Abstract
Objective. High-frequency oscillations (HFOs) have emerged as a promising clinical biomarker for presurgical evaluation in childhood epilepsy. HFOs are commonly classified in stereo-encephalography as ripples (80–200 Hz) and fast ripples (200–500 Hz). Ripples are less specific and not so directly associated with epileptogenic activity because of their physiological and pathological origin. The aim of this paper is to distinguish HFOs in the ripple band and to improve the evaluation of the epileptogenic zone (EZ). Approach. This study constitutes a novel modeling approach evaluated in ten patients from Sant Joan de Deu Pediatric Hospital (Barcelona, Spain), with clearly-defined seizure onset zones (SOZ) during presurgical evaluation. A subject-by-subject basis analysis is proposed: a probabilistic Gaussian mixture model (GMM) based on the combination of specific ripple features is applied for estimating physiological and pathological ripple subpopulations. Main Results. Clear pathological and physiological ripples are identified. Features differ considerably among patients showing within-subject variability, suggesting that individual models are more appropriate than a traditional whole-population approach. The difference in rates inside and outside the SOZ for pathological ripples is significantly higher than when considering all the ripples. These significant differences also appear in signal segments without epileptiform activity. Pathological ripple rates show a sharp decline from SOZ to non-SOZ contacts and a gradual decrease with distance. Significance. This novel individual GMM approach improves ripple classification and helps to refine the delineation of the EZ, as well as being appropriate to investigate the interaction of epileptogenic and propagation networks.
Highlights
High-frequency oscillations (HFOs) have emerged as a promising clinical biomarker for helping in the identification of the epileptogenic zone (EZ), defined as the brain area indispensable for seizure generation [1]
Classification between physiological and pathological ripples Once HFOs were detected for each patient using SGM, independent Gaussian mixture model (GMM) were fitted to each subject and feature to obtain clearly pathological and physiological groups that contained events whose features were more distinctive
Whereas pathological HFOs are more specific to the epileptogenic tissue, physiological HFOs occur across different brain areas, mostly in the occipital and temporal cortex [30]
Summary
High-frequency oscillations (HFOs) have emerged as a promising clinical biomarker for helping in the identification of the epileptogenic zone (EZ), defined as the brain area indispensable for seizure generation [1]. The top priority is the selection of the most appropriate treatment for each child [2] In this sense, individualized HFOs study provides new insights into personalized presurgical evaluation [3]. Frequencies higher than 1 kHz and 2 kHz are required to identify ripples and fast ripples, respectively [9], leading to large storage, high processing, and extended computation time requirements for long-term intracranial EEG recordings [10]. For this reason, recent studies are still focused on the ripple band [11,12,13]
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