Towards pratical Mapping of Complex White Matter Fiber Pathways by Disffusion-Wei

描述（由申请人提供）：拟议项目的总体目标是开发一种实用的方法，即使在存在病理的情况下，也可以通过复杂纤维几何形状的区域在大脑中长距离绘制白色物质通路。基于扩散张量的确定性流线纤维跟踪，使用扩散加权MRI（DW-MRI）的数据，可以映射高度组织化的白色物质路径，但遇到纤维交叉和肿瘤和白色物质疾病的典型低各向异性区域时失败。许多功能上重要的白色物质通路不能用常规方法绘制。拟议项目的具体目标是开发具有客观优化的正则化的球面去卷积，这是一种用于定义纤维方向分布（FOD）的方法，作为概率跟踪的基础，以在一小时内使用传统计算资源定义运动路径。功能重要的运动通路包括许多交叉点。虽然基于FOD的持续角结构（PAS）估计的概率跟踪已经被示出识别到整个运动通路的连接，但是PAS的计算成本是过高的，对于体内数据集需要大约90个cpu-DAYS。具有客观优化的正则化的球面反卷积需要两个CPU分钟。然而，由于基于PAS的跟踪已经识别了整个运动区，并且已经在动物模型中得到了验证，因此在缺乏容易获得的金标准的情况下，它将作为比较的基础。因此，拟议的项目将比较PAS和球面去卷积与客观优化的正则化，就其在跟踪运动通路方面的性能。一个20处理器的Linux集群将能够进行PAS计算，并将用于优化球面去卷积方法。来自20名健康受试者的DW-MRI数据将用于通过球面反卷积计算FOD，其中客观优化的正则化和PAS作为概率跟踪的基础。初级运动皮层，跟踪的种子区域，将通过BOLD-fMRI识别。与双侧运动皮层区域相交的轨迹将被识别为运动通路。如果发现每种方法识别的运动通路之间具有统计学显著的相关性，并且使用常规计算资源的总计算时间小于1小时，则该项目的目标已经实现。同样的分析将在10名多发性硬化症患者中进行，作为一个单独的组，以评估存在疾病的方法。在实现总体目标后，将在绘制白色物质路径的实用方法方面取得进展。与灰质相比，由于成像上相对缺乏解剖标志，与白色物质的给定区域相关的功能及其损伤可能不清楚。开发一种更普遍适用的定义白色物质通路的方法将作为改进手术前计划和更好地评估治疗对白色物质区域损伤或修复的重要性的基础。公共卫生相关性大脑中的白色物质包含功能上重要的连接途径。拟议的项目旨在开发一种实用的方法，用于非侵入性映射难以或不可能用当前方法描绘的通路，从而将这种映射的实用性扩展到整个大脑。因此，可以提高对白色疾病的诊断，更好地评估白色病变的潜在影响，并改善术前计划。

DESCRIPTION (provided by applicant): The overall objective of the proposed project is to develop a practical method for mapping white matter pathways over long distances in the brain through regions of complex fiber geometries even in the presence of pathology. Diffusion tensor-based deterministic streamline fiber tracking, using data from Diffusion-Weighted MRI (DW-MRI), can map highly organized white matter pathways, but fails upon encountering fiber crossings and low anisotropy regions typical of neoplasms and white matter disease. A number of functionally important white matter pathways cannot be mapped by conventional methods. The specific aim of the proposed project is to develop spherical deconvolution with objectively optimized regularization, a method for defining the Fiber Orientation Distribution (FOD), as the basis of probabilistic tracking to define the motor pathway in under one hour with conventional computing resources. The functionally important motor pathway encompasses numerous crossings. Although probabilisitic tracking based on persistent angular structure (PAS) estimation of the FOD has been shown to identify connections to the entire motor pathway, the computational cost of PAS is prohibitive, requiring on the order of 90 cpu-DAYS for an in vivo dataset. Spherical deconvolution with objectively optimized regularization requires two cpu-minutes. However, as PAS-based tracking has identified the entire motor area and has been validated in an animal model, it will serve as the basis for comparison in the absence of a readily accessible gold standard. The proposed project will therefore compare PAS and spherical deconvolution with objectively optimized regularization with regard to their performance in tracking the motor pathway. A 20-processor Linux cluster will enable the PAS calculation and will be used to optimize the spherical deconvolution method. DW-MRI data from 20 healthy subjects will be used to calculate FODs by spherical deconvolution with objectively optimized regularization and PAS as the basis of probabilistic tracking. Primary motor cortex, the seed regions for tracking, will be identified by BOLD-fMRI. Tracks that intersect both bilateral motor cortex regions will be identified as the motor pathway. The goal of this project will have been achieved if a statistically significant correlation between motor pathway identified by each method is found, and the total computation time is under one hour with conventional computing resources. The same analysis will be performed in 10 multiple sclerosis patients as a separate group to evaluate the methodology in the presence of disease. Upon achievement of the overall objective, progress toward a practical method for mapping white matter pathways will have been made. Due to a relative lack of anatomical landmarks on imaging, as compared with gray matter, the function associated with a given region of white matter and damage thereto can be unclear. Development of a more universally applicable method for defining white matter pathways will serve as the basis for improved presurgical planning and better assessment of the importance of injury or repair by therapy to regions of white matter. PUBLIC HEALTH RELEVANCE White matter in the brain contains functionally important connection pathways. The proposed project aims to develop a practical method for noninvasive mapping of pathways that are difficult or impossible to delineate with current methods, thus extending the utility of such mapping to the entire brain. Improved diagnosis of white matter disease, better assessment of the potential impact of lesions in white matter, and improved presurgical planning may therefore result.