Diffusion MRI (dMRI) tractography is currently the only method for in vivo mapping of the brain's white matter (WM) connections. Tractometry is an advanced tractography analysis technique for along-tract profiling to investigate the morphology and microstructural properties along the fiber tracts. Tractometry has become an essential tool for studying local along-tract differences between different populations (e.g., health vs disease). In this study, we propose a novel atlas-guided fine-scale tractometry method, namely AGFS-Tractometry, that leverages tract spatial information and permutation testing to enhance the along-tract statistical analysis between populations. There are two major contributions in AGFS-Tractometry. First, we create a novel atlas-guided tract profiling template that enables consistent, fine-scale, along-tract parcellation of subject-specific fiber tracts. Second, we propose a novel nonparametric permutation testing group comparison method to enable simultaneous analysis across all along-tract parcels while correcting for multiple comparisons. We perform experimental evaluations on synthetic datasets with known group differences and in vivo real data. We compare AGFS-Tractometry with two state-of-the-art tractometry methods, including Automated Fiber-tract Quantification (AFQ) and BUndle ANalytics (BUAN). Our results show that the proposed AGFS-Tractometry obtains enhanced sensitivity and specificity in detecting local WM differences. In the real data analysis experiments, AGFS-Tractometry can identify more regions with significant differences, which are anatomically consistent with the existing literature. Overall, these demonstrate the ability of AGFS-Tractometry to detect subtle or spatially localized WM group-level differences. The created tract profiling template and related code are available at: https://github.com/ZhengRuixi/AGFS-Tractometry.git.

翻译：扩散磁共振成像（dMRI）纤维束成像技术是目前唯一能够活体绘制大脑白质（WM）连接的方法。纤维束测量是一种先进的纤维束成像分析技术，通过对纤维束进行沿束分析，以研究沿纤维束的形态学和微观结构特性。纤维束测量已成为研究不同群体（例如，健康与疾病）之间局部沿束差异的重要工具。在本研究中，我们提出了一种新型的图谱引导精细尺度纤维束测量方法，即AGFS-Tractometry，该方法利用纤维束空间信息和置换检验来增强群体间的沿束统计分析。AGFS-Tractometry有两个主要贡献。首先，我们创建了一种新颖的图谱引导纤维束分析模板，能够对个体特异性纤维束进行一致、精细尺度的沿束分区。其次，我们提出了一种新的非参数置换检验群体比较方法，能够在校正多重比较的同时，对所有沿束分区进行同步分析。我们在已知群体差异的合成数据集和活体真实数据上进行了实验评估。我们将AGFS-Tractometry与两种先进的纤维束测量方法进行了比较，包括自动纤维束量化（AFQ）和纤维束分析（BUAN）。我们的结果表明，所提出的AGFS-Tractometry在检测局部白质差异方面获得了更高的敏感性和特异性。在真实数据分析实验中，AGFS-Tractometry能够识别出更多具有显著差异的区域，这些区域在解剖学上与现有文献一致。总体而言，这些结果证明了AGFS-Tractometry检测细微或空间局部化白质群体水平差异的能力。所创建的纤维束分析模板及相关代码可在以下网址获取：https://github.com/ZhengRuixi/AGFS-Tractometry.git。