aDepartment of Physical Therapy, The University of British Columbia, Vancouver, Canada; bSchool of Allied Health, College of Science, Health and Engineering, La Trobe University, Melbourne, Australia; cFlorey Institute of Neuroscience and Mental Health, National Health and Medical Research Council and University of Melbourne, Parkville, Australia; dCentre for Research Excellence in Stroke Rehabilitation and Brain Recovery, Melbourne, Australia; eBC Children’s Hospital Research Institute, Vancouver, Canada; and fMonash University, Clayton, Australia

Dr Schmidt completed the article screening and data extraction and led the review and manuscript preparation, the conception and design of the review, the analysis of the studies included in the review, and the interpretation of data; Dr Hayward substantially contributed to the article screening and data extraction, completed the analysis of the studies included in the review, and contributed to the conception and design of the review and interpretation of data; Dr Brown substantially contributed to the conception and design of the review, completed the analysis of the studies included in the review, and contributed to the interpretation of data; Drs Zwicker and Ponsford contributed to the conception and design of the review and interpretation of data; Dr van Donkelaar contributed to the conception and design of the review and interpretation of data and provided significant input regarding the mechanism of mild traumatic brain injury;

To cite: Schmidt J, Hayward KS, Brown KE, et al. Imaging in Pediatric Concussion: A Systematic Review. Pediatrics. 2018;141(5):e20173406

CONTEXT: Pediatric mild traumatic brain injury (mTBI) is a common and poorly understood injury. Neuroimaging indexes brain injury and outcome after pediatric mTBI, but remains largely unexplored.OBJECTIVE: To investigate the differences in neuroimaging findings in children/youth with mTBI. Measures of behavior, symptoms, time since injury, and age at injury were also considered.DATA SOURCES: A systematic review was conducted up to July 6, 2016.STUDY SELECTION: Studies were independently screened by 2 authors and included if they met predetermined eligibility criteria: (1) children/youth (5–18 years of age), (2) diagnosis of mTBI, and (3) use of neuroimaging.DATA EXTRACTION: Two authors independently appraised study quality and extracted demographic and outcome data.RESULTS: Twenty-two studies met the eligibility criteria, involving 448 participants with mTBI (mean age = 12.7 years ± 2.8). Time postinjury ranged from 1 day to 5 years. Seven different neuroimaging methods were investigated in included studies. The most frequently used method, diffusion tensor imaging (41%), had heterogeneous findings with respect to the specific regions and tracts that showed group differences. However, group differences were observed in many regions containing the corticospinal tract, portions of the corpus callosum, or frontal white-matter regions; fractional anisotropy was increased in 88% of the studies.LIMITATIONS: This review included a heterogeneous sample with regard to participant ages, time since injury, symptoms, and imaging methods which prevented statistical pooling/modelling.CONCLUSIONS: These data highlight essential priorities for future research (eg, common data elements) that are foundational to progress the understanding of pediatric concussion.

Imaging in Pediatric Concussion: A Systematic ReviewJulia Schmidt, OT, PhD, a, b Kathryn S. Hayward, PhD, a, c, d Katlyn E. Brown, PhD, a Jill G. Zwicker, PhD, a, e Jennie Ponsford, PhD, f Paul van Donkelaar, PhD, a Shelina Babul, PhD, a, e Lara A. Boyd, PhDa

abstract

PEDIATRICS Volume 141, number 5, May 2018:e20173406 REVIEW ARTICLE

Pediatric concussion (ie, mild traumatic brain injury [mTBI]) is a common but poorly understood injury.1 Symptoms of mTBI are widespread, encompassing physical, behavioral, emotional, and cognitive aspects.2, 3 Although in most children and/or youth, mTBI symptoms resolve within 1 month, 4 ∼20% experience persistent symptoms months after the initial injury.5, 6 These symptoms can disrupt a child’s everyday life, particularly activities involved in learning and social development.7 It is not known why some individuals experience persistent postconcussive symptoms and others do not.4

An assessment of pediatric mTBI includes self- or parent-reported questionnaires or behavioral assessments (eg, cognitive tests, neuropsychological tests, symptom reporting, and functional tests). Although useful in the immediate (ie, <3 days) and short-term (ie, 1 month) stages postinjury, 4 these measures are not sensitive to detect differences among individuals in the long-term (ie, >1 month) stages postinjury.8 Additionally, these measures do not provide an index of the underlying neuropathology.9, 10 It is possible that measures of brain structure or function could inform our understanding of persistent post-mTBI symptoms.

Investigating the neuropathological causes of pediatric mTBI is important for 2 reasons. Firstly, the inclusion of an assessment that can help explain the underlying pathology may be key to the stratification of individuals and identifying those who are more likely to experience persistent symptoms.11 Secondly, quantifying the neurobiological impact of brain injury on behavioral outcomes or the trajectory of recovery is an essential first step to designing effective interventions.12, 13 Thus, together, this information could help advance our understanding of the “right person, right intervention” approach

and progress toward personalized medicine after mTBI.

Brain biomarkers that reflect alterations in brain structure and function may help explain the recovery trajectory and neurobiology of an outcome after neurologic injury.12 There are a number of reviews in which researchers identify brain biomarkers in adult mTBI that collectively reveal alterations in white matter, 10, 14, 15 connectivity, 16 and neurophysiology.17, 18 To date, there has been no systematic review in which researchers investigate all the neuroimaging methods used to determine brain biomarkers in pediatric mTBI.

Imaging of pediatric mTBI reveals neurologic alterations. Changes include an increase in fractional anisotropy (FA) on diffusion imaging in various regions of the brain at a single time point after injury compared with matched controls19 – 22 and increased and decreased activation in various regions, such as the prefrontal cortex.23 – 25 Yet, it is unclear how these changes relate to behavior (eg, cognitive ability, neuropsychological function, symptom reporting, and motor function) or recovery. The identification of the brain biomarkers of pediatric mTBI will enable the quantification of the impact of an injury and trajectory of recovery.13, 26 This will directly inform future research and the impact of persistent post-mTBI symptoms, which may help refine return-to-activity decision-making and assist in the development of effective interventions.

Therefore, our main aim in this systematic review was to investigate neuroimaging studies using behavioral outcomes to identify potential brain biomarkers in children and/or youth with mTBI. We considered the following questions: What changes are evident on neuroimaging after mTBI by time point postinjury? Are differences

evident on neuroimaging related to behavior? And are neuroimaging findings related to age at the time of mTBI, type of mTBI, or recovery pattern from mTBI?

METHODS

A systematic review with a best-evidence synthesis was planned.27 – 29 Pooling data for a meta-analysis was intended (data permitting). If no data pooling was possible, the provision of means, SDs, and proportions was planned.

This review was registered on PROSPERO on July 6, 2016 (CRD42016041499). A literature search of English-language studies was conducted by using the following electronic databases up to July 6, 2016: Medline Ovid, Embase Ovid, the Cumulative Index to Nursing and Allied Health Literature EBSCO, and PsycINFO. The full search strategy for Medline Ovid and Embase Ovid is shown in Supplemental Table 6. The search strategy included keywords and expanded Medical Subjects Headings terms related to pediatrics, imaging methodology, and mTBI. The imaging methods targeted in our search strategy were MRI, functional MRI (fMRI), resting-state functional MRI (rsfMRI), diffusion tensor imaging (DTI), susceptibility-weighted imaging (SWI), EEG, transcranial magnetic stimulation, magnetoencephalography, magnetic resonance spectroscopy (MRS), and positron emission tomography. Definitions of key neuroimaging methods, the measures used, what they index, and how to interpret findings are outlined in Table 1.

Studies were included if they met the following predetermined eligibility criteria:

1. Population: Human children and youth aged 5 to 18 years diagnosed with mTBI at any stage postinjury as determined by the individual study criteria were

SCHMIDT et al2

PEDIATRICS Volume 141, number 5, May 2018 3

TABLE 1 Biomarker Description and Interpretation

Measure Description Interpretation

DTI FA Assesses the degree to which water molecules can diffuse

within a voxel (Alexander et al30)In general, high FA values may indicate dense axonal packing, large

axonal diameter, and/or high myelination; low FA values may reflect axonal degeneration and demyelination. Lower FA values reflect free water diffusion in all directions; higher FA values reflect diffusion along 1 axis. Specifically, in TBI, high FA values are hypothesized to indicate axonal cytotoxic edema because the water molecules have more constraints (Wilde et al22).

AD Measures the rate of diffusion in the principle diffusion direction or the longitudinal axis (Alexander et al30)

Decreases after axonal injury. These are reported to increase with brain maturation. High AD values may reflex large axonal diameter and/or high myelination; low AD values may reflect axonal degeneration (Shenton et al10).

RD Measures the rate of diffusion perpendicular to the principle diffusion direction (Alexander et al30)

May reflect changes in the axonal diameters or density. Lower RD may reflect large axonal diameter and/or high myelination or dense axonal packing; high RD values may reflect demyelination (Barzo et al31).

MD Characterizes the net degree of displacement of the water molecules; total diffusion within a voxel (Alexander et al30)

High MD values may reflect a higher degree of diffusion.Low MD values may be related to a decrease in overall extracellular

water diffusion because of an alteration in the ratio of intra- to extracellular water; it could also be the result of axonal stretching inducing a disturbance in gated ion channels, creating intracellular swelling and decreased extracellular water (Rosenblum32).

ADC Assesses how freely water molecules can diffuse; overall average measure of diffusion (Alexander et al30)

A reduction in ADC values may indicate trauma-induced inflammation and cytotoxic edema (Barzo et al31).

Anatomic MRI Volume of white and/

or gray matterAs a result of injury, damaged tissue degenerates, leaving

areas of reduced functional tissue volume with a focal increase in the amount of cerebrospinal fluid (Bigler and Maxwell33).

Severe TBI is associated with larger lesions, more generalized white- and/or gray-matter volume loss, increased cerebral spinal fluid, as well as greater whole-brain volume loss (Levine et al34).

fMRI Task-based fMRI Indirect measure of neuronal activity. This is used to

investigate how different regions of the brain are activated or deactivated in response to a specific task compared with baseline measures. Brain regions that show an elevated metabolic activity in contrast to a predefined baseline during the task are interpreted as being associated with the task (Dettwiler et al35).

Hyperactivation, particularly in the prefrontal and frontal-parietal regions, may reflect an engagement of additional cognitive and attention resources required to accomplish the task in a compromised neural system or may be due to brain reorganization after injury (Hillary36).

Hypoactivation is less understood but may be related to several processes, including difficulty in allocating appropriate cognitive and attention-related resources to the task or impaired neural functioning (Mayer et al37).

rsfMRI Intrinsic brain activity is characterized by synchronized spontaneous activity, with brain regions displaying a distinct coordinated pattern or networks, which represent the functional organization of the brain (Raichle et al38).

Alterations in brain dynamics and connectivity within functional networks is thought to be related to alterations in brain function (Zhou et al39).

SWI Covert lesions A high-resolution structural MRI technique that uses the

magnetic susceptibility differences between tissues, enabling the detection of small hemorrhages (ie, covert lesions; Haacke et al40)

In children with severe TBI, the No. and volume of covert lesions is correlated with global clinical outcomes (Fiser et al41) and cognitive ability (Tong et al42).

EEG Amplitude of P3b This is a subcomponent of the P300, an event-related

potential component that can be observed through brain electrical activity recordings. Improbable and/or unexpected events during a task will elicit a P3b (eg, the less probable the event, the greater the P3b; Agam and Sekuler43).

An indication of the cognitive demand of the task is shown through P3b values; a higher P3b indicates more demand on the cognitive workload (Moore et al44).

Proton MRI (MRS) Concentrations of

brain metabolite (namely, NAA)

Reductions in NAA concentrations are due to metabolic alterations in the brain after injury (Vagnozzi et al45).

In adults with mTBI, reductions in NAA concentrations are observed (Vagnozzi et al45).

AD, axial diffusivity; NAA, N-acetyl aspartate; RD, radial diffusivity.

included. Mixed age samples of group data were eligible provided that >50% of the sample was within the specified age range;

2. Intervention: The type of intervention did not influence eligibility. Studies that involved any nonpharmacological intervention (eg, rehabilitation, behavioral interventions, devices, and complementary and/or alternative medicine) or no intervention were included. If intervention studies were found, data were extracted from both pre- and postintervention time points. Only the preintervention time point data were used to pool with other single time point studies;

3. Comparator: Cohort studies with or without a comparison group were included. Studies in which researchers compared participants with mTBI to participants with more severe traumatic brain injury (TBI) (eg, moderate-to-severe TBI) were not included. Studies were excluded if an imaging method used (eg, computed tomography [CT]) was collected in the context of routine clinical diagnosis (eg, determining a skull fracture) because these provided primarily diagnostic information and did not quantify the nature of the neurologic injury or recovery from mTBI; and

4. Study type: All study types were included except for systematic reviews, literature reviews, and single-case studies.

From the initial search, all duplicate references were excluded by using the Endnote “find duplicates” filter and then by hand search of references (J.S.). Two authors (J.S. and K.S.H.) screened all reference titles and abstracts according to the predetermined eligibility criteria. Full texts of the remaining studies were independently screened by 2 authors (J.S. and K.S.H.). Disagreements

regarding the inclusion of a study were resolved by discussion and criteria review between J.S. and K.S.H. If not resolved, a third author (K.E.B.) was involved to achieve a consensus. If still not resolved, an additional 2 authors (L.A.B. and J.G.Z.) reviewed the study. If majority agreement was not reached, it was documented. Reference lists of all eligible studies were hand searched by J.S. to identify potential studies that were not identified through the initial search process, along with a citation-tracking database, using Web of Science.

Data extraction was undertaken by 1 author (J.S.) and was independently verified by a second author (K.E.B.) by using a predetermined extraction form. Information extracted included the following: (1) study details (ie, authors, date, and study location), (2) participants (ie, age, sex, and characteristics of the injury), (3) imaging method used (ie, measure of brain injury and/or recovery, method of measurement, timing of measurement, and frequency of measurement), (4) clinical measures of mTBI symptoms (ie, symptom reporting, measures of cognition, physical function and mental health, timing of measurement, and frequency of measurement), (5) intervention (ie, no intervention or nonpharmacological interventions, such as behavioral interventions or rehabilitation), (6) comparator (ie, no comparator or children with no neurologic or orthopedic injury), (7) results (ie, means, SDs, coefficients, P values, and effect size), and (8) miscellaneous data that were viewed to be of potential importance to the research questions. Reports were reviewed to ensure that data were only included once in the review.

Study quality and risk of bias were independently appraised by 2 authors (J.S. and K.S.H.). We used a modified version of the Case Control Study Checklist or the Cohort Study Checklist, using items

that are pertinent to quality rating, developed by the Critical Appraisal Skills Program46 and the risk of bias tool from the Cochrane Handbook.47 If disagreement occurred, resolution was sought through discussion and review of the study and appraisal checklist. If not resolved, a third reviewer (K.E.B.) was involved to achieve a consensus. If still not resolved, an additional 2 authors (S.B. and J.G.Z.) were asked to review the study and appraisal checklist. If consensus was not reached, it was documented. A best-evidence synthesis was planned by using the best set of studies determined by the quality rating score (at least 8 of 10) and risk of bias (a rating of 3 of 3) to draw conclusions.27

RESULTS

Flow of Studies Through the Review

Through the search, we identified 1421 studies, with 717 remaining after duplicate removal. In Fig 1, we outline the flow of studies. All inclusion criteria disagreements were resolved through discussion. Twenty-two studies met all eligibility criteria. In Table 2, we describe each study. Notably, there has been a progressive increase in imaging studies conducted over time (Fig 2).

Characteristics of Included Studies

Study Characteristics

Seven different imaging methods were identified, including DTI (41%), 19, 21, 22, 48, 53, 55, 57, 58 fMRI (27%), 23– 25, 56, 60, 61 SWI (27%), 22, 48, 55 EEG (14%), 44, 49, 59 anatomic MRI (14%), 51, 54, 55 rsfMRI (5%), 52 and MRS (5%)55 (Table 2). Time postinjury ranged from 1 day to 5 years. Researchers in all but 2 studies44, 54 reported behavioral data (378 participants; Table 2) using 75 different tests and/or subtests. Researchers in 10 studies did not

SCHMIDT et al4

analyze the relationship between brain imaging and behavior.* Researchers in 6 studies (n = 90) reported individual patient data from 5 different brain imaging methods21, 23, 52, 55, 57, 60; data were collected between 24 hours and 1 year postinjury. Most studies (n = 14 of 22 studies; 64%) were conducted within ∼1 month postinjury (Fig 3).

Participants and Injury Characteristics

In total, 931 participants (448 with mTBI: average of 13 years old at injury [range 9–16 years]) were included (Fig 4). The cause of injury

* Refs 23, 25, 44, 48, 50, 52, 54, 56, 58, 61.

was documented in 18 studies (220 participants)†: sport-related injury (70%), falls (18%), kicked and/or struck by object (6%), and motor vehicle crash (5%). Imaging methods were diverse when pooling participants with common causes of injury (Fig 5). Researchers in 5 studies (177 participants)22, 50, 51, 53, 54 reported Glasgow Coma Scale scores (average of 14.7 ± 0.4 out of 15, indicating minimal disruption in consciousness).62 Loss of consciousness (<30 minutes) was reported in 6 studies (131 participants).20, 24, 48, 50, 53, 55 Researchers in 7 studies used

† Refs 19– 25, 44, 48– 50, 52, 53, 55– 57, 59, 60.

standardized symptom scales (112 participants)19, 21 –25, 48 and in 2 studies (80 participants)50, 59 recorded the number of symptoms that participants experienced.

Quality and Risk of Bias

Quality scores ranged from 2 to 7 out of 8 (average of 5.1; SD of 1.5), revealing moderate quality. Risk of bias ranged from 0 to 3 out of 3 (average of 1.8; SD of 1.2), revealing a low risk of bias. Results regarding quality appraisal and risk of bias are provided in Table 3.

PEDIATRICS Volume 141, number 5, May 2018 5

FIGURE 1Flow of studies through database search to inclusion in the systematic review.

Question 1: What Differences Are Evident on Neuroimaging After mTBI by Time Postinjury?

Researchers in all the studies provided data on neuroimaging by comparing participants with mTBI to controls. Because of the heterogeneity in imaging type, time

postinjury, and age of participants, it was not possible to conduct a best-evidence synthesis. In Table 4, we describe each imaging method based on time postinjury. Most of these data reflect a single time point; only 3 studies included longitudinal data.20, 55, 58 As such, we were not able to include a statistical analysis

of differences on time postinjury. However, below is a description of the findings from each imaging method used in the included studies.

All studies in which researchers used DTI (n = 9) revealed differences in diffusion data between the mTBI and control groups. Researchers in all

SCHMIDT et al6

TABLE 2 Study Demographics

Aims Addresseda

No. Participants

in Study

No. Participants

With mTBI

Age at Testing, y

Time Postinjury at

Testing, d

Imaging Method

Neurocognitive Measure Concussion Measure

1 2 3

Babcock et al48 X X — 43 23 13 2 DTI, SWI FAD, CBCL PCSSBaillargeon et al49 X X — 96 33 13 174 EEG BPT, COWAT, BVMT-R, HVLT-R,

SDMT, PSU, Trail Making Test—

Beauchamp et al50 X X — 106 71 10 36 SWI ABAS, CBCL, WAIS, WISC-IV —Bigler et al51 X X — 53 32 11 932 MRI, SWI WAIS, WISC-IV —Borich et al19 X X — 22 12 16 36 DTI — SCAT-2Borich et al52 X X — 22 12 16 36 rsfMRI — SCAT-2Chu et al53 X X — 20 10 16 3 DTI BSI RPCSQKeightley et al23 X X — 30 15 14 39 fMRI Beck Youth Inventory, b CBCL,

CPRS, PASAT, Pegboard, Rey Inventoryb, SDMT, Stroop

Color-Word Test, Trail Making Test, WAIS

PCSS

Krivitzky et al24 X X — 26 13 13 29 fMRI ACT, BREIF, digit span, FSIQ, Pegboard, Rey Verbal Fluency, Symbol Digit Modalities Test, WJ-III

PCSS

Levin et al54 X — — 124 54 12 1944 MRI — —Maugans et al55 X X — 24 12 13 2 DTI, SWI,

MRI, MRS

ImPACT —

Mayer et al20 X X — 30 15 14 16 DTI BASC-2 —Moore et al44 X — — 32 16 9 756 EEG — —Saluja et al25 X X — 50 15 — 39 fMRI Beck Youth Inventoryb, CBCL,

PASAT, Pegboard, Rey Inventoryb, SDMT, Stroop

Color-Word Test, Trail Making Test, WAIS

PCSS

Sinopoli et al56 X X — 27 13 13 135 fMRI CPRS, Pegboard, Stroop Color-Word Test, Trail Making Test,

WAIS

—

van Beek et al57 X X — 36 18 11 17 DTI WISC-III —van Beek et al58

2015X X — 40 20 11 182 DTI WISC-III —

Virji-Babul et al21 X X — 22 12 16 36 DTI — SCAT-2Virji-Babul et al59 X X — 42 9 16 45 EEG ImPACT —Wilde et al22 X X — 20 10 16 5 DTI, SWI BSI RPCSQWestfall et al60 X X — 38 19 15 226 fMRI BREIF, WAIS —Yang et al61 X X — 28 14 14 16 fMRI, SWI BASC-2, EF, PS, WRAT —

ABAS, Adaptive Behavior Assessment System; ACT, Auditory Consonant Trigram; BASC-2, Behavior Assessment System for Children, Second Edition; BPT, Brown-Peterson Test; BREIF, Behavior Rating Inventory of Executive Function; BSI, Brief Symptom Inventory; BVMT-R, Brief Visuospatial Memory Test-Revised; CBCL, Child Behavioral Checklist; COWAT, Controlled Oral Word Association Test; CPRS, Conners Rating Scale for Parents; EF, Executive Function; FAD, Family Assessment Device; FSIQ, full-scale IQ; HVLT-R, Hopkins Verbal Learning Test-Revised; ImPACT, Immediate Post-Concussion Assessment and Cognitive Testing; PASAT, Paced Auditory Serial Addition Test; PCSS, Post-Concussion Symptom Scale; PS, Processing Speed; PSU, Pennsylvania State University Cancellation Task; RPCSQ, Rivermead Post-Concussion Symptoms Questionnaire; SCAT-2, Sports Concussion Assessment Tool 2; SDMT, Symbol Digit Modalities Test; WAIS, Wechsler Abbreviated Intelligence Scale; WISC-IV, Wechsler Intelligence Scale for Children, Fourth Edition; WJ-III, Woodcock Johnson-III; WRAT, Wide Range Achievement Test; —, not applicable.a Aim 1: What changes are evident on neuroimaging? Aim 2: Are neuroimaging changes related to behavior? Aim 3: Are neuroimaging findings related to age at mTBI, type of mTBI, or recovery patterns from mTBI?b For the Beck youth and Rey inventories, only some subtests were used.

but 1 study55 reported an increase in FA19 –22, 48, 53, 57, 58 (88% of the studies). Researchers in 2 studies investigated an apparent diffusion coefficient (ADC). Here, there was a decrease in values in the mTBI group compared with the controls.22, 53 Mean diffusivity (MD) was explored in 4 studies and generally decreased in the mTBI group compared with controls: 2 studies revealed significantly decreased values, 21, 48 1 study revealed a nonsignificant trend

of decreased values, 19 and 1 study revealed no significant differences.58 Studies (n = 7) in which researchers reported radial diffusivity values had mixed findings: 4 studies revealed decreased values, 22, 48, 53, 57 and 3 studies revealed no difference between groups.19, 55, 58 Studies (n = 6) in which researchers reported axial diffusivity values also yielded mixed results: 1 study revealed decreased values, 19 1 study revealed increased values, 48 and 4 studies revealed no

significant differences.53, 55, 57, 58 There was a large amount of heterogeneity among the included studies with respect to the specific regions and tracts that showed group differences; however, many contained the corticospinal tract, components of the corpus callosum (CC), or frontal white-matter regions.

Studies in which researchers used fMRI (n = 6) revealed mixed patterns of brain activity. Two reported decreased activation in areas that included the dorsolateral prefrontal cortex and premotor and/or supplementary motor areas during a verbal working memory task23 and in various regions (including the cerebellum, basal ganglia, and thalamus) during an auditory orienting task.61 Two studies revealed increased activation, specifically in the cerebellum during an inhibitory control component of a task24 and in various clusters during a working memory task.60 Two studies revealed both higher and lower activation, primarily in the dorsolateral prefrontal cortex during various conditions of a working memory task56 and a navigational memory task.25 Researchers in 1 study used rsfMRI at 1 month postinjury, revealing altered functional connectivity in 3 resting-state networks (eg, the default mode network, executive function network, and ventral attention network) in the mTBI compared with the control group.52

Other imaging methods included in this review were SWI, EEG, MRI, and MRS. Four of the 5 studies using SWI generally revealed no differences between those with mTBI compared with matched controls.22, 48, 55, 61 One study revealed a lower volume and number of covert lesions in participants with uncomplicated mTBI (eg, no abnormalities on clinical MRI and/or CT) compared with complicated mTBI (eg, imaging abnormalities on clinical MRI and/or CT).50 Two of the 3 EEG studies

PEDIATRICS Volume 141, number 5, May 2018 7

FIGURE 2Number of pediatric mTBI studies using imaging published over the past 22 years.

FIGURE 3Number of studies using various imaging methods across the time course of injury.

revealed lower P3b amplitude after mTBI compared with controls.44, 49, 59 Three studies in which researchers used anatomic MRI revealed no differences in participants with and without mTBI.51, 54, 55 Yet, 1 revealed that participants with mTBI had decreased volume in the CC white matter compared with controls.51 Researchers in 1 study employed proton MRS, finding no differences between the mTBI and control groups in concentrations of N-acetyl aspartate, N-acetyl aspartate creatine, and phosphocreatine.55

Question 2: Are Neuroimaging Findings Related to Behavior?

There were 20 studies that provided data on behavior, with or without noting a relationship to brain imaging data (Table 5). Most studies (n = 14 of 17; 82%) in which researchers used neurocognitive assessments did not reveal any differences between the mTBI and control groups.‡ Researchers in most studies (n = 7 of 9; 78%) that provided data on postconcussive symptoms used a standardized measure, with the majority of these (n = 6 of 9; 67%)

‡ Refs 20, 22, 24, 25, 48– 51, 53, 56, 58– 61.

reporting a significant difference between the mTBI and control groups.19, 23 –25, 48, 52

Researchers in 12 studies§ analyzed correlations between brain imaging and behavioral data. Results are described in Table 4, grouped by the type of imaging method. It was not possible to conduct a best-evidence synthesis because of the heterogeneity of the imaging type, time postinjury, participant ages, and measures of behavior. In summary, most DTI studies (n = 5 of 7; 71%) revealed significant correlations, with alterations in diffusivity relating to symptom reporting, 22, 53 emotional distress, 22, 53 arithmetic problem-solving, 57 and concussion outcome scores.19, 21 All EEG studies (n = 2) revealed significant correlations, with alterations in EEG data relating to symptom reporting.49, 59 One of 2 fMRI studies revealed a significant relationship between brain activation and neurocognitive assessments and symptom reporting.24 A minority of studies (n = 4 of 12; 33%) with brain-behavior analysis revealed no significant correlations or

§ Refs 19– 22, 24, 49, 51, 53, 55, 57, 59, 60.

associations, including studies in which researchers used DTI and neurocognitive assessment20 and concussion assessment scale, 55 fMRI and memory task, 60 and anatomic MRI volumetric measures and neurocognitive assessments.51

Question 3: Are Neuroimaging Findings Related to Age at the Time of the Injury, Type of Injury, or Recovery Pattern From Injury?

Age at the Time of mTBI

Because of the heterogeneity of the data, including imaging methods and behavioral measures, a statistical analysis accounting for age was not possible. Additionally, no individual study provided a statistical analysis on data for these metrics.

Cause of Injury

Because of the heterogeneity of studies, specifically the time postinjury, age at the time of the injury, and imaging method used, it was not possible to perform a meta-analysis of these data.

Recovery Time After mTBI

Because of the large variability in the time frame of the postinjury assessments and lack of data regarding recovery patterns, it was

SCHMIDT et al8

FIGURE 4Number of pediatric mTBI studies across different ages. The average age of the participants in each study is represented. No pediatric mTBI study has been conducted with an average age <9 years. Most studies have an average age of 13 to 16 years.

FIGURE 5Imaging techniques conducted on participants with sport-related mTBI.

not possible to statistically analyze these data.

DISCUSSION

This is the first systematic review in which researchers investigate all neuroimaging methods in pediatric mTBI. The identified studies represent a heterogeneous cohort pertaining to age, time postinjury, imaging method, and behavioral data. Despite this, the included studies provide pertinent information on emerging areas for future research and gaps in our current knowledge that warrant discussion.

Firstly, with respect to DTI findings, which indicate variability in the diffusion properties of water molecules, differences were revealed between the mTBI and control groups. Specifically, the mTBI group generally had increased FA values, a decreased ADC, and decreased MD values up to 6 months postinjury (see Table 1 for definition and explanation). It is thought that these alterations occur immediately postinjury (eg, within 2 days)63 because of cytotoxic edema compressing intracellular space between fibers, and thus restricting diffusion to a uniform direction.63 Surprisingly, findings revealed that FA values in participants with mTBI were elevated even at 6 months postinjury. These longer-term alterations may be due to prolonged subtle cytotoxic edema, which may be more prevalent in a developing brain and, therefore, only apparent in the pediatric population.22 These findings contrast with research in the adult population, in whom many studies reveal decreased FA in the mTBI group64 – 66; others show increased FA, 67, 68 and 1 reveals both increased and decreased FA at 2 different time points in the early phase of recovery (ie, <8 days) postinjury.69 In summary, findings from the DTI studies show altered diffusion properties.

PEDIATRICS Volume 141, number 5, May 2018 9

TABL

E 3

Qual

ity A

ppra

isal

and

Bia

s Ra

ting

Stud

y Au

thor

Addr

esse

d a

Clea

rly

Focu

sed

Issu

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Appr

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ate

Met

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to A

nsw

er

Ques

tion

Acce

ptab

le

Recr

uitm

ent

(Con

cuss

ion)

Acce

ptab

le

Recr

uitm

ent

(Con

trol

s)

Expo

sure

Ac

cura

tely

M

easu

red

to

Min

imiz

e Bi

asa

Acco

unte

d fo

r Po

tent

ial

Conf

ound

ing

Fact

ora

Prec

ise

Resu

lts

(Est

imat

e of

Ri

sk)a

Resu

lts

Gene

raliz

ed

to O

ther

Po

pula

tions

Tota

l Qua

lity

Scor

e (O

ut o

f 8)

Tota

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ore

(Out

of 3

)a

Babc

ock

et a

l481

11

11

10

06

2Ba

illar

geon

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l491

11

N/A

11

10

63

Beau

cham

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al50

11

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10

52

Bigl

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11

00

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41

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t al52

11

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et a

l531

10

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TABLE 4 Imaging Results

Reference Time Postinjury, d Results

DTI FA Babcock et al48 2 Participants with mTBI showed higher FA in areas such as the left-middle temporal gyrus, left superior temporal

gyrus, left- and right-anterior CR, and right superior longitudinal fasciculus. Chu et al53 3 Participants with mTBI were found to have increased FA in a whole-brain analysis. Wilde et al22 5 Participants with mTBI had increased FA in the entirety of the CC. Mayer et al20 16 Participants with mTBI had higher FA values in multiple white-matter structures with various analyses methods (eg,

tract-based spatial statistics, voxelwise analysis), including the anterior, superior, and posterior CR; bilateral CP; sections of the internal capsule; thalamic radiations; sections of the CC; and the superior longitudinal fasciculus.

van Beek et al57 17 Participants with mTBI showed higher FA values in the CC splenium, and no significant group differences were observed in the CC genu. Additionally, there were no group differences in metrics in long-association pathways

(eg, the superior and inferior longitudinal fasciculus). Borich et al19 36 Participants with mTBI showed clusters of significantly higher FA values, primarily located in the anterior

associative and descending motor pathways. Virji-Babul et al21 36 Participants with mTBI showed increased whole-brain FA. van Beek et al58 182 Participants with mTBI had a significant increase in FA in the right-anterior CR, left cerebral peduncles, and left

superior CR and at ∼6 mo postinjury showed increased FA values in the CC splenium. In the CC splenium, there was a significant increase in FA from 1 to 6 mo in both the control and mTBI groups, with

the mTBI group showing higher splenial FA values than controls. Axial diffusivity van Beek et al57 17 No group differences were observed in AD measures of the CC genu. Borich et al19 36 Participants with mTBI demonstrated higher AD values in the left-superior temporal gyrus, left pulvinar (thalamus),

and left- and right-superior parietal lobe compared with orthopedically injured controls; lower AD values were shown in participants with mTBI in 1 region of the superior parietal lobe compared with controls.

van Beek et al58 182 No significant effects over time were observed for AD values in the CC genu; the AD values in the CC splenium showed no significant effects. Additionally, no changes over time or between groups were seen in the superior

longitudinal fasciculus or inferior longitudinal fasciculus. MD Babcock et al48 2 Participants with mTBI had lower MD values in the right-lateral orbital, left-anterior CR, and the right-middle frontal

gyrus. van Beek et al57 17 Participants with mTBI had lower MD values in the CC genu but no other areas of the CC. Virji-Babul et al21 36 The mTBI group had decreased MD by using whole-brain DTI analysis. van Beek et al58 182 No significant effects over time were observed for MD values in the CC genu; the MD values in the CC splenium

showed no significant effects. Additionally, no changes over time or between groups were seen in the superior longitudinal fasciculus or inferior longitudinal fasciculus.

Radial diffusivity Babcock et al48 2 Participants with mTBI had lower RD values in many regions, including the CC. Wilde et al22 5 Participants with mTBI had decreased RD values for the whole CC. Mayer et al20 16 Participants with mTBI had lower RD bilaterally in the ACR. Mayer et al20 16 Participants with mTBI had lower RD bilaterally in the ACR. van Beek et al57 17 Participants with mTBI had lower RD values in the CC genu. van Beek et al58 182 RD values of the CC genu were significantly decreased in the control group but not the mTBI group from 1 to 6 mo

postinjury; however, there was no significant difference between groups. RD values of the CC splenium were significantly decreased over time in the control group but not the mTBI group; however, there was no significant

difference between the groups. ADC Chu et al53 3 Participants with mTBI showed 6 unspecified regions with significant decreases in ADC values and no areas with

increased ADC. Wilde et al22 5 Participants mTBI had decreased ADC values for the whole CC.fMRI Task based Yang et al61 16 Participants with mTBI showed less activation by using fMRI during an auditory orienting task in various areas,

including the bilateral posterior cingulate gyrus (BA 23); bilateral medial dorsal, ventral anterior, and ventral lateral nuclei of the thalamus; basal ganglia (including bilateral caudate and left putamen and/or globus

pallidus); bilateral substantia nigra; bilateral subthalamic nucleus; left red nucleus; right pons; and bilateral cerebellar (lingual and culmen).

Krivitzky et al24 29 Participants with mTBI showed no differences in the working memory aspects of a task but had greater activation in the posterior cerebellum when given an additional cognitive demand of inhibitory control.

Keightley et al23 39 The mTBI group showed significantly less activation in areas including the bilateral dorsolateral prefrontal cortex, left premotor cortex, supplementary motor area, and left-superior parietal lobule during the verbal working

memory condition in various regions.

Secondly, although there was heterogeneity in the specific regions and tracts that showed differences, many of these regions contained the corticospinal tract components of the CC or frontal white-matter regions. This finding could reflect limited sensitivity in DTI as a method because only major white-matter tracts reliably show changes.30 Nevertheless, this trend is interesting in the pediatric context: myelination commences early (eg, in the third trimester)70 and does not become electrophysiologically complete until adolescence (ie, ∼13 years of age).71

Future researchers could investigate a younger population to understand whether the involvement of the corticospinal pathway is consistent with normal age-related maturation or is due to changes post-mTBI.

Finally, many studies were conducted in the short-term postinjury, which provides relevant information to indicate how neuroimaging may be related to the manifestation of early symptoms (eg, 2 days) and the typical resolution of behavioral symptoms (eg, 1 month postinjury). Notably, studies with a younger average age

at injury often had a longer time from injury to assessment, which creates difficulty with data pooling. More longitudinal studies are necessary to pool data.

Clinically, current best practice in concussion management relies on a variety of tools for diagnosis and assessment. Imaging is not currently sensitive or reliable for this purpose. To provide a complete and accurate assessment and build the post-mTBI management plan, brain imaging combined with behavioral measures and other emerging biological

PEDIATRICS Volume 141, number 5, May 2018 11

Reference Time Postinjury, d Results Saluja et al25 39 By using a navigation memory task, the mTBI group had decreased activation in the retrosplenial,

parahippocampal, and thalamic areas bilaterally and the right dorsolateral prefrontal and left precuneus areas. The mTBI group had significantly higher activation in the left hippocampal and right-middle temporal areas.

Sinopoli et al56 135 Participants with mTBI had both higher and lower activity during various conditions of a working memory task, primarily in the dorsolateral prefrontal cortex, compared with the control group at 3–6 mo postinjury.

Westfall et al60 226 During a working memory task, the mTBI group had significantly greater activation in 3 clusters, including BA 13, 19, and 39; BA 6 and 13; and BA 4 and 6, which was observed on only the most difficult component of the task.

Resting state Borich et al19 36 Participants with mTBI showed altered functional connectivity in 3 resting-state networks, including (1) alterations

in the default mode network, (2) increased connectivity in the right-frontal pole of the executive functional network, and (3) increased connectivity in the left-frontal pole operculum cortex associated with the ventral

attention network.SWI Babcock et al48 2 No differences in the No. and size of covert lesions were shown in participants with mTBI compared with matched

controls. Maugans et al55 2, 14, 90 No differences in the No. and size of covert lesions were shown in participants with mTBI compared with matched

controls at any time point. Wilde et al22 5 No differences in the No. and size of covert lesions were shown in participants with mTBI compared with matched

controls. Yang et al61 16 No differences in the No. and size of covert lesions were shown in participants with mTBI compared with matched

controls. Beauchamp et al50 36 Participants with mTBI and no abnormalities on clinical MRI and/or CT showed a lower volume and No. covert

lesions compared with participants with mTBI who had imaging abnormalities on clinical MRI and/or CT. Bigler et al51 932 No statistical comparisons were made between participants with mTBI and controls.EEG Virji-Babul et al59 45 Participants with mTBI showed reduced connections corresponding to the right frontopolar prefrontal cortex and

increased values of betweenness and degree in frontal electrode sites corresponding to the right dorsolateral prefrontal cortex and the right-inferior frontal gyrus by using graph theory analysis.

Baillargeon et al49 174 Participants with mTBI had a smaller P3b amplitude compared with healthy controls. Moore et al44 756 Participants with mTBI had a smaller P3b amplitude compared with healthy controls.MRI Maugans et al55 2, 14, 90 No abnormalities or differences between the mTBI and healthy control groups were found. Bigler et al51 932 Participants with mTBI showed a decreased volume in anterior and posterior CC white matter compared with

orthopedically injured controls, and no difference was seen in other aspects analyzed (eg, ventricle-to-brain ratio, total ventricular volume, and whole-brain gray-matter volume).

Levin et al54 1944 Approximately 28% of participants with mTBI had frontal lesions observed on anatomic MRI, with no statistical comparisons made between the mTBI and control groups.

MRS Maugans et al55 2, 14, 90 No group differences were observed between participants with mTBI and controls in the concentrations of N-acetyl

aspartate and N-acetyl aspartate creatine and phosphocreatine.

AD, axial diffusivity; BA, Brodmann area; CP, cerebral peduncles; CR, corona radiate; RD, radial diffusivity.

TABLE 4 Continued

biomarkers (eg, genetics and blood)11 may represent best practice.

Some imaging methods identified in this review did not reveal significant differences between participants with and without mTBI (eg, anatomic MRI, SWI, and MRS) nor correlations with behavior. It may be that these imaging methods are viable as potential biomarkers for pediatric mTBI, but investigation in larger samples is required to show group

differences.26 The data presented here suggest that they may not provide useful information with which to predict recovery from mTBI in children and/or adolescents.

This systematic review had several limitations, demonstrating the need for future research. First, because of the heterogeneity of the studies, small number of publications, and low proportion of individual patient-reported data (6 studies), we were

not able to conduct a best-evidence synthesis or meta-analysis. Pooling individual patient data can depict a different summary than can aggregated group data.72 Therefore, future research using imaging in pediatric mTBI would benefit from publishing individual patient data as well as common data elements73 to allow for the pooling of data. In this way, the scope of a meta-analysis will broaden and possibly be refined on the basis of imaging type (eg, fMRI or

SCHMIDT et al12

TABLE 5 Behavioral Results

Reference Time Postinjury, d Behavioral Results

DTI Borich et al19 36 A significant negative correlation between whole-brain MD, AD, and AD values and a concussion assessment scale

was shown, with lower scores indicating worse outcomes (ie, as MD, AD, and AD increased, concussion outcome scores decreased).

No correlation was identified between whole-brain FA values and a concussion assessment scale. Chu et al53 3 A significant negative relationship was shown between RD and ADC values and a postconcussive symptom scale in

regions predominantly located in the white matter, suggesting that diffusivity decreased as symptoms increased.A positive relationship was shown with FA values and the experience of symptoms in that FA increased as symptoms

increased.Correlations were also described with a measure of emotional distress and ADC, indicating that ADC values

decreased as emotional distress increased. Maugans et al55 2, 14, 90 No significant correlations were shown. Mayer et al20 16 No correlation or relationship was identified between FA in the regions of interest and cognitive performance (ie,

attention and processing-speed domains). van Beek et al57 17 A significant correlation was identified in the mTBI group with FA and RD in the CC splenium and large arithmetic

problem-solving, with higher FA and lower RD in the splenium being more accurate in solving large arithmetic problems.

No correlation was identified in the mTBI group with large arithmetic problem-solving and FA, RD, and MD in the CC genu and MD in the CC splenium.

Virji-Babul et al21 36 A significant association was shown with whole-brain FA and MD values with the SCAT-2, in which higher FA values and lower MD values were associated with lower concussion outcome scores (ie, worse outcomes).

Wilde et al22 5 Total CC FA values were significantly positively correlated with symptom severity and emotional distress in the mTBI group (ie, as FA values increased, symptom severity and emotional distress increased).

A significant negative relationship was shown between RD and ADC values and a postconcussive symptom scale in regions predominantly located in the white matter, suggesting that diffusivity decreased as symptoms increased.

fMRI Krivitzky et al24 29 A negative correlation was shown between a neurocognitive subtest (ie, metacognitive index) and activation in the

posterior cerebellum.Significant positive correlations were identified between the number of symptoms and activation in the cerebellum

and posterior cerebrum (temporal and/or parietal regions) in that as brain activation increased, symptoms increased.

No correlation was shown between the measures of working memory and activation during a working memory task. Westfall et al60 226 No correlations were shown between fMRI activation and fMRI task performance accuracy or reaction time.EEG Baillargeon

et al49174 A significant negative relationship was found between the total symptom score and amplitude of P3b for a group

of older adolescents with concussion ranging from 13 to 16 y, but this relationship was not seen in the younger group ranging from 9 to 12 y.

Adolescents who had more symptoms at the time of injury had a lower amplitude of P3b at the time of testing. Virji-Babul et al59 45 A significant negative correlation between the degree and hub value and/or authority with total symptom score at

the Fpz node was shown.MRI Bigler et al51 932 No correlation was shown between neurocognitive performance and several volumetric measures (ventricle-to-brain

ratio, total brain volume, total white matter and total gray matter volume, total posterior CC volume, and total CC volume).

AD, axial diffusivity; Fpz, electrode near the frontal pole on the midline; RD, radial diffusivity; SCAT-2, Sports Concussion Assessment Tool 2.

DTI), time postinjury, and age at the time of the injury as well as inform clinically ready brain biomarkers.

Second, there were limitations in both the population included in this review and the data reported in individual studies. For example, this review did not include studies with children <5 years of age. Younger children are a neurologically distinct population because of structural immaturities (eg, a lack of myelination)74 and functional differences (eg, differing levels and areas of activation during task performance).75 Thus, the younger age group requires specific investigation.

Additionally, there was heterogeneity in the mechanism of concussive injury (eg, diffuse axonal injury). This, coupled with differences in brain development among children and/or youth, may limit the reliability of currently reported findings. For example, even animal models with specific experimental control of biomechanical forces and homogeneity of age and/or development reveal heterogeneous patterns of diffuse axonal injuries despite the fiber bundles being exposed to nearly identical forces.76, 77 As such, future researchers should report on the mechanism of injury and account for this in analyses.

Given that the investigation of pediatric mTBI is in its infancy, our inclusion criteria were designed to maximize the number of studies included. As such, some work outlined in this review includes comparisons between mTBI and other clinical injuries (eg, orthopedic injuries). As data accumulate, researchers in pediatric brain

biomarker identification studies should compare mTBI and control groups with no history of neurologic injury or report on the severity and effect of other nonhead injuries. Although comparisons to participants with recent injuries not involving the head are common to account for subtle, nonspecific effects of an injury (eg, anxiety and distress), nonhead-injured control groups may have behavioral differences that limit data pooling.

There were only 3 longitudinal studies included in which researchers collected data up to 6 months postinjury. Long-term studies are vital to indicating predictive biomarkers for persistent impairments in behavior. Findings could help determine which individuals are more at risk for persistent impairments, and thus require more intensive monitoring or comprehensive clinical assessments.78 Furthermore, it could guide individualized mTBI management, including intervention plans and return-to-activity decisions.79 Longitudinal studies are particularly important for pediatric mTBI because of the variability of normal developmental74 and individual outcomes after mTBI.13 Future researchers should include multiple time points after injury and manage individuals for at least 12 months.

There are a number of potentially appropriate imaging and/or brain stimulation methods that were not identified in this review, which have been established in the adult mTBI population. These include transcranial magnetic stimulation17 and near-infrared spectroscopy80

methods, which may yield important data that allow for the detection of subtle brain changes that link the brain and behavior after mTBI.81

CONCLUSIONS

This systematic review represents an important step forward in mTBI research and will inform future work. It has been challenging to identify brain biomarkers in pediatric mTBI, in part because of the dynamic time course of changes postinjury16 and heterogeneity across the experiments performed to date. The most frequently used imaging method, DTI, had equally heterogeneous findings, although FA was increased in all but 1 of the included studies. Collectively, this study represents the critical first step in enabling pediatric concussion brain biomarker researchers to overcome the inherent lag behind advancements in the adult population.

ABBREVIATIONS

ADC:  apparent diffusion coefficient

CC:  corpus callosumCT:  computed tomographyDTI:  diffusion tensor imagingFA:  fractional anisotropyfMRI:  functional MRIMD:  mean diffusivityMRS:  magnetic resonance

spectroscopymTBI:  mild traumatic brain

injuryrsfMRI:  resting-state functional

MRISWI:  susceptibility-weighted

imagingTBI:  traumatic brain injury

PEDIATRICS Volume 141, number 5, May 2018 13

Dr Babul contributed to the conception and design of the review and interpretation of data with an emphasis on the clinical management of mild traumatic brain injuries and how findings relate to current literature; Dr Boyd guided the conception and design of the review and interpretation of data with a specific emphasis on brain imaging findings; and all authors revised the manuscript critically for intellectual content, approved the final manuscript as submitted, and agree to be accountable for all aspects of the work.

This trial has been registered on PROSPERO (identifier: CRD42016041499).

DOI: https:// doi. org/ 10. 1542/ peds. 2017- 3406

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Accepted for publication Feb 12, 2018

Address correspondence to Julia Schmidt, OT, PhD, Department of Physical Therapy, University of British Columbia, 212-2177 Wesbrook Mall, Vancouver, BC, Canada V6T 1Z3. E-mail: julia.schmidt@ubc.ca

PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).

Copyright © 2018 by the American Academy of Pediatrics

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

FUNDING: Funded by a grant from the Jakeway Family Foundation. Dr Schmidt receives salary support from the Michael Smith Foundation for Health Research (MSFHR); Dr Hayward is funded by Australia’s National Health and Medical Research Council (1088449) and the MSFHR (15980); Dr Brown was supported by the Natural Sciences and Engineering Research Council of Canada; and Dr Zwicker is funded by the MSFHR, Canadian Child Health Clinician Scientist Program, the BC Children’s Hospital Research Institute, the Sunny Hill Foundation, and the Canadian Institutes of Health Research.

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

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