Chapter

Computational Neuroimaging of Epilepsy

If you want to read the PDF, try requesting it from the authors.

Abstract

Imaging Biomarkers in Epilepsy - edited by Andrea Bernasconi January 2019

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
Background Detailed neuropathological information on the structural brain lesions underlying seizures is valuable for understanding drug-resistant focal epilepsy. Methods We report the diagnoses made on the basis of resected brain specimens from 9523 patients who underwent epilepsy surgery for drug-resistant seizures in 36 centers from 12 European countries over 25 years. Histopathological diagnoses were determined through examination of the specimens in local hospitals (41%) or at the German Neuropathology Reference Center for Epilepsy Surgery (59%). Results The onset of seizures occurred before 18 years of age in 75.9% of patients overall, and 72.5% of the patients underwent surgery as adults. The mean duration of epilepsy before surgical resection was 20.1 years among adults and 5.3 years among children. The temporal lobe was involved in 71.9% of operations. There were 36 histopathological diagnoses in seven major disease categories. The most common categories were hippocampal sclerosis, found in 36.4% of the patients (88.7% of cases were in adults), tumors (mainly ganglioglioma) in 23.6%, and malformations of cortical development in 19.8% (focal cortical dysplasia was the most common type, 52.7% of cases of which were in children). No histopathological diagnosis could be established for 7.7% of the patients. Conclusions In patients with drug-resistant focal epilepsy requiring surgery, hippocampal sclerosis was the most common histopathological diagnosis among adults, and focal cortical dysplasia was the most common diagnosis among children. Tumors were the second most common lesion in both groups. (Funded by the European Union and others.)
Article
Full-text available
The human neocortex is organized radially into six layers which differ in their myelination and the density and arrangement of neuronal cells. This cortical cyto- and myeloarchitecture plays a central role in the anatomical and functional neuroanatomy but is primarily accessible through invasive histology only. To overcome this limitation, several non-invasive MRI approaches have been, and are being, developed to resolve the anatomical cortical layers. As a result, recent studies on large populations and structure-function relationships at the laminar level became possible. Early proof-of-concept studies targeted conspicuous laminar structures such as the stria of Gennari in the primary visual cortex. Recent work characterized the laminar structure outside the visual cortex, investigated the relationship between laminar structure and function, and demonstrated layer-specific maturation effects. This paper reviews the methods and in-vivo MRI studies on the anatomical layers in the human cortex based on conventional and quantitative MRI (excluding diffusion imaging). A focus is on the related challenges, promises and potential future developments. The rapid development of MRI scanners, motion correction techniques, analysis methods and biophysical modeling promise to overcome the challenges of spatial resolution, precision and specificity of systematic imaging of cortical laminae.
Article
Full-text available
Neuroimaging studies of malformations of cortical development have mainly focused on the characterization of the primary lesional substrate, while whole-brain investigations remain scarce. Our purpose was to assess large-scale brain organization in prevalent cortical malformations. Based on experimental evidence suggesting that distributed effects of focal insults are modulated by stages of brain development, we postulated differential patterns of network anomalies across subtypes of malformations. We studied a cohort of patients with focal cortical dysplasia type II (n = 63), subcortical nodular heterotopia (n = 44), and polymicrogyria (n = 34), and compared them to 82 age- and sex-matched controls. Graph theoretical analysis of structural covariance networks indicated a consistent rearrangement towards a regularized architecture characterized by increased path length and clustering, as well as disrupted rich-club topology, overall suggestive of inefficient global and excessive local connectivity. Notably, we observed a gradual shift in network reconfigurations across subgroups, with only subtle changes in focal cortical dysplasia type II, moderate effects in heterotopia and maximal effects in polymicrogyria. Analysis of resting state functional connectivity also revealed gradual network changes, with most marked rearrangement in polymicrogyria; contrary to findings in the structural domain, however, functional architecture was characterized by decreases in both local and global parameters. Diverging results in the structural and functional domain were supported by formal structure–function coupling analysis. Our findings support the concept that time of insult during corticogenesis impacts the severity of topological network reconfiguration. Specifically, late-stage malformations, typified by polymicrogyria, may selectively disrupt the formation of large-scale cortico-cortical networks and thus lead to a more profound impact on whole-brain organization than early stage disturbances of predominantly radial migration patterns observed in cortical dysplasia type II, which likely affect a relatively confined cortical territory.
Article
Full-text available
This companion paper to the introduction of the International League Against Epilepsy (ILAE) 2017 classification of seizure types provides guidance on how to employ the classification. Illustration of the classification is enacted by tables, a glossary of relevant terms, mapping of old to new terms, suggested abbreviations, and examples. Basic and extended versions of the classification are available, depending on the desired degree of detail. Key signs and symptoms of seizures (semiology) are used as a basis for categories of seizures that are focal or generalized from onset or with unknown onset. Any focal seizure can further be optionally characterized by whether awareness is retained or impaired. Impaired awareness during any segment of the seizure renders it a focal impaired awareness seizure. Focal seizures are further optionally characterized by motor onset signs and symptoms: atonic, automatisms, clonic, epileptic spasms, or hyperkinetic, myoclonic, or tonic activity. Nonmotor-onset seizures can manifest as autonomic, behavior arrest, cognitive, emotional, or sensory dysfunction. The earliest prominent manifestation defines the seizure type, which might then progress to other signs and symptoms. Focal seizures can become bilateral tonic-clonic. Generalized seizures engage bilateral networks from onset. Generalized motor seizure characteristics comprise atonic, clonic, epileptic spasms, myoclonic, myoclonic-atonic, myoclonic-tonic-clonic, tonic, or tonic-clonic. Nonmotor (absence) seizures are typical or atypical, or seizures that present prominent myoclonic activity or eyelid myoclonia. Seizures of unknown onset may have features that can still be classified as motor, nonmotor, tonic-clonic, epileptic spasms, or behavior arrest. This "users' manual" for the ILAE 2017 seizure classification will assist the adoption of the new system.
Article
Full-text available
Over the last decade, the field of imaging genomics has combined high-throughput genotype data with quantitative magnetic resonance imaging (QMRI) measures to identify genes associated with brain structure, cognition, and several brain-related disorders. Despite its successful application in different psychiatric and neurological disorders, the field has yet to be advanced in epilepsy. In this article we examine the relevance of imaging genomics for future genetic studies in epilepsy from three perspectives. First, we discuss prior genome-wide genetic mapping efforts in epilepsy, considering the possibility that some studies may have been constrained by inherent theoretical and methodological limitations of the genome-wide association study (GWAS) method. Second, we offer a brief overview of the imaging genomics paradigm, from its original inception, to its role in the discovery of important risk genes in a number of brain-related disorders, and its successful application in large-scale multinational research networks. Third, we provide a comprehensive review of past studies that have explored the eligibility of brain QMRI traits as endophenotypes for epilepsy. While the breadth of studies exploring QMRI-derived endophenotypes in epilepsy remains narrow, robust syndrome-specific neuroanatomical QMRI traits have the potential to serve as accessible and relevant intermediate phenotypes for future genetic mapping efforts in epilepsy.
Article
Full-text available
Background and Purpose: Automated subfield volumetry of hippocampus is desirable for use in temporal lobe epilepsy (TLE), but its utility has not been established. Automatic segmentation of hippocampal subfields (ASHS) and the new version of FreeSurfer software (ver.6.0) using high-resolution T2-weighted MR imaging are candidates for this volumetry. The aim of this study was to evaluate hippocampal subfields in TLE patients using ASHS as well as the old and new versions of FreeSurfer. Materials and Methods: We recruited 50 consecutive unilateral TLE patients including 25 with hippocampal sclerosis (TLE-HS) and 25 without obvious etiology (TLE-nonHS). All patients and 45 healthy controls underwent high-resolution T2-weighted and 3D-volume T1-weighted MRI scanning. We analyzed all of their MR images by FreeSurfer ver.5.3, ver.6.0 and ASHS. For each subfield, normalized _z_-scores were calculated and compared among groups. Results: In TLE-HS groups, ASHS and FreeSurfer ver.6.0 revealed maximal _z_-scores in ipsilateral cornu ammonis (CA) 1, CA4 and dentate gyrus (DG), whereas in FreeSurfer ver.5.3 ipsilateral subiculum showed maximal z-scores. In TLE-nonHS group, there was no significant volume reduction by either ASHS or FreeSurfer. Conclusions: ASHS and the new version of FreeSurfer may have an advantage in compatibility with existing histopathological knowledge in TLE patients with HS compared to the old version of FreeSurfer (ver.5.3), although further investigations with pathological findings and/or surgical outcomes are desirable.
Article
Full-text available
The hippocampus is composed of distinct anatomical subregions that participate in multiple cognitive processes and are differentially affected in prevalent neurological and psychiatric conditions. Advances in high-field MRI allow for the non-invasive identification of hippocampal substructure. These approaches, however, demand time-consuming manual segmentation that relies heavily on anatomical expertise. Here, we share manual labels and associated high-resolution MRI data (MNI-HISUB25; submillimetric T1-and T2-weighted images, detailed sequence information, and stereotaxic probabilistic anatomical maps) based on 25 healthy subjects. Data were acquired on a widely available 3 Tesla MRI system using a 32 phased-array head coil. The protocol divided the hippocampal formation into three subregions: subicular complex, merged Cornu Ammonis 1, 2 and 3 (CA1-3) subfields, and CA4-dentate gyrus (CA4-DG). Segmentation was guided by consistent intensity and morphology characteristics of the densely myelinated molecular layer together with few geometry-based boundaries flexible to overall mesiotemporal anatomy, and achieved excellent intra-/inter-rater reliability (Dice index ≥90/87%). The dataset can inform neuroimaging assessments of the mesiotemporal lobe and help to develop segmentation algorithms relevant for basic and clinical neurosciences.
Article
Full-text available
Automated analysis of MRI data of the subregions of the hippocampus requires computational atlases built at a higher resolution than those that are typically used in current neuroimaging studies. Here we describe the construction of a statistical atlas of the hippocampal formation at the subregion level using ultra-high resolution, ex vivo MRI. Fifteen autopsy samples were scanned at 0.13 mm isotropic resolution (on average) using customized hardware. The images were manually segmented into 13 different hippocampal substructures using a protocol specifically designed for this study; precise delineations were made possible by the extraordinary resolution of the scans. In addition to the subregions, manual annotations for neighboring structures (e.g., amygdala, cortex) were obtained from a separate dataset of in vivo, T1-weighted MRI scans of the whole brain (1 mm resolution). The manual labels from the in vivo and ex vivo data were combined into a single computational atlas of the hippocampal formation with a novel atlas building algorithm based on Bayesian inference. The resulting atlas can be used to automatically segment the hippocampal subregions in structural MRI images, using an algorithm that can analyze multimodal data and adapt to variations in MRI contrast due to differences in acquisition hardware or pulse sequences. The applicability of the atlas, which we will release as part of FreeSurfer (version 6.0), is demonstrated with experiments on three different publicly available datasets with different types of MRI contrast. The results show that the atlas and companion segmentation method: 1) can segment T1 and T2 images, as well as their combination, 2) replicate findings on mild cognitive impairment based on high-resolution T2 data, and 3) can discriminate between Alzheimer's disease subjects and elderly controls with 88% accuracy in standard resolution (1 mm) T1 data, significantly outperforming the atlas in FreeSurfer version 5.3 (86% accuracy) and classification based on whole hippocampal volume (82% accuracy). Copyright © 2015. Published by Elsevier Inc.
Article
Full-text available
Objective There are competing explanations for persistent postoperative seizures after temporal lobe surgery. One is that 1 or more particular subtypes of mesial temporal lobe epilepsy (mTLE) exist that are particularly resistant to surgery. We sought to identify a common brain structural and connectivity alteration in patients with persistent postoperative seizures using preoperative quantitative magnetic resonance imaging and diffusion tensor imaging (DTI).Methods We performed a series of studies in 87 patients with mTLE (47 subsequently rendered seizure free, 40 who continued to experience postoperative seizures) and 80 healthy controls. We investigated the relationship between imaging variables and postoperative seizure outcome. All patients had unilateral temporal lobe seizure onset, had ipsilateral hippocampal sclerosis as the only brain lesion, and underwent amygdalohippocampectomy.ResultsQuantitative imaging factors found not to be significantly associated with persistent seizures were volumes of ipsilateral and contralateral mesial temporal lobe structures, generalized brain atrophy, and extent of resection. There were nonsignificant trends for larger amygdala and entorhinal resections to be associated with improved outcome. However, patients with persistent seizures had significant atrophy of bilateral dorsomedial and pulvinar thalamic regions, and significant alterations of DTI-derived thalamotemporal probabilistic paths bilaterally relative to those patients rendered seizure free and controls, even when corrected for extent of mesial temporal lobe resection.InterpretationPatients with bihemispheric alterations of thalamotemporal structural networks may represent a subtype of mTLE that is resistant to temporal lobe surgery. Increasingly sensitive multimodal imaging techniques should endeavor to transform these group-based findings to individualize prediction of patient outcomes. Ann Neurol 2015;77:760–774
Article
Full-text available
Temporal cortex abnormalities are common in patients with mesial temporal lobe epilepsy due to hippocampal sclerosis (MTLE+HS) and believed to be relevant to the underlying mechanisms. In the present study, we set out to determine the familiarity of temporal cortex morphologic alterations in a cohort of MTLE+HS patients and their asymptomatic siblings. A surface-based morphometry (SBM) method was applied to process MRI data acquired from 140 individuals (50 patients with unilateral MTLE+HS, 50 asymptomatic siblings of patients, and 40 healthy controls). Using a region-of-interest approach, alterations in temporal cortex morphology were determined in patients and their asymptomatic siblings by comparing with the controls. Alterations in temporal cortex morphology were identified in MTLE+HS patients ipsilaterally within the anterio-medial regions, including the entorhinal cortex, parahippocampal gyrus, and temporal pole. Subtle but similar pattern of morphology changes with a medium effect size were also noted in the asymptomatic siblings. These localized alterations were related to volume loss that appeared driven by shared contractions in cerebral cortex surface area. These findings indicate that temporal cortex morphologic alterations are common to patients and their asymptomatic siblings and suggest that such localized traits are possibly heritable. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Article
Full-text available
The advent of MRI has revolutionized the evaluation and management of drug-resistant epilepsy by allowing the detection of the lesion associated with the region that gives rise to seizures. Recent evidence indicates marked chronic alterations in the functional organization of lesional tissue and large-scale cortico-subcortical networks. In this review, we focus on recent methodological developments in functional MRI (fMRI) analysis techniques and their application to the two most common drug-resistant focal epilepsies, i.e., temporal lobe epilepsy related to mesial temporal sclerosis and extra-temporal lobe epilepsy related to focal cortical dysplasia. We put particular emphasis on methodological developments in the analysis of task-free or "resting-state" fMRI to probe the integrity of intrinsic networks on a regional, inter-regional, and connectome-wide level. In temporal lobe epilepsy, these techniques have revealed disrupted connectivity of the ipsilateral mesiotemporal lobe, together with contralateral compensatory reorganization and striking reconfigurations of large-scale networks. In cortical dysplasia, initial observations indicate functional alterations in lesional, peri-lesional, and remote neocortical regions. While future research is needed to critically evaluate the reliability, sensitivity, and specificity, fMRI mapping promises to lend distinct biomarkers for diagnosis, presurgical planning, and outcome prediction.
Conference Paper
Full-text available
We propose a multispectral MRI-based clinical decision support approach to carry out automated seizure focus lateralization in patients with temporal lobe epilepsy (TLE). Based on high-resolution T1- and T2-weighted MRI with hippocampal subfield segmentations, our approach samples MRI features along the medial sheet of each subfield to minimize partial volume effects. To establish correspondence of sampling points across subjects, we propagate a spherical harmonic parameterization derived from the hippocampal boundary along a Laplacian gradient field towards the medial sheet. Volume and intensity data sampled on the medial sheet are finally fed into a supervised classifier. Testing our approach in TLE patients in whom the seizure focus could not be lateralized using conventional MR volumetry, the proposed approach correctly lateralized all patients and outperformed classification performance based on global subfield volumes or mean T2-intensity (100% vs. 68%). Moreover, statistical group-level comparisons revealed patterns of subfield abnormalities that were not evident in the global measurements and that largely agree with known histopathological changes.
Article
Full-text available
Hippocampal sclerosis (HS) is a common pathology encountered in mesial temporal lobe epilepsy (MTLE) as well as other epilepsy syndromes and in both surgical and post-mortem practice. The 2013 International League Against Epilepsy (ILAE) classification segregates HS into typical (type 1) and atypical (type 2 and 3) groups, based on the histological patterns of subfield neuronal loss and gliosis. In addition, granule cell reorganisation and alterations of interneuronal populations, neuropeptide fibre networks and mossy fibre sprouting are distinctive features of HS associated with epilepsies; they can be useful diagnostic aids to discriminate from other causes of HS, as well as highlighting potential mechanisms of hippocampal epileptogenesis. The cause of HS remains elusive and may be multi-factorial; the contribution of febrile seizures, genetic susceptibility, inflammatory and neurodevelopmental factors are discussed. Post-mortem based research in HS, as an addition to studies on surgical samples, has the added advantage of enabling the study of the wider network changes associated with HS, the long-term effects of epilepsy on the pathology and associated co-morbidities. It is likely that HS is heterogeneous in aspects of its cause, epileptogenetic mechanisms, network alterations and response to medical and surgical treatments. Future neuropathological studies will contribute to better recognition and understanding of these clinical and patho-aetiological subtypes of HS.
Article
Full-text available
The human brain can be modeled as a network, whose structure can be revealed by either anatomical or functional connectivity analyses. Little is known, so far, about the topological features of large-scale interregional functional covariance network (FCN) in the brain. Furthermore, the relationship between FCN and structural covariance network (SCN) has not been characterized yet, in the intact as well as in the diseased brain. Here, we studied 59 patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures and 59 healthy controls. We estimated FCN and SCN by measuring amplitudes of low-frequency fluctuations (ALFF) and gray matter volume (GMV), respectively, and then we conducted graph theoretical analyses. Our ALFF-based FCN and GMV-based results revealed that the normal human brain is characterized by specific topological properties such as small-worldness and highly-connected hub regions. The patients had altered overall topology compared to controls, suggesting that epilepsy is primarily a disorder of cerebral network organization. Furthermore, the patients had altered nodal characteristics in subcortical and medial temporal regions and default mode regions, for both FCN and SCN. Importantly, the correspondence between FCN and SCN was significantly larger in patients than in controls. These results support the hypothesis that the SCN reflects shared long-term trophic mechanisms within functionally synchronous systems. They can also provide crucial information for understanding the interactions between whole-brain network organization and pathology in generalized tonic-clonic seizures.
Article
Full-text available
Malformations of cerebral cortical development include a wide range of developmental disorders that are common causes of neurodevelopmental delay and epilepsy. In addition, study of these disorders contributes greatly to the understanding of normal brain development and its perturbations. The rapid recent evolution of molecular biology, genetics and imaging has resulted in an explosive increase in our knowledge of cerebral cortex development and in the number and types of malformations of cortical development that have been reported. These advances continue to modify our perception of these malformations. This review addresses recent changes in our perception of these disorders and proposes a modified classification based upon updates in our knowledge of cerebral cortical development.
Article
Full-text available
Focal cortical dysplasias (FCD) which represent a composite group of cortical malformations are increasingly recognized as morphological substrate for severe therapy-refractory epilepsy in children and young adults. However, presurgical evaluation remains challenging as not all FCD variants can be reliably detected by high-resolution magnetic resonance imaging (MRI). Here, we studied a cohort of 52 epilepsy patients with neuropathological evidence for FCD using the 2011 classification of the International League against Epilepsy (ILAE) and systematically analysed those histopathologic features applicable also for MRI diagnostics. Histopathologic parameters included quantitative measurements of cellular profiles, cortical thickness, heterotopic neurons in white matter, and myelination that were compared between FCD subtypes and age-/localization-matched controls (n = 36) using multivariate analysis. Dysmorphic neurons in both FCD Type II variants showed significantly increased diameter of their cell bodies and nuclei. Cortical thickness was also increased with a distinct loss of myelin content specifying FCD Type IIb from IIa. The data further suggested that myelination deficits in FCD Type IIb result from compromised oligodendroglial lineage differentiation and we concluded that the "transmantle sign" is a unique finding in FCD Type IIb. In contrast, FCD Type Ia was characterized by a smaller cortical ribbon and higher neuronal densities, but these parameters failed to reach statistical significance (considering age- and location-dependent variability in controls). All FCD variants showed abnormal grey-white matter boundaries with increased numbers of heterotopic neurons. Similar results were obtained also at deep white matter location. Thus, many FCD variants may indeed escape visual MRI inspection, but suspicious areas with increased or decreased cortical thickness as well as grey-white matter blurring may be uncovered using post-processing protocols of neuroimaging data. The systematic analysis of well-specified histopathological features could be helpful to improve sensitivity and specificity in MRI detection during pre-surgical work-up of patients with drug-resistant focal epilepsies.
Conference Paper
Full-text available
Hippocampal atrophy and developmental positional variants may co-occur in various neurological disorders. We propose a surface-based framework to analyze independently volume and positioning. After extracting the spherical harmonics combined with point distribution models (SPHARM-PDM) from manual labels, we computed displacement vectors between individual surfaces and the template. Then, we computed surface-based Jacobian determinants (SJD) from these vectors to localize volume changes. To analyze positional variants, we constructed a mean meridian axis (MEMAX), inheriting the shape-constrained point correspondences of SPHARM, on which we compute local curvatures and position vectors. We validated our method on synthetic shapes, and a large database of healthy subjects and patients with temporal lobe epilepsy. Our comprehensive analysis showed that in patients atrophy and positional changes co-occurred at the level of the posterior hippocampus. Indeed, in this region, while SPHARM-PDM showed mirrored deformations, SJD detected atrophy, and shape analysis of MEMAX unveiled medial positioning due to bending.
Article
Full-text available
The human brain is a large-scale integrated network in the functional and structural domain. Graph theoretical analysis provides a novel framework for analysing such complex networks. While previous neuroimaging studies have uncovered abnormalities in several specific brain networks in patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures, little is known about changes in whole-brain functional and structural connectivity networks. Regarding functional and structural connectivity, networks are intimately related and share common small-world topological features. We predict that patients with idiopathic generalized epilepsy would exhibit a decoupling between functional and structural networks. In this study, 26 patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures and 26 age- and sex-matched healthy controls were recruited. Resting-state functional magnetic resonance imaging signal correlations and diffusion tensor image tractography were used to generate functional and structural connectivity networks. Graph theoretical analysis revealed that the patients lost optimal topological organization in both functional and structural connectivity networks. Moreover, the patients showed significant increases in nodal topological characteristics in several cortical and subcortical regions, including mesial frontal cortex, putamen, thalamus and amygdala relative to controls, supporting the hypothesis that regions playing important roles in the pathogenesis of epilepsy may display abnormal hub properties in network analysis. Relative to controls, patients showed further decreases in nodal topological characteristics in areas of the default mode network, such as the posterior cingulate gyrus and inferior temporal gyrus. Most importantly, the degree of coupling between functional and structural connectivity networks was decreased, and exhibited a negative correlation with epilepsy duration in patients. Our findings suggest that the decoupling of functional and structural connectivity may reflect the progress of long-term impairment in idiopathic generalized epilepsy, and may be used as a potential biomarker to detect subtle brain abnormalities in epilepsy. Overall, our results demonstrate for the first time that idiopathic generalized epilepsy is reflected in a disrupted topological organization in large-scale brain functional and structural networks, thus providing valuable information for better understanding the pathophysiological mechanisms of generalized tonic-clonic seizures.
Article
Full-text available
Temporal lobe resection is an established treatment for medication-resistant temporal lobe epilepsy, which in recent years has increasingly been performed in children. However, little is known about the long-term outcome in these children. The aim of this study was to characterize intellectual and psychosocial functioning of children after temporal lobe resection as they progress into late adolescence and adulthood. We report the long-term follow-up of 42 children who underwent temporal lobe surgery after an average postoperative period of 9 years. Longitudinal change in IQ was documented, psychosocial outcome including quality of life was assessed, and preoperative and postoperative T1-weighted MRI brain scans were evaluated quantitatively. A well-matched nonsurgical comparison group of 11 children with similar clinical characteristics was also assessed. At follow-up, 86% of the surgical group were seizure-free, and 57% were no longer taking antiepileptic medication. A significant increase in IQ was found in the surgical group after an extended follow-up period of >5 years. This IQ change was not found in the nonsurgical comparison group. IQ increases were associated with cessation of antiepileptic medication and changes in MRI-derived gray matter volume. The surgical group also reported better psychosocial outcome including quality of life, which was more strongly associated with seizure freedom rather than surgery per se. Surgery for temporal lobe epilepsy performed in childhood results in excellent long-term seizure control and favorable cognitive outcome along with positive effects on brain development. This study provides Class III evidence that temporal lobectomy in children with temporal lobe epilepsy is associated with improved long-term intellectual outcomes compared with those undergoing standard medical treatment.
Article
Full-text available
  Focal cortical dysplasias (FCD) are localized regions of malformed cerebral cortex and are very frequently associated with epilepsy in both children and adults. A broad spectrum of histopathology has been included in the diagnosis of FCD. An ILAE task force proposes an international consensus classification system to better characterize specific clinicopathological FCD entities. Thirty-two Task Force members have reevaluated available data on electroclinical presentation, imaging, neuropathological examination of surgical specimens as well as postsurgical outcome. The ILAE Task Force proposes a three-tiered classification system. FCD Type I refers to isolated lesions, which present either as radial (FCD Type Ia) or tangential (FCD Type Ib) dyslamination of the neocortex, microscopically identified in one or multiple lobes. FCD Type II is an isolated lesion characterized by cortical dyslamination and dysmorphic neurons without (Type IIa) or with balloon cells (Type IIb). Hence, the major change since a prior classification represents the introduction of FCD Type III, which occurs in combination with hippocampal sclerosis (FCD Type IIIa), or with epilepsy-associated tumors (FCD Type IIIb). FCD Type IIIc is found adjacent to vascular malformations, whereas FCD Type IIId can be diagnosed in association with epileptogenic lesions acquired in early life (i.e., traumatic injury, ischemic injury or encephalitis). This three-tiered classification system will be an important basis to evaluate imaging, electroclinical features, and postsurgical seizure control as well as to explore underlying molecular pathomechanisms in FCD.
Conference Paper
Focal cortical dysplasia (FCD), a malformation of cortical development, is a frequent cause of drug-resistant epilepsy. This surgically-amenable lesion is histologically characterized by cortical dyslamination, dysmorphic neurons, and balloon cells, which may extend into the immediate subcortical white matter. On MRI, FCD is typically associated with cortical thickening, blurring of the cortical boundary, and intensity anomalies. Notably, even histologically-verified FCD may not be clearly visible on preoperative MRI. We propose a novel FCD detection algorithm, which aggregates surface-based descriptors of morphology and intensity derived from T1-weighted (T1w) MRI, T2-weighted fluid attenuation inversion recovery (FLAIR) MRI, and FLAIR/T1w ratio images. Features were systematically sampled at multiple intracortical/subcortical levels and fed into a two-stage classifier for automated lesion detection based on ensemble learning. Using 5-fold cross-validation, we evaluated the approach in 41 patients with histologically-verified FCD and 38 age-and sex-matched healthy controls. Our approach showed excellent sensitivity (83%, 34/41 lesions detected) and specificity (92%, no findings in 35/38 controls), suggesting benefits for presurgical diagnostics.
Conference Paper
Several neurological disorders are associated with hippocampal pathology. As changes may be localized to specific subfields or spanning across different subfields, accurate subfield segmentation may improve non-invasive diagnostics. We propose an automated subfield segmentation procedure, which combines surface-based processing with a patch-based template library and feature matching. Validation experiments in 25 healthy individuals showed high segmentation accuracy (Dice >82 % across all subfields) and robustness to variations in the template library size. Applying the algorithm to a cohort of patients with temporal lobe epilepsy and hippocampal sclerosis, we correctly lateralized the seizure focus in >90 %. This advantageously compares to classifiers relying on volumes retrieved from other state-of-the-art algorithms.
Article
Objective: To characterize in vivo MRI signatures of focal cortical dysplasia (FCD) type IIA and type IIB through combined analysis of morphology, intensity, microstructure, and function. Methods: We carried out a multimodal 3T MRI profiling of 33 histologically proven FCD type IIA (9) and IIB (24) lesions. A multisurface approach operating on manual consensus labels systematically sampled intracortical and subcortical lesional features. Geodesic distance mapping quantified the same features in the lesion perimeter. Logistic regression assessed the relationship between MRI and histology, while supervised pattern learning was used for individualized subtype prediction. Results: FCD type IIB was characterized by abnormal morphology, intensity, diffusivity, and function across all surfaces, while type IIA lesions presented only with increased fluid-attenuated inversion recovery signal and reduced diffusion anisotropy close to the gray-white matter interface. Similar to lesional patterns, perilesional anomalies were more marked in type IIB extending up to 16 mm. Structural MRI markers correlated with categorical histologic characteristics. A profile-based classifier predicted FCD subtypes with equal sensitivity of 85%, while maintaining a high specificity of 94% against healthy and disease controls. Conclusions: Image processing applied to widely available MRI contrasts has the ability to dissociate FCD subtypes at a mesoscopic level. Integrating in vivo staging of pathologic traits with automated lesion detection is likely to provide an objective definition of lesional boundary and assist emerging approaches, such as minimally invasive thermal ablation, which do not supply tissue specimen.
Article
Purpose: To provide a more detailed investigation of hippocampal subfields using 7T magnetic resonance imaging (MRI) for the identification of hippocampal sclerosis in temporal lobe epilepsy (TLE). Materials and methods: Patients (n = 13) with drug-resistant TLE previously identified by conventional imaging as having hippocampal sclerosis (HS) or not (nine without HS, four HS) and 20 age-matched healthy controls were scanned and compared using a 7T MRI protocol. Using a manual segmentation scheme to delineate hippocampal subfields, subfield-specific volume changes and apparent transverse relaxation rate ( R2*) were studied between the two groups. In addition, qualitative assessment at 7T and clinical outcomes were correlated with measured subfield changes. Results: Volumetry of the hippocampus at 7T in HS patients revealed significant ipsilateral subfield atrophy in CA1 (P = 0.001) and CA4+DG (P < 0.001). Volumetry also uncovered subfield atrophy in 33% of patients without HS, which had not been detected using conventional imaging. R2* was significantly lower in the CA4+DG subfields (P = 0.001) and the whole hippocampus (P = 0.029) of HS patients compared to controls but not significantly lower than the group without HS (P = 0.077, P = 0.109). No correlation was found between quantitative volumetry and qualitative assessment as well as surgical outcomes (Sub, P = 0.495, P = 0.567, P = 0.528; CA1, P = 0.104 ± 0.171, P = 0.273, P = 0.554; CA2+CA3, P = 0.517, P = 0.952, P = 0.130 ± 0.256; CA4+DG, P = 0.052 ± 0.173, P = 0.212, P = 0.124 ± 0.204; WholeHipp, P = 0.187, P = 0.132 ± 0.197, P = 0.628). Conclusion: These preliminary findings indicate that hippocampal subfield volumetry assessed at 7T is capable of identifying characteristic patterns of hippocampal atrophy in HS patients; however, difficulty remains in using imaging to identify hippocampal pathologies in cases without HS. Level of evidence: 2 J. MAGN. RESON. IMAGING 2017;45:1359-1370.
Article
Sudden unexpected death in epilepsy (SUDEP) can affect individuals of any age, but is most common in younger adults (aged 20–45 years). Generalised tonic-clonic seizures are the greatest risk factor for SUDEP; most often, SUDEP occurs after this type of seizure in bed during sleep hours and the person is found in a prone position. SUDEP excludes other forms of seizure-related sudden death that might be mechanistically related (eg, death after single febrile, unprovoked seizures, or status epilepticus). Typically, postictal apnoea and bradycardia progress to asystole and death. A crucial element of SUDEP is brainstem dysfunction, for which postictal generalised EEG suppression might be a biomarker. Dysfunction in serotonin and adenosine signalling systems, as well as genetic disorders affecting cardiac conduction and neuronal excitability, might also contribute. Because generalised tonic-clonic seizures precede most cases of SUDEP, patients must be better educated about prevention. The value of nocturnal monitoring to detect seizures and postictal stimulation is unproven but warrants further study.
Article
View largeDownload slide Temporal lobe epilepsy is a systems level disorder. Using multi-modal MRI, Liu et al. reveal temporolimbic anomalies in the superficial white matter (SWM) immediately below the cortex. The SWM is pivotal to maintaining corticocortical connectivity, and changes in this region may link hippocampal atrophy with large-scale default mode network alterations. View largeDownload slide Temporal lobe epilepsy is a systems level disorder. Using multi-modal MRI, Liu et al. reveal temporolimbic anomalies in the superficial white matter (SWM) immediately below the cortex. The SWM is pivotal to maintaining corticocortical connectivity, and changes in this region may link hippocampal atrophy with large-scale default mode network alterations.
Article
Objective. Although most temporal lobe epilepsy (TLE) patients show marked hippocampal sclerosis (HS) upon pathological examination, 40% present with no significant cell loss but gliotic changes only. To evaluate effects of hippocampal pathology on brain structure and functional networks, we aimed at dissociating multimodal MRI characteristics in patients with HS (TLE-HS) and those with gliosis only (TLE-G). Methods. In 20 TLE-HS, 19 TLE-G, and 25 healthy controls, we carried out a novel MRI-based hippocampal subfield surface analysis that integrated volume, T2-signal intensity, and diffusion markers with seed-based hippocampal functional connectivity. Results. Compared to controls, TLE-HS presented with marked ipsilateral atrophy, T2-hyperintensity, and mean diffusivity increases across all subfields, while TLE-G presented with dentate gyrus hypertrophy and focal increases in T2-intensity and mean diffusivity. Multivariate assessment confirmed a more marked ipsilateral load of anomalies across all subfields in TLE-HS, while anomalies in TLE-G were restricted to the subiculum. A between-cohort dissociation was independently suggested by resting-state functional connectivity analysis, revealing marked hippocampal decoupling from anterior and posterior default mode hubs in TLE-HS, while TLE-G did not differ from controls. Back-projection connectivity analysis from cortical targets revealed consistently decreased network embedding across all subfields in TLE-HS, while changes in TLE-G were limited to the subiculum. Hippocampal disconnectivity strongly correlated to T2-hyperintensity and marginally to atrophy. Conclusion. Multimodal MRI reveals diverging structural and functional connectivity profiles across the TLE spectrum. Pathology-specific modulations of large-scale functional brain networks lends novel evidence for a close interplay of structural and functional disruptions in focal epilepsy.
Article
Objective: To assess the diagnostic yield of 7T magnetic resonance imaging (MRI) in detecting and characterizing structural lesions in patients with intractable focal epilepsy and unrevealing conventional (1.5 or 3T) MRI. Methods: We conducted an observational clinical imaging study on 21 patients (17 adults and 4 children) with intractable focal epilepsy, exhibiting clinical and electroencephalographic features consistent with a single seizure-onset zone (SOZ) and unrevealing conventional MRI. Patients were enrolled at two tertiary epilepsy surgery centers and imaged at 7T, including whole brain (three-dimensional [3D] T1 -weighted [T1W] fast-spoiled gradient echo (FSPGR), 3D susceptibility-weighted angiography [SWAN], 3D fluid-attenuated inversion recovery [FLAIR]) and targeted imaging (2D T2 *-weighted dual-echo gradient-recalled echo [GRE] and 2D gray-white matter tissue border enhancement [TBE] fast spin echo inversion recovery [FSE-IR]). MRI studies at 1.5 or 3T deemed unrevealing at the referral center were reviewed by three experts in epilepsy imaging. Reviewers were provided information regarding the suspected localization of the SOZ. The same team subsequently reviewed 7T images. Agreement in imaging interpretation was reached through consensus-based discussions based on visual identification of structural abnormalities and their likely correlation with clinical and electrographic data. Results: 7T MRI revealed structural lesions in 6 (29%) of 21 patients. The diagnostic gain in detection was obtained using GRE and FLAIR images. Four of the six patients with abnormal 7T underwent epilepsy surgery. Histopathology revealed focal cortical dysplasia (FCD) in all. In the remaining 15 patients (71%), 7T MRI remained unrevealing; 4 of the patients underwent epilepsy surgery and histopathologic evaluation revealed gliosis. Significance: 7T MRI improves detection of epileptogenic FCD that is not visible at conventional field strengths. A dedicated protocol including whole brain FLAIR and GRE images at 7T targeted at the suspected SOZ increases the diagnostic yield.
Article
Objective: To perform whole-brain morphometry in patients with frontal lobe epilepsy and evaluate the utility of group-level patterns for individualized diagnosis and prognosis. Methods: We compared MRI-based cortical thickness and folding complexity between 2 frontal lobe epilepsy cohorts with histologically verified focal cortical dysplasia (FCD) (13 type I; 28 type II) and 41 closely matched controls. Pattern learning algorithms evaluated the utility of group-level findings to predict histologic FCD subtype, the side of the seizure focus, and postsurgical seizure outcome in single individuals. Results: Relative to controls, FCD type I displayed multilobar cortical thinning that was most marked in ipsilateral frontal cortices. Conversely, type II showed thickening in temporal and postcentral cortices. Cortical folding also diverged, with increased complexity in prefrontal cortices in type I and decreases in type II. Group-level findings successfully guided automated FCD subtype classification (type I: 100%; type II: 96%), seizure focus lateralization (type I: 92%; type II: 86%), and outcome prediction (type I: 92%; type II: 82%). Conclusion: FCD subtypes relate to diverse whole-brain structural phenotypes. While cortical thickening in type II may indicate delayed pruning, a thin cortex in type I likely results from combined effects of seizure excitotoxicity and the primary malformation. Group-level patterns have a high translational value in guiding individualized diagnostics.
Article
Objectives: Our aim is to assess the subfield-specific histopathological correlates of hippocampal volume and intensity changes (T1, T2) as well as diff!usion MRI markers in TLE, and investigate the efficacy of quantitative MRI measures in predicting histopathology in vivo. Experimental design: We correlated in vivo volumetry, T2 signal, quantitative T1 mapping, as well as diffusion MRI parameters with histological features of hippocampal sclerosis in a subfield-specific manner. We made use of on an advanced co-registration pipeline that provided a seamless integration of preoperative 3 T MRI with postoperative histopathological data, on which metrics of cell loss and gliosis were quantitatively assessed in CA1, CA2/3, and CA4/DG. Principal observations: MRI volumes across all subfields were positively correlated with neuronal density and size. Higher T2 intensity related to increased GFAP fraction in CA1, while quantitative T1 and diffusion MRI parameters showed negative correlations with neuronal density in CA4 and DG. Multiple linear regression analysis revealed that in vivo multiparametric MRI can predict neuronal loss in all the analyzed subfields with up to 90% accuracy. Conclusion: Our results, based on an accurate co-registration pipeline and a subfield-specific analysis of MRI and histology, demonstrate the potential of MRI volumetry, diffusion, and quantitative T1 as accurate in vivo biomarkers of hippocampal pathology. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc.
Article
The burden of comorbidity in people with epilepsy is high. Several diseases, including depression, anxiety, dementia, migraine, heart disease, peptic ulcers, and arthritis are up to eight times more common in people with epilepsy than in the general population. Several mechanisms explain how epilepsy and comorbidities are associated, including shared risk factors and bidirectional relations. There is a pressing need for new and validated screening instruments and guidelines to help with the early detection and treatment of comorbid conditions. Preliminary evidence suggests that some conditions, such as depression and migraine, negatively affect seizure outcome and quality of life. Further investigation is needed to explore these relations and the effects of targeted interventions. Future advances in the investigation of the comorbidities of epilepsy will strengthen our understanding of epilepsy and could play an important part in stratification for genetic studies.
Article
Summary Despite neuropathological and electrophysiological evidence for the involvement of parahippocampal structures in temporal lobe epilepsy (TLE), little attention has been paid to morphometric measurements of these structures in patients with TLE. Using high resolution MRI, we previously showed that the volume of the entorhinal cortex was decreased in patients with TLE. The purpose of this study was: (i) to determine whether changes in the volume of the perirhinal cortex and posterior parahippocampal cortex were detectable by MRI; and (ii) to study the distribution and degree of atrophy in mesial temporal structures including the hippocampal head, body and tail, amygdala, entorhinal cortex, perirhinal cortex and posterior parahippocampal cortex. MRI volumetric analysis was performed using a T1-weighted three-dimensional gradient echo sequence in 20 healthy subjects and 25 TLE patients with intractable TLE. In patients with either left or right TLE, the hippocampal head, body and tail and the entorhinal and perirhinal cortices ipsilateral to the seizure focus were significantly smaller than in normal controls. The mean volume of the posterior parahippocampal cortex was not different from that of normal controls. Within the hippocampus, the hippocampal head was more atrophic than the hippocampal body and hippocampal tail. Within the parahippocampal region, the entorhinal cortex was more severely affected than the perirhinal cortex. Our MRI results confirm pathological findings of damage in the mesial temporal lobe, involving not only the hippocampus and the amygdala, but also the entorhinal and perirhinal cortices. The pattern of atrophy may be explained by cell loss secondary to a disruption of entorhinal‐hippocampal connections as a result of privileged electrical dialogue between these two structures.
Article
Hippocampal atrophy in temporal lobe epilepsy (TLE) can indicate mesial temporal sclerosis and predict surgical success. Yet many patients with TLE do not have significant atrophy (magnetic resonance imaging (MRI) negative), which presents a diagnostic challenge. We used a new variant of high-dimensional large-deformation mapping to assess whether patients with apparently normal hippocampi have local shape changes that mirror those of patients with significant hippocampal atrophy. Forty-seven patients with unilateral TLE and 32 controls underwent structural brain MRI. High-dimensional large-deformation mapping provided hippocampal surface and volume estimates for each participant, dividing patients into low versus high hippocampal atrophy groups. A vertex-level generalized linear model compared local shape changes between groups. Patients with low-atrophy TLE (MRI negative) had significant local hippocampal shape changes compared to controls, similar to those in the contralateral hippocampus of high-atrophy patients. These changes primarily involved the subicular and hilar/dentate regions, instead of the classically affected CA1 region. Disease duration instead co-varied with lateral hippocampal atrophy, co-localizing with the CA1 subfield. These findings show that patients with "MRI-negative" TLE have regions of hippocampal atrophy that cluster medially, sparing the lateral regions (CA1) involved in high-atrophy patients. This suggests an overall effect of temporal lobe seizures manifesting as bilateral medial hippocampal atrophy, and a more selective effect of hippocampal seizures leading to disease-proportional CA1 atrophy, potentially reflecting epileptogenesis. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.
Article
Pathological perturbations of the brain are rarely confined to a single locus; instead, they often spread via axonal pathways to influence other regions. Patterns of such disease propagation are constrained by the extraordinarily complex, yet highly organized, topology of the underlying neural architecture; the so-called connectome. Thus, network organization fundamentally influences brain disease, and a connectomic approach grounded in network science is integral to understanding neuropathology. Here, we consider how brain-network topology shapes neural responses to damage, highlighting key maladaptive processes (such as diaschisis, transneuronal degeneration and dedifferentiation), and the resources (including degeneracy and reserve) and processes (such as compensation) that enable adaptation. We then show how knowledge of network topology allows us not only to describe pathological processes but also to generate predictive models of the spread and functional consequences of brain disease.
Article
Objective: In temporal lobe epilepsy (TLE), although hippocampal atrophy lateralizes the focus, the value of magnetic resonance imaging (MRI) to predict postsurgical outcome is rather modest. Prediction solely based on the hippocampus may be hampered by widespread mesiotemporal structural damage shown by advanced imaging. Increasingly complex and high-dimensional representation of MRI metrics motivates a shift to machine learning to establish objective, data-driven criteria for pathogenic processes and prognosis. Methods: We applied clustering to 114 consecutive unilateral TLE patients using 1.5T MRI profiles derived from surface morphology of hippocampus, amygdala, and entorhinal cortex. To evaluate the diagnostic validity of the classification, we assessed its yield to predict outcome in 79 surgically treated patients. Reproducibility of outcome prediction was assessed in an independent cohort of 27 patients evaluated on 3.0T MRI. Results: Four similarly sized classes partitioned our cohort; in all, alterations spanned over the 3 mesiotemporal structures. Compared to 46 controls, TLE-I showed marked bilateral atrophy; in TLE-II atrophy was ipsilateral; TLE-III showed mild bilateral atrophy; whereas TLE-IV showed hypertrophy. Classes differed with regard to histopathology and freedom from seizures. Classwise surface-based classifiers accurately predicted outcome in 92 ± 1% of patients, outperforming conventional volumetry. Predictors of relapse were distributed bilaterally across structures. Prediction accuracy was similarly high in the independent cohort (96%), supporting generalizability. Interpretation: We provide a novel description of individual variability across the TLE spectrum. Class membership was associated with distinct patterns of damage and outcome predictors that did not spatially overlap, emphasizing the ability of machine learning to disentangle the differential contribution of morphology to patient phenotypes, ultimately refining the prognosis of epilepsy surgery.
Article
We evaluate a fully automatic technique for labeling hippocampal subfields and cortical subregions in the medial temporal lobe in in vivo 3 Tesla MRI. The method performs segmentation on a T2-weighted MRI scan with 0.4 × 0.4 × 2.0 mm3 resolution, partial brain coverage, and oblique orientation. Hippocampal subfields, entorhinal cortex, and perirhinal cortex are labeled using a pipeline that combines multi-atlas label fusion and learning-based error correction. In contrast to earlier work on automatic subfield segmentation in T2-weighted MRI [Yushkevich et al., 2010], our approach requires no manual initialization, labels hippocampal subfields over a greater anterior-posterior extent, and labels the perirhinal cortex, which is further subdivided into Brodmann areas 35 and 36. The accuracy of the automatic segmentation relative to manual segmentation is measured using cross-validation in 29 subjects from a study of amnestic mild cognitive impairment (aMCI) and is highest for the dentate gyrus (Dice coefficient is 0.823), CA1 (0.803), perirhinal cortex (0.797), and entorhinal cortex (0.786) labels. A larger cohort of 83 subjects is used to examine the effects of aMCI in the hippocampal region using both subfield volume and regional subfield thickness maps. Most significant differences between aMCI and healthy aging are observed bilaterally in the CA1 subfield and in the left Brodmann area 35. Thickness analysis results are consistent with volumetry, but provide additional regional specificity and suggest nonuniformity in the effects of aMCI on hippocampal subfields and MTL cortical subregions. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
Article
Objective: To detect automatically focal cortical dysplasia (FCD) type II in patients with extratemporal epilepsy initially diagnosed as MRI-negative on routine inspection of 1.5 and 3.0T scans. Methods: We implemented an automated classifier relying on surface-based features of FCD morphology and intensity, taking advantage of their covariance. The method was tested on 19 patients (15 with histologically confirmed FCD) scanned at 3.0T, and cross-validated using a leave-one-out strategy. We assessed specificity in 24 healthy controls and 11 disease controls with temporal lobe epilepsy. Cross-dataset classification performance was evaluated in 20 healthy controls and 14 patients with histologically verified FCD examined at 1.5T. Results: Sensitivity was 74%, with 100% specificity (i.e., no lesions detected in healthy or disease controls). In 50% of cases, a single cluster colocalized with the FCD lesion, while in the remaining cases a median of 1 extralesional cluster was found. Applying the classifier (trained on 3.0T data) to the 1.5T dataset yielded comparable performance (sensitivity 71%, specificity 95%). Conclusion: In patients initially diagnosed as MRI-negative, our fully automated multivariate approach offered a substantial gain in sensitivity over standard radiologic assessment. The proposed method showed generalizability across cohorts, scanners, and field strengths. Machine learning may assist presurgical decision-making by facilitating hypothesis formulation about the epileptogenic zone. Classification of evidence: This study provides Class II evidence that automated machine learning of MRI patterns accurately identifies FCD among patients with extratemporal epilepsy initially diagnosed as MRI-negative.
Article
In many patients, focal cortical dysplasia (FCD) is characterized by minor structural changes that may go unrecognized by standard radiological analysis. To increase the sensitivity of magnetic resonance imaging (MRI) for the detection of subtle lesions of FCD, we developed voxel-based image postprocessing methods, including first-order texture analysis and morphological processing modeled on known MRI features of FCD. We selected 16 patients with histologically proven FCD. Image processing features were calculated over a neighborhood for each voxel in the three-dimensional T1-weighted MRI. Three feature maps were generated: (1) gray matter thickness map to model cortical thickening, (2) gradient map to model blurring of the gray matter–white matter junction, and (3) relative intensity map to model the hyperintense signal within the lesion. Two observers detected lesions on conventional MRI in 8/16 and on ratio maps in 14/16 patients. Sensitivity was 87.5% (14/16) for the ratio maps compared to 50% (8/16) for MRI (p < 0.003). Specificity was 95% (19/20) for ratio maps and 100% (20/20) for MRIs. Cohen's kappa was 0.53 for MRIs, indicating moderate agreement, and 0.83 for ratio maps, indicating strong agreement beyond chance between the 2 observers. The image-processing methods developed in this study improve visual detection of FCD, even in cases where no lesion is obvious on MRI. These techniques could increase the number of patients with partial epilepsy who could benefit from surgery.
Article
In the last two decades our understanding of MTLE and its pathophysiology has grown remarkably. Perhaps the most important recognition is that it is not a single entity with a uniform pathology. Rather, it is associated with significant variations in pathology that, in turn, are likely associated with different causes, functional anatomies, physiologies, and outcomes to treatment (medi-cal and surgical). There are numerous changes in the expression of channels and receptors that contribute to the development of epilepsy and, perhaps, drug resistance. This progress in our understanding has also been aided immeasurably by the development of animal models with many parallels to the human condition.These models have allowed us to look at changes in anatomy and physiology and to dissect the circuits in ways that have not been possible in humans. The animal models have also allowed us to create hypotheses about the pathophysiology of the disorder that we have started to exam-ine with the new imaging tools. At present, it is best to summarize our understanding of MTLE by saying there are multiple changes in multiple sites that contribute to the development of the chronic condition. For this reason alone, we should consider MTLE to be a systems disorder.
Article
Diffusion tensor imaging (DTI) tractography has shown tract-specific pathology in temporal lobe epilepsy (TLE). This technique normally yields a single value per diffusion parameter per tract, potentially reducing the sensitivity for the detection of focal changes. Our goal was to spatially characterize diffusion abnormalities of fasciculi carrying temporal lobe connections. We studied 30 patients with drug-resistant TLE and 21 healthy control subjects. Twenty-four patients underwent DTI toward the end of video-EEG telemetry, with an average of 50 ± 54 hours between the last seizure and DTI examination. After manual dissection of the uncinate and inferior longitudinal and arcuate bundle, they were spatially matched based on their distance to the temporal lobe, providing between-subject correspondence of tract segments. We evaluated point-wise differences in diffusion parameters along each tract at group and subject levels. Our approach localized increased mean diffusivity restricted to or more prominent within the ipsilateral temporal lobe. These abnormalities tapered off as tracts exited the temporal lobe. We observed that the shorter the interval between the last seizure and DTI, the higher the mean diffusivity (MD) of the ipsilateral tracts. Linear discriminant analysis of tract segments correctly lateralized 87% of patients. The centrifugal pattern of white matter diffusion abnormalities probably reflects astrogliosis and microstructure derangement related to seizure activity in the vicinity of the focus. The negative correlation between the interval from last seizure and MD suggests a role for postictal vasogenic edema. The ability to assess tracts segmentally may contribute to a better understanding of the extent of white matter pathology in epilepsy and assist in the presurgical evaluation of patients with TLE, particularly those with unremarkable conventional imaging results.
Article
In drug-resistant temporal lobe epilepsy (TLE), detecting hippocampal atrophy on MRI is crucial as it allows defining the surgical target. In addition to atrophy, about 40% of patients present with malrotation, a developmental anomaly characterized by atypical morphologies of the hippocampus and collateral sulcus. We have recently shown that both atrophy and malrotation impact negatively the performance of single averaged- and multi-template volume-based techniques. Here, we propose a novel hippocampal segmentation algorithm (SurfMulti) that integrates deformable parametric surfaces, vertex-wise modeling of locoregional texture and shape, and multiple templates in a unified framework. To account for inter-subject variability, including shape variants, we used a library derived from a large database of healthy (n=80) and diseased (n=288) hippocampi. To quantify malrotation, we generated 3D models from manual hippocampal labels and automatically extracted collateral sulci. The accuracy of SurfMulti was evaluated relative to manual labeling and segmentation obtained through a volume-based multi-template approach (Vol-multi) using the Dice similarity index and surface-based shape mapping, for which we computed vertex-wise displacement vectors between automated and manual segmentations. We then correlated segmentation accuracy with malrotation features and atrophy. SurfMulti outperformed Vol-multi and achieved a level of accuracy in TLE patients (Dice=86.9%) virtually identical to healthy controls (Dice=87.5%). Vertex-wise shape mapping showed that SurfMulti had an excellent overlap with manual labels, with sub-millimetric precision. Its performance was not influenced by atrophy or malrotation (|r|<0.20, p>0.2), while Vol-multi was hampered by both anomalies (|r|>0.28, p<0.05). The magnitude of atrophy detected using SurfMulti was the closest to manual volumetry (Cohen's d: manual=1.71, t=7.6; SurfMulti=1.60, t=7.0; Vol-multi=1.38, t=6.1). The high performance of SurfMulti regardless of cohort, atrophy and shape variants identifies this algorithm as a robust segmentation tool for hippocampal volumetry.
Article
Atypical morphology of the surface of the cerebral cortex may be related to abnormal cortical folding (gyrification) and therefore may indicate underlying malformations of cortical development (MCDs). Using magnetic resonance imaging (MRI)-based analysis, we examined cortical morphology in patients with juvenile myoclonic epilepsy (JME). MRI data was collected for 24 patients with JME and 40 demographically matched healthy controls. FreeSurfer, an automated cortical surface reconstruction method, was applied to compare cortical morphology between patients and controls. Areas of anomalous cortical morphology were defined as regions of interest (ROIs) to contrast regional cortical parameters, such as surface area, average thickness, and mean curvature between patients and controls. In patients with JME, changes to cortical morphology were detected in several regions. In the left hemisphere, these were in insular and cingulate cortices, occipital pole, and middle temporal and fusiform gyri. In the right hemisphere, changes were detected in insular cortex, inferior temporal gyrus, and precuneus. Further analysis of ROIs revealed that these changes are related to differences in surface area rather than average cortical thickness. In addition, mean curvature abnormalities were detected in the insula bilaterally, the left cingulate cortex, and right inferior temporal gyrus. The morphologic findings in this study suggest that structural abnormalities in JME extend beyond mesial frontal lobe regions of the brain. These may be indicative of areas of subtle cortical folding abnormality related to early disruption of cortical development.
Article
Although experimental work has provided evidence that the thalamus is a crucial relay structure in temporal lobe epilepsy (TLE), the relation of the thalamus to neocortical pathology remains unclear. To assess thalamocortical network pathology in TLE, we mapped pointwise patterns of thalamic atrophy and statistically related them to neocortical thinning. We studied cross-sectionally 36 patients with drug-resistant TLE and 19 age- and sex-matched healthy control subjects using high-resolution MRI. To localize thalamic pathology, we converted manual labels into surface meshes using the spherical harmonic description and calculated local deformations relative to a template. In addition, we measured cortical thickness by means of the constrained Laplacian anatomic segmentation using proximity algorithm. Compared with control subjects, patients with TLE showed ipsilateral thalamic atrophy that was located along the medial surface, encompassing anterior, medial, and posterior divisions. Unbiased analysis correlating the degree of medial thalamic atrophy with cortical thickness measurements mapped bilateral frontocentral, lateral temporal, and mesiotemporal cortices. These areas overlapped with those of cortical thinning found when patients were compared with control subjects. Thalamic atrophy intensified with a longer duration of epilepsy and was more severe in patients with a history of febrile convulsions. The degree and distribution of thalamic pathology relates to the topography and extent of neocortical atrophy, lending support to the concept that the thalamus is an important hub in the pathologic network of TLE.
Article
Magnetic resonance imaging (MRI) is a pivotal component in the investigation of patients with any form of epilepsy because of its unmatched ability in visualizing structural brain pathology. The MRI signature of newly diagnosed epilepsy is not yet fully defined, mainly because of the lack of a cohesive methodology to evaluate structural changes in the early stages of the disease. By revealing subtle lesions that previously eluded visual inspection in patients with drug-resistant epilepsy, quantitative computer-assisted image analysis has clearly demonstrated increased sensitivity and diagnostic accuracy compared to conventional techniques. Therefore, the application of image processing methods in patients with newly diagnosed epilepsy promises to reduce the trial-error period in potential surgical candidates, provide solid biomarkers for monitoring the disease and identifying treatment responders. A clearer understanding of brain pathology at the early stages of the disorder will help clinicians to develop better criteria for identifying patients who are at risk of secondary brain damage and for timely intervention that achieves seizure control.
Article
The aim of this study was to determine if there were focal cortical abnormalities in juvenile myoclonic epilepsy (JME) using neuropsychological investigations and MRI. Twenty-eight patients with JME and a large sample of healthy controls were assessed using a series of neuropsychological tests as well as structural and diffusion tensor MRI (DTI). DTI measures assessed fractional anisotropy (FA) within a white matter skeleton. Neuropsychological testing indicated subtle dysfunctions in verbal fluency, comprehension, and expression, as well as nonverbal memory and mental flexibility. Utilizing whole-brain voxel-based morphometry for gray matter MRI data and tract-based spatial statistics for white matter diffusion MRI data, we found reductions in gray matter volume (GMV) in the supplementary motor area and posterior cingulate cortex and reductions in FA in underlying white matter of the corpus callosum. Supplementary motor area FA predicted scores in word naming tasks and expression scores. Posterior cingulate cortex GMV and FA predicted cognitive inhibition scores on the mental flexibility task. The neuropsychological, structural, and tractography results implicate mesial frontal cortex, especially the supplementary motor area, and posterior cingulate cortex in JME.
Article
Converging evidence suggests that abnormalities of brain development may play a role in the pathogenesis of temporal lobe epilepsy (TLE). As sulco-gyral patterns are thought to be a footprint of cortical development, we set out to quantitatively map folding complexity across the neocortex in TLE. Additionally, we tested whether there was a relationship between cortical complexity and features of hippocampal maldevelopment, commonly referred to as malrotation. To quantify folding complexity, we obtained whole-brain surface-based measures of absolute mean cortical curvature from MRI scans acquired in 43 drug-resistant patients with TLE with unilateral hippocampal atrophy, and 40 age- and sex-matched healthy controls. In patients, we correlated changes in cortical curvature with 3-dimensional measures of hippocampal positioning. We found increased folding complexity in the temporolimbic cortices encompassing parahippocampal, temporopolar, insular, and fronto-opercular regions. Increased complexity was observed ipsilateral to the seizure focus in patients with left TLE (LTLE), whereas these changes were bilateral in patients with right TLE (RTLE). In both TLE groups, increased temporolimbic complexity was associated with increased hippocampal malrotation. We found tendencies for increased complexity in bilateral posterior temporal cortices in LTLE and contralateral parahippocampal cortices in RTLE to be predictive of unfavorable seizure outcome after surgery. The anatomic distribution of increased cortical complexity overlapping with limbic seizure networks in TLE and its association with hippocampal maldevelopment further imply that neurodevelopmental factors may play a role in the epileptogenic process of TLE.