Diffusion Tensor Imaging of Wallerian Degeneration in MS

描述（申请人提供）：弥散张量MRI （Diffusion tensor MRI， DTI）是一种强大的体内技术，对深部脑组织水微动力学和微观结构敏感。dti衍生的定向和标量图具有独特的潜力，可以提供客观和具体的多发性硬化症病理测量。多发性硬化的病理特征可能包括炎症、脱髓鞘、神经胶质瘤、直接或间接通过沃勒氏变性（WD）引起的轴突损失。WD可引起初始脱髓鞘病变远端轴突损失，其在MS中的特征尚未通过综合DTI和常规MRI方法阐明。胼胝体（CC）、锥体、皮质脊髓束穿过内囊（IC）是与MS神经功能障碍有关的重要结构。不幸的是，有限的关于MS在这些结构中的DTI的发表文献往往不一致，有时甚至是相互矛盾的。根据我们的初步研究，这些不一致和矛盾，至少在一定程度上可以归因于次优获取方案、任意兴趣区域放置、未能认识到这些结构的区域异质性、DTI测量的年龄和性别依赖性。为了克服这些限制，我们建议在不同年龄组的正常男性和女性中使用平行成像来获取3.0 T时的DTI数据。此外，还将获取MS受试者的MRI数据。DTI数据将使用优化的Icosa21方案从整个大脑中获取，该方案被证明是平衡和公正的。具体来说，我们将集中研究与多发性硬化症有关的CC、锥体和CST束，以确定多发性硬化症的WD特征。我们将胼胝体分为七个功能不同的亚区。同样，内部胶囊将被划分为四个象限，其时空相关性将纵向遵循。DTI值将从这些单独的结构中派生出来。一个强大的DTI分析工具将被开发用于自动分析。该工具还将有助于融合多模态MRI数据，对CC和1C的子区域进行稳健的分割。在考虑年龄和性别依赖后，DTI措施将与临床措施相关。

DESCRIPTION (provided by applicant): Diffusion tensor MRI (DTI) is a powerful in vivo technique that is sensitive to deep brain tissue water microdynamics and microstructure. DTI-derived orientation and scalar maps have the unique potential to provide objective and specific measures of the Multiple Sclerosis pathology. The hallmarks of MS pathology may include inflammation, demyelination, gliosis, direct axonal loss directly or indirectly through Wallerian degeneration (WD). WD can cause axonal loss distal from the initial demyelinating lesion and its signature in MS has not been elucidated using a comprehensive DTI and conventional MRI approach. The Corpus callosum (CC), pyramidal, corticospinal tracts coursing through the internal capsule (IC) are important structures that are implicated in neurological deficit in MS. Unfortunately, the limited published literature on DTI of MS in these structures is often inconsistent and sometimes contradictory. Based on our preliminary studies, these inconsistencies and contradictions, at least in part, could be attributed to sub-optimal acquisition schemes, arbitrary region of interest placement, failure to recognize the regional heterogeneity of these structures, the age and gender dependence of DTI measure. In order to overcome some of these limitations, we propose to acquire DTI data at 3.0 T using parallel imaging at different age groups on normal males and females. In addition, MRI data will also be acquired on MS subjects. The DTI data will be acquired from the whole brain using optimized Icosa21 scheme that is shown to be balanced and unbiased. Specifically we will concentrate on the CC, pyramidal and CST tracts which are implicated in MS, to identify WD signature in MS. We will divide the corpus callosum into seven functionally distinct sub regions. Similarly the internal capsule will be divided into four quadrants and its temporal-spatial correlations will be followed longitudinally. DTI values will be derived from each one of these individual structures. A robust DTI analysis tool will be developed for automatic analysis. This tool will also help in the fusion of multi-modal MRI data for a robust segmentation of the subregions of CC and 1C. The DTI measures, after accounting for the age and gender dependence will be correlated with the clinical measures.