Diffusion-Weighted Imaging in Mild Traumatic Brain Injury: A Systematic Review of the Literature

Lindsey, Hannah M.; Hodges, Cooper B.; Greer, Kaitlyn M.; Wilde, Elisabeth A.; Merkley, Tricia L.

doi:10.1007/s11065-021-09485-5

Cited by 26 publications

(21 citation statements)

References 242 publications

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“…Even in mTBI, studies generally report abnormalities in diffusion imaging metrics across several regions, most commonly in the corpus callosum, corona radiata, internal capsule, cingulum bundle, and long association pathways, including the superior longitudinal fasciculus. 15 In children, adolescents, and adults, there is some evidence of initially increased fractional anisotropy and decreased apparent diffusion coefficient or mean diffusivity in the acute to subacute recovery phase, although longitudinal studies do not necessarily suggest a consistent pattern of DTI changes over time. 15 , 16 Additional longitudinal studies and studies of mTBI are needed to further explore the precise trajectory of change in diffusion metrics over the course of recovery.…”

Section: Diagnostic Biomarkersmentioning

confidence: 99%

“… 15 In children, adolescents, and adults, there is some evidence of initially increased fractional anisotropy and decreased apparent diffusion coefficient or mean diffusivity in the acute to subacute recovery phase, although longitudinal studies do not necessarily suggest a consistent pattern of DTI changes over time. 15 , 16 Additional longitudinal studies and studies of mTBI are needed to further explore the precise trajectory of change in diffusion metrics over the course of recovery.…”

Section: Diagnostic Biomarkersmentioning

confidence: 99%

“…Similarly, the majority of studies found a relationship between diffusion imaging and cognitive performance (e.g., attention, memory, processing speed, executive functioning, mental status), particularly in the early recovery phase. 15 Other techniques, described in more detail subsequently, are promising, but are also still in the discovery phase.…”

Section: Prognostic and Predictive Biomarkersmentioning

confidence: 99%

See 2 more Smart Citations

A Framework to Advance Biomarker Development in the Diagnosis, Outcome Prediction, and Treatment of Traumatic Brain Injury

Wilde

Wanner

Kenney

et al. 2022

Journal of Neurotrauma

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Multi-modal biomarkers (e.g., imaging, blood-based, physiological) of unique traumatic brain injury (TBI) endophenotypes are necessary to guide the development of personalized and targeted therapies for TBI. Optimal biomarkers will be specific, sensitive, rapidly and easily accessed, minimally invasive, cost effective, and bidirectionally translatable for clinical and research use. For both uses, understanding how TBI biomarkers change over time is critical to reliably identify appropriate time windows for an intervention as the injury evolves. Biomarkers that enable researchers and clinicians to identify cellular injury and monitor clinical improvement, inflection, arrest, or deterioration in a patient's clinical trajectory are needed for precision healthcare. Prognostic biomarkers that reliably predict outcomes and recovery windows to assess neurodegenerative change and guide decisions for return to play or duty are also important. TBI biomarkers that fill these needs will transform clinical practice and could reduce the patient's risk for long-term symptoms and lasting deficits. This article summarizes biomarkers currently under investigation and outlines necessary steps to achieve short- and long-term goals, including how biomarkers can advance TBI treatment and improve care for patients with TBI.

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Section: Diagnostic Biomarkersmentioning

confidence: 99%

Section: Diagnostic Biomarkersmentioning

confidence: 99%

Section: Prognostic and Predictive Biomarkersmentioning

confidence: 99%

See 1 more Smart Citation

A Framework to Advance Biomarker Development in the Diagnosis, Outcome Prediction, and Treatment of Traumatic Brain Injury

Wilde

Wanner

Kenney

et al. 2022

Journal of Neurotrauma

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“…Pediatric mild traumatic brain injury (mTBI) is a prevalent global public health concern (8)(9)(10)(11) that is characterized by subtle and diffuse alterations in brain tissue [reviewed in (12,13)]. The neurobiology of pediatric mTBI remains poorly understood [see (12)].…”

Section: Introductionmentioning

confidence: 99%

“…The neurobiology of pediatric mTBI remains poorly understood [see (12)]. White matter microstructural alterations can occur after pediatric mTBI, and multiple studies have examined specific white matter tracts using diffusion tensor imaging [DTI; (13)(14)(15)]. Emerging evidence indicates that pediatric mTBI can alter global and regional brain networks (16)(17)(18)(19).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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

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Longitudinal changes in brain parenchyma due to mild traumatic brain injury during the first year after injury

et al. 2021

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Chronic gray matter (GM) atrophy is a known consequence of moderate and severe traumatic brain injuries but has not been consistently shown in mild traumatic brain injury (mTBI). The aim of this study was to investigate the longitudinal effect of uncomplicated mTBI on the brain's GM and white matter (WM) from 6 weeks to 12 months after injury. Voxel-based-morphometry (VBM) was computed with the T1-weighted images of 48 uncomplicated mTBI patients and 37 orthopedic controls. Over the period from 6 weeks to 12 months, only patients who experienced uncomplicated mTBI, but not control participants, showed significant GM decrease predominantly in the right hemisphere along the GM-CSF border in lateral and medial portions of the sensorimotor cortex extending into the rolandic operculum, middle frontal gyrus, insula, and temporal pole. Additionally, only mTBI patients, but not controls, experienced significant WM decrease predominantly in the right hemisphere in the superior fasciculus longitudinalis, arcuate fasciculus, and cortical-pontine tracts as well as a significant WM increase in left arcuate fasciculus and left capsula extrema. We did not observe any significant change in the controls for the same time interval or any significant group differences in GM and WM probability at each of the two timepoints. This suggests that the changes along the brain tissue borders observed in the mTBI group represent a reorganization associated with subtle microscopical changes in intracortical myelin and not a direct degenerative process as a result of mTBI.

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Diffusion-Weighted Imaging in Mild Traumatic Brain Injury: A Systematic Review of the Literature

Cited by 26 publications

References 242 publications

A Framework to Advance Biomarker Development in the Diagnosis, Outcome Prediction, and Treatment of Traumatic Brain Injury

A Framework to Advance Biomarker Development in the Diagnosis, Outcome Prediction, and Treatment of Traumatic Brain Injury

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

Longitudinal changes in brain parenchyma due to mild traumatic brain injury during the first year after injury

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