Simon J. Vogrin

Stereo-EEG-guided radiofrequency thermocoagulation (RFTHC) has been proposed as relatively safe from a cognitive perspective; however, there is a lack of evidence based on neuropsychological assessments supporting this. This study is the first prospective evaluation of neuropsychological outcomes associated with stereo-EEG-guided RFTHC in patients with focal drug-resistant epilepsy. This cohort study involved prospective recruitment of consecutive patients undergoing stereo-EEG from 2 Australian centers. A comprehensive neuropsychological assessment was administered before implantation and 3 months after RFTHC (M = 104.51 days, SD = 29.25). Outcomes across cognitive domains were assessed at a group level with repeated measures t tests. Factorial repeated measures analyses of variance compared memory and language outcomes according to whether dominant mesial temporal lobe (mTL) structures were coagulated. Reliable change indices (RCIs) were computed to explore psychometrically reliable changes at an individual level. The sample comprised 39 patients who underwent stereo-EEG (M = 37.08 ± 9.67 years, range = 17-56 years, 54% female). Nineteen (49%) had a language dominant epileptogenic zone (EZ), 16 (41%) a nondominant EZ, and 4 (10%) a bilateral EZ. All patients underwent RFTHC with a mean of 11.87 (SD = 6.82, range = 2-29) coagulation sites. Ten patients (26%) had RFTHC within the dominant mTL. At a group level, RFTHC was not associated with a significant decline on any neuropsychological measures (all comparisons p > 0.05). Subgroup analyses revealed a decline in delayed verbal recall after RFTHC of dominant mTL structures (F(1,37) = 4.46, p = 0.04, η_p² = 0.11, 95% CI [0-0.30]; medium to large effect), although it did not remain statistically significant after correction for false discovery rate. No statistically significant group differences were observed on visual memory or language measures post-RFTHC (all comparisons p > 0.05). RCI revealed that after RFTHC within the dominant mTL, 20% of patients experienced a decline in verbal memory and 10% in visual memory. By contrast, 7% declined in verbal memory and 10% in visual memory post-RFTHC outside the dominant mTL. While these findings support the current view that RFTHC is cognitively benign for most cases, the results raise the question of a verbal memory decline after coagulation of the dominant mTL. Individualized neuropsychological counseling before stereo-EEG is essential to avoid unanticipated deficits.

Background: Alzheimer’s disease (AD) can be challenging to diagnose early as cognitive changes are mild. Neuropsychological assessment, in contrast to cognitive screening or isolated cognitive tests, are more sensitive to the mild cognitive changes in early AD. Magnetic resonance imaging (MRI) can detect early structural brain changes in AD, particularly entorhinal cortex, transentorhinal cortex, and hippocampal atrophy. Combining neuropsychological assessment with MRI examination may yield improved ability to detect early AD. The current study examined combining neuropsychological and MRI measures to detect patients with mild cognitive impairment (MCI) in a memory clinic sample.Method: Neuropsychological assessment and entorhinal cortex, transentorhinal cortex, and hippocampal volume measurement were conducted in memory clinic patients, including 38 with memory symptoms, 16 with MCI, and 16 with dementia due to AD, and in 40 healthy controls. Backward stepwise multinomial logistic regression was used to compare the neuropsychological measures and MRI measures.Result: Among the neuropsychological measures, memory and processing speed were the most important measures that contributed to group membership prediction. All MRI measures contributed to group membership prediction. The neuropsychological measures were more accurate than the MRI measures at detecting patients with MCI. Combining the MRI measures with the neuropsychological measures did not improve group membership prediction.Conclusion: Neuropsychological assessment is an important tool to support MCI diagnosis. MRI measures contribute little diagnostic value over and above neuropsychological assessment. Further advancement in deriving MRI‐based measurements is required to achieve clinical utility.

Objective. Magnetoencephalography (MEG) is a powerful non-invasive diagnostic modality for presurgical epilepsy evaluation. However, the clinical utility of MEG mapping for localising epileptic foci is limited by its low efficiency, high labour requirements, and considerable interoperator variability. To address these obstacles, we proposed a novel artificial intelligence–based automated magnetic source imaging (AMSI) pipeline for automated detection and localisation of epileptic sources from MEG data. Approach. To expedite the analysis of clinical MEG data from patients with epilepsy and reduce human bias, we developed an autolabelling method, a deep-learning model based on convolutional neural networks and a hierarchical clustering method based on a perceptual hash algorithm, to enable the coregistration of MEG and magnetic resonance imaging, the detection and clustering of epileptic activity, and the localisation of epileptic sources in a highly automated manner. We tested the capability of the AMSI pipeline by assessing MEG data from 48 epilepsy patients. Main results. The AMSI pipeline was able to rapidly detect interictal epileptiform discharges with 93.31% ± 3.87% precision based on a 35-patient dataset (with sevenfold patientwise cross-validation) and robustly rendered accurate localisation of epileptic activity with a lobar concordance of 87.18% against interictal and ictal stereo-electroencephalography findings in a 13-patient dataset. We also showed that the AMSI pipeline accomplishes the necessary processes and delivers objective results within a much shorter time frame (∼12 min) than traditional manual processes (∼4 h). Significance. The AMSI pipeline promises to facilitate increased utilisation of MEG data in the clinical analysis of patients with epilepsy.

Drug-resistant focal epilepsy is a major clinical problem and surgery is under-used. Better non-invasive techniques for epileptogenic zone localization are needed when MRI shows no lesion or an extensive lesion. The problem is interictal and ictal localization before propagation from the epileptogenic zone. High-density EEG (HDEEG) and magnetoencephalography (MEG) offer millisecond-order temporal resolution to address this but co-acquisition is challenging, ictal MEG studies are rare, long-term prospective studies are lacking, and fundamental questions remain. Should HDEEG-MEG discharges be assessed independently [electroencephalographic source localization (ESL), magnetoencephalographic source localization (MSL)] or combined (EMSL) for source localization? Which phase of the discharge best characterizes the epileptogenic zone (defined by intracranial EEG and surgical resection relative to outcome)? Does this differ for interictal and ictal discharges? Does MEG detect mesial temporal lobe discharges? Thirteen patients (10 non-lesional, three extensive-lesional) underwent synchronized HDEEG-MEG (72–94 channel EEG, 306-sensor MEG). Source localization (standardized low-resolution tomographic analysis with MRI patient-individualized boundary-element method) was applied to averaged interictal epileptiform discharges (IED) and ictal discharges at three phases: ‘early-phase’ (first latency 90% explained variance), ‘mid-phase’ (first of 50% rising-phase, 50% mean global field power), ‘late-phase’ (negative peak). ‘Earliest-solution’ was the first of the three early-phase solutions (ESL, MSL, EMSL). Prospective follow-up was 3–21 (median 12) months before surgery, 14–39 (median 21) months after surgery. IEDs (n = 1474) were recorded, seen in: HDEEG only, 626 (42%); MEG only, 232 (16%); and both 616 (42%). Thirty-three seizures were captured, seen in: HDEEG only, seven (21%); MEG only, one (3%); and both 25 (76%). Intracranial EEG was done in nine patients. Engel scores were I (9/13, 69%), II (2/13,15%), and III (2/13). MEG detected baso-mesial temporal lobe epileptogenic zone sources. Epileptogenic zone OR [odds ratio(s)] were significantly higher for earliest-solution versus early-phase IED-surgical resection and earliest-solution versus all mid-phase and late-phase solutions. ESL outperformed EMSL for ictal-surgical resection [OR 3.54, 95% confidence interval (CI) 1.09–11.55, P = 0.036]. MSL outperformed EMSL for IED-intracranial EEG (OR 4.67, 95% CI 1.19–18.34, P = 0.027). ESL outperformed MSL for ictal-surgical resection (OR 3.73, 95% CI 1.16–12.03, P = 0.028) but was outperformed by MSL for IED-intracranial EEG (OR 0.18, 95% CI 0.05–0.73, P = 0.017). Thus, (i) HDEEG and MEG source solutions more accurately localize the epileptogenic zone at the earliest resolvable phase of interictal and ictal discharges, not mid-phase (as is common practice) or late peak-phase (when signal-to-noise ratios are maximal); (ii) from empirical observation of the differential timing of HDEEG and MEG discharges and based on the superiority of ESL plus MSL over either modality alone and over EMSL, concurrent HDEEG-MEG signals should be assessed independently, not combined; (iii) baso-mesial temporal lobe sources are detectable by MEG; and (iv) MEG is not ‘more accurate’ than HDEEG—emphasis is best placed on the earliest signal (whether HDEEG or MEG) amenable to source localization. Our findings challenge current practice and our reliance on invasive monitoring in these patients.

Summary: According to the International League Against Epilepsy (ILAE) definition, no structural abnormalities are present on a standard brain magnetic resonance image in genetic generalized epilepsy (GGE) patients. However, recent studies raise contradictory evidence with increasing use of quantitative magnetic resonance imaging techniques. FollowingPRISMAguidelines, a systematic, quantitative review was conducted using 28 peer‐reviewed, case–control studies published after 1989. Furthermore, a meta‐analysis with a random‐effect model revealed differences in structural brain abnormalities betweenGGEpatients and controls. Significant structural differences betweenGGEand healthy controls were observed with volume reductions in whole brain, thalamus, putamen, caudate, pallidum, and supplementary motor area. Furthermore, gray matter volume reduction in the right and left hemispheres, thalamus, and insula, and surface area reduction in the caudal anterior cingulate cortex were revealed, along with gray matter increase in the medial frontal gyrus. Due to methodological differences, findings should be interpreted with caution. Nevertheless, contrary to theILAEdefinition, it would appear that structural brain abnormalities may be present inGGEpatients. Findings are consistent with a hypothesis regarding the underlying involvement of the thalamocortical networks in the generation of generalized spike‐wave discharges, but structural abnormalities appear to extend outside these regions to potentially involve attention and other cognitive domains.

Summary: We previously observed that adults with Lennox‐Gastaut syndrome (LGS) show abnormal functional connectivity among cognitive networks, suggesting that this may contribute to impaired cognition. Herein we report network reorganization following seizure remission in a child with LGS who underwent functional magnetic resonance imaging (fMRI) before and after resection of a cortical dysplasia. Concurrent electroencephalography (EEG) was acquired during presurgical fMRI. Presurgical and postsurgical functional connectivity were compared using (1) graph theoretical analyses of small‐world network organization and node‐wise strength; and (2) seed‐based analyses of connectivity within and between five functional networks. To explore the specificity of these postsurgical network changes, connectivity was further compared to nine children with LGS who did not undergo surgery. The presurgical EEG‐fMRI revealed diffuse activation of association cortex during interictal discharges. Following surgery and seizure control, functional connectivity showed increased small‐world organization, stronger connectivity in subcortical structures, and greater within‐network integration/between‐network segregation. These changes suggest network improvement, and diverged sharply from the comparison group of nonoperated children. Following surgery, this child with LGS achieved seizure control and showed extensive reorganization of networks that underpin cognition. This case illustrates that the epileptic process of LGS can directly contribute to abnormal network organization, and that this network disruption may be reversible.