Lesion volume and spike frequency on EEG impact perfusion values in focal cortical dysplasia: a pediatric arterial spin labeling study.

Arterial spin labelling (ASL), an MRI sequence non-invasively imaging brain perfusion, has yielded promising results in the presurgical workup of children with focal cortical dysplasia (FCD)-related epilepsy. However, the interpretation of ASL-derived perfusion patterns remains unclear. Hence, we compared ASL qualitative and quantitative findings to their clinical, EEG, and MRI counterparts. We included children with focal structural epilepsy related to an MRI-detectable FCD who underwent single delay pseudo-continuous ASL. ASL perfusion changes were assessed qualitatively by visual inspection and quantitatively by estimating the asymmetry index (AI). We considered 18 scans from 15 children. 16 of 18 (89%) scans showed FCD-related perfusion changes: 10 were hypoperfused, whereas six were hyperperfused. Nine scans had perfusion changes larger than and seven equal to the FCD extent on anatomical images. Hyperperfusion was associated with frequent interictal spikes on EEG (p = 0.047). Perfusion changes in ASL larger than the FCD corresponded to larger lesions (p = 0.017). Higher AI values were determined by frequent interictal spikes on EEG (p = 0.004). ASL showed FCD-related perfusion changes in most cases. Further, higher spike frequency on EEG may increase ASL changes in affected children. These observations may facilitate the interpretation of ASL findings, improving treatment management, counselling, and prognostication in children with FCD-related epilepsy.

Scalp HFO rates are higher for larger lesions.

High-frequency oscillations (HFO) in scalp EEG are a new and promising noninvasive epilepsy biomarker, providing added prognostic value, particularly in pediatric lesional epilepsy. However, it is unclear if lesion characteristics, such as lesion volume, depth, type, and localization, impact scalp HFO rates. We analyzed scalp EEG from 13 children and adolescents with focal epilepsy associated with focal cortical dysplasia (FCD), low-grade tumors, or hippocampal sclerosis. We applied a validated automated detector to determine HFO rates in bipolar channels. We identified the lesion characteristics in MRI. Larger lesions defined by MRI volumetric analysis corresponded to higher cumulative scalp HFO rates (P = .01) that were detectable in a higher number of channels (P = .05). Both superficial and deep lesions generated HFO detectable in the scalp EEG. Lesion type (FCD vs tumor) and lobar localization (temporal vs extratemporal) did not affect scalp HFO rates in our study. Our observations support that all lesions may generate HFO detectable in scalp EEG, irrespective of their characteristics, whereas larger epileptogenic lesions generate higher scalp HFO rates over larger areas that are thus more accessible to detection. Our study provides crucial insight into scalp HFO detectability in pediatric lesional epilepsy, facilitating their implementation as an epilepsy biomarker in a clinical setting.

Variation of scalp EEG high frequency oscillation rate with sleep stage and time spent in sleep in patients with pediatric epilepsy.

OBJECTIVE: High frequency oscillations (HFO) in scalp EEG are a new and promising epilepsy biomarker. However, considerable fluctuations of HFO rates have been observed through sleep stages and cycles. Here, we aimed to identify the optimal timing within sleep and the minimal data length for sensitive and reproducible HFO detection. METHODS: We selected 16 whole-night scalp EEG recordings of paediatric patients with a focal structural epilepsy. We used an automated clinically validated HFO detector to determine HFO rates (80-250 Hz). We evaluated the reproducibility of HFO detection across intervals. RESULTS: HFO rates were higher in N3 than in N2 and REM (rapid eye movement) sleep and highest in the first sleep cycle, decreasing with time in sleep. In N3 sleep, the median reliability of HFO detection increased from 67% (interquartile range: iqr 57) to 78% (iqr 59) to 100% (iqr 70%) for 5-, 10-, and 15-min data intervals, improving significantly (p = 0.004, z = 2.9) from 5 to 10 min but not from 10 to 15 min. CONCLUSIONS: We identified the first N3 sleep stage as the most sensitive time window for HFO rate detection. At least 10 min N3 data intervals are required and sufficient for reliable measurements of HFO rates. SIGNIFICANCE: Our study provides a robust and reliable framework for scalp HFO detection that may facilitate their implementation as an EEG biomarker in paediatric epilepsy.

Scalp HFO rates decrease after successful epilepsy surgery and are not impacted by the skull defect resulting from craniotomy.

Epilepsy surgery can achieve seizure freedom in selected pediatric candidates, but reliable postsurgical predictors of seizure freedom are missing. High frequency oscillations (HFO) in scalp EEG are a new and promising biomarker of treatment response. However, it is unclear if the skull defect resulting from craniotomy interferes with HFO detection in postsurgical recordings. We considered 14 children with focal lesional epilepsy who underwent presurgical evaluation, epilepsy surgery, and postsurgical follow-up of ≥ 1 year. We identified the nearest EEG electrodes to the skull defect in the postsurgical MRI. We applied a previously validated automated HFO detector to determine HFO rates in presurgical and postsurgical EEG. Overall, HFO rates showed a positive correlation with seizure frequency (p < 0.001). HFO rates in channels over the HFO area decreased following successful epilepsy surgery, irrespective of their proximity to the skull defect (p = 0.005). HFO rates in channels outside the HFO area but near the skull defect showed no increase following surgery (p = 0.091) and did not differ from their contralateral channels (p = 0.726). Our observations show that the skull defect does not interfere with postsurgical HFO detection. This supports the notion that scalp HFO can predict postsurgical seizure freedom and thus guide therapy management in focal lesional epilepsy.

Scalp high-frequency oscillation rates are higher in younger children.

High-frequency oscillations in scalp EEG are promising non-invasive biomarkers of epileptogenicity. However, it is unclear how high-frequency oscillations are impacted by age in the paediatric population. We prospectively recorded whole-night scalp EEG in 30 children and adolescents with focal or generalized epilepsy. We used an automated and clinically validated high-frequency oscillation detector to determine ripple rates (80-250 Hz) in bipolar channels. Children < 7 years had higher high-frequency oscillation rates (P = 0.021) when compared with older children. The median test-retest reliability of high-frequency oscillation rates reached 100% (iqr 50) for a data interval duration of 10 min. Scalp high-frequency oscillation frequency decreased with age (r = -0.558, P = 0.002), whereas scalp high-frequency oscillation duration and amplitude were unaffected. The signal-to-noise ratio improved with age (r = 0.37, P = 0.048), and the background ripple band activity decreased with age (r = -0.463, P = 0.011). We characterize the relationship of scalp high-frequency oscillation features and age in paediatric patients. EEG intervals of ≥ 10 min duration are required for reliable measurements of high-frequency oscillation rates. This study is a further step towards establishing scalp high-frequency oscillations as a valid epileptogenicity biomarker in this vulnerable age group.