Association of fast ripples on intracranial EEG and outcomes after epilepsy surgery

Nevalainen, Päivi; Ellenrieder, Nicolás von; Klimeš, Petr; Dubeau, François; Frauscher, Birgit; Gotman, Jean

doi:10.1212/wnl.0000000000010468

Cited by 46 publications

(47 citation statements)

References 46 publications

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“…Among the 8 patients with post-operative MRI, fRonO had the highest accuracy for localizing the EZ, which is consistent with many past studies relating resection of HFOs with outcome 4 , 6 , 7 , 15 , 32 , 54 , 55 . By contrast, fRonO rates had the lowest accuracy of all the HFO types for identifying the SOZ in both intraoperative and sleep recordings.…”

Section: Discussionsupporting

confidence: 88%

“…One contentious issue is whether the spatial distribution of HFO rates during non-REM sleep is stable 15 , 30 , 31 . One recent large study found that the classification accuracy of fast ripples for the EZ was higher when a full night of non-REM sleep was analyzed as opposed to 5-min segments 32 . This issue is of particular importance to comparing intraoperative to sleep recordings, since the duration of the intraoperative recordings are intrinsically limited.…”

Section: Introductionmentioning

confidence: 99%

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Accuracy of high-frequency oscillations recorded intraoperatively for classification of epileptogenic regions

Weiss

Staba

Sharan

et al. 2021

Sci Rep

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To see whether acute intraoperative recordings using stereo EEG (SEEG) electrodes can replace prolonged interictal intracranial EEG (iEEG) recording, making the process more efficient and safer, 10 min of iEEG were recorded following electrode implantation in 16 anesthetized patients, and 1–2 days later during non-rapid eye movement (REM) sleep. Ripples on oscillations (RonO, 80–250 Hz), ripples on spikes (RonS), sharp-spikes, fast RonO (fRonO, 250–600 Hz), and fast RonS (fRonS) were semi-automatically detected. HFO power and frequency were compared between the conditions using a generalized linear mixed-effects model. HFO rates were compared using a two-way repeated measures ANOVA with anesthesia type and SOZ as factors. A receiver-operating characteristic (ROC) curve analysis quantified seizure onset zone (SOZ) classification accuracy, and the scalar product was used to assess spatial reliability. Resection of contacts with the highest rate of events was compared with outcome. During sleep, all HFOs, except fRonO, were larger in amplitude compared to intraoperatively (p < 0.01). HFO frequency was also affected (p < 0.01). Anesthesia selection affected HFO and sharp-spike rates. In both conditions combined, sharp-spikes and all HFO subtypes were increased in the SOZ (p < 0.01). However, the increases were larger during the sleep recordings (p < 0.05). The area under the ROC curves for SOZ classification were significantly smaller for intraoperative sharp-spikes, fRonO, and fRonS rates (p < 0.05). HFOs and spikes were only significantly spatially reliable for a subset of the patients (p < 0.05). A failure to resect fRonO areas in the sleep recordings trended the most sensitive and accurate for predicting failure. In summary, HFO morphology is altered by anesthesia. Intraoperative SEEG recordings exhibit increased rates of HFOs in the SOZ, but their spatial distribution can differ from sleep recordings. Recording these biomarkers during non-REM sleep offers a more accurate delineation of the SOZ and possibly the epileptogenic zone.

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Section: Discussionsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Accuracy of high-frequency oscillations recorded intraoperatively for classification of epileptogenic regions

Weiss

Staba

Sharan

et al. 2021

Sci Rep

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“…According to the EZ theory, if the EZ and SOZ are discordant, then a resection that targets the SOZ should result in little to no improvement in post-operative seizure outcome (Figure 1A). We used rates of HFO as a proxy for the EZ 24, 26, 27, 30, 31, 69, 70 to test the hypothesis that there is less overlap of EZ with the SOZ in non-responders than in responders. We calculated receiver operating characteristic (ROC) curves for each HFO subtype and sharp-spikes (Figure 1B) rates in classifying the SOZ for each of the patient cohorts (Figure 2A-E).…”

Section: Resultsmentioning

confidence: 99%

Graph Theoretical Measures of Fast Ripples Support the Epileptic Network Hypothesis.

Weiss

Pastore

Orosz

et al. 2022

Preprint

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The epileptic network hypothesis and epileptogenic zone (EZ) hypothesis are two theories of ictogenesis. The network hypothesis posits that coordinated activity among interconnected nodes produces seizures. The EZ hypothesis posits that distinct regions are necessary and sufficient for seizure generation. High-frequency oscillations (HFOs), and particularly fast ripples (FR), are thought to be biomarkers of the EZ. We sought to test these theories by comparing HFO rates and networks in surgical responders and non-responders, with no appreciable change in seizure frequency or severity, within a retrospective cohort of 48 patients implanted with stereo-EEG electrodes. We recorded inter-ictal activity during non-rapid eye movement sleep and semi-automatically detected and quantified HFOs. Each electrode contact was localized in normalized coordinates. We found that the accuracy of seizure-onset zone (SOZ) electrode contact classification using HFO rates (ripples 80-250 Hz, and FR 250-600 Hz) was not significantly different in surgical responders and non-responders, suggesting that in non-responders the EZ partially encompassed the SOZ(s) (p>0.05). We also found that in the responders, FR on oscillations exhibited a higher spectral content in the SOZ compared to the non-SOZ (p<1e-5). In contrast, in the non-responders the FR had a lower spectral content in the SOZ (p<1e-5). We constructed two different networks of FR with a spectral content > 350 Hz. The first was a rate-distance network that multiplied the Euclidian distance between FR generating contacts by the average rate of FR in the two contacts. The radius of the rate-distance network, which excluded SOZ nodes, discriminated non-responders, including patients not offered resection or responsive neurostimulation (RNS) due to diffuse multi-focal onsets, with an accuracy of 0.77 [95% confidence interval (CI) 0.56-0.98]. The second FR network was constructed using the mutual information (MI) between the timing of the events to measure functional connectivity. For most non-responders, this network had a longer characteristic path length, lower mean local efficiency in the non-SOZ, and a higher nodal strength among non-SOZ nodes relative to SOZ nodes. The graphical theoretical measures from the rate-distance and MI networks of 22 non-RNS treated patients was used to train a support vector machine, which when tested on 13 distinct patients classified non-responders with an accuracy of 0.92 [95% CI 0.75-1]. These results support the epileptic network hypothesis, refute the EZ hypothesis, and suggest that surgical non-responders, and patients not selected for resection or RNS, exhibit a decentralized FR network consisting of widely distributed, hyperexcitable FR generating nodes.

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“…The occurrence rate of FRs recorded on clinical macroelectrodes depends on vigilance states, showing the highest incidence during sleep 18 . Here, we asked whether FRs detected on micro-wires were also modulated by vigilance states at a fine temporal resolution.…”

Section: Resultsmentioning

confidence: 99%

Local neuronal excitation and global inhibition during epileptic fast ripples in humans

Curot

Barbeau

Despouy

et al. 2021

Preprint

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Understanding the neuronal basis of epileptiform activity is a major challenge in neurology. Interictal epileptiform discharges are associated with fast ripples (FRs, >200 Hz) in the local field potential (LFP) and are a promising marker of the epileptogenic zone. Here, by using a novel hybrid macro-micro depth electrode, combining classic depth recording of LFP and two or three tetrodes enabling up to 15 neurons in local circuits to be recorded simultaneously, we have characterized neuronal responses to FRs on the same hybrid and other electrodes targeting other brain regions. While FRs were associated with increased neuronal activity in local circuits only, they were followed by inhibition in large-scale networks. Neuronal responses to FRs were homogeneous in local networks but differed across brain areas. Similarly, post-FR inhibition varied across recording locations and subjects and was shorter than typical inter-FR intervals, suggesting that this inhibition is a fundamental refractory process for the networks. These findings demonstrate that FRs engage local and global networks and point to network features that pave the way for new diagnostic and therapeutic strategies.

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Association of fast ripples on intracranial EEG and outcomes after epilepsy surgery

Cited by 46 publications

References 46 publications

Accuracy of high-frequency oscillations recorded intraoperatively for classification of epileptogenic regions

Accuracy of high-frequency oscillations recorded intraoperatively for classification of epileptogenic regions

Graph Theoretical Measures of Fast Ripples Support the Epileptic Network Hypothesis.

Local neuronal excitation and global inhibition during epileptic fast ripples in humans

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