Cortical neuronal loss and hippocampal sclerosis are not detected by voxel-based morphometry in individual epilepsy surgery patients

Voxel-based morphometry (VBM) has detected differences between brains of groups of patients with epilepsy and controls, but the sensitivity for detecting subtle pathological changes in single subjects has not been established. The aim of the study was to test the sensitivity of VBM using statistical parametric mapping (SPM5) to detect hippocampal sclerosis (HS) and cortical neuronal loss in individual patients. T1-weighted volumetric 1.5 T MR images from 13 patients with HS and laminar cortical neuronal loss were segmented, normalised and smoothed using SPM5. Both modulated and non-modulated analyses were performed. Comparisons of one control subject against the rest (n ¼ 23) were first performed to ascertain the smoothing level with the lowest number of SPM changes in controls. Each patient was then compared against the whole control group. The lowest number of SPM changes in control subjects was found at a smoothing level of 10 mm full width half maximum for modulated and non-modulated data. In the patient group, no SPM abnormalities were found in the affected temporal lobe or hippocampus at this smoothing level. At lower smoothing levels there were numerous SPM findings in controls and patients. VBM did not detect any abnormalities associated with either laminar cortical neuronal loss or HS. This may be due to normalisation and smoothing of images and low statistical power in areas with larger interindividual differences. This suggests that the methodology may currently not be suitable to detect particular occult abnormalities possibly associated with seizure onset zone in individual epilepsy patients with unremarkable standard structural MRI

Structural imaging biomarkers of sudden unexpected death in epilepsy.

Sudden unexpected death in epilepsy is a major cause of premature death in people with epilepsy. We aimed to assess whether structural changes potentially attributable to sudden death pathogenesis were present on magnetic resonance imaging in people who subsequently died of sudden unexpected death in epilepsy. In a retrospective, voxel-based analysis of T1 volume scans, we compared grey matter volumes in 12 cases of sudden unexpected death in epilepsy (two definite, 10 probable; eight males), acquired 2 years [median, interquartile range (IQR) 2.8] before death [median (IQR) age at scanning 33.5 (22) years], with 34 people at high risk [age 30.5 (12); 19 males], 19 at low risk [age 30 (7.5); 12 males] of sudden death, and 15 healthy controls [age 37 (16); seven males]. At-risk subjects were defined based on risk factors of sudden unexpected death in epilepsy identified in a recent combined risk factor analysis. We identified increased grey matter volume in the right anterior hippocampus/amygdala and parahippocampus in sudden death cases and people at high risk, when compared to those at low risk and controls. Compared to controls, posterior thalamic grey matter volume, an area mediating oxygen regulation, was reduced in cases of sudden unexpected death in epilepsy and subjects at high risk. The extent of reduction correlated with disease duration in all subjects with epilepsy. Increased amygdalo-hippocampal grey matter volume with right-sided changes is consistent with histo-pathological findings reported in sudden infant death syndrome. We speculate that the right-sided predominance reflects asymmetric central influences on autonomic outflow, contributing to cardiac arrhythmia. Pulvinar damage may impair hypoxia regulation. The imaging findings in sudden unexpected death in epilepsy and people at high risk may be useful as a biomarker for risk-stratification in future studies

Computational brain anatomy in patients with temporal lobe epilepsy

BACKGROUND Temporal lobe epilepsy (TLE) is a frequent type of focal epilepsy that constitutes 30% to 50% of all epileptic syndromes. This medical condition is often associated with hippocampal sclerosis, however it can be due to cortical dysplasia, brain tumour, vascular malformation or without any evidence for pathology (cryptogenic). Even though the main symptoms are the seizures, epilepsy sometimes interferes with cognitive functions such as visual or verbal memory, language or attention. TLE is frequently pharmaco-­‐resistant and only a hippocampal resection helps patients to become seizure-­‐free. Temporal lobe epilepsy is also described as a progressive disorder that causes chronic brain tissue damages. History of febrile seizures and status epilepticus, frequency of seizures and age at onset of seizure, as well as epilepsy duration or years of anti-­‐epileptic drugs use are all factors that impact the gravity of the brain structure's damage. Magnetic resonance imaging (MRI) has undergone a considerable development and, nowadays, has become an essential clinical tool in the diagnosis of TLE. It is currently used to reveal precisely cerebral abnormalities that may induce seizures. PURPOSE The aim of this cross-­‐sectional study is to investigate the pattern of microstructural brain tissue characteristics (grey and white matter volumes) occurring in three clinically distinctive TLE entities: mesial temporal sclerosis (MTS), focal cortical dysplasia (FCD) and cryptogenic epilepsy. By comparing them to each other, we want to acquire in-­‐depth knowledge of their pathological mechanism. We use well-­‐established computational anatomy methodology -­‐ voxel-­‐ based morphometry (VBM) to investigate brain anatomy changes related to the present clinical phenotype. CONTRIBUTION OF THE STUDY In the past few years, there has been a lot of controversy concerning structural MRI findings in TLE. Most of the studies looked for informative brain changes in epilepsy with MTS compared with healthy controls. This study is the first to take into consideration all clinical aspects of TLE together -­‐ mesial temporal sclerosis, focal cortical dysplasia and cryptogenic epilepsy. MATERIAL AND METHODS In-­‐vivo anatomical brain imaging data (MRI at 1.5T) was acquired in patients with clinical diagnosis of temporal lobe epilepsy. TLE patients were divided in three groups according to radiological description of brain MRI findings -­‐ mesial temporal sclerosis [MTS_group], focal cortical dysplasia [Dysplasia_group] and cryptogenic epilepsy [NoMRI_group] and compared with healthy volunteers. VBM technique was used to identify brain tissues alterations (GM and WM). RESULTS We demonstrate that MTS showed similar grey and white matter volumes reduction in the hippocampus, thalamus and cerebellum ipsilateral to the epileptogenic focus when compared with cryptogenic epilepsy patients and healthy controls. The focal cortical dysplasia patients showed grey matter volume loss restricted to the thalamus

Multivariate Analysis of MR Images in Temporal Lobe Epilepsy

Epilepsy stands aside from other neurological diseases because clinical patterns of progression are unknown: The etiology of each epilepsy case is unique and so it is the individual prognosis. Temporal lobe epilepsy (TLE) is the most frequent type of focal epilepsy and the surgical excision of the hippocampus and the surrounding tissue is an accepted treatment in refractory cases, specially when seizures become frequent increasingly affecting the performance of daily tasks and significantly decreasing the quality of life of the patient. The sensitivity of clinical imaging is poor for patients with no hippocampal involvement and invasive procedures such as the Wada test and intracranial EEG are required to detect and lateralize epileptogenic tissue. This thesis develops imaging processing techniques using quantitative relaxometry and diffusion tensor imaging with the aiming to provide a less invasive alternative when detectability is low. Chapter 2 develops the concept of individual feature maps on regions of interest. A laterality score on these maps correctly distinguished left TLE from right TLE in 12 out of 15 patients. Chapter 3 explores machine learning models to detect TLE, obtaining perfect classification for left patients, and 88.9% accuracy for right TLE patients. Chapter 4 focuses on temporal lobe asymmetry developing a voxel-based method for assessing asymmetry and verifying its applicability to individual predictions (92% accuracy) and group-wise statistical analyses. Informative ROI and voxel-based informative features are described for each experiment, demonstrating the relative importance of mean diffusivity over other MR imaging alternatives in identification and lateralization of TLE patients. Finally, the conclusion chapter discuss contributions, main limitations and outlining options for future research

Detection of Epileptogenic Cortical Malformations with Surface-Based MRI Morphometry

Magnetic resonance imaging has revolutionized the detection of structural abnormalities in patients with epilepsy. However, many focal abnormalities remain undetected in routine visual inspection. Here we use an automated, surface-based method for quantifying morphometric features related to epileptogenic cortical malformations to detect abnormal cortical thickness and blurred gray-white matter boundaries. Using MRI morphometry at 3T with surface-based spherical averaging techniques that precisely align anatomical structures between individual brains, we compared single patients with known lesions to a large normal control group to detect clusters of abnormal cortical thickness, gray-white matter contrast, local gyrification, sulcal depth, jacobian distance and curvature. To assess the effects of threshold and smoothing on detection sensitivity and specificity, we systematically varied these parameters with different thresholds and smoothing levels. To test the effectiveness of the technique to detect lesions of epileptogenic character, we compared the detected structural abnormalities to expert-tracings, intracranial EEG, pathology and surgical outcome in a homogeneous patient sample. With optimal parameters and by combining thickness and GWC, the surface-based detection method identified 92% of cortical lesions (sensitivity) with few false positives (96% specificity), successfully discriminating patients from controls 94% of the time. The detected structural abnormalities were related to the seizure onset zones, abnormal histology and positive outcome in all surgical patients. However, the method failed to adequately describe lesion extent in most cases. Automated surface-based MRI morphometry, if used with optimized parameters, may be a valuable additional clinical tool to improve the detection of subtle or previously occult malformations and therefore could improve identification of patients with intractable focal epilepsy who may benefit from surgery

Role of Neuroimaging in the Presurgical Evaluation of Epilepsy

A significant minority of patients with focal epilepsy are candidates for resective epilepsy surgery. Structural and functional neuroimaging plays an important role in the presurgical evaluation of theses patients. The most frequent etiologies of pharmacoresistant epilepsy in the adult population are mesial temporal sclerosis, malformations of cortical development, cavernous angiomas, and low-grade neoplasms. High-resolution multiplanar magnetic resonance imaging (MRI) with sequences providing T1 and T2 contrast is the initial imaging study of choice to detect these epileptogenic lesions. The epilepsy MRI protocol can be individually tailored when considering the patient's clinical and electrophysiological data. Metabolic imaging techniques such as positron emission tomography (PET) and single photon emission tomography (SPECT) visualize metabolic alterations of the brain in the ictal and interictal states. These techniques may have localizing value in patients with a normal MRI scan. Functional MRI is helpful in non-invasively identifying areas of eloquent cortex

Thalamic medial dorsal nucleus atrophy in medial temporal lobe epilepsy: A VBM meta-analysis

Purpose: Medial temporal lobe epilepsy (MTLE) is associated with MTLE network pathology within and beyond the hippocampus. The purpose of this meta-analysis was to identify consistent MTLE structural change to guide subsequent targeted analyses of these areas. Methods: We performed an anatomic likelihood estimation (ALE) meta-analysis of 22 whole-brain voxel-based morphometry experiments from 11 published studies. We grouped these experiments in three ways. We then constructed a meta-analytic connectivity model (MACM) for regions of consistent MTLE structural change as reported by the ALE analysis. Key findings: ALE reported spatially consistent structural change across VBM studies only in the epileptogenic hippocampus and the bilateral thalamus; within the thalamus, the medial dorsal nucleus of the thalamus (MDN thalamus) represented the greatest convergence (Pb0.05 corrected for multiple comparisons). The subsequent MACM for the hippocampus and ipsilateral MDN thalamus demonstrated that the hippocampus and ipsilateral MDN thalamus functionally co-activate and are nodes within the same network, suggesting that MDN thalamic damage could result from MTLE network excitotoxicity. Significance: Notwithstanding our large sample of studies, these findings aremore restrictive thanprevious reports and demonstrate the utility of our inclusion filters and of recently modified meta-analyticmethods in approximating clinical relevance. Thalamic pathology is commonly observed in animal and human studies, suggesting it could be a clinically useful indicator. Thalamus-specific research as a clinical marker awaits further investigation