Metabolic evidence for episodic memory plasticity in the nonepileptic temporal lobe of patients with mesial temporal epilepsy

Patterns of hypometabolism in frontal lobe epilepsy originating in different frontal regions

Objectives

Analysis of FDG‐PET imaging commonly shows that hypometabolism extends into extra‐epileptogenic zones (extra‐EZ). This study investigates the distribution patterns of hypometabolism in frontal lobe epilepsy (FLE) originating in different frontal regions.

Methods

Sixty‐four patients with FLE were grouped by EZ localization according to Brodmann areas (BAs): Group 1 (the frontal motor and premotor area), BAs 4, 6, and 8; Group 2 (the inferior frontal gyrus and opercular area), BAs 44, 45, and 47; Group 3 (the dorsal prefrontal area), BAs 9, 10, 11, and 46; and Group 4 (the medial frontal and anterior cingulate gyrus), BAs 32 and 24. Regions of extra‐EZ hypometabolism were statistically analyzed between FLE groups and healthy controls. Correlation analysis was performed to identify relationships between the intensity of hypometabolism and clinical characteristics.

Results

Significant hypometabolism in the ipsilateral (Groups 1 and 4) or bilateral (Groups 2 and 3) anterior insulae was found. Groups 1 and 4 presented with limited distribution of extra‐EZ hypometabolism, whereas Groups 2 and 3 showed widely distributed extra‐EZ hypometabolism in the rectus gyrus, cingulate gyrus, and other regions. Additionally, the intensity of hypometabolism was correlated with epilepsy duration in Groups 2 and 3.

Conclusions

All FLE groups showed hypometabolism in the anterior insula. In addition, distinct patterns of extra‐EZ hypometabolism were identified for each FLE group. This quantitative FDG‐PET analysis expanded our understanding of the topography of epileptic networks and can guide EZ localization in the future.

Characterizing the hyper- and hypometabolism in temporal lobe epilepsy using multivariate machine learning

Mesial temporal lobe epilepsy (MTLE) is the most common type of focal epilepsy, presenting both structural and metabolic abnormalities in the ipsilateral mesial temporal lobe. While it has been demonstrated that the metabolic abnormalities in MTLE actually extend beyond the epileptogenic zone, how such multidimensional information is associated with the diagnosis of MTLE remains to be tested. Here, we explore the whole-brain metabolic patterns in 23 patients with MTLE and 24 healthy controls using [¹⁸ F]fluorodeoxyglucose PET imaging. Based on a multivariate machine learning approach, we demonstrate that the brain metabolic patterns can discriminate patients with MTLE from controls with a superior accuracy (>95%). Importantly, voxels showing the most extreme contributing weights to the classification (i.e., the most important regional predictors) distribute across both hemispheres, involving both ipsilateral negative weights over the anterior part of lateral and medial temporal lobe, posterior insula, and lateral orbital frontal gyrus, and contralateral positive weights over the anterior frontal lobe, temporal lobe, and lingual gyrus. Through region-of-interest analyses, we verify that in patients with MTLE, the negatively weighted regions are hypometabolic, and the positively weighted regions are hypermetabolic, compared to controls. Interestingly, despite that both hypo- and hypermetabolism have mutually contributed to our model, they may reflect different pathological and/or compensative responses. For instance, patients with earlier age at epilepsy onset present greater hypometabolism in the ipsilateral inferior temporal gyrus, while we find no evidence of such association with hypermetabolism. In summary, quantitative models utilizing multidimensional brain metabolic information may provide additional assistance to presurgical workups in TLE.

Structural and metabolic brain abnormalities in COVID-19 patients with sudden loss of smell

OBJECTIVES

Sudden loss of smell is a very common symptom of coronavirus disease 19 (COVID-19). This study characterizes the structural and metabolic cerebral correlates of dysosmia in patients with COVID-19.

METHODS

Structural brain magnetic resonance imaging (MRI) and positron emission tomography with [18F]-fluorodeoxyglucose (FDG-PET) were prospectively acquired simultaneously on a hybrid PET-MR in 12 patients (2 males, 10 females, mean age: 42.6 years, age range: 23-60 years) with sudden dysosmia and positive detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on nasopharyngeal swab specimens. FDG-PET data were analyzed using a voxel-based approach and compared with that of a group of healthy subjects.

RESULTS

Bilateral blocking of the olfactory cleft was observed in six patients, while subtle olfactory bulb asymmetry was found in three patients. No MRI signal abnormality downstream of the olfactory tract was observed. Decrease or increase in glucose metabolism abnormalities was observed (p < .001 uncorrected, k ≥ 50 voxels) in core olfactory and high-order neocortical areas. A modulation of regional cerebral glucose metabolism by the severity and the duration of COVID-19-related dysosmia was disclosed using correlation analyses.

CONCLUSIONS

This PET-MR study suggests that sudden loss of smell in COVID-19 is not related to central involvement due to SARS-CoV-2 neuroinvasiveness. Loss of smell is associated with subtle cerebral metabolic changes in core olfactory and high-order cortical areas likely related to combined processes of deafferentation and active functional reorganization secondary to the lack of olfactory stimulation.

Alterations in resting-state network dynamics along the Alzheimer's disease continuum

Human brain activity is intrinsically organized into resting-state networks (RSNs) that transiently activate or deactivate at the sub-second timescale. Few neuroimaging studies have addressed how Alzheimer's disease (AD) affects these fast temporal brain dynamics, and how they relate to the cognitive, structural and metabolic abnormalities characterizing AD. We aimed at closing this gap by investigating both brain structure and function using magnetoencephalography (MEG) and hybrid positron emission tomography-magnetic resonance (PET/MR) in 10 healthy elders, 10 patients with subjective cognitive decline (SCD), 10 patients with amnestic mild cognitive impairment (aMCI) and 10 patients with typical Alzheimer's disease with dementia (AD). The fast activation/deactivation state dynamics of RSNs were assessed using hidden Markov modeling (HMM) of power envelope fluctuations at rest measured with MEG. Correlations were sought between temporal properties of HMM states and participants' cognitive test scores, whole hippocampal grey matter volume and regional brain glucose metabolism. The posterior default-mode network (DMN) was less often activated and for shorter durations in AD patients than matched healthy elders. No significant difference was found in patients with SCD or aMCI. The time spent by participants in the activated posterior DMN state did not correlate significantly with cognitive scores, nor with the whole hippocampal volume. However, it correlated positively with the regional glucose consumption in the right dorsolateral prefrontal cortex (DLPFC). AD patients present alterations of posterior DMN power activation dynamics at rest that identify an additional electrophysiological correlate of AD-related synaptic and neural dysfunction. The right DLPFC may play a causal role in the activation of the posterior DMN, possibly linked to the occurrence of mind wandering episodes. As such, these data might suggest a neural correlate of the decrease in mind wandering episodes reported in pathological aging.

Metabolic covariance networks combining graph theory measuring aberrant topological patterns in mesial temporal lobe epilepsy

OBJECTIVE

We aimed to study the networks' mechanism of metabolic covariance networks in mesial temporal lobe epilepsy (mTLE), through examining the brain value of fluorine-18-fluorodeoxyglucose positron emission tomography (18 F-FDG-PET).

METHODS

18 F-FDG-PET images from 16 patients with mTLE were analyzed using local and global metabolic covariance network (MCN) approaches, including whole metabolic pattern analysis (WMPA), hippocampus-based (h-) MCN, whole brain (w-) MCN, and edge-based connectivity analysis (EBCA).

RESULTS

WMPA showed a typical ipsilateral hypometabolism and contralateral hypermetabolism pattern to epileptic zones in mTLE. h-MCN revealed decreased hippocampus-based synchronization in contralateral regions. w-MCN exhibited a disrupted metabolic network with globally increased small-world properties and regionally decreased nodal metrics in the ipsilateral hemisphere. Hippocampus (h)-EBCA and whole brain EBCA (w-EBCA) both detected a reduced-connectivity dominated metabolic covariant network. Moreover, the reduced interhemisphere connectivity seemingly played a major role in the aberrant epileptic topological pattern.

CONCLUSION

From a metabolic point of view, we demonstrated the damaging effects with reduced contralateral intranetwork metrics properties and the compensatory effects in contralateral intranetworks with increased network properties. However, the import role of significant reduced interhemisphere connection has rarely been reported in other mTLE studies. Taken together, 18 F-FDG-PET MCN analysis provides new evidence that the mTLE is a system neurological disorder with disrupted networks.

Anatomy Based Networks and Topology Alteration in Seizure-Related Cognitive Outcomes

Epilepsy is a paroxysmal neurological disorder characterized by recurrent and unprovoked seizures affecting approximately 50 million people worldwide. Cognitive dysfunction induced by seizures is a severe comorbidity of epilepsy and epilepsy syndromes and reduces patients’ quality of life. Seizures, along with accompanying histopathological and pathophysiological changes, are associated with cognitive comorbidities. Advances in imaging technology and computing allow anatomical and topological changes in neural networks to be visualized. Anatomical components including the hippocampus, amygdala, cortex, corpus callosum (CC), cerebellum and white matter (WM) are the fundamental components of seizure- and cognition-related topological networks. Damage to these structures and their substructures results in worsening of epilepsy symptoms and cognitive dysfunction. In this review article, we survey structural, network changes and topological alteration in different regions of the brain and in different epilepsy and epileptic syndromes, and discuss what these changes may mean for cognitive outcomes related to these disease states.

Mismatch negativity is abnormal but not lateralizing in temporal lobe epilepsy

We investigated the changes of mismatch negativity (MMN) in patients with temporal lobe epilepsy (TLE) and explored the possible role of MMN in lateralizing their seizure focus. Thirty patients with TLE and thirty healthy controls were included. MMN was elicited in each subject. Patients with TLE were divided into three subgroups: unilateral left TLE; unilateral right TLE, and bilateral TLE. MMN amplitudes and latencies were compared between the patients with TLE and the control group, and also among the three subgroups of TLE, using repeated measures analyses of variance (ANOVA). To assess the lateralizing value of MMN, MMN latencies and amplitudes at the mastoid sites between the ipsilateral and contralateral sides of epileptic focus in patients with unilateral TLE were compared using t-test. Compared with controls, each subgroup of patients with TLE had longer latencies of MMN at both fronto-central and mastoid sites, but the amplitudes of MMN were not significantly different. The amplitudes and latencies of MMN were not significantly different between the ipsilateral and contralateral sides of seizure focus at mastoid sites. The present findings of prolonged latencies of MMN are suggestive of cognitive impairment in TLE. Both the mastoid sites and the fronto-central sites are involved, which likely reflect widespread cortical abnormalities in TLE. However, the changes of MMN during the interictal phase are not useful for lateralizing the seizure focus in patients with TLE.

Increased MRI volumetric correlation contralateral to seizure focus in temporal lobe epilepsy

Quantification of volumetric correlation may be sensitive to disease alterations undetected by standard voxel based morphometry (VBM) such as subtle, synchronous alterations in regional volumes, and may provide complementary evidence of the structural impact of temporal lobe epilepsy (TLE) on the brain. The purpose of this study was to quantify differences of regional volumetric correlation in right (RTLE) and left (LTLE) TLE patients compared to healthy controls. A T1 weighted 3T MRI was acquired (1mm(3)) in 44 drug resistant unilateral TLE patients (n=26 RTLE, n=18 LTLE) and 44 individually age and gender matched healthy controls. Images were processed using a standard VBM framework and volumetric correlation was calculated across subjects in 90 regions and compared between patients and controls. Results were summarized across hemispheres and region groups. There was increased correlation involving the contralateral homologues of the seizure foci/network in the limbic, subcortical and temporal regions in both RTLE and LTLE. Outside these regions, results implied widespread correlated alterations across several contralateral lobes in LTLE, with more focal changes in RTLE. These findings complement previous volumetric studies in TLE describing more ipsilateral atrophy, by revealing subtle coordinated volumetric changes to identify a more widespread effect of TLE across the brain.

Limbic networks: clinical perspective

Limbic epilepsy refers to a condition that consists of epileptic seizures that originate in or preferentially involve the limbic system. The majority of cases are medically refractory, necessitating surgical resection when possible. However, even resection of structures thought to be responsible for seizure generation may not leave a patient seizure free. While mesial temporal lobe limbic structures are centrally involved, there is growing evidence that the epileptogenic network consists of a broader area, involving structures outside of the temporal lobe and the limbic system. Information on structural, functional, and metabolic connectivity in patients with limbic epilepsy is available from a large body of studies employing methods such as MRI, EEG, MEG, fMRI, PET, and SPECT scanning, implicating the involvement of various brain regions in the epileptogenic network. To date, there are no consistent and conclusive findings to define the exact boundaries of this network, but it is possible that in the future studies of network connectivity in the individual patient may allow more tailored treatment and prognosis in terms of surgical resection.

Changes in functional integration with the non-epileptic temporal lobe of patients with unilateral mesiotemporal epilepsy

Purpose

To investigate epilepsy-induced changes in effective connectivity between the non-epileptic amygdalo-hippocampal complex (AHC) and the rest of the brain in patients with unilateral mesiotemporal lobe epilepsy (MTLE) associated with hippocampal sclerosis (HS).

Methods

Thirty-three patients with unilateral MTLE associated with HS (20 females, mean age: 36 years, 19 left HS) and 33 adult controls matched for age and gender underwent ¹⁸F-Fluorodeoxyglucose positron emission tomography (FDG-PET). Right-HS patients' FDG-PET data were flipped to obtain a left–epileptic–focus–lateralized group of patients. Voxels of interest (VOI) were selected within the cytoarchitectonic probabilistic maps of the non-epileptic AHC (probability level  = 100%, SPM8 Anatomy toolbox v1.7). Patients and controls were compared using VOI metabolic activity as covariate of interest to search for epilepsy-induced changes in the contribution of the non-epileptic AHC to the level of metabolic activity in other brain areas. Age, gender, duration of epilepsy, seizure type and frequency were used as covariates of no-interest for connectivity analyses.

Key findings

Significant decrease in effective connectivity was found between the non-epileptic AHC and ventral prefrontal cortical areas bilaterally, as well as with the temporal pole and the posterior cingulate cortex contralateral to HS. Significant increase in connectivity was found between the non-epileptic AHC and midline structures, such as the anterior cingulate and dorsal medial prefrontal cortices, as well as the temporo-parietal junction bilaterally. Connectivity analyses also revealed a preserved positive connectivity between the non-epileptic and the epileptic AHC in the patients' group.

Significance

This study evidences epilepsy-induced changes in connectivity between the non-epileptic AHC and some limbic and default mode network areas. These changes in connectivity probably account for emotional, cognitive and decision-making impairments frequently observed in MTLE patients. The preserved neurometabolic connectivity between the non-epileptic and the epileptic AHC in MTLE patients is pivotal to explain the epilepsy-induced changes found in this study.

Resting state functional connectivity of the hippocampus associated with neurocognitive function in left temporal lobe epilepsy

The majority of patients with temporal lobe epilepsy (TLE) experience disturbances of episodic memory from structural damage or dysfunction of the hippocampus. The objective of this study was to use functional Magnetic Resonance Imaging (fMRI) to identify regions where resting state connectivity to the left hippocampus (LH) is correlated with neuropsychological measures of verbal memory retention in TLE patients. Eleven left TLE (LTLE) patients and 15 control subjects participated in resting state fMRI scans. All LTLE patients underwent neuropsychological testing. Resting state functional connectivity maps to the LH were calculated for each patient, and subsequently used in a multiple regression analysis with verbal memory retention scores as a covariate. The analysis identified brain regions whose connectivity to the LH was linearly related to memory retention scores across the group of patients. In LTLE patients, right sided (contralateral) clusters in the precuneus and inferior parietal lobule (IPL) exhibited increased connectivity to the LH with increased memory retention score; left sided (ipsilateral) regions in the precuneus and IPL showed increased connectivity to the LH with decreased retention score. Patients with high memory retention scores had greater connectivity between the LH-right parietal clusters than between the LH-left parietal clusters; in contrast, control subjects had significantly and consistently greater LH-left hemisphere than LH-right hemisphere connectivity. Our results suggest that increased connectivity in contralateral hippocampal functional pathways within the episodic verbal memory network represents a strengthening of alternative pathways in LTLE patients with strong verbal memory retention abilities.