Towards precision medicine in epilepsy surgery

High-Frequency Oscillations and Epileptogenic Network

Epilepsy is a network disease caused by aberrant neocortical large-scale connectivity spanning regions on the scale of several centimeters. High-frequency oscillations, characterized by the 80-600 Hz signals in electroencephalography, have been proven to be a promising biomarker of epilepsy that can be used in assessing the severity and susceptibility of epilepsy as well as the location of the epileptogenic zone. However, the presence of a high-frequency oscillation network remains a topic of debate as high-frequency oscillations have been previously thought to be incapable of propagation, and the relationship between high-frequency oscillations and the epileptogenic network has rarely been discussed. Some recent studies reported that high-frequency oscillations may behave like networks that are closely relevant to the epileptogenic network. Pathological highfrequency oscillations are network-driven phenomena and elucidate epileptogenic network development; high-frequency oscillations show different characteristics coincident with the epileptogenic network dynamics, and cross-frequency coupling between high-frequency oscillations and other signals may mediate the generation and propagation of abnormal discharges across the network.

The Legacy of the TTASAAN Report - Premature Conclusions and Forgotten Promises About SPECT Neuroimaging: A Review of Policy and Practice Part II

Brain perfusion single photon emission computed tomography (SPECT) scans were initially developed in 1970s. A key radiopharmaceutical, hexamethylpropyleneamine oxime (HMPAO), was not stabilized until 1993 and most early SPECT scans were performed on single-head gamma cameras. These early scans were of inferior quality. In 1996, the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology (TTASAAN) issued a report regarding the use of SPECT in the evaluation of neurological disorders. This two-part series explores the policies and procedures related to perfusion SPECT functional neuroimaging. In Part I, the comparison between the quality of the SPECT scans and the depth of the data for key neurological and psychiatric indications at the time of the TTASAAN report vs. the intervening 25 years were presented. In Part II, the technical aspects of perfusion SPECT neuroimaging and image processing will be explored. The role of color scales will be reviewed and the process of interpreting a SPECT scan will be presented. Interpretation of a functional brain scans requires not only anatomical knowledge, but also technical understanding on correctly performing a scan, regardless of the scanning modality. Awareness of technical limitations allows the clinician to properly interpret a functional brain scan. With this foundation, four scenarios in which perfusion SPECT neuroimaging, together with other imaging modalities and testing, lead to a narrowing of the differential diagnoses and better treatment. Lastly, recommendations for the revision of current policies and practices are made.

The Legacy of the TTASAAN Report-Premature Conclusions and Forgotten Promises: A Review of Policy and Practice Part I

Brain perfusion single photon emission computed tomography (SPECT) scans were initially developed in 1970's. A key radiopharmaceutical, hexamethylpropyleneamine oxime (HMPAO), was originally approved in 1988, but was unstable. As a result, the quality of SPECT images varied greatly based on technique until 1993, when a method of stabilizing HMPAO was developed. In addition, most SPECT perfusion studies pre-1996 were performed on single-head gamma cameras. In 1996, the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology (TTASAAN) issued a report regarding the use of SPECT in the evaluation of neurological disorders. Although the TTASAAN report was published in January 1996, it was approved for publication in October 1994. Consequently, the reported brain SPECT studies relied upon to derive the conclusions of the TTASAAN report largely pre-date the introduction of stabilized HMPAO. While only 12% of the studies on traumatic brain injury (TBI) in the TTASAAN report utilized stable tracers and multi-head cameras, 69 subsequent studies with more than 23,000 subjects describe the utility of perfusion SPECT scans in the evaluation of TBI. Similarly, dementia SPECT imaging has improved. Modern SPECT utilizing multi-headed gamma cameras and quantitative analysis has a sensitivity of 86% and a specificity of 89% for the diagnosis of mild to moderate Alzheimer's disease-comparable to fluorodeoxyglucose positron emission tomography. Advances also have occurred in seizure neuroimaging. Lastly, developments in SPECT imaging of neurotoxicity and neuropsychiatric disorders have been striking. At the 25-year anniversary of the publication of the TTASAAN report, it is time to re-examine the utility of perfusion SPECT brain imaging. Herein, we review studies cited by the TTASAAN report vs. current brain SPECT imaging research literature for the major indications addressed in the report, as well as for emerging indications. In Part II, we elaborate technical aspects of SPECT neuroimaging and discuss scan interpretation for the clinician.

Transcriptomic profiling of high- and low-spiking regions reveals novel epileptogenic mechanisms in focal cortical dysplasia type II patients

Focal cortical dysplasia (FCD) is a malformation of the cerebral cortex with poorly-defined epileptogenic zones (EZs), and poor surgical outcome in FCD is associated with inaccurate localization of the EZ. Hence, identifying novel epileptogenic markers to aid in the localization of EZ in patients with FCD is very much needed. High-throughput gene expression studies of FCD samples have the potential to uncover molecular changes underlying the epileptogenic process and identify novel markers for delineating the EZ. For this purpose, we, for the first time performed RNA sequencing of surgically resected paired tissue samples obtained from electrocorticographically graded high (MAX) and low spiking (MIN) regions of FCD type II patients and autopsy controls. We identified significant changes in the MAX samples of the FCD type II patients when compared to non-epileptic controls, but not in the case of MIN samples. We found significant enrichment for myelination, oligodendrocyte development and differentiation, neuronal and axon ensheathment, phospholipid metabolism, cell adhesion and cytoskeleton, semaphorins, and ion channels in the MAX region. Through the integration of both MAX vs non-epileptic control and MAX vs MIN RNA sequencing (RNA Seq) data, PLP1, PLLP, UGT8, KLK6, SOX10, MOG, MAG, MOBP, ANLN, ERMN, SPP1, CLDN11, TNC, GPR37, SLC12A2, ABCA2, ABCA8, ASPA, P2RX7, CERS2, MAP4K4, TF, CTGF, Semaphorins, Opalin, FGFs, CALB2, and TNC were identified as potential key regulators of multiple pathways related to FCD type II pathology. We have identified novel epileptogenic marker elements that may contribute to epileptogenicity in patients with FCD and could be possible markers for the localization of EZ.

Contributions of Robotics to the Safety and Efficacy of Invasive Monitoring With Stereoelectroencephalography

The purpose of this review is to provide a discussion of the history and utility of robotics in invasive monitoring for epilepsy surgery using stereoelectroencephalography (sEEG). The authors conducted a literature review of available sources to describe how the advent of surgical robotics has improved the efficacy and ease of performing sEEG surgery. The sEEG method integrates anatomic, electrographic, and clinical information to test hypotheses regarding the localization of the epileptogenic zone (EZ) and has been used in Europe since the 1950s. One of the primary benefits of robot-assisted sEEG implantation techniques is the ability to seamlessly transition between both orthogonal and oblique trajectory types using a single technique. Based on available information, it is our view that, when applied appropriately, robotic sEEG can have a low rate of complications and many advantages over both non-robotic sEEG implantation and traditional craniotomy-based invasive monitoring methods.

Link Prediction Investigation of Dynamic Information Flow in Epilepsy

As a brain disorder, epilepsy is characterized with abnormal hypersynchronous neural firings. It is known that seizures initiate and propagate in different brain regions. Long-term intracranial multichannel electroencephalography (EEG) reflects broadband ictal activity under seizure occurrence. Network-based techniques are efficient in discovering brain dynamics and offering finger-print features for specific individuals. In this study, we adopt link prediction for proposing a novel workflow aiming to quantify seizure dynamics and uncover pathological mechanisms of epilepsy. A dataset of EEG signals was enrolled that recorded from 8 patients with 3 different types of pharmocoresistant focal epilepsy. Weighted networks are obtained from phase locking value (PLV) in subband EEG oscillations. Common neighbor (CN), resource allocation (RA), Adamic-Adar (AA), and Sorenson algorithms are brought in for link prediction performance comparison. Results demonstrate that RA outperforms its rivals. Similarity, matrix was produced from the RA technique performing on EEG networks later. Nodes are gathered to form sequences by selecting the ones with the highest similarity. It is demonstrated that variations are in accordance with seizure attack in node sequences of gamma band EEG oscillations. What is more, variations in node sequences monitor the total seizure journey including its initiation and termination.