Exploring personalized structural connectomics for moderate-to-severe traumatic brain injury
Journal article
Imms, Phoebe, Clemente, Adam, Deutscher, Evelyn, Radwan, Ahmed M., Akhlaghi, Hamed, Beech, Paul, Wilson, Peter H., Irimia, Andrei, Poudel, Govinda, Domínguez Duque, Juan F. and Caeyenberghs, Karen. (2023). Exploring personalized structural connectomics for moderate-to-severe traumatic brain injury. Network Neuroscience. 7(1), pp. 160-183. https://doi.org/10.1162/netn_a_00277
Authors | Imms, Phoebe, Clemente, Adam, Deutscher, Evelyn, Radwan, Ahmed M., Akhlaghi, Hamed, Beech, Paul, Wilson, Peter H., Irimia, Andrei, Poudel, Govinda, Domínguez Duque, Juan F. and Caeyenberghs, Karen |
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Abstract | 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 (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 personalized rehabilitation protocols based on their unique lesion load and connectome. |
Keywords | traumatic brain injury; structural connectomics; graph theory; personalized medicine; personalized connectomics; lesion filling |
Year | 2023 |
Journal | Network Neuroscience |
Journal citation | 7 (1), pp. 160-183 |
Publisher | MIT Press |
ISSN | 2472-1751 |
Digital Object Identifier (DOI) | https://doi.org/10.1162/netn_a_00277 |
PubMed ID | 37334004 |
Scopus EID | 2-s2.0-85148659365 |
PubMed Central ID | PMC10270710 |
Open access | Published as ‘gold’ (paid) open access |
Page range | 160-183 |
Funder | Australian Catholic University (ACU) |
National Health and Medical Research Council (NHMRC) | |
National Institutes of Health (NIH), United States of America | |
Department of Defense, United States of America | |
Hanson-Thorell Family Research Scholarship | |
James J. and Sue Femino Foundation | |
Publisher's version | License File Access Level Open |
Output status | Published |
Publication dates | |
Online | 01 Jan 2023 |
Publication process dates | |
Accepted | 06 Sep 2022 |
Deposited | 14 Aug 2023 |
Grant ID | 902915 |
1143816 | |
R01 NS 100973 | |
W81-XWH-1810413 |
https://acuresearchbank.acu.edu.au/item/8z825/exploring-personalized-structural-connectomics-for-moderate-to-severe-traumatic-brain-injury
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Publisher's version
OA_Imms_2023_Exploring_personalized_structural_connectomics_for_moderate.pdf | |
License: CC BY 4.0 | |
File access level: Open |
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