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Background and objectivesThere is growing evidence that bilingualism can induce neuroplasticity and modulate neural efficiency, resulting in greater resistance to neurologic disease. However, whether bilingualism is beneficial to neural health in the presence of epilepsy is unknown. We tested whether bilingual individuals with temporal lobe epilepsy (TLE) have improved whole-brain structural white matter network organization.MethodsHealthy controls and individuals with TLE recruited from 2 specialized epilepsy centers completed diffusion-weighted MRI and neuropsychological testing as part of an observational cohort study. Whole-brain connectomes were generated via diffusion tractography and analyzed using graph theory. Global analyses compared network integration (path length) and specialization (transitivity) in TLE vs controls and in a 2 (left vs right TLE) × 2 (bilingual vs monolingual) model. Local analyses compared mean local efficiency of predefined frontal-executive and language (i.e., perisylvian) subnetworks. Exploratory correlations examined associations between network organization and neuropsychological performance.ResultsA total of 29 bilingual and 88 monolingual individuals with TLE matched on several demographic and clinical variables and 81 age-matched healthy controls were included. Globally, a significant interaction between language status and side of seizure onset revealed higher network organization in bilinguals compared with monolinguals but only in left TLE (LTLE). Locally, bilinguals with LTLE showed higher efficiency in frontal-executive but not in perisylvian networks compared with LTLE monolinguals. Improved whole-brain network organization was associated with better executive function performance in bilingual but not monolingual LTLE.DiscussionHigher white matter network organization in bilingual individuals with LTLE suggests a neuromodulatory effect of bilingualism on whole-brain connectivity in epilepsy, providing evidence for neural reserve. This may reflect attenuation of or compensation for epilepsy-related dysfunction of the left hemisphere, potentially driven by increased efficiency of frontal-executive networks that mediate dual-language control. This highlights a potential role of bilingualism as a protective factor in epilepsy, motivating further research across neurologic disorders to define mechanisms and develop interventions.

ObjectiveRisk for memory decline is a common concern for individuals with temporal lobe epilepsy (TLE) undergoing surgery. Global and local network abnormalities are well documented in TLE. However, it is less known whether network abnormalities predict postsurgical memory decline. The authors examined the role of preoperative global and local white matter network organization and risk of postoperative memory decline in TLE.MethodsOne hundred one individuals with TLE (n = 51 with left TLE and 50 with right TLE) underwent preoperative T1-weighted MRI, diffusion MRI, and neuropsychological memory testing in a prospective longitudinal study. Fifty-six age- and sex-matched controls completed the same protocol. Forty-four patients (22 with left TLE and 22 with right TLE) subsequently underwent temporal lobe surgery and postoperative memory testing. Preoperative structural connectomes were generated via diffusion tractography and analyzed using measures of global and local (i.e., medial temporal lobe [MTL]) network organization. Global metrics measured network integration and specialization. The local metric was calculated as an asymmetry of the mean local efficiency between the ipsilateral and contralateral MTLs (i.e., MTL network asymmetry).ResultsHigher preoperative global network integration and specialization were associated with higher preoperative verbal memory function in patients with left TLE. Higher preoperative global network integration and specialization, as well as greater leftward MTL network asymmetry, predicted greater postoperative verbal memory decline for patients with left TLE. No significant effects were observed in right TLE. Accounting for preoperative memory score and hippocampal volume asymmetry, MTL network asymmetry uniquely explained 25%-33% of the variance in verbal memory decline for left TLE and outperformed hippocampal volume asymmetry and global network metrics. MTL network asymmetry alone produced good diagnostic classification of memory decline in left TLE (i.e., an area under the receiver operating characteristic curve of 0.80-0.84 and correct classification of 65%-76% of cases with cross-validation).ConclusionsThese preliminary data suggest that global white matter network disruption contributes to verbal memory impairment preoperatively and predicts postsurgical verbal memory outcomes in left TLE. However, a leftward asymmetry of MTL white matter network organization may confer the highest risk for verbal memory decline. Although this requires replication in a larger sample, the authors demonstrate the importance of characterizing preoperative local white matter network properties within the to-be-operated hemisphere and the reserve capacity of the contralateral MTL network, which may eventually be useful in presurgical planning.

ObjectiveRecent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross-sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE-HS) correlate with clinical features.MethodsWe extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1-weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA-Epilepsy consortium, comprising 804 people with MTLE-HS and 1625 healthy controls from 25 centers. Features with a moderate case-control effect size (Cohen d ≥ .5) were used to train an event-based model (EBM), which estimates a sequence of disease-specific biomarker changes from cross-sectional data and assigns a biomarker-based fine-grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance.ResultsIn MTLE-HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume, and finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated with duration of illness (Spearman ρ = .293, p = 7.03 × 10-16 ), age at onset (ρ = -.18, p = 9.82 × 10-7 ), and ASM resistance (area under the curve = .59, p = .043, Mann-Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE-HS with mild or nondetectable abnormality on T1W MRI.SignificanceFrom cross-sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE-HS subjects in other cohorts and help establish connections between imaging-based progression staging and clinical features.

ObjectiveEpisodic memory impairment and hippocampal pathology are hallmark features of both temporal lobe epilepsy (TLE) and amnestic mild cognitive impairment (aMCI). Pattern separation (PS), which enables the distinction between similar but unique experiences, is thought to contribute to successful encoding and retrieval of episodic memories. Impaired PS has been proposed as a potential mechanism underling episodic memory impairment in aMCI, but this association is less established in TLE. In this study, we examined behavioral PS in patients with TLE and explored whether profiles of performance in TLE are similar to aMCI.MethodPatients with TLE, aMCI, and age-matched, healthy controls (HCs) completed a modified recognition task that relies on PS for the discrimination of highly similar lure items, the Mnemonic Similarity Task (MST). Group differences were evaluated and relationships between clinical characteristics, California Verbal Learning Test-Second Edition scores, and MST performance were tested in the TLE group.ResultsPatients with TLE and aMCI demonstrated poorer PS performance relative to the HCs, but performance did not differ between the two patient groups. Neither the side of seizure focus nor having hippocampal sclerosis affected performance in TLE. However, TLE patients with clinically defined memory impairment showed the poorest performance.ConclusionMemory performance on a task that relies on PS was disrupted to a similar extent in TLE and aMCI. The MST could provide a clinically useful tool for measuring hippocampus-dependent memory impairments in TLE and other neurological disorders associated with hippocampal damage.

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.

Individuals with left temporal lobe epilepsy (TLE) have a higher rate of atypical (i.e., bilateral or right hemisphere) language lateralization compared to healthy controls. In addition, bilinguals have been observed to have a less left-lateralized pattern of language representation. We examined the combined influence of bilingual language experience and side of seizure focus on language lateralization profiles in TLE to determine whether bilingualism promotes re-organization of language networks. Seventy-two monolingual speakers of English (21 left TLE; LTLE, 22 right TLE; RTLE, 29 age-matched healthy controls; HC) and 24 English-dominant bilinguals (6 LTLE, 7 RTLE, 11 HC) completed a lexical-semantic functional MRI task and standardized measures of language in English. Language lateralization was determined using laterality indices based on activations in left vs right homologous perisylvian regions-of-interest (ROIs). In a fronto-temporal ROI, LTLE showed the expected pattern of weaker left language lateralization relative to HC, and monolinguals showed a trend of weaker left language lateralization relative to bilinguals. Importantly, these effects were qualified by a significant group by language status interaction, revealing that bilinguals with LTLE had greater rightward language lateralization relative to monolingual LTLE, with a large effect size particularly in the lateral temporal region. Rightward language lateralization was associated with better language scores in bilingual LTLE. These preliminary findings suggest a combined effect of bilingual language experience and a left hemisphere neurologic insult, which may together increase the likelihood of language re-organization to the right hemisphere. Our data underscore the need to consider bilingualism as an important factor contributing to language laterality in patients with TLE. Bilingualism may be neuroprotective pre-surgically and may mitigate post-surgical language decline following left anterior temporal lobectomy, which will be important to test in larger samples.

We report a case study of a surgical candidate, a 51-year-old woman with left temporal lobe epilepsy, who failed a left injection intracarotid amobarbital procedure (e.g., Wada test), scoring 0 of 8 items. This raised concerns for postoperative memory decline. However, the patient was uninterested in a neuromodulatory approach and wished to be reconsidered for surgery. A stereotactic laser amygdalohippocampotomy (SLAH) was considered, encouraging the need for an alternative test to evaluate risk of memory decline. We developed a novel approach to testing memory during stimulation of a depth electrode implanted in the hippocampus, i.e., an electric Wada. During multiple stimulation trials across a range of amplitudes, the patient scored up to 8 of 8 items, which suggested strong contralateral memory support. The surgical team proceeded with a radiofrequency ablation and a subsequent SLAH. The patient remains seizure-free at 12 months post SLAH with no evidence of verbal or visuospatial memory decline based on a post-surgical neuropsychological battery. We believe that this case study provides a proof of concept for the feasibility and possible utility of an electric version of the Wada procedure. Future studies are needed to develop an optimal paradigm and to validate this approach.

Background and objectivesRisk for memory decline is a substantial concern in patients with temporal lobe epilepsy (TLE) undergoing anterior temporal lobectomy (ATL). Although prior studies have identified associations between memory and integrity of white matter (WM) networks within the medial temporal lobe (MTL) preoperatively, we contribute a study examining whether microstructural asymmetry of deep and superficial WM networks within the MTL predicts postoperative memory decline.MethodsPatients with drug-resistant TLE were recruited from 2 epilepsy centers in a prospective longitudinal study. All patients completed preoperative T1 and diffusion-weighted MRI (DWI) as well as preoperative and postoperative neuropsychological testing. Preoperative fractional anisotropy (FA) of the WM directly beneath the neocortex (i.e., superficial WM [SWM]) and of deep WM tracts associated with memory were calculated. Asymmetry was calculated for hippocampal volume and FA of each WM tract or region and examined in linear and logistic regressions with preoperative to postoperative memory change as the primary outcome.ResultsData were analyzed from 42 patients with TLE (19 left TLE [LTLE], 23 right TLE [RTLE]) who underwent ATL. Leftward FA asymmetry of the entorhinal SWM was associated with decline on prose and associative recall in LTLE, whereas leftward FA asymmetry of the uncinate fasciculus (UNC) was associated with decline on prose recall only. After controlling for preoperative memory score and hippocampal volume, leftward FA asymmetry of the entorhinal SWM uniquely contributed to decline in both prose and associative recall (β = -0.46; SE 0.14 and β = -0.68; SE 0.22, respectively) and leftward FA asymmetry of the UNC uniquely contributed to decline in prose recall (β = -0.31; SE 0.14). A model combining asymmetry of hippocampal volume and entorhinal FA correctly classified memory outcomes in 79% of patients with LTLE for prose (area under the curve [AUC] 0.89; sensitivity 82%; specificity 75%) and 81% of patients for associative (AUC 0.79; sensitivity 83%; specificity 80%) recall. Entorhinal SWM asymmetry was the strongest predictor in both models.DiscussionPreoperative asymmetry of deep WM and SWM integrity within the MTL is a strong predictor of postoperative memory decline in TLE, suggesting that surgical decision-making may benefit from considering each patient's WM network adequacy and reserve in addition to hippocampal integrity.Classification of evidenceThis study provides Class II evidence that preoperative asymmetry of deep WM and SWM integrity within the MTL is a predictor of postoperative memory decline.

Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller-scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well-established by the ENIGMA Consortium, ENIGMA-Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event-based modeling analysis. We explore age of onset- and duration-related features, as well as phenomena-specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA-Epilepsy.

ObjectiveEmerging research highlights the importance of basal-temporal cortex, centered on the fusiform gyrus, to both pre-surgical naming ability and post-surgical naming outcomes in temporal lobe epilepsy (TLE). In this study, we investigate whether integrity of the white matter network that interconnects this basal region to the distributed language network affects naming ability and risk for post-surgical naming decline.MethodsPatients with drug-resistant TLE were recruited from two epilepsy centers in a prospective longitudinal study. The pre-surgical dataset included 50 healthy controls, 47 left TLE (L-TLE), and 41 right TLE (R-TLE) patients. All participants completed pre-surgical T1- and diffusion-weighted MRI (dMRI), as well as neuropsychological tests of auditory and visual naming. Nineteen L-TLE and 18 R-TLE patients underwent anterior temporal lobectomy (ATL) and also completed post-surgical neuropsychological testing. Pre-surgical fractional anisotropy (FA) of the white matter directly beneath the fusiform neocortex (i.e., superficial white matter; SWM) and of deep white matter tracts with connections to the basal-temporal cortex [inferior longitudinal fasciculus (ILF) and inferior frontal occipital fasciculus (IFOF)] was calculated. Clinical variables, hippocampal volume, and FA of each white matter tract or region were examined in linear regressions with naming scores, or change in naming scores, as the primary outcomes.ResultsPre-surgically, higher FA in the bilateral ILF, bilateral IFOF, and left fusiform SWM was associated with better visual and auditory naming scores (all ps

Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-transcriptomic signatures could potentially guide diagnosis or tailor therapeutic approaches to specific epilepsy syndromes.

Numerous brain disorders demonstrate structural brain abnormalities, which are thought to arise from molecular perturbations or connectome miswiring. The unique and shared contributions of these molecular and connectomic vulnerabilities to brain disorders remain unknown, and has yet to be studied in a single multi-disorder framework. Using MRI morphometry from the ENIGMA consortium, we construct maps of cortical abnormalities for thirteen neurodevelopmental, neurological, and psychiatric disorders from N = 21,000 participants and N = 26,000 controls, collected using a harmonised processing protocol. We systematically compare cortical maps to multiple micro-architectural measures, including gene expression, neurotransmitter density, metabolism, and myelination (molecular vulnerability), as well as global connectomic measures including number of connections, centrality, and connection diversity (connectomic vulnerability). We find a relationship between molecular vulnerability and white-matter architecture that drives cortical disorder profiles. Local attributes, particularly neurotransmitter receptor profiles, constitute the best predictors of both disorder-specific cortical morphology and cross-disorder similarity. Finally, we find that cross-disorder abnormalities are consistently subtended by a small subset of network epicentres in bilateral sensory-motor, inferior temporal lobe, precuneus, and superior parietal cortex. Collectively, our results highlight how local molecular attributes and global connectivity jointly shape cross-disorder cortical abnormalities.

Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive. We used support vector machine (SV) and deep learning (DL) models based on region of interest (ROI-based) structural (n = 336) and diffusion (n = 863) brain MRI data from patients with TLE with ("lesional") and without ("non-lesional") radiographic features suggestive of underlying hippocampal sclerosis from the multinational (multi-center) ENIGMA-Epilepsy consortium. Our data showed that models to identify TLE performed better or similar (68-75%) compared to models to lateralize the side of TLE (56-73%, except structural-based) based on diffusion data with the opposite pattern seen for structural data (67-75% to diagnose vs. 83% to lateralize). In other aspects, structural and diffusion-based models showed similar classification accuracies. Our classification models for patients with hippocampal sclerosis were more accurate (68-76%) than models that stratified non-lesional patients (53-62%). Overall, SV and DL models performed similarly with several instances in which SV mildly outperformed DL. We discuss the relative performance of these models with ROI-level data and the implications for future applications of machine learning and artificial intelligence in epilepsy care.

Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional mega-analysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1021 adults with epilepsy compared to 1564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy colocalized with highly interconnected cortical hub regions, whereas idiopathic generalized epilepsy showed preferential subcortical hub involvement. These morphological abnormalities were anchored to the connectivity profiles of distinct disease epicenters, pointing to temporo-limbic cortices in temporal lobe epilepsy and fronto-central cortices in idiopathic generalized epilepsy. Negative effects of age on atrophy further revealed a strong influence of connectome architecture in temporal lobe, but not idiopathic generalized, epilepsy. Our findings were reproduced across individual sites and single patients and were robust across different analytical methods. Through worldwide collaboration in ENIGMA-Epilepsy, we provided deeper insights into the macroscale features that shape the pathophysiology of common epilepsies.

The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analysed from 1069 healthy controls and 1249 patients: temporal lobe epilepsy with hippocampal sclerosis (n = 599), temporal lobe epilepsy with normal MRI (n = 275), genetic generalized epilepsy (n = 182) and non-lesional extratemporal epilepsy (n = 193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fibre tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at P

ObjectiveWe previously identified 4 empirically derived mild cognitive impairment (MCI) subtypes via cluster analysis within the Alzheimer's Disease Neuroimaging Initiative (ADNI) and demonstrated high correspondence between patterns of cortical thinning at baseline and each cognitive subtype. We aimed to determine whether our MCI subtypes demonstrate unique longitudinal atrophy patterns.MethodsADNI participants (295 with MCI and 134 cognitively normal [CN]) underwent annual structural MRI and neuropsychological assessments. General linear modeling compared vertex-wise differences in cortical atrophy rates between each MCI subtype and the CN group. Linear mixed models examined trajectories of cortical atrophy over 3 years within lobar regions of interest.ResultsCompared to the CN group, those with amnestic MCI (memory deficit) initially demonstrated greater atrophy rates within medial temporal lobe regions that became more widespread over time. Those with dysnomic/amnestic MCI (naming/memory deficits) showed greater atrophy rates largely localized to temporal lobe regions. The mixed MCI (impairment in all cognitive domains) group showed greater atrophy rates in widespread regions at all time points. The cluster-derived normal group, who had intact neuropsychological performance and normal cortical thickness at baseline despite their MCI diagnosis via conventional diagnostic criteria, continued to show normal cognition and minimal cortical atrophy over 3 years.ConclusionsADNI's purported amnestic MCI sample produced more refined cognitive subtypes with unique longitudinal cortical atrophy rates. These novel MCI subtypes reliably reflect underlying atrophy, reduce false-positive diagnostic errors, and improve prediction of clinical course. Such improvements have implications for the selection of participants for clinical trials and for providing more precise risk assessment for individuals diagnosed with MCI.

Immunotherapy is increasingly used in the treatment of glioblastoma (GBM), with immune checkpoint therapy gaining in popularity given favorable outcomes achieved for other tumors. However, immune-mediated (IM)-pseudoprogression is common, remains poorly characterized, and renders conventional imaging of little utility when evaluating for treatment response. We present the case of a 64-year-old man with GBM who developed pathologically proven IM-pseudoprogression after initiation of a checkpoint inhibitor, and who subsequently developed true tumor progression at a distant location. Based on both qualitative and quantitative analysis, we demonstrate that an advanced diffusion-weighted imaging (DWI) technique called restriction spectrum imaging (RSI) can differentiate IM-pseudoprogression from true progression even when conventional imaging, including standard DWI/apparent diffusion coefficient (ADC), is not informative. These data complement existing literature supporting the ability of RSI to estimate tumor cellularity, which may help to resolve complex diagnostic challenges such as the identification of IM-pseudoprogression.

IntroductionWe investigated multi-domain baseline neurocognition of primary brain tumor patients prior to radiotherapy (RT), including clinical predictors of function and association between pre-RT and post-RT impairment on a prospective trial.MethodsA multi-domain neuropsychological battery (memory, executive functioning, language, attention, processing) was performed on 37 patients, pre-RT and 3-(n = 21), 6-(n = 22) and 12-(n = 14) months post-RT. Impairment rate was the proportion of patients with standardized T-scores ≤ 1.5 standard deviations below normative means. Per-patient impairment across all domains was calculated using a global deficit score (GDS; higher value indicates more impairment). Associations between baseline GDS and clinical variables were tested. Global GDS impairment rate at each time point was the fraction of patients with GDS scores > 0.5.ResultsStatistically significant baseline neurocognitive impairments were identified on 4 memory (all p ≤ 0.03) and 2 out of 3 (p = 0.01, p = 0.027) executive functioning tests. Per-patient baseline GDS was significantly associated with tumor volume (p = 0.048), tumor type (p = 0.043), seizure history (p = 0.007), and use of anti-epileptics (p = 0.009). The percentage of patients with the same impairment status at 3-, 6-, and 12-months as at baseline were 88%, 85%, and 85% respectively.ConclusionsMemory and executive functioning impairment were the most common cognitive deficits prior to RT. Patients with larger tumors, more aggressive histology, and use of anti-epileptics had higher baseline GDS values. GDS is a promising tool to encompass multi-domain neurocognitive function, and baseline GDS can identify those at risk of cognitive impairment.

ObjectiveThe distributed white matter network underlying language leads to difficulties in extracting clinically meaningful summaries of neural alterations leading to language impairment. Here we determine the predictive ability of the structural connectome (SC), compared with global measures of white matter tract microstructure and clinical data, to discriminate language impaired patients with temporal lobe epilepsy (TLE) from TLE patients without language impairment.MethodsT1- and diffusion-MRI, clinical variables (CVs), and neuropsychological measures of naming and verbal fluency were available for 82 TLE patients. Prediction of language impairment was performed using a robust tree-based classifier (XGBoost) for three models: (1) a CV-model which included demographic and epilepsy-related clinical features, (2) an atlas-based tract-model, including four frontotemporal white matter association tracts implicated in language (i.e., the bilateral arcuate fasciculus, inferior frontal occipital fasciculus, inferior longitudinal fasciculus, and uncinate fasciculus), and (3) a SC-model based on diffusion MRI. For the association tracts, mean fractional anisotropy was calculated as a measure of white matter microstructure for each tract using a diffusion tensor atlas (i.e., AtlasTrack). The SC-model used measurement of cortical-cortical connections arising from a temporal lobe subnetwork derived using probabilistic tractography. Dimensionality reduction of the SC was performed with principal components analysis (PCA). Each model was trained on 49 patients from one epilepsy center and tested on 33 patients from a different center (i.e., an independent dataset). Randomization was performed to test the stability of the results.ResultsThe SC-model yielded a greater area under the curve (AUC; .73) and accuracy (79%) compared to both the tract-model (AUC: .54, p

PurposeWe used quantitative magnetic resonance imaging to prospectively analyze the association between microstructural damage to memory-associated structures within the medial temporal lobe and longitudinal memory performance after brain radiation therapy (RT).Methods and materialsPatients with a primary brain tumor receiving fractionated brain RT were enrolled on a prospective trial (n = 27). Patients underwent high-resolution volumetric brain magnetic resonance imaging, diffusion-weighted imaging, and neurocognitive testing before and 3, 6, and 12 months post-RT. Medial temporal lobe regions (hippocampus; entorhinal, parahippocampal, and temporal pole white matter [WM]) were autosegmented, quantifying volume and diffusion biomarkers of WM integrity (mean diffusivity [MD]; fractional anisotropy [FA]). Reliable change indices measured changes in verbal (Hopkins Verbal Learning Test-Revised) and visuospatial (Brief Visuospatial Memory Test-Revised [BVMT-R]) memory. Linear mixed-effects models assessed longitudinal associations between imaging parameters and memory.ResultsVisuospatial memory significantly declined at 6 months post-RT (mean reliable change indices, -1.3; P = .012). Concurrent chemotherapy and seizures trended toward a significant association with greater decline in visuospatial memory (P = .053 and P = .054, respectively). Higher mean dose to the left temporal pole WM was significantly associated with decreased FA (r = -0.667; P = .002). Over all time points, smaller right hippocampal volume (P = .021), lower right entorhinal FA (P = .023), greater right entorhinal MD (P = .047), and greater temporal pole MD (BVMT-R total recall, P = .003; BVMT-R delayed recall, P = .042) were associated with worse visuospatial memory. The interaction between right entorhinal MD (BVMT-R total recall, P = .021; BVMT-R delayed recall, P = .004) and temporal pole FA (BVMT-R delayed recall, P = .024) significantly predicted visuospatial memory performance.ConclusionsBrain tumor patients exhibited visuospatial memory decline post-RT. Microstructural damage to critical memory regions, including the hippocampus and medial temporal lobe WM, were associated with post-RT memory decline. The integrity of medial temporal lobe structures is critical to memory performance post-RT, representing possible avoidance targets for memory preservation.

Background and purposeThe amygdalae are deep brain nuclei critical to emotional processing and the creation and storage of memory. It is not known whether the amygdalae are affected by brain radiotherapy (RT). We sought to quantify dose-dependent amygdala change one year after brain RT.Materials and methods52 patients with primary brain tumors were retrospectively identified. Study patients underwent high-resolution, volumetric magnetic resonance imaging before RT and 1 year afterward. Images were processed using FDA-cleared software for automated segmentation of amygdala volume. Tumor, surgical changes, and segmentation errors were manually censored. Mean amygdala RT dose was tested for correlation with amygdala volume change 1 year after RT via the Pearson correlation coefficient. A linear mixed-effects model was constructed to evaluate potential predictors of amygdala volume change, including age, tumor hemisphere, sex, seizure history, and bevacizumab treatment during the study period. As 51 of 52 patients received chemotherapy, possible chemotherapy effects could not be studied. A two-tailed p-value

IntroductionThe Alzheimer's Disease Neuroimaging Initiative (ADNI) separates "early" and "late" mild cognitive impairment (MCI) based on a single memory test. We compared ADNI's MCI classifications to our neuropsychological approach, which more broadly assesses cognitive abilities.MethodsThree hundred thirty-six ADNI-2 participants were classified as "early" or "late" MCI. Cluster analysis was performed on neuropsychological test data, and participants were reclassified based on cluster results. These two staging approaches were compared on progression rates, cerebrospinal fluid biomarkers, and cortical thickness profiles.ResultsThere was little correspondence between the two staging methods. ADNI's early MCI group included a large proportion of false-positive diagnostic errors. The reclassified neuropsychological MCI groups showed steeper survival curves and more abnormal biomarkers.ConclusionsOur novel neuropsychological approach improved the staging of MCI by (1) capturing individuals at an early symptomatic stage, (2) minimizing false-positive cases, and (3) identifying a late MCI group further along the disease trajectory.

ObjectivesTemporal lobe epilepsy (TLE) is known to affect large-scale gray and white matter networks, and these network changes likely contribute to the verbal memory impairments observed in many patients. In this study, we investigate multimodal imaging patterns of brain alterations in TLE and evaluate the sensitivity of different imaging measures to verbal memory impairment.MethodsDiffusion tensor imaging (DTI), volumetric magnetic resonance imaging (vMRI), and resting-state functional MRI (rs-fMRI) were evaluated in 46 patients with TLE and 33 healthy controls to measure patterns of microstructural, structural, and functional alterations, respectively. These measurements were obtained within the white matter directly beneath neocortex (ie, superficial white matter [SWM]) for DTI and across neocortex for vMRI and rs-fMRI. The degree to which imaging alterations within left medial temporal lobe/posterior cingulate (LMT/PC) and left lateral temporal regions were associated with verbal memory performance was evaluated.ResultsPatients with left TLE and right TLE both demonstrated pronounced microstructural alterations (ie, decreased fractional anisotropy [FA] and increased mean diffusivity [MD]) spanning the entire frontal and temporolimbic SWM, which were highly lateralized to the ipsilateral hemisphere. Conversely, reductions in cortical thickness in vMRI and alterations in the magnitude of the rs-fMRI response were less pronounced and less lateralized than the microstructural changes. Both stepwise regression and mediation analyses further revealed that FA and MD within SWM in LMT/PC regions were the most robust predictors of verbal memory, and that these associations were independent of left hippocampal volume.SignificanceThese findings suggest that microstructural loss within the SWM is pronounced in patients with TLE, and injury to the SWM within the LMT/PC region plays a critical role in verbal memory impairment.

OBJECTIVE:To identify distinct cognitive phenotypes in temporal lobe epilepsy (TLE) and evaluate patterns of white matter (WM) network alterations associated with each phenotype. METHODS:Seventy patients with TLE were characterized into 4 distinct cognitive phenotypes based on patterns of impairment in language and verbal memory measures (language and memory impaired, memory impaired only, language impaired only, no impairment). Diffusion tensor imaging was obtained in all patients and in 46 healthy controls (HC). Fractional anisotropy (FA) and mean diffusivity (MD) of the WM directly beneath neocortex (i.e., superficial WM [SWM]) and of deep WM tracts associated with memory and language were calculated for each phenotype. Regional and network-based SWM analyses were performed across phenotypes. RESULTS:The language and memory impaired group and the memory impaired group showed distinct patterns of microstructural abnormalities in SWM relative to HC. In addition, the language and memory impaired group showed widespread alterations in WM tracts and altered global SWM network topology. Patients with isolated language impairment exhibited poor network structure within perisylvian cortex, despite relatively intact global SWM network structure, whereas patients with no impairment appeared similar to HC across all measures. CONCLUSIONS:These findings demonstrate a differential pattern of WM microstructural abnormalities across distinct cognitive phenotypes in TLE that can be appreciated at both the regional and network levels. These findings not only help to unravel the underlying neurobiology associated with cognitive impairment in TLE, but they could also aid in establishing cognitive taxonomies or in the prediction of cognitive course in TLE.

Background and purposeExecutive function (EF) decline is common after brain radiation therapy (RT), yet the etiology is unclear. We analyzed the association between longitudinal changes in frontal lobe white matter microstructure and decline in EF following RT in brain tumor patients on a prospective clinical trial.Materials and methodsDiffusion tensor imaging was obtained on 22 patients with brain tumors prior to RT, as well as 3- and 6-months post-RT, in a prospective, observational trial. Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were calculated within the superficial white matter (SWM) of the anterior cingulate (AC) and dorsolateral prefrontal cortex. Measures of cognitive flexibility, verbal fluency, and verbal set-shifting were obtained pre- and post-RT. Reliable change indices were calculated to determine significant baseline to 6-month EF changes.ResultsDecreases in FA and increases in MD were observed in the caudal AC (CAC) at 3-months post-RT. CAC changes were characterized by increased RD bilaterally. From baseline to 6-months post-RT, decreased FA and increased MD and RD of the CAC was associated with decline in verbal set-shifting ability, whereas increased MD in the CAC was associated with a decline in cognitive flexibility.ConclusionWhite matter underlying the AC may be particularly vulnerable to radiation effects. Early microstructural loss within AC SWM represents an important biomarker for EF decline, and dose reduction in this region may represent a possibility for cognitive preservation for patients receiving radiotherapy.

ObjectiveIndividuals with temporal lobe epilepsy (TLE) often experience diminished quality of life (QoL). Although comorbid depression is one of the most recognized predictors of poor QoL in TLE, impairments in verbal memory (VM) and executive functioning (EF), have also been identified as risk factors, independent of other biological and psychosocial factors. In this study, we examine the contribution of depression, VM, and EF to QoL in 52 well-characterized medically-refractory TLE patients.MethodsQuality of life was assessed with the Quality of Life in Epilepsy (QOLIE-31) questionnaire and depression symptomatology was evaluated with the Beck Depression Inventory-II (BDI-II). Tests of VM included the California Verbal Learning Test-Second Edition and the Wechsler Memory Scale-Third Edition, Logical Memory and Verbal Paired Associates subtests. Tests of EF included the D-KEFS Category Switching and Color Word Interference Tests, and the Trail Making Test. Using these measures, a principal component (PC) was derived for VM and for EF. Hierarchical multiple linear regression analysis was used to evaluate the unique contributions of BDI-II Score, VM PC, and EF PC to the QOLIE-31 Total Score, while controlling for important clinical and demographic variables. Post-hoc analyses were also performed to examine the contribution of each variable to specific QOLIE subscales.ResultsOf the clinical variables, only number of antiepileptic drugs contributed to QOLIE scores. As expected, severity of depressive symptoms was the most significant predictor of QOLIE Total Score, explaining 43.4% of the variance in total QoL. The VM PC did not contribute to the QOLIE Total Score. Rather, our EF PC emerged as an important predictor of QoL, explaining an additional 5% of the variance, after controlling for clinical variables, depression severity, and VM performance.SignificanceThese findings suggest that a combination of clinical, affective, and cognitive factors influence QoL in patients with TLE. Designing interventions with careful attention to depression and EF may be needed to optimize QoL in patients with refractory TLE and potentially other epilepsy syndromes.

BackgroundMolecular markers of WHO grade II/III glioma are known to have important prognostic and predictive implications and may be associated with unique imaging phenotypes. The purpose of this study is to determine whether three clinically relevant molecular markers identified in gliomas-IDH, 1p/19q, and MGMT status-show distinct quantitative MRI characteristics on FLAIR imaging.MethodsSixty-one patients with grade II/III gliomas who had molecular data and MRI available prior to radiation were included. Quantitative MRI features were extracted that measured tissue heterogeneity (homogeneity and pixel correlation) and FLAIR border distinctiveness (edge contrast; EC). T-tests were conducted to determine whether patients with different genotypes differ across the features. Logistic regression with LASSO regularization was used to determine the optimal combination of MRI and clinical features for predicting molecular subtypes.ResultsPatients with IDH wildtype tumors showed greater signal heterogeneity (p = 0.001) and lower EC (p = 0.008) within the FLAIR region compared to IDH mutant tumors. Among patients with IDH mutant tumors, 1p/19q co-deleted tumors had greater signal heterogeneity (p = 0.002) and lower EC (p = 0.005) compared to 1p/19q intact tumors. MGMT methylated tumors showed lower EC (p = 0.03) compared to the unmethylated group. The combination of FLAIR border distinctness, heterogeneity, and pixel correlation optimally classified tumors by IDH status.ConclusionQuantitative imaging characteristics of FLAIR heterogeneity and border pattern in grade II/III gliomas may provide unique information for determining molecular status at time of initial diagnostic imaging, which may then guide subsequent surgical and medical management.

ObjectiveRecall and recognition memory abilities are known to decline with increasing age, yet much of the evidence stems from studies that used simple measures of total target recall or recognition. The California Verbal Learning Test-Second Edition (CVLT-II) includes a new measure of recall discriminability that is analogous to recognition discriminability. These discriminability measures yield more thorough assessments of recall and recognition by accounting for intrusion and false positive errors, respectively. Research also has shown that women outperform men on verbal episodic memory tests. However, gender differences in recall and recognition discriminability and the age-by-gender interaction on these constructs have not been thoroughly examined.MethodCognitively healthy adults (N = 223) 18-91 years in age completed the CVLT-II. Multiple regression analyses were conducted to examine effects of age, gender, and the age-by-gender interaction on CVLT-II subtypes of recall and recognition discriminability.ResultsDiscriminability scores decreased with increasing age, and women outperformed men. There was an age-by-gender interaction on total, immediate, and free recall discriminability - the negative association between age and scores was stronger in men than in women. Exploratory analyses revealed an inverted U-shaped relationship between age and recall discriminability scores in women.ConclusionsThe present findings support and expand upon the extant literature on aging, gender, and verbal episodic memory, plus describe a novel age-by-gender interaction intrinsic to subtypes of recall discriminability. The findings suggest that methods traditionally used to assess recognition memory function can be used to elucidate age- and gender-related changes in recall ability across the adult lifespan.

In the initial online publication, the values in the last two rows in Table 1 were in the wrong rows. The original article has been corrected.

The 2016 World Health Organization Classification of Tumors of the Central Nervous System incorporates the use of molecular information into the classification of brain tumors, including grade II and III gliomas, providing new prognostic information that cannot be delineated based on histopathology alone. We hypothesized that these genomic subgroups may also have distinct imaging features. A retrospective single institution study was performed on 40 patients with pathologically proven infiltrating WHO grade II/III gliomas with a pre-treatment MRI and molecular data on IDH, chromosomes 1p/19q and ATRX status. Two blinded Neuroradiologists qualitatively assessed MR features. The relationship between each parameter and molecular subgroup (IDH-wildtype; IDH-mutant-1p/19q codeleted-ATRX intact; IDH-mutant-1p/19q intact-ATRX loss) was evaluated with Fisher's exact test. Progression free survival (PFS) was also analyzed. A border that could not be defined on FLAIR was most characteristic of IDH-wildtype tumors, whereas IDH-mutant tumors demonstrated either well-defined or slightly ill-defined borders (p = 0.019). Degree of contrast enhancement and presence of restricted diffusion did not distinguish molecular subgroups. Frontal lobe predominance was associated with IDH-mutant tumors (p = 0.006). The IDH-wildtype subgroup had significantly shorter PFS than the IDH-mutant groups (p

This study explored the relationships among multimodal imaging, clinical features, and language impairment in patients with left temporal lobe epilepsy (LTLE). Fourteen patients with LTLE and 26 controls underwent structural MRI, functional MRI, diffusion tensor imaging, and neuropsychological language tasks. Laterality indices were calculated for each imaging modality and a principal component (PC) was derived from language measures. Correlations were performed among imaging measures, as well as to the language PC. In controls, better language performance was associated with stronger left-lateralized temporo-parietal and temporo-occipital activations. In LTLE, better language performance was associated with stronger right-lateralized inferior frontal, temporo-parietal, and temporo-occipital activations. These right-lateralized activations in LTLE were associated with right-lateralized arcuate fasciculus fractional anisotropy. These data suggest that interhemispheric language reorganization in LTLE is associated with alterations to perisylvian white matter. These concurrent structural and functional shifts from left to right may help to mitigate language impairment in LTLE.

Radiation therapy (RT) is a critical treatment modality for patients with brain tumors, although it can cause adverse effects. Recent data suggest that brain RT is associated with dose-dependent cortical atrophy, which could disrupt neocortical networks. This study examines whether brain RT affects structural network properties in brain tumor patients. We applied graph theory to MRI-derived cortical thickness estimates of 54 brain tumor patients before and after RT. Cortical surfaces were parcellated into 68 regions and correlation matrices were created for patients pre- and post-RT. Significant changes in graph network properties were tested using nonparametric permutation tests. Linear regressions were conducted to measure the association between dose and changes in nodal network connectivity. Increases in transitivity, modularity, and global efficiency (n = 54, p

PurposeWe used multi-b-value diffusion models to characterize microstructural white matter changes after brain radiation into fast and slow components, in order to better understand the pathophysiology of radiation-induced tissue damage.MethodsFourteen patients were included in this retrospective analysis with imaging prior to, and at 1, 4-5, and 9-10 months after radiotherapy (RT). Diffusion signal decay within brain white matter was fit to a biexponential model to separate changes within the slow and fast components. Linear mixed-effects models were used to obtain estimates of the effect of radiation dose and time on the model parameters.ResultsWe found an increase of 0.11 × 10-4 and 0.14 × 10-4 mm2 /s in the fast diffusion coefficient per unit dose-time (Gy-month) in the longitudinal and transverse directions, respectively. By contrast, the longitudinal slow diffusion coefficient decreased independently of dose, by 0.18 × 10-4 , 0.16 × 10-4 , and 0.098 × 10-4 mm2 /s at 1, 4, and 9 months post-RT, respectively.ConclusionsRadiation-induced white matter changes in the first year following RT are driven by dose-dependent increases in the fast component and dose-independent decreases in the slow component.

Purpose and objectivesNeurologic deficits after brain radiation therapy (RT) typically involve decline in higher-order cognitive functions such as attention and memory rather than sensory defects or paralysis. We sought to determine whether areas of the cortex critical to cognition are selectively vulnerable to radiation dose-dependent atrophy.Methods and materialsWe measured change in cortical thickness in 54 primary brain tumor patients who underwent fractionated, partial brain RT. The study patients underwent high-resolution, volumetric magnetic resonance imaging (T1-weighted; T2 fluid-attenuated inversion recovery, FLAIR) before RT and 1 year afterward. Semiautomated software was used to segment anatomic regions of the cerebral cortex for each patient. Cortical thickness was measured for each region before RT and 1 year afterward. Two higher-order cortical regions of interest (ROIs) were tested for association between radiation dose and cortical thinning: entorhinal (memory) and inferior parietal (attention/memory). For comparison, 2 primary cortex ROIs were also tested: pericalcarine (vision) and paracentral lobule (somatosensory/motor). Linear mixed-effects analyses were used to test all other cortical regions for significant radiation dose-dependent thickness change. Statistical significance was set at α = 0.05 using 2-tailed tests.ResultsCortical atrophy was significantly associated with radiation dose in the entorhinal (P=.01) and inferior parietal ROIs (P=.02). By contrast, no significant radiation dose-dependent effect was found in the primary cortex ROIs (pericalcarine and paracentral lobule). In the whole-cortex analysis, 9 regions showed significant radiation dose-dependent atrophy, including areas responsible for memory, attention, and executive function (P≤.002).ConclusionsAreas of cerebral cortex important for higher-order cognition may be most vulnerable to radiation-related atrophy. This is consistent with clinical observations that brain radiation patients experience deficits in domains of memory, executive function, and attention. Correlations of regional cortical atrophy with domain-specific cognitive functioning in prospective trials are warranted.

BackgroundRadiation-induced cognitive impairment may be mediated by hippocampal damage, but the structural integrity of this region in tumor patients at baseline is unclear. Hippocampal volumes of 31 glioma patients prior to receiving radiotherapy were compared to a group of 34 healthy controls.Materials and methodsLeft and right hippocampi on T1-weighted pre-contrast magnetic resonance images were automatically segmented using Freesurfer, and visually inspected for segmentation errors. Normalized hippocampal volume for each subject was calculated as the sum of left and right hippocampal volumes divided by the estimated total intracranial volume. The normalized amygdala volume was similarly analyzed as a reference structure.ResultsA Wilcoxon rank-sum test showed a significant difference in normalized hippocampal volumes between patients and controls (mean value 0.499 vs. 0.524, p = .01). No statistically significant difference was found for the amygdala. A post-hoc analysis revealed a significant difference in normalized hippocampal volumes between patients who had experienced seizures (mean value: 0.480, p

PurposeAfter radiation therapy (RT) to the brain, patients often experience memory impairment, which may be partially mediated by damage to the hippocampus. Hippocampal sparing in RT planning is the subject of recent and ongoing clinical trials. Calculating appropriate hippocampal dose constraints would be improved by efficient in vivo measurements of hippocampal damage. In this study we sought to determine whether brain RT was associated with dose-dependent hippocampal atrophy.Methods and materialsHippocampal volume was measured with magnetic resonance imaging (MRI) in 52 patients who underwent fractionated, partial brain RT for primary brain tumors. Study patients had high-resolution, 3-dimensional volumetric MRI before and 1 year after RT. Images were processed using software with clearance from the US Food and Drug Administration and Conformité Européene marking for automated measurement of hippocampal volume. Automated results were inspected visually for accuracy. Tumor and surgical changes were censored. Mean hippocampal dose was tested for correlation with hippocampal atrophy 1 year after RT. Average hippocampal volume change was also calculated for hippocampi receiving high (>40 Gy) or low (

Restriction spectrum imaging (RSI) is a novel diffusion-weighted MRI technique that uses the mathematically distinct behavior of water diffusion in separable microscopic tissue compartments to highlight key aspects of the tissue microarchitecture with high conspicuity. RSI can be acquired in less than 5 min on modern scanners using a surface coil. Multiple field gradients and high b-values in combination with postprocessing techniques allow the simultaneous resolution of length-scale and geometric information, as well as compartmental and nuclear volume fraction filtering. RSI also uses a distortion correction technique and can thus be fused to high resolution T2-weighted images for detailed localization, which improves delineation of disease extension into critical anatomic structures. In this review, we discuss the acquisition, postprocessing, and interpretation of RSI for prostate MRI. We also summarize existing data demonstrating the applicability of RSI for prostate cancer detection, in vivo characterization, localization, and targeting.Level of evidence5 J. Magn. Reson. Imaging 2017;45:323-336.

Objective: This study evaluated the diagnostic performance of a widely available cognitive screener, the Montreal cognitive assessment (MoCA), to detect cognitive impairment in older patients (age ≥ 55) with epilepsy residing in the US, using the International Classification of Cognitive Disorders in Epilepsy (IC‐CoDE) as the gold standard. Methods: Fifty older adults with focal epilepsy completed the MoCA and neuropsychological measures of memory, language, executive function, and processing speed/attention. The IC‐CoDE taxonomy divided participants into IC‐CoDE Impaired and Intact groups. Sensitivity and specificity across several MoCA cutoffs were examined. Spearman correlations examined relationships between the MoCA total score and clinical and demographic variables and MoCA domain scores and individual neuropsychological tests. Results: IC‐CoDE impaired patients demonstrated significantly lower scores on the MoCA total, visuospatial/executive, naming, language, delayed recall, and orientation domain scores (Cohen's d range: 0.336–2.77). The recommended MoCA cutoff score < 26 had an overall accuracy of 72%, 88.2% sensitivity, and 63.6% specificity. A MoCA cutoff score < 24 yielded optimal sensitivity (70.6%) and specificity (78.8%), with overall accuracy of 76%. Higher MoCA total scores were associated with greater years of education (p = 0.016) and fewer antiseizure medications (p = 0.049). The MoCA memory domain was associated with several standardized measures of memory, MoCA language domain with category fluency, and MoCA abstraction domain with letter fluency. Significance: This study provides initial validation of the MoCA as a useful screening tool for older adults with epilepsy that can be used to identify patients who may benefit from comprehensive neuropsychological testing. Further, we demonstrate that a lower cutoff (i.e., <24) better captures cognitive impairment in older adults with epilepsy than the generally recommended cutoff and provides evidence for construct overlap between MoCA domains and standard neuropsychological tests. Critically, similar efforts in other regions of the world are needed. Plain Language Summary: The Montreal cognitive assessment (MoCA) can be a helpful tool to screen for cognitive impairment in older adults with epilepsy. We recommend that adults 55 or older with epilepsy who score less than 24 on the MoCA are referred to a neuropsychologist for a comprehensive evaluation to assess any changes in cognitive abilities and mood. [ABSTRACT FROM AUTHOR]

Objective: Efforts to understand the global variability in cognitive profiles in patients with epilepsy have been stymied by the lack of a standardized diagnostic system. This study examined the cross‐cultural applicability of the International Classification of Cognitive Disorders in Epilepsy (IC‐CoDE) in a cohort of patients with temporal lobe epilepsy (TLE) in India that was diverse in language, education, and cultural background. Methods: A cohort of 548 adults with TLE from Mumbai completed a presurgical comprehensive neuropsychological evaluation. The IC‐CoDE taxonomy was applied to derive cognitive phenotypes in the sample. Analyses of variance were conducted to examine differences in demographic and clinical characteristics across the phenotypes, and chi‐squared tests were used to determine whether the phenotype distribution differed between the Mumbai sample and published data from a multicenter US sample. Results: Using the IC‐CoDE criteria, 47% of our cohort showed an intact cognitive profile, 31% a single‐domain impairment, 16% a bidomain impairment, and 6% a generalized impairment profile. The distribution of cognitive phenotypes was similar between the Indian and US cohorts for the intact and bidomain phenotypes, but differed for the single and generalized domains. There was a larger proportion of patients with single‐domain impairment in the Indian cohort and a larger proportion with generalized impairment in the US cohort. Among patients with single‐domain impairment, a greater proportion exhibited memory impairment in the Indian cohort, whereas a greater proportion showed language impairment in the US sample, likely reflecting differences in language administration procedures and sample characteristics including a higher rate of mesial temporal sclerosis in the Indian sample. Significance: Our results demonstrate the applicability of IC‐CoDE in a group of culturally and linguistically diverse patients from India. This approach enhances our understanding of cognitive variability across cultures and enables harmonized and inclusive research into the neuropsychological aspects of epilepsy. [ABSTRACT FROM AUTHOR]