Longitudinal white matter microstructural changes in pediatric mild traumatic brain injury: An<scp>A‐CAP</scp>study

Ware, Ashley L.; Yeates, Keith Owen; Tang, Ken; Shukla, Ayushi; Onicas, Adrian; Guo, Sunny; Goodrich-Hunsaker, Naomi J.; Abdeen, Nishard; Beauchamp, Miriam H.; Beaulieu, Christian; Björnson, Bruce; Craig, William; Dehaes, Mathieu; Doan, Quynh; Deschênes, Sylvain; Freedman, Stephen B.; Goodyear, Bradley G.; Gravel, Jocelyn; Ledoux, Andrée-Anne; Zemek, Roger; Lebel, Catherine

doi:10.1002/hbm.25885

Cited by 23 publications

(23 citation statements)

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“…The children with mTBI and OI did not differ in any global network metrics before or after each harmonization approach. This was expected given that DTI and NODDI indices of white matter microstructure did not differ between groups previously in this sample (18,32,35), and other pediatric samples at similar time points (52). Another study compared a subset of this sample (children recruited at the Calgary site) to typically developing children and also did not find global or regional (nodal) network differences between mTBI and mild OI groups post-acutely, but did find an effect of injury more generally relative to typical development (18).…”

Section: Discussionsupporting

confidence: 54%

“…All participants provided written informed assent and parents/guardians provided written informed consent (22). This study examined data from the MRI scans collected during the post-acute visit, as previously described (32,35).…”

Section: Study Design and Proceduresmentioning

confidence: 99%

“…Visual quality checks of all raw images were conducted to identify and exclude scans with structural abnormalities/incidental findings, scanner artifacts (e.g., warping), incomplete acquisition, or not collected using the standardized scan parameters (32). Data that passed the initial quality assessment were subsequently rated for motion by two trained analysts.…”

Section: Quality Assurancementioning

confidence: 99%

“…Unlike tractography, which yields a final value for each white matter tract, connectome analyses use weighted adjacency matrices to calculate network parameters. In tractography or region-of-interest analyses, multisite harmonization is performed on final metrics [e.g., average fractional anisotropy measures; (26,(30)(31)(32)]. However, graph theory analysis takes place after connections in a network have been mapped, mathematically represented as an adjacency matrix, and summarized by the computation of network parameters (33).…”

Section: Introductionmentioning

confidence: 99%

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Multisite Harmonization of Structural DTI Networks in Children: An A-CAP Study

et al. 2022

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The analysis of large, multisite neuroimaging datasets provides a promising means for robust characterization of brain networks that can reduce false positives and improve reproducibility. However, the use of different MRI scanners introduces variability to the data. Managing those sources of variability is increasingly important for the generation of accurate group-level inferences. ComBat is one of the most promising tools for multisite (multiscanner) harmonization of structural neuroimaging data, but no study has examined its application to graph theory metrics derived from the structural brain connectome. The present work evaluates the use of ComBat for multisite harmonization in the context of structural network analysis of diffusion-weighted scans from the Advancing Concussion Assessment in Pediatrics (A-CAP) study. Scans were acquired on six different scanners from 484 children aged 8.00–16.99 years [Mean = 12.37 ± 2.34 years; 289 (59.7%) Male] ~10 days following mild traumatic brain injury (n = 313) or orthopedic injury (n = 171). Whole brain deterministic diffusion tensor tractography was conducted and used to construct a 90 x 90 weighted (average fractional anisotropy) adjacency matrix for each scan. ComBat harmonization was applied separately at one of two different stages during data processing, either on the (i) weighted adjacency matrices (matrix harmonization) or (ii) global network metrics derived using unharmonized weighted adjacency matrices (parameter harmonization). Global network metrics based on unharmonized adjacency matrices and each harmonization approach were derived. Robust scanner effects were found for unharmonized metrics. Some scanner effects remained significant for matrix harmonized metrics, but effect sizes were less robust. Parameter harmonized metrics did not differ by scanner. Intraclass correlations (ICC) indicated good to excellent within-scanner consistency between metrics calculated before and after both harmonization approaches. Age correlated with unharmonized network metrics, but was more strongly correlated with network metrics based on both harmonization approaches. Parameter harmonization successfully controlled for scanner variability while preserving network topology and connectivity weights, indicating that harmonization of global network parameters based on unharmonized adjacency matrices may provide optimal results. The current work supports the use of ComBat for removing multiscanner effects on global network topology.

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Section: Discussionsupporting

confidence: 54%

Section: Study Design and Proceduresmentioning

confidence: 99%

Section: Quality Assurancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multisite Harmonization of Structural DTI Networks in Children: An A-CAP Study

et al. 2022

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“…Finally, although the current study exclusively focused on GM changes postinjury, several recent studies have also observed white matter pathology post-pmTBI in large samples that also persist multiple months postinjury. 45,47 Thus, future studies that examine pathology from a multimodal perspective are needed, as well as the potential relationship between injury biomarkers and clinical outcomes.…”

Section: Discussionmentioning

confidence: 99%

Prospective Study of Gray Matter Atrophy Following Pediatric Mild Traumatic Brain Injury

et al. 2023

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Background and Objectives:The clinical and physiological time-course for recovery following pediatric mild traumatic brain injury (pmTBI) remains actively debated. The primary objective of the current study was to prospectively examine structural brain changes (cortical thickness and subcortical volumes) and age-at-injury effects.A prioristudy hypotheses predicted reduced cortical thickness and hippocampal volumes up to 4 months post-injury, which would be inversely associated with age-at-injury.Methods:Prospective cohort study design with consecutive recruitment. Study inclusion adapted from American Congress of Rehabilitation Medicine (upper threshold) and Zurich Concussion in Sport Group (minimal threshold) and diagnosed by Emergency Department and Urgent Care clinicians. Major neurological, psychiatric or developmental disorders were exclusionary. Clinical (Common Data Element) and structural (3 Tesla MRI) evaluations within 11 days (sub-acute visit [SA]) and at 4 months (early chronic visit [EC]) post-injury. Age and sex-matched healthy children (HC) to control for repeat testing/neurodevelopment. Clinical outcomes based on self-report and cognitive testing. Structural images quantified with FreeSurfer (version 7.1.1).Results:208 pmTBI (age=14.4±2.9; 40.4% female) and 176 HC (age=14.2±2.9; 42.0% female) included in final analyses (>80% retention). Reduced cortical thickness (right rostral middle frontal gyrus;d=−0.49) and hippocampal volumes (d=−0.24) observed for pmTBI, but not associated with age-at-injury. Hippocampal volume recovery was mediated by loss of consciousness/post-traumatic amnesia. Significantly greater post-concussive symptoms and cognitive deficits were observed at SA and EC visits, but were not associated with the structural abnormalities. Structural abnormalities slightly improved balanced classification accuracy above and beyond clinical gold standards (∆+3.9%), with a greater increase in specificity (∆+7.5%) relative to sensitivity (∆+0.3%).Discussion:Current findings indicate structural brain abnormalities may persist up to four months post-pmTBI, and are partially mediated by initial markers of injury severity. These results contribute to a growing body of evidence suggesting prolonged physiological recovery post-pmTBI. In contrast, there was no evidence for age-of-injury effects or for physiological correlates of persistent symptoms in our sample.

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Longitudinal white matter microstructural changes in pediatric mild traumatic brain injury: AnA‐CAPstudy

Ware

Yeates

Tang³

et al. 2022

Human Brain Mapping

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In the largest sample studied to date, white matter microstructural trajectories and their relation to persistent symptoms were examined after pediatric mild traumatic brain injury (mTBI). This prospective, longitudinal cohort study recruited children aged 8-16.99 years with mTBI or mild orthopedic injury (OI) from five pediatric emergency [Correction added on 04 May 2022, after first online publication: Quynh Doan's affiliation is updated and subsequent affiliations were re-numbered.]

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Longitudinal white matter microstructural changes in pediatric mild traumatic brain injury: AnA‐CAPstudy

Cited by 23 publications

References 50 publications

Multisite Harmonization of Structural DTI Networks in Children: An A-CAP Study

Multisite Harmonization of Structural DTI Networks in Children: An A-CAP Study

Prospective Study of Gray Matter Atrophy Following Pediatric Mild Traumatic Brain Injury

Longitudinal white matter microstructural changes in pediatric mild traumatic brain injury: AnA‐CAPstudy

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