Voxel-based morphometric magnetic resonance imaging (MRI) postprocessing in MRI-negative epilepsies

An Evolutionary Computation Approach to Examine Functional Brain Plasticity

One common research goal in systems neurosciences is to understand how the functional relationship between a pair of regions of interest (ROIs) evolves over time. Examining neural connectivity in this way is well-suited for the study of developmental processes, learning, and even in recovery or treatment designs in response to injury. For most fMRI based studies, the strength of the functional relationship between two ROIs is defined as the correlation between the average signal representing each region. The drawback to this approach is that much information is lost due to averaging heterogeneous voxels, and therefore, the functional relationship between a ROI-pair that evolve at a spatial scale much finer than the ROIs remain undetected. To address this shortcoming, we introduce a novel evolutionary computation (EC) based voxel-level procedure to examine functional plasticity between an investigator defined ROI-pair by simultaneously using subject-specific BOLD-fMRI data collected from two sessions seperated by finite duration of time. This data-driven procedure detects a sub-region composed of spatially connected voxels from each ROI (a so-called sub-regional-pair) such that the pair shows a significant gain/loss of functional relationship strength across the two time points. The procedure is recursive and iteratively finds all statistically significant sub-regional-pairs within the ROIs. Using this approach, we examine functional plasticity between the default mode network (DMN) and the executive control network (ECN) during recovery from traumatic brain injury (TBI); the study includes 14 TBI and 12 healthy control subjects. We demonstrate that the EC based procedure is able to detect functional plasticity where a traditional averaging based approach fails. The subject-specific plasticity estimates obtained using the EC-procedure are highly consistent across multiple runs. Group-level analyses using these plasticity estimates showed an increase in the strength of functional relationship between DMN and ECN for TBI subjects, which is consistent with prior findings in the TBI-literature. The EC-approach also allowed us to separate sub-regional-pairs contributing to positive and negative plasticity; the detected sub-regional-pairs significantly overlap across runs thus highlighting the reliability of the EC-approach. These sub-regional-pairs may be useful in performing nuanced analyses of brain-behavior relationships during recovery from TBI.

Surgical strategies for pediatric epilepsy

Pediatric epilepsy is a debilitating condition that impacts millions of patients throughout the world. Approximately 20-30% of children with recurrent seizures have drug-resistant epilepsy (DRE). For these patients, surgery offers the possibility of not just seizure freedom but significantly improved neurocognitive and behavioral outcomes. The spectrum of surgical options is vast, ranging from outpatient procedures such as vagus nerve stimulation to radical interventions including hemispherectomy. The thread connecting all of these interventions is a common goal-seizure freedom, an outcome that can be achieved safely and durably in a large proportion of patients. In this review, we discuss many of the most commonly performed surgical interventions and describe the indications, complications, and outcomes specific to each.

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.