By: Catherine Joachin
Neuroimaging and Epilepsy
Introduction
Neuroimaging in epilepsy involves using noninvasive brain imaging techniques to explore the structure and function of the central nervous systemic relation to epilepsy syndromes, seizure types and the precipitating mechanisms that cause seizures.
Although EEG, which uses sensors called electrodes to record electrical brain activity along the scalp, is the most widely used tool for seizure detection, other methods may be used to detect more subtle changes in brain activity. These include computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET), to name a few.
Advanced neuroimaging approaches are increasingly being integrated into research and clinical settings to improve the diagnosis, prognosis, and treatment of epilepsy. Recent developments in high-field imaging and post-processing techniques such as automated volumetry and voxel-based morphometry (VBM), for instance, have made it easier to localize seizure onset and predict outcomes after epilepsy surgery (Sidhu, Duncan & Sander, 2018). The integration of machine learning models has also improved diagnostic accuracy and post-surgical seizure outcomes predictions.
Neuroimaging in Juvenile Myoclonic Epilepsy
The evolution of highly sensitive neuroimaging modalities has enabled a deeper exploration of the pathological mechanisms underlying specific epilepsy syndromes, such as juvenile myoclonic epilepsy (JME).
Juvenile myoclonic epilepsy is the most prevalent form of idiopathic generalized epilepsy, accounting for 26.7% of all generalized epilepsies of unknown origin and 4.1% of all epilepsies, making it an important global health concern (Serafini et al., 2013). It is characterized by generalized tonic-clonic seizures, uncontrollable jerks and, at times, absence seizures (Koepp et al., 2013). Changes in EEG can be detected at sleep onset and awakenings, however some JME patients recordings show no detectable abnormalities (Serafini et al., 2013).
Functional magnetic resonance imaging (fMRI) studies showing an increase in frontal and parietal lobe excitability during cognitive or motor tasks suggest that the intense cognitive demand of such tasks may precipitate seizures in JME patients (Koepp et al., 2013). Moreover, quantitative MRI, which uses techniques such as VBM to identify small cortical and subcortical changes not detectable on conventional MRI (e.g., by tracking white and grey matter volumes) has identified grey matter abnormalities in the medial frontal region of JME patients. These anomalies indicate that changes in frontal lobe connectivity, especially in the supplementary motor area, might be responsible for seizure precipitation and seizure type in JME (Koepp et al., 2013). Together these findings suggest that JME may be a focal variant of a multi-regional thalamocortical epilepsy rather than a generalized form of epilepsy, highlighting how neuroimaging can challenge widely held assumptions about the neurophysiological processes underlying epilepsy syndromes.
Conclusion
The development of imaging modalities has led to important findings about epilepsies, seizures and epileptogenesis. Neuroimaging plays a crucial role in the diagnosis, evaluation and treatment of epilepsy, particularly in understanding the neurobiology and surgical outcomes of generalized epilepsies.
References
Koepp, M. J., Woermann, F., Savic, I., & Wandschneider, B. (2013). Juvenile myoclonic epilepsy — Neuroimaging findings. EPILEPSY & BEHAVIOR, 28, S40–S44. https://doi.org/10.1016/j.yebeh.2012.06.035
Serafini, A., Rubboli, G., Gigli, G. L., Koutroumanidis, M., & Gelisse, P. (2013). Neurophysiology of juvenile myoclonic epilepsy. Epilepsy & Behavior, 28, S30–S39. https://doi.org/10.1016/j.yebeh.2012.11.042
Sidhu, M. K., Duncan, J. S., & Sander, J. W. (2018). Neuroimaging in epilepsy. Current Opinion in Neurology, 31(4), 371–378. https://doi.org/10.1097/WCO.0000000000000568
