Epilepsy: Imaging the epileptic brain--time for new standards

A semi-automatic registration protocol to match ex-vivo high-field 7T MR images and histological slices in surgical samples from patients with drug-resistant epilepsy

BACKGROUND

MRI is a fundamental tool to detect brain structural anomalies and improvement in this technique has the potential to visualize subtle abnormalities currently undetected. Correlation between pre-operative MRI and histopathology is required to validate the neurobiological basis of MRI abnormalities. However, precise MRI-histology matching is very challenging with the surgical samples. We previously developed a coregistration protocol to match the in-vivo MRI with ex-vivo MRI obtained from surgical specimens. Now, we complete the process to successfully align ex-vivo MRI data with the proper digitalized histological sections in an automatic way.

NEW METHOD

The implemented pipeline is composed by the following steps: a) image pre-processing made of MRI and histology volumes conversion and masking; b) gross rigid body alignment between MRI volume and histology virtual slides; c) rigid alignment between each MRI section and histology slice and estimate of the correlation coefficient for each step to select the MRI slice that best matches histology; d) final linear registration of the selected slices.

RESULTS

This method is fully automatic, except for the first masking step, fast and reliable in comparison to the manual one, as assessed using a Bland-Altman plot.

COMPARISON WITH EXISTING METHODS

The visual assessment usually employed for choosing the best fitting ex-vivo MRI slice for each stained section takes hours and requires practice. Goubran et al. (2015) proposed an iterative registration protocol but its aim and methods were different from ours. No others similar methods are reported in the literature.

CONCLUSIONS

This protocol completes our previous pipeline. The ultimate goal will be to apply the entire process to finely investigate the relationship between clinical MRI data and histopathological features in patients with drug-resistant epilepsy.

Quantitative [18]FDG PET asymmetry features predict long-term seizure recurrence in refractory epilepsy

OBJECTIVE

Fluorodeoxyglucose-positron emission tomography (FDG-PET) is an established, independent, strong predictor of surgical outcome in refractory epilepsy. In this study, we explored the added value of quantitative [¹⁸F]FDG-PET features combined with clinical variables, including electroencephalography (EEG), [¹⁸F]FDG-PET, and magnetic resonance imaging (MRI) qualitative interpretations, to predict long-term seizure recurrence (mean post-op follow-up of 5.85 ± 3.77 years).

METHODS

Machine learning predictive models of surgical outcome were created using a random forest classifier trained on quantitative features in 89 patients with drug-refractory temporal lobe epilepsy evaluated at the Hospital of the University of Pennsylvania epilepsy surgery program (2003-2016). Quantitative features were calculated from asymmetry features derived from image processing using Advanced Normalization Tools (ANTs).

RESULTS

The best-performing model used quantification and had an out-of-bag accuracy of 0.71 in identifying patients with seizure recurrence (Engel IB or worse) which outperformed that using qualitative clinical data by 10%. This model is shared through open-source software for research use. In addition, several asymmetry features in temporal and extratemporal regions that were significantly associated with seizure freedom are identified for future study.

SIGNIFICANCE

Complex quantitative [¹⁸F]FDG-PET imaging features can predict seizure recurrence in patients with refractory temporal lobe epilepsy. These initial retrospective results in a cohort with long-term follow-up suggest that using quantitative imaging features from regions in the epileptogenic network can inform the clinical decision-making process.

Recommendations of the Russian League Against Epilepsy (RLAE) on the use of magnetic resonance imaging in the diagnosis of epilepsy

Introduction. The MRI method has revolutionized the diagnosis of epilepsy. However, the widespread adoption of MRI in clinical practice is slowed by an insufficient number of high-field MRI scanners, a shortage of trained specialists, and the lack of standard examination protocols. The aim of this article is to present the Recommendations of the Russian League Against Epilepsy (RLAE) on the use of magnetic resonance imaging in the diagnosis of epilepsy.

Materials and methods. As a structural element of the International League Against Epilepsy (ILAE), the RLAE considers it important to adapt the Protocol developed by ILAE for specialists in Russia and EAEU countries. The working group analyzed and generalized the clinical practice existing in the Russian Federation, the Republic of Kazakhstan, the Republic of Belarus and the Republic of Uzbekistan. These recommendations are intended for doctors in specialized centers of epilepsy surgery, and for doctors in general medical centers. The recommendations are applicable primarily to adult patients, but the general principles are relevant to children as well.

Results. In all patients with convulsive seizures shortly after the first seizure, or patients diagnosed with epilepsy who have an unexplained increase in the frequency of seizures, rapid decrease in cognitive functions or the appearance / worsening of neuropsychiatric symptoms, the RLAE recommends using a unified MR protocol for the neuroimaging of structural sequences in epilepsy with three-dimensional pulse sequences T1 and T2 FLAIR with isotropic voxel 1 × 1 × 1 mm3 and two-dimensional T2- weighted pulse sequences with a pixel size of 1 × 1 mm2 or less. The MRI examination should be combined with EEG or EEG-video monitoring. Using this protocol allows one to set a unified standard for examining patients with epilepsy in order to detect (with high sensitivity) brain lesions playing a key role in the occurrence of seizures. Here, all 13 recommendations are presented.

Conclusion. Implementation of these recommendations in clinical practice will improve the access to high-tech medical care and optimize health care costs. 

WONOEP appraisal: Network concept from an imaging perspective

Neuroimaging techniques applied to a variety of organisms-from zebrafish, to rodents to humans-can offer valuable insights into neuronal network properties and their dysfunction in epilepsy. A wide range of imaging methods used to monitor neuronal circuits and networks during evoked seizures in animal models and advances in functional magnetic resonance imaging (fMRI) applied to patients with epilepsy were discussed during the XIV Workshop on Neurobiology of Epilepsy (XIV WONOEP) organized in 2017 by the Neurobiology Commission of the International League Against Epilepsy (ILAE). We review the growing number of technological approaches developed, as well as the current state of knowledge gained from studies applying these advanced imaging approaches to epilepsy research.

Recommendations for the use of structural magnetic resonance imaging in the care of patients with epilepsy: A consensus report from the International League Against Epilepsy Neuroimaging Task Force

Structural magnetic resonance imaging (MRI) is of fundamental importance to the diagnosis and treatment of epilepsy, particularly when surgery is being considered. Despite previous recommendations and guidelines, practices for the use of MRI are variable worldwide and may not harness the full potential of recent technological advances for the benefit of people with epilepsy. The International League Against Epilepsy Diagnostic Methods Commission has thus charged the 2013-2017 Neuroimaging Task Force to develop a set of recommendations addressing the following questions: (1) Who should have an MRI? (2) What are the minimum requirements for an MRI epilepsy protocol? (3) How should magnetic resonance (MR) images be evaluated? (4) How to optimize lesion detection? These recommendations target clinicians in established epilepsy centers and neurologists in general/district hospitals. They endorse routine structural imaging in new onset generalized and focal epilepsy alike and describe the range of situations when detailed assessment is indicated. The Neuroimaging Task Force identified a set of sequences, with three-dimensional acquisitions at its core, the harmonized neuroimaging of epilepsy structural sequences-HARNESS-MRI protocol. As these sequences are available on most MR scanners, the HARNESS-MRI protocol is generalizable, regardless of the clinical setting and country. The Neuroimaging Task Force also endorses the use of computer-aided image postprocessing methods to provide an objective account of an individual's brain anatomy and pathology. By discussing the breadth and depth of scope of MRI, this report emphasizes the unique role of this noninvasive investigation in the care of people with epilepsy.

Histological and MRI markers of white matter damage in focal epilepsy

Growing evidence highlights the importance of white matter in the pathogenesis of focal epilepsy. Ex vivo and post-mortem studies show pathological changes in epileptic patients in white matter myelination, axonal integrity, and cellular composition. Diffusion-weighted MRI and its analytical extensions, particularly diffusion tensor imaging (DTI), have been the most widely used technique to image the white matter in vivo for the last two decades, and have shown microstructural alterations in multiple tracts both in the vicinity and at distance from the epileptogenic focus. These techniques have also shown promising ability to predict cognitive status and response to pharmacological or surgical treatments. More recently, the hypothesis that focal epilepsy may be more adequately described as a system-level disorder has motivated a shift towards the study of macroscale brain connectivity. This review will cover emerging findings contributing to our understanding of white matter alterations in focal epilepsy, studied by means of histological and ultrastructural analyses, diffusion MRI, and large-scale network analysis. Focus is put on temporal lobe epilepsy and focal cortical dysplasia. This topic was addressed in a special interest group on neuroimaging at the 70th annual meeting of the American Epilepsy Society, held in Houston December 2-6, 2016.

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.

Towards precision medicine in epilepsy surgery

Up to a third of all patients with epilepsy are refractory to medical therapy even in the context of the introduction of new antiepileptic drugs (AEDs) with considerable advantages in safety and tolerability over the last two decades. It has been widely accepted that epilepsy surgery is a highly effective therapeutic option in a selected subset of patients with refractory focal seizure. There is no doubt that accurate localization of the epileptogenic zone (EZ) is crucial to the success of resection surgery for intractable epilepsy. The pre-surgical evaluation requires a multimodality approach wherein each modality provides unique and complimentary information. Accurate localization of EZ still remains challenging, especially in patients with normal features on MRI. Whereas substantial progress has been made in the methods of pre-surgical assessment in recent years, which widened the applicability of surgical treatment for children and adults with refractory seizure. Advances in neuroimaging including voxel-based morphometric MRI analysis, multimodality techniques and computer-aided subtraction ictal SPECT co-registered to MRI have improved our ability to identify subtle structural and metabolic lesions causing focal seizure. Considerable observations from animal model with epilepsy and pre-surgical patients have consistently found a strong correlation between high frequency oscillations (HFOs) and epileptogenic brain tissue that suggest HFOs could be a potential biomarker of EZ. Since SEEG emphasizes the importance to study the spatiotemporal dynamics of seizure discharges, accounting for the dynamic, multidirectional spatiotemporal organization of the ictal discharges, it has greatly deep our understanding of the anatomo-electro-clinical profile of seizure. In this review, we focus on some state-of-the-art pre-surgical investigations that contribute to the precision medicine. Furthermore, advances also provide opportunity to achieve the minimal side effects and maximal benefit individually, which meets the need for the current concept of precision medicine in epilepsy surgery.