Quantitative relaxometry and diffusion MRI for lateralization in MTS and non-MTS temporal lobe epilepsy.

We developed novel methodology for investigating the use of quantitative relaxometry (T1 and T2) and diffusion tensor imaging (DTI) for lateralization in temporal lobe epilepsy. Patients with mesial temporal sclerosis confirmed by pathology (N=8) and non-MTS unilateral temporal lobe epilepsy (N=6) were compared against healthy controls (N=19) using voxel-based analysis restricted to the anterior temporal lobes, and laterality indices for each MRI metric (T1, T2, fractional anisotropy (FA), mean diffusivity, axial and radial diffusivities) were computed based on the proportion of significant voxels on each side. The diffusivity metrics were the most lateralizing MRI metrics in MTS and non-MTS subsets, with significant differences also seen with FA, T1 and T2. Patient-specific multi-modal laterality indices were also computed and were shown to clearly separate the left-onset and right-onset patients. Marked differences between left-onset and right-onset patients were also observed, with left-onset patients exhibiting stronger laterality indices. Finally, neocortical abnormalities were found to be more common in the non-MTS patients. These preliminary results on a small sample size support the further investigation of quantitative MRI and multi-modal image analysis in clinical determination of seizure onset. The presence of more neocortical abnormalities in the non-MTS group suggests a role in seizure onset or propagation and motivates the investigation of more sensitive histopathological analysis to detect and delineate potentially subtle neocortical pathology

Mesial temporal sclerosis is linked with more widespread white matter changes in temporal lobe epilepsy

AbstractTemporal lobe epilepsy patients with unilateral mesial temporal sclerosis (TLE+uMTS) have been demonstrated to have extensive white matter abnormalities both ipsilateral and contralateral to the seizure onset zone. However, comparatively less is known about the white matter integrity of TLE patients without MTS (non-lesional TLE, nl-TLE). The purpose of the study was to investigate the diffusion properties of thirteen major white matter tracts in patients with TLE+uMTS and nl-TLE. Diffusion tensor imaging (DTI) was performed on 23 TLE+uMTS (15 left MTS and 8 right MTS), 15nl-TLE and 21 controls. Thirteen tracts were delineated by tractography and their diffusion parameters compared for the two TLE groups relative to controls, with left and right hemispheres combined per tract. A subgroup analysis investigated left and right MTS separately. Compared to controls, reduced anisotropy was detected in ten tracts for TLE+uMTS, but only the parahippocampal cingulum and tapetum for nl-TLE. Right MTS subgroup showed reduced anisotropy in 7 tracts bilaterally (3 limbic, 3 association, 1 projection) and 2 tracts ipsilaterally (1 association, 1 projection) and the body of the corpus callosum whereas the left MTS subgroup showed reduced anisotropy in 4 tracts bilaterally (2 limbic, 1 association, 1 projection) and 2 tracts ipsilaterally (1 limbic, 1 association). Diffusion abnormalities in tracts were observed within and beyond the temporal lobe in TLE+uMTS and were more widespread than in nl-TLE. Patients with right MTS had more extensive, bilateral abnormalities in comparison to left MTS. These findings suggest different dysfunctional networks in TLE patients with and without MTS

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

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

Preoperative automated fibre quantification predicts postoperative seizure outcome in temporal lobe epilepsy

Approximately one in every two patients with pharmacoresistant temporal lobe epilepsy will not be rendered completely seizure-free after temporal lobe surgery. The reasons for this are unknown and are likely to be multifactorial. Quantitative volumetric magnetic resonance imaging techniques have provided limited insight into the causes of persistent postoperative seizures in patients with temporal lobe epilepsy. The relationship between postoperative outcome and preoperative pathology of white matter tracts, which constitute crucial components of epileptogenic networks, is unknown. We investigated regional tissue characteristics of preoperative temporal lobe white matter tracts known to be important in the generation and propagation of temporal lobe seizures in temporal lobe epilepsy, using diffusion tensor imaging and automated fibre quantification. We studied 43 patients with mesial temporal lobe epilepsy associated with hippocampal sclerosis and 44 healthy controls. Patients underwent preoperative imaging, amygdalohippocampectomy and postoperative assessment using the International League Against Epilepsy seizure outcome scale. From preoperative imaging, the fimbria-fornix, parahippocampal white matter bundle and uncinate fasciculus were reconstructed, and scalar diffusion metrics were calculated along the length of each tract. Altogether, 51.2% of patients were rendered completely seizure-free and 48.8% continued to experience postoperative seizure symptoms. Relative to controls, both patient groups exhibited strong and significant diffusion abnormalities along the length of the uncinate bilaterally, the ipsilateral parahippocampal white matter bundle, and the ipsilateral fimbria-fornix in regions located within the medial temporal lobe. However, only patients with persistent postoperative seizures showed evidence of significant pathology of tract sections located in the ipsilateral dorsal fornix and in the contralateral parahippocampal white matter bundle. Using receiver operating characteristic curves, diffusion characteristics of these regions could classify individual patients according to outcome with 84% sensitivity and 89% specificity. Pathological changes in the dorsal fornix were beyond the margins of resection, and contralateral parahippocampal changes may suggest a bitemporal disorder in some patients. Furthermore, diffusion characteristics of the ipsilateral uncinate could classify patients from controls with a sensitivity of 98%; importantly, by co-registering the preoperative fibre maps to postoperative surgical lacuna maps, we observed that the extent of uncinate resection was significantly greater in patients who were rendered seizure-free, suggesting that a smaller resection of the uncinate may represent insufficient disconnection of an anterior temporal epileptogenic network. These results may have the potential to be developed into imaging prognostic markers of postoperative outcome and provide new insights for why some patients with temporal lobe epilepsy continue to experience postoperative seizures

Automated tractography in patients with temporal lobe epilepsy using TRActs Constrained by UnderLying Anatomy (TRACULA)

Purpose A detailed understanding of white matter tract alterations in patients with temporal lobe epilepsy (TLE) is important as it may provide useful information for likely side of seizure onset, cognitive impairment and postoperative prognosis. However, most diffusion-tensor imaging (DTI) studies have relied on manual reconstruction of tract bundles, despite the recent development of automated techniques. In the present study, we used an automated white matter tractography analysis approach to quantify temporal lobe white matter tract alterations in TLE and determine the relationships between tract alterations, the extent of hippocampal atrophy and the chronicity and severity of the disorder. Methods We acquired preoperative T1-weighted and DTI data in 64 patients with well-characterized TLE, with imaging and histopathological evidence of hippocampal sclerosis. Identical acquisitions were collected for 44 age- and sex-matched healthy controls. We employed automatic probabilistic tractography DTI analysis using TRActs Constrained by UnderLying Anatomy (TRACULA) available in context of Freesurfer software for the reconstruction of major temporal lobe tract bundles. We determined the factors influencing probabilistic tract reconstruction and investigated alterations of DTI scalar metrics along white matter tracts with respect to hippocampal volume, which was automatically estimated using Freesurfer's morphometric pipelines. We also explored the relationships between white matter tract alterations and duration of epilepsy, age of onset of epilepsy and seizure burden (defined as a function of seizure frequency and duration of epilepsy). Results Whole-tract diffusion characteristics of patients with TLE differed according to side of epilepsy and were significantly different between patients and controls. Waypoint comparisons along each tract revealed that patients had significantly altered tissue characteristics of the ipsilateral inferior-longitudinal, uncinate fasciculus, superior longitudinal fasciculus and cingulum relative to controls. Changes were more widespread (ipsilaterally and contralaterally) in patients with left TLE while patients with right TLE showed changes that remained spatially confined in ipsilateral tract regions. We found no relationship between DTI alterations and volume of the epileptogenic hippocampus. DTI alterations of anterior ipsilateral uncinate and inferior-longitudinal fasciculus correlated with duration of epilepsy (over and above effects of age) and age at onset of epilepsy. Seizure burden correlated with tissue characteristics of the uncinate fasciculus. Conclusion This study shows that TRACULA permits the detection of alterations of DTI tract scalar metrics in patients with TLE. It also provides the opportunity to explore relationships with structural volume measurements and clinical variables along white matter tracts. Our data suggests that the anterior temporal lobe portions of the uncinate and inferior-longitudinal fasciculus may be particularly vulnerable to pathological alterations in patients with TLE. These alterations are unrelated to the extent of hippocampal atrophy (and therefore potentially mediated by independent mechanisms) but influenced by chronicity and severity of the disorder

International Veterinary Epilepsy Task Force recommendations for a veterinary epilepsy-specific MRI protocol

Epilepsy is one of the most common chronic neurological diseases in veterinary practice. Magnetic resonance imaging (MRI) is regarded as an important diagnostic test to reach the diagnosis of idiopathic epilepsy. However, given that the diagnosis requires the exclusion of other differentials for seizures, the parameters for MRI examination should allow the detection of subtle lesions which may not be obvious with existing techniques. In addition, there are several differentials for idiopathic epilepsy in humans, for example some focal cortical dysplasias, which may only apparent with special sequences, imaging planes and/or particular techniques used in performing the MRI scan. As a result, there is a need to standardize MRI examination in veterinary patients with techniques that reliably diagnose subtle lesions, identify post-seizure changes, and which will allow for future identification of underlying causes of seizures not yet apparent in the veterinary literature. There is a need for a standardized veterinary epilepsy-specific MRI protocol which will facilitate more detailed examination of areas susceptible to generating and perpetuating seizures, is cost efficient, simple to perform and can be adapted for both low and high field scanners. Standardisation of imaging will improve clinical communication and uniformity of case definition between research studies. A 6–7 sequence epilepsy-specific MRI protocol for veterinary patients is proposed and further advanced MR and functional imaging is reviewed

Quantitative MRI correlates of hippocampal and neocortical pathology in intractable temporal lobe epilepsy

Intractable or drug-resistant epilepsy occurs in over 30% of epilepsy patients, with many of these patients undergoing surgical excision of the affected brain region to achieve seizure control. Advances in MRI have the potential to improve surgical treatment of epilepsy through improved identification and delineation of lesions. However, validation is currently needed to investigate histopathological correlates of these new imaging techniques. The purpose of this work is to investigate histopathological correlates of quantitative relaxometry and DTI from hippocampal and neocortical specimens of intractable TLE patients. To achieve this goal I developed and evaluated a pipeline for histology to in-vivo MRI image registration, which finds dense spatial correspondence between both modalities. This protocol was divided in two steps whereby sparsely sectioned histology from temporal lobe specimens was first registered to the intermediate ex-vivo MRI which is then registered to the in-vivo MRI, completing a pipeline for histology to in-vivo MRI registration. When correlating relaxometry and DTI with neuronal density and morphology in the temporal lobe neocortex, I found T1 to be a predictor of neuronal density in the neocortical GM and demonstrated that employing multi-parametric MRI (combining T1 and FA together) provided a significantly better fit than each parameter alone in predicting density of neurons. This work was the first to relate in-vivo T1 and FA values to the proportion of neurons in GM. When investigating these quantitative multimodal parameters with histological features within the hippocampal subfields, I demonstrated that MD correlates with neuronal density and size, and can act as a marker for neuron integrity within the hippocampus. More importantly, this work was the first to highlight the potential of subfield relaxometry and diffusion parameters (mainly T2 and MD) as well as volumetry in predicting the extent of cell loss per subfield pre-operatively, with a precision so far unachievable. These results suggest that high-resolution quantitative MRI sequences could impact clinical practice for pre-operative evaluation and prediction of surgical outcomes of intractable epilepsy