Microstructural Imaging in Temporal Lobe Epilepsy: Diffusion Imaging Changes Relate to Reduced Neurite Density

Purpose: Previous imaging studies in patients with refractory temporal lobe epilepsy (TLE) have examined the spatial distribution of changes in imaging parameters such as diffusion tensor imaging (DTI) metrics and cortical thickness. Multi-compartment models offer greater specificity with parameters more directly related to known changes in TLE such as altered neuronal density and myelination. We studied the spatial distribution of conventional and novel metrics including neurite density derived from NODDI (Neurite Orientation Dispersion and Density Imaging) and myelin water fraction (MWF) derived from mcDESPOT (Multi-Compartment Driven Equilibrium Single Pulse Observation of T1/T2)] to infer the underlying neurobiology of changes in conventional metrics. / Methods: 20 patients with TLE and 20 matched controls underwent magnetic resonance imaging including a volumetric T1-weighted sequence, multi-shell diffusion from which DTI and NODDI metrics were derived and a protocol suitable for mcDESPOT fitting. Models of the grey matter-white matter and grey matter-CSF surfaces were automatically generated from the T1-weighted MRI. Conventional diffusion and novel metrics of neurite density and MWF were sampled from intracortical grey matter and subcortical white matter surfaces and cortical thickness was measured. / Results: In intracortical grey matter, diffusivity was increased in the ipsilateral temporal and frontopolar cortices with more restricted areas of reduced neurite density. Diffusivity increases were largely related to reductions in neurite density, and to a lesser extent CSF partial volume effects, but not MWF. In subcortical white matter, widespread bilateral reductions in fractional anisotropy and increases in radial diffusivity were seen. These were primarily related to reduced neurite density, with an additional relationship to reduced MWF in the temporal pole and anterolateral temporal neocortex. Changes were greater with increasing epilepsy duration. Bilaterally reduced cortical thickness in the mesial temporal lobe and centroparietal cortices was unrelated to neurite density and MWF. / Conclusions: Diffusivity changes in grey and white matter are primarily related to reduced neurite density with an additional relationship to reduced MWF in the temporal pole. Neurite density may represent a more sensitive and specific biomarker of progressive neuronal damage in refractory TLE that deserves further study

Event-based modelling 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 multi-centre 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) MRI scans collected by the ENIGMA-Epilepsy consortium, comprising 804 people with MTLE-HS and 1,625 healthy controls from 25 centres. Features with a moderate case-control effect size (Cohen's d≥0.5) 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 of onset and anti-seizure 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 to duration of illness (Spearman's ρ=0.293, p=7.03x10-16 ), age of onset (ρ=-0.18, p=9.82x10-7 ) and ASM resistance (AUC=0.59, p=0.043, Mann-Whitney U test). However, associations were driven by cases assigned to EBM stage zero, which represents MTLE-HS with mild or non-detectable 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

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

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.11Nsciescopu

Multicontrast MRI analysis of gray and white matter pathology in temporal lobe epilepsy

Introduction: Quantitative MRI studies have consistently demonstrated that drug-resistant temporal lobe epilepsy (TLE) is associated with multilobar cortical thinning affecting lateral temporal and fronto-central regions (Bernhardt et al. 2010). While diffusion weighted imaging studies have also reported widespread white matter (WM) changes (Otte et al. 2012), their spatial relationship to cortical pathology is unclear, possibly given the targeted sampling of deep fibre tracts. Moreover, metrics of grey matter (GM) morphology and microstructural WM integrity have not been evaluated conjointly. Here, we mapped diffusion properties of the immediate subcortical WM and cortical GM thickness in a unified surface-based framework. Methods: We studied 61 drug-resistant TLE patients (34±9 years, 46 males; 31/30 left/right TLE) and 42 healthy controls (30±7 years, 21 males). Participants were scanned on a 3.0T Siemens TimTrio MRI. Based on T1-weighted MRI (3D-MPRAGE, 1x1x1mm3 isotropic voxels), we generated cortical surface models and measured cortical thickness across 80k vertices. We computed a Laplacian potential field between the cortex and ventricles, which guided the placement of subcortical surfaces at 1, 2 and 3 mm below the GM-WM boundary, with intrinsic vertex-correspondence to the overlying cortex. Based on co-registered diffusion MRI (64 directions, b=1000 s/mm2, 2x2x2mm3 isotropic voxels), we sampled vertex-wise mean diffusivity (MD) and fractional anisotropy (FA) on subcortical WM surface. Hemisphere-specific measurements of left and right TLE patients were normalized with respect to controls, and sorted into ipsilateral/contralateral to the seizure focus. Following correction for age and gender, we carried out vertex-wise t-tests to detect cortical thickness and subcortical WM diffusion differences between patients and controls across surfaces. Findings were corrected using random field theory at FWE<0.05. Results: Relative to controls, TLE patients presented with diffuse bilateral cortical thinning in anterior temporal, frontal, and centro-parietal regions; conversely, subcortical WM diffusion changes (MD increase and FA decrease) were more restricted, and largely limited to ipsilateral limbic cortices, including the parahippocampus, anterior cingulate, lateral temporal, and orbitofrontal regions (Fig 1). Diffusion abnormalities were similar at 1, 2, and 3 mm depth. Within the temporal lobe, MD and FA changes overlapped with cortical thinning in parahippocampal and lateral cortices; in the frontal lobe, overlaps were observed in dorsolateral prefrontal and frontopolar regions. Conclusions: Our study compared for the first time point-wise patterns of cortical and subcortical WM structural alterations in TLE and showed a differential distribution of anomalies. Predominantly ipsilateral limbic diffusion alterations may reflect gliosis and/or demyelination due to mesiotemporal deafferentation; on the other hand, extensive and multi-lobar bilateral GM atrophy is likely secondary to excitotoxicity in neocortical circuits affected by seizure spread

Multicontrast MRI analysis of gray and white matter pathology in temporal lobe epilepsy

Introduction: Quantitative MRI studies have consistently demonstrated that drug-resistant temporal lobe epilepsy (TLE) is associated with multilobar cortical thinning affecting lateral temporal and fronto-central regions (Bernhardt et al. 2010). While diffusion weighted imaging studies have also reported widespread white matter (WM) changes (Otte et al. 2012), their spatial relationship to cortical pathology is unclear, possibly given the targeted sampling of deep fibre tracts. Moreover, metrics of grey matter (GM) morphology and microstructural WM integrity have not been evaluated conjointly. Here, we mapped diffusion properties of the immediate subcortical WM and cortical GM thickness in a unified surface-based framework. Methods: We studied 61 drug-resistant TLE patients (34±9 years, 46 males; 31/30 left/right TLE) and 42 healthy controls (30±7 years, 21 males). Participants were scanned on a 3.0T Siemens TimTrio MRI. Based on T1-weighted MRI (3D-MPRAGE, 1x1x1mm3 isotropic voxels), we generated cortical surface models and measured cortical thickness across 80k vertices. We computed a Laplacian potential field between the cortex and ventricles, which guided the placement of subcortical surfaces at 1, 2 and 3 mm below the GM-WM boundary, with intrinsic vertex-correspondence to the overlying cortex. Based on co-registered diffusion MRI (64 directions, b=1000 s/mm2, 2x2x2mm3 isotropic voxels), we sampled vertex-wise mean diffusivity (MD) and fractional anisotropy (FA) on subcortical WM surface. Hemisphere-specific measurements of left and right TLE patients were normalized with respect to controls, and sorted into ipsilateral/contralateral to the seizure focus. Following correction for age and gender, we carried out vertex-wise t-tests to detect cortical thickness and subcortical WM diffusion differences between patients and controls across surfaces. Findings were corrected using random field theory at FWE<0.05. Results: Relative to controls, TLE patients presented with diffuse bilateral cortical thinning in anterior temporal, frontal, and centro-parietal regions; conversely, subcortical WM diffusion changes (MD increase and FA decrease) were more restricted, and largely limited to ipsilateral limbic cortices, including the parahippocampus, anterior cingulate, lateral temporal, and orbitofrontal regions (Fig 1). Diffusion abnormalities were similar at 1, 2, and 3 mm depth. Within the temporal lobe, MD and FA changes overlapped with cortical thinning in parahippocampal and lateral cortices; in the frontal lobe, overlaps were observed in dorsolateral prefrontal and frontopolar regions. Conclusions: Our study compared for the first time point-wise patterns of cortical and subcortical WM structural alterations in TLE and showed a differential distribution of anomalies. Predominantly ipsilateral limbic diffusion alterations may reflect gliosis and/or demyelination due to mesiotemporal deafferentation; on the other hand, extensive and multi-lobar bilateral GM atrophy is likely secondary to excitotoxicity in neocortical circuits affected by seizure spread

MRI phenotyping of hippocampal subfield pathology in temporal lobe epilepsy

Introduction: Temporal lobe epilepsy (TLE) is the most common drug-resistant epilepsy in adults. Its hallmark lesion is hippocampal sclerosis which manifests with variably distributed neuronal loss and gliosis across subfields. This lesional entity is apparent on MRI as atrophy, T2 signal changes, and diffusion alterations. Surgery renders the majority of patients seizure-free; yet, individualized outcome predictors remain unknown. We performed a surface-based multivariate integration of volume, T2 intensity, and diffusion parameters across subfields; we evaluated group-level changes with respect to healthy controls and assessed the prognostic yield to predict surgical outcome in single patients. Methods: We studied 39 consecutive drug-resistant TLE patients (14 males; 32±9 years; 21/18 LTLE/RTLE). Twenty-one patients underwent surgery; at a follow-up of 42±18 months, 16 (76%) achieved seizure freedom, while 6 (24%) had residual attacks. Hippocampal specimens were of sufficient quality for histopathological analysis in 17 patients, and revealed neuronal loss and gliosis in 10 and isolated gliosis in 7. The control group consisted of 25 age- and sex-matched healthy individuals (12 males; 31±8 years). MRI data were acquired on a 3T Siemens using a 32-channel head coil, including submillimetric T1-weighted (3D-MPRAGE; 0.6×0.6×0.6 mm3 voxels) and T2-weighted MRI (2D-TSE; 0.4×0.4×2.0 mm3 voxels), as well as diffusion-weighted images (twice-refocused 2D-EPI sequence; 2.0×2.0×2.0 mm3 voxels). T1- and T2-weighted images underwent intensity inhomogeneity correction and were linearly registered to the MNI152 template; diffusion images were corrected for head motion and eddy current distortions, and co-registered to the same space. One rater (JKY) manually segmented the subfields cornu. Ammonis (CA) 1-3, CA4 and dentate gyrus (DG), as well as the subiculum. Using our recently described method (Kim et al. 2014), we extracted medial sheets along the central path of a given subfield on which we sampled surface-wise T2 intensity, mean diffusivity, and fractional anisotropy, and calculated local columnar volume changes. Patients were analyzed relative to the epileptogenic lobe (i.e., ipsilateral and contralateral to the seizure focus). Prior to pooling, we normalized measures at a given surface-point using a z-transformation with respect to the corresponding distribution in controls, thereby accounting for normal inter-hemispheric variations seen in healthy individuals. We used SurfStat for Matlab for statistical analyses (Worsley et al., 2009). Surface-based comparisons assessed anomalies in our patients relative to controls and the relationship to post-surgical outcome. Findings were corrected for multiple comparisons at FWE<0.05. A support vector machine classifier with leave-one-out-cross-validation was employed to predict outcome in single patients. For each patient, we carried out surface-based t-tests between the remaining seizure-free and non-seizure patients to select regions from which features were sampled. Results: Compared to controls, patients showed T2 increases across all subfields bilaterally, with most marked effects in ipsilateral CA1-3 and CA4-DG; the latter subfields also showed markedly increased mean diffusivity and decreased anisotropy. Columnar volume was decreased in the ipsilateral CA1-3 and subiculum. Compared to those who achieved seizure freedom, non-seizure free patients displayed bilateral mean diffusivity increases and contralateral columnar volume decreases. A classifier combining volume and mean diffusivity changes accurately predicted surgical outcome in 20/21 (96%) patients. Conclusions: Surface-based multivariate integration of morphology, signal and diffusion provides in vivo phenotyping of hippocampal subfield pathology in TLE, and accurately predicts post-surgical outcome

MRI phenotyping of hippocampal subfield pathology in temporal lobe epilepsy

Introduction: Temporal lobe epilepsy (TLE) is the most common drug-resistant epilepsy in adults. Its hallmark lesion is hippocampal sclerosis which manifests with variably distributed neuronal loss and gliosis across subfields. This lesional entity is apparent on MRI as atrophy, T2 signal changes, and diffusion alterations. Surgery renders the majority of patients seizure-free; yet, individualized outcome predictors remain unknown. We performed a surface-based multivariate integration of volume, T2 intensity, and diffusion parameters across subfields; we evaluated group-level changes with respect to healthy controls and assessed the prognostic yield to predict surgical outcome in single patients. Methods: We studied 39 consecutive drug-resistant TLE patients (14 males; 32±9 years; 21/18 LTLE/RTLE). Twenty-one patients underwent surgery; at a follow-up of 42±18 months, 16 (76%) achieved seizure freedom, while 6 (24%) had residual attacks. Hippocampal specimens were of sufficient quality for histopathological analysis in 17 patients, and revealed neuronal loss and gliosis in 10 and isolated gliosis in 7. The control group consisted of 25 age- and sex-matched healthy individuals (12 males; 31±8 years). MRI data were acquired on a 3T Siemens using a 32-channel head coil, including submillimetric T1-weighted (3D-MPRAGE; 0.6×0.6×0.6 mm3 voxels) and T2-weighted MRI (2D-TSE; 0.4×0.4×2.0 mm3 voxels), as well as diffusion-weighted images (twice-refocused 2D-EPI sequence; 2.0×2.0×2.0 mm3 voxels). T1- and T2-weighted images underwent intensity inhomogeneity correction and were linearly registered to the MNI152 template; diffusion images were corrected for head motion and eddy current distortions, and co-registered to the same space. One rater (JKY) manually segmented the subfields cornu. Ammonis (CA) 1-3, CA4 and dentate gyrus (DG), as well as the subiculum. Using our recently described method (Kim et al. 2014), we extracted medial sheets along the central path of a given subfield on which we sampled surface-wise T2 intensity, mean diffusivity, and fractional anisotropy, and calculated local columnar volume changes. Patients were analyzed relative to the epileptogenic lobe (i.e., ipsilateral and contralateral to the seizure focus). Prior to pooling, we normalized measures at a given surface-point using a z-transformation with respect to the corresponding distribution in controls, thereby accounting for normal inter-hemispheric variations seen in healthy individuals. We used SurfStat for Matlab for statistical analyses (Worsley et al., 2009). Surface-based comparisons assessed anomalies in our patients relative to controls and the relationship to post-surgical outcome. Findings were corrected for multiple comparisons at FWE<0.05. A support vector machine classifier with leave-one-out-cross-validation was employed to predict outcome in single patients. For each patient, we carried out surface-based t-tests between the remaining seizure-free and non-seizure patients to select regions from which features were sampled. Results: Compared to controls, patients showed T2 increases across all subfields bilaterally, with most marked effects in ipsilateral CA1-3 and CA4-DG; the latter subfields also showed markedly increased mean diffusivity and decreased anisotropy. Columnar volume was decreased in the ipsilateral CA1-3 and subiculum. Compared to those who achieved seizure freedom, non-seizure free patients displayed bilateral mean diffusivity increases and contralateral columnar volume decreases. A classifier combining volume and mean diffusivity changes accurately predicted surgical outcome in 20/21 (96%) patients. Conclusions: Surface-based multivariate integration of morphology, signal and diffusion provides in vivo phenotyping of hippocampal subfield pathology in TLE, and accurately predicts post-surgical outcome

Attribute-filtering and knowledge extraction for vessel segmentation

International audienceAttribute-filtering, relying on the notion of component-tree, enables to process grey-level images by taking into account high-level a priori knowledge. Based on these notions, a method is proposed for automatic segmentation of vascular structures from phase-contrast magnetic resonance angiography. Experiments performed on 16 images and validations by comparison to results obtained by two human experts emphasise the relevance of the method