Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal.
ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal.
Hum Brain Mapp. 2022 Jun 1;43(8):2419-2443. doi: 10.1002/hbm.25773. Epub 2022 Mar 11.
Connectivity-based parcellation (CBP) methods are used to define homogenous and biologically meaningful parcels or nodes-the foundations of brain network fingerprinting-by grouping voxels with similar patterns of brain connectivity. However, we still lack a gold standard method and the use of CBPs to study the aging brain remains scarce. Our study proposes a novel CBP method from diffusion MRI data and shows its potential to produce a more accurate characterization of the longitudinal alterations in brain network topology occurring in aging. For this, we constructed whole-brain connectivity maps from diffusion MRI data of two datasets: an aging cohort evaluated at two timepoints (mean interval time: 52.8 ± 7.24 months) and a normative adult cohort-MGH-HCP. State-of-the-art clustering techniques were used to identify the best performing technique. Furthermore, we developed a new metric (connectivity homogeneity fingerprint [CHF]) to evaluate the success of the final CBP in improving regional/global structural connectivity homogeneity. Our results show that our method successfully generates highly homogeneous parcels, as described by the significantly larger CHF score of the resulting parcellation, when compared to the original. Additionally, we demonstrated that the developed parcellation provides a robust anatomical framework to assess longitudinal changes in the aging brain. Our results reveal that aging is characterized by a reorganization of the brain's structural network involving the decrease of intra-hemispheric, increase of inter-hemispheric connectivity, and topological rearrangement. Overall, this study proposes a new methodology to perform accurate and robust evaluations of CBP of the human brain.
基于连接的分区（CBP）方法用于通过将具有相似脑连接模式的体素分组来定义同质且具有生物学意义的区域或节点 - 即脑网络特征的基础。然而，我们仍然缺乏黄金标准方法，并且使用 CBP 来研究衰老大脑的情况仍然很少。我们的研究提出了一种从弥散磁共振成像数据中获取新的 CBP 方法，并展示了其在产生更准确描述衰老过程中脑网络拓扑结构纵向变化方面的潜力。为此，我们从两个数据集的弥散磁共振成像数据构建了全脑连接图：一个在两个时间点进行评估的衰老队列（平均间隔时间：52.8±7.24 个月）和一个正常成人队列 - MGH-HCP。使用最先进的聚类技术来识别表现最佳的技术。此外，我们开发了一种新的度量标准（连接同质性指纹[CHF]）来评估最终 CBP 在提高区域/全局结构连接同质性方面的成功。我们的结果表明，我们的方法成功地生成了高度同质的区域，这正如从原始分区中显著更大的 CHF 分数所描述的那样。此外，我们证明了所开发的分区为评估衰老大脑的纵向变化提供了稳健的解剖结构框架。我们的结果表明，衰老的特点是大脑结构网络的重组，涉及到半球内连接的减少、半球间连接的增加以及拓扑重排。总体而言，这项研究提出了一种新的方法来对人脑的 CBP 进行准确和稳健的评估。
