Brain alterations in regions associated with end-organ diabetic microvascular disease in diabetes mellitus: A UK Biobank study.

BACKGROUND: Diabetes mellitus (DM) is associated with structural grey matter alterations in the brain, including changes in the somatosensory and pain processing regions seen in association with diabetic peripheral neuropathy. In this case-controlled biobank study, we aimed to ascertain differences in grey and white matter anatomy in people with DM compared with non-diabetic controls (NDC). METHODS: This study utilises the UK Biobank prospective, population-based, multicentre study of UK residents. Participants with diabetes and age/gender-matched controls without diabetes were selected in a three-to-one ratio. We excluded people with underlying neurological/neurodegenerative disease. Whole brain, cortical, and subcortical volumes (188 regions) were compared between participants with diabetes against NDC corrected for age, sex, and intracranial volume using univariate regression models, with adjustment for multiple comparisons. Diffusion tensor imaging analysis of fractional anisotropy (FA) was performed along the length of 50 white matter tracts. RESULTS: We included 2404 eligible participants who underwent brain magnetic resonance imaging (NDC, n = 1803 and DM, n = 601). Participants with DM had a mean (±standard deviation) diagnostic duration of 18 ± 11 years, with adequate glycaemic control (HbA1C 52 ± 13 mmol/mol), low prevalence of microvascular complications (diabetic retinopathy prevalence, 5.8%), comparable cognitive function to controls but greater self-reported pain. Univariate volumetric analyses revealed significant reductions in grey matter volume (whole brain, total, and subcortical grey matter), with mean percentage differences ranging from 2.2% to 7% in people with DM relative to NDC (all p < 0.0002). The subcortical (bilateral cerebellar cortex, brainstem, thalamus, central corpus callosum, putamen, and pallidum) and cortical regions linked to sensorimotor (bilateral superior frontal, middle frontal, precentral, and postcentral gyri) and visual functions (bilateral middle and superior occipital gyri), all had lower grey matter volumes in people with DM relative to NDC. People with DM had significantly reduced FA along the length of the thalamocortical radiations, thalamostriatal projections, and commissural fibres of the corpus callosum (all; p < 0·001). INTERPRETATION: This analysis suggests that anatomic differences in brain regions are present in a cohort with adequately controlled glycaemia without prevalent microvascular disease when compared with volunteers without diabetes. We hypothesise that these differences may predate overt end-organ damage and complications such as diabetic neuropathy and retinopathy. Central nervous system alterations/neuroplasticity may occur early in the natural history of microvascular complications; therefore, brain imaging should be considered in future mechanistic and interventional studies of DM.

Clinical prediction models for treatment outcomes in newly diagnosed epilepsy: A systematic review.

Up to 35% of individuals diagnosed with epilepsy continue to have seizures despite treatment, commonly referred to as drug-resistant epilepsy. Uncontrolled seizures can directly, or indirectly, negatively impact an individual's quality of life. To inform clinical management and life decisions, it is important to be able to predict the likelihood of seizure control. Those likely to achieve seizure control will be able to return sooner to their usual work and leisure activities and require less follow-up, whereas those with a poor prognosis will need more frequent clinical attendance and earlier consideration of epilepsy surgery. This is a systematic review aimed at identifying demographic, clinical, physiological (e.g., electroencephalographic), and imaging (e.g., magnetic resonance imaging) factors that may be predictive of treatment outcomes in patients with newly diagnosed epilepsy (NDE). MEDLINE and Embase were searched for prediction models of treatment outcomes in patients with NDE. Study characteristics were extracted and subjected to assessment of risk of bias (and applicability concerns) using the PROBAST (Prediction Model Risk of Bias Assessment Tool) tool. Baseline variables associated with treatment outcomes are reported as prognostic factors. After screening, 48 models were identified in 32 studies, which generally scored low for concerns of applicability, but universally scored high for susceptibility to bias. Outcomes reported fit broadly into four categories: drug resistance, short-term treatment response, seizure remission, and mortality. Prognostic factors were also heterogenous, but the predictors that were commonly significantly associated with outcomes were those related to seizure characteristics/types, epilepsy history, and age at onset. Antiseizure medication response was often included as a baseline variable, potentially obscuring other factor relationships at baseline. Currently, outcome prediction models for NDE demonstrate a high risk of bias. Model development could be improved with a stronger adherence to recommended TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) practices. Furthermore, we outline actionable changes to common practices that are intended to improve the overall quality of prediction model development in NDE.

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.

Automatic and manual segmentation of the piriform cortex: Method development and validation in patients with temporal lobe epilepsy and Alzheimer's disease.

The piriform cortex (PC) is located at the junction of the temporal and frontal lobes. It is involved physiologically in olfaction as well as memory and plays an important role in epilepsy. Its study at scale is held back by the absence of automatic segmentation methods on MRI. We devised a manual segmentation protocol for PC volumes, integrated those manually derived images into the Hammers Atlas Database (n = 30) and used an extensively validated method (multi-atlas propagation with enhanced registration, MAPER) for automatic PC segmentation. We applied automated PC volumetry to patients with unilateral temporal lobe epilepsy with hippocampal sclerosis (TLE; n = 174 including n = 58 controls) and to the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI; n = 151, of whom with mild cognitive impairment (MCI), n = 71; Alzheimer's disease (AD), n = 33; controls, n = 47). In controls, mean PC volume was 485 mm3 on the right and 461 mm3 on the left. Automatic and manual segmentations overlapped with a Jaccard coefficient (intersection/union) of ~0.5 and a mean absolute volume difference of ~22 mm3 in healthy controls, ~0.40/ ~28 mm3 in patients with TLE, and ~ 0.34/~29 mm3 in patients with AD. In patients with TLE, PC atrophy lateralised to the side of hippocampal sclerosis (p < .001). In patients with MCI and AD, PC volumes were lower than those of controls bilaterally (p < .001). Overall, we have validated automatic PC volumetry in healthy controls and two types of pathology. The novel finding of early atrophy of PC at the stage of MCI possibly adds a novel biomarker. PC volumetry can now be applied at scale.

Cortical morphometric vulnerability to generalised epilepsy reflects chromosome- and cell type-specific transcriptomic signatures.

AIMS: Generalised epilepsy is thought to involve distributed brain networks. However, the molecular and cellular factors that render different brain regions more vulnerable to epileptogenesis remain largely unknown. We aimed to investigate epilepsy-related morphometric similarity network (MSN) abnormalities at the macroscale level and their relationships with microscale gene expressions at the microscale level. METHODS: We compared the MSN of genetic generalised epilepsy with generalised tonic-clonic seizure patients (GGE-GTCS, n = 101) to demographically matched healthy controls (HC, n = 150). Cortical MSNs were estimated by combining seven morphometric features derived from structural magnetic resonance imaging for each individual. Regional gene expression profiles were derived from brain-wide microarray measurements provided by the Allen Human Brain Atlas. RESULTS: GGE-GTCS patients exhibited decreased regional MSNs in primary motor, prefrontal and temporal regions and increases in occipital, insular and posterior cingulate cortices, when compared with the HC. These case-control neuroimaging differences were validated using split-half analyses and were not affected by medication or drug response effects. When assessing associations with gene expression, genes associated with GGE-GTCS-related MSN differences were enriched in several biological processes, including 'synapse organisation', 'neurotransmitter transport' pathways and excitatory/inhibitory neuronal cell types. Collectively, the GGE-GTCS-related cortical vulnerabilities were associated with chromosomes 4, 5, 11 and 16 and were dispersed bottom-up at the cellular, pathway and disease levels, which contributed to epileptogenesis, suggesting diverse neurobiologically relevant enrichments in GGE-GTCS. CONCLUSIONS: By bridging the gaps between transcriptional signatures and in vivo neuroimaging, we highlighted the importance of using MSN abnormalities of the human brain in GGE-GTCS patients to investigate disease-relevant genes and biological processes.

From basic sciences and engineering to epileptology: A translational approach.

Collaborative efforts between basic scientists, engineers, and clinicians are enabling translational epileptology. In this article, we summarize the recent advances presented at the International Conference for Technology and Analysis of Seizures (ICTALS 2022): (1) novel developments of structural magnetic resonance imaging; (2) latest electroencephalography signal-processing applications; (3) big data for the development of clinical tools; (4) the emerging field of hyperdimensional computing; (5) the new generation of artificial intelligence (AI)-enabled neuroprostheses; and (6) the use of collaborative platforms to facilitate epilepsy research translation. We highlight the promise of AI reported in recent investigations and the need for multicenter data-sharing initiatives.

Resting state functional connectivity demonstrates increased segregation in bilateral temporal lobe epilepsy.

OBJECTIVE: Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. An increasingly identified subset of patients with TLE consists of those who show bilaterally independent temporal lobe seizures. The purpose of this study was to leverage network neuroscience to better understand the interictal whole brain network of bilateral TLE (BiTLE). METHODS: In this study, using a multicenter resting state functional magnetic resonance imaging (rs-fMRI) data set, we constructed whole-brain functional networks of 19 patients with BiTLE, and compared them to those of 75 patients with unilateral TLE (UTLE). We quantified resting-state, whole-brain topological properties using metrics derived from network theory, including clustering coefficient, global efficiency, participation coefficient, and modularity. For each metric, we computed an average across all brain regions, and iterated this process across network densities. Curves of network density vs each network metric were compared between groups. Finally, we derived a combined metric, which we term the "integration-segregation axis," by combining whole-brain average clustering coefficient and global efficiency curves, and applying principal component analysis (PCA)-based dimensionality reduction. RESULTS: Compared to UTLE, BiTLE had decreased global efficiency (p = .031), and decreased whole brain average participation coefficient across a range of network densities (p = .019). Modularity maximization yielded a larger number of smaller communities in BiTLE than in UTLE (p = .020). Differences in network properties separate BiTLE and UTLE along the integration-segregation axis, with regions within the axis having a specificity of up to 0.87 for BiTLE. Along the integration-segregation axis, UTLE patients with poor surgical outcomes were distributed in the same regions as BiTLE, and network metrics confirmed similar patterns of increased segregation in both BiTLE and poor outcome UTLE. SIGNIFICANCE: Increased interictal whole-brain network segregation, as measured by rs-fMRI, is specific to BiTLE, as well as poor surgical outcome UTLE, and may assist in non-invasively identifying this patient population prior to intracranial electroencephalography or device implantation.

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.

Midbrain structure volume, estimated myelin and functional connectivity in idiopathic generalised epilepsy.

BACKGROUND: Structural and functional neuroimaging studies often overlook lower basal ganglia structures located in and adjacent to the midbrain due to poor contrast on clinically acquired T1-weighted scans. Here, we acquired T1-weighted, T2-weighted, and resting-state fMRI scans to investigate differences in volume, estimated myelin content and functional connectivity of the substantia nigra (SN), subthalamic nuclei (SubTN) and red nuclei (RN) of the midbrain in IGE. METHODS: Thirty-three patients with IGE (23 refractory, 10 non-refractory) and 39 age and sex-matched healthy controls underwent MR imaging. Midbrain structures were automatically segmented from T2-weighted images and structural volumes were calculated. The estimated myelin content for each structure was determined using a T1-weighted/T2-weighted ratio method. Resting-state functional connectivity analysis of midbrain structures (seed-based) was performed using the CONN toolbox. RESULTS: An increased volume of the right RN was found in IGE and structural volumes of the right SubTN differed between patients with non-refractory and refractory IGE. However, no volume findings survived corrections for multiple comparisons. No myelin alterations of midbrain structures were found for any subject groups. We found functional connectivity alterations including significantly decreased connectivity between the left SN and the thalamus and significantly increased connectivity between the right SubTN and the superior frontal gyrus in IGE. CONCLUSIONS: We report volumetric and functional connectivity alterations of the midbrain in patients with IGE. We postulate that potential increases in structural volumes are due to increased iron deposition that impacts T2-weighted contrast. These findings are consistent with previous studies demonstrating pathophysiological abnormalities of the lower basal ganglia in animal models of generalised epilepsy.

High b-value diffusion tractography: Abnormal axonal network organization associated with medication-refractory epilepsy.

Diffusion magnetic resonance imaging (dMRI) tractography has played a critical role in characterizing patterns of aberrant brain network reorganization among patients with epilepsy. However, the accuracy of dMRI tractography is hampered by the complex biophysical properties of white matter tissue. High b-value diffusion imaging overcomes this limitation by better isolating axonal pathways. In this study, we introduce tractography derived from fiber ball imaging (FBI), a high b-value approach which excludes non-axonal signals, to identify atypical neuronal networks in patients with epilepsy. Specifically, we compared network properties obtained from multiple diffusion tractography approaches (diffusion tensor imaging, diffusion kurtosis imaging, FBI) in order to assess the pathophysiological relevance of network rearrangement in medication-responsive vs. medication-refractory adults with focal epilepsy. We show that drug-resistant epilepsy is associated with increased global network segregation detected by FBI-based tractography. We propose exploring FBI as a clinically feasible alternative to quantify topological changes that could be used to track disease progression and inform on clinical outcomes.

Event-based modeling in temporal lobe epilepsy demonstrates progressive atrophy from cross-sectional data.

OBJECTIVE: Recent 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. METHODS: We 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. RESULTS: In 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. SIGNIFICANCE: From 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.

Increased volume of cerebral oedema is associated with risk of acute seizure activity and adverse neurological outcomes in encephalitis - regional and volumetric analysis in a multi-centre cohort.

BACKGROUND: Seizures can occur unpredictably in patients with acute encephalitis syndrome (AES), and many suffer from poor long-term neurological sequelae. Establishing factors associated with acute seizures risk and poor outcomes could support clinical care. We aimed to conduct regional and volumetric analysis of cerebral oedema on magnetic resonance imaging (MRI) in patients with AES. We assessed the relationship of brain oedema with acute seizure activity and long-term neurological outcome. METHODS: In a multi-centre cohort study, adults and children presenting with an AES were recruited in the UK. The clinical and brain MRI data were retrospectively reviewed. The outcomes variables were inpatient acute seizure activity and neurological disability at six-months post-discharge. A poor outcome was defined as a Glasgow outcome score (GOS) of 1-3. We quantified regional brain oedema on MRI through stereological examination of T2-weighted images using established methodology by independent and blinded assessors. Clinical and neuroimaging variables were analysed by multivariate logistic regression to assess for correlation with acute seizure activity and outcome. RESULTS: The study cohort comprised 69 patients (mean age 31.8 years; 53.6% female), of whom 41 (59.4%) had acute seizures as inpatients. A higher Glasgow coma scale (GCS) score on admission was a negative predictor of seizures (OR 0.61 [0.46-0.83], p = 0.001). Even correcting for GCS on admission, the presence of cortical oedema was a significant risk factor for acute seizure activity (OR 5.48 [1.62-18.51], p = 0.006) and greater volume of cerebral oedema in these cortical structures increased the risk of acute seizures (OR 1.90 [1.12-3.21], p = 0.017). At six-month post-discharge, 21 (30.4%) had a poor neurological outcome. Herpes simplex virus encephalitis was associated with higher risk of poor outcomes in univariate analysis (OR 3.92 [1.08-14.20], p = 0.038). When controlling for aetiology, increased volume of cerebral oedema was an independent risk factor for adverse neurological outcome at 6 months (OR 1.73 [1.06-2.83], p = 0.027). CONCLUSIONS: Both the presence and degree of cerebral oedema on MRIs of patients with AES may help identify patients at risk of acute seizure activity and subsequent long-term morbidity.

Automated subcortical volume estimation from 2D MRI in epilepsy and implications for clinical trials.

PURPOSE: Most techniques used for automatic segmentation of subcortical brain regions are developed for three-dimensional (3D) MR images. MRIs obtained in non-specialist hospitals may be non-isotropic and two-dimensional (2D). Automatic segmentation of 2D images may be challenging and represents a lost opportunity to perform quantitative image analysis. We determine the performance of a modified subcortical segmentation technique applied to 2D images in patients with idiopathic generalised epilepsy (IGE). METHODS: Volume estimates were derived from 2D (0.4 × 0.4 × 3 mm) and 3D (1 × 1x1mm) T1-weighted acquisitions in 31 patients with IGE and 39 healthy controls. 2D image segmentation was performed using a modified FSL FIRST (FMRIB Integrated Registration and Segmentation Tool) pipeline requiring additional image reorientation, cropping, interpolation and brain extraction prior to conventional FIRST segmentation. Consistency between segmentations was assessed using Dice coefficients and volumes across both approaches were compared between patients and controls. The influence of slice thickness on consistency was further assessed using 2D images with slice thickness increased to 6 mm. RESULTS: All average Dice coefficients showed excellent agreement between 2 and 3D images across subcortical structures (0.86-0.96). Most 2D volumes were consistently slightly lower compared to 3D volumes. 2D images with increased slice thickness showed lower agreement with 3D images with lower Dice coefficients (0.55-0.83). Significant volume reduction of the left and right thalamus and putamen was observed in patients relative to controls across 2D and 3D images. CONCLUSION: Automated subcortical volume estimation of 2D images with a resolution of 0.4 × 0.4x3mm using a modified FIRST pipeline is consistent with volumes derived from 3D images, although this consistency decreases with an increased slice thickness. Thalamic and putamen atrophy has previously been reported in patients with IGE. Automated subcortical volume estimation from 2D images is feasible and most reliable at using in-plane acquisitions greater than 1 mm x 1 mm and provides an opportunity to perform quantitative image analysis studies in clinical trials.

Probabilistic mapping of thalamic nuclei and thalamocortical functional connectivity in idiopathic generalised epilepsy.

It is well established that abnormal thalamocortical systems play an important role in the generation and maintenance of primary generalised seizures. However, it is currently unknown which thalamic nuclei and how nuclear-specific thalamocortical functional connectivity are differentially impacted in patients with medically refractory and non-refractory idiopathic generalised epilepsy (IGE). In the present study, we performed structural and resting-state functional magnetic resonance imaging (MRI) in patients with refractory and non-refractory IGE, segmented the thalamus into constituent nuclear regions using a probabilistic MRI segmentation method and determined thalamocortical functional connectivity using seed-to-voxel connectivity analyses. We report significant volume reduction of the left and right anterior thalamic nuclei only in patients with refractory IGE. Compared to healthy controls, patients with refractory and non-refractory IGE had significant alterations of functional connectivity between the centromedian nucleus and cortex, but only patients with refractory IGE had altered cortical connectivity with the ventral lateral nuclear group. Patients with refractory IGE had significantly increased functional connectivity between the left and right ventral lateral posterior nuclei and cortical regions compared to patients with non-refractory IGE. Cortical effects were predominantly located in the frontal lobe. Atrophy of the anterior thalamic nuclei and resting-state functional hyperconnectivity between ventral lateral nuclei and cerebral cortex may be imaging markers of pharmacoresistance in patients with IGE. These structural and functional abnormalities fit well with the known importance of thalamocortical systems in the generation and maintenance of primary generalised seizures, and the increasing recognition of the importance of limbic pathways in IGE.

Fiber ball white matter modeling in focal epilepsy.

Multicompartment diffusion magnetic resonance imaging (MRI) approaches are increasingly being applied to estimate intra-axonal and extra-axonal diffusion characteristics in the human brain. Fiber ball imaging (FBI) and its extension fiber ball white matter modeling (FBWM) are such recently described multicompartment approaches. However, these particular approaches have yet to be applied in clinical cohorts. The modeling of several diffusion parameters with interpretable biological meaning may offer the development of new, noninvasive biomarkers of pharmacoresistance in epilepsy. In the present study, we used FBI and FBWM to evaluate intra-axonal and extra-axonal diffusion properties of white matter tracts in patients with longstanding focal epilepsy. FBI/FBWM diffusion parameters were calculated along the length of 50 white matter tract bundles and statistically compared between patients with refractory epilepsy, nonrefractory epilepsy and controls. We report that patients with chronic epilepsy had a widespread distribution of extra-axonal diffusivity relative to controls, particularly in circumscribed regions along white matter tracts projecting to cerebral cortex from thalamic, striatal, brainstem, and peduncular regions. Patients with refractory epilepsy had significantly greater markers of extra-axonal diffusivity compared to those with nonrefractory epilepsy. The extra-axonal diffusivity alterations in patients with epilepsy observed in the present study could be markers of neuroinflammatory processes or a reflection of reduced axonal density, both of which have been histologically demonstrated in focal epilepsy. FBI is a clinically feasible MRI approach that provides the basis for more interpretive conclusions about the microstructural environment of the brain and may represent a unique biomarker of pharmacoresistance in epilepsy.

Temporal Lobe Epilepsy Surgical Outcomes Can Be Inferred Based on Structural Connectome Hubs: A Machine Learning Study.

OBJECTIVE: Medial temporal lobe epilepsy (TLE) is the most common form of medication-resistant focal epilepsy in adults. Despite removal of medial temporal structures, more than one-third of patients continue to have disabling seizures postoperatively. Seizure refractoriness implies that extramedial regions are capable of influencing the brain network and generating seizures. We tested whether abnormalities of structural network integration could be associated with surgical outcomes. METHODS: Presurgical magnetic resonance images from 121 patients with drug-resistant TLE across 3 independent epilepsy centers were used to train feed-forward neural network models based on tissue volume or graph-theory measures from whole-brain diffusion tensor imaging structural connectomes. An independent dataset of 47 patients with TLE from 3 other epilepsy centers was used to assess the predictive values of each model and regional anatomical contributions toward surgical treatment results. RESULTS: The receiver operating characteristic area under the curve based on regional betweenness centrality was 0.88, significantly higher than a random model or models based on gray matter volumes, degree, strength, and clustering coefficient. Nodes most strongly contributing to the predictive models involved the bilateral parahippocampal gyri, as well as the superior temporal gyri. INTERPRETATION: Network integration in the medial and lateral temporal regions was related to surgical outcomes. Patients with abnormally integrated structural network nodes were less likely to achieve seizure freedom. These findings are in line with previous observations related to network abnormalities in TLE and expand on the notion of underlying aberrant plasticity. Our findings provide additional information on the mechanisms of surgical refractoriness. ANN NEUROL 2020;88:970-983.

White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA-Epilepsy study.

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 < 0.001). Across 'all epilepsies' lower fractional anisotropy was observed in most fibre tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. There were also less robust increases in mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Individuals with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced reductions in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and increased mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of diffusion abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibres in a large multicentre study of epilepsy. Overall, patients with epilepsy showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding more detailed insights into pathological substrates that may explain cognitive and psychiatric co-morbidities and be used to guide biomarker studies of treatment outcomes and/or genetic research.

Cortical disconnection in temporal lobe epilepsy.

A critical concept in neurology is cortical disconnection, in which seemingly normal gray matter can have reduced function due to loss of white matter (WM) connections. White matter damage has been extensively described in temporal lobe epilepsy (TLE), but the anatomical distribution of cortical disconnection in TLE is not fully characterized. Here, we studied 221 participants (64 left-TLE, 55 right-TLE, 102 controls) from three different epilepsy treatment centers. We employed a group connectometry diffusion imaging tractography approach to identify WM fibers with reduced integrity in TLE. We then assessed the anatomical distribution of the gray matter endpoint projections of abnormal fibers to map the anatomical pattern of disconnections. As expected, left- and right-TLE were associated with multiple WM pathways with reduced integrity, which were associated with extensive cortical disconnection involving predominantly limbic structures. Controlling for medial temporal gray matter atrophy, cortical disconnection of the left cingulum and the thalamus as well as disconnection of the bilateral putamen and the amygdala was associated with lower verbal memory immediate recall. In conclusion, our results support that cortical disconnection is an underappreciated but pervasive phenomenon in TLE, and cortical disconnection of limbic structures beyond the medial temporal regions is related to verbal memory performance.

The ENIGMA-Epilepsy working group: Mapping disease from large data sets.

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.

Interictal structural and functional connectivity in idiopathic generalized epilepsy: A systematic review of graph theoretical studies.

The evaluation of the role of anomalous neuronal networks in epilepsy using a graph theoretical approach is of growing research interest. There is currently no consensus on optimal methods for performing network analysis, and it is possible that variations in study methodology account for diverging findings. This review focuses on global functional and structural interictal network characteristics in people with idiopathic generalized epilepsy (IGE) with the aim of appraising the methodological approaches used and assessing for meaningful consensus. Thirteen studies were included in the review. Data were heterogenous and not suitable for meta-analysis. Overall, there is a suggestion that the cerebral neuronal networks of people with IGE have different global structural and functional characteristics to people without epilepsy. However, the nature of the aberrations is inconsistent with some studies demonstrating a more regular network configuration in IGE, and some, a more random topology. There is greater consistency when different data modalities and connectivity subtypes are compared separately, with a tendency towards increased small-worldness of networks in functional electroencephalography/magnetoencephalography (EEG/MEG) studies and decreased small-worldness of networks in structural studies. Prominent variation in study design at all stages is likely to have contributed to differences in study outcomes. Despite increasing literature surrounding neuronal network analysis, systematic methodological studies are lacking. Absence of consensus in this area significantly limits comparison of results from different studies, and the ability to draw firm conclusions about network characteristics in IGE.