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首页> 外文期刊>Magnetic resonance imaging: An International journal of basic research and clinical applications >Evaluation of diffusion models of fiber tracts using diffusion tensor magnetic resonance imaging
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Evaluation of diffusion models of fiber tracts using diffusion tensor magnetic resonance imaging

机译:使用扩散张量磁共振成像评估纤维束的扩散模型

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摘要

Modeling of water diffusion in white matter is useful for revealing microstructure of the brain tissue and hence diagnosis and evaluation of white matter diseases. Researchers have modeled diffusion in white matter using mathematical and mechanical analysis at the cellular level. However, less work has been devoted to evaluate these models using macroscopic real data such as diffusion tensor magnetic resonance imaging (DTMRI) data. DTMRI is a noninvasive tool for evaluating white matter microstructure by measuring random motion of water molecules referred to as diffusion. It reflects directional information of microscopic structures such as fibers. Thus, it is applicable for evaluation and modification of mathematical models of white matter. Nevertheless, a realistic relation between a fiber model and imaging data does not exist. This work opens a promising avenue for relating DTMRI data to microstructural parameters of white matter. First, we propose a strategy for relating DTMRI and fiber model parameters to evaluate mathematical models in light of real data. The proposed strategy is then applied to evaluate and extend an existing model of white matter based on clinically available DTMRI data. Next, the proposed strategy is used to estimate microstructural characteristics of fiber tracts. We illustrate this approach through its application to approximation of myelin sheath thickness and fraction of volume occupied by fibers. Using sufficiently small imaging voxels, the proposed approach is capable of estimating model parameters with desirable precision.
机译:白质中水扩散的模型可用于揭示脑组织的微观结构,从而诊断和评估白质疾病。研究人员已经在细胞水平上使用数学和力学分析对白质中的扩散进行了建模。但是,使用宏观真实数据(例如扩散张量磁共振成像(DTMRI)数据)评估这些模型的工作较少。 DTMRI是一种非侵入性工具,可通过测量水分子的随机运动(称为扩散)来评估白质微观结构。它反映了诸如纤维之类的微观结构的方向信息。因此,它适用于白质数学模型的评估和修改。然而,在纤维模型和成像数据之间不存在现实的关系。这项工作为将DTMRI数据与白质的微观结构参数相关开辟了广阔的前景。首先,我们提出了一种将DTMRI和纤维模型参数相关联以根据实际数据评估数学模型的策略。然后根据临床可用的DTMRI数据,将提出的策略应用于评估和扩展现有的白质模型。接下来,所提出的策略用于估计纤维束的微结构特征。我们通过将其应用于髓鞘厚度和纤维所占体积分数的近似值来说明这种方法。使用足够小的成像体素,提出的方法能够以期望的精度估计模型参数。

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