Graph theoretical analysis of the structural connectome has been employed successfully to characterise 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 personalised connectomics approach that examines structural brain alterations in five chronic patients with moderate-to-severe TBI who underwent anatomical and diffusion magnetic resonance imaging (MRI). We generated individualised profiles of lesion characteristics and network measures (including personalised graph metric ‘GraphMe’ plots, and nodal and edge-based brain network alterations) and compared them against healthy reference cases (N = 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 personalised rehabilitation protocols based on their unique lesion load and connectome.

Graph theoretical analysis of the structural connectome has been employed successfully to characterise 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 personalised connectomics approach that examines structural brain alterations in six chronic patients with moderate-to-severe TBI who underwent anatomical and diffusion magnetic resonance imaging (MRI). We generated individualised profiles of lesion characteristics and network measures (including personalised graph metric ‘GraphMe’ plots, and nodal and edge-based brain network alterations) and compared them against healthy reference cases (N=12) to assess brain damage qualitatively and quantitatively at the individual level. Our findings revealed clinically significant alterations of brain networks with high variability between patients. Our profiling can be used by clinicians to formulate a neuroscience-guided integrative rehabilitation program for TBI patients, and for designing personalised rehabilitation protocols based on their unique lesion load and connectome.

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Approximately 65% of moderate-to-severe traumatic brain injury (m-sTBI) patients present with poor long-term behavioural outcomes, which can significantly impair activities of daily living. Numerous diffusion-weighted MRI studies have linked these poor outcomes to decreased white matter integrity of several commissural tracts, association fibres and projection fibres in the brain. However, these studies focused on group-based analyses, which are unable to deal with the substantial between-patient heterogeneity in m-sTBI. As a result, there is increasing interest in conducting individualised neuroimaging analyses. Here, we generated a detailed subject-specific characterisation of microstructural organisation of white matter tracts in 5 chronic patients with m-sTBI (29 – 49y, 2 females). We developed an imaging analysis framework using fixel-based analysis and TractLearn to determine whether the values of fibre density of white matter tracts at the individual patient level deviate from the healthy control group (n = 12, 8F, Mage=35.7y, age range 25 – 64y). Our individualised analysis confirmed unique white matter profiles, and the heterogeneous nature of m-sTBI to properly characterise the extent of brain abnormality. Future studies incorporating clinical data, as well as utilising larger reference samples and examining the test-retest reliability of the fixel-wise metrics are warranted. This proof-of-concept study suggests that these resulting individual profiles may assist clinicians in planning personalised training programs for chronic m-sTBI patients, which is necessary to achieve optimal behavioural outcomes and improved quality of life.