Development of a stereo-EEG based seizure matching system for clinical decision making in epilepsy surgery.

The proportion of patients becoming seizure-free after epilepsy surgery has stagnated. Large multi-center stereo-electroencephalography (SEEG) datasets can allow comparing new patients to past similar cases and making clinical decisions with the knowledge of how cases were treated in the past. However, the complexity of these evaluations makes the manual search for similar patients impractical.

Combined value of interictal markers and stimulated seizures to estimate the seizure onset zone in stereoelectroencephalography.

Objective: This study was undertaken to investigate the potential of interictal electroencephalographic (EEG) findings and electrically stimulated seizures during stereo-EEG (SEEG) as surrogate markers for the spontaneous seizure onset zone (spSOZ). We hypothesized that combining the localizing information of these markers would allow clinically meaningful estimation of the spSOZ.

Methods: We included all patients (n = 63) who underwent SEEG between January 2013 and March 2020 at Helsinki University Hospital and had spontaneous seizures during the recording.

Quantitative EEG features during the first day correlate to clinical outcome in perinatal asphyxia.

Objective: To assess whether computational electroencephalogram (EEG) measures during the first day of life correlate to clinical outcomes in infants with perinatal asphyxia with or without hypoxic-ischemic encephalopathy (HIE).

Methods: We analyzed four-channel EEG monitoring data from 91 newborn infants after perinatal asphyxia. Altogether 42 automatically computed amplitude- and synchrony-related EEG features were extracted as 2-hourly average at very early (6 h) and early (24 h) postnatal age; they were correlated to the severity of HIE in all infants, and to four clinical outcomes available in a subcohort of 40 newborns: time to full oral feeding (nasogastric tube NGT), neonatal brain MRI, Hammersmith Infant Neurological Examination (HINE) at three months, and Griffiths Scales at two years.

Clinical outcome prediction with an automated EEG trend, Brain State of the Newborn, after perinatal asphyxia.

Objective: To evaluate the utility of a fully automated deep learning -based quantitative measure of EEG background, Brain State of the Newborn (BSN), for early prediction of clinical outcome at four years of age.

Methods: The EEG monitoring data from eighty consecutive newborns was analyzed using the automatically computed BSN trend. BSN levels during the first days of life (a of total 5427 hours) were compared to four clinical outcome categories: favorable, cerebral palsy (CP), CP with epilepsy, and death.

Networks of cortical activity show graded responses to perinatal asphyxia.

Background: Perinatal asphyxia often leads to hypoxic-ischemic encephalopathy (HIE) with a high risk of neurodevelopmental consequences. While moderate and severe HIE link to high morbidity, less is known about brain effects of perinatal asphyxia with no or only mild HIE. Here, we test the hypothesis that cortical activity networks in the newborn infants show a dose-response to asphyxia.

Seizure Burden and Neurologic Outcomes After Neonatal Encephalopathy.

Background And Objectives: Seizures are common during neonatal encephalopathy (NE), but the contribution of seizure burden (SB) to outcomes remains controversial. This study aims to examine the relationship between electrographic SB and neurologic outcomes after NE.

Methods: This prospective cohort study recruited newborns ≥36 weeks postmenstrual age around 6 hours of life between August 2014 and November 2019 from a neonatal intensive care unit (NICU).

An automated bedside measure for monitoring neonatal cortical activity: a supervised deep learning-based electroencephalogram classifier with external cohort validation.

Background: Electroencephalogram (EEG) monitoring is recommended as routine in newborn neurocritical care to facilitate early therapeutic decisions and outcome predictions. EEG's larger-scale implementation is, however, hindered by the shortage of expertise needed for the interpretation of spontaneous cortical activity, the EEG background. We developed an automated algorithm that transforms EEG recordings to quantified interpretations of EEG background and provides simple intuitive visualisations in patient monitors.

Poor aEEG background recovery after perinatal hypoxic ischemic encephalopathy predicts postneonatal epilepsy by age 4 years.

Objective: This study evaluated the accuracy of neonatal amplitude-integrated electroencephalography (aEEG) brain monitoring for predicting development of postneonatal epilepsy after perinatal hypoxic ischemic encephalopathy (HIE).

Methods: We studied a population-based cohort of 85 consecutive neonates with moderate-to-severe HIE that had aEEG started <12 hours postnatally. We marked electrographic seizures and graded each hour of the aEEG background as inactive, burst-suppression, or continuous without or with sleep cycling.

Sleep State Trend (SST), a bedside measure of neonatal sleep state fluctuations based on single EEG channels.

Objective: To develop and validate an automated method for bedside monitoring of sleep state fluctuations in neonatal intensive care units.

Methods: A deep learning-based algorithm was designed and trained using 53 EEG recordings from a long-term (a)EEG monitoring in 30 near-term neonates. The results were validated using an independent dataset from 30 polysomnography recordings.

Ensemble Learning Using Individual Neonatal Data for Seizure Detection.

Objective: Sharing medical data between institutions is difficult in practice due to data protection laws and official procedures within institutions. Therefore, most existing algorithms are trained on relatively small electroencephalogram (EEG) data sets which is likely to be detrimental to prediction accuracy. In this work, we simulate a case when the data can not be shared by splitting the publicly available data set into disjoint sets representing data in individual institutions.

Asymmetry in sleep spindles and motor outcome in infants with unilateral brain injury.

Aim: To determine whether interhemispheric difference in sleep spindles in infants with perinatal unilateral brain injury could link to a pathological network reorganization that underpins the development of unilateral cerebral palsy (CP).

Method: This was a multicentre retrospective study of 40 infants (19 females, 21 males) with unilateral brain injury. Sleep spindles were detected and quantified with an automated algorithm from electroencephalograph records performed at 2 months to 5 months of age.

Validating an SVM-based neonatal seizure detection algorithm for generalizability, non-inferiority and clinical efficacy.

Neonatal seizure detection algorithms (SDA) are approaching the benchmark of human expert annotation. Measures of algorithm generalizability and non-inferiority as well as measures of clinical efficacy are needed to assess the full scope of neonatal SDA performance. We validated our neonatal SDA on an independent data set of 28 neonates.

Early oxygen levels contribute to brain injury in extremely preterm infants.

Background: Extremely low gestational age newborns (ELGANs) are at risk of neurodevelopmental impairments that may originate in early NICU care. We hypothesized that early oxygen saturations (SpO), arterial pO levels, and supplemental oxygen (FiO) would associate with later neuroanatomic changes.

Methods: SpO, arterial blood gases, and FiO from 73 ELGANs (GA 26.

Towards multimodal brain monitoring in asphyxiated newborns with amplitude-integrated EEG and simultaneous somatosensory evoked potentials.

Background: Somatosensory evoked potentials (SEPs) offer an additional bedside tool for outcome prediction after perinatal asphyxia.

Aims: To assess the reliability of SEPs recorded with bifrontoparietal amplitude-integrated electroencephalography (aEEG) brain monitoring setup for outcome prediction in asphyxiated newborns undergoing therapeutic hypothermia.

Study Design: Retrospective observational single-center study.

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

Objective: To examine whether fast ripples (FRs) are an accurate marker of the epileptogenic zone, we analyzed overnight stereo-EEG recordings from 43 patients and hypothesized that FR resection ratio, maximal FR rate, and FR distribution predict postsurgical seizure outcome.

Methods: We detected FRs automatically from an overnight recording edited for artifacts and visually from a 5-minute period of slow-wave sleep. We examined primarily the accuracy of removing ≥50% of total FR events or of channels with FRs to predict postsurgical seizure outcome (Engel class I = good, classes II-IV = poor) according to the whole-night and 5-minute analysis approaches.

Neonatal neuroimaging and neurophysiology predict infantile onset epilepsy after perinatal hypoxic ischemic encephalopathy.

Purpose: To evaluate the accuracy of hypoxic ischemic encephalopathy (HIE) grade, and neonatal neurophysiological and neuroimaging measures for predicting development of infantile spasms syndrome (IS) or other postneonatal, infantile onset epilepsy after perinatal HIE.

Methods: We examined a population-based cohort of 92 consequent infants with moderate-to-severe HIE. The HIE grade and neonatal neuroimaging (MRI) and neurophysiology (EEG and somatosensory evoked potentials, SEPs) findings were compared to the development of IS or other epilepsy within the first year of life.

Cortical responses to tactile stimuli in preterm infants.

The conventional assessment of preterm somatosensory functions using averaged cortical responses to electrical stimulation ignores the characteristic components of preterm somatosensory evoked responses (SERs). Our study aimed to systematically evaluate the occurrence and development of SERs after tactile stimulus in preterm infants. We analysed SERs performed during 45 electroencephalograms (EEGs) from 29 infants at the mean post-menstrual age of 30.

Bedside neurophysiological tests can identify neonates with stroke leading to cerebral palsy.

Objective: The unspecific symptoms of neonatal stroke still challenge its bedside diagnosis. We studied the accuracy of routine electroencephalography (EEG) and simultaneously recorded somatosensory evoked potentials (EEG-SEP) for diagnosis and outcome prediction of neonatal stroke.

Methods: We evaluated EEG and EEG-SEPs from a hospital cohort of 174 near-term neonates with suspected seizures or encephalopathy, 32 of whom were diagnosed with acute ischemic or hemorrhagic stroke in MRI.

Evaluation of SEPs in asphyxiated newborns using a 4-electrode aEEG brain monitoring set-up.

Objective: To evaluate the reliability of recording cortical somatosensory evoked potentials (SEPs) in asphyxiated newborns using the 4-electrode setup applied in routine long-term amplitude-integrated EEG (aEEG) brain monitoring and to assess the number of averages needed for reliably detecting the cortical responses.

Methods: We evaluated median nerve SEPs in 50 asphyxiated full-term newborns. The SEP interpretation (present or absent) from the original recordings with 21-electrodes and approximately 600 trials served as the reference.

Soleus H-Reflex and Its Modulation With Vibration in Idiopathic Toe Walkers and Typically Developing Children.

Idiopathic toe walking is a relatively common developmental condition often leading to secondary problems such as pain and muscle contractures in the lower extremities. The cause of idiopathic toe walking is unknown, which hinders the development of treatment strategies. To test whether children with idiopathic toe walking have functional alterations in their spinal motor circuits, we studied the properties of the soleus H-reflex and its modulation with vibration in 26 idiopathic toe walkers and 16 typically developing children.