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We evaluated whether spike ripples, the combination of epileptiform spikes and ripples, provide a reliable and improved biomarker for the epileptogenic zone compared with other leading interictal biomarkers in a multicentre, international study. We first validated an automated spike ripple detector on intracranial EEG recordings. We then applied this detector to subjects from four centres who subsequently underwent surgical resection with known 1-year outcomes. We evaluated the spike ripple rate in subjects cured after resection [International League Against Epilepsy Class 1 outcome (ILAE 1)] and those with persistent seizures (ILAE 2–6) across sites and recording types. We also evaluated available interictal biomarkers: spike, spike-gamma, wideband high frequency oscillation (HFO, 80–500 Hz), ripple (80–250 Hz) and fast ripple (250–500 Hz) rates using previously validated automated detectors. The proportion of resected events was computed and compared across subject outcomes and biomarkers. Overall, 109 subjects were included. Most spike ripples were removed in subjects with ILAE 1 outcome (P < 0.001), and this was qualitatively observed across all sites and for depth and subdural electrodes (P < 0.001 and P < 0.001, respectively). Among ILAE 1 subjects, the mean spike ripple rate was higher in the resected volume (0.66/min) than in the non-removed tissue (0.08/min, P < 0.001). A higher proportion of spike ripples were removed in subjects with ILAE 1 outcomes compared with ILAE 2–6 outcomes (P = 0.06). Among ILAE 1 subjects, the proportion of spike ripples removed was higher than the proportion of spikes (P < 0.001), spike-gamma (P < 0.001), wideband HFOs (P < 0.001), ripples (P = 0.009) and fast ripples (P = 0.009) removed. At the individual level, more subjects with ILAE 1 outcomes had the majority of spike ripples removed (79%, 38/48) than spikes (69%, P = 0.12), spike-gamma (69%, P = 0.12), wideband HFOs (63%, P = 0.03), ripples (45%, P = 0.01) or fast ripples (36%, P < 0.001) removed. Thus, in this large, multicentre cohort, when surgical resection was successful, the majority of spike ripples were removed. Furthermore, automatically detected spike ripples localize the epileptogenic tissue better than spikes, spike-gamma, wideband HFOs, ripples and fast ripples. [ABSTRACT FROM AUTHOR]

The search for valid biomarkers to aid in epilepsy diagnosis and management is a major goal of the Epilepsy Research Benchmarks. Many papers and grants answer this call by searching for new biomarkers from a wide range of disciplines. However, the academic use of the word "biomarker" is often imprecise. Without proper definition, such work is not well-prepared to progress to the next step of translating these biomarkers into clinical use. In 2016, the Food and Drug Administration and National Institutes of Health collaborated to develop the BEST (Biomarkers, EndpointS, and other Tools) Resource as a guide to adopt formal definitions that aid in pushing successful biomarkers toward regulatory approval. Using the vignette of high-frequency oscillations, which have been proposed as a potential biomarker of several potential aspects of epilepsy, we demonstrate how improper use of the term "biomarker," and lack of a clear context of use, can lead to confusion and difficulty obtaining regulatory approval. Similar conditions are likely in many areas of biomarker research. This Resource should be adopted by all researchers developing epilepsy biomarkers. Adopting the BEST guidelines will improve reproducibility, guide research objectives toward translation, and better target the Epilepsy Benchmarks. [ABSTRACT FROM AUTHOR]

Purpose Recent studies in epilepsy, cognition, and brain machine interfaces have shown the utility of recording intracranial electroencephalography (i EEG) with greater spatial resolution. Many of these studies utilize microelectrodes connected to specialized amplifiers that are optimized for such recordings. We recently measured the impedances of several commercial microelectrodes and demonstrated that they will distort i EEG signals if connected to clinical EEG amplifiers commonly used in most centers. In this study we demonstrate the clinical implications of this effect and identify some of the potential difficulties in using microelectrodes. Methods Human i EEG data were digitally filtered to simulate the signal recorded by a hybrid grid (two macroelectrodes and eight microelectrodes) connected to a standard EEG amplifier. The filtered iEEG data were read by three trained epileptologists, and high frequency oscillations ( HFOs) were detected with a well-known algorithm. The filtering method was verified experimentally by recording an injected EEG signal in a saline bath with the same physical acquisition system used to generate the model. Several electrodes underwent scanning electron microscopy ( SEM). Key Findings Macroelectrode recordings were unaltered compared to the source i EEG signal, but microelectrodes attenuated low frequencies. The attenuated signals were difficult to interpret: all three clinicians changed their clinical scoring of slowing and seizures when presented with the same data recorded on different sized electrodes. The HFO detection algorithm was oversensitive with microelectrodes, classifying many more HFOs than when the same data were recorded with macroelectrodes. In addition, during experimental recordings the microelectrodes produced much greater noise as well as large baseline fluctuations, creating sharply contoured transients, and superimposed 'false' HFOs. SEM of these microelectrodes demonstrated marked variability in exposed electrode surface area, lead fractures, and sharp edges. Significance Microelectrodes should not be used with low impedance (<1 GΩ) amplifiers due to severe signal attenuation and variability that changes clinical interpretations. The current method of preparing microelectrodes can leave sharp edges and nonuniform amounts of exposed wire. Even when recorded with higher impedance amplifiers, microelectrode data are highly prone to artifacts that are difficult to interpret. Great care must be taken when analyzing i EEG from high impedance microelectrodes. [ABSTRACT FROM AUTHOR]