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首页> 外文期刊>NeuroImage >Distribution of grey matter atrophy in Huntington's disease patients: a combined ROI-based and voxel-based morphometric study.
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Distribution of grey matter atrophy in Huntington's disease patients: a combined ROI-based and voxel-based morphometric study.

机译:亨廷顿病患者中灰质萎缩的分布:基于ROI和基于体素的形态学研究相结合。

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The striatum, a subcortical structure, is the principal target of the neurodegenerative process in Huntington's disease (HD). The measurement of striatal atrophy using the bicaudate ratio on CT scanner images has therefore been used for years to assess disease progression, but this measure only takes into account unidimensional changes in the head of the caudate nucleus. Recently, voxel-based morphometry (VBM), which permits automated statistical comparisons of whole-brain MRI images, has been proposed to quantify striatal atrophy. However, VBM was not originally designed to study subcortical structures, and severe deep brain deformations that occur in HD may hamper the automatic processing of VBM. Here, we validate the use of the optimised protocol of VBM to quantify subcortical atrophy in HD by comparing results obtained with this method to those provided by manual segmentation of subcortical structures. We studied 20 patients with early HD and 12 controls matched for age, sex and handedness using animproved T1-weighted sequence that eased grey matter segmentation. Both manual and automated methods evidenced the dorso-ventral gradient of striatal atrophy, a loss of grey matter in the globus pallidus and the thalamus, and similar correlations between clinical scores and subcortical atrophy. Furthermore, we were able to detect with VBM grey matter loss in the substantia nigra, the hypothalamus, the amygdala, the insular cortex and the premotor and sensorimotor cortices. Finally, VBM provided results consistent with previous post mortem results and proved to be a sensitive biomarker capable of correctly managing subcortical distortions throughout HD patients' brains.
机译:纹状体是皮层下的结构,是亨廷顿舞蹈病(HD)中神经退行性过程的主要目标。因此,使用CT扫描仪图像上的双尾形比测量纹状体萎缩已被用于评估疾病的进展多年,但是这种测量仅考虑了尾状核头部的一维变化。最近,已经提出了基于体素的形态计量学(VBM),其可以对全脑MRI图像进行自动统计比较,以量化纹状体萎缩。但是,VBM最初并不是设计用于研究皮层下结构的,HD中发生的严重的深部脑部变形可能会妨碍VBM的自动处理。在这里,我们通过将用这种方法获得的结果与通过人工分割皮层下结构提供的结果进行比较,来验证使用VBM优化协议量化HD皮层下萎缩的情况。我们使用改良的T1加权序列简化了灰质分割,研究了20例早期HD患者和12例年龄,性别和惯用性匹配的对照。手动和自动方法均证明纹状体萎缩的背腹梯度,苍白球和丘脑中灰质的损失以及临床评分与皮质下萎缩之间的相似相关性。此外,我们能够用VBM检测到黑质,下丘脑,杏仁核,岛叶皮层以及运动前和感觉运动皮质的灰质损失。最后,VBM提供的结果与以前的验尸结果一致,并被证明是一种敏感的生物标记物,能够正确处理整个HD患者大脑中的皮层下畸变。

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