Frontal lobe hypometabolism associated with Sudden Unexpected Death in Epilepsy (SUDEP) risk: An objective PET study

Imaging biomarkers of sleep-related hypermotor epilepsy and sudden unexpected death in epilepsy: a review

In recent years, imaging has emerged as a promising source of several intriguing biomarkers in epilepsy, due to the impressive growth of imaging technology, supported by methodological advances and integrations of post-processing techniques. Bearing in mind the mutually influencing connection between sleep and epilepsy, we focused on sleep-related hypermotor epilepsy (SHE) and sudden unexpected death in epilepsy (SUDEP), aiming to make order and clarify possible clinical utility of emerging multimodal imaging biomarkers of these two epilepsy-related entities commonly occurring during sleep. Regarding SHE, advanced structural techniques might soon emerge as a promising source of diagnostic and predictive biomarkers, tailoring a targeted therapeutic (surgical) approach for MRI-negative subjects. Functional and metabolic imaging may instead unveil SHE's extensive and night-related altered brain networks, providing insights into distinctions and similarities with non-epileptic sleep phenomena, such as parasomnias. SUDEP is considered a storm that strikes without warning signals, but objective subtle structural and functional alterations in autonomic, cardiorespiratory, and arousal centers are present in patients eventually experiencing SUDEP. These alterations could be seen both as susceptibility and diagnostic biomarkers of the underlying pathological ongoing loop ultimately ending in death. Finally, given that SHE and SUDEP are rare phenomena, most evidence on the topic is derived from small single-center experiences with scarcely comparable results, hampering the possibility of performing any meta-analytic approach. Multicenter, longitudinal, well-designed studies are strongly encouraged.

Nuclear imaging for localization and surgical outcome prediction in epilepsy: A review of latest discoveries and future perspectives

Background

Epilepsy is one of the most common neurological disorders. Approximately, one-third of patients with epilepsy have seizures refractory to antiepileptic drugs and further require surgical removal of the epileptogenic region. In the last decade, there have been many recent developments in radiopharmaceuticals, novel image analysis techniques, and new software for an epileptogenic zone (EZ) localization.

Objectives

Recently, we provided the latest discoveries, current challenges, and future perspectives in the field of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) in epilepsy.

Methods

We searched for relevant articles published in MEDLINE and CENTRAL from July 2012 to July 2022. A systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis was conducted using the keywords "Epilepsy" and "PET or SPECT." We included both prospective and retrospective studies. Studies with preclinical subjects or not focusing on EZ localization or surgical outcome prediction using recently developed PET radiopharmaceuticals, novel image analysis techniques, and new software were excluded from the review. The remaining 162 articles were reviewed.

Results

We first present recent findings and developments in PET radiopharmaceuticals. Second, we present novel image analysis techniques and new software in the last decade for EZ localization. Finally, we summarize the overall findings and discuss future perspectives in the field of PET and SPECT in epilepsy.

Conclusion

Combining new radiopharmaceutical development, new indications, new techniques, and software improves EZ localization and provides a better understanding of epilepsy. These have proven not to only predict prognosis but also to improve the outcome of epilepsy surgery.

Toward automated prediction of sudden unexpected death in epilepsy

Sudden unexpected death in epilepsy (SUDEP) is a devastating yet overlooked complication of epilepsy. The rare and complex nature of SUDEP makes it challenging to study. No prediction or prevention of SUDEP is currently available in a clinical setting. In the past decade, significant advances have been made in our knowledge of the pathophysiologic cascades that lead to SUDEP. In particular, studies of brain, heart, and respiratory functions in both human patients at the epilepsy monitoring unit and animal models during fatal seizures provide critical information to integrate computational tools for SUDEP prediction. The rapid advances in automated seizure detection and prediction algorithms provide a fundamental framework for their adaption in predicting SUDEP. If a SUDEP can be predicted, then there will be a potential for medical intervention to be administered, either by their caregivers or via an implanted device automatically delivering electrical stimulation or medication, and finally save lives from fatal seizures. This article presents recent developments of SUDEP studies focusing on the pathophysiologic basis of SUDEP and computational implications of machine learning techniques that can be adapted and extended for SUDEP prediction. This article also discusses some novel ideas for SUDEP prediction and rescue including principal component analysis and closed-loop intervention.

Age-matched control or age-specific template, which is essential for voxel-wise analysis of cerebral metabolism abnormality in pediatric patients with epilepsy?

The aim of this study was to explore the influences of age-matched control and/or age-specific template on voxel-wise analysis of brain ¹⁸ F-fluorodeoxyglucose positron emission tomography (¹⁸ F-FDG PET) data in pediatric epilepsy patients. We, retrospectively, included 538 pediatric (196 females; age range of 12 months to 18 years) and 35 adult subjects (18 females; age range of 20-50 years) without any cerebral pathology as pediatric and adult control group, respectively, as well as 109 pediatric patients with drug-resistant epilepsy (38 females; age range of 13 months to 18 years) as epilepsy group. Statistical parametric mapping (SPM) analysis for ¹⁸ F-FDG PET data of each epilepsy patients was performed in four types of procedures, by using age-matched controls with age-specific template, age-matched controls with adult template, adult controls with age-specific template or adult controls with adult template. The numbers of brain regions affected by artifacts among these four types of SPM analysis procedures were further compared. Any template being adopted, the artifacts were significantly less in SPM analysis procedures using age-matched controls than those using adult controls in each age range (p < .001 in each comparison), except in the age range of 15-18 (p > .05 in each comparison). No significant difference was found in artifacts, when compared procedures using the identical control group with different templates (p = 1.000 in each comparison). In conclusion, the age stratification for age-matched control should be divided as many layers as possible for the SPM analysis of brain ¹⁸ F-FDG PET images, especially in pediatric patients ≤14-year-old, while age-specific template is not mandatory.

Raphe and ventrolateral medulla proteomics in epilepsy and sudden unexpected death in epilepsy

Brainstem nuclei dysfunction is implicated in sudden unexpected death in epilepsy. In animal models, deficient serotonergic activity is associated with seizure-induced respiratory arrest. In humans, glia are decreased in the ventrolateral medullary pre-Botzinger complex that modulate respiratory rhythm, as well as in the medial medullary raphe that modulate respiration and arousal. Finally, sudden unexpected death in epilepsy cases have decreased midbrain volume. To understand the potential role of brainstem nuclei in sudden unexpected death in epilepsy, we evaluated molecular signalling pathways using localized proteomics in microdissected midbrain dorsal raphe and medial medullary raphe serotonergic nuclei, as well as the ventrolateral medulla in brain tissue from epilepsy patients who died of sudden unexpected death in epilepsy and other causes in diverse epilepsy syndromes and non-epilepsy control cases (n = 15-16 cases per group/region). Compared with the dorsal raphe of non-epilepsy controls, we identified 89 proteins in non-sudden unexpected death in epilepsy and 219 proteins in sudden unexpected death in epilepsy that were differentially expressed. These proteins were associated with inhibition of EIF2 signalling (P-value of overlap = 1.29 × 10-8, z = -2.00) in non-sudden unexpected death in epilepsy. In sudden unexpected death in epilepsy, there were 10 activated pathways (top pathway: gluconeogenesis I, P-value of overlap = 3.02 × 10-6, z = 2.24) and 1 inhibited pathway (fatty acid beta-oxidation, P-value of overlap = 2.69 × 10-4, z = -2.00). Comparing sudden unexpected death in epilepsy and non-sudden unexpected death in epilepsy, 10 proteins were differentially expressed, but there were no associated signalling pathways. In both medullary regions, few proteins showed significant differences in pairwise comparisons. We identified altered proteins in the raphe and ventrolateral medulla of epilepsy patients, including some differentially expressed in sudden unexpected death in epilepsy cases. Altered signalling pathways in the dorsal raphe of sudden unexpected death in epilepsy indicate a shift in cellular energy production and activation of G-protein signalling, inflammatory response, stress response and neuronal migration/outgrowth. Future studies should assess the brain proteome in relation to additional clinical variables (e.g. recent tonic-clonic seizures) and in more of the reciprocally connected cortical and subcortical regions to better understand the pathophysiology of epilepsy and sudden unexpected death in epilepsy.

Common ictal and interictal perfusion patterns. A window into the epileptogenic network and SUDEP mechanism in Drug Resistant Focal Epilepsy?

BACKGROUND

Focal epilepsies have been described as network disease. Noninvasive investigative techniques have been used to characterize epileptogenic networks.

OBJETIVE

To describe ictal and interictal cortical and subcortical perfusion patterns using single photon emission computed tomography (SPECT), in patients with drug-resistant epilepsy (DRE).

METHODS

Thirty-five interictal- ictal SPECT scans were obtained from 15 patients with DRE. A methodology was developed to get a relative perfusion index (PI) of 74 cortical and sub-cortical brain structures. K-means algorithm together with a modified v-fold cross-validation were used to identify the two regions of interest (ROI's) that represent hypoperfused and hyperperfused areas.

RESULTS

In common with the individual analysis, the statistical analysis evidenced that the hyperperfusion ROIs resulting from group analysis during interictal, and ictal involved mainly the cingulate gyrus, cuneus, the lingual gyrus, gyrus rectus as well as the putamen. ROIs hypoperfused included the red nucleus, the substantia nigra, and the medulla. The medians of the group analysis of the hypoperfusion and hyperperfusion ROIs were 0.601-0.565 and 1,133 - 1,119 for the ictal and interictal states, correspondingly. A group of mostly cortical structures involved in the hyperperfused ROIs in both interictal and ictal states showed no change or negative change in the transition from interictal to ictal state (mean change of -0.002). On the other hand, the brain stem, basal ganglia, red nucleus, and thalamus revealed a mean global change of 0.19, indicating a mild increase in the PI. However, some of these structures (red nucleus, substantia nigra, and medulla oblongata) remained hypoperfused during the interictal to ictal transition.

CONCLUSION

The methodology employed made it possible to identify common cortical and subcortical perfusion patterns not directly linked to epileptogenicity, but open a window for the epileptogenic network and sudden unexpected death (SUDEP) mechanism in DRE .

The role of monoaminergic neurons in modulating respiration during sleep and the connection with SUDEP

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of death among epilepsy patients, occurring even more frequently in cases with anti-epileptic drug resistance. Despite some advancements in characterizing SUDEP, the underlying mechanism remains incompletely understood. This review summarizes the latest advances in our understanding of the pathogenic mechanisms of SUDEP, in order to identify possible targets for the development of new strategies to prevent SUDEP. Based on our previous research along with the current literature, we focus on the role of sleep-disordered breathing (SDB) and its related neural mechanisms to consider the possible roles of monoaminergic neurons in the modulation of respiration during sleep and the occurrence of SUDEP. Overall, this review suggests that targeting the monoaminergic neurons is a promising approach to preventing SUDEP. The proposed roles of SDB and related monoaminergic neural mechanisms in SUDEP provide new insights for explaining the pathogenesis of SUDEP.

Advanced neuroimaging techniques in epilepsy

PURPOSE OF REVIEW

We review significant advances in epilepsy imaging in recent years.

RECENT FINDINGS

Structural MRI at 7T with optimization of acquisition and postacquisition image processing increases the diagnostic yield but artefactual findings remain a challenge. MRI analysis from multiple sites indicates different atrophy patterns and white matter diffusion abnormalities in temporal lobe and generalized epilepsies, with greater abnormalities close to the presumed seizure source. Structural and functional connectivity relate to seizure spread and generalization; longitudinal studies are needed to clarify the causal relationship of these associations. Diffusion MRI may help predict surgical outcome and network abnormalities extending beyond the epileptogenic zone. Three-dimensional multimodal imaging can increase the precision of epilepsy surgery, improve seizure outcome and reduce complications. Language and memory fMRI are useful predictors of postoperative deficits, and lead to risk minimization. FDG PET is useful for clinical studies and specific ligands probe the pathophysiology of neurochemical fluxes and receptor abnormalities.

SUMMARY

Improved structural MRI increases detection of abnormalities that may underlie epilepsy. Diffusion, structural and functional MRI indicate the widespread associations of epilepsy syndromes. These can assist stratification of surgical outcome and minimize risk. PET has continued utility clinically and for research into the pathophysiology of epilepsies.

Interictal 18F-FDG brain PET metabolism in patients with postictal EEG suppression

OBJECTIVE

Postictal generalized suppression (PGES) may be associated with SUDEP risk. We aimed to study metabolic changes on ¹⁸Fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET) in patients with focal to bilateral (generalized) seizures (GTCS) and PGES on stereoelectroencephalography (SEEG).

METHODS

We analyzed interictal brain metabolism in a group of 19 patients with widespread postictal suppression (PGES+) associated with SEEG-recorded GTCS. This group was compared to 25 patients without widespread suppression (PGES-) as defined by SEEG, matched for epilepsy localization and lateralization. Frequency of GTCS was observed to be higher in the PGES+ group (high risk group for SUDEP). Analysis of metabolic data was performed by statistical parametric mapping (SPM) on the whole-brain, and principal component analysis (PCA) on AAL (automated anatomical labeling) atlas.

RESULTS

Statistical parametric mapping showed right temporal pole hypometabolism in the PGES+ group (T-score = 3.90; p < 0.001; k = 185), in comparison to the PGES- group. Principal component analysis showed association between the metabolic values of certain regions of interest and PGES+/PGES- groups, confirmed by a significant difference (p < 0.05) in the values of the right dorsal temporal pole and of the left temporal pole between the two groups. Principal component analysis showed two dimensions significantly related to the PGES+/PGES- partition, involving the following regions: right temporal pole, right parahippocampal gyrus, right Rolandic operculum, bilateral paracentral lobule, right precuneus, right thalamus, right caudate and pallidum, bilateral cerebellum, left temporal pole, left Heschl's gyrus, left calcarine region, and left caudate, with loss of connection in PGES+ patients. Metabolic differences were independent of epilepsy localization and lateralization and persisted after correction for GTCS frequency.

SIGNIFICANCE

Interictal metabolic changes within a predominantly right-sided network involving temporal lobe and connected cortical and subcortical structures were seen in patients with frequent GTCS presenting widespread postictal suppression.