Abstracts

Rationale: High frequency oscillations (HFOs) are emerging as a new biomarker of epileptogenicity (approximately ~2884 Hz). However, HFOs can also be recorded from normal hippocampus and parahippocampal structures of humans and animals. The objective of this study was to develop a new approach to distinction between pathological and physiological HFOs with magnetoencephalography (MEG) and artificial intelligent (AI) techniques for precise localization of epileptogenic zones. Methods: Sixty patients with epilepsy and 60 age- and gender match healthy subjects were studied with MEG. To precisely measure the spectral power in multiple frequency ranges, MEG data were transformed to time-frequency representation in 1-4 Hz, 4-8 Hz, 8-12 Hz, 13-30 Hz, 30-45 Hz, 65-80 Hz, 80-250 Hz, and 250-600 Hz. Neuromagnetic sources were localized with accumulated source imaging. To compare magnetic sources in multiple frequency ranges, magnetic sources in each frequency range were then color coded to generate a frequency-encoded source imaging (FESI) with MEG Processor. Epileptogenicity of HFOs were quantitatively assessed at source levels. AI techniques including SVD and template matching have been used to build an “expert system” for automatically and intelligently searching epileptic HFOs. Epileptogenic zones in patients with epilepsy were then analyzed with with intracranial recordings and surgical outcomes. Results: Compared with FESI from healthy subjects (controls), FESI from patients with epilepsy showed significantly strength activity in multiple frequency bands. The relative strength of brain activity in 65-80 Hz, 80-250 Hz, and 250-600 Hz were consistently enhanced in epilepsy group than that of controls. In the present study, MEG HFOs and intracranial HFOs were co-localized to the same region in 47 cases, while MEG spikes and intracranial spikes ere co-localized to the same region in 39 cases. With FESI and AI techniques, MEG HFOs and intracranial HFOs were co-localized to the same region in 58 cases, while the conventional spikes did not show any changes. Conclusions: epileptogenic zones could be automatically localized and assessed by using HFOs based FESI and AI techniques. The results suggest that localization of HFOs with FESI and AI techniques will significantly change the outcome of clinical treatment of epilepsy. Funding: This project was partially supported by grant number R21NS072817 and 1R21NS081420-01A1 from the National Institutes of Health, NationalInstitute of Neurological Disorders and Stroke.