Diffusion Tensor Imaging of Wallerian Degeneration in MS

描述（由申请人提供）：扩散张量MRI（DTI）是一种功能强大的体内技术，对深部脑组织水微动力学和微观结构敏感。DTI衍生的方向和标量图具有独特的潜力，提供客观和具体的措施，多发性硬化症的病理。MS病理学的标志可能包括炎症、脱髓鞘、神经胶质增生、直接或间接通过沃勒变性（WD）导致的直接轴突丢失。WD可引起最初脱髓鞘病变远端的轴突丢失，其在MS中的特征尚未使用全面的DTI和常规MRI方法阐明。胼胝体（CC），锥体束，皮质脊髓束通过内囊（IC）是重要的结构，涉及在MS的神经功能缺损。不幸的是，有限的发表文献的MS在这些结构的DTI往往是不一致的，有时是矛盾的。基于我们的初步研究，这些不一致和矛盾，至少部分，可以归因于次优的采集方案，任意的感兴趣区域的位置，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。为了克服这些局限性，我们建议在3.0 T采集DTI数据，在不同年龄组的正常男性和女性使用并行成像。此外，还将采集MS受试者的MRI数据。DTI数据将使用优化的Icosa21方案从全脑采集，该方案被证明是平衡和无偏的。具体来说，我们将集中在CC，锥体束和CST涉及MS，以确定WD签名MS。我们将胼胝体分为七个功能不同的子区域。同样，内囊将被分为四个象限，其时空相关性将被纵向跟踪。将从这些单独结构中的每一个获得DTI值。将开发一个强大的DTI分析工具进行自动分析。该工具还将有助于多模态MRI数据的融合，以实现CC和1C子区域的稳健分割。在考虑年龄和性别依赖性后，DTI测量将与临床测量相关。

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.