Imaging biomarkers of epileptogenecity after traumatic brain injury – Preclinical frontiers

Immonen, Riikka; Harris, Neil; Wright, David K.; Johnston, Leigh A.; Manninen, Eppu; Smith, Gregory S.; Paydar, Afshin; Branch, Craig A.; Gröhn, Olli

doi:10.1016/j.nbd.2018.10.008

Cited by 19 publications

(15 citation statements)

References 114 publications

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“…The challenge is to identify biomarkers for these processes and target interventions. Imaging markers such as gradient echo MRI for blood products or diffusion tensor MRI for pathway remodelling, evidence of thalamic or hippocampal damage may help to stratify risk [ 29 ]. Genetic markers help stratification of the interaction between acquired and constitutional risk.…”

Section: Prevention Of Seizures and Epilepsymentioning

confidence: 99%

A review of seizures and epilepsy following traumatic brain injury

2020

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Traumatic brain injury (TBI) is one of the commonest presentations to emergency departments and is associated with seizures carrying different significance at different stages following injury. We describe the epidemiology of early and late seizures following TBI, the significance of intracranial haemorrhage of different types in the risk of later epilepsy and the gaps in current understanding of risk factors contributing to the risk of post-traumatic epilepsy (PTE). The delay from injury to epilepsy presents an opportunity to understand the mechanisms underlying changes in the brain and how they may reveal potential targets for anti-epileptogenic therapy. We review existing treatments, both medical and surgical and conclude that current research is not tailored to differentiate between PTE and other forms of focal epilepsy. Finally, we review the increasing understanding of the frequency and significance of dissociative seizures following mild TBI.

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Section: Prevention Of Seizures and Epilepsymentioning

confidence: 99%

A review of seizures and epilepsy following traumatic brain injury

2020

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“…Microstructural hippocampal changes are of particular interest, as the dentate gyrus in TBI rats has shown to be particularly susceptible to generating self-sustaining epileptic activity following stimulation compared with controls. 48 DTI abnormalities may thus reveal biomarkers of epileptogenic etiology unique from injury. FA and axial, radial, and mean diffusivities were each altered following both SE and TBI, where changes followed a gradient: SE > ipsilateral to TBI > contralateral to TBI.…”

Section: Dti Highlights Structural Plasticity In Preclinical Modelsmentioning

confidence: 99%

“…47 LFP models have also proposed that mossy fiber sprouting in the dentate gyrus of the hippocampus is associated with increased seizure susceptibility, suggesting that network plasticity may be a mechanism of spontaneous seizure generation. 48 DTI abnormalities may thus reveal biomarkers of epileptogenic etiology unique from injury.…”

Section: Dti Highlights Structural Plasticity In Preclinical Modelsmentioning

confidence: 99%

“…For instance, rs-fMRI generally relies on grouplevel analysis, which potentially prevents biomarker identification at the individual level. 48 Furthermore, although alternative statistical frameworks suitable for single-dataset (eg, single-patient) inference have been employed in other fields, 102,103 their application to neuroimaging data, and patients in particular, is still in its infancy. 104 Novel approaches may also include exploratory machine learning and deep learning methods as well as model-based approaches that can leverage large, multimodal, datasets.…”

Section: Interpretation and Validation For Clinical Applicationsmentioning

confidence: 99%

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Imaging biomarkers of posttraumatic epileptogenesis

et al. 2019

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Traumatic brain injury (TBI) affects 2.5 million people annually within the United States alone, with over 300 000 severe injuries resulting in emergency room visits and hospital admissions. Severe TBI can result in long‐term disability. Posttraumatic epilepsy (PTE) is one of the most debilitating consequences of TBI, with an estimated incidence that ranges from 2% to 50% based on severity of injury. Conducting studies of PTE poses many challenges, because many subjects with TBI never develop epilepsy, and it can be more than 10 years after TBI before seizures begin. One of the unmet needs in the study of PTE is an accurate biomarker of epileptogenesis, or a panel of biomarkers, which could provide early insights into which TBI patients are most susceptible to PTE, providing an opportunity for prophylactic anticonvulsant therapy and enabling more efficient large‐scale PTE studies. Several recent reviews have provided a comprehensive overview of this subject (Neurobiol Dis, 123, 2019, 3; Neurotherapeutics, 11, 2014, 231). In this review, we describe acute and chronic imaging methods that detect biomarkers for PTE and potential mechanisms of epileptogenesis. We also describe shortcomings in current acquisition methods, analysis, and interpretation that limit ongoing investigations that may be mitigated with advancements in imaging techniques and analysis.

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“…Changes in gray matter and white matter related to epilepsy have been widely observed by using structural MRI (Immonen et al, 2018;Shah et al, 2019;Lutkenhoff et al, 2020). Many recent studies have shown that machine learning techniques and multiplex networks applied to completely non-invasive neuroimaging techniques, such as structural MRI, can be useful and efficient to detect pathological alterations in several neurological diseases, such as Alzheimer's disease, Parkinson's disease, and epilepsy (Amoroso et al, 2018c;La Rocca et al, 2018;Bharath et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Multiplex Networks to Characterize Seizure Development in Traumatic Brain Injury Patients

et al. 2020

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Traumatic brain injury (TBI) may cause secondary debilitating problems, such as post-traumatic epilepsy (PTE), which occurs with unprovoked recurrent seizures, months or even years after TBI. Currently, the Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) has been enrolling moderate-severe TBI patients with the goal to identify biomarkers of epileptogenesis that may help to prevent seizure occurrence and better understand the mechanism underlying PTE. In this work, we used a novel complex network approach based on segmenting T1-weighted Magnetic Resonance Imaging (MRI) scans in patches of the same dimension (network nodes) and measured pairwise patch similarities using Pearson's correlation (network connections). This network model allowed us to obtain a series of single and multiplex network metrics to comprehensively analyze the different interactions between brain components and capture structural MRI alterations related to seizure development. We used these complex network features to train a Random Forest (RF) classifier and predict, with an accuracy of 70 and a 95% confidence interval of [67, 73%], which subjects from EpiBioS4Rx have had at least one seizure after a TBI. This complex network approach also allowed the identification of the most informative scales and brain areas for the discrimination between the two clinical groups: seizure-free and seizure-affected subjects, demonstrating to be a promising pilot study which, in the future, may serve to identify and validate biomarkers of PTE.

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Imaging biomarkers of epileptogenecity after traumatic brain injury – Preclinical frontiers

Cited by 19 publications

References 114 publications

A review of seizures and epilepsy following traumatic brain injury

A review of seizures and epilepsy following traumatic brain injury

Imaging biomarkers of posttraumatic epileptogenesis

Multiplex Networks to Characterize Seizure Development in Traumatic Brain Injury Patients

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