Surgical resection of ripple onset predicts outcome in pediatric epilepsy

Tamilia, Eleonora; Park, Eun-Hyoung; Percivati, Stefania; Bolton, Jeffrey; Taffoni, Fabrizio; Peters, Jurriaan M.; Grant, P. Ellen; Pearl, Phillip L.; Madsen, Joseph R.; Papadelis, Christos

doi:10.1002/ana.25295

Cited by 62 publications

(102 citation statements)

References 48 publications

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“…These results, taken together with previous findings, suggest that the notion that at least 4–10 cm 2 of synchronously active cortex is necessary to observe epileptiform discharges on the scalp does not hold for ripples . Moreover, icEEG studies showed that ripples are focal events that can appear in individual subdural contacts or be asynchronously present in different contacts . We thus may speculate that ripples on HD‐EEG or MEG reflect multiple focal generators asynchronously activated within a short latency, while focal ripples on individual icEEG contacts (which constitute the majority of icEEG ripples in children with refractory epilepsy) are most likely missed by HD‐EEG or MEG due to spatial undersampling .…”

Section: Discussionsupporting

confidence: 54%

“…To define the icEEG‐ripple‐zone, we analyzed 5–10 min of interictal icEEG data, recorded using XLTEK NeuroWorks (Natus Medical Inc.), as previously described . We detected ripples using a validated automated detector .…”

Section: Methodsmentioning

confidence: 99%

“…Furthermore, very few studies investigated the localizing value of scalp‐recorded ripples as epilepsy biomarkers for surgery. This may have significant clinical impact since several icEEG studies showed that ripples are not always generated by epileptogenic areas, but can also represent physiological events generated by non‐epileptogenic tissues …”

Section: Introductionmentioning

confidence: 99%

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Scalp ripples as prognostic biomarkers of epileptogenicity in pediatric surgery

Tamilia

Dirodi

Alhilani

et al. 2020

Ann Clin Transl Neurol

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Objective To assess the ability of high‐density Electroencephalography (HD‐EEG) and magnetoencephalography (MEG) to localize interictal ripples, distinguish between ripples co‐occurring with spikes (ripples‐on‐spike) and independent from spikes (ripples‐alone), and evaluate their localizing value as biomarkers of epileptogenicity in children with medically refractory epilepsy. Methods We retrospectively studied 20 children who underwent epilepsy surgery. We identified ripples on HD‐EEG and MEG data, localized their generators, and compared them with intracranial EEG (icEEG) ripples. When ripples and spikes co‐occurred, we performed source imaging distinctly on the data above 80 Hz (to localize ripples) and below 70 Hz (to localize spikes). We assessed whether missed resection of ripple sources predicted poor outcome, separately for ripples‐on‐spikes and ripples‐alone. Similarly, predictive value of spikes was calculated. Results We observed scalp ripples in 16 patients (10 good outcome). Ripple sources were highly concordant to the icEEG ripples (HD‐EEG concordance: 79%; MEG: 83%). When ripples and spikes co‐occurred, their sources were spatially distinct in 83‐84% of the cases. Removing the sources of ripples‐on‐spikes predicted good outcome with 90% accuracy for HD‐EEG (P = 0.008) and 86% for MEG (P = 0.044). Conversely, removing ripples‐alone did not predict outcome. Resection of spike sources (generated at the same time as ripples) predicted good outcome for HD‐EEG (P = 0.036; accuracy = 87%), while did not reach significance for MEG (P = 0.1; accuracy = 80%). Interpretation HD‐EEG and MEG localize interictal ripples with high precision in children with refractory epilepsy. Scalp ripples‐on‐spikes are prognostic, noninvasive biomarkers of epileptogenicity, since removing their cortical generators predicts good outcome. Conversely, scalp ripples‐alone are most likely generated by non‐epileptogenic areas.

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Section: Discussionsupporting

confidence: 54%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Scalp ripples as prognostic biomarkers of epileptogenicity in pediatric surgery

Tamilia

Dirodi

Alhilani

et al. 2020

Ann Clin Transl Neurol

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“…We note that our reproducibility analyses would translate to a host of noninvasive electrophysiology modalities, including scalp EEG and magnetoencephalography (MEG), as the methodology is based generically on event times and locations. Finally, due to nonuniform availability of postresection imaging, we did not attempt to correlate spike propagation patterns with the extent of surgical resection, which has been examined elsewhere …”

Section: Discussionmentioning

confidence: 99%

“…Each coactivation discharge could thus be represented as a spatiotemporal activation sequence , beginning with the earliest spike in the discharge (ie, “leader”) and proceeding through downstream spikes in order of peak latency. For each network, activation sequences were extracted using a previously described algorithm . Briefly, the first detected spike in the network was initialized as the ‘leader’ of a candidate activation sequence, and all subsequent spikes with a latency <50 msec from the leader (or <15 msec from the preceding spike) were appended to the sequence.…”

Section: Methodsmentioning

confidence: 99%

Reproducibility of interictal spike propagation in children with refractory epilepsy

et al. 2019

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Summary Objective Interictal spikes are a characteristic feature of invasive electroencephalography (EEG) recordings in children with refractory epilepsy. Spikes frequently co‐occur across multiple brain regions with discernable latencies, suggesting that spikes can propagate through distributed neural networks. The purpose of this study was to examine the long‐term reproducibility of spike propagation patterns over hours to days of interictal recording. Methods Twelve children (mean age 13.1 years) were retrospectively studied. A mean ± standard deviation (SD) of 47.2 ± 40.1 hours of interictal EEG recordings were examined per patient (range 17.5‐166.5 hours). Interictal recordings were divided into 30‐minute segments. Networks were extracted based on the frequency of spike coactivation between pairs of electrodes. For each 30‐minute segment, electrodes were assigned a “Degree Preference (DP)” based on the tendency to appear upstream or downstream within propagation sequences. The consistency of DPs across segments (“DP‐Stability”) was quantified using the Spearman rank correlation. Results Regions exhibited highly stable preferences to appear upstream, intermediate, or downstream in spike propagation sequences. Across networks, the mean ± SD DP‐Stability was 0.88 ± 0.07, indicating that propagation patterns observed in 30‐minute segments were representative of the patterns observed in the full interictal window. At the group level, regions involved in seizure generation appeared more upstream in spike propagation sequences. Significance Interictal spike propagation is a highly reproducible output of epileptic networks. These findings shed new light on the spatiotemporal dynamics that may constrain the network mechanisms of refractory epilepsy.

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Association of Seizure Spread With Surgical Failure in Epilepsy

et al. 2019

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IMPORTANCE Seizures recur in as many as half of patients who undergo surgery for drug-resistant temporal lobe epilepsy (TLE). Understanding why TLE is resistant to surgery in some patients may reveal insights into epileptogenic networks and direct new therapies to improve outcomes. OBJECTIVE To characterize features of surgically refractory TLE. DESIGN, SETTING, AND PARTICIPANTS Medical records from a comprehensive epilepsy center were retrospectively reviewed for 131 patients who received a standard anteromedial temporal resection by a single surgeon from January 1, 2000, to December 31, 2015. Thirteen patients were excluded for having less than 1 year of follow-up. Patients at the highest risk for seizure recurrence were identified. Intracranial electroencephalogram (iEEG) analyses generated 3-dimensional seizure spread representations and quantified rapid seizure spread. The final analyses of seizure outcome and follow-up data were performed in June 2017. MAIN OUTCOMES AND MEASURES The Engel class seizure outcome following surgery was evaluated for all patients, defining seizure recurrence as Engel class II or greater. Intracranial recordings of neocortical grids/strips and depth electrodes were analyzed visually for seizure spread. Fast β power was projected onto reconstructions of patients' brain magnetic resonance imaging scans to visualize spread patterns and was quantified to compare power within vs outside resective margins. RESULTS Of 118 patients with 1 year of follow-up or more (mean [SD], 6.5 [4.6] years), 66 (55.9%) were women and 52 (44.1%) were men (median age, 39 years [range, 4-66 years]). The cumulative probability of continuous Engel class I seizure freedom since surgery at postoperative year 10 and afterward was 65.6%, with 92% of recurrences in years 1 to 3. Multivariable statistical analyses found that the selection for iEEG study was the most reliable predictor of seizure recurrence, with a mixed-effects model estimating that the Engel score in the iEEG cohort was higher by a mean (SD) of 1.1 (0.33) (P = .001). In patients with iEEG results, rapid seizure spread in less than 10 seconds was associated with recurrence (hazard ratio, 5.99; 95% CI, 1.7-21.1; P < .01). In the first 10 seconds of seizures, fast β power activity outside the resective margins in the lateral temporal cortex was significantly greater in patients whose seizures recurred compared with patients who were seizure-free (mean [SEM], 137.5% [16.8%] vs 93.4% [4.6%]; P < .05). CONCLUSIONS AND SIGNIFICANCE Rapid seizure spread outside anteromedial temporal resection resective margins plays a significant role in the surgical failure of drug-resistant TLE. Seizure control after epilepsy surgery might be improved by investigating areas of early spread as candidates for resection or neuromodulation.

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Surgical resection of ripple onset predicts outcome in pediatric epilepsy

Cited by 62 publications

References 48 publications

Scalp ripples as prognostic biomarkers of epileptogenicity in pediatric surgery

Scalp ripples as prognostic biomarkers of epileptogenicity in pediatric surgery

Reproducibility of interictal spike propagation in children with refractory epilepsy

Association of Seizure Spread With Surgical Failure in Epilepsy

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