Advanced Imaging Techniques in the Diagnosis of Nonlesional Epilepsy: MRI, MRS, PET, and SPECT

MR-Guided PET Reconstruction: A Potential Advancement for Patients With Epilepsy

ABSTRACT

We report a case of a 33-year-old man with epilepsy and equivocal EEG, MRI signs of mesiotemporal sclerosis, and nondiagnostic standard FDG-PET imaging. The patient underwent repeat FDG-PET/MRI to clarify the sidedness of the epileptogenic focus and to confirm the suspected MTS. The standard PET reconstruction using block sequential regularized expectation maximization failed to provide evidence of a clear epileptogenic focus. However, using MR-guided PET reconstruction, circumscribed hypometabolism was observed in the right-sided entorhinal cortex, compatible with the epileptogenic focus. The MR-guided PET reconstruction provided significantly improved gray/white matter differentiation, enhancing confidence in imaging interpretation.

Clinical study of the effect of 5 kinds of antiepileptic drugs on the postictal state

OBJECTIVE

To compare the effects of levetiracetam（LEV）, lamotrigine(LTG), oxcarbazepine(OXC), topiramate(TPM) and valproate (VPA) on postictal state (PIS).

METHODS

A total of 187 epilepsy patients undergoing monotherapy were enrolled in a long-term follow-up study at the Affiliated Hospital of Yangzhou College. This included 30 patients on levetiracetam, 41 on valproate, 30 on oxcarbazepine, 28 on topiramate, and 31 on lamotrigine. A control group of 28 newly diagnosed or previously untreated epilepsy patients was also included. The Liverpool Seizure Severity Scale 2.0 (LSSS2.0) and the Seizure Severity Questionnaire (SSQ) were utilized to evaluate the patients' condition, with comparison based on the results of the postictal status items. EEG during PIS termination was assessed using the Grand Total EEG score (GTE) as an objective tool to measure the impact of Antiseizure medications (ASMs) on the post-seizure state.

RESULTS

The LSSS2.0 score indicated a statistically significant difference in post-seizure status score among the 5 groups (p < 0.05). The difference between the 5 groups and the control group was statistically significant (p < 0.05). Results of the SSQ demonstrated that all 5 drugs significantly reduced the post-seizure status score compared to the control group (p < 0.05). The GTE score revealed that, in the later stage of the seizure, the GTE score of the levetiracetam group, valproate group, oxcarbazepine group, and lamotrigine group significantly decreased compared to the control group (P < 0.05). There was no significant decrease in the GTE score in the topiramate group (P < 0.05).

CONCLUSION

Levetiracetam, lamotrigine, oxcarbazepine, topiramate, and valproate demonstrate favorable efficacy in ameliorating the severity of post-seizure condition. Further investigations are warranted to assess the potential of other widely employed anti-seizure medications in enhancing post-seizure status.

The significance of multimodality approach in the management of non-lesional drug-resistant focal parietal lobe epilepsies

Due to extensive connectivity of the parietal lobe, non-lesional drug-resistant (DRE) parietal lobe epilepsies (PLEs) are difficult to localize and often imitate other epilepsies. Therefore, patients with PLEs have low rates of seizure freedom following epilepsy surgery. Previous studies have highlighted the need to combine EEG and semiology for more accurate localization of PLEs. As sophisticated tools for localization become more available, the use of multiple different neuroimaging and neurophysiologic diagnostic tests may more readily identify PLE. We hereby report a unique case of a complex localization in a non-lesional PLE, which was initially falsely localized to frontal lobe. This case underscores the utility of voxel-based morphometry (VBM) in identifying an epileptogenic lesion on a non-lesional MRI and the significance of multimodality approach including PET, magnetoencephalopathy (MEG), interictal and ictal EEG, semiology and cortical stimulation for accurate localization of PLEs. Understanding epilepsy through multimodality approach in this fashion can help with accurate localization especially in difficulty to localize and deceptive non-lesional PLEs. PLAIN LANGUAGE SUMMARY: Parietal lobe epilepsies are hard to pinpoint in the brain and can mimic other types of epilepsy, especially when brain MRIs appear normal. As sophisticated tools for locating epilepsies in the brain become more available, using multiple diagnostic tests may help identify parietal lobe epilepsies more easily. We describe a unique case of a parietal lobe epilepsy patient with normal brain MRI whose epilepsy was initially misidentified as being in the frontal lobe. Using various advanced diagnostic tests, we accurately found the epilepsy's true location in the parietal lobe and successfully treated the patient with surgery.

Resting-State fMRI Can Detect Alterations in Seizure Onset and Spread Regions in Patients with Non-Lesional Epilepsy: A Pilot Study

Introduction

Epilepsy is defined as non-lesional (NLE) when a lesion cannot be localized via standard neuroimaging. NLE is known to have a poor response to surgery. Stereotactic electroencephalography (sEEG) can detect functional connectivity (FC) between zones of seizure onset (OZ) and early (ESZ) and late (LSZ) spread. We examined whether resting-state fMRI (rsfMRI) can detect FC alterations in NLE to see whether noninvasive imaging techniques can localize areas of seizure propagation to potentially target for intervention.

Methods

This is a retrospective study of 8 patients with refractory NLE who underwent sEEG electrode implantation and 10 controls. The OZ, ESZ, and LSZ were identified by generating regions around sEEG contacts that recorded seizure activity. Amplitude synchronization analysis was used to detect the correlation of the OZ to the ESZ. This was also done using the OZ and ESZ of each NLE patient for each control. Patients with NLE were compared to controls individually using Wilcoxon tests and as a group using Mann-Whitney tests. Amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), degree of centrality (DoC), and voxel-mirrored homotopic connectivity (VMHC) were calculated as the difference between NLE and controls and compared between the OZ and ESZ and to zero. A general linear model was used with age as a covariate with Bonferroni correction for multiple comparisons.

Results

Five out of 8 patients with NLE showed decreased correlations from the OZ to the ESZ. Group analysis showed patients with NLE had lower connectivity with the ESZ. Patients with NLE showed higher fALFF and ReHo in the OZ but not the ESZ, and higher DoC in the OZ and ESZ. Our results indicate that patients with NLE show high levels of activity but dysfunctional connections in seizure-related areas.

Discussion

rsfMRI analysis showed decreased connectivity directly between seizure-related areas, while FC metric analysis revealed increases in local and global connectivity in seizure-related areas. FC analysis of rsfMRI can detect functional disruption that may expose the pathophysiology underlying NLE.

Magnetic resonance imaging (MRI) volumetry in children with nonlesional epilepsy, does it help?

Background

Epilepsy is a chronic condition characterized by repeated spontaneous seizures. It affects up to 1% of the population worldwide. Children with magnetic resonance imaging (MRI) negative (or “nonlesional”) focal epilepsy constitute the most challenging pharmacoresistant group undergoing pre-neurosurgical evaluation. Volumetric magnetic resonance imaging (VMRI) is a non-invasive brain imaging technique done to measure the volume and structure of specific regions of the brain. It is useful for many things, but primarily for discovering atrophy (wasting away of body tissue) and measuring its progression. The aim of this study is to assess role of volumetric magnetic resonance imaging in evaluation of nonlesional childhood epilepsy in which no specific findings detected in conventional MRI.

Results

There were 20 children with normal MRI brain volumetry (33.3%) and 40 children (66.6%) with abnormal MRI brain volumetry.

Grey matter volume in the abnormal group was significantly higher (P value was 0.001*) than the normal group (mean ± S.D 934.04 ± 118.12 versus 788.57 ± 57.71 respectively). White matter volume in the abnormal group was significantly smaller (P value was < 0.0001*) than in the normal group (mean ± S.D 217.79 ± 65.22 versus 418.07 ± 103.76 respectively). Right hippocampus CA4-DG volume in the abnormal volume group was found to be significantly smaller (P value < 0.0001*) than that of the normal group volume (mean ± S.D 0.095 ± 0.04 versus 0.32 ± 0.36 respectively). Right hippocampus subiculum volume in the abnormal volume group were found to be significantly smaller (P value was < 0.0001*) than that of the normal group volume (mean ± S.D 0.42 ± 0.11 versus 0.84 ± 0.09 respectively). Thalamus volume in the abnormal group was significantly smaller (P value 0.048*) than in the normal group (mean ± S.D 10.235 ± 3.22 versus 11.82 ± 0.75 respectively). Right thalamus was significantly smaller (P value was 0.028*) than in the normal group (mean ± S.D 5.01 ± 1.62 versus 5.91 ± 0.39 respectively). The sensitivity of the right hippocampus subiculum volume and right hippocampus CA4-DG was 100%. The sensitivity of white matter volume and grey matter volume and thalamus was 85% and 75% and 55% respectively. The specificity of the right hippocampus subiculum volume and right hippocampus CA4-DG was 90% and 90% respectively. The specificity of the right hippocampus subiculum volume and right hippocampus CA4-DG and grey matter volume and white matter volume and total hippocampus and thalamus was 100%. The specificity of brain volume was 60%. The accuracy of the right hippocampus subiculum volume and right hippocampus CA4-DG was 100%. The specificity of white matter volume, grey matter volume, thalamus, total hippocampus, and brain volume was 97%, 87%, 65%, 61%, and 57% respectively.

Conclusion

Volumetric magnetic resonance imaging is a promising imaging technique that can provide assistance in evaluation of nonlesional pharmacoresistant childhood epilepsy.

Application value of molecular imaging technology in epilepsy

Epilepsy is a common neurological disease with various seizure types, complicated etiologies, and unclear mechanisms. Its diagnosis mainly relies on clinical history, but an electroencephalogram is also a crucial auxiliary examination. Recently, brain imaging technology has gained increasing attention in the diagnosis of epilepsy, and conventional magnetic resonance imaging can detect epileptic foci in some patients with epilepsy. However, the results of brain magnetic resonance imaging are normal in some patients. New molecular imaging has gradually developed in recent years and has been applied in the diagnosis of epilepsy, leading to enhanced lesion detection rates. However, the application of these technologies in epilepsy patients with negative brain magnetic resonance must be clarified. Thus, we reviewed the relevant literature and summarized the information to improve the understanding of the molecular imaging application value of epilepsy.

Automated fusion of multimodal imaging data for identifying epileptogenic lesions in patients with inconclusive magnetic resonance imaging

Many methods applied to data acquired by various imaging modalities have been evaluated for their benefit in localizing lesions in magnetic resonance (MR) negative epilepsy patients. No approach has proven to be a stand-alone method with sufficiently high sensitivity and specificity. The presented study addresses the potential benefit of the automated fusion of results of individual methods in presurgical evaluation. We collected electrophysiological, MR, and nuclear imaging data from 137 patients with pharmacoresistant MR-negative/inconclusive focal epilepsy. A subgroup of 32 patients underwent surgical treatment with known postsurgical outcomes and histopathology. We employed a Gaussian mixture model to reveal several classes of gray matter tissue. Classes specific to epileptogenic tissue were identified and validated using the surgery subgroup divided into two disjoint sets. We evaluated the classification accuracy of the proposed method at a voxel-wise level and assessed the effect of individual methods. The training of the classifier resulted in six classes of gray matter tissue. We found a subset of two classes specific to tissue located in resected areas. The average classification accuracy (i.e., the probability of correct classification) was significantly higher than the level of chance in the training group (0.73) and even better in the validation surgery subgroup (0.82). Nuclear imaging, diffusion-weighted imaging, and source localization of interictal epileptic discharges were the strongest methods for classification accuracy. We showed that the automatic fusion of results can identify brain areas that show epileptogenic gray matter tissue features. The method might enhance the presurgical evaluations of MR-negative epilepsy patients.

Comparative contribution of magnetoencephalography (MEG) and single-photon emission computed tomography (SPECT) in pre-operative localization for epilepsy surgery: A prospective blinded study

PURPOSE

The aim of this study was to compare the diagnostic value and accuracy of ictal SPECT and inter-ictal magnetoencephalography (MEG) in localizing the site for surgery in persons with drug resistant epilepsy.

METHOD

This was a prospective observational study. Patients expected to undergo epilepsy surgery were enrolled consecutively and the localization results from different imaging modalities were discussed in an epilepsy surgery meet. Odds ratio of good outcome (Engel I) were calculated in patients who underwent surgery in concordance with MEG and SPECT findings. Post-surgical seizure freedom lasting at least 36 months or more was considered the gold standard for determining the diagnostic output of SPECT and MEG.

RESULTS

MEG and SPECT were performed in 101 and 57 patients respectively. In 45 patients SPECT could not be done due to delay in injection or technical factors. The accuracy of MEG and SPECT in localizing the epileptogenic zone was found to be 74.26 % and 78.57 % respectively. The diagnostic odds ratio for Engel I surgical outcome was reported as 2.43 and 5.0 for MEG and SPECT respectively. The diagnostic odds ratio for MEG in whom SPECT was non-informative was found to be 6.57 [95 % CI 1.1, 39.24], although it was not significantly associated with good surgical outcome. MEG was useful in indicating sites for SEEG implantation.

CONCLUSION

SPECT was found to be non-informative for most patients, but reported better diagnostic output than MEG. MEG may be a useful alternative for patients in whom SPECT cannot be done or was non-localizing.

MRI-negative PET-negative epilepsy long-term surgical outcomes: A single-institution retrospective review

PURPOSE

Surgical planning for people with drug resistant non-lesional focal epilepsy can be challenging. Prior studies focus on cases that are only MRI-negative or MRI-negative with PET-positive imaging, but little is known about outcomes in patients with non-lesional findings on both MRI and PET imaging. In this study, we investigate 5-year surgical outcomes in patients who underwent epilepsy surgery for drug resistant MRI/PET-negative focal epilepsy.

METHODS

We collected clinical and testing data on 131 consecutive patients with drug resistant non-lesional epilepsy who were presented at a multidisciplinary epilepsy surgery conference at the New York University Comprehensive Epilepsy Center between 2010 and 2014, and identified those who underwent epilepsy surgery in order to review 5-year surgical outcomes.

RESULTS

There were 103 with non-lesional MRI studies, and of these, 22 had corresponding non-lesional PET imaging. 14 MRI/PET-negative patients pursued a surgical treatment option and 9 underwent resections after intracranial EEG. At 5 years, 77.8 % of patients had favorable (ILAE class 1 and 2) outcomes. Most (77.8 %) had focal cortical dysplasia type Ia (FCDIa) on pathology.

CONCLUSION

These findings suggest that with careful planning and patient selection, surgery for patients with drug resistant MRI/PET-negative focal epilepsy can be successful.

Analysis of the aetiology of epilepsy in 3,216 adult patients attending a tertiary referral center enabled by an electronic patient record

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Large scale studies examining the aetiologies of the epilepsies in existence worldwide are few.

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Assigning causation in epilepsy is a dynamic and evolving diagnostic process owing to continuous advances in science and technology.

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Electronic patient records offer immense clinical and research opportunities to clinicians.

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The data acquisition process used in this study utilised a bespoke extant dynamic clinically utilised electronic heath record.

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This is the first robust large analysis of aetiology following the publication of updated ILAE 2017 classification system.

Purpose

The aim of this study was to review the causes of the epilepsies in our institution, an adult tertiary referral center for neurology and neurosurgery in Dublin, Ireland. Data was obtained from a bespoke epilepsy electronic patient record (EPR).

Methods

Predetermined search parameters of well-established broad categories of epilepsy aetiology were used to identify patients with a diagnosis of epilepsy attending Beaumont Hospital, Dublin. There were 3216 patients that met the inclusion criteria for this study. We included living patients with epilepsy attending our institution. We then excluded patients with a diagnosis of pure non-epileptic attack disorder and patients found to have idiopathic generalised epilepsy (IGE) (n = 382) from our final cohort. We excluded IGE due to the complex polygenic basis underlying this patient group.

Results

An aetiology was identified in 54.3 % (n = 1747) of the total number of patients studied. Of the symptomatic epilepsies, 41.08 % (n = 1321) were acquired and 13.3 % (n = 426) were predominantly of genetic or developmental aetiology. The most common causes of the acquired epilepsies were hippocampal sclerosis (n = 380; 28.75 %), cerebral tumor (n = 279; 21.06 %), traumatic brain injury (n = 248; 18.77 %), stroke and cerebrovascular disease (n = 151; 11.43 %) and perinatal causes (n = 138; 10.45 %). The leading causes in the genetic / developmental category included cavernous haemangiomas (n = 62, 22.22 %), arteriovenous malformations (n = 59; 21.15 %) and cortical dysplasia (n = 55; 19.71 %). The aetiology of a patient’s epilepsy was undetermined in 45.68 % (n = 1469) of individuals.

Conclusion

This study emphasizes the clinical utility of the ILAE’s 2017 revised classification of the epilepsies and highlights the evolving dynamic nature of attributing causality in epilepsy. This is the largest single centre analysis of the aetiology of the epilepsies described in the literature. It is also the first large scale study examining aetiology utilising a bespoke electronic patient record in epilepsy.

Detection of cortical malformations using enhanced synthetic contrast images derived from quantitative T1 maps

The detection of cortical malformations in conventional MR images can be challenging. Prominent examples are focal cortical dysplasias (FCD), the most common cause of drug-resistant focal epilepsy. The two main MRI hallmarks of cortical malformations are increased cortical thickness and blurring of the gray (GM) and white matter (WM) junction. The purpose of this study was to derive synthetic anatomies from quantitative T1 maps for the improved display of the above imaging characteristics in individual patients. On the basis of a T1 map, a mask comprising pixels with T1 values characteristic for GM is created from which the local cortical extent (CE) is determined. The local smoothness (SM) of the GM-WM junctions is derived from the T1 gradient. For display of cortical malformations, the resulting CE and SM maps serve to enhance local intensities in synthetic double inversion recovery (DIR) images calculated from the T1 map. The resulting CE- and/or SM-enhanced DIR images appear hyperintense at the site of cortical malformations, thus facilitating FCD detection in epilepsy patients. However, false positives may arise in areas with naturally elevated CE and/or SM, such as large GM structures and perivascular spaces. In summary, the proposed method facilitates the detection of cortical abnormalities such as cortical thickening and blurring of the GM-WM junction which are typical FCD markers. Still, subject motion artifacts, perivascular spaces, and large normal GM structures may also yield signal hyperintensity in the enhanced synthetic DIR images, requiring careful comparison with clinical MR images by an experienced neuroradiologist to exclude false positives.

The neuronal migration hypothesis of dyslexia: A critical evaluation 30 years on

The capacity for language is one of the key features underlying the complexity of human cognition and its evolution. However, little is known about the neurobiological mechanisms that mediate normal or impaired linguistic ability. For developmental dyslexia, early postmortem studies conducted in the 1980s linked the disorder to subtle defects in the migration of neurons in the developing neocortex. These early studies were reinforced by human genetic analyses that identified dyslexia susceptibility genes and subsequent evidence of their involvement in neuronal migration. In this review, we examine recent experimental evidence that does not support the link between dyslexia and neuronal migration. We critically evaluate gene function studies conducted in rodent models and draw attention to the lack of robust evidence from histopathological and imaging studies in humans. Our review suggests that the neuronal migration hypothesis of dyslexia should be reconsidered, and the neurobiological basis of dyslexia should be approached with a fresh start.

A multimodal concept for invasive diagnostics and surgery based on neuronavigated voxel-based morphometric MRI postprocessing data in previously nonlesional epilepsy

OBJECTIVE

Diagnosis and surgical treatment of refractory and apparent nonlesional focal epilepsy is challenging. Morphometric MRI voxel-based and other postprocessing methods can help to localize the epileptogenic zone and thereby support the planning of further invasive electroencephalography (EEG) diagnostics, and maybe resective epilepsy surgery.

METHODS

The authors developed an algorithm to implement regions of interest (ROI), based on postprocessed MRI data, into a neuronavigation tool. This was followed by stereotactic ROI-guided implantation of depth electrodes and ROI-navigated resective surgery. Data on diagnostic yield, histology, and seizure outcome were collected and evaluated.

RESULTS

Fourteen consecutive patients with apparently nonlesional epilepsy were included in this study. Reevaluation of the MR images with the help of MRI postprocessing analysis led to the identification of probable subtle lesions in 11 patients. Additional information obtained by SPECT imaging and MRI reevaluation suggested possible lesions in the remaining 3 patients. The ROI-guided invasive implantation of EEG yielded interictal and ictal activity in 13 patients who were consequently referred to resective surgery. Despite the apparently negative MRI findings, focal cortical dysplasia was found in 64% of the patients (n = 9). At the last available outcome, 8 patients (57%) were completely seizure free (International League Against Epilepsy Class 1).

CONCLUSIONS

The results demonstrate the feasibility and usefulness of a robust and straightforward algorithm for implementation of MRI postprocessing-based targets into the neuronavigation system. This approach allowed the stereotactic implantation of a low number of depth electrodes only, which confirmed the seizure-onset hypothesis in 90% of the cases without causing any complications. Furthermore, the neuronavigated ROI-guided lesionectomy helped to perform resective surgery in this rather challenging subgroup of patients with apparent nonlesional epilepsy.

Image-Guided Neurosurgery

Image-guided surgery provides more precise targeting, is less invasive, and has improved outcomes when compared with conventional surgical approaches. Imaging is used to plan, monitor progress, and assess results. Because no one modality offers real-time physiological and anatomical information, a wide range of imaging modalities are used at each phase of the surgery. This article will discuss how various modalities are used in image-guided neurosurgery for common brain pathologies.

Computational analysis in epilepsy neuroimaging: A survey of features and methods

Epilepsy affects 65 million people worldwide, a third of whom have seizures that are resistant to anti-epileptic medications. Some of these patients may be amenable to surgical therapy or treatment with implantable devices, but this usually requires delineation of discrete structural or functional lesion(s), which is challenging in a large percentage of these patients.

Advances in neuroimaging and machine learning allow semi-automated detection of malformations of cortical development (MCDs), a common cause of drug resistant epilepsy. A frequently asked question in the field is what techniques currently exist to assist radiologists in identifying these lesions, especially subtle forms of MCDs such as focal cortical dysplasia (FCD) Type I and low grade glial tumors. Below we introduce some of the common lesions encountered in patients with epilepsy and the common imaging findings that radiologists look for in these patients. We then review and discuss the computational techniques introduced over the past 10 years for quantifying and automatically detecting these imaging findings. Due to large variations in the accuracy and implementation of these studies, specific techniques are traditionally used at individual centers, often guided by local expertise, as well as selection bias introduced by the varying prevalence of specific patient populations in different epilepsy centers. We discuss the need for a multi-institutional study that combines features from different imaging modalities as well as computational techniques to definitively assess the utility of specific automated approaches to epilepsy imaging. We conclude that sharing and comparing these different computational techniques through a common data platform provides an opportunity to rigorously test and compare the accuracy of these tools across different patient populations and geographical locations. We propose that these kinds of tools, quantitative imaging analysis methods and open data platforms for aggregating and sharing data and algorithms, can play a vital role in reducing the cost of care, the risks of invasive treatments, and improve overall outcomes for patients with epilepsy.

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We introduce common epileptogenic lesions encountered in patients with drug resistant epilepsy.

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We discuss state of the art computational techniques used to detect lesions.

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There is a need for multi-institutional studies that combine these techniques.

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Clinically validated pipelines alongside the advances in imaging and electrophysiology will improve outcomes.