Diffusion Tensor Imaging of Wallerian Degeneration in MS

描述(申请人提供)：弥散张量磁共振成像(DTI)是一种强大的在体技术，对深部脑组织水、微动力学和微结构敏感。DTI定位图和标量图具有提供多发性硬化症病理的客观和特定测量的独特潜力。多发性硬化症的病理特征可能包括炎症、脱髓鞘、胶质增生、直接或间接通过沃勒变性(WD)造成的轴突丢失。WD可导致最初脱髓鞘病变远端的轴突丢失，其在MS中的特征尚未通过全面的DTI和常规MRI方法阐明。通过内囊(IC)的胼胝体、锥体、皮质脊髓束是MS的重要结构，与MS的神经功能障碍有关。遗憾的是，有关MS在这些结构中的弥散张量成像的有限文献往往是不一致的，有时甚至是矛盾的。根据我们的初步研究，这些不一致和矛盾，至少部分可以归因于次优获取方案，任意的感兴趣区域布置，未能认识到这些结构的区域异质性，DTI测量的年龄和性别相关性。为了克服这些局限性，我们建议在3.0T下对正常男性和女性进行不同年龄段的并行成像。此外，还将获得多发性硬化症受试者的MRI数据。DTI数据将使用优化的ICosa21方案从整个大脑获取，该方案被证明是平衡和无偏见的。具体地说，我们将集中在多发性硬化症中涉及的CC、锥体和CST束，以识别多发性硬化症中的WD特征。我们将胼胝体划分为七个功能不同的亚区。类似地，内舱将被分成四个象限，其时间-空间相关性将被纵向跟踪。DTI值将从这些单独的结构中的每一个派生出来。将开发一个强大的DTI分析工具，用于自动分析。该工具还将有助于融合多模式MRI数据，以实现CC和1C亚区的稳健分割。DTI测量在考虑了年龄和性别依赖后，将与临床测量相关联。

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.