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High frequency oscillations relate to cognitive improvement after epilepsy surgery in children
Journal Pre-proofs High frequency oscillations relate to cognitive improvement after epilepsy surgery in children Dongqing Sun, Maryse A. van 't Klooster, Monique M.J. van Schooneveld, Willemiek J.E.M. Zweiphenning, Nicole E.C. van Klink, Cyrille H. Ferrier, Peter H. Gosselaar, Kees P.J. Braun, Maeike Zijlmans PII: DOI: Reference:
S1388-2457(20)30052-3 https://doi.org/10.1016/j.clinph.2020.01.019 CLINPH 2009124
To appear in:
Clinical Neurophysiology
Received Date: Revised Date: Accepted Date:
23 June 2019 19 December 2019 12 January 2020
Please cite this article as: Sun, D., van 't Klooster, M.A., van Schooneveld, M.M.J., Zweiphenning, W.J.E., van Klink, N.E.C., Ferrier, C.H., Gosselaar, P.H., Braun, K.P.J., Zijlmans, M., High frequency oscillations relate to cognitive improvement after epilepsy surgery in children, Clinical Neurophysiology (2020), doi: https://doi.org/ 10.1016/j.clinph.2020.01.019
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High frequency oscillations relate to cognitive improvement after epilepsy surgery in children Dongqing Suna, Maryse A. van ’t Kloostera, Monique M. J. van Schooneveldb, Willemiek J. E. M. Zweiphenninga, Nicole E. C. van Klinka, Cyrille H. Ferriera, Peter H. Gosselaara, Kees P. J. Braunc, Maeike Zijlmansa,d
a
Brain Center Rudolf Magnus, University Medical Center Utrecht, Department of Neurology
and Neurosurgery, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands b
Wilhelmina Children’s Hospital, University Medical Center Utrecht, Department of
Pediatric Psychology, Lundlaan 6, 3584 EA Utrecht, The Netherlands c
Brain Center Rudolf Magnus, University Medical Center Utrecht, Department of Child
Neurology, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands d
Stichting Epilepsie Instellingen Nederland, Achterweg 2, 2103 SW Heemstede, The
Netherlands
Corresponding author: Dongqing Sun G02.230, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands Phone: +31 887555555 E-mail address: [email protected]
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Contact information co-authors: Maryse van ’t Klooster: [email protected] Monique van Schooneveld: [email protected] Willemiek Zweiphenning: [email protected] Nicole van Klink: [email protected] Cyrille Ferrier: [email protected] Peter Gosselaar: [email protected] Kees Braun: [email protected] Maeike Zijlmans: [email protected]
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Abstract Objective To investigate how high frequency oscillations (HFOs; ripples 80-250Hz, fast ripples(FRs) 250-500Hz) and spikes in intra-operative electrocorticography(ioECoG) relate to cognitive outcome after epilepsy surgery in children. Methods We retrospectively included 20 children who were seizure free after epilepsy surgery using ioECoG and determined their intelligence quotients(IQ) pre- and two years postoperatively. We analyzed whether the number of HFOs and spikes in pre- and postresection ioECoGs, and their change in the non-resected areas relate to cognitive improvement (with ≥5 IQ points increase considered to be clinically relevant (=IQ+ group) and <5 IQ points as irrelevant (=IQ- group)). Results The IQ+ group showed significantly more FRs in the resected tissue (p=0.01) and less FRs in the postresection ioECoG (p=0.045) compared to the IQ- group. Postresection decrease of ripples on spikes was correlated with postoperative cognitive improvement (correlation coefficient = −0.62 with p=0.01). Conclusions Postoperative cognitive improvement was related to reduction of pathological HFOs signified by removing FR generating areas with subsequently less residual FRs, and decrease of ripples on spikes in the resection edge of the non-resected area. Significance HFOs recorded in ioECoG could play a role as biomarkers in the prediction and understanding of cognitive outcome after epilepsy surgery.
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Highlights
Postoperative cognitive improvement relates to the removal of fast ripple generating tissue.
Postoperative decrease of ripples on spikes is associated with cognitive improvement.
High frequency oscillations are potential predictive markers for postoperative cognitive outcome.
Keywords: Epilepsy surgery; High Frequency Oscillations, Electrocorticography; Children; Intelligence.
Abbreviations Intra-operative electrocorticography, ioECoG; high frequency oscillations, HFOs; fast ripples, FRs; intelligence quotients, IQ; developmental quotient, DQ; preresection ECoG, preECoG; postresection ECoG, postECoG; ripple on spike, RonS; ripple not on spike, RnonS; FR on spike, FRonS; FR not on spike, FRnonS; Δ, change in.
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1. INTRODUCTION Epilepsy surgery is the most effective and the only potentially curative treatment for patients with focal refractory epilepsy (Ryvlin et al. 2014). A paradigm shift is taking place towards surgery early in life (Pelliccia et al. 2017; Braun and Cross 2018) as refractory epilepsy in children can significantly jeopardize their cognitive development (Elliott et al. 2005; Freitag and Tuxhorn 2005; Van Schooneveld and Braun 2013). Successful pediatric epilepsy surgery may interrupt cognitive regression and improve intellectual outcome (Van Schooneveld and Braun 2013; Braun 2017). Successful surgical treatment depends on the removal or disconnection of the entire epileptogenic zone, while preserving the eloquent cortex (Rosenow and Lüders 2001). Intra-operative electrocorticography (ioECoG) helps to delineate epileptogenic tissue during surgery and the interpretation of ioECoG findings has long been largely based on interictal spikes (Rosenow and Lüders 2001).
High-frequency oscillations (HFOs: ripples 80-250Hz, fast ripples (FRs) 250-500Hz) in the electrocorticography have gained increasing attention as potential new markers for epileptogenic tissue (Jacobs et al. 2008; Wu et al. 2010; Zijlmans et al. 2012; Van Klink et al. 2014). FRs are proposed to be more accurate markers for epileptogenic tissue than spikes (Wu et al. 2010; Zijlmans et al. 2012; van’t Klooster et al. 2015). Surgical resection of the cortical areas containing HFOs in ioECoG relates to postsurgical seizure freedom (Fujiwara et al. 2012; Zijlmans et al. 2012; Höller et al. 2015; van’t Klooster et al. 2015). The increase of physiological ripples after resection is associated with good postsurgical seizure outcome, which may be an early indicator of healthy network reorganization (Van Klink et al. 2014). To increase our understanding of the role of invasively recorded HFOs in pediatric cognitive development after epilepsy surgery, we investigated the relation between the prevalence of
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HFOs in the pre- and postoperative ioECoG and the change of HFOs after surgery and postsurgical cognitive outcome in children.
2. METHODS 2.1 Study design and study population We retrospectively included patients with focal refractory epilepsy who underwent epilepsy surgery at the University Medical Centre in Utrecht, The Netherlands, between 2008 and 2012 from our preselected database (van’t Klooster et al. 2015). One hundred and one patients underwent ioECoG-guided epilepsy surgery at 2048Hz sampling frequency in this period. Van ‘t Klooster et al. included 54 patients and excluded 47 patients: 19 had incomplete data, 13 received long-term invasive EEG-monitoring preceding epilepsy surgery, 9 had recurrent tumor growth or radiotherapy after surgery and 6 underwent disconnective surgery (van’t Klooster et al. 2015). We applied additional exclusion criteria in this database: 1) patients older than 18 years at time of surgery, 2) incomplete follow-up at 2 years and 3) poor postsurgical seizure outcome (Engel 1c and above (Engel et al. 1993)). The ioECoG recordings were performed during surgery before (preECoG) and after tissue resection (postECoG). IoECoG-guided surgical tailoring was based on interictal spikes and spike patterns; HFOs were only analyzed after surgery. Patients without any spikes or HFOs on the preECoG were excluded from the subsequent analysis to ensure feasibility of epileptic event recording.
2.2 Ethical approval The institutional ethical committee approved the study and waived the requirement of written informed consent as the study is retrospective, provided patient data are treated anonymously.
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2.3 Intraoperative ECoG We recorded ioECoG using 4x5 or 4x8 electrode grids and 1x6 or 1x8 electrode strips (AdTech, Racine, WI) placed directly on the cortex. The ioECoG was registered with a 64channel EEG system (MircoMed, Veneto, Italy) at 2048 sampling rate using an anti-aliasing filter at 538Hz. The grids and electrode strips were placed before and after resection in multiple configurations. The resection was tailored during surgery based on interictal spikes and ictiform spike patterns in ioECoG. The recordings preceding the first resection were defined as preECoG and the recordings after the final resection were defined as postECoG. Pre- and postECoG recordings could overlap in space. Propofol was used as general anesthetic during surgery and was stopped during ioECoG recordings to obtain a continuous background pattern while the patients remained asleep. Information about surgical procedures and positioning of the ioECoG electrodes were available from clinical reports. We matched the electrode positions with the photographs taken during surgery based on anatomic structures in Photoshop CS5 (Adobe Systems Inc., San Jose, CA, USA). The positions of electrode pairs in a bipolar montage were assigned as covering the resected area or the nonresected area. The non-resected areas were subdivided into the resection edge (≤1 cm from the eventual resection margin) and the extramarginal area (>1cm from the resection margin). We classified electrode pairs as being positioned in the overlapping area when the electrode pairs of the preECoG and the postECoG sampled the same area.
2.4 HFO and spike analysis We analyzed HFOs in the ioECoG using an automated, MATLAB-based detector adapted from the Montreal Neurological Institute detector (Zelmann et al. 2010; Van Klink et al. 2014). Every identified HFO (ripple or FR), was visually checked in Stellate Harmonie
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Reviewer (v7.0, Montreal, QC, Canada) by one of the two reviewers (MvtK/NvK). When needed a third reviewer (MZ) was consulted to reach consensus. We used a split screen with 80Hz high-pass finite impulse response filter on the left and a 250Hz high-pass finite impulse response filter on the right at a gain of 5 µV/mm for ripples and 1µV/mm for fast ripples, and about 0.4 seconds/page. We visually marked spikes (MvtK) in Stellate Harmonie Reviewer in a bipolar montage with conventional filter settings 0.5–70Hz (IIR filter) at a gain of 75–200µV/mm and 10 seconds/page. Marked spikes were checked by a neurophysiologist (FL). We defined spikes as sharp transients, with minimal amplitude of twice the baseline and maximum duration of 80msec (Alarcon et al. 1997). Spikes and HFOs were scored in the last one-minute epochs of the pre- and postresection ioECoG, to diminish the propofol effect. Epochs were selected to be free of artefacts. Events in all electrodes were counted. Very sharp waves, which escaped the strict definition of spikes, were also marked as spikes if they co-occurred with spikes on other channels at the same time point. HFOs co-occurring with spikes on the same channel at the same time were defined as HFO on spike. We marked spikes independently and blinded for HFOs and vice versa. All events were marked blinded for cognitive and seizure outcome.
2.5 Cognitive assessments Cognitive functioning was assessed preoperatively and 24-months after surgery using standardized intelligence tests or development tests, according to age and cognitive level of the child. Intelligence quotients (IQ) or developmental quotient (DQ) were determined, both with a mean of 100 and a standard deviation of 15. We did not differentiate between IQ and DQ in our analysis as both are highly correlated (Kurita et al. 2003). The following tests (Dutch versions) were administered by the clinical neuropsychologist to capture the child’s cognitive abilities: Bayley Scales of Infant Development II for children of age 1-3 years
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(Bayley 1993), Wechsler Preschool and Primary Scale of Intelligence for children age 3-6 years (Wechsler 2002), Wechsler Intelligence Scale of Children III for children 6-15 years of age (Wechsler 1991) and Wechsler Adult Intelligence Scale III (Wechsler 1997) or Adult Intelligence Test (Kaufman et al. 2014) for children of 16 years and older.
2.6 Statistical analyses We compared the results of the two years postoperative neuropsychological assessments with the preoperative assessments. To assess cognitive outcome, we calculated the changes in IQ (ΔIQ = postoperative IQ – preoperative IQ) and dichotomized the results into two groups: (1) clinically relevant IQ/DQ improvements (≥5 IQ/DQ points increase (=IQ+)), and (2) no clinically relevant improvement (<5 IQ/DQ points increase, equal IQ/DQ or IQ/DQ decline (=IQ-)). Due to the expected small sample size, we decided to analyze data with nonparametric tests. We gave the median with interquartile range (IQR) for continuous variables and the frequency for the categorical variables. Mann-Whitney U tests (MWU-test) were used for continuous variables and Fisher’s exact tests/Fisher-Freeman-Halton tests for categorical variables. We tested the correlation between two continuous variables using the Spearman’s rho test. P-values less than 0.05 were considered to indicate statistical significance. We analyzed the following events in the pre- and postECoG: number of interictal spikes, ripples and FRs; ripples and FRs were categorized based on their co-occurrence with spikes into: (1) ripples on spikes (RonS), (2) ripples not on spikes (RnonS), (3) FRs on spikes (FRonS), (4) FRs not on spikes (FRnonS). The number of events was defined as the total number of events per minute of recording, measured in all electrodes in the preECoG and in the postECoG. If the same brain area was measured several times due to configuration change of the electrodes, the number of events in that area was defined as the mean number of events measures by all electrodes in that area. We used the overlapping areas to compare the postresection change in
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the number of events in the non-resected area. The change in events was calculated by subtracting the number of events in the preECoG from the number of events in the postECoG in those overlapping areas (Δevents = number of events in postECoG – number of events in preECoG). We left patients with no overlapping areas out of this analysis. Statistical analysis was performed in IBM SPSS Statistics 21 (IBM Corp., Armonk, NY).
3. RESULTS 3.1 Population We analyzed the data of 20 children (10 males, median age at surgery 12.0 [6.5-14.0] years) with good seizure outcome (Engel 1a or Engel 1b (Engel et al. 1993)) after two years followup period after epilepsy surgery. This is a selection of our existing patient database of 54 patients who underwent ioECoG assisted epilepsy surgery due to focal refractory epilepsy (van’t Klooster et al. 2015). We additionally excluded 34 patients: 24 patients were adults, 6 had incomplete data and 4 had poor postsurgical seizure outcome [figure 1]. Of the 20 included patients ten children had an epileptic focus in the left hemisphere and the other ten in the right hemisphere. No patients had bilateral or multiple foci. Focal resections were confined to the temporal lobe in nine children and were extra-temporal in eleven. One patient showed no abnormality on MRI. One patient had mesial temporal sclerosis on pathological examination, eleven had low-grade epilepsy-associated tumors (LEATs), seven had malformations of cortical development, and one child had scarring and glial tissue, possibly due to perinatal asphyxia. Six children still used one or more anti-epileptic drugs two years after surgery. Baseline characteristics were distributed equally between both IQ-groups. Twelve patients showed cognitive improvement of five or more IQ points after two years (table 1).
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3.2 Events in ioECoG and cognitive outcome The preECoG showed no spikes in four patients and no FRs in nine patients. These patients were excluded from the subsequent analyses of spikes and FRs. Ripples were present in the preECoG of all patients. We found 10113 spikes in 16 patients (median number electrodes was 36 IQR[27-46]), 13099 ripples in all 20 patients (median number electrodes was 36 IQR[27-46]) and 878 FRs in 11 patients (median number electrodes was 43 IQR[35-48]). In the postECoG of the entire cohort, we detected 4718 spikes in 14 patients (median number electrodes was 20 IQR[16-32]), 5856 ripples in 20 patients (median number electrodes was 19 IQR[16-28]) and 86 FRs in four patients (median number electrodes was 25 IQR[16-41]). We analyzed the relation between events in ioECoG and cognitive outcome. The number of spikes measured in all electrodes of the preECoG and in all electrodes of the postECoG was comparable between the IQ+ and the IQ- groups. The number of spikes in the resected area was borderline significantly higher in the IQ+ group than the IQ- group (p = 0.05; table 2A). The number of ripples registered in all electrodes of the preECoG, in the electrodes of the resected area and in all electrodes of the postECoG was not different between the two outcome groups (table 2B). The IQ+ group showed more FRs in the resected area and less FRs in the postECoG compared to the IQ- group (p = 0.01; p = 0.045, respectively; table 2C). Three of the four patients in the IQ- group had residual FRs after the final resection while one of the seven patients in the IQ+ group had residual FRs (p = 0.09, two-tailed fisher’s exact test). We found no correlation between IQ change and the number of events (spikes and HFOs) when using the continuous scales in the analysis (data not shown).
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3.3 Postoperative change in events in the non-resected area We recorded 243 pairs of bipolar electrodes in the overlapping – and thus non-resected – ECoG areas, varying from two to 29 bipolar channels per patient. The number of electrodes in the overlapping areas did not deviate between the IQ+ group (median number of electrodes 13 IQR[8-17]) and the IQ- group (median number of electrodes 10 IQR[8-21]). Nineteen patients had one or more electrodes overlapping between the preECoG and the postECoG. One patient with good cognitive outcome did not have electrodes in overlapping areas and was thus excluded from this analysis.
3.3.1 Event changes in the resection edge and cognitive outcome We analyzed the association between the postresection changes in spikes and HFOs in the resection edge and cognitive outcome. Spikes tended to decrease more in the IQ+ group than the IQ- group (p = 0.07; table 3A). The correlation analysis revealed that the postresection decrease in spikes was linked to postoperative IQ increase (correlation coefficient = −0.59 with p = 0.03; figure 2). Ripples decreased more in the IQ+ group than in the IQ- group (p = 0.003; table 3A). Further categorizing ripples into ripples co-occurring with spikes and ripples independent from spikes, the analyses showed that postoperative changes in RonS were associated with cognitive outcome (p = 0.04; table 3A). Postresection decrease of ripples was correlated with a favorable cognitive outcome (correlation coefficient = −0.74 with p = 0.002; figure 3). Such negative relationship was also seen between RonS and cognitive outcome (correlation coefficient = −0.62 with p = 0.01; figure 4), but not for RnonS. The postresection change in the number of FRs did not differ between the IQ+ and the IQ- group.
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3.3.2 Event changes in the extra-marginal area and cognitive outcome No significant differences and changes in events were found in the extra-marginal areas.
DISCUSSION We investigated how the cognitive outcome related to the number of HFOs in the PreECoG and PostECoG and the postresection change in the number of HFO in the non-resected area within the context of pediatric epilepsy surgery. We found that the removal of FR-rich areas was related to good cognitive outcome beyond the benefits of seizure freedom on cognitive development. Corresponding with this finding, the number of residual FRs was lower in the postECoG of children with favorable cognitive outcome. The correlation analyses of FRs did not show a significant result in contrast to the dichotomized analyses. This suggests that accurate removal of FR-rich areas yields postoperative cognitive improvement but the absolute number of FRs does not relate to the IQ increase. The difference may also result from the small sample size of FRs. The postoperative change in the number of ripples in the edge of the resected area associated with the cognitive outcome. Decrease of ripples in the resection edge immediate after tissue resection correlated with IQ improvement two years after surgery. We further divided ripples into two groups based on their co-occurrence with spikes: the presumably pathological RonS and the RnonS (Engel et al. 2009; Clemens et al. 2011; Wang et al. 2013). We established that RonS in the resection edge decreased in the IQ+ group whereas they mainly increased in the IQ- group. No association was found between postresection change in RnonS in the nonresected area and cognitive outcome. The prevalence and postresection change in spikes in ioECoG did not relate to postoperative cognitive outcome.
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The relation between HFOs and cognitive outcome independent from the benefits of seizure freedom could be explained by surgical induced alterations in epileptiform discharges, which interfere with the functional deficit zone outside the epileptogenic zone. The epileptogenic zone is defined as the cortical area indispensable for generating seizures, and currently there are no diagnostic tools available to measure it directly. Only if patients become seizure free after epilepsy surgery, we can conclude that the epileptogenic zone was included within the resected area (Rosenow and Lüders 2001; Moosa and Wyllie 2017). In our patients, who were all seizure free and thus have their epileptogenic zone completely resected, the removal of FR generating tissue and less postoperative residual FRs related to better cognitive outcome. The effect of HFOs on cognitive outcome beyond the influence of the epileptogenic zone and clinical seizures could be due to the recover potential of the surrounding functional brain tissue.
FRs, which are generally deemed epileptiform discharges (Wu et al. 2010; Zijlmans et al. 2012; van’t Klooster et al. 2015), may not only relate to seizure genesis but also to network dysfunction. We consider their presence in postECoG to be pathological even though not they no always elicit clinical seizures. Patients may be more likely to experience cognitive improvements if most of the FR generating tissues were removed due to the reduction of network interfering residual FRs (Ewell et al. 2019). Decrease of pathological RonS in the resection edge after surgery may also reflect improved background signal and thus relate to postoperative cognitive improvements. Our results support HFOs being more discriminative markers for pathological network than spikes and uncover its potential predictive value for postoperative cognitive outcome. We hypothesized that physiological ripples could increase after the resection of epileptogenic tissue in the non-resected areas as a reflection of brain plasticity responding to the ceased electrical disruption, especially in patients with good
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cognitive outcome. This could not be confirmed with the present data, maybe because the development of physiological ripples might require extensive network reorganization which is a slow process and could not be reflected in ioECoG recordings immediately after resection.
Our study is limited by the small sample size and the retrospective design. Due to the small cohort, we were not able to perform multivariate analysis including covariates that might have influenced our findings. Different locations of the resected area could lead to deficits in various cognitive domains (Dulay and Busch 2012). Anti-epileptic drugs may disadvantage cognitive outcome (Van Schooneveld and Braun 2013), and bias our selection of seizure free patients by masking the remaining epileptogenic zone. Epilepsy surgery could be more beneficial for the cognitive outcome of children at the lower end of the IQ spectrum than children with average-high IQs, although the differences are only observed after long-term follow-up of six years and not after two years (Freitag and Tuxhorn 2005, Skirrow et al. 2011). Most importantly, the number of events was not corrected for the number of electrodes recorded. Although we cannot exclude that the correlation between ECoG events and postoperative IQ change is partly attributed to differences in the number of electrodes, lobar localization, use of anti-epileptic drugs or presurgical IQ, our two cognitive outcome groups did not significantly deviate with respect to these four variables. Aside from potential confounding baseline characteristics, the ioECoG recording site may have biased our physiological ripple analyses as the prevalence of physiological events depends on the anatomy and thus their recording site (Frauscher et al. 2018). To limit this bias, we also compared the number of ripples before and after surgery in the same location in the same patient.
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We scored spikes and HFOs in all electrodes in one recording. It is possible that the same epileptiform events were measured in several electrodes. Postresection decrease of the number of events could be partially attributed by altered volume conduction and the loss of connectivity rather than epileptogenic source reduction alone; hence decrease in the number of events in the overlapping electrodes not necessarily reflected the amount of epileptogenic source reduction. We do not expect this to introduce bias as the measurements of events in the IQ+ group and the IQ- group would be affected in comparable ways. Decrease in the extent of epileptiform discharges in the brain network is also considered beneficial for cognitive outcome (Ewell et al. 2019). FRs occur focal and have spatial sampling limitations, especially when measuring the deeper structures (Wu et al. 2010). This is inherent in studying intraoperative HFOs. The exclusion of patients without events in preECoG might lead to an underestimation of our results. In spite of this we considered this approach to be more critical because it is in line with the clinical approach: we expect that true epileptiform events are at least present before the resection and thus for the difference between before and after we deemed sampling of events before the resection essential. Also, the dichotomization of the intelligence quotient changes by using five points of improvement as cut-off could be argued. Other studies have used cut-off points varying from 5-15 points (Van Schooneveld and Braun 2013; Viggedal et al. 2013). We choose the lower end of this cut-off range to incorporate subtle cognitive changes, which might be missed otherwise. We choose not to correct for multiple comparisons because the studied relations are partly dependent, and the explorative character of this study in which the relevance of reporting all potential effects transcends the importance of avoiding type I errors.
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Despite these limitations, our study is the first study to investigate the relation between invasively recorded HFOs and cognitive outcome in pediatric epilepsy surgery. We revealed that HFOs in ioECoG were associated with postoperative cognitive outcome and that the resection of FR rich tissue potentially related to good cognitive outcome. This study features as explorative research and provides preliminary evidence of the role of HFOs in postoperative prognosis for cognitive outcome in children. Future prospective studies performed in larger cohort using HFOs based surgical tailoring are needed to obtain more solid evidence for HFOs as promising ioECoG biomarkers. Such studies should provide detailed information of the involved anatomy and preferably include this as a covariate in a multivariate analysis.
5. CONCLUSION Our results illustrate the added value of HFOs as potential predictive markers for cognitive outcome in pediatric epilepsy surgery. The removal of FR-generating tissue and less residual FRs were associated with cognitive improvement in children after epilepsy surgery. This is possibly due to its superior capacity of representing pathological tissue. In addition, the decrease of ripples co-occurring with spikes, the pathological ripples, in the resection edge after surgical resection seems to indicate favorable cognitive outcome. Surgical tailoring using FRs rather than spikes may result in better cognitive outcome in children, and HFOs in ioECoG may predict postsurgical cognitive outcome. Prospective future studies should be conducted to provide more extensive knowledge on this matter.
DECLARATION OF COMPETING INTEREST None of the authors have potential conflicts of interest to be disclosed.
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ACKNOWLEDGMENTS Dongqing Sun, Maryse A. van ’t Klooster and Maeike Zijlmans gratefully acknowledge funding from the European Research Council via starting grant 803880. All authors have approved the final version of the article.
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van’t Klooster MA, Van Klink NEC, Leijten FSS, Zelmann R, Gebbink TA, Gosselaar PH, et al. Residual fast ripples in the intraoperative corticogram predict epilepsy surgery outcome. Neurology. 2015;85:120–8.
van ’t Klooster MA, van Klink NEC, Zweiphenning WJEM, Leijten FSS, Zelmann R, Ferrier CH, et al. Tailoring epilepsy surgery with fast ripples in the intraoperative electrocorticogram. Ann Neurol. 2017;81:664–76.
Viggedal G, Olsson I, Carlsson G, Rydenhag B, Uvebrant P. Intelligence two years after epilepsy surgery in children. Epilepsy Behav. 2013;29:565–70.
Wang S, Wang IZ, Bulacio JC, Mosher JC, Gonzalez-Martinez J, Alexopoulos A V., et al. Ripple classification helps to localize the seizure-onset zone in neocortical epilepsy. Epilepsia. 2013;54:370–6.
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Wechsler D. Wechsler Intelligence Scale for Children. 3rd ed. San Antonio: Psychological Corporation; 1991.
Wechsler D. Wechsler adult intelligence scale. 3rd ed. San Antonio: Psychological Corporation; 1997.
Wechsler D. Wechsler Preschool and Primary Scale of Intelligence. 3rd ed. San Antonio: Psychological Corporation; 2002.
Wu JY, Sankar R, Lerner JT, Matsumoto JH, Vinters H V, Mathern GW. Removing interictal fast ripples on electrocorticography linked with seizure freedom in children. Neurology. 2010;75:1686–94.
Zelmann R, Mari F, Jacobs J, Zijlmans M, Chander R, Gotman J. Automatic detector of high frequency oscillations for human recordings with macroelectrodes. Conf Proc IEEE Eng Med Biol Soc. 2010;2010:2329–33.
Zijlmans M, Jiruska P, Zelmann R, Leijten FSS, Jefferys JGR, Gotman J. High-frequency oscillations as a new biomarker in epilepsy. Ann Neurol. 2012;71:169–78.
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Table 1. Baseline characteristics. Table 1
Baseline characteristics
Patient characteristics
All patients (n=20)
Gender (Female)
10
7 (70.0%)
3 (30.0%)
p-value1 = 0.65
Age at surgery (y)
12.0 [6.5-14.0]
12.0 [6.5-14.8]
12.0 [6.5-13.8]
U = 44,50; Z = −0,27; p-value² = 0.81
Age at seizure onset (y)
6.0 [1.0-10.8]
7.0 [1.2-10.0]
3.5 [0.3-11.0]
U = 43.00; Z = −0.39; p-value² = 0,72
Epilepsy duration (y)
4.0 [2.0-8.0]
3.0 [2.0-8.3]
5.0 [1.2-8.0]
U = 47.50; Z = −0.04; p-value² = 0,99
Use of postoperative AED
6
4 (66.7%)
2 (33.3%)
p-value1 = 1.00
Resection region
Temporal
9 {45.0%}
Extra-temporal
IQ improvement (n=12)
No IQ improvement (n=8)
Statistics
7 (77.8%)
2 (22.2%)
11 {55.0%}
5 (45.5%)
6 (54.5%)
p-value1 = 0.12
Focus side (left)
10
6 (60%)
4 (40.0%)
p-value1 = 1.00
MRI abnormality
19
11 (57.9%)
8 (42.1%)
p-value1 = 1.00
Pathology
MTS
1 {5.0%}
1 (100%)
0
LEAT
11 {55.0%}
6 (54.5%)
5 (45.5%)
MCD
7 {35.0%}
5 (71.4%)
2 (28.6%)
Other
1 {5.0%}
0
1 (100%)
p-value3 = 0.60
Number of bipolar electrodes Preresection
36 [27-46]
36 [33-43]
17 [14-31]
U = 47.00; Z = −0.77; p-value² = 0,96
Postresection
18 [16-28]
36 [13-62]
25 [17-28]
U = 38.00; Z = −0.74; p-value² = 0,46
Intelligence Quotient Preoperative
81 [75-88]
Postoperative
90 [78-105]
80 [69-88] 97 [79-105]
85 [76-101]
U = 37.50; Z = −0.81; p-value² = 0,43
83 [78-104]
U = 39.00; Z = −0.69; p-value² = 0,52
Abbreviations: y = years; AED = anti-epileptic drugs; MTS = mesial temporal sclerosis; LEAT = low-grade epilepsy-associated tumors; MCD = malformation of cortical development P-value: 1 = Fisher’s exact test; 2 = Mann-Whitney U test; 3 = Fisher-Freeman-Halton test; * = significant; (%) = percentage in row; {%} = percentage in column
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Table 2: Comparison of the number of events between children with and without postoperative cognitive improvement. Table 2.
Events & postoperative cognitive outcome
A.
Patients with spikes on preECoG (n=16)
Events
IQ improvement (n=9)
No IQ improvement (n=7)
Statistics
Spike preresection
1042 [105 - 1374]
114 [8 - 547]
U = 17.50; Z = −1.48; p-value = 0.15
Spike in resection area
314 [62 - 678]
3 [0 - 105]
U = 13.00; Z = −1.96; p-value = 0.05
Spike postresection
38 [8 - 258] (residu in 8)
45 [2 - 176] (residu in 6)
U = 30.50; Z = − 0,11; p-value = 0.94
B.
Patients with ripples on preECoG (n=20)
Events
IQ improvement (n=12)
No IQ improvement (n=8)
Statistics
Ripple preresection
481 [99 - 1042]
294 [198 - 830]
U = 43.00; Z = −0.38; p-value = 0.73
Ripple in resection area
138 [29 - 387]
49 [4 - 142]
U = 31.00; Z = −1.31; p-value = 0.21
Ripple postresection
45 [25 - 215] (residu in 12)
232 [110 - 488] (residu in 8)
U = 23.00; Z = −1.92; p-value = 0.35
C.
Patients with FR on preECoG (n=11)
Events
IQ improvement (n=7)
No IQ improvement (n=4)
Statistics
FR preresection
69 [9 - 69]
7 [2 - 34]
U = 4.50; Z = −1.80; p-value = 0.08
FR in resection area
12 [6 - 117]
1 [1 - 3]
U = 1.00; Z = −2.46; p-value = 0.01*
FR postresection
0 [0 - 0] (residu in 1)
16 [1 - 45] (residu in 3)
U = 5.00; Z = −1.97; p-value = 0.045*
Table 2A: The number of spikes in ioECoG of the cognitive improvement group vs the no improvement group Table 2B: The number of ripples in ioECoG of the cognitive improvement group vs the no improvement group Table 2C: The number of FRs in ioECoG of the cognitive improvement group vs the no improvement group Abbreviations: n = the number of patients; ioECoG = intra-operative electrocorticography IQ = intelligence quotient; FR = fast ripples P-value: Mann-Whitney U test (exact two-tailed); * = significant; (residu) = residual event registered after resection
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Table 3: Comparison of the postresection change in the number of events in overlapping areas between children with and without postoperative cognitive improvement. Table 3.
Event changes in overlapping electrode locations & Cognitive outcome
A.
Resection edge
ΔEvents
IQ improvement
No IQ improvement
Statistics
ΔSpike
−53.8 [−186.5 - −12.5] (n=6)
−2 [−13 - 0] (n=7)
U = 8.00; Z = −1.86; p-value = 0.07
ΔRipple
−50 [−149 - 21] (n=7)
0 [−4 - 10] (n=8)
U = 4.00; Z = −2.78; p-value = 0.003*
-
ΔRonS
−7 [−45 - 0] (n=7)
0 [0 - 12] (n=8)
U = 10.00; Z = −2.12; p-value = 0.04*
-
ΔRnonS
−19 [−103 - −1] (n=7)
−1 [−5 - 0] (n=8)
U = 12.00; Z = −1.74; p-value = 0.09
−0.5 [−3.3 - 0.5] (n=5)
−0.0 [−0.8 - 15.4] (n=4)
U = 6.00; Z = −1.00; p-value = 0.41
ΔFR -
ΔFRonS
−0.0 [−2.3 - 0.5] (n=5)
−0.0 [−9.0 - 15.4] (n=4)
U = 9.00; Z = −0.26; p-value = 0.88
-
ΔFRnonS
−0.0 [−1.3 - 0.0] (n=5)
−0.0 [−4.5 - 0.0] (n=4)
U = 9.50; Z = −0.15; p-value = 1
B.
Extra-marginal area
ΔEvents
IQ improvement
No IQ improvement
Statistics
ΔSpike
−27 [-166 - 31] (n=9)
9 [−5.0 - 60.0] (n=7)
U = 17.00; Z = −1.54; p-value = 0.14
ΔRipple
−26 [−171.0 – 0.0] (n=11)
−4 [−73.0 – 10.0] (n=8)
U = 33.50; Z = −0.87; p-value = 0.41
-
ΔRonS
−1 [−19.0 – 0.0] (n=11)
3 [0.0 – 21.0] (n=8)
U = 21.00; Z = −1.92; p-value = 0.06
-
ΔRnonS
−21 [−65.0 – 2.0] (n=11)
−11 [−75.0 – 2.0] (n=8)
U = 42.50; Z = −0.12; p-value = 0.90
−0.3 [−2.0 – 0.0] (n=7)
0.5 [−4.5 - 18.3] (n=4)
U = 9.00; Z = −0.95; p-value = 0.41
ΔFR -
ΔFRonS
0.0 [0.0 - 0.0] (n=3)
1 [0.3 – 17.0] (n=4)
U = 5.50; Z = −1.76; p-value = 0.12
-
ΔFRnonS
0.5 [-2.0 - 0.0] (n=7)
0 [−5.3 - 0.8] (n=4)
U = 9.00; Z = −0.97; p-value = 0.36
Table 3A: Changes in events (number of events in postECoG − number of events in preECoG) in resection edge Table 3B: Changes in events ( number of events in postECoG − number of events in preECoG) in extra-marginal area Abbreviations: n = the number of patients; Δ = change in, IQ = intelligence quotient; RonS = Ripples co-occurring with spikes, RnonS = Ripples independent from spikes; FRonS = Fast ripples co-occurring with spikes, FRnonS = Fast ripples independent from spikes; P-value: Mann-Whitney U test; * = statistical significant; − indicates postresection decrease
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Legend Figure 1. Flowchart of patient inclusion.
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Figure 2. Correlation between postresection change in spike and IQ development
The scatterplot reflects the correlation between the postresection change in the number of spikes in the resection edge (X-axis) and the postoperative IQ development (Y-axis) with best fitted linear regression line and 95% interquartile range. Postresection decrease in spikes was positively related with postoperative IQ increase. (Correlation coefficient and p-value calculated using the Spearman’s rho)
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Figure 3. Correlation between postresection change in ripples and IQ development
The scatterplot reflects the correlation between the postresection change in the number of ripples in the resection edge (X-axis) and the postoperative IQ development (Y-axis) with best fitted linear regression line and 95% interquartile range. Postresection decrease in ripples was positively correlated with postoperative IQ increase. (Correlation coefficient and p-value calculated using the Spearman’s rho).
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Figure 4. Correlation between postresection change in RonS and IQ development
The scatterplot reflects the correlation between the postresection change in the number of ripples on spikes (RonS) in the resection edge (X-axis) and the postoperative IQ development (Y-axis) with best fitted linear regression line and 95% interquartile range. Postresection decrease in RonS was positively correlated with postoperative IQ increase. (Correlation coefficient and p-value calculated using the Spearman’s rho).
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Figure 2
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Figure 3
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S1388-2457(20)30052-3 https://doi.org/10.1016/j.clinph.2020.01.019 CLINPH 2009124
To appear in:
Clinical Neurophysiology
Received Date: Revised Date: Accepted Date:
23 June 2019 19 December 2019 12 January 2020
Please cite this article as: Sun, D., van 't Klooster, M.A., van Schooneveld, M.M.J., Zweiphenning, W.J.E., van Klink, N.E.C., Ferrier, C.H., Gosselaar, P.H., Braun, K.P.J., Zijlmans, M., High frequency oscillations relate to cognitive improvement after epilepsy surgery in children, Clinical Neurophysiology (2020), doi: https://doi.org/ 10.1016/j.clinph.2020.01.019
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© 2020 Published by Elsevier B.V. on behalf of International Federation of Clinical Neurophysiology.
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High frequency oscillations relate to cognitive improvement after epilepsy surgery in children Dongqing Suna, Maryse A. van ’t Kloostera, Monique M. J. van Schooneveldb, Willemiek J. E. M. Zweiphenninga, Nicole E. C. van Klinka, Cyrille H. Ferriera, Peter H. Gosselaara, Kees P. J. Braunc, Maeike Zijlmansa,d
a
Brain Center Rudolf Magnus, University Medical Center Utrecht, Department of Neurology
and Neurosurgery, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands b
Wilhelmina Children’s Hospital, University Medical Center Utrecht, Department of
Pediatric Psychology, Lundlaan 6, 3584 EA Utrecht, The Netherlands c
Brain Center Rudolf Magnus, University Medical Center Utrecht, Department of Child
Neurology, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands d
Stichting Epilepsie Instellingen Nederland, Achterweg 2, 2103 SW Heemstede, The
Netherlands
Corresponding author: Dongqing Sun G02.230, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands Phone: +31 887555555 E-mail address: [email protected]
Sun
Contact information co-authors: Maryse van ’t Klooster: [email protected] Monique van Schooneveld: [email protected] Willemiek Zweiphenning: [email protected] Nicole van Klink: [email protected] Cyrille Ferrier: [email protected] Peter Gosselaar: [email protected] Kees Braun: [email protected] Maeike Zijlmans: [email protected]
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Abstract Objective To investigate how high frequency oscillations (HFOs; ripples 80-250Hz, fast ripples(FRs) 250-500Hz) and spikes in intra-operative electrocorticography(ioECoG) relate to cognitive outcome after epilepsy surgery in children. Methods We retrospectively included 20 children who were seizure free after epilepsy surgery using ioECoG and determined their intelligence quotients(IQ) pre- and two years postoperatively. We analyzed whether the number of HFOs and spikes in pre- and postresection ioECoGs, and their change in the non-resected areas relate to cognitive improvement (with ≥5 IQ points increase considered to be clinically relevant (=IQ+ group) and <5 IQ points as irrelevant (=IQ- group)). Results The IQ+ group showed significantly more FRs in the resected tissue (p=0.01) and less FRs in the postresection ioECoG (p=0.045) compared to the IQ- group. Postresection decrease of ripples on spikes was correlated with postoperative cognitive improvement (correlation coefficient = −0.62 with p=0.01). Conclusions Postoperative cognitive improvement was related to reduction of pathological HFOs signified by removing FR generating areas with subsequently less residual FRs, and decrease of ripples on spikes in the resection edge of the non-resected area. Significance HFOs recorded in ioECoG could play a role as biomarkers in the prediction and understanding of cognitive outcome after epilepsy surgery.
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Highlights
Postoperative cognitive improvement relates to the removal of fast ripple generating tissue.
Postoperative decrease of ripples on spikes is associated with cognitive improvement.
High frequency oscillations are potential predictive markers for postoperative cognitive outcome.
Keywords: Epilepsy surgery; High Frequency Oscillations, Electrocorticography; Children; Intelligence.
Abbreviations Intra-operative electrocorticography, ioECoG; high frequency oscillations, HFOs; fast ripples, FRs; intelligence quotients, IQ; developmental quotient, DQ; preresection ECoG, preECoG; postresection ECoG, postECoG; ripple on spike, RonS; ripple not on spike, RnonS; FR on spike, FRonS; FR not on spike, FRnonS; Δ, change in.
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1. INTRODUCTION Epilepsy surgery is the most effective and the only potentially curative treatment for patients with focal refractory epilepsy (Ryvlin et al. 2014). A paradigm shift is taking place towards surgery early in life (Pelliccia et al. 2017; Braun and Cross 2018) as refractory epilepsy in children can significantly jeopardize their cognitive development (Elliott et al. 2005; Freitag and Tuxhorn 2005; Van Schooneveld and Braun 2013). Successful pediatric epilepsy surgery may interrupt cognitive regression and improve intellectual outcome (Van Schooneveld and Braun 2013; Braun 2017). Successful surgical treatment depends on the removal or disconnection of the entire epileptogenic zone, while preserving the eloquent cortex (Rosenow and Lüders 2001). Intra-operative electrocorticography (ioECoG) helps to delineate epileptogenic tissue during surgery and the interpretation of ioECoG findings has long been largely based on interictal spikes (Rosenow and Lüders 2001).
High-frequency oscillations (HFOs: ripples 80-250Hz, fast ripples (FRs) 250-500Hz) in the electrocorticography have gained increasing attention as potential new markers for epileptogenic tissue (Jacobs et al. 2008; Wu et al. 2010; Zijlmans et al. 2012; Van Klink et al. 2014). FRs are proposed to be more accurate markers for epileptogenic tissue than spikes (Wu et al. 2010; Zijlmans et al. 2012; van’t Klooster et al. 2015). Surgical resection of the cortical areas containing HFOs in ioECoG relates to postsurgical seizure freedom (Fujiwara et al. 2012; Zijlmans et al. 2012; Höller et al. 2015; van’t Klooster et al. 2015). The increase of physiological ripples after resection is associated with good postsurgical seizure outcome, which may be an early indicator of healthy network reorganization (Van Klink et al. 2014). To increase our understanding of the role of invasively recorded HFOs in pediatric cognitive development after epilepsy surgery, we investigated the relation between the prevalence of
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HFOs in the pre- and postoperative ioECoG and the change of HFOs after surgery and postsurgical cognitive outcome in children.
2. METHODS 2.1 Study design and study population We retrospectively included patients with focal refractory epilepsy who underwent epilepsy surgery at the University Medical Centre in Utrecht, The Netherlands, between 2008 and 2012 from our preselected database (van’t Klooster et al. 2015). One hundred and one patients underwent ioECoG-guided epilepsy surgery at 2048Hz sampling frequency in this period. Van ‘t Klooster et al. included 54 patients and excluded 47 patients: 19 had incomplete data, 13 received long-term invasive EEG-monitoring preceding epilepsy surgery, 9 had recurrent tumor growth or radiotherapy after surgery and 6 underwent disconnective surgery (van’t Klooster et al. 2015). We applied additional exclusion criteria in this database: 1) patients older than 18 years at time of surgery, 2) incomplete follow-up at 2 years and 3) poor postsurgical seizure outcome (Engel 1c and above (Engel et al. 1993)). The ioECoG recordings were performed during surgery before (preECoG) and after tissue resection (postECoG). IoECoG-guided surgical tailoring was based on interictal spikes and spike patterns; HFOs were only analyzed after surgery. Patients without any spikes or HFOs on the preECoG were excluded from the subsequent analysis to ensure feasibility of epileptic event recording.
2.2 Ethical approval The institutional ethical committee approved the study and waived the requirement of written informed consent as the study is retrospective, provided patient data are treated anonymously.
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2.3 Intraoperative ECoG We recorded ioECoG using 4x5 or 4x8 electrode grids and 1x6 or 1x8 electrode strips (AdTech, Racine, WI) placed directly on the cortex. The ioECoG was registered with a 64channel EEG system (MircoMed, Veneto, Italy) at 2048 sampling rate using an anti-aliasing filter at 538Hz. The grids and electrode strips were placed before and after resection in multiple configurations. The resection was tailored during surgery based on interictal spikes and ictiform spike patterns in ioECoG. The recordings preceding the first resection were defined as preECoG and the recordings after the final resection were defined as postECoG. Pre- and postECoG recordings could overlap in space. Propofol was used as general anesthetic during surgery and was stopped during ioECoG recordings to obtain a continuous background pattern while the patients remained asleep. Information about surgical procedures and positioning of the ioECoG electrodes were available from clinical reports. We matched the electrode positions with the photographs taken during surgery based on anatomic structures in Photoshop CS5 (Adobe Systems Inc., San Jose, CA, USA). The positions of electrode pairs in a bipolar montage were assigned as covering the resected area or the nonresected area. The non-resected areas were subdivided into the resection edge (≤1 cm from the eventual resection margin) and the extramarginal area (>1cm from the resection margin). We classified electrode pairs as being positioned in the overlapping area when the electrode pairs of the preECoG and the postECoG sampled the same area.
2.4 HFO and spike analysis We analyzed HFOs in the ioECoG using an automated, MATLAB-based detector adapted from the Montreal Neurological Institute detector (Zelmann et al. 2010; Van Klink et al. 2014). Every identified HFO (ripple or FR), was visually checked in Stellate Harmonie
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Reviewer (v7.0, Montreal, QC, Canada) by one of the two reviewers (MvtK/NvK). When needed a third reviewer (MZ) was consulted to reach consensus. We used a split screen with 80Hz high-pass finite impulse response filter on the left and a 250Hz high-pass finite impulse response filter on the right at a gain of 5 µV/mm for ripples and 1µV/mm for fast ripples, and about 0.4 seconds/page. We visually marked spikes (MvtK) in Stellate Harmonie Reviewer in a bipolar montage with conventional filter settings 0.5–70Hz (IIR filter) at a gain of 75–200µV/mm and 10 seconds/page. Marked spikes were checked by a neurophysiologist (FL). We defined spikes as sharp transients, with minimal amplitude of twice the baseline and maximum duration of 80msec (Alarcon et al. 1997). Spikes and HFOs were scored in the last one-minute epochs of the pre- and postresection ioECoG, to diminish the propofol effect. Epochs were selected to be free of artefacts. Events in all electrodes were counted. Very sharp waves, which escaped the strict definition of spikes, were also marked as spikes if they co-occurred with spikes on other channels at the same time point. HFOs co-occurring with spikes on the same channel at the same time were defined as HFO on spike. We marked spikes independently and blinded for HFOs and vice versa. All events were marked blinded for cognitive and seizure outcome.
2.5 Cognitive assessments Cognitive functioning was assessed preoperatively and 24-months after surgery using standardized intelligence tests or development tests, according to age and cognitive level of the child. Intelligence quotients (IQ) or developmental quotient (DQ) were determined, both with a mean of 100 and a standard deviation of 15. We did not differentiate between IQ and DQ in our analysis as both are highly correlated (Kurita et al. 2003). The following tests (Dutch versions) were administered by the clinical neuropsychologist to capture the child’s cognitive abilities: Bayley Scales of Infant Development II for children of age 1-3 years
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(Bayley 1993), Wechsler Preschool and Primary Scale of Intelligence for children age 3-6 years (Wechsler 2002), Wechsler Intelligence Scale of Children III for children 6-15 years of age (Wechsler 1991) and Wechsler Adult Intelligence Scale III (Wechsler 1997) or Adult Intelligence Test (Kaufman et al. 2014) for children of 16 years and older.
2.6 Statistical analyses We compared the results of the two years postoperative neuropsychological assessments with the preoperative assessments. To assess cognitive outcome, we calculated the changes in IQ (ΔIQ = postoperative IQ – preoperative IQ) and dichotomized the results into two groups: (1) clinically relevant IQ/DQ improvements (≥5 IQ/DQ points increase (=IQ+)), and (2) no clinically relevant improvement (<5 IQ/DQ points increase, equal IQ/DQ or IQ/DQ decline (=IQ-)). Due to the expected small sample size, we decided to analyze data with nonparametric tests. We gave the median with interquartile range (IQR) for continuous variables and the frequency for the categorical variables. Mann-Whitney U tests (MWU-test) were used for continuous variables and Fisher’s exact tests/Fisher-Freeman-Halton tests for categorical variables. We tested the correlation between two continuous variables using the Spearman’s rho test. P-values less than 0.05 were considered to indicate statistical significance. We analyzed the following events in the pre- and postECoG: number of interictal spikes, ripples and FRs; ripples and FRs were categorized based on their co-occurrence with spikes into: (1) ripples on spikes (RonS), (2) ripples not on spikes (RnonS), (3) FRs on spikes (FRonS), (4) FRs not on spikes (FRnonS). The number of events was defined as the total number of events per minute of recording, measured in all electrodes in the preECoG and in the postECoG. If the same brain area was measured several times due to configuration change of the electrodes, the number of events in that area was defined as the mean number of events measures by all electrodes in that area. We used the overlapping areas to compare the postresection change in
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the number of events in the non-resected area. The change in events was calculated by subtracting the number of events in the preECoG from the number of events in the postECoG in those overlapping areas (Δevents = number of events in postECoG – number of events in preECoG). We left patients with no overlapping areas out of this analysis. Statistical analysis was performed in IBM SPSS Statistics 21 (IBM Corp., Armonk, NY).
3. RESULTS 3.1 Population We analyzed the data of 20 children (10 males, median age at surgery 12.0 [6.5-14.0] years) with good seizure outcome (Engel 1a or Engel 1b (Engel et al. 1993)) after two years followup period after epilepsy surgery. This is a selection of our existing patient database of 54 patients who underwent ioECoG assisted epilepsy surgery due to focal refractory epilepsy (van’t Klooster et al. 2015). We additionally excluded 34 patients: 24 patients were adults, 6 had incomplete data and 4 had poor postsurgical seizure outcome [figure 1]. Of the 20 included patients ten children had an epileptic focus in the left hemisphere and the other ten in the right hemisphere. No patients had bilateral or multiple foci. Focal resections were confined to the temporal lobe in nine children and were extra-temporal in eleven. One patient showed no abnormality on MRI. One patient had mesial temporal sclerosis on pathological examination, eleven had low-grade epilepsy-associated tumors (LEATs), seven had malformations of cortical development, and one child had scarring and glial tissue, possibly due to perinatal asphyxia. Six children still used one or more anti-epileptic drugs two years after surgery. Baseline characteristics were distributed equally between both IQ-groups. Twelve patients showed cognitive improvement of five or more IQ points after two years (table 1).
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3.2 Events in ioECoG and cognitive outcome The preECoG showed no spikes in four patients and no FRs in nine patients. These patients were excluded from the subsequent analyses of spikes and FRs. Ripples were present in the preECoG of all patients. We found 10113 spikes in 16 patients (median number electrodes was 36 IQR[27-46]), 13099 ripples in all 20 patients (median number electrodes was 36 IQR[27-46]) and 878 FRs in 11 patients (median number electrodes was 43 IQR[35-48]). In the postECoG of the entire cohort, we detected 4718 spikes in 14 patients (median number electrodes was 20 IQR[16-32]), 5856 ripples in 20 patients (median number electrodes was 19 IQR[16-28]) and 86 FRs in four patients (median number electrodes was 25 IQR[16-41]). We analyzed the relation between events in ioECoG and cognitive outcome. The number of spikes measured in all electrodes of the preECoG and in all electrodes of the postECoG was comparable between the IQ+ and the IQ- groups. The number of spikes in the resected area was borderline significantly higher in the IQ+ group than the IQ- group (p = 0.05; table 2A). The number of ripples registered in all electrodes of the preECoG, in the electrodes of the resected area and in all electrodes of the postECoG was not different between the two outcome groups (table 2B). The IQ+ group showed more FRs in the resected area and less FRs in the postECoG compared to the IQ- group (p = 0.01; p = 0.045, respectively; table 2C). Three of the four patients in the IQ- group had residual FRs after the final resection while one of the seven patients in the IQ+ group had residual FRs (p = 0.09, two-tailed fisher’s exact test). We found no correlation between IQ change and the number of events (spikes and HFOs) when using the continuous scales in the analysis (data not shown).
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3.3 Postoperative change in events in the non-resected area We recorded 243 pairs of bipolar electrodes in the overlapping – and thus non-resected – ECoG areas, varying from two to 29 bipolar channels per patient. The number of electrodes in the overlapping areas did not deviate between the IQ+ group (median number of electrodes 13 IQR[8-17]) and the IQ- group (median number of electrodes 10 IQR[8-21]). Nineteen patients had one or more electrodes overlapping between the preECoG and the postECoG. One patient with good cognitive outcome did not have electrodes in overlapping areas and was thus excluded from this analysis.
3.3.1 Event changes in the resection edge and cognitive outcome We analyzed the association between the postresection changes in spikes and HFOs in the resection edge and cognitive outcome. Spikes tended to decrease more in the IQ+ group than the IQ- group (p = 0.07; table 3A). The correlation analysis revealed that the postresection decrease in spikes was linked to postoperative IQ increase (correlation coefficient = −0.59 with p = 0.03; figure 2). Ripples decreased more in the IQ+ group than in the IQ- group (p = 0.003; table 3A). Further categorizing ripples into ripples co-occurring with spikes and ripples independent from spikes, the analyses showed that postoperative changes in RonS were associated with cognitive outcome (p = 0.04; table 3A). Postresection decrease of ripples was correlated with a favorable cognitive outcome (correlation coefficient = −0.74 with p = 0.002; figure 3). Such negative relationship was also seen between RonS and cognitive outcome (correlation coefficient = −0.62 with p = 0.01; figure 4), but not for RnonS. The postresection change in the number of FRs did not differ between the IQ+ and the IQ- group.
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3.3.2 Event changes in the extra-marginal area and cognitive outcome No significant differences and changes in events were found in the extra-marginal areas.
DISCUSSION We investigated how the cognitive outcome related to the number of HFOs in the PreECoG and PostECoG and the postresection change in the number of HFO in the non-resected area within the context of pediatric epilepsy surgery. We found that the removal of FR-rich areas was related to good cognitive outcome beyond the benefits of seizure freedom on cognitive development. Corresponding with this finding, the number of residual FRs was lower in the postECoG of children with favorable cognitive outcome. The correlation analyses of FRs did not show a significant result in contrast to the dichotomized analyses. This suggests that accurate removal of FR-rich areas yields postoperative cognitive improvement but the absolute number of FRs does not relate to the IQ increase. The difference may also result from the small sample size of FRs. The postoperative change in the number of ripples in the edge of the resected area associated with the cognitive outcome. Decrease of ripples in the resection edge immediate after tissue resection correlated with IQ improvement two years after surgery. We further divided ripples into two groups based on their co-occurrence with spikes: the presumably pathological RonS and the RnonS (Engel et al. 2009; Clemens et al. 2011; Wang et al. 2013). We established that RonS in the resection edge decreased in the IQ+ group whereas they mainly increased in the IQ- group. No association was found between postresection change in RnonS in the nonresected area and cognitive outcome. The prevalence and postresection change in spikes in ioECoG did not relate to postoperative cognitive outcome.
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The relation between HFOs and cognitive outcome independent from the benefits of seizure freedom could be explained by surgical induced alterations in epileptiform discharges, which interfere with the functional deficit zone outside the epileptogenic zone. The epileptogenic zone is defined as the cortical area indispensable for generating seizures, and currently there are no diagnostic tools available to measure it directly. Only if patients become seizure free after epilepsy surgery, we can conclude that the epileptogenic zone was included within the resected area (Rosenow and Lüders 2001; Moosa and Wyllie 2017). In our patients, who were all seizure free and thus have their epileptogenic zone completely resected, the removal of FR generating tissue and less postoperative residual FRs related to better cognitive outcome. The effect of HFOs on cognitive outcome beyond the influence of the epileptogenic zone and clinical seizures could be due to the recover potential of the surrounding functional brain tissue.
FRs, which are generally deemed epileptiform discharges (Wu et al. 2010; Zijlmans et al. 2012; van’t Klooster et al. 2015), may not only relate to seizure genesis but also to network dysfunction. We consider their presence in postECoG to be pathological even though not they no always elicit clinical seizures. Patients may be more likely to experience cognitive improvements if most of the FR generating tissues were removed due to the reduction of network interfering residual FRs (Ewell et al. 2019). Decrease of pathological RonS in the resection edge after surgery may also reflect improved background signal and thus relate to postoperative cognitive improvements. Our results support HFOs being more discriminative markers for pathological network than spikes and uncover its potential predictive value for postoperative cognitive outcome. We hypothesized that physiological ripples could increase after the resection of epileptogenic tissue in the non-resected areas as a reflection of brain plasticity responding to the ceased electrical disruption, especially in patients with good
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cognitive outcome. This could not be confirmed with the present data, maybe because the development of physiological ripples might require extensive network reorganization which is a slow process and could not be reflected in ioECoG recordings immediately after resection.
Our study is limited by the small sample size and the retrospective design. Due to the small cohort, we were not able to perform multivariate analysis including covariates that might have influenced our findings. Different locations of the resected area could lead to deficits in various cognitive domains (Dulay and Busch 2012). Anti-epileptic drugs may disadvantage cognitive outcome (Van Schooneveld and Braun 2013), and bias our selection of seizure free patients by masking the remaining epileptogenic zone. Epilepsy surgery could be more beneficial for the cognitive outcome of children at the lower end of the IQ spectrum than children with average-high IQs, although the differences are only observed after long-term follow-up of six years and not after two years (Freitag and Tuxhorn 2005, Skirrow et al. 2011). Most importantly, the number of events was not corrected for the number of electrodes recorded. Although we cannot exclude that the correlation between ECoG events and postoperative IQ change is partly attributed to differences in the number of electrodes, lobar localization, use of anti-epileptic drugs or presurgical IQ, our two cognitive outcome groups did not significantly deviate with respect to these four variables. Aside from potential confounding baseline characteristics, the ioECoG recording site may have biased our physiological ripple analyses as the prevalence of physiological events depends on the anatomy and thus their recording site (Frauscher et al. 2018). To limit this bias, we also compared the number of ripples before and after surgery in the same location in the same patient.
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We scored spikes and HFOs in all electrodes in one recording. It is possible that the same epileptiform events were measured in several electrodes. Postresection decrease of the number of events could be partially attributed by altered volume conduction and the loss of connectivity rather than epileptogenic source reduction alone; hence decrease in the number of events in the overlapping electrodes not necessarily reflected the amount of epileptogenic source reduction. We do not expect this to introduce bias as the measurements of events in the IQ+ group and the IQ- group would be affected in comparable ways. Decrease in the extent of epileptiform discharges in the brain network is also considered beneficial for cognitive outcome (Ewell et al. 2019). FRs occur focal and have spatial sampling limitations, especially when measuring the deeper structures (Wu et al. 2010). This is inherent in studying intraoperative HFOs. The exclusion of patients without events in preECoG might lead to an underestimation of our results. In spite of this we considered this approach to be more critical because it is in line with the clinical approach: we expect that true epileptiform events are at least present before the resection and thus for the difference between before and after we deemed sampling of events before the resection essential. Also, the dichotomization of the intelligence quotient changes by using five points of improvement as cut-off could be argued. Other studies have used cut-off points varying from 5-15 points (Van Schooneveld and Braun 2013; Viggedal et al. 2013). We choose the lower end of this cut-off range to incorporate subtle cognitive changes, which might be missed otherwise. We choose not to correct for multiple comparisons because the studied relations are partly dependent, and the explorative character of this study in which the relevance of reporting all potential effects transcends the importance of avoiding type I errors.
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Despite these limitations, our study is the first study to investigate the relation between invasively recorded HFOs and cognitive outcome in pediatric epilepsy surgery. We revealed that HFOs in ioECoG were associated with postoperative cognitive outcome and that the resection of FR rich tissue potentially related to good cognitive outcome. This study features as explorative research and provides preliminary evidence of the role of HFOs in postoperative prognosis for cognitive outcome in children. Future prospective studies performed in larger cohort using HFOs based surgical tailoring are needed to obtain more solid evidence for HFOs as promising ioECoG biomarkers. Such studies should provide detailed information of the involved anatomy and preferably include this as a covariate in a multivariate analysis.
5. CONCLUSION Our results illustrate the added value of HFOs as potential predictive markers for cognitive outcome in pediatric epilepsy surgery. The removal of FR-generating tissue and less residual FRs were associated with cognitive improvement in children after epilepsy surgery. This is possibly due to its superior capacity of representing pathological tissue. In addition, the decrease of ripples co-occurring with spikes, the pathological ripples, in the resection edge after surgical resection seems to indicate favorable cognitive outcome. Surgical tailoring using FRs rather than spikes may result in better cognitive outcome in children, and HFOs in ioECoG may predict postsurgical cognitive outcome. Prospective future studies should be conducted to provide more extensive knowledge on this matter.
DECLARATION OF COMPETING INTEREST None of the authors have potential conflicts of interest to be disclosed.
Sun
ACKNOWLEDGMENTS Dongqing Sun, Maryse A. van ’t Klooster and Maeike Zijlmans gratefully acknowledge funding from the European Research Council via starting grant 803880. All authors have approved the final version of the article.
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Ewell LA, Fischer KB, Leibold C, Leutgeb S, Leutgeb JK. The impact of pathological high-frequency oscillations on hippocampal network activity in rats with chronic epilepsy. Elife. 2019;8:e42148.
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van ’t Klooster MA, van Klink NEC, Zweiphenning WJEM, Leijten FSS, Zelmann R, Ferrier CH, et al. Tailoring epilepsy surgery with fast ripples in the intraoperative electrocorticogram. Ann Neurol. 2017;81:664–76.
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Table 1. Baseline characteristics. Table 1
Baseline characteristics
Patient characteristics
All patients (n=20)
Gender (Female)
10
7 (70.0%)
3 (30.0%)
p-value1 = 0.65
Age at surgery (y)
12.0 [6.5-14.0]
12.0 [6.5-14.8]
12.0 [6.5-13.8]
U = 44,50; Z = −0,27; p-value² = 0.81
Age at seizure onset (y)
6.0 [1.0-10.8]
7.0 [1.2-10.0]
3.5 [0.3-11.0]
U = 43.00; Z = −0.39; p-value² = 0,72
Epilepsy duration (y)
4.0 [2.0-8.0]
3.0 [2.0-8.3]
5.0 [1.2-8.0]
U = 47.50; Z = −0.04; p-value² = 0,99
Use of postoperative AED
6
4 (66.7%)
2 (33.3%)
p-value1 = 1.00
Resection region
Temporal
9 {45.0%}
Extra-temporal
IQ improvement (n=12)
No IQ improvement (n=8)
Statistics
7 (77.8%)
2 (22.2%)
11 {55.0%}
5 (45.5%)
6 (54.5%)
p-value1 = 0.12
Focus side (left)
10
6 (60%)
4 (40.0%)
p-value1 = 1.00
MRI abnormality
19
11 (57.9%)
8 (42.1%)
p-value1 = 1.00
Pathology
MTS
1 {5.0%}
1 (100%)
0
LEAT
11 {55.0%}
6 (54.5%)
5 (45.5%)
MCD
7 {35.0%}
5 (71.4%)
2 (28.6%)
Other
1 {5.0%}
0
1 (100%)
p-value3 = 0.60
Number of bipolar electrodes Preresection
36 [27-46]
36 [33-43]
17 [14-31]
U = 47.00; Z = −0.77; p-value² = 0,96
Postresection
18 [16-28]
36 [13-62]
25 [17-28]
U = 38.00; Z = −0.74; p-value² = 0,46
Intelligence Quotient Preoperative
81 [75-88]
Postoperative
90 [78-105]
80 [69-88] 97 [79-105]
85 [76-101]
U = 37.50; Z = −0.81; p-value² = 0,43
83 [78-104]
U = 39.00; Z = −0.69; p-value² = 0,52
Abbreviations: y = years; AED = anti-epileptic drugs; MTS = mesial temporal sclerosis; LEAT = low-grade epilepsy-associated tumors; MCD = malformation of cortical development P-value: 1 = Fisher’s exact test; 2 = Mann-Whitney U test; 3 = Fisher-Freeman-Halton test; * = significant; (%) = percentage in row; {%} = percentage in column
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Table 2: Comparison of the number of events between children with and without postoperative cognitive improvement. Table 2.
Events & postoperative cognitive outcome
A.
Patients with spikes on preECoG (n=16)
Events
IQ improvement (n=9)
No IQ improvement (n=7)
Statistics
Spike preresection
1042 [105 - 1374]
114 [8 - 547]
U = 17.50; Z = −1.48; p-value = 0.15
Spike in resection area
314 [62 - 678]
3 [0 - 105]
U = 13.00; Z = −1.96; p-value = 0.05
Spike postresection
38 [8 - 258] (residu in 8)
45 [2 - 176] (residu in 6)
U = 30.50; Z = − 0,11; p-value = 0.94
B.
Patients with ripples on preECoG (n=20)
Events
IQ improvement (n=12)
No IQ improvement (n=8)
Statistics
Ripple preresection
481 [99 - 1042]
294 [198 - 830]
U = 43.00; Z = −0.38; p-value = 0.73
Ripple in resection area
138 [29 - 387]
49 [4 - 142]
U = 31.00; Z = −1.31; p-value = 0.21
Ripple postresection
45 [25 - 215] (residu in 12)
232 [110 - 488] (residu in 8)
U = 23.00; Z = −1.92; p-value = 0.35
C.
Patients with FR on preECoG (n=11)
Events
IQ improvement (n=7)
No IQ improvement (n=4)
Statistics
FR preresection
69 [9 - 69]
7 [2 - 34]
U = 4.50; Z = −1.80; p-value = 0.08
FR in resection area
12 [6 - 117]
1 [1 - 3]
U = 1.00; Z = −2.46; p-value = 0.01*
FR postresection
0 [0 - 0] (residu in 1)
16 [1 - 45] (residu in 3)
U = 5.00; Z = −1.97; p-value = 0.045*
Table 2A: The number of spikes in ioECoG of the cognitive improvement group vs the no improvement group Table 2B: The number of ripples in ioECoG of the cognitive improvement group vs the no improvement group Table 2C: The number of FRs in ioECoG of the cognitive improvement group vs the no improvement group Abbreviations: n = the number of patients; ioECoG = intra-operative electrocorticography IQ = intelligence quotient; FR = fast ripples P-value: Mann-Whitney U test (exact two-tailed); * = significant; (residu) = residual event registered after resection
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Table 3: Comparison of the postresection change in the number of events in overlapping areas between children with and without postoperative cognitive improvement. Table 3.
Event changes in overlapping electrode locations & Cognitive outcome
A.
Resection edge
ΔEvents
IQ improvement
No IQ improvement
Statistics
ΔSpike
−53.8 [−186.5 - −12.5] (n=6)
−2 [−13 - 0] (n=7)
U = 8.00; Z = −1.86; p-value = 0.07
ΔRipple
−50 [−149 - 21] (n=7)
0 [−4 - 10] (n=8)
U = 4.00; Z = −2.78; p-value = 0.003*
-
ΔRonS
−7 [−45 - 0] (n=7)
0 [0 - 12] (n=8)
U = 10.00; Z = −2.12; p-value = 0.04*
-
ΔRnonS
−19 [−103 - −1] (n=7)
−1 [−5 - 0] (n=8)
U = 12.00; Z = −1.74; p-value = 0.09
−0.5 [−3.3 - 0.5] (n=5)
−0.0 [−0.8 - 15.4] (n=4)
U = 6.00; Z = −1.00; p-value = 0.41
ΔFR -
ΔFRonS
−0.0 [−2.3 - 0.5] (n=5)
−0.0 [−9.0 - 15.4] (n=4)
U = 9.00; Z = −0.26; p-value = 0.88
-
ΔFRnonS
−0.0 [−1.3 - 0.0] (n=5)
−0.0 [−4.5 - 0.0] (n=4)
U = 9.50; Z = −0.15; p-value = 1
B.
Extra-marginal area
ΔEvents
IQ improvement
No IQ improvement
Statistics
ΔSpike
−27 [-166 - 31] (n=9)
9 [−5.0 - 60.0] (n=7)
U = 17.00; Z = −1.54; p-value = 0.14
ΔRipple
−26 [−171.0 – 0.0] (n=11)
−4 [−73.0 – 10.0] (n=8)
U = 33.50; Z = −0.87; p-value = 0.41
-
ΔRonS
−1 [−19.0 – 0.0] (n=11)
3 [0.0 – 21.0] (n=8)
U = 21.00; Z = −1.92; p-value = 0.06
-
ΔRnonS
−21 [−65.0 – 2.0] (n=11)
−11 [−75.0 – 2.0] (n=8)
U = 42.50; Z = −0.12; p-value = 0.90
−0.3 [−2.0 – 0.0] (n=7)
0.5 [−4.5 - 18.3] (n=4)
U = 9.00; Z = −0.95; p-value = 0.41
ΔFR -
ΔFRonS
0.0 [0.0 - 0.0] (n=3)
1 [0.3 – 17.0] (n=4)
U = 5.50; Z = −1.76; p-value = 0.12
-
ΔFRnonS
0.5 [-2.0 - 0.0] (n=7)
0 [−5.3 - 0.8] (n=4)
U = 9.00; Z = −0.97; p-value = 0.36
Table 3A: Changes in events (number of events in postECoG − number of events in preECoG) in resection edge Table 3B: Changes in events ( number of events in postECoG − number of events in preECoG) in extra-marginal area Abbreviations: n = the number of patients; Δ = change in, IQ = intelligence quotient; RonS = Ripples co-occurring with spikes, RnonS = Ripples independent from spikes; FRonS = Fast ripples co-occurring with spikes, FRnonS = Fast ripples independent from spikes; P-value: Mann-Whitney U test; * = statistical significant; − indicates postresection decrease
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Legend Figure 1. Flowchart of patient inclusion.
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Figure 2. Correlation between postresection change in spike and IQ development
The scatterplot reflects the correlation between the postresection change in the number of spikes in the resection edge (X-axis) and the postoperative IQ development (Y-axis) with best fitted linear regression line and 95% interquartile range. Postresection decrease in spikes was positively related with postoperative IQ increase. (Correlation coefficient and p-value calculated using the Spearman’s rho)
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Figure 3. Correlation between postresection change in ripples and IQ development
The scatterplot reflects the correlation between the postresection change in the number of ripples in the resection edge (X-axis) and the postoperative IQ development (Y-axis) with best fitted linear regression line and 95% interquartile range. Postresection decrease in ripples was positively correlated with postoperative IQ increase. (Correlation coefficient and p-value calculated using the Spearman’s rho).
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Figure 4. Correlation between postresection change in RonS and IQ development
The scatterplot reflects the correlation between the postresection change in the number of ripples on spikes (RonS) in the resection edge (X-axis) and the postoperative IQ development (Y-axis) with best fitted linear regression line and 95% interquartile range. Postresection decrease in RonS was positively correlated with postoperative IQ increase. (Correlation coefficient and p-value calculated using the Spearman’s rho).
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