自动子束示踪测量揭示复杂白质拓扑中的局部微结构变异

中文摘要 AI 辅助

传统示踪测量将白质微结构平均为单一剖面，掩盖了束内空间异质性并稀释了局部改变。我们提出了一种自动子束示踪测量框架，使用基于Fréchet的层次聚类将纤维束分解为几何上连贯的子束，无需经验阈值即可解析复杂的扇形配置。多隔室指标（各向异性分数，FA；各向同性自由水分数，IFW）被投影到这些聚类上。我们在140名参与者中评估了该框架，涵盖早期生活（ELD）和晚期生活（LLD）抑郁队列，以及年龄匹配的健康对照。我们基于微结构同质性、对年龄的敏感性和临床组差异来评估性能。所提出的子束指标显著比经典全束剖面更同质（p < 0.001）。我们的方法显示出增强的敏感性，在老年对照中检测到更多与年龄相关的纤维束（11对5），并在LLD中检测到更多临床组差异（FA：6对4；IFW：23对17），且效应量更大。在ELD中，它改善了缓解与耐药个体之间细微FA差异的检测（2.9%对1.8%）。增益在LLD中尤为显著，反映了该框架解析易受脑老化影响的扇形纤维束的能力。通过保留空间异质性，这种自动分解为大规模临床示踪测量提供了稳健的基础。

英文摘要

Conventional tractometry averages white matter microstructure into a single profile, masking intra-bundle spatial heterogeneity and diluting localized alterations. We propose an automatic sub-bundle tractometry framework using Fr{é}chet-based hierarchical clustering to decompose bundles into geometrically coherent sub-bundles, resolving complex fanning configurations without empirical thresholds. Multi-compartment metrics (fractional anisotropy, FA; isotropic free-water fraction, IFW) are projected onto these clusters. We evaluated this framework in 140 participants across early-life (ELD) and late-life (LLD) depression cohorts, alongside age-matched healthy controls. We assessed performance based on microstructural homogeneity, sensitivity to age, and clinical group differences. Proposed sub-bundle metrics were significantly more homogeneous than classical full bundle profiles (p < 0.001). Our approach showed enhanced sensitivity, detecting more age-correlated bundles in elderly controls (11 vs. 5) and more clinical group differences in LLD (FA: 6 vs. 4; IFW: 23 vs. 17) with larger effect sizes. In ELD, it improved the detection of subtle FA differences between remitted and resistant individuals (2.9% vs. 1.8%). Gains were particularly pronounced in LLD, reflecting the framework's ability to resolve fanning tracts susceptible to brain aging. By preserving spatial heterogeneity, this automatic decomposition provides a robust foundation for large-scale clinical tractometry.

发表机构

• Univ Rennes, INRIA, CNRS, INSERM, IRISA UMR 6074, Empenn ERL U 1228（雷恩大学）
• Adult University Psychiatry Department, Guillaume Régnier Hospital（吉约姆·雷尼尔医院成人大学精神科）
• Université de Tours, INSERM, Imaging Brain & Neuropsychiatry iBraiN U1253（图尔大学）
• CHU de Tours, INSERM, CIC1415（图尔大学医院）
• Centre for Population Neuroscience and Stratified Medicine, Charité Universitätsmedizin Berlin（柏林夏里特医科大学人口神经科学与分层医学中心）
• INSERM U1299 "Developmental Trajectories & Psychiatry", Centre Borelli, UMR9010（巴黎萨克雷大学）
• Dept mathematics, ENS Paris-Saclay, Univ Paris Saclay（皮蒂埃萨尔佩特里埃尔医院）
• AP-HP Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital

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