Cerebral blood flow in children with persisting postconcussive symptoms and posttraumatic headache at 2 weeks postconcussion

Feiven Fan Murdoch Children’s Research Institute, Melbourne, Victoria;
Melbourne School of Psychological Sciences, University of Melbourne, Victoria;

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Richard Beare Murdoch Children’s Research Institute, Melbourne, Victoria;
National Centre for Healthy Ageing and Peninsula Clinical School, Monash University, Melbourne, Victoria, Australia;

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Michael Takagi Murdoch Children’s Research Institute, Melbourne, Victoria;
Melbourne School of Psychological Sciences, University of Melbourne, Victoria;

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Nicholas Anderson Murdoch Children’s Research Institute, Melbourne, Victoria;

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Silvia Bressan Murdoch Children’s Research Institute, Melbourne, Victoria;
Department of Women’s and Children’s Health, University of Padova, Italy;

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Cathriona J. Clarke Murdoch Children’s Research Institute, Melbourne, Victoria;

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Gavin A. Davis Murdoch Children’s Research Institute, Melbourne, Victoria;
Department of Neurosurgery, Austin and Cabrini Hospitals, Melbourne, Victoria;

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Kevin Dunne Murdoch Children’s Research Institute, Melbourne, Victoria;
Department of Pediatrics, University of Melbourne, Victoria;
Department of Rehabilitation Medicine, Royal Children’s Hospital, Melbourne, Victoria, Australia;

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Fabian Fabiano Murdoch Children’s Research Institute, Melbourne, Victoria;

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Stephen J. C. Hearps Murdoch Children’s Research Institute, Melbourne, Victoria;

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Vera Ignjatovic Murdoch Children’s Research Institute, Melbourne, Victoria;
Institute for Clinical and Translational Research, Johns Hopkins All Children’s, St. Petersburg, Florida;

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Georgia Parkin Murdoch Children’s Research Institute, Melbourne, Victoria;

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Vanessa C. Rausa Murdoch Children’s Research Institute, Melbourne, Victoria;

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Marc Seal Murdoch Children’s Research Institute, Melbourne, Victoria;
Department of Pediatrics, University of Melbourne, Victoria;

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Jesse S. Shapiro Murdoch Children’s Research Institute, Melbourne, Victoria;
School of Psychology, Deakin University, Geelong, Victoria;

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Franz E. Babl Murdoch Children’s Research Institute, Melbourne, Victoria;
Department of Pediatrics, University of Melbourne, Victoria;
Emergency Department, Royal Children’s Hospital, Melbourne, Victoria; and

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Vicki Anderson Murdoch Children’s Research Institute, Melbourne, Victoria;
Melbourne School of Psychological Sciences, University of Melbourne, Victoria;
Department of Pediatrics, University of Melbourne, Victoria;
Psychology Service, Royal Children’s Hospital, Melbourne, Victoria, Australia

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OBJECTIVE

Persisting postconcussive symptoms (pPCS), particularly headache, can significantly disrupt children’s recovery and functioning. However, the underlying pathophysiology of these symptoms remains unclear. The goal in this study was to determine whether pPCS are related to cerebral blood flow (CBF) at 2 weeks postconcussion. The authors also investigated whether variations in CBF can explain the increased risk of acute posttraumatic headache (PTH) in female children following concussion.

METHODS

As part of a prospective, longitudinal study, the authors recruited children 5–18 years old who were admitted to the emergency department of a tertiary pediatric hospital with a concussion sustained within 48 hours of admission. Participants underwent pseudocontinuous arterial spin labeling MRI at 2 weeks postconcussion to quantify global mean gray and white matter perfusion (in ml/100 g/min). Conventional frequentist analysis and Bayesian analysis were performed.

RESULTS

Comparison of recovered (n = 26) and symptomatic (n = 12) groups (mean age 13.15 years, SD 2.69 years; 28 male) found no differences in mean global gray and white matter perfusion at 2 weeks postconcussion (Bayes factors > 3). Although female sex was identified as a risk factor for PTH with migraine features (p = 0.003), there was no difference in CBF between female children with and without PTH.

CONCLUSIONS

Global CBF was not associated with pPCS and female PTH at 2 weeks after pediatric concussion. These findings provide evidence against the use of CBF measured by arterial spin labeling as an acute biomarker for pediatric concussion recovery.

ABBREVIATIONS

ASL = arterial spin labeling; BF = Bayes factor; CBF = cerebral blood flow; ED = emergency department; mTBI = mild traumatic brain injury; PCSI = Post-Concussion Symptom Inventory; pPCS = persisting postconcussive symptoms; PTH = posttraumatic headache; RCH = Royal Children’s Hospital.

OBJECTIVE

Persisting postconcussive symptoms (pPCS), particularly headache, can significantly disrupt children’s recovery and functioning. However, the underlying pathophysiology of these symptoms remains unclear. The goal in this study was to determine whether pPCS are related to cerebral blood flow (CBF) at 2 weeks postconcussion. The authors also investigated whether variations in CBF can explain the increased risk of acute posttraumatic headache (PTH) in female children following concussion.

METHODS

As part of a prospective, longitudinal study, the authors recruited children 5–18 years old who were admitted to the emergency department of a tertiary pediatric hospital with a concussion sustained within 48 hours of admission. Participants underwent pseudocontinuous arterial spin labeling MRI at 2 weeks postconcussion to quantify global mean gray and white matter perfusion (in ml/100 g/min). Conventional frequentist analysis and Bayesian analysis were performed.

RESULTS

Comparison of recovered (n = 26) and symptomatic (n = 12) groups (mean age 13.15 years, SD 2.69 years; 28 male) found no differences in mean global gray and white matter perfusion at 2 weeks postconcussion (Bayes factors > 3). Although female sex was identified as a risk factor for PTH with migraine features (p = 0.003), there was no difference in CBF between female children with and without PTH.

CONCLUSIONS

Global CBF was not associated with pPCS and female PTH at 2 weeks after pediatric concussion. These findings provide evidence against the use of CBF measured by arterial spin labeling as an acute biomarker for pediatric concussion recovery.

In Brief

Researchers used a novel imaging technique, arterial spin labeling, to quantitatively evaluate changes in cerebral blood flow (CBF) in persisting postconcussive symptoms, including headache, in children and adolescents following a concussion. Global CBF was not associated with persisting postconcussive symptoms, nor was female posttraumatic headache at 2 weeks postinjury. Findings provide evidence against the use of CBF measured by arterial spin labeling as an acute biomarker for pediatric concussion recovery.

Concussion is defined as a subset of mild traumatic brain injury (mTBI) induced by biomechanical forces resulting in a cascade of complex pathophysiological changes in brain function.1 This form of TBI accounts for 60% of children with mTBI admitted to pediatric emergency departments (EDs).2 Although the majority of children who sustain a concussion recover within 2 weeks of injury, approximately one-third experience persisting postconcussive symptoms (pPCS)3,4 beyond 1 month postinjury; these are characterized by a constellation of somatic, cognitive, emotional, fatigue, and behavioral symptoms.1

Based on current guidelines, a diagnosis of concussion requires an absence of structural injury if standard structural neuroimaging (e.g., CT and/or MRI) was conducted.1 However, there is an increasing focus on examining other indicators of brain disruption associated with pPCS, such as cerebral blood flow (CBF).5 Often used synonymously with perfusion, CBF directly parallels changes in cerebral metabolic demand and neuronal activity.6 It is highly sensitive to the impacts of head injury that results in abnormal states of inadequate and excess perfusion,7 which may modify oxygen and glucose consumption and waste removal in gray and white matter tissue.8 One commonly used method to assess CBF is arterial spin labeling (ASL),6,8 a noninvasive technique that uses radiofrequency pulses to magnetically label inflowing arterial blood water to quantify cerebral tissue perfusion,6 making it a particularly feasible tool for measuring CBF in the pediatric population.

There is substantial variability in CBF alterations as measured using ASL during the acute to postacute phase after pediatric concussion, ranging from no difference9,10 to increased1115 and reduced1618 global and regional CBF postinjury. However, there is emerging evidence to suggest that distinct patterns of altered CBF may be associated with clinical severity11,13,16 and pPCS subgroups.12,15 One key unresolved issue is the need for valid and objective biomarkers that clinicians can rely on to diagnose and predict recovery outcome or to determine the risk of delayed recovery.1 However, despite myriad studies investigating CBF in concussion recovery, findings remain inconclusive due to conflicting evidence. As further highlighted in a recent systematic review by Rausa et al.,5 variability in the timing of imaging relative to time of injury within and across studies is likely to contribute to the disparate findings. Thus, methodologically rigorous studies addressing the current limitations of existing research are critical to establish the clinical utility of ASL in pediatric concussion recovery.

Within the context of pPCS subgroups and CBF, an important yet underinvestigated area is the influence of CBF on posttraumatic headache (PTH), which represents the most common acute and persistent symptom following concussion.19 Although there is preliminary evidence to implicate altered mechanisms of cerebral metabolism and perfusion in PTH pathophysiology following concussion,2023 these studies are limited by small numbers and inconsistent adherence to clinical criteria for PTH definitions. Furthermore, female sex remains a consistently identified yet incompletely understood risk factor for PTH and migraine in children.4,2426 Crucially, female sex, migraine history, and acute headache have been identified as part of a clinical risk score for predicting later pPCS among a large cohort of children (n = 3063) who presented within 48 hours of a concussion.4 Thus, this raises the question whether a neurobiological factor exists to explain why female patients are at a higher risk for developing PTH following concussion. Therefore, one promising line of inquiry is to identify whether variations in CBF can explain the increased risk of acute PTH and migraine in female children and adolescents following concussion.

Objective biomarkers that enable early identification of children at risk of pPCS following concussion remain a critical unmet need. CBF may serve as an objective marker of concussion severity, assist to identify children at risk of pPCS requiring early intervention, and inform clinical decisions around safe return to school and sport.1,27 In the present study we aimed to investigate CBF correlates of 1) recovery and 2) PTH in female patients within a narrow time window of 2 weeks following concussion. We expected that there would be significant differences in global CBF between recovered and symptomatic groups, as determined by the presence of postconcussive symptoms at 2 weeks postinjury, and that PTH and migraine in female patients would be related to CBF differences.

Methods

Ethics Statement

This study was approved by the Royal Children’s Hospital (RCH) Human Research Ethics Committee.

Study Design

The present study represents a substudy of a larger single-site, prospective, longitudinal study conducted at a state-wide tertiary pediatric hospital.27 Participants were recruited between December 2015 and July 2017, assessed acutely, and followed up at 2 weeks postinjury. Sample size of the larger study was optimized for the analysis of neurocognitive data, as reported elsewhere.27 The final sample size for this substudy was determined by the number of participants who consented to neuroimaging at the 2-week postinjury time point.

Participants

Participants included children 5–18 years old who presented to the RCH ED within 48 hours of sustaining a concussive event. Concussion was defined according to the Berlin Consensus Statement on Concussion in Sport Group1 as a head injury induced by biomechanical forces resulting in ≥ 1 symptoms in the following categories: somatic, cognitive, emotional, physical, fatigue/sleep, and behavioral. Exclusion criteria were as follows: Glasgow Coma Scale score < 13 on admission; positive CT result; CSF leak; fever, multiple traumas; intubation; general anesthesia or neurosurgical intervention; intentional injury; complex neurological or psychiatric history (developmental or intellectual disability, psychosis, bipolar disorder, moderate or severe TBI, or neurological conditions); bleeding disorders (e.g., hemophilia); antidepressant and stimulant medication use; alcohol intoxication at ED admission; insufficient understanding of English for participation; current enrollment in study; and/or no clear evidence of trauma as the primary event. Parents or guardians of participating children provided written informed consent at the time of recruitment. Children ≥ 13 years of age provided written informed consent, and children < 13 years of age provided verbal assent to participate.

Participants who were symptomatic at 2 weeks postinjury (see below) were classified as having pPCS, whereas those with ≤ 1 symptoms were designated as recovered.

Demographics and Clinical Characteristics

A standardized clinical report form recorded information on the child’s age, sex, handedness, injury mechanisms, and prior concussions.

Postconcussive Symptoms

The Post-Concussion Symptom Inventory (PCSI) is a 20-item measure of pre- and postinjury function across 4 domains (somatic, cognitive, emotional, and fatigue) on a 7-point Likert scale (0 = not a problem, 3 = moderate problem, 6 = severe problem).28 The PCSI has demonstrated strong internal consistency (α = 0.8–0.9), moderate to strong test–retest reliability (intraclass correlation coefficient = 0.65–0.89), and high convergent validity (r = 0.8).29 We collected both child- and parent-reported symptoms. Given that child self-report PCSI forms are age specific, with different forms for 5- to 7-year-old, 8- to 12-year-old, and 13- to 18-year-old children, we have used parent-reported PCSI data, which is standard across our study’s age range.

Headache and Migraine

Based on the International Classification of Headache Disorders, Third Edition,30 PTH was defined as a new or worsened headache attributed to head injury. Participants with increased severity (≥ 1 point) on the headache item of the PCSI compared to preinjury were classified into the PTH group. PTH with migraine features was defined as a new or worsened headache of moderate to severe intensity (PCSI headache item severity between 3 and 6) in association with nausea (≥ 1 point) and/or both photophobia and phonophobia (≥ 1 point), compared to preinjury.

Cerebral Blood Flow

Imaging was performed on a 3-T Siemens Trio MRI scanner (Siemens Medical Solutions) with a 32-channel head coil at the RCH in Melbourne, Australia. All MRI acquisitions were performed without sedation. High-resolution anatomical T1-weighted measurements were obtained (TR = 2530 msec, TE1 = 1.77 msec, TE2 = 3.51 msec, TE3 = 5.32 msec, TE4 = 7.2 msec, voxel size = 0.9 mm3). Quantitative whole-brain CBF measurements were performed using pseudocontinuous ASL6 with the following parameters: TR = 3370 msec, TE = 18 msec, voxel size = 2.5 × 2.5 × 3.0 mm, label duration = 1500 msec, postlabeling delay = 1600 msec, 50 repeats, 2D multislice acquisition = 37.50 msec per slice with a multiband factor of 6. Proton density weighted calibration image (sequence TR = 8.30 seconds, mode = voxelwise) was used to generate relative mean gray and white matter perfusion in absolute units (ml/100 g/min). Visual inspections for severe motion artifacts were performed. One consideration is the potential impact of age- and sex-related variability in hematocrit levels on ASL-derived CBF.31 The present study accounts for this by adjusting for age and sex on CBF outcomes in analysis.

Supplementary Table 1 reports ASL methodology according to the Committee on Best Practice in Data Analysis and Sharing (COBIDAS) guidelines.32

Procedure

Children presenting to the RCH ED were screened via electronic medical records in real time by trained research assistants. Families of eligible children were approached to participate in the study in consultation with the treating physician. Upon receiving parent or guardian and child consent or assent, injury-related data were obtained, and parents and children completed the PCSI. At 2 weeks postinjury (range 9–24 days), parents and children completed follow-up PCSI and participants underwent ASL imaging. Children with ≥ 2 symptoms on the parent PCSI with increased severity (≥ 1 point) compared to retrospective preinjury symptoms on the PCSI report were classified into the symptomatic group.3 Children who did not meet these criteria or who returned to preinjury or lower PCSI scores were classified into the recovered group.3 The 2-week time point was selected based on recent findings from several large-scale prospective, longitudinal studies, which have demonstrated that symptom recovery is either complete or stabilizes at 2 weeks postconcussion in children, with very little further symptom reduction in ensuing weeks.3,4,19,33

Statistical Analysis

Demographics and injury characteristics of the study cohort were explored using descriptive statistics (Table 1). Data analysis conformed to the parameters for the kinetic model provided in the ASL consensus guidelines.6 The FSL Bayesian Inference for ASL (BASIL) suite, version 6.0.434 with default settings, was used to estimate mean gray and white matter perfusion in absolute units (ml/100 g tissue/min).34 Pairwise label − control image subtractions were performed and averaged to generate a mean difference perfusion-weighted image; this was subsequently registered to a high-resolution T1-weighted image.6 The quality of gray matter and white matter tissue segmentation maps was confirmed by manual inspection.

TABLE 1.

Demographics and injury characteristics for children with pPCS

Recovered GroupSymptomatic GroupTotal Samplet (df)/χ2p ValueCohen’s d/φ
No. (%)26 (68.4%)12 (31.6%)38
Age at recruitment in yrs (SD)12.79 (2.83)13.92 (2.27)13.15 (2.69)−1.21 (36)0.2330.42
Male sex, no. (%)22 (84.6%)6 (50.0%)28 (73.7%)5.07 (1)0.0240.37
Rt handedness, no. (%)23 (88.5%)12 (100.0%)35 (92.1%)1.50 (1)0.2200.20
No. of previous concussions (%)0.14 (36)0.8920.05
 016 (61.5%)8 (66.7%)24 (63.2%)
 12 (7.7%)2 (16.7%)4 (10.5%)
 25 (19.2%)0 (0%)5 (13.2%)
 ≥33 (11.5%)2 (16.7%)5 (13.2%)
No. of days btwn ED recruitment & imaging (SD)14.50 (3.67)15.50 (4.08)14.82 (3.78)−0.75 (36)0.4560.26
Hx of HA &/or migraine, no. (%)*4 (15.4%)1 (8.3%)5 (13.2%)
Cause of injury, no. (%)
 Fall18 (69.2%)6 (50.0%)24 (63.2%)
 Fall from bike/motorbike7 (26.9%)0 (0%)7 (18.4%)
 High-speed projectile8 (30.8%)0 (0%)8 (21.1%)
 High-impact object8 (30.8%)0 (0%)8 (21.1%)
 Collision w/ child or object13 (50.0%)6 (50.0%)19 (50.0%)
Preinjury Sx no. (SD)4.69 (5.67)5.58 (6.10)4.97 (5.74)−0.44 (36)0.663−0.15
Preinjury Sx severity (SD)9.27 (15.06)7.58 (10.00)8.74 (13.55)0.35 (36)0.7270.12
Postinjury Sx no. (SD)2.38 (3.29)10.00 (5.74)4.79 (5.47)−4.29 (36)0.001−1.78
Postinjury Sx severity (SD)4.23 (8.94)20.17 (18.65)9.26 (14.62)−2.82 (36)0.014−1.23

HA = headache; Hx = history; Sx = symptom.

Age, number of previous concussions, number of days between recruitment and imaging, and pre- and postinjury total symptom number and severity were analyzed with independent samples t-tests. Sex and handedness were analyzed with chi-square tests. Cause of injury was not analyzed in all cases due to participants belonging to multiple groups and missing data. Unless otherwise indicated, values are expressed as the number of patients (%) or as the mean (SD).

Data missing for 3 participants.

Frequentist statistical analyses were performed using IBM SPSS Statistics 27.0. Between-group comparisons were examined using independent samples t-tests for continuous variables and chi-square tests for categorical variables. Multiple linear regressions were conducted to investigate gray and white matter perfusion differences between the recovery groups (recovered and symptomatic), while controlling for age and sex. Between-group differences were calculated using Cohen’s f2 effect sizes, and 0.02, 0.15, and 0.35 were termed small, medium, and large, respectively.35 We used Fisher’s exact test to examine the association between sex and PTH. Independent samples t-tests were conducted to examine gray and white matter perfusion differences between PTH present and absent groups, and Cohen’s d effect sizes of 0.2, 0.5, and 0.8 were termed small, medium, and large, respectively.35 In the context of null frequentist findings, Bayesian analysis was performed to clarify the evidence for and against the null hypothesis of no effect—i.e., whether there truly is no effect or whether the study is underpowered to detect an effect. A benefit of Bayesian analysis is that evidence can be obtained for and against both the null and alternative statistical models. Unpaired two-group tests of mean differences were performed using the bayestestR (version 0.11.5) package for R (version 4.1.1).36,37 The strength of evidence categories of Bayes factors (BFs) was based on the classification scheme proposed by Jeffreys in 1998.38 The evidence for the effect of recovery group on CBF was represented by the BF for the alternative hypothesis (BF10). A BF10 > 3 was considered as evidence for the alternative hypothesis, and a BF10 < 1/3 was considered as evidence for the null hypothesis of no effect. BF10 values between 0.33 and 1.00 were considered inconclusive for either hypothesis.

Results

Forty-five participants underwent neuroimaging at the 2-week follow-up time point. Of those imaged, ASL sequencing was not performed for 5 participants. A further 2 participants were excluded from analysis due to poor image quality from orthodontic braces (n = 1) and MRI acquisition error (n = 1). The final sample of 38 participants (28 male and 10 female) was included in data analysis (n = 26 recovered, n = 12 symptomatic) ranging in age from 6 to 18 years (mean 13.15, SD 2.69 years) over a follow-up period of 9–24 days (mean 14.82, SD 3.78 days). Supplementary Methods reports participation at each study stage in detail.

There were no statistically significant differences between the recovered and symptomatic groups for age, number of days between recruitment and imaging, number of previous concussions, handedness, and preinjury total number and severity of symptoms (p > 0.05; Table 1). We did find a significantly greater proportion of females in the symptomatic group than in the recovered group. Furthermore, as expected, the total number and severity of symptoms postinjury were significantly greater in the symptomatic group than in the recovered group. Five participants (13%; 4 male, 1 female) had a history of headache and/or migraine prior to the concussion (n = 4 in the recovered group, n = 1 in the symptomatic group).

Preliminary analyses ensured that the assumptions of normality, linearity, and homoscedasticity were met. After controlling for age and sex, there were no statistically significant differences found between the recovery groups at 2 weeks postconcussion for either mean gray matter perfusion (t[3] = 0.99, p = 0.330, Cohen’s f2 = 0.019) or mean white matter perfusion (t[3] = –0.87, p = 0.392, Cohen’s f2 = 0.020) (Table 2). Bayesian analysis revealed strong evidence of no effect of recovery group on both gray matter perfusion (BF10 = 0.08) and white matter perfusion (BF10 = 0.08; Table 3). There was strong evidence for an effect of age on gray matter perfusion (BF10 = 25.55) and substantial evidence against an effect of age on white matter perfusion (BF10 = 0.32). Finally, there was strong evidence of no effect of sex on both gray matter perfusion (BF10 = 0.05) and white matter perfusion (BF10 = 0.05).

TABLE 2.

Participant groups and mean global gray and white matter perfusion

No.Gray Matter, Mean (SD)White Matter, Mean (SD)
Recovered group2671.38 (11.32)23.66 (3.66)
Symptomatic group1272.10 (12.33)22.29 (2.32)
Females w/ PTH667.65 (8.10)22.08 (1.92)
Females w/o PTH475.76 (8.84)24.31 (1.29)
Females w/ PTH/migraine features468.73 (10.10)22.57 (2.26)
Females w/o PTH/migraine features672.33 (8.76)23.24 (1.94)

Values are expressed in ml/100 g tissue/min.

TABLE 3.

Posterior distribution median, 95% CI, and BF of recovery group, age, sex, female headache, and migraine on gray and white matter perfusion

Gray Matter PerfusionWhite Matter Perfusion
β95% CIBF10β95% CIBF10
Recovery group3.55–4.04, 10.820.08–1.08–3.52, 1.340.08
Age–2.52–3.71, –1.2525.55*–0.39–0.78, 0.050.32
Sex–0.24–7.67, 7.650.050.39–2.23, 2.930.05
Female HA–7.76–20.28, 4.250.29–2.15–4.61, 0.430.63
Female migraine–3.60–16.44, 9.340.13–0.62–3.44, 2.440.12

β = standardized model coefficient (median of posterior distribution); 95% CI = confidence intervals for the model coefficient.

A BF10 > 3 represents evidence for the alternative hypothesis.

At 2 weeks postinjury, there was no significant association between female sex and PTH (Fisher’s exact test p = 0.127, two-sided). Furthermore, we detected no significant differences for females with and without PTH for either gray matter perfusion (t[8] = 1.50, p = 0.172, Cohen’s d = 0.97, 95% CI −0.41, 2.29) or white matter perfusion (t[8] = 2.02, p = 0.079, Cohen’s d = 1.30, 95% CI −0.14, 2.68). Bayesian analysis revealed evidence of no effect of female headache on gray matter perfusion (BF10 = 0.29), whereas evidence for an effect of female headache on white matter perfusion was inconclusive (BF10 = 0.63).

In terms of the migraine phenotype, there was a statistically significant association found between female sex and PTH with migraine features at 2 weeks postinjury (Fisher’s exact test p = 0.003, two-sided), but we detected no significant differences for females with and without PTH and migraine features for gray matter perfusion (t[8] = 0.60, p = 0.565, Cohen’s d = 0.39, 95% CI −0.90, 1.66) and white matter perfusion (t[8] = 0.50, p = 0.631, Cohen’s d = 0.32, 95% CI −0.96, 1.59). Bayesian analysis revealed substantial evidence against an effect of female migraine on both gray matter perfusion (BF10 = 0.13) and white matter perfusion (BF10 = 0.12).

Discussion

In the present study we investigated CBF correlates of recovery and female PTH within a narrow time window around a 2-week time point following pediatric concussion. Bayesian analysis revealed evidence of no difference in mean gray and white matter perfusion between recovered and symptomatic children at 2 weeks postconcussion. Although female sex was identified as a risk factor for PTH with migraine features (i.e., nausea and/or sensitivity to light and sound), there was no difference in CBF between female children with and without acute PTH at 2 weeks postconcussion.

Contrary to our hypothesis, children with postconcussive symptoms at 2 weeks postinjury showed no differences in global CBF compared to recovered children. The absence of CBF differences at the 2-week time point is consistent with experimental concussion models that show peak CBF perturbations occurring within the first few hours of injury and largely stabilizing, with return to baseline at 7–10 days.39 Our results extend previous findings by Churchill et al.9,12 and Militana et al.10 to suggest that, in addition to no difference in global CBF between concussed children and healthy controls within the 1st week of injury, the global CBF of concussed children who continue to report pPCS was no different from those who had recovered from concussion at 2 weeks postinjury.

Our findings are in contrast with previous studies reporting both reduced1618 and increased1115 CBF in pediatric patients within the acute to postacute period following concussion. Although methodological heterogeneity may in part explain discrepancies in the data, it raises the possibility that concussion may impact key cerebrovascular regulatory mechanisms that maintain perfusion in response to changes in arterial carbon dioxide (i.e., vasoreactivity) and arterial blood pressure (i.e., autoregulation), and not necessarily global or regional CBF at rest.7,20,23,40,41 For example, a recent paper reported reduced vasoreactivity in concussed adolescents compared with healthy controls at 3–4 months postinjury, despite no difference in resting CBF.40 Concussive injury may alter the vasodilatory capacity of blood vessels, thereby impairing the supply of CBF to meet the metabolic demands of cerebral tissue.23,40 In terms of pPCS, reduced vasoreactivity and autoregulation have been shown to be strongly associated with greater somatic symptoms (i.e., headache, sensitivity to light/sound) in concussed adolescents within 2 weeks postinjury.23 This is further consistent with a prior report that almost 60% of the variability in PTH severity at 5 months postinjury can be explained by changes in cerebral vasoreactivity in a cohort of adolescents with concussion.20 Thus, the present study cannot rule out the potential impacts of concussion-induced changes in cerebrovascular regulatory mechanisms in pediatric patients with pPCS, despite the present finding of no difference in resting global CBF between recovered and symptomatic children at 2 weeks postinjury.

Our study further adds to the growing body of literature implicating female sex as a risk factor for the migraine phenotype of PTH.25,42 Importantly, this study provides the first evidence of no difference in CBF between female children with and without PTH and migraine at 2 weeks postconcussion. Further exploration of novel markers of PTH in females is required, as female sex remains a consistently identified yet incompletely understood risk factor for pPCS in children.4,2426 Delineating sex-related differences in brain pathophysiology associated with recovery trajectory, symptomatology, and subsequent clinical translation to inform targeted diagnostic and therapeutic directives remains a critical unmet need.

Taken together, our findings provide no support for the role of CBF measured by ASL as an acute biomarker for pediatric concussion recovery at 2 weeks postinjury. Given that children who are symptomatic at 2 weeks postinjury show a marginal reduction in pPCS and are still likely to be symptomatic at 4 weeks,33 the present findings further question the prognostic utility of CBF to predict clinical recovery outcomes postconcussion. The present findings add to our previous research demonstrating no difference between recovered and symptomatic children at 2 weeks postinjury in terms of other advanced neuroimaging modalities including diffusion metrics,43 susceptibility weighted imaging, and resting-state functional MRI.44 It may be that other neurometabolic correlates (i.e., serum markers of axonal injury or inflammation) or evaluation of cerebrovascular function (i.e., vasoreactivity and autoregulation) will better explain pPCS at the 2-week time point.

There are several methodological strengths for the present study. Neuroimaging took place within a narrow time window of 9–24 days, averaging 2 weeks from injury to imaging. Additionally, the present study used a robust cohort design with standardized protocols, strict concussion definition, and exclusion of complicated mTBI.1 Furthermore, few participants had preexisting headache and/or migraine history, and there was no bias in terms of preinjury symptom level or severity between the recovery groups prior to concussion. Finally, well-validated measures of pediatric postconcussive symptoms28,29 and recovery classification at 2 weeks postinjury3 were used.

The main limitation of the present study is the relatively small sample size. However, given that Bayesian analysis yielded overall conclusive findings, this indicates that statistical power was not a likely explanation for null findings. Although the recovered and symptomatic groups differed in terms of the proportion of female participants, this finding is consistent with previous literature reporting higher rates of delayed recovery among female patients,4,24 suggesting that the present sample is representative of the demographic characteristics of pediatric concussion. In the absence of a non–head injury trauma comparison group (e.g., orthopedic injury), it is difficult to delineate CBF changes specific to a concussive injury. Although the definitions of PTH and migraine phenotype were based on clinical criteria outlined in International Classification of Headache Disorders, Third Edition,30 further validation of PTH by using PCSI data is required.25 CBF was only measured at a single time point postinjury; therefore our study cannot account for the longitudinal process of CBF recovery. To robustly investigate the diagnostic and prognostic utility of CBF, future studies may consider conducting imaging within 48 hours of injury in the ED to predict acute and persistent PTH at 1–2 weeks and 3 months,30 respectively. Treatment exposure data including the effects of exercise, medication, and biofeedback on PTH were not collected but may be important covariates of interest in future studies. This is particularly important given that there are preliminary data to suggest that low-intensity exercise elevates CBF to produce headache symptoms, thereby further limiting exercise tolerance postconcussion.21 Therefore, in terms of prognostic significance, the return of normal regulation of CBF with low-intensity exercise may serve as a physiological marker of concussion recovery.

Conclusions

Our finding that global CBF was not associated with recovery and female PTH at 2 weeks after pediatric concussion suggest that the pathophysiology of pediatric pPCS is not likely to be related to acute CBF alterations. These findings provide evidence against the use of CBF measured by ASL as an acute biomarker for pediatric concussion recovery. We add new data to the limited research on markers of PTH in female patients to show no difference in CBF between female children and adolescents with and without acute PTH and migraine. Further research is required to delineate sex-related differences in brain pathophysiology associated with pPCS.

Acknowledgments

We thank all student researchers who assisted in data collection.

Disclosures

Dr. Davis is a member of the Scientific Committee of the 6th International Consensus Conference on Concussion in Sport; he is an honorary member of the Australian Football League Concussion Scientific Committee; he is section editor, Sport and Rehabilitation, Neurosurgery; and has attended meetings organized by sporting organizations including the National Football League, National Rugby League, International Ice Hockey Federation, and Fédération Internationale de Football Association. However, he has not received any payment, research funding, or other monies from these groups other than for travel costs.

Author Contributions

Conception and design: Fan, Beare, Takagi, Davis, Ignjatovic, Seal, Babl, V Anderson. Acquisition of data: Fan, N Anderson, Clarke, Dunne, Fabiano, Parkin, Rausa, Babl. Analysis and interpretation of data: Fan, Beare, Takagi, Hearps, Ignjatovic, Seal, V Anderson. Drafting the article: Fan, Hearps. Critically revising the article: all authors. Reviewed submitted version of manuscript: all authors. Approved the final version of the manuscript on behalf of all authors: Fan. Statistical analysis: Fan, Beare, Hearps. Administrative/technical/material support: Beare, N Anderson, Clarke, Parkin, Rausa, Seal, Shapiro. Study supervision: Beare, Takagi, Babl, V Anderson.

Supplemental Information

Online-Only Content

Supplemental material is available with the online version of the article.

References

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    • PubMed
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    Babl FE, Rausa VC, Borland ML, et al. Characteristics of concussion based on patient age and sex: a multicenter prospective observational study. J Neurosurg Pediatr. 2021;28(6):647656.

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    Hearps SJ, Takagi M, Babl FE, et al. Validation of a score to determine time to postconcussive recovery. Pediatrics. 2017;139(2):e20162003.

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    Zemek R, Barrowman N, Freedman SB, et al. Clinical risk score for persistent postconcussion symptoms among children with acute concussion in the ED. JAMA. 2016;315(10):10141025.

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    Churchill NW, Hutchison MG, Graham SJ, Schweizer TA. Symptom correlates of cerebral blood flow following acute concussion. Neuroimage Clin. 2017;16:234239.

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    Churchill NW, Hutchison MG, Graham SJ, Schweizer TA. Mapping brain recovery after concussion: from acute injury to 1 year after medical clearance. Neurology. 2019;93(21):e1980e1992.

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    Eisenberg MA, Meehan WP III, Mannix R. Duration and course of post-concussive symptoms. Pediatrics. 2014;133(6):9991006.

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    Albalawi T, Hamner JW, Lapointe M, Meehan WP, Tan CO. The relationship between cerebral vasoreactivity and post-concussive symptom severity. J Neurotrauma. 2017;34(19):27002705.

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    • Export Citation
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    Clausen M, Pendergast DR, Willer B, Leddy J. Cerebral blood flow during treadmill exercise is a marker of physiological postconcussion syndrome in female athletes. J Head Trauma Rehabil. 2016;31(3):215224.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22

    Purkayastha S, Sorond FA, Lyng S, et al. Impaired cerebral vasoreactivity despite symptom resolution in sports-related concussion. J Neurotrauma. 2019;36(16):23852390.

    • PubMed
    • Search Google Scholar
    • Export Citation
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    Aaron SE, Hamner JW, Ozturk ED, et al. Cerebrovascular neuroprotection after acute concussion in adolescents. Ann Neurol. 2021;90(1):4351.

  • 24

    Zemek RL, Farion KJ, Sampson M, McGahern C. Prognosticators of persistent symptoms following pediatric concussion: a systematic review. JAMA Pediatr. 2013;167(3):259265.

    • PubMed
    • Search Google Scholar
    • Export Citation
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    Kamins J, Richards R, Barney BJ, et al. Evaluation of posttraumatic headache phenotype and recovery time after youth concussion. JAMA Netw Open. 2021;4(3):e211312.

    • PubMed
    • Search Google Scholar
    • Export Citation
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    Iverson GL, Gardner AJ, Terry DP, et al. Predictors of clinical recovery from concussion: a systematic review. Br J Sports Med. 2017;51(12):941948.

  • 27

    Takagi M, Babl FE, Anderson N, et al. Protocol for a prospective, longitudinal, cohort study of recovery pathways, acute biomarkers and cost for children with persistent postconcussion symptoms: the Take CARe Biomarkers study. BMJ Open. 2019;9(2):e022098.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28

    Gioia GA, Schneider JC, Vaughan CG, Isquith PK. Which symptom assessments and approaches are uniquely appropriate for paediatric concussion? Br J Sports Med. 2009;43(suppl 1):i13-i22.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29

    Sady MD, Vaughan CG, Gioia GA. Psychometric characteristics of the postconcussion symptom inventory in children and adolescents. Arch Clin Neuropsychol. 2014;29(4):348363.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30

    Headache Classification Committee of the International Headache Society (IHS). The International Classification of Headache Disorders,. 3rd edition. Cephalalgia. 2018;38(1):1211.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31

    Pluncevic Gligoroska J, Gontarev S, Dejanova B, Todorovska L, Shukova Stojmanova D, Manchevska S. Red blood cell variables in children and adolescents regarding the age and sex. Iran J Public Health. 2019;48(4):704712.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32

    Nichols TE, Das S, Eickhoff SB, et al. Best practices in data analysis and sharing in neuroimaging using MRI. Nat Neurosci. 2017;20(3):299303.

  • 33

    Anderson V, Davis GA, Takagi M, et al. Trajectories and predictors of clinician-determined recovery after child concussion. J Neurotrauma. 2020;37(12):13921400.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34

    Chappell M, Groves A, Whitcher B, Woolrich M. Variational Bayesian inference for a nonlinear forward model. IEEE Trans Signal Process. 2009;57:223236.

  • 35

    Cohen J. Statistical Power Analysis for the Behavioral Sciences. L Erlbaum Associates; 1988.

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    Makowski D, Ben-Shachar MS, Chen SHA, Lüdecke D. Indices of effect existence and significance in the Bayesian framework. Front Psychol. 2019;10:2767.

  • 37

    Makowski D, Ben-Shachar MS, Lüdecke D. bayestestR: Describing effects and their uncertainty, existence and significance within the Bayesian framework. J Open Source Softw. 2019;4(40):1541.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38

    Jeffreys H. The Theory of Probability. Oxford University Press; 1998.

  • 39

    Yoshino A, Hovda DA, Kawamata T, Katayama Y, Becker DP. Dynamic changes in local cerebral glucose utilization following cerebral conclusion in rats: evidence of a hyper- and subsequent hypometabolic state. Brain Res. 1991;561(1):106119.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40

    Coverdale NS, Fernandez-Ruiz J, Champagne AA, Mark CI, Cook DJ. Co-localized impaired regional cerebrovascular reactivity in chronic concussion is associated with BOLD activation differences during a working memory task. Brain Imaging Behav. 2020;14(6):24382449.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 41

    Leddy J, Baker JG, Haider MN, Hinds A, Willer B. A physiological approach to prolonged recovery from sport-related concussion. J Athl Train. 2017;52(3):299308.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42

    Blume HK, Vavilala MS, Jaffe KM, et al. Headache after pediatric traumatic brain injury: a cohort study. Pediatrics. 2012;129(1):e31e39.

  • 43

    Shapiro JS, Silk T, Takagi M, et al. Examining microstructural white matter differences between children with typical and those with delayed recovery two weeks post-concussion. J Neurotrauma. 2020;37(11):13001305.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44

    Shapiro JS, Takagi M, Silk TJ, et al. No evidence of a difference in SWI lesion burden or functional network connectivity between children with typical and delayed recovery two weeks post-concussion. J Neurotrauma. 2021;38(17):23842390.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Collapse
  • Expand
Figure from Leclair et al. (pp 82–90).
  • 1

    McCrory P, Meeuwisse W, Dvořák J, et al. Consensus statement on concussion in sport—the 5th international conference on concussion in sport held in Berlin, October 2016. Br J Sports Med. 2017;51(11):838847.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2

    Babl FE, Rausa VC, Borland ML, et al. Characteristics of concussion based on patient age and sex: a multicenter prospective observational study. J Neurosurg Pediatr. 2021;28(6):647656.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3

    Hearps SJ, Takagi M, Babl FE, et al. Validation of a score to determine time to postconcussive recovery. Pediatrics. 2017;139(2):e20162003.

  • 4

    Zemek R, Barrowman N, Freedman SB, et al. Clinical risk score for persistent postconcussion symptoms among children with acute concussion in the ED. JAMA. 2016;315(10):10141025.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5

    Rausa VC, Shapiro J, Seal ML, et al. Neuroimaging in paediatric mild traumatic brain injury: a systematic review. Neurosci Biobehav Rev. 2020;118:643653.

  • 6

    Alsop DC, Detre JA, Golay X, et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: A consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med. 2015;73(1):102116.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7

    Len TK, Neary JP. Cerebrovascular pathophysiology following mild traumatic brain injury. Clin Physiol Funct Imaging. 2011;31(2):8593.

  • 8

    Chappell M, MacIntosh B, Okell T. Introduction to Perfusion Quantification Using Arterial Spin Labelling. 1st ed. Oxford University Press; 2018.

  • 9

    Churchill NW, Hutchison MG, Richards D, Leung G, Graham SJ, Schweizer TA. The first week after concussion: Blood flow, brain function and white matter microstructure. Neuroimage Clin. 2017;14:480489.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10

    Militana AR, Donahue MJ, Sills AK, et al. Alterations in default-mode network connectivity may be influenced by cerebrovascular changes within 1 week of sports related concussion in college varsity athletes: a pilot study. Brain Imaging Behav. 2016;10(2):559568.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    Barlow KM, Marcil LD, Dewey D, et al. Cerebral perfusion changes in post-concussion syndrome: a prospective controlled cohort study. J Neurotrauma. 2017;34(5):9961004.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12

    Churchill NW, Hutchison MG, Graham SJ, Schweizer TA. Symptom correlates of cerebral blood flow following acute concussion. Neuroimage Clin. 2017;16:234239.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13

    Churchill NW, Hutchison MG, Graham SJ, Schweizer TA. Mapping brain recovery after concussion: from acute injury to 1 year after medical clearance. Neurology. 2019;93(21):e1980e1992.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14

    Churchill NW, Hutchison MG, Graham SJ, Schweizer TA. Baseline vs. cross-sectional MRI of concussion: distinct brain patterns in white matter and cerebral blood flow. Sci Rep. 2020;10(1):1643.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15

    Stephens JA, Liu P, Lu H, Suskauer SJ. Cerebral blood flow after mild traumatic brain injury: associations between symptoms and post-injury perfusion. J Neurotrauma. 2018;35(2):241248.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16

    Meier TB, Bellgowan PS, Singh R, Kuplicki R, Polanski DW, Mayer AR. Recovery of cerebral blood flow following sports-related concussion. JAMA Neurol. 2015;72(5):530538.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17

    Wang Y, Nelson LD, LaRoche AA, et al. Cerebral blood flow alterations in acute sport-related concussion. J Neurotrauma. 2016;33(13):12271236.

  • 18

    Wang Y, Nencka AS, Meier TB, et al. Cerebral blood flow in acute concussion: preliminary ASL findings from the NCAA-DoD CARE consortium. Brain Imaging Behav. 2019;13(5):13751385.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Eisenberg MA, Meehan WP III, Mannix R. Duration and course of post-concussive symptoms. Pediatrics. 2014;133(6):9991006.

  • 20

    Albalawi T, Hamner JW, Lapointe M, Meehan WP, Tan CO. The relationship between cerebral vasoreactivity and post-concussive symptom severity. J Neurotrauma. 2017;34(19):27002705.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21

    Clausen M, Pendergast DR, Willer B, Leddy J. Cerebral blood flow during treadmill exercise is a marker of physiological postconcussion syndrome in female athletes. J Head Trauma Rehabil. 2016;31(3):215224.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22

    Purkayastha S, Sorond FA, Lyng S, et al. Impaired cerebral vasoreactivity despite symptom resolution in sports-related concussion. J Neurotrauma. 2019;36(16):23852390.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23

    Aaron SE, Hamner JW, Ozturk ED, et al. Cerebrovascular neuroprotection after acute concussion in adolescents. Ann Neurol. 2021;90(1):4351.

  • 24

    Zemek RL, Farion KJ, Sampson M, McGahern C. Prognosticators of persistent symptoms following pediatric concussion: a systematic review. JAMA Pediatr. 2013;167(3):259265.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25

    Kamins J, Richards R, Barney BJ, et al. Evaluation of posttraumatic headache phenotype and recovery time after youth concussion. JAMA Netw Open. 2021;4(3):e211312.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26

    Iverson GL, Gardner AJ, Terry DP, et al. Predictors of clinical recovery from concussion: a systematic review. Br J Sports Med. 2017;51(12):941948.

  • 27

    Takagi M, Babl FE, Anderson N, et al. Protocol for a prospective, longitudinal, cohort study of recovery pathways, acute biomarkers and cost for children with persistent postconcussion symptoms: the Take CARe Biomarkers study. BMJ Open. 2019;9(2):e022098.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28

    Gioia GA, Schneider JC, Vaughan CG, Isquith PK. Which symptom assessments and approaches are uniquely appropriate for paediatric concussion? Br J Sports Med. 2009;43(suppl 1):i13-i22.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29

    Sady MD, Vaughan CG, Gioia GA. Psychometric characteristics of the postconcussion symptom inventory in children and adolescents. Arch Clin Neuropsychol. 2014;29(4):348363.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30

    Headache Classification Committee of the International Headache Society (IHS). The International Classification of Headache Disorders,. 3rd edition. Cephalalgia. 2018;38(1):1211.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31

    Pluncevic Gligoroska J, Gontarev S, Dejanova B, Todorovska L, Shukova Stojmanova D, Manchevska S. Red blood cell variables in children and adolescents regarding the age and sex. Iran J Public Health. 2019;48(4):704712.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32

    Nichols TE, Das S, Eickhoff SB, et al. Best practices in data analysis and sharing in neuroimaging using MRI. Nat Neurosci. 2017;20(3):299303.

  • 33

    Anderson V, Davis GA, Takagi M, et al. Trajectories and predictors of clinician-determined recovery after child concussion. J Neurotrauma. 2020;37(12):13921400.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34

    Chappell M, Groves A, Whitcher B, Woolrich M. Variational Bayesian inference for a nonlinear forward model. IEEE Trans Signal Process. 2009;57:223236.

  • 35

    Cohen J. Statistical Power Analysis for the Behavioral Sciences. L Erlbaum Associates; 1988.

  • 36

    Makowski D, Ben-Shachar MS, Chen SHA, Lüdecke D. Indices of effect existence and significance in the Bayesian framework. Front Psychol. 2019;10:2767.

  • 37

    Makowski D, Ben-Shachar MS, Lüdecke D. bayestestR: Describing effects and their uncertainty, existence and significance within the Bayesian framework. J Open Source Softw. 2019;4(40):1541.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38

    Jeffreys H. The Theory of Probability. Oxford University Press; 1998.

  • 39

    Yoshino A, Hovda DA, Kawamata T, Katayama Y, Becker DP. Dynamic changes in local cerebral glucose utilization following cerebral conclusion in rats: evidence of a hyper- and subsequent hypometabolic state. Brain Res. 1991;561(1):106119.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40

    Coverdale NS, Fernandez-Ruiz J, Champagne AA, Mark CI, Cook DJ. Co-localized impaired regional cerebrovascular reactivity in chronic concussion is associated with BOLD activation differences during a working memory task. Brain Imaging Behav. 2020;14(6):24382449.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 41

    Leddy J, Baker JG, Haider MN, Hinds A, Willer B. A physiological approach to prolonged recovery from sport-related concussion. J Athl Train. 2017;52(3):299308.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42

    Blume HK, Vavilala MS, Jaffe KM, et al. Headache after pediatric traumatic brain injury: a cohort study. Pediatrics. 2012;129(1):e31e39.

  • 43

    Shapiro JS, Silk T, Takagi M, et al. Examining microstructural white matter differences between children with typical and those with delayed recovery two weeks post-concussion. J Neurotrauma. 2020;37(11):13001305.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44

    Shapiro JS, Takagi M, Silk TJ, et al. No evidence of a difference in SWI lesion burden or functional network connectivity between children with typical and delayed recovery two weeks post-concussion. J Neurotrauma. 2021;38(17):23842390.

    • PubMed
    • Search Google Scholar
    • Export Citation

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