A window into eye movement dysfunction following mTBI: A scoping review of magnetic resonance imaging and eye tracking findings

McDonald, Matthew A; Tayebi, Maryam; McGeown, Joshua P.; Kwon, Eryn; Holdsworth, Samantha J.; Danesh‐Meyer, Helen V.

doi:10.1002/brb3.2714

Cited by 8 publications

(12 citation statements)

References 211 publications

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“…Previous studies using DTI to evaluate PCS at the group level have focused on univariate analyses of diffusion metrics, such as fractional anisotropy (FA), apparent diffusion coe cient (ADC), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD) [24] . Although microstructural changes in DTI metrics have been demonstrated at a group level in patients with PCS, the practical application of these changes at an individual level for diagnosis, treatment, and follow-up care has been lacking [18,25] .…”

Section: Introductionmentioning

confidence: 99%

Clinical Performance of a Multiparametric MRI-based Post Concussive Syndrome Index

Meyers

Hirad

González³

et al. 2023

Preprint

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Background Diffusion Tensor Imaging (DTI) has shown measurable changes in the brains of patients with persistent post-concussive syndrome (PCS). Because of inconsistent results in univariate DTI metrics among patients with mild traumatic brain injury (mTBI), currently, there is no single objective and reliable MRI index for the clinical decision-making for patients with PCS.Objectives The aim of this study was to evaluate the performance of a newly developed post-concussive syndrome index (PCSI) derived from machine learning of multiparametric MRI data, to classify and differentiate subjects with mTBI and PCS history from those without history of mTBI.Methods Data were retrospectively extracted from 139 patients aged between 18 and 60 years with PCS who had MRI examinations obtained 2 weeks to 1-year post-mTBI, as well as MRI data from 333 subjects without a history of head trauma. The performance of the PCSI was assessed by comparing patients with a clinical diagnosis of PCS to control subjects. The PCSI values for patients with PCS were compared based on mechanism of injury, time interval from injury to MRI examination, gender, prior concussion history, loss of consciousness, and reported symptoms.Results Patients with mTBI had a mean PCSI value of 0.57, compared to the control group, which had a mean PCSI value of 0.12 (p = 8.42e− 23) with accuracy of 88%, sensitivity of 64%, and specificity of 95% respectively. No statistically significant differences were found in PCSI values when comparing by mechanism of injury, gender, or loss of consciousness.Conclusion The PCSI for individuals aged between 18 and 60 years was able to accurately identify patients with post-concussive injuries from 2 weeks to 1-year post-mTBI and differentiate them from controls. The study's results suggest that the multiparametric MRI-based PCSI has great potential as an objective clinical tool to support the diagnosis, treatment, and follow-up care of those with post-concussive syndrome. Future research is required to investigate the replicability of this method using other types of clinical MRI scanners.

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Section: Introductionmentioning

confidence: 99%

Clinical Performance of a Multiparametric MRI-based Post Concussive Syndrome Index

Meyers

Hirad

González³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Previous studies using DTI to evaluate PCS at the group level have focused on univariate analyses of diffusion metrics such as FA, ADC, MD, RD, and AD ( 24 ). Although microstructural changes in DTI metrics have been demonstrated at the group level in patients with PCS, the complexity of advanced DTI post-analysis limits its application of these changes at the individual level in clinical settings for diagnosis, treatment, and follow-up care ( 18 , 25 ).…”

Section: Introductionmentioning

confidence: 99%

“…Despite advances in measuring changes in the brain related to traumatic brain injury, there is currently no objective and reliable MRI assessment to guide clinical decision-making for individual patients with mTBI and PCS ( 18 , 24 , 25 ). The lack of objective data on mTBI in patients leads to challenges in the diagnosis, prognosis, and treatment of patients with a history of mTBI and PCS, based on subjective symptom reports and clinical examinations ( 25 ). To address this issue, machine learning (ML) approaches have been suggested ( 26–28 ).…”

Section: Introductionmentioning

confidence: 99%

Clinical performance of a multiparametric MRI-based post concussive syndrome index

Meyers,

Hirad,

Gonzalez

et al. 2023

Front. Neurol.

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IntroductionDiffusion Tensor Imaging (DTI) has revealed measurable changes in the brains of patients with persistent post-concussive syndrome (PCS). Because of inconsistent results in univariate DTI metrics among patients with mild traumatic brain injury (mTBI), there is currently no single objective and reliable MRI index for clinical decision-making in patients with PCS.PurposeThis study aimed to evaluate the performance of a newly developed PCS Index (PCSI) derived from machine learning of multiparametric magnetic resonance imaging (MRI) data to classify and differentiate subjects with mTBI and PCS history from those without a history of mTBI.Materials and methodsData were retrospectively extracted from 139 patients aged between 18 and 60 years with PCS who underwent MRI examinations at 2 weeks to 1-year post-mTBI, as well as from 336 subjects without a history of head trauma. The performance of the PCS Index was assessed by comparing 69 patients with a clinical diagnosis of PCS with 264 control subjects. The PCSI values for patients with PCS were compared based on the mechanism of injury, time interval from injury to MRI examination, sex, history of prior concussion, loss of consciousness, and reported symptoms.ResultsInjured patients had a mean PCSI value of 0.57, compared to the control group, which had a mean PCSI value of 0.12 (p = 8.42e-23) with accuracy of 88%, sensitivity of 64%, and specificity of 95%, respectively. No statistically significant differences were found in the PCSI values when comparing the mechanism of injury, sex, or loss of consciousness.ConclusionThe PCSI for individuals aged between 18 and 60 years was able to accurately identify patients with post-concussive injuries from 2 weeks to 1-year post-mTBI and differentiate them from the controls. The results of this study suggest that multiparametric MRI-based PCSI has great potential as an objective clinical tool to support the diagnosis, treatment, and follow-up care of patients with post-concussive syndrome. Further research is required to investigate the replicability of this method using other types of clinical MRI scanners.

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“… 12 , 13 Similar results have been reported in patients with mild TBI, both within 24 h and one month after the injury. 14 – 16 Oculomotor functions are known to be linked to perceptual visual attention, too. 17 Patients with mild-to-severe TBI tend to spend less time on visual target stimuli compared to controls.…”

Section: Introductionmentioning

confidence: 99%

A Potential Multimodal Test for Clinical Assessment of Visual Attention in Neurological Disorders

et al. 2022

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Attention is an important aspect of human brain function and often affected in neurological disorders. Objective assessment of attention may assist in patient care, both for diagnostics and prognostication. We present a compact test using a combination of a choice reaction time task, eye-tracking and EEG for assessment of visual attention in the clinic. The system quantifies reaction time, parameters of eye movements (i.e. saccade metrics and fixations) and event related potentials (ERPs) in a single and fast (15 min) experimental design. We present pilot data from controls, patients with mild traumatic brain injury and epilepsy, to illustrate its potential use in assessing attention in neurological patients. Reaction times and eye metrics such as fixation duration, saccade duration and latency show significant differences (p < .05) between neurological patients and controls. Late ERP components (200–800 ms) can be detected in the central line channels for all subjects, but no significant group differences could be found in the peak latencies and mean amplitudes. Our system has potential to assess key features of visual attention in the clinic. Pilot data show significant differences in reaction times and eye metrics between controls and patients, illustrating its promising use for diagnostics and prognostication.

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A window into eye movement dysfunction following mTBI: A scoping review of magnetic resonance imaging and eye tracking findings

Cited by 8 publications

References 211 publications

Clinical Performance of a Multiparametric MRI-based Post Concussive Syndrome Index

Clinical Performance of a Multiparametric MRI-based Post Concussive Syndrome Index

Clinical performance of a multiparametric MRI-based post concussive syndrome index

A Potential Multimodal Test for Clinical Assessment of Visual Attention in Neurological Disorders

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