Xu Frederick, Duong-Tran Duy, Zhao Yize, Shen Li
Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
Department of Mathematics, United States Naval Academy, Annapolis, MD, USA.
IEEE EMBS Int Conf Biomed Health Inform. 2024 Nov;2024. doi: 10.1109/bhi62660.2024.10913835. Epub 2025 Mar 17.
Neuroimaging studies have demonstrated that Alzheimer's disease (AD) is closely related to changes in neuroanatomy in the form of damage to both grey matter and white matter. However, the exact nature of AD's relationship with white matter anatomical deterioration is not fully understood at a systemic level. To investigate this knowledge gap, we constructed structural brain networks from ADNI-GO/2 diffusion tensor imaging (DTI) images with brain regions of interest (ROIs) as nodes and white matter connections as edges weighted by fiber density. The cohort consists of healthy control (HC), mild cognitive impairment (MCI), and clinically diagnosed AD subjects. By optimizing consensus modularity of structural brain networks at a subpopulation level to investigate community structure throughout a range of resolution parameters (γ), we observed a split of the reward-based decision-making module in the AD group at γ = 1.3, thus finding a 7 consensus community in the AD consensus brain network partition that was not present in that of MCI or HC populations. Upon further investigation, we found that thalamic and caudal regions were involved in the increased segregation of AD brain networks. These regions are implicated in regulation of decision-making processes, and their segregation from other decision-making regions is a novel finding in white matter biomarker studies of AD. Our study presents novel evidence that AD may be a disconnection syndrome at the mesoscopic structural level, with potential new avenues of exploration into the role of the thalamus and caudate that may reveal neural correlates of cognitive deficits in clinically diagnosed AD.
神经影像学研究表明，阿尔茨海默病（AD）与神经解剖结构的变化密切相关，表现为灰质和白质均受损。然而，在系统层面上，AD与白质解剖结构恶化之间关系的确切性质尚未完全明了。为了填补这一知识空白，我们利用阿尔茨海默病神经成像计划（ADNI）-GO/2扩散张量成像（DTI）图像构建了脑结构网络，将感兴趣的脑区（ROI）作为节点，白质连接作为边，并根据纤维密度进行加权。该队列包括健康对照（HC）、轻度认知障碍（MCI）和临床诊断为AD的受试者。通过在亚群体水平上优化脑结构网络的一致性模块度，以研究一系列分辨率参数（γ）下的社区结构，我们观察到在γ = 1.3时，AD组中基于奖励的决策模块出现分裂，从而在AD一致性脑网络分区中发现了一个MCI或HC群体中不存在的7个一致性社区。进一步研究发现，丘脑和尾状区域参与了AD脑网络分离的增加。这些区域与决策过程的调节有关，它们与其他决策区域的分离是AD白质生物标志物研究中的一个新发现。我们的研究提供了新的证据，表明AD可能是一种介观结构水平的连接障碍综合征，为探索丘脑和尾状核的作用开辟了新的途径，这可能揭示临床诊断AD中认知缺陷的神经关联。
