Search

Building precise and detailed parcellations of anatomically and functionally distinct brain areas has been a major focus in Neuroscience. Pioneer anatomists parcellated the cortical manifold based on extensive histological studies of post-mortem brain, harnessing local variations in cortical cyto- and myeloarchitecture to define areal boundaries. Compared to the cytoarchitectonic field, where multiple neuroimaging studies have recently translated this old legacy data into useful analytical resources, myeloarchitectonics, which parcellate the cortex based on the organization of myelinated fibers, has received less attention. Here, we present the neocortical surface-based myeloarchitectonic atlas based on the histology-derived maps of the Vogt-Vogt school and its 2D translation by Nieuwenhuys. In addition to a myeloarchitectonic parcellation, our package includes intracortical laminar profiles of myelin content based on Vogt-Vogt-Hopf original publications. Histology-derived myelin density mapped on our atlas demonstrated a close overlap with in vivo quantitative MRI markers for myelin and relates to cytoarchitectural features. Complementing the existing battery of approaches for digital cartography, the whole-brain myeloarchitectonic atlas offers an opportunity to validate imaging surrogate markers of myelin in both health and disease., Competing Interests: Declaration of Competing Interest The authors declare that there is no conflict of interest related to this manuscript., (Copyright © 2022. Published by Elsevier Inc.)

Objective: To study the intrinsic organization of the thalamocortical circuitry in patients with generalized epilepsy with tonic-clonic seizures (GTCS) via resting-state fMRI (rs-fMRI) connectome analysis and to evaluate its relation to drug response., Methods: In a prospectively followed-up sample of 41 patients and 27 healthy controls, we obtained rs-fMRI and structural MRI. After 1 year of follow-up, 27 patients were classified as seizure-free and 14 as drug-resistant. We examined connectivity within and between resting-state communities in cortical and thalamic subregions. In addition to comparing patients to controls, we examined associations with seizure control. We assessed reproducibility in an independent cohort of 21 patients., Results: Compared to controls, patients showed a more constrained network embedding of the thalamus, while frontocentral neocortical regions expressed increased functional diversity. Findings remained significant after regressing out thalamic volume and cortical thickness, suggesting independence from structural alterations. We observed more marked network imbalances in drug-resistant compared to seizure-free patients. Findings were similar in the reproducibility dataset., Conclusions: Our findings suggest a pathoconnectomic mechanism of generalized epilepsy centered on diverging changes in cortical and thalamic connectivity. More restricted thalamic connectivity could reflect the tendency to engage in recursive thalamocortical loops, which may contribute to hyperexcitability. Conversely, increased connectional diversity of frontocentral networks may relay abnormal activity to an extended bilateral territory. Network imbalances were observed shortly after diagnosis and related to future drug response, suggesting clinical utility., (© 2019 American Academy of Neurology.)

The majority of MRI studies in temporal lobe epilepsy (TLE) have utilized morphometry to map widespread cortical alterations. Morphological markers, such as cortical thickness or grey matter density, reflect combinations of biological events largely driven by overall cortical geometry rather than intracortical tissue properties. Because of its sensitivity to intracortical myelin, quantitative measurement of longitudinal relaxation time (qT 1 ) provides and an in vivo proxy for cortical microstructure. Here, we mapped the regional distribution of qT 1 in a consecutive cohort of 24 TLE patients and 20 healthy controls. Compared to controls, patients presented with a strictly ipsilateral distribution of qT 1 increases in temporopolar, parahippocampal and orbitofrontal cortices. Supervised statistical learning applied to qT 1 maps could lateralize the seizure focus in 92% of patients. Intracortical profiling of qT 1 along streamlines perpendicular to the cortical mantle revealed marked effects in upper levels that tapered off at the white matter interface. Findings remained robust after correction for cortical thickness and interface blurring, suggesting independence from previously reported morphological anomalies in this disorder. Mapping of qT 1 along hippocampal subfield surfaces revealed marked increases in anterior portions of the ipsilateral CA1-3 and DG that were also robust against correction for atrophy. Notably, in operated patients, qualitative histopathological analysis of myelin stains in resected hippocampal specimens confirmed disrupted internal architecture and fiber organization. Both hippocampal and neocortical qT 1 anomalies were more severe in patients with early disease onset. Finally, analysis of resting-state connectivity from regions of qT 1 increases revealed altered intrinsic functional network embedding in patients, particularly to prefrontal networks. Analysis of qT 1 suggests a preferential susceptibility of ipsilateral limbic cortices to microstructural damage, possibly related to disrupted myeloarchitecture. These alterations may reflect atypical neurodevelopment and affect the integrity of fronto-limbic functional networks., (Copyright © 2017 Elsevier Inc. All rights reserved.)

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 magnetic resonance imaging (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, whereas TLE-G presented with dentate gyrus hypertrophy, focal increases in T2 intensity and mean diffusivity. Multivariate assessment confirmed a more marked ipsilateral load of anomalies across all subfields in TLE-HS, whereas 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, whereas 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., Interpretation: Multimodal MRI reveals diverging structural and functional connectivity profiles across the TLE spectrum. Pathology-specific modulations of large-scale functional brain networks lend novel evidence for a close interplay of structural and functional disruptions in focal epilepsy. Ann Neurol 2016;80:142-153., (© 2016 American Neurological Association.)

Accurate tissue classification is a crucial prerequisite to MRI morphometry. Automated methods based on intensity histograms constructed from the entire volume are challenged by regional intensity variations due to local radiofrequency artifacts as well as disparities in tissue composition, laminar architecture and folding patterns. Current work proposes a novel anatomy-driven method in which parcels conforming cortical folding were regionally extracted from the brain. Each parcel is subsequently classified using nonparametric mean shift clustering. Evaluation was carried out on manually labeled images from two datasets acquired at 3.0 Tesla (n = 15) and 1.5 Tesla (n = 20). In both datasets, we observed high tissue classification accuracy of the proposed method (Dice index >97.6% at 3.0 Tesla, and >89.2% at 1.5 Tesla). Moreover, our method consistently outperformed state-of-the-art classification routines available in SPM8 and FSL-FAST, as well as a recently proposed local classifier that partitions the brain into cubes. Contour-based analyses localized more accurate white matter-gray matter (GM) interface classification of the proposed framework compared to the other algorithms, particularly in central and occipital cortices that generally display bright GM due to their highly degree of myelination. Excellent accuracy was maintained, even in the absence of correction for intensity inhomogeneity. The presented anatomy-driven local classification algorithm may significantly improve cortical boundary definition, with possible benefits for morphometric inference and biomarker discovery., (© 2015 Wiley Periodicals, Inc.)

Objective: 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., Methods: 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., Results: 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., Conclusion: 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.

Temporal lobe epilepsy (TLE) is the most common drug-resistant epilepsy in adults. As morphometric studies have shown widespread structural damage in TLE, this condition is often referred to as a system disorder with disrupted structural networks. Studies based on univariate statistical comparisons can only indirectly test such hypothesis. Graph theory provides a new approach to formally analyze large-scale networks. Using graph-theoretical analysis of magnetic resonance imaging-based cortical thickness correlations, we investigated the structural basis of the organization of such networks in 122 TLE patients and 47 age- and sex-matched healthy controls. Networks in patients and controls were characterized by a short path length between anatomical regions and a high degree of clustering, suggestive of a small-world topology. However, compared with controls, patients showed increased path length and clustering, altered distribution of network hubs, and higher vulnerability to targeted attacks, suggesting a reorganization of cortical thickness correlation networks. Longitudinal analysis demonstrated that network alterations intensify over time. Bootstrap simulations showed high reproducibility of network parameters across random subsamplings, indicating that altered network topology in TLE is a consistent finding. Increased network disruption was associated with unfavorable postoperative seizure outcome, implying adverse effects of epileptogenesis on large-scale network organization.

Objective: To assess the reproducibility of neocortical atrophy and its clinical significance across the spectrum of temporal lobe epilepsy (TLE), in particular with respect to postsurgical outcome., Methods: MRI-based cortical thickness measurement was obtained in 105 patients. A total of 58 had hippocampal atrophy on magnetic resonance volumetry (TLE-HA) and 47 had normal hippocampal volumes (TLE-NV). Twenty-seven patients had repeated scans with a mean interval of 28 months. Patients were compared to 48 age- and sex-matched healthy controls. We used linear models to assess cortical thinning and the effect of seizure control after surgery. Reproducibility of finding cortical atrophy was statistically evaluated using bootstrap simulations., Results: Cross-sectional and longitudinal analyses revealed highly similar topology and rates of neocortical thinning in both TLE groups, predominantly in frontocentral, temporal, and cingulate regions. Bootstrap methods showed that at least 20 subjects per group were necessary to reliably observe these patterns of atrophy in TLE. Moreover, power analysis showed that even with sample sizes of 80 subjects per group, differences in thickness between TLE-HA and TLE-NV would be marginal. With respect to postsurgical outcome, we found an association between residual seizures and atrophy in temporopolar and insular cortices in TLE-HA, and in the posterior quadrant in TLE-NV., Conclusion: We demonstrated with a high degree of confidence that static and dynamic effects of epilepsy impact similarly the neocortex of patients with hippocampal atrophy and patients with normal hippocampal volumes. On the contrary, areas predicting unfavorable postsurgical outcome were distinct, suggesting different configurations of epileptogenic networks in these 2 groups.

Epileptic activity underlying idiopathic generalized epilepsy (IGE) is related to abnormal thalamo-cortical interactions. Our purpose was to map in vivo the organization of the thalamo-cortical network in IGE. We measured cortical thickness and thalamic volumes on MRI in 23 IGE patients with generalized tonic-clonic seizures only and 46 healthy controls. Significant correlations between thalamic volumes and cortical thickness were interpreted as thalamo-cortical network connections. In controls, thickness of frontal, limbic, and occipital regions was positively correlated with the thalamic volumes, corresponding to known anatomical connections from sacrificial tracer studies in primates and human in vivo DTI data. In patients, thalamo-cortical network correlations increased in fronto-central and parietal regions, but decreased in limbic areas. Group analysis revealed that, compared to controls, IGE patients had bilateral thalamic atrophy and widespread cortical thinning that was most prominent in fronto-central areas, with a prevalence of up to 40%. Duration of epilepsy affected negatively thalamic volumes and thickness of fronto-central and limbic cortices. These effects were significantly different from aging in controls. Patients with poorly controlled seizures showed an even faster progression in these neocortical regions. Fronto-centro-parietal atrophy in IGE is likely the effect of generalized seizure activity inducing thalamo-cortical network remodeling. On the other hand, limbic abnormalities may take place secondary to thalamic disconnection.

Background: Whether recurrent epileptic seizures induce brain damage is debated. Disease progression in epilepsy has been evaluated only in a few community-based studies involving patients with seizures well controlled by medication. These studies concluded that epilepsy does not inevitably lead to global cerebral damage., Objective: To track the progression of neocortical atrophy in pharmacoresistant temporal lobe epilepsy (TLE) using longitudinal and cross-sectional designs., Methods: Using a fully automated measure of cortical thickness on MRI, we studied a homogeneous sample of patients with pharmacoresistant TLE. In the longitudinal analysis (n = 18), fixed-effect models were used to quantify cortical atrophy over a mean interscan interval of 2.5 years (range = 7 to 90 months). In the cross-sectional analysis (n = 121), we correlated epilepsy duration and thickness. To dissociate normal aging from pathologic progression, we compared aging effects in TLE to healthy controls., Results: The longitudinal analysis mapped progression in ipsilateral temporopolar and central and contralateral orbitofrontal, insular, and angular regions. In patients with more than 14 years of disease, atrophy progressed more rapidly in frontocentral and parietal regions that in those with shorter duration. The cross-sectional study showed progressive atrophy in the mesial and superolateral frontal, and parietal cortices., Conclusions: Our combined cross-sectional and longitudinal analysis in patients with pharmacoresistant temporal lobe epilepsy demonstrated progressive neocortical atrophy over a mean interval of 2.5 years that is distinct from normal aging, likely representing seizure-induced damage. The cumulative character of atrophy underlies the importance of early surgical treatment in this group of patients.

Focal cortical dysplasia (FCD), a malformation of cortical development, is an important cause of pharmacoresistant epilepsy. Small FCD lesions are difficult to distinguish from normal cortex and remain often overlooked on radiological MRI inspection. This paper presents a method to detect small FCD lesions on T1-MRI relying on surface-based features that model their textural and morphometric characteristics. The automatic detection was performed by a two step classification. First, a vertex-wise classifier based on a neural-network bagging trained on manual labels. Then, a cluster-wise classification designed to remove false positive clusters. The method was tested on 19 patients with small FCD. At the first classification step, 18/19 (95%) lesions were detected. The second classification step kept 13/19 (68%) lesions and decreased efficiently the amount of false positive. This new approach may assist the presurgical evaluation of patients with intractable epilepsy, especially those with unremarkable MRI findings.

Focal cortical dysplasia (FCD) is the most frequent malformation of cortical development in patients with medically intractable epilepsy. On MRI, FCD lesions are not easily differentiable from the normal cortex and defining their spatial extent is challenging. In this paper, we introduce a method to segment FCD lesions on T1-weighted MRI. It relies on two successive three-dimensional deformable models, whose evolutions are based on the level set framework. The first deformable model is driven by probability maps obtained from three MRI features: cortical thickness, relative intensity and gradient. These features correspond to the visual characteristics of FCD and allow discriminating lesions and normal tissues. In a second stage, the previous result is expanded towards the underlying and overlying cortical boundaries, throughout the whole cortical section. The method was quantitatively evaluated by comparison with manually traced labels in 18 patients with FCD. The automated segmentations achieved a strong agreement with the manuals labels, demonstrating the applicability of the method to assist the delineation of FCD lesions on MRI. This new approach may become a useful tool for the presurgical evaluation of patients with intractable epilepsy related to cortical dysplasia.

Objective: To assess whether different types of malformation of cortical development (MCD) are associated with specific patterns of hippocampal abnormalities., Methods: A total of 122 consecutive patients with MRI diagnosis of MCD (53 males, age range 1-58 years) were included in the study. Hippocampal measurements were made on 1-3 mm coronal T1-weighted MRIs and compared with MRIs of normal controls., Results: A total of 39 patients had focal cortical dysplasia, 5 had hemimegalencephaly, 5 had lissencephaly-agyria-pachygyria, 11 had SLH, 11 had PNH, 12 had bilateral contiguous PNH, 5 had schizencephaly, and 34 had polymicrogyria. The frequency of hippocampal abnormalities in these patients with MCD was 29.5%. A small hippocampus was present in all types of MCD. Only patients with lissencephaly and SLH had an enlarged hippocampus. Abnormalities in hippocampal rotation and shape were present in all types of MCD; however, these predominated in PNH. None of the patients with lissencephaly-agyria-pachygyria or SLH had hyperintense signal on T2 or FLAIR images or abnormal hippocampal internal architecture., Conclusion: A small hippocampus was present in all types of MCD; however, the classic MRI characteristics of hippocampal sclerosis were often lacking. Abnormal enlargement of the hippocampus was associated with only diffuse MCD due to abnormal neuronal migration (lissencephaly-agyria-pachygyria and SLH).

High-resolution MRI of the brain has made it possible to identify focal cortical dysplasia (FCD) in an increasing number of patients. There is evidence for structural abnormalities extending beyond the visually identified FCD lesion. Voxel-based morphometry (VBM) has the potential of detecting both lesions and extra-lesional abnormalities because it performs a whole brain voxel-wise comparison. However, on T1-weighted MRI, FCD lesions are characterized by a wide spectrum of signal hyperintensity that may compromise the results of the segmentation step in VBM. Our purpose was to investigate gray matter (GM) changes in individual FCD patients using voxel-based morphometry (VBM). In addition, we sought to assess the performance of this technique for FCD detection with respect to lesion intensity using an operator designed to emphasize areas of hyperintense T1 signal. We studied 27 patients with known FCD and focal epilepsy and 39 healthy controls. We compared the GM map of each subject (controls and patients) with the average GM map of all controls and obtained a GM z-score map for each individual. The protocol being designed to achieve a maximal specificity, no differences in GM concentration were found in the control group. The z-score maps showed an increase in GM that coincided with the lesion in 21/27 (78%) patients. Five of the six remaining patients whose lesions were not detected by VBM presented with a strong lesion hyperintensity, and a significant part of their lesion was misclassified as white matter. In 16/27 (59%) patients, there were additional areas of GM increase distant from the primary lesion. Areas of GM decrease were found in 8/27 (30%) patients. In conclusion, individual voxel-based analysis was able to detect FCD in a majority of patients. Moreover, FCD was often associated with widespread GM changes extending beyond the visible lesion. In its current form, however, individual VBM may be unable to detect lesions characterized by strong signal intensity abnormalities.

Purpose: On MRI, focal cortical dysplasia (FCD) is characterized by a combination of increased cortical thickness, hyperintense signal within the dysplastic lesion, and blurred transition between gray and white matter (GM-WM). The visual identification of these abnormal characteristics may be difficult, and it is unclear to what degree these features occur among different FCD lesions. Our purpose was to investigate the pattern of occurrence of abnormal MRI characteristics in FCD by using a set of computational models and to generate quantitative lesion profiling., Methods: A set of voxel-wise operators was applied to high-resolution 3D T1-weighted MRI in 23 patients with histologically proven FCD and 39 healthy controls, creating maps of GM thickness, maps of relative intensity highlighting areas with hyperintense signal, and maps of gradient magnitude modeling the GM-WM transition. All FCD lesions were segmented manually on the T1-weighted MRI., Results: FCD volumes ranged from 734 mm3 to 80,726 mm3 (mean, 8,629 mm3 +/- 16,238). The manually segmented FCD lesions were used to estimate features in the lesional area and to determine possible local variations of each feature by means of a histogram. In 78% of the patients, FCD lesions were characterized by simultaneous GM thickening, hyperintense signal, and blurring of the GM-WM transition. Moreover, in all patients, the FCD lesion had at least two of these three characteristics., Conclusions: The three features occurred regardless of the lesion volume, and they characterized not only large FCD lesions, but also subtle ones that had been overlooked by conventional radiologic inspection before surgery.

Focal cortical dysplasia (FCD), a malformation of cortical development, is an important cause of medically intractable epilepsy. FCD lesions are difficult to distinguish from non-lesional cortex and their delineation on MRI is a challenging task. This paper presents a method to segment FCD lesions on T1-weighted MRI, based on a 3D deformable model, implemented using the level set framework. The deformable model is driven by three MRI features: cortical thickness, relative intensity and gradient. These features correspond to the visual characteristics of FCD and allow to differentiate lesions from normal tissues. The proposed method was tested on 18 patients with FCD and its performance was quantitatively evaluated by comparison with the manual tracings of two trained raters. The validation showed that the similarity between the level set segmentation and the manual labels is similar to the agreement between the two human raters. This new approach may become a useful tool for the presurgical evaluation of patients with intractable epilepsy.

Focal cortical dysplasia (FCD), a malformation of cortical development, is a frequent cause of pharmacologically intractable epilepsy. FCD is characterized on Tl-weighted MRI by cortical thickening, blurring of the gray-matter/white-matter interface, and gray-level hyperintensity. We have previously used computational models of these characteristics to enhance visual lesion detection. In the present study we seek to improve our methods by combining these models with features derived from texture analysis of MRI, which allows measurement of image properties not readily accessible by visual analysis. These computational models and texture features were used to develop a two-stage Bayesian classifier to perform automated FCD lesion detection. Eighteen patients with histologically confirmed FCD and 14 normal controls were studied. On the MRI volumes of the 18 patients, 20 FCD lesions were manually labeled by an expert observer. Three-dimensional maps of the computational models and texture features were constructed for all subjects. A Bayesian classifier was trained on the computational models to classify voxels as cerebrospinal fluid, gray-matter, white-matter, transitional, or lesional. Voxels classified as lesional were subsequently reclassified based on the texture features. This process produced a 3D lesion map, which was compared to the manual lesion labels. The automated classifier identified 17/20 manually labeled lesions. No lesions were identified in controls. Thus, combining models of the T1-weighted MRI characteristics of FCD with texture analysis enabled successful construction of a classifier. This computer-based, automated method may be useful in the presurgical evaluation of patients with severe epilepsy related to FCD.

In many patients, focal cortical dysplasia (FCD) is characterized by minor structural changes that may go unrecognized by standard radiological analysis. We previously demonstrated that visual analysis of a composite map based on three simple models of MRI features of FCD increased the sensitivity of FCD lesion detection, compared to visual analysis of conventional MRI. Here we report on the use of improved methods for characterizing FCD which improve contrast in the composite maps: a Laplacian-based metric for measuring cortical thickness, a convolutional kernel to model blurring of the GM-WM interface, and an operator to measure hyperintense T1 signal. To validate these methods, we processed the MRIs of 14 FCD patients with our original set of image processing operators and an improved set of image processing operators. Comparison of the composite maps associated with the two sets of operators revealed that contrast between lesional tissue and nonlesional cortex was significantly increased in the composite maps associated with the set of improved operators. Increasing this contrast is an important step toward the goal of automated FCD lesion detection.

Purpose: To analyze the results of surgical treatment of intractable epilepsy in patients with subcortical band heterotopia, or double cortex syndrome, a diffuse neuronal migration disorder., Methods: We studied eight patients (five women) with double cortex syndrome and intractable epilepsy. All had a comprehensive presurgical evaluation including prolonged video-EEG recordings and magnetic resonance imaging (MRI)., Results: All patients had partial seizures, with secondary generalization in six of them. Neurologic examination was normal in all. Three were of normal intelligence, and five were mildly retarded. Six patients underwent invasive EEG recordings, three of them with subdural grids and three with stereotactic implanted depth electrodes (SEEG). Although EEG recordings showed multilobar epileptic abnormalities in most patients, regional or focal seizure onset was recorded in all. MRI showed bilateral subcortical band heterotopia, asymmetric in thickness in three. An additional area of cortical thickening in the left frontal lobe was found in one patient. Surgical procedures included multiple subpial transections in two patients, frontal lesionectomy in one, temporal lobectomy with amygdalohippocampectomy in five, and an additional anterior callosotomy in one. Five patients had no significant improvement, two had some improvement, and one was greatly improved., Conclusion: Our results do not support focal surgical removal of epileptogenic tissue in patients with double cortex syndrome, even in the presence of a relatively localized epileptogenic area.

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.

Abstract: Classification approaches for neurological diseases tend to concentrate on specific structures such as the hippocampus (HC). The hypothesis for the novel methodology presented in this work is that pathologies will impact large tissue areas with detectable variations of T1-weighted MR signal intensity and registration metrics. The technique is applied to lateralization of seizure focus in 127 patients with intractable temporal lobe epilepsy (TLE), in which the site of seizure onset was determined by comprehensive evaluation (69 with left MTL seizure focus (SF) (group “L”) and 58 with right SF (group “R”)). The method analyses large, non-specific Volumes of Interest (VOI) centered on the left and right medial temporal lobes (MTL) (55 × 82 × 80 voxels) in pre-processed scans aligned in stereotaxic space. Extracted VOIs are linearly and nonlinearly registered to a reference target image. Principal Components Analyses of (i) the normalized intensity and (ii) the trace, a measure of local volume change, are used to generate a multidimensional reference space from a set of 152 neurologically healthy subjects. VOIs from TLE patients, processed in a similar fashion, are projected in this space, and leave-one-out, forward stepwise linear discriminant analysis of the eigencoordinate distributions is used for classification. Following manual MRI volumetric analysis, 80 patients had HC atrophy (group “HA”) ipsilateral to the SF (42 with left SF or “LHA”, and 38 with right or “RHA”), and the remaining 47 had normal HC volumes (group “HNV”) (27 with left SF or “LNV”, and 20 with right SF or “RNV”). The automated method was 100% accurate at separating “HA” vs. “HNV”, “LHA” vs. “RHA”, and “LNV” vs “RNV”. It was also 96% accurate at separating “L” vs. “R”. Our results indicate that MR data projected in multidimensional feature domains can lateralize SF in epilepsy patients with a high accuracy, irrespective of HC volumes. This single-scan, practical and objective method holds promise for the pre-surgical evaluation of TLE patients. [Copyright &y& Elsevier]