Imaging biomarkers of epileptogenecity after traumatic brain injury – Preclinical frontiers

Abstract

Posttraumatic epilepsy (PTE) is a major neurodegenerative disease accounting for 20% of symptomatic epilepsy cases. A long latent phase offers a potential window for prophylactic treatment strategies to prevent epilepsy onset, provided that the patients at risk can be identified. Some promising imaging biomarker candidates for posttraumatic epileptogenesis have been identified, but more are required to provide the specificity and sensitivity for accurate prediction. Experimental models and preclinical longitudinal, multimodal imaging studies allow follow-up of complex cascade of events initiated by traumatic brain injury, as well as monitoring of treatment effects. Preclinical imaging data from the posttraumatic brain are rich in information, yet examination of their specific relevance to epilepsy is lacking. Accumulating evidence from ongoing preclinical studies in TBI support insight into processes involved in epileptogenesis, e.g. inflammation and changes in functional and structural brain-wide connectivity. These efforts are likely to produce both new biomarkers and treatment targets for PTE.

A review of seizures and epilepsy following traumatic brain injury

“…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.…”

Imaging biomarkers of posttraumatic epileptogenesis

“…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.…”

“…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.…”

“…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.…”

Multiplex Networks to Characterize Seizure Development in Traumatic Brain Injury Patients

“…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).…”