Post-Traumatic Stress Symptoms after Pediatric Injury: Relation to Pre-Frontal Limbic Circuitry

Bayesian varying-effects vector autoregressive models for inference of brain connectivity networks and covariate effects in pediatric traumatic brain injury

In this article, we develop an analytical approach for estimating brain connectivity networks that accounts for subject heterogeneity. More specifically, we consider a novel extension of a multi-subject Bayesian vector autoregressive model that estimates group-specific directed brain connectivity networks and accounts for the effects of covariates on the network edges. We adopt a flexible approach, allowing for (possibly) nonlinear effects of the covariates on edge strength via a novel Bayesian nonparametric prior that employs a weighted mixture of Gaussian processes. For posterior inference, we achieve computational scalability by implementing a variational Bayes scheme. Our approach enables simultaneous estimation of group-specific networks and selection of relevant covariate effects. We show improved performance over competing two-stage approaches on simulated data. We apply our method on resting-state functional magnetic resonance imaging data from children with a history of traumatic brain injury (TBI) and healthy controls to estimate the effects of age and sex on the group-level connectivities. Our results highlight differences in the distribution of parent nodes. They also suggest alteration in the relation of age, with peak edge strength in children with TBI, and differences in effective connectivity strength between males and females.

Concussion risk and symptomology severity in adolescents are associated with pre-season drowsiness and emotional complaints

Background

Concussions are an ever present risk for many sports. Underlying emotional disturbances and drowsiness are associated with worse post-concussion symptom scores. Yet, not study has examined associations of both emotional disturbances and drowsiness on concussion severity and symptomology.

Objectives

Examine the associations between baseline sleepiness, emotional complaints, and concussion risk and symptom severity in adolescent athletes.

Methods

A cohort of 626 adolescent athletes underwent baseline/pre-season concussion screening. Those who experienced a physician diagnosed concussion underwent follow up concussion symptomology assessment. Over 90% of players were seen within two weeks of the concussion incident. Linear regression examined for associations between concussion symptom scores and baseline drowsiness and baseline emotional symptoms. Logistic regression examined for association between each symptom and baseline drowsiness and baseline emotional symptoms.

Results

Of the 626 athletes that underwent baseline testing, 292 experienced a concussion. Of those 292 athletes, 174 (59.6%) reported baseline drowsiness and 183 (62.7%) baseline emotional symptoms. Baseline drowsiness and emotional complaints were associated with a 2.6 (95% confidence interval = 1.9 to 3.6) and 2.8 (95% confidence interval = 2.0 to 3.9) times greater odds of sustaining a concussion respectively. Increased symptomology after concussion was associated with both baseline drowsiness (unstandardised b = 4.6, p < 0.01) and baseline emotional complaints (unstandardised b = 6.0, p < 0.01).

Conclusion

Preseason drowsiness and emotional complaints in adolescent athletes are associated with higher risk of adverse clinical outcomes following concussion. Therefore, clinicians and coaches should be aware, and properly screen, for sleep and emotional problems as part of pre-season/baseline health screening.

Unraveling the relations between post-traumatic stress symptoms, neurocognitive functioning, and limbic white matter in pediatric brain tumor patients

Background

Pediatric brain tumor patients are at risk of developing neurocognitive impairments and associated white matter alterations. In other populations, post-traumatic stress symptoms (PTSS) impact cognition and white matter. This study aims to investigate the effect of PTSS on neurocognitive functioning and limbic white matter in pediatric brain tumor patients.

Methods

Sixty-six patients (6-16 years) completed neuropsychological assessment and brain MRI (1-year post-diagnosis) and parents completed PTSS proxy questionnaires (CRIES-13; 1-3 months and 1-year post-diagnosis). Mean Z-scores and percentage impaired (>1SD) for attention, processing speed, executive functioning, and memory were compared to normscores (t-tests, chi-square tests). Multi-shell diffusion MRI data were analyzed for white matter tractography (fractional anisotropy/axial diffusivity). Effects of PTSS on neurocognition and white matter were explored with linear regression models (FDR correction for multiple testing), including age at diagnosis, treatment intensity, and tumor location as covariates. Neurocognition and limbic white matter associations were explored with correlations.

Results

Attention (M = -0.49, 33% impaired; P < .05) and processing speed (M = -0.57, 34% impaired; P < .05) were significantly lower than healthy peers. PTSS was associated with poorer processing speed (β = -0.64, P < .01). Treatment intensity, age at diagnosis, and tumor location, but not PTSS, were associated with limbic white matter metrics. Neurocognition and white matter metrics were not associated.

Conclusions

Higher PTSS was associated with poorer processing speed, highlighting the need for monitoring, and timely referrals to optimize psychological well-being and neurocognitive functioning. Future research should focus on longitudinal follow-up and explore the impact of PTSS interventions on neurocognitive performance.

Multimodal Analysis of Secondary Cerebellar Alterations After Pediatric Traumatic Brain Injury

Importance

Traumatic brain injury (TBI) is known to cause widespread neural disruption in the cerebrum. However, less is known about the association of TBI with cerebellar structure and how such changes may alter executive functioning.

Objective

To investigate alterations in subregional cerebellum volume and cerebral white matter microstructure after pediatric TBI and examine subsequent changes in executive function.

Design, Setting, and Participants

This retrospective cohort study combined 12 data sets (collected between 2006 and 2020) from 9 sites in the Enhancing Neuroimaging Genetics Through Meta-Analysis Consortium Pediatric TBI working group in a mega-analysis of cerebellar structure. Participants with TBI or healthy controls (some with orthopedic injury) were recruited from trauma centers, clinics, and institutional trauma registries, some of which were followed longitudinally over a period of 0.7 to 1.9 years. Healthy controls were recruited from the surrounding community. Data analysis occurred from October to December 2022.

Exposure

Accidental mild complicated-severe TBI (msTBI) for those in the TBI group. Some controls received a diagnosis of orthopedic injury.

Main Outcomes and Measures

Volume of 18 cerebellar lobules and vermal regions were estimated from 3-dimensional T1-weighted magnetic resonance imaging (MRI) scans. White matter organization in 28 regions of interest was assessed with diffusion tensor MRI. Executive function was measured by parent-reported scores from the Behavior Rating Inventory of Executive Functioning.

Results

A total of 598 children and adolescents (mean [SD] age, 14.05 [3.06] years; range, 5.45-19.70 years; 386 male participants [64.5%]; 212 female participants [35.5%]) were included in the study, with 314 participants in the msTBI group, and 284 participants in the non-TBI group (133 healthy individuals and 151 orthopedically injured individuals). Significantly smaller total cerebellum volume (d = -0.37; 95% CI, -0.52 to -0.22; P < .001) and subregional cerebellum volumes (eg, corpus medullare; d = -0.43; 95% CI, -0.58 to -0.28; P < .001) were observed in the msTBI group. These alterations were primarily seen in participants in the chronic phase (ie, >6 months postinjury) of injury (total cerebellar volume, d = -0.55; 95% CI, -0.75 to -0.35; P < .001). Smaller cerebellum volumes were associated with higher scores on the Behavior Rating Inventory of Executive Functioning Global Executive Composite score (β = -208.9 mm3; 95% CI, -319.0 to -98.0 mm3; P = .008) and Metacognition Index score (β = -202.5 mm3; 95% CI, -319.0 to -85.0 mm3; P = .02). In a subset of 185 participants with longitudinal data, younger msTBI participants exhibited cerebellum volume reductions (β = 0.0052 mm3; 95% CI, 0.0013 to 0.0090 mm3; P = .01), and older participants slower growth rates. Poorer white matter organization in the first months postinjury was associated with decreases in cerebellum volume over time (β=0.52 mm3; 95% CI, 0.19 to 0.84 mm3; P = .005).

Conclusions and Relevance

In this cohort study of pediatric msTBI, our results demonstrated robust cerebellar volume alterations associated with pediatric TBI, localized to the posterior lobe. Furthermore, longitudinal cerebellum changes were associated with baseline diffusion tensor MRI metrics, suggesting secondary cerebellar atrophy. These results provide further understanding of secondary injury mechanisms and may point to new opportunities for intervention.

A Review of Family Environment and Neurobehavioral Outcomes Following Pediatric Traumatic Brain Injury: Implications of Early Adverse Experiences, Family Stress, and Limbic Development

Pediatric traumatic brain injury (TBI) is a public health crisis, with neurobehavioral morbidity observed years after an injury associated with changes in related brain structures. A substantial literature base has established family environment as a significant predictor of neurobehavioral outcomes following pediatric TBI. The neural mechanisms linking family environment to neurobehavioral outcomes have, however, received less empiric study in this population. In contrast, limbic structural differences as well as challenges with emotional adjustment and behavioral regulation in non-TBI populations have been linked to a multitude of family environmental factors, including family stress, parenting style, and adverse childhood experiences. In this article, we systematically review the more comprehensive literature on family environment and neurobehavioral outcomes in pediatric TBI and leverage the work in both TBI and non-TBI populations to expand our understanding of the underlying neural mechanisms. Thus, we summarize the extant literature on the family environment's role in neurobehavioral sequelae in children with TBI and explore potential neural correlates by synthesizing the wealth of literature on family environment and limbic development, specifically related to the amygdala. This review underscores the critical role of environmental factors, especially those predating the injury, in modeling recovery outcomes post-TBI in childhood, and discusses clinical and research implications across pediatric populations. Given the public health crisis of pediatric TBI, along with the context of sparse available medical interventions, a broader understanding of factors contributing to outcomes is warranted to expand the range of intervention targets.

White Matter Disruption in Pediatric Traumatic Brain Injury: Results From ENIGMA Pediatric Moderate to Severe Traumatic Brain Injury

OBJECTIVE

Our study addressed aims (1) to test the hypothesis that moderate-severe traumatic brain injury (TBI) in pediatric patients is associated with widespread white matter (WM) disruption, (2) to test the hypothesis that age and sex affect WM organization after injury, and (3) to examine associations between WM organization and neurobehavioral outcomes.

METHODS

Data from 10 previously enrolled, existing cohorts recruited from local hospitals and clinics were shared with the Enhancing NeuroImaging Genetics Through Meta-Analysis (ENIGMA) Pediatric Moderate/Severe TBI (msTBI) working group. We conducted a coordinated analysis of diffusion MRI (dMRI) data using the ENIGMA dMRI processing pipeline.

RESULTS

Five hundred seven children and adolescents (244 with complicated msTBI and 263 controls) were included. Patients were clustered into 3 postinjury intervals: acute/subacute, <2 months; postacute, 2 to 6 months; and chronic, ≥6 months. Outcomes were dMRI metrics and postinjury behavioral problems as indexed by the Child Behavior Checklist. Our analyses revealed altered WM diffusion metrics across multiple tracts and all postinjury intervals (effect sizes range d = -0.5 to -1.3). Injury severity is a significant contributor to the extent of WM alterations but explained less variance in dMRI measures with increasing time after injury. We observed a sex-by-group interaction: female patients with TBI had significantly lower fractional anisotropy in the uncinate fasciculus than controls (β = 0.043), which coincided with more parent-reported behavioral problems (β = -0.0027).

CONCLUSIONS

WM disruption after msTBI is widespread, persistent, and influenced by demographic and clinical variables. Future work will test techniques for harmonizing neurocognitive data, enabling more advanced analyses to identify symptom clusters and clinically meaningful patient subtypes.

BVAR-Connect: A Variational Bayes Approach to Multi-Subject Vector Autoregressive Models for Inference on Brain Connectivity Networks

In this paper we propose BVAR-connect, a variational inference approach to a Bayesian multi-subject vector autoregressive (VAR) model for inference on effective brain connectivity based on resting-state functional MRI data. The modeling framework uses a Bayesian variable selection approach that flexibly integrates multi-modal data, in particular structural diffusion tensor imaging (DTI) data, into the prior construction. The variational inference approach we develop allows scalability of the methods and results in the ability to estimate subject- and group-level brain connectivity networks over whole-brain parcellations of the data. We provide a brief description of a user-friendly MATLAB GUI released for public use. We assess performance on simulated data, where we show that the proposed inference method can achieve comparable accuracy to the sampling-based Markov Chain Monte Carlo approach but at a much lower computational cost. We also address the case of subject groups with imbalanced sample sizes. Finally, we illustrate the methods on resting-state functional MRI and structural DTI data on children with a history of traumatic injury.

Post-acute white matter microstructure predicts post-acute and chronic post-concussive symptom severity following mild traumatic brain injury in children

INTRODUCTION

Mild traumatic brain injury (TBI) is a global public health concern that affects millions of children annually. Mild TBI tends to result in subtle and diffuse alterations in brain tissue, which challenges accurate clinical detection and prognostication. Diffusion tensor imaging (DTI) holds promise as a diagnostic and prognostic tool, but little research has examined DTI in post-acute mild TBI. The current study compared post-acute white matter microstructure in children with mild TBI versus those with mild orthopedic injury (OI), and examined whether post-acute DTI metrics can predict post-acute and chronic post-concussive symptoms (PCS).

MATERIALS AND METHODS

Children aged 8-16.99 years with mild TBI (n = 132) or OI (n = 69) were recruited at emergency department visits to two children's hospitals, during which parents rated children's pre-injury symptoms retrospectively. Children completed a post-acute (<2 weeks post-injury) assessment, which included a 3T MRI, and 3- and 6-month post-injury assessments. Parents and children rated PCS at each assessment. Mean diffusivity (MD) and fractional anisotropy (FA) were derived from diffusion-weighted MRI using Automatic Fiber Quantification software. Multiple multivariable linear and negative binomial regression models were used to test study aims, with False Discovery Rate (FDR) correction for multiple comparisons.

RESULTS

No significant group differences were found in any of the 20 white matter tracts after FDR correction. DTI metrics varied by age and sex, and site was a significant covariate. No interactions involving group, age, and sex were significant. DTI metrics in several tracts robustly predicted PCS ratings at 3- and 6-months post-injury, but only corpus callosum genu MD was significantly associated with post-acute PCS after FDR correction. Significant group by DTI metric interactions on chronic PCS ratings indicated that left cingulum hippocampus and thalamic radiation MD was positively associated with 3-month PCS in the OI group, but not in the mild TBI group.

CONCLUSIONS

Post-acute white matter microstructure did not differ for children with mild TBI versus OI after correcting for multiple comparisons, but was predictive of post-acute and chronic PCS in both injury groups. These findings support the potential prognostic utility of this advanced DTI technique.