分割所有提取的大脑后,构建每组的GM模板以对脑图像进行归一化以进行参数统计分析,这是使用SPM12实现的。

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