Spinocerebellar Ataxia type 7 (SCA7) is a neurodegenerative disease characterized by progressive cerebellar ataxia and retinal degeneration. Increasing loss of visual function complicates the use of clinical scales to track the progression of motor symptoms, hampering our ability to develop accurate biomarkers of disease progression, and thus test the efficacy of potential treatments. In this cross-sectional study, we aimed to identify imaging measures of neurodegeneration, which may more accurately reflect SCA7 severity and progression. We analyzed diffusion tensor imaging (DTI) data collected from a cohort of 13 SCA7 patients and 14 healthy volunteers using two recent methodological advances: 1) a diffusion tensor-based image registration technique, and 2) a dual-compartment DTI model to control for the potential increase in extracellular CSF-like water due to neurodegeneration. These methodologies allowed us to assess both volumetric and microstructural abnormalities in both white and gray matter brain-wide in SCA7 patients for the first time. To measure tissue volume, we performed diffusion tensor-based morphometry (DTBM) using the tensor-based registration. To assess tissue microstructure, we computed the parenchymal mean diffusivity (pMD) and parenchymal fractional anisotropy (pFA) using the dual compartment model. This model also enabled us to estimate the parenchymal volume fraction (pVF), a measure of parenchymal tissue volume within a given voxel. While DTBM and pVF revealed tissue loss primarily in the brainstem, cerebellum, thalamus, and a subset of cerebral white matter tracts in patients, pMD and pFA detected microstructural abnormalities brain-wide (p < 0.05, FWE corrected; Hedge's g > 1). This distinction was meaningful in terms of motor symptom severity, as we found that patient scores on the Scale for the Assessment and Rating of Ataxia correlated most strongly with cerebellar pVF (r = -0.66, p = 0.015) and global white matter pFA (r = -0.64, p = 0.018). Since this contrast between focal tissue loss and global microstructural abnormality has previously been described in neuropathology, we believe the approach employed here is well suited for the in-vivo assessment of neurodegeneration. Moving forward, this approach could be applied to characterize the full spatiotemporal pattern of neurodegeneration in SCA7, and potentially develop an accurate imaging biomarker of disease progression.

中文翻译：

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体内评估7型脊髓小脑共济失调的神经变性

脊髓小脑共济失调7型（SCA7）是一种神经退行性疾病，其特征是进行性小脑共济失调和视网膜变性。越来越多的视觉功能丧失使临床量表难以追踪运动症状的进展，从而阻碍了我们开发疾病进展的准确生物标志物的能力，从而测试了潜在疗法的有效性。在这项横断面研究中，我们旨在确定神经退行性变的影像学指标，它可能更准确地反映SCA7的严重程度和进展。我们使用两项最新的方法学进展分析了从13名SCA7患者和14名健康志愿者的队列中收集的扩散张量成像（DTI）数据：1）基于扩散张量的图像配准技术，2）双室DTI模型，以控制由于神经变性导致的细胞外CSF样水的潜在增加。这些方法使我们能够首次评估SCA7患者全脑的白质和灰质的体积和微结构异常。为了测量组织体积，我们使用基于张量的配准进行了基于扩散张量的形态测定（DTBM）。为了评估组织的微观结构，我们使用双室模型计算了实质平均扩散率（pMD）和实质分数各向异性（pFA）。该模型还使我们能够估计实质体积分数（pVF），这是给定体素内实质组织体积的量度。虽然DTBM和pVF揭示组织损失主要发生在脑干，小脑，丘脑，以及患者脑白质子集的一部分，pMD和pFA在全脑范围内检测到微结构异常（p <0.05，经FWE校正； Hedge's g> 1）。就运动症状的严重程度而言，这种区别是有意义的，因为我们发现共济失调评估和评定量表上的患者评分与小脑pVF（r = -0.66，p = 0.015）和总体白质pFA（r ＝ -0.64，p ＝ 0.018）。由于先前已在神经病理学中描述了局灶性组织丢失与整体微结构异常之间的这种对比，因此我们认为此处采用的方法非常适合于 因为我们发现共济失调评估和评定量表上的患者评分与小脑pVF（r = -0.66，p = 0.015）和整体白质pFA（r = -0.64，p = 0.018）密切相关。由于先前已在神经病理学中描述了局灶性组织丢失与整体微结构异常之间的这种对比，因此我们认为此处采用的方法非常适合于 因为我们发现共济失调评估和评定量表上的患者评分与小脑pVF（r = -0.66，p = 0.015）和整体白质pFA（r = -0.64，p = 0.018）密切相关。由于先前已在神经病理学中描述了局灶性组织丢失与整体微结构异常之间的这种对比，因此我们认为此处采用的方法非常适合于体内评估神经变性。展望未来，该方法可用于表征SCA7中神经变性的完整时空模式，并有可能开发出疾病进展的精确成像生物标记。