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Group analysis of DTI fiber tract statistics with application to neurodevelopment.

机译:DTI纤维束统计数据的分组分析及其在神经发育中的应用。

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Diffusion tensor imaging (DTI) provides a unique source of information about the underlying tissue structure of brain white matter in vivo including both the geometry of major fiber bundles as well as quantitative information about tissue properties represented by derived tensor measures. This paper presents a method for statistical comparison of fiber bundle diffusion properties between populations of diffusion tensor images. Unbiased diffeomorphic atlas building is used to compute a normalized coordinate system for populations of diffusion images. The diffeomorphic transformations between each subject and the atlas provide spatial normalization for the comparison of tract statistics. Diffusion properties, such as fractional anisotropy (FA) and tensor norm, along fiber tracts are modeled as multivariate functions of arc length. Hypothesis testing is performed non-parametrically using permutation testing based on the Hotelling T(2) statistic. The linear discriminant embedded in the T(2) metric providesan intuitive, localized interpretation of detected differences. The proposed methodology was tested on two clinical studies of neurodevelopment. In a study of 1 and 2 year old subjects, a significant increase in FA and a correlated decrease in Frobenius norm was found in several tracts. Significant differences in neonates were found in the splenium tract between controls and subjects with isolated mild ventriculomegaly (MVM) demonstrating the potential of this method for clinical studies.
机译:扩散张量成像(DTI)提供了有关体内脑白质潜在组织结构的信息的唯一来源,包括主要纤维束的几何形状以及有关由派生张量度量表示的组织性质的定量信息。本文提出了一种用于统计比较扩散张量图像种群之间的纤维束扩散特性的方法。无偏微晶态图集构建用于计算扩散图像总体的归一化坐标系。每个对象和地图集之间的微分变换为空间统计的比较提供了空间归一化。沿纤维束的扩散特性(例如分数各向异性(FA)和张量范数)被建模为电弧长度的多元函数。假设检验是使用基于Hotelling T(2)统计量的置换检验非参数执行的。嵌入在T(2)度量中的线性判别式提供了对检测到的差异的直观,本地化解释。在两项神经发育的临床研究中对提出的方法进行了测试。在一项针对1岁和2岁受试者的研究中,在几个区域中发现FA显着增加,而Frobenius规范相应降低。在对照组和孤立的轻度心室肥大(MVM)受试者之间的脾脏中发现了新生儿的显着差异,证明了该方法在临床研究中的潜力。

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