Automated segmentation of epilepsy surgical resection cavities: Comparison of four methods to manual segmentation.

Accurate resection cavity segmentation on MRI is important for neuroimaging research involving epilepsy surgical outcomes. Manual segmentation, the gold standard, is highly labour intensive. Automated pipelines are an efficient potential solution; however, most have been developed for use following temporal epilepsy surgery. Our aim was to compare the accuracy of four automated segmentation pipelines following surgical resection in a mixed cohort of subjects following temporal or extra temporal epilepsy surgery. We identified 4 open-source automated segmentation pipelines. Epic-CHOP and ResectVol utilise SPM-12 within MATLAB, while Resseg and Deep Resection utilise 3D U-net convolutional neural networks. We manually segmented the resection cavity of 50 consecutive subjects who underwent epilepsy surgery (30 temporal, 20 extratemporal). We calculated Dice similarity coefficient (DSC) for each algorithm compared to the manual segmentation. No algorithm identified all resection cavities. ResectVol (n = 44, 88 %) and Epic-CHOP (n = 42, 84 %) were able to detect more resection cavities than Resseg (n = 22, 44 %, P < 0.001) and Deep Resection (n = 23, 46 %, P < 0.001). The SPM-based pipelines (Epic-CHOP and ResectVol) performed better than the deep learning-based pipelines in the overall and extratemporal surgery cohorts. In the temporal cohort, the SPM-based pipelines had higher detection rates, however there was no difference in the accuracy between methods. These pipelines could be applied to machine learning studies of outcome prediction to improve efficiency in pre-processing data, however human quality control is still required.

Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA-Epilepsy study.

OBJECTIVE: The intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current corticocentric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural magnetic resonance imaging in 1602 adults with epilepsy and 1022 healthy controls across 22 sites from the global ENIGMA-Epilepsy working group. METHODS: A state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions. Linear mixed models compared total and regional cerebellar volume in (1) all epilepsies, (2) temporal lobe epilepsy with hippocampal sclerosis (TLE-HS), (3) nonlesional temporal lobe epilepsy, (4) genetic generalized epilepsy, and (5) extratemporal focal epilepsy (ETLE). Relationships were examined for cerebellar volume versus age at seizure onset, duration of epilepsy, phenytoin treatment, and cerebral cortical thickness. RESULTS: Across all epilepsies, reduced total cerebellar volume was observed (d = .42). Maximum volume loss was observed in the corpus medullare (dmax = .49) and posterior lobe gray matter regions, including bilateral lobules VIIB (dmax = .47), crus I/II (dmax = .39), VIIIA (dmax = .45), and VIIIB (dmax = .40). Earlier age at seizure onset ( η ρ max 2 = .05) and longer epilepsy duration ( η ρ max 2 = .06) correlated with reduced volume in these regions. Findings were most pronounced in TLE-HS and ETLE, with distinct neuroanatomical profiles observed in the posterior lobe. Phenytoin treatment was associated with reduced posterior lobe volume. Cerebellum volume correlated with cerebral cortical thinning more strongly in the epilepsy cohort than in controls. SIGNIFICANCE: We provide robust evidence of deep cerebellar and posterior lobe subregional gray matter volume loss in patients with chronic epilepsy. Volume loss was maximal for posterior subregions implicated in nonmotor functions, relative to motor regions of both the anterior and posterior lobe. Associations between cerebral and cerebellar changes, and variability of neuroanatomical profiles across epilepsy syndromes argue for more precise incorporation of cerebellar subregional damage into neurobiological models of epilepsy.

Automated Methods for Detecting and Quantitation of Enlarged Perivascular spaces on MRI.

The brain's glymphatic system is a network of intracerebral vessels that function to remove "waste products" such as degraded proteins from the brain. It comprises of the vasculature, perivascular spaces (PVS), and astrocytes. Poor glymphatic function has been implicated in numerous diseases; however, its contribution is still unknown. Efforts have been made to image the glymphatic system to further assess its role in the pathogenesis of different diseases. Numerous imaging modalities have been utilized including two-photon microscopy and contrast-enhanced magnetic resonance imaging (MRI). However, these are associated with limitations for clinical use. PVS form a part of the glymphatic system and can be visualized on standard MRI sequences when enlarged. It is thought that PVS become enlarged secondary to poor glymphatic drainage of metabolites. Thus, quantitating PVS could be a good surrogate marker for glymphatic function. Numerous manual rating scales have been developed to measure the PVS number and size on MRI scans; however, these are associated with many limitations. Instead, automated methods have been created to measure PVS more accurately in different diseases. In this review, we discuss the imaging techniques currently available to visualize the glymphatic system as well as the automated methods currently available to measure PVS, and the strengths and limitations associated with each technique. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

E2730, an uncompetitive γ-aminobutyric acid transporter-1 inhibitor, suppresses epileptic seizures in a rat model of chronic mesial temporal lobe epilepsy.

OBJECTIVE: More than one third of mesial temporal lobe epilepsy (MTLE) patients are resistant to current antiseizure medications (ASMs), and half experience mild-to-moderate adverse effects of ASMs. There is therefore a strong need to develop and test novel ASMs. The objective of this work is to evaluate the pharmacokinetics and neurological toxicity of E2730, a novel uncompetitive inhibitor of γ-aminobutyric acid transporter-1, and to test its seizure suppression effects in a rat model of chronic MTLE. METHODS: We first examined plasma levels and adverse neurological effects of E2730 in healthy Wistar rats. Adult male rats were implanted with osmotic pumps delivering either 10, 20, or 100 mg/kg/day of E2730 subcutaneously for 1 week. Blood sampling and behavioral assessments were performed at several timepoints. We next examined whether E2730 suppressed seizures in rats with chronic MTLE. These rats were exposed to kainic acid-induced status epilepticus, and 9 weeks later, when chronic epilepsy was established, were assigned to receive one of the three doses of E2730 or vehicle for 1 week in a randomized crossover design. Continuous video-electroencephalographic monitoring was acquired during the treatment period to evaluate epileptic seizures. RESULTS: Plasma levels following continuous infusion of E2730 showed a clear dose-related increase in concentration. The drug was well tolerated at all doses, and any sedation or neuromotor impairment was mild and transient, resolving within 48 h of treatment initiation. Remarkably, E2730 treatment in chronically epileptic rats led to seizure suppression in a dose-dependent manner, with 65% of rats becoming seizure-free at the highest dose tested. Mean seizure class did not differ between the treatment groups. SIGNIFICANCE: This study shows that continuous subcutaneous infusion of E2730 over 7 days results in a marked, dose-dependent suppression of spontaneous recurrent seizures, with minimal adverse neurological effects, in a rat model of chronic MTLE. E2730 shows strong promise as an effective new ASM to be translated into clinical trials.

Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy.

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.

Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study.

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.

Neuroinflammation in the Cerebellum and Brainstem in Friedreich Ataxia: An [18F]-FEMPA PET Study.

BACKGROUND: Neuroinflammation is proposed to accompany, or even contribute to, neuropathology in Friedreich ataxia (FRDA), with implications for disease treatment and tracking. OBJECTIVES: To examine brain glial activation and systemic immune dysfunction in people with FRDA and quantify their relationship with symptom severity, duration, and onset age. METHODS: Fifteen individuals with FRDA and 13 healthy controls underwent brain positron emission tomography using the translocator protein (TSPO) radioligand [18 F]-FEMPA, a marker of glial activation, together with the quantification of blood plasma inflammatory cytokines. RESULTS: [18 F]-FEMPA binding was significantly increased in the dentate nuclei (d = 0.67), superior cerebellar peduncles (d = 0.74), and midbrain (d = 0.87), alongside increased plasma interleukin-6 (IL-6) (d = 0.73), in individuals with FRDA compared to controls. Increased [18 F]-FEMPA binding in the dentate nuclei, brainstem, and cerebellar anterior lobe correlated with earlier age of symptom onset (controlling for the genetic triplet repeat expansion length; all r part < -0.6), and in the pons and anterior lobe with shorter disease duration (r = -0.66; -0.73). CONCLUSIONS: Neuroinflammation is evident in brain regions implicated in FRDA neuropathology. Increased neuroimmune activity may be related to earlier disease onset and attenuate over the course of the illness. © 2021 International Parkinson and Movement Disorder Society.

Machine learning approaches for imaging-based prognostication of the outcome of surgery for mesial temporal lobe epilepsy.

OBJECTIVES: Around 30% of patients undergoing surgical resection for drug-resistant mesial temporal lobe epilepsy (MTLE) do not obtain seizure freedom. Success of anterior temporal lobe resection (ATLR) critically depends on the careful selection of surgical candidates, aiming at optimizing seizure freedom while minimizing postoperative morbidity. Structural MRI and FDG-PET neuroimaging are routinely used in presurgical assessment and guide the decision to proceed to surgery. In this study, we evaluate the potential of machine learning techniques applied to standard presurgical MRI and PET imaging features to provide enhanced prognostic value relative to current practice. METHODS: Eighty two patients with drug resistant MTLE were scanned with FDG-PET pre-surgery and T1-weighted MRI pre- and postsurgery. From these images the following features of interest were derived: volume of temporal lobe (TL) hypometabolism, % of extratemporal hypometabolism, presence of contralateral TL hypometabolism, presence of hippocampal sclerosis, laterality of seizure onset volume of tissue resected and % of temporal lobe hypometabolism resected. These measures were used as predictor variables in logistic regression, support vector machines, random forests and artificial neural networks. RESULTS: In the study cohort, 24 of 82 (28.3%) who underwent an ATLR for drug-resistant MTLE did not achieve Engel Class I (i.e., free of disabling seizures) outcome at a minimum of 2 years of postoperative follow-up. We found that machine learning approaches were able to predict up to 73% of the 24 ATLR surgical patients who did not achieve a Class I outcome, at the expense of incorrect prediction for up to 31% of patients who did achieve a Class I outcome. Overall accuracies ranged from 70% to 80%, with an area under the receiver operating characteristic curve (AUC) of .75-.81. We additionally found that information regarding overall extent of both total and significantly hypometabolic tissue resected was crucial to predictive performance, with AUC dropping to .59-.62 using presurgical information alone. Incorporating the laterality of seizure onset and the choice of machine learning algorithm did not significantly change predictive performance. SIGNIFICANCE: Collectively, these results indicate that "acceptable" to "good" patient-specific prognostication for drug-resistant MTLE surgery is feasible with machine learning approaches utilizing commonly collected imaging modalities, but that information on the surgical resection region is critical for optimal prognostication.

Atlas of lesion locations and postsurgical seizure freedom in focal cortical dysplasia: A MELD study.

OBJECTIVE: Drug-resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs). The distribution of these lesions across the cerebral cortex and the impact of lesion location on clinical presentation and surgical outcome are largely unknown. We created a neuroimaging cohort of patients with individually mapped FCDs to determine factors associated with lesion location and predictors of postsurgical outcome. METHODS: The MELD (Multi-centre Epilepsy Lesion Detection) project collated a retrospective cohort of 580 patients with epilepsy attributed to FCD from 20 epilepsy centers worldwide. Magnetic resonance imaging-based maps of individual FCDs with accompanying demographic, clinical, and surgical information were collected. We mapped the distribution of FCDs, examined for associations between clinical factors and lesion location, and developed a predictive model of postsurgical seizure freedom. RESULTS: FCDs were nonuniformly distributed, concentrating in the superior frontal sulcus, frontal pole, and temporal pole. Epilepsy onset was typically before the age of 10 years. Earlier epilepsy onset was associated with lesions in primary sensory areas, whereas later epilepsy onset was associated with lesions in association cortices. Lesions in temporal and occipital lobes tended to be larger than frontal lobe lesions. Seizure freedom rates varied with FCD location, from around 30% in visual, motor, and premotor areas to 75% in superior temporal and frontal gyri. The predictive model of postsurgical seizure freedom had a positive predictive value of 70% and negative predictive value of 61%. SIGNIFICANCE: FCD location is an important determinant of its size, the age at epilepsy onset, and the likelihood of seizure freedom postsurgery. Our atlas of lesion locations can be used to guide the radiological search for subtle lesions in individual patients. Our atlas of regional seizure freedom rates and associated predictive model can be used to estimate individual likelihoods of postsurgical seizure freedom. Data-driven atlases and predictive models are essential for evidence-based, precision medicine and risk counseling in epilepsy.

Cerebrospinal fluid neurofilament light chain differentiates primary psychiatric disorders from rapidly progressive, Alzheimer's disease and frontotemporal disorders in clinical settings.

INTRODUCTION: Many patients with cognitive and neuropsychiatric symptoms face diagnostic delay and misdiagnosis. We investigated whether cerebrospinal fluid (CSF) neurofilament light (NfL) and total-tau (t-tau) could assist in the clinical scenario of differentiating neurodegenerative (ND) from psychiatric disorders (PSY), and rapidly progressive disorders. METHODS: Biomarkers were examined in patients from specialist services (ND and PSY) and a national Creutzfeldt-Jakob registry (Creutzfeldt-Jakob disease [CJD] and rapidly progressive dementias/atypically rapid variants of common ND, RapidND). RESULTS: A total of 498 participants were included: 197 ND, 67 PSY, 161 CJD, 48 RapidND, and 20 controls. NfL was elevated in ND compared to PSY and controls, with highest levels in CJD and RapidND. NfL distinguished ND from PSY with 95%/78% positive/negative predictive value, 92%/87% sensitivity/specificity, 91% accuracy. NfL outperformed t-tau in most real-life clinical diagnostic dilemma scenarios, except distinguishing CJD from RapidND. DISCUSSION: We demonstrated strong generalizable evidence for the diagnostic utility of CSF NfL in differentiating ND from psychiatric disorders, with high accuracy.

Effective Preparation of [18F]Flumazenil Using Copper-Mediated Late-Stage Radiofluorination of a Stannyl Precursor.

(1) Background: [18F]Flumazenil 1 ([18F]FMZ) is an established positron emission tomography (PET) radiotracer for the imaging of the gamma-aminobutyric acid (GABA) receptor subtype, GABAA in the brain. The production of [18F]FMZ 1 for its clinical use has proven to be challenging, requiring harsh radiochemical conditions, while affording low radiochemical yields. Fully characterized, new methods for the improved production of [18F]FMZ 1 are needed. (2) Methods: We investigate the use of late-stage copper-mediated radiofluorination of aryl stannanes to improve the production of [18F]FMZ 1 that is suitable for clinical use. Mass spectrometry was used to identify the chemical by-products that were produced under the reaction conditions. (3) Results: The radiosynthesis of [18F]FMZ 1 was fully automated using the iPhase FlexLab radiochemistry module, affording a 22.2 ± 2.7% (n = 5) decay-corrected yield after 80 min. [18F]FMZ 1 was obtained with a high radiochemical purity (>98%) and molar activity (247.9 ± 25.9 GBq/µmol). (4) Conclusions: The copper-mediated radiofluorination of the stannyl precursor is an effective strategy for the production of clinically suitable [18F]FMZ 1.

Low prevalence of amyloid and tau pathology in drug-resistant temporal lobe epilepsy.

OBJECTIVE: Cognitive impairment is common in patients with chronic drug-resistant temporal lobe epilepsy (TLE). Hyperphosphorylated tau (pTau) and amyloid-ß (Aß) plaques, pathological hallmarks of Alzheimer disease, have been hypothesized to play a mechanistic role. We investigated Aß plaques and pTau prevalence in TLE patients who underwent resective surgery and correlated their presence with preoperative psychometric test scores and clinical factors. METHODS: Patients were retrospectively selected from the epilepsy surgery register of the Royal Melbourne Hospital, Australia. Sections from the resected temporal lobe were immunostained for pTau and Aß plaques (antibodies: AT8, 1E8). The presence and severity of pathology were correlated with clinical characteristics, and verbal and visual learning functions as measured by the Verbal Pair Associates (VPA) test and Rey Complex Figure Test. RESULTS: Fifty-six patients (55% female) aged 20-68 years (median = 34 years) at surgery were included. Aß plaques were detected in four patients (7%), all at the moderate level. There was no difference in duration, age at onset of epilepsy, or side of resection between patients with and without Aß plaques. Sparse pTau was found in two patients (3.5%). Both had moderate Aß plaques and were >50 years of age. Patients with Aß plaques had a lower median score for the VPA hard assessment compared to those without (0 vs. 4; p = .02). There was otherwise no correlation between pathology and psychometric test scores. SIGNIFICANCE: Aß plaques and pTau were uncommon in the resected brain tissue of patients who have undergone temporal lobectomy, and did not correlate with clinical characteristics or preoperative psychometric test scores, except for a lower VPA median score in patients with Aß plaques. Therefore, considering the low prevalence of Aß plaques and pTau herein observed, it is unlikely that cognitive impairment in TLE is driven by the same mechanisms as in Alzheimer disease.

The effect of injection time on rates of epileptogenic zone localization using SISCOM and STATISCOM.

BACKGROUND: The identification of hyperperfusion on ictal single-photon emission computed tomography (SPECT) scan is a technique for the localization of the epileptogenic zone (EZ) in patients with focal epilepsy undergoing presurgical evaluation. The accuracy of this technique has been improved by subtraction from an interictal image and coregistration with magnetic resonance imaging (MRI) (subtraction ictal SPECT coregistered to MRI (SISCOM)), and subsequently by the development of Statistical Ictal SPECT Co-registered to MRI (STATISCOM) which is reported to further improve localization accuracy by statistically accounting for random variation between images. However, the use of ictal SPECT is limited by the necessity for rapid injection of the radiotracer. The purpose of this study was to investigate the effect of tracer injection time on EZ localization rates using both STATISCOM and SISCOM. METHODS: Consecutive patients with drug-resistant focal epilepsy who had an ictal SPECT scan while admitted to the video-electroencephalography (EEG) monitoring unit at the Royal Melbourne Hospital, Victoria, Australia, and a subsequent interictal scan, between 2009 and 2017 were included. The information collected included age, sex, seizure type, epilepsy diagnosis, and injection time. Statistical Ictal SPECT Co-registered to MRI and SISCOM images were generated and reviewed by two blinded reviewers. The rates of potential localization of the EZ, and the agreement with the EEG, were determined for each scan. Localization rates were compared between ictal scans with different radiotracer injection time windows (<30 s, 30-45 s, 45-60 s, 60-90 s, 90-120 s, >120 s). RESULTS: Seventy patients (male = 32, 16-67 years) were included in the study. Overall agreement between the primary raters was moderate for STATISCOM (k = 0.44) and SISCOM (k = 0.57). The ability of SPECT to localize the potential EZ was 69% (48/70) for STATISCOM and 59% (41/70) for SISCOM. Injection time was not associated with the rate of localizing the potential EZ for STATISCOM (p = 0.64), whereas for SISCOM there was a trend that shorter injection times were associated with better ability to localize the potential EZ (p = 0.06). Agreement between SPECT and video-EEG data was 54% (38/70) for STATISCOM and 39% (27/70) for SISCOM. Statistical Ictal SPECT Co-registered to MRI did not show any difference of agreement across injection time groups (p = 0.42) whereas SISCOM showed better agreement with video-EEG data in the earlier injection time groups (p = 0.02). No differences in agreement between SPECT and video-EEG data were seen between patients with and without MRI lesions for either STATISCOM or SISCOM. Statistical Ictal SPECT Co-registered to MRI showed significantly better agreement for temporal than extratemporal seizures, with no difference of agreement between early (<45 s) and late (>45 s) injections. CONCLUSION: Statistical Ictal SPECT Co-registered to MRI showed overall higher agreement rates with EZ localization by video-EEG than SISCOM, which was not affected by the injection times. Statistical Ictal SPECT Co-registered to MRI may provide localizing information for "late" injections where visual reads and SISCOM are inconclusive.

Cognitive profiles in patients with epileptic and nonepileptic seizures evaluated using a brief cognitive assessment tool.

BACKGROUND: There is a need for the development of brief tools to screen for cognitive impairments in epilepsy patients in order to prioritize and direct formal comprehensive cognitive testing. Yet, shorter cognitive screening tools are limited in their breadth of cognitive domains or have not been intensively studied on an epilepsy population. This study used a brief cognitive screening tool in order to compare cognitive profiles between patients with epilepsy and those with nonepileptic seizures. METHODS: Patients admitted to the Royal Melbourne Hospital video-EEG monitoring unit between 2005 and 2017 were included. Patients were categorized according to seizure etiology (epileptic, psychogenic or other nonepileptic seizures), epilepsy syndrome (focal or generalized; temporal lobe (TLE) or extra-temporal lobe epilepsy (ETLE)), seizure frequency, and anti-seizure medications (ASMs). Attention, visuoconstructional, memory, executive, and language functioning were assessed with the Neuropsychiatry Unit Cognitive Assessment Tool (NUCOG). General linear mixed models were computed to investigate cognitive profiles according to diagnostic group and other clinicodemographic variables. RESULTS: 800 patients were included in the analysis (61% female and 39 % male, median age 36 years). Patients with both epileptic seizures and psychogenic seizures (n = 25) had the lowest total scores on NUCOG, followed by patients with epileptic seizures (n = 411), psychogenic seizures (n = 185), and nonepileptic seizures (n = 179, p = 0.002). Specifically, patients with epileptic seizures performed worse than those with nonepileptic seizures in the executive, language, and memory domain, and had lower language domain scores than those with psychogenic seizures. Patients with bilateral TLE had poorer performance than those with unilateral TLE, particularly for memory function. Specific ASMs and polypharmacy but not seizure frequency had a negative effect on cognition (p < 0.001). NUCOG scores did not differ between focal and generalized epilepsies, or between TLE and ETLE. CONCLUSION: The NUCOG differentiated cognitive profiles in patients with uncontrolled seizures due to different etiologies. Bilateral TLE and medication adversely affected cognitive performance, and overall patients with epilepsy performed worse than those with nonepileptic seizures. These results provide further evidence for sensitivity of the NUCOG for detecting cognitive impairment in patients with seizure disorders.

Metabolic patterns and seizure outcomes following anterior temporal lobectomy.

OBJECTIVE: We investigated the relationship between the interictal metabolic patterns, the extent of resection of 18 F-fluorodeoxyglucose positron emission tomography (18 FDG-PET) hypometabolism, and seizure outcomes in patients with unilateral drug-resistant mesial temporal lobe epilepsy (MTLE) following anterior temporal lobe (TL) resection. METHODS: Eighty-two patients with hippocampal sclerosis or normal magnetic resonance imaging (MRI) findings, concordant 18 FDG-PET hypometabolism, and at least 2 years of postoperative follow-up were included in this 2-center study. The hypometabolic regions in each patient were identified with reference to 20 healthy controls (p < 0.005). The resected TL volume and the volume of resected TL PET hypometabolism (TLH) were calculated from the pre- and postoperative MRI scans coregistered with interictal 18 FDG-PET. RESULTS: Striking differences in metabolic patterns were observed depending on the lateralization of the epileptogenic TL. The extent of the ipsilateral TLH was significantly greater in left MTLE patients (p < 0.001), whereas right MTLE patients had significantly higher rates of contralateral (CTL) TLH (p = 0.016). In right MTLE patients, CTL hypometabolism was the strongest predictor of an unfavorable seizure outcome, associated with a 5-fold increase in the likelihood of seizure recurrence (odds ratio [OR] = 4.90, 95% confidence interval [CI] = 1.07-22.39, p = 0.04). In left MTLE patients, greater extent of resection of ipsilateral TLH was associated with lower rates of seizure recurrence (p = 0.004) in univariate analysis; however, its predictive value did not reach statistical significance (OR = 0.96, 95% CI = 0.90-1.02, p = 0.19). INTERPRETATION: The difference in metabolic patterns depending on the lateralization of MTLE may represent distinct epileptic networks in patients with right versus left MTLE, and can guide preoperative counseling and surgical planning. Ann Neurol 2019; 1-10 ANN NEUROL 2019;85:241-250.

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study.

Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by meta-analysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen's d = -0.24 to -0.73; P < 1.49 × 10-4), and lower thickness in the precentral gyri bilaterally (d = -0.34 to -0.52; P < 4.31 × 10-6). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = -1.73 to -1.91, P < 1.4 × 10-19), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = -0.36 to -0.52; P < 1.49 × 10-4). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = -0.29 to -0.54; P < 1.49 × 10-4). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = -0.27 to -0.51; P < 1.49 × 10-4). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b < -0.0018; P < 1.49 × 10-4). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed.

Semi-automated hippocampal segmentation in people with cognitive impairment using an age appropriate template for registration.

BACKGROUND: To evaluate a new semi-automated segmentation method for calculating hippocampal volumes and to compare results with standard software tools in a cohort of people with subjective memory complaints (SMC) and mild cognitive impairment (MCI). METHODS: Data from 58 participants, 39 with SMC (17 male, 22 female, mean age 72.6) and 19 with MCI (6 male, 13 female, mean age 74.3), were analyzed. For each participant, T1-weighted images were acquired using an MPRAGE sequence on a 3 Tesla MRI system. Hippocampal volumes (left, right, and total) were calculated with a new, age appropriate registration template, based on older people and using the advanced software tool ANTs (Advanced Normalization Tools). The results were compared with manual tracing (seen as the reference standard) and two widely accepted automated software tools (FSL, FreeSurfer). RESULTS: The hippocampal volumes, calculated by using the age appropriate registration template were significantly (P < 0.05) more accurate (mean volume accuracy more than 90%) than those obtained with FreeSurfer and FSL (both less than 70%). Dice coefficients for the hippocampal segmentations with the new template method (75.3%) were slightly, but significantly (P < 0.05) higher than those from FreeSurfer (72.4%). CONCLUSION: These results suggest that an age appropriate registration template might be a more accurate alternative to calculate hippocampal volumes when manual segmentation is not feasible.

Role of the glymphatic system and perivascular spaces as a potential biomarker for post-stroke epilepsy.

Stroke is one of the most common causes of acquired epilepsy, which can also result in disability and increased mortality rates particularly in elderly patients. No preventive treatment for post-stroke epilepsy is currently available. Development of such treatments has been greatly limited by the lack of biomarkers to reliably identify high-risk patients. The glymphatic system, including perivascular spaces (PVS), is the brain's waste clearance system, and enlargement or asymmetry of PVS (ePVS) is hypothesized to play a significant role in the pathogenesis of several neurological conditions. In this article, we discuss potential mechanisms for the role of perivascular spaces in the development of post-stroke epilepsy. Using advanced MR-imaging techniques, it has been shown that there is asymmetry and impairment of glymphatic function in the setting of ischemic stroke. Furthermore, studies have described a dysfunction of PVS in patients with different focal and generalized epilepsy syndromes. It is thought that inflammatory processes involving PVS and the blood-brain barrier, impairment of waste clearance, and sustained hypertension affecting the glymphatic system during a seizure may play a crucial role in epileptogenesis post-stroke. We hypothesize that impairment of the glymphatic system and asymmetry and dynamics of ePVS in the course of a stroke contribute to the development of PSE. Automated ePVS detection in stroke patients might thus assist in the identification of high-risk patients for post-stroke epilepsy trials. PLAIN LANGUAGE SUMMARY: Stroke often leads to epilepsy and is one of the main causes of epilepsy in elderly patients, with no preventative treatment available. The brain's waste removal system, called the glymphatic system which consists of perivascular spaces, may be involved. Enlargement or asymmetry of perivascular spaces could play a role in this and can be visualised with advanced brain imaging after a stroke. Detecting enlarged perivascular spaces in stroke patients could help identify those at risk for post-stroke epilepsy.

Monash-Alfred protocol for assessment of atypical parkinsonian syndromes (MAP-APS).

Introduction: Atypical parkinsonian syndromes (APS) are rare neurodegenerative syndromes for which parkinsonism is one significant feature. APS includes progressive supranuclear palsy (PSP), multiple system atrophy (MSA) and corticobasal syndrome (CBS). The diagnosis of APS remains reliant on clinical features with no available diagnostic or prognostic biomarker. Clinical scales remain the gold standard assessment measures in clinical trials and research. The lack of standardised approach for research cohorts has contributed to shortcomings in disease understanding and limits collaboration between researchers. The primary objectives of this study are to (1) establish an assessment protocol for parkinsonian syndromes and (2) to implement it at a single site to establish the viability and utility of populating a clinical and biological databank of patients with APS. Methods: The Monash Alfred Protocol for Assessment of APS was devised by expert consensus within a broad multidisciplinary team. Eligible patients are diagnosed as possible or probable PSP, MSA or CBS by a consultant neurologist with expertise in movement disorders. Participants will be assessed at recruitment and then annually for up to 3 years; individuals within 5 years of index symptom onset will also undergo a once-off 6-month assessment. Ethics and dissemination: Each participant or their legally authorised representative will provide informed written consent prior to commencement of the study. Data will be stored on a locally hosted Research Electronic Data Capture database. Trial registration number: Australian New Zealand Clinical Trials Registry (ANZCTN 12622000923763).