Imms Phoebe, Clemente Adam, Deutscher Evelyn, Radwan Ahmed M, Akhlaghi Hamed, Beech Paul, Wilson Peter H, Irimia Andrei, Poudel Govinda, Domínguez Duque Juan F, Caeyenberghs Karen
Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
Healthy Brain and Mind Research Centre, School of Behavioural, Health, and Human Sciences, Faculty of Health Sciences, Australian Catholic University, Fitzroy, Victoria, Australia.
Netw Neurosci. 2023 Jan 1;7(1):160-183. doi: 10.1162/netn_a_00277. eCollection 2023.
Graph theoretical analysis of the structural connectome has been employed successfully to characterize brain network alterations in patients with traumatic brain injury (TBI). However, heterogeneity in neuropathology is a well-known issue in the TBI population, such that group comparisons of patients against controls are confounded by within-group variability. Recently, novel single-subject profiling approaches have been developed to capture inter-patient heterogeneity. We present a personalized connectomics approach that examines structural brain alterations in five chronic patients with moderate to severe TBI who underwent anatomical and diffusion magnetic resonance imaging. We generated individualized profiles of lesion characteristics and network measures (including personalized graph metric GraphMe plots, and nodal and edge-based brain network alterations) and compared them against healthy reference cases ( = 12) to assess brain damage qualitatively and quantitatively at the individual level. Our findings revealed alterations of brain networks with high variability between patients. With validation and comparison to stratified, normative healthy control comparison cohorts, this approach could be used by clinicians to formulate a neuroscience-guided integrative rehabilitation program for TBI patients, and for designing personalized rehabilitation protocols based on their unique lesion load and connectome.
结构连接组的图论分析已成功用于表征创伤性脑损伤(TBI)患者的脑网络改变。然而,神经病理学的异质性是TBI患者群体中一个众所周知的问题,以至于患者与对照组的组间比较会因组内变异性而混淆。最近,已开发出新颖的单受试者分析方法来捕捉患者间的异质性。我们提出了一种个性化连接组学方法,该方法研究了五名中度至重度TBI慢性患者的脑结构改变,这些患者接受了解剖学和扩散磁共振成像。我们生成了病变特征和网络测量的个性化概况(包括个性化图指标GraphMe图,以及基于节点和边的脑网络改变),并将它们与健康对照病例(n = 12)进行比较,以在个体水平上定性和定量地评估脑损伤。我们的研究结果揭示了患者间脑网络的高度变异性改变。通过验证并与分层的、规范的健康对照比较队列进行比较,临床医生可以使用这种方法为TBI患者制定神经科学指导的综合康复计划,并根据他们独特的损伤负荷和连接组设计个性化康复方案。