MEG detection of high frequency oscillations and intracranial-EEG validation in pediatric epilepsy surgery

Magnetoencephalography for Epilepsy Presurgical Evaluation

PURPOSE OF THE REVIEW

Magnetoencephalography (MEG) is a functional neuroimaging technique that records neurophysiology data with millisecond temporal resolution and localizes it with subcentimeter accuracy. Its capability to provide high resolution in both of these domains makes it a powerful tool both in basic neuroscience as well as clinical applications. In neurology, it has proven useful in its ability to record and localize epileptiform activity. Epilepsy workup typically begins with scalp electroencephalography (EEG), but in many situations, EEG-based localization of the epileptogenic zone is inadequate. The complementary sensitivity of MEG can be crucial in such cases, and MEG has been adopted at many centers as an important resource in building a surgical hypothesis. In this paper, we review recent work evaluating the extent of MEG influence of presurgical evaluations, novel analyses of MEG data employed in surgical workup, and new MEG instrumentation that will likely affect the field of clinical MEG.

RECENT FINDINGS

MEG consistently contributes to presurgical evaluation and these contributions often change the plan for epilepsy surgery. Extensive work has been done to develop new analytic methods for localizing the source of epileptiform activity with MEG. Systems using optically pumped magnetometry (OPM) have been successfully deployed to record and localize epileptiform activity. MEG remains an important noninvasive tool for epilepsy presurgical evaluation. Continued improvements in analytic methodology will likely increase the diagnostic yield of the test. Novel instrumentation with OPM may contribute to this as well, and may increase accessibility of MEG by decreasing cost.

Interictal magnetoencephalography abnormalities to guide intracranial electrode implantation and predict surgical outcome

Intracranial EEG is the gold standard technique for epileptogenic zone localization but requires a preconceived hypothesis of the location of the epileptogenic tissue. This placement is guided by qualitative interpretations of seizure semiology, MRI, EEG and other imaging modalities, such as magnetoencephalography. Quantitative abnormality mapping using magnetoencephalography has recently been shown to have potential clinical value. We hypothesized that if quantifiable magnetoencephalography abnormalities were sampled by intracranial EEG, then patients' post-resection seizure outcome may be better. Thirty-two individuals with refractory neocortical epilepsy underwent magnetoencephalography and subsequent intracranial EEG recordings as part of presurgical evaluation. Eyes-closed resting-state interictal magnetoencephalography band power abnormality maps were derived from 70 healthy controls as a normative baseline. Magnetoencephalography abnormality maps were compared to intracranial EEG electrode implantation, with the spatial overlap of intracranial EEG electrode placement and cerebral magnetoencephalography abnormalities recorded. Finally, we assessed if the implantation of electrodes in abnormal tissue and subsequent resection of the strongest abnormalities determined by magnetoencephalography and intracranial EEG corresponded to surgical success. We used the area under the receiver operating characteristic curve as a measure of effect size. Intracranial electrodes were implanted in brain tissue with the most abnormal magnetoencephalography findings-in individuals that were seizure-free postoperatively (T = 3.9, P = 0.001) but not in those who did not become seizure-free. The overlap between magnetoencephalography abnormalities and electrode placement distinguished surgical outcome groups moderately well (area under the receiver operating characteristic curve = 0.68). In isolation, the resection of the strongest abnormalities as defined by magnetoencephalography and intracranial EEG separated surgical outcome groups well, area under the receiver operating characteristic curve = 0.71 and area under the receiver operating characteristic curve = 0.74, respectively. A model incorporating all three features separated surgical outcome groups best (area under the receiver operating characteristic curve = 0.80). Intracranial EEG is a key tool to delineate the epileptogenic zone and help render individuals seizure-free postoperatively. We showed that data-driven abnormality maps derived from resting-state magnetoencephalography recordings demonstrate clinical value and may help guide electrode placement in individuals with neocortical epilepsy. Additionally, our predictive model of postoperative seizure freedom, which leverages both magnetoencephalography and intracranial EEG recordings, could aid patient counselling of expected outcome.

Detection of pathological high-frequency oscillations in refractory epilepsy patients undergoing simultaneous stereo-electroencephalography and magnetoencephalography

BACKGROUND

Stereo-electroencephalography (SEEG) and magnetoencephalography (MEG) have generally been used independently as part of the pre-surgical evaluation of drug-resistant epilepsy (DRE) patients. However, the possibility of simultaneously employing these recording techniques to determine whether MEG has the potential of offering the same information as SEEG less invasively, or whether it could offer a greater spatial indication of the epileptogenic zone (EZ) to aid surgical planning, has not been previously evaluated.

METHODS

Data from 24 paediatric and adult DRE patients, undergoing simultaneous SEEG and MEG as part of their pre-surgical evaluation, was analysed employing manual and automated high-frequency oscillations (HFOs) detection, and spectral and source localisation analyses.

RESULTS

Twelve patients (50%) were included in the analysis (4 males; mean age=25.08 years) and showed interictal SEEG and MEG HFOs. HFOs detection was concordant between the two recording modalities, but SEEG displayed higher ability of differentiating between deep and superficial epileptogenic sources. Automated HFO detector in MEG recordings was validated against the manual MEG detection method. Spectral analysis revealed that SEEG and MEG detect distinct epileptic events. The EZ was well correlated with the simultaneously recorded data in 50% patients, while 25% patients displayed poor correlation or discordance.

CONCLUSION

MEG recordings can detect HFOs, and simultaneous use of SEEG and MEG HFO identification facilitates EZ localisation during the presurgical planning stage for DRE patients. Further studies are necessary to validate these findings and support the translation of automated HFO detectors into routine clinical practice.

Automated seizure onset zone locator from resting-state functional MRI in drug-resistant epilepsy

OBJECTIVE

Accurate localization of a seizure onset zone (SOZ) from independent components (IC) of resting-state functional magnetic resonance imaging (rs-fMRI) improves surgical outcomes in children with drug-resistant epilepsy (DRE). Automated IC sorting has limited success in identifying SOZ localizing ICs in adult normal rs-fMRI or uncategorized epilepsy. Children face unique challenges due to the developing brain and its associated surgical risks. This study proposes a novel SOZ localization algorithm (EPIK) for children with DRE.

METHODS

EPIK is developed in a phased approach, where fMRI noise-related biomarkers are used through high-fidelity image processing techniques to eliminate noise ICs. Then, the SOZ markers are used through a maximum likelihood-based classifier to determine SOZ localizing ICs. The performance of EPIK was evaluated on a unique pediatric DRE dataset (n = 52). A total of 24 children underwent surgical resection or ablation of an rs-fMRI identified SOZ, concurrently evaluated with an EEG and anatomical MRI. Two state-of-art techniques were used for comparison: (a) least squares support-vector machine and (b) convolutional neural networks. The performance was benchmarked against expert IC sorting and Engel outcomes for surgical SOZ resection or ablation. The analysis was stratified across age and sex.

RESULTS

EPIK outperformed state-of-art techniques for SOZ localizing IC identification with a mean accuracy of 84.7% (4% higher), a precision of 74.1% (22% higher), a specificity of 81.9% (3.2% higher), and a sensitivity of 88.6% (16.5% higher). EPIK showed consistent performance across age and sex with the best performance in those < 5 years of age. It helped achieve a ~5-fold reduction in the number of ICs to be potentially analyzed during pre-surgical screening.

SIGNIFICANCE

Automated SOZ localization from rs-fMRI, validated against surgical outcomes, indicates the potential for clinical feasibility. It eliminates the need for expert sorting, outperforms prior automated methods, and is consistent across age and sex.