FDG-PET/MRI in the presurgical evaluation of pediatric epilepsy.

In patients with drug-resistant epilepsy, difficulties in identifying the epileptogenic zone are well known to correlate with poorer clinical outcomes post-surgery. The integration of PET and MRI in the presurgical assessment of pediatric patients likely improves diagnostic precision by confirming or widening treatment targets. PET and MRI together offer superior insights compared to either modality alone. For instance, PET highlights abnormal glucose metabolism, while MRI precisely localizes structural anomalies, providing a comprehensive understanding of the epileptogenic zone. Furthermore, both methodologies, whether utilized through simultaneous PET/MRI scanning or the co-registration of separately acquired PET and MRI data, present unique advantages, having complementary roles in lesional and non-lesional cases. Simultaneous FDG-PET/MRI provides precise co-registration of functional (PET) and structural (MR) imaging in a convenient one-stop-shop approach, which minimizes sedation time and reduces radiation exposure in children. Commercially available fusion software that allows retrospective co-registration of separately acquired PET and MRI images is a commonly used alternative. This review provides an overview and illustrative cases that highlight the role of combining 18F-FDG-PET and MRI imaging and shares the authors' decade-long experience utilizing simultaneous PET/MRI in the presurgical evaluation of pediatric epilepsy.

A Comparison of Automatically Extracted Quantitative EEG Features for Seizure Risk Stratification in Neonatal Encephalopathy.

PURPOSE: Seizures occur in up to 40% of neonates with neonatal encephalopathy. Earlier identification of seizures leads to more successful seizure treatment, but is often delayed because of limited availability of continuous EEG monitoring. Clinical variables poorly stratify seizure risk, and EEG use to stratify seizure risk has previously been limited by need for manual review and artifact exclusion. The goal of this study is to compare the utility of automatically extracted quantitative EEG (qEEG) features for seizure risk stratification. METHODS: We conducted a retrospective analysis of neonates with moderate-to-severe neonatal encephalopathy who underwent therapeutic hypothermia at a single center. The first 24 hours of EEG underwent automated artifact removal and qEEG analysis, comparing qEEG features for seizure risk stratification. RESULTS: The study included 150 neonates and compared the 36 (23%) with seizures with those without. Absolute spectral power best stratified seizure risk with area under the curve ranging from 63% to 71%, followed by range EEG lower and upper margin, median and SD of the range EEG lower margin. No features were significantly more predictive in the hour before seizure onset. Clinical examination was not associated with seizure risk. CONCLUSIONS: Automatically extracted qEEG features were more predictive than clinical examination in stratifying neonatal seizure risk during therapeutic hypothermia. qEEG represents a potential practical bedside tool to individualize intensity and duration of EEG monitoring and decrease time to seizure recognition. Future work is needed to refine and combine qEEG features to improve risk stratification.

Macroperiodic Oscillations: A Potential Novel Biomarker of Outcome in Neonatal Encephalopathy.

PURPOSE: Neonatal encephalopathy (NE) is a common cause of neurodevelopmental morbidity. Tools to accurately predict outcomes after therapeutic hypothermia remain limited. We evaluated a novel EEG biomarker, macroperiodic oscillations (MOs), to predict neurodevelopmental outcomes. METHODS: We conducted a secondary analysis of a randomized controlled trial of neonates with moderate-to-severe NE who underwent standardized clinical examination, magnetic resonance (MR) scoring, video EEG, and neurodevelopmental assessment with Bayley III evaluation at 18 to 24 months. A non-NE cohort of neonates was also assessed for the presence of MOs. The relationship between clinical examination, MR score, MOs, and neurodevelopmental assessment was analyzed. RESULTS: The study included 37 neonates with 24 of whom survived and underwent neurodevelopmental assessment (70%). The strength of MOs correlated with severity of clinical encephalopathy. MO strength and spread significantly correlated with Bayley III cognitive percentile (P = 0.017 and 0.046). MO strength outperformed MR score in predicting a combined adverse outcome of death or disability (P = 0.019, sensitivity 100%, specificity 77% vs. P = 0.079, sensitivity 100%, specificity 59%). CONCLUSIONS: MOs are an EEG-derived, quantitative biomarker of neurodevelopmental outcome that outperformed a comprehensive validated MRI injury score and a detailed systematic discharge examination in this small cohort. Future work is needed to validate MOs in a larger cohort and elucidate the underlying pathophysiology of MOs.

Detecting slow narrowband modulation in EEG signals.

BACKGROUND: We observed an unusual modulatory phenomenon in the electroencephalogram (EEG) of pediatric patients with acquired brain injury. The modulation is orders of magnitude slower than the fast EEG background activity, necessitating new analysis procedures to systematically detect and quantify the phenomenon. NEW METHOD: We propose a method for analyzing spatial and temporal relationships associated with slow, narrowband modulation of EEG. We extract envelope signals from physiological frequency bands of EEG. Then, we construct a sparse representation of the spectral content of the envelope signal across sliding windows. For the latter, we use an augmented LASSO regression to incorporate spatial and temporal filtering into the solution. The method can be applied to windows of variable length, depending on the desired frequency resolution. RESULTS: The sparse estimates of the envelope power spectra enable the detection of narrowband modulation in the millihertz frequency range. Subsequently, we are able to assess non-stationarity in the frequency and spatial relationships across channels. The method can be paired with unsupervised anomaly detection to identify windows with significant modulation. We validated such findings by applying our method to a control set of EEGs. COMPARISON WITH EXISTING METHODS: To our knowledge, no methods have been previously proposed to quantify second order modulation at such disparate time-scales. CONCLUSIONS: We provide a general EEG analysis framework capable of detecting signal content below 0.1 Hz, which is especially germane to clinical recordings that may contain multiple hours worth of continuous data.

Resolving and characterizing the incidence of millihertz EEG modulation in critically ill children.

OBJECTIVE: We analyze a slow electrographic pattern, Macroperiodic Oscillations (MOs), in the EEG from a cohort of young critical care patients (n = 43) with continuous EEG monitoring. We construct novel quantitative methods to quantify and understand MOs. METHODS: We applied a nonparametric bilevel spectral analysis to identify MOs, a millihertz (0.004-0.01 Hz) modulation of 5-15 Hz activity in two separate ICU patient cohorts (n = 195 total). We also developed a rigorous measure to quantify MOs strength and spatial expression, which was validated against surrogate noise data. RESULTS: Strong or spatially widespread MOs appear in both high clinical suspicion and a general ICU population. In the former, patients with strong or spatially widespread MOs tended to have worse clinical outcomes. Intracranial pressure and heart rate data from one patient provide insight into a potential broader physiological mechanism for MOs. CONCLUSIONS: We quantified millihertz EEG modulation (MOs) in cohorts of critically ill pediatric patients. We demonstrated high incidence in two patient populations. In a high suspicion cohort, MOs are associated with poor outcome, suggesting future potential as a diagnostic and prognostic aid. SIGNIFICANCE: These results support the existence of EEG dynamics across disparate time-scales and may provide insight into brain injury physiology in young children.

Macroperiodic Oscillations Are Associated With Seizures Following Acquired Brain Injury in Young Children.

PURPOSE: Seizures occur in 10% to 40% of critically ill children. We describe a phenomenon seen on color density spectral array but not raw EEG associated with seizures and acquired brain injury in pediatric patients. METHODS: We reviewed EEGs of 541 children admitted to an intensive care unit between October 2015 and August 2018. We identified 38 children (7%) with a periodic pattern on color density spectral array that oscillates every 2 to 5 minutes and was not apparent on the raw EEG tracing, termed macroperiodic oscillations (MOs). Internal validity measures and interrater agreement were assessed. We compared demographic and clinical data between those with and without MOs. RESULTS: Interrater reliability yielded a strong agreement for MOs identification (kappa: 0.778 [0.542-1.000]; P < 0.0001). There was a 76% overlap in the start and stop times of MOs among reviewers. All patients with MOs had seizures as opposed to 22.5% of the general intensive care unit monitoring population ( P < 0.0001). Macroperiodic oscillations occurred before or in the midst of recurrent seizures. Patients with MOs were younger (median of 8 vs. 208 days; P < 0.001), with indications for EEG monitoring more likely to be clinical seizures (42 vs. 16%; P < 0.001) or traumatic brain injury (16 vs. 5%, P < 0.01) and had fewer premorbid neurologic conditions (10.5 vs. 33%; P < 0.01). CONCLUSIONS: Macroperiodic oscillations are a slow periodic pattern occurring over a longer time scale than periodic discharges in pediatric intensive care unit patients. This pattern is associated with seizures in young patients with acquired brain injuries.

Immediate Postoperative Electroencephalography Monitoring in Pediatric Moyamoya Disease and Syndrome.

BACKGROUND: Moyamoya disease and syndrome are progressive steno-occlusive cerebrovascular diseases that manifest clinically with ischemic episodes. There is evidence for the use of electroencephalography (EEG) in preoperative and long-term postoperative evaluation of these patients, as well as in the intraoperative period to monitor for changes correlated with perioperative ischemic events. However, the utility of EEG in the immediate postprocedure time period has not previously been described. METHODS: We review six patients who underwent pial synangiosis from 2017 to 2019. EEGs from the preoperative, intraoperative, and immediate postoperative period were evaluated, as well as clinical examination changes and subsequent interventions. RESULTS: Six patients with postoperative EEG monitoring following pial synangiosis were included. EEG data was collected preoperatively, intraoperatively, and continuously postoperatively. Preoperatively, five of six patients had normal background activity on EEG, whereas one of six had hemispheric asymmetry. Three patients had new or worsening hemispheric intracerebral asymmetry on EEG during the immediate postsurgical period. Two of these had no clinical manifestations of ischemia, and one had transient left facial weakness. All three underwent blood pressure augmentation with improvement in the asymmetry on EEG and clinical improvement in the symptomatic patient. CONCLUSIONS: Although widely accepted as a useful tool during the preoperative and intraoperative periods of evaluation and management of moyamoya disease and syndrome, we propose that the use of continuous EEG in the immediate postoperative period may have potential as a useful adjunct by both detecting early clinical and subclinical intracranial ischemia.