Publications

OBJECTIVE: To assess whether ictal electric source imaging (ESI) on low-density scalp EEG can approximate the seizure onset zone (SOZ) location and predict surgical outcome in children with refractory epilepsy undergoing surgery.

METHODS: We examined 35 children with refractory epilepsy. We dichotomized surgical outcome into seizure- and non-seizure-free. We identified ictal onsets recorded with scalp and intracranial EEG and localized them using equivalent current dipoles and standardized low-resolution magnetic tomography (sLORETA). We estimated the localization accuracy of scalp EEG as distance of scalp dipoles from intracranial dipoles. We also calculated the distances of scalp dipoles from resection, as well as their resection percentage and compared between seizure-free and non-seizure-free patients. We built receiver operating characteristic curves to test whether resection percentage predicted outcome.

RESULTS: Resection distance was lower in seizure-free patients for both dipoles (p = 0.006) and sLORETA (p = 0.04). Resection percentage predicted outcome with a sensitivity of 57.1% (95% CI, 34-78.2%), a specificity of 85.7% (95% CI, 57.2-98.2%) and an accuracy of 68.6% (95% CI, 50.7-83.5%) (p = 0.01).

CONCLUSION: Ictal ESI performed on low-density scalp EEG can delineate the SOZ and predict outcome.

SIGNIFICANCE: Such an application may increase the number of children who are referred for epilepsy surgery and improve their outcome.

A term neonate is born with the ability to suck; this neuronal network is already formed and functional by 28 weeks gestational age and continues to evolve into adulthood. Because of the necessity of acquiring nutrition, the complexity of the neuronal network needed to suck, and neuroplasticity in infancy, the skill of sucking has the unique ability to give insight into areas of the brain that may be damaged either during or before birth. Interpretation of the behaviors during sucking shows promise in guiding therapies and how to potentially repair the damage early in life, when neuroplasticity is high. Sucking requires coordinated suck-swallow-breathe actions and is classified into two basic types, nutritive and non-nutritive. Each type of suck has particular characteristics that can be measured and used to learn about the infant's neuronal circuitry. Basic sucking and swallowing are present in embryos and further develop to incorporate breathing ex utero. Due to the rhythmic nature of the suck-swallow-breathe process, these motor functions are controlled by central pattern generators. The coordination of swallowing, breathing, and sucking is an enormously complex sensorimotor process. Because of this complexity, brain injury before birth can have an effect on these sucking patterns. Clinical assessments allow evaluators to score the oral-motor pattern, however, they remain ultimately subjective. Thus, clinicians are in need of objective measures to identify the specific area of deficit in the sucking pattern of each infant to tailor therapies to their specific needs. Therapeutic approaches involve pacifiers, cheek/chin support, tactile, oral kinesthetic, auditory, vestibular, and/or visual sensorimotor inputs. These therapies are performed to train the infant to suck appropriately using these subjective assessments along with the experience of the therapist (usually a speech therapist), but newer, more objective measures are coming along. Recent studies have correlated pathological sucking patterns with neuroimaging data to get a map of the affected brain regions to better inform therapies. The purpose of this review is to provide a broad scope synopsis of the research field of infant nutritive and non-nutritive feeding, their underlying neurophysiology, and relationship of abnormal activity with brain injury in preterm and term infants.

OBJECTIVES: Photoplethysmography (PPG) reflects variations of blood perfusion in tissues, which may signify seizure-related autonomic changes. The aim of this study is to assess the variability of PPG signals and their value in detecting peri-ictal changes in patients with focal impaired awareness seizures (FIASs).

METHODS: PPG data were recorded using a wearable sensor placed on the wrist or ankle of children with epilepsy admitted for long-term video-electroencephalographic monitoring. We analyzed PPG data in four different periods: seizure-free, preictal, ictal, and postictal. Multiple features were automatically extracted from the PPG signal-frequency, duration, amplitude, increasing and decreasing slopes, smoothness, and area under the curve (AUC)-and were used to identify preictal, ictal, or postictal changes by comparing them with seizure-free periods and with each other using a linear mixed-effects model.

RESULTS: We studied PPG in 11 patients (18 FIASs), including seizure-free, preictal, and postictal periods, and a subset of eight patients (12 FIASs) including the ictal period. Compared to the seizure-free period, we found significant changes in PPG (1) during the ictal period across all features; (2) during the preictal period in amplitude, duration, increasing slope, and AUC; and (3) during the postictal period in decreasing slope.

SIGNIFICANCE: Specific PPG changes can be seen before, during, and after FIASs. The peri-ictal changes in the PPG features of patients with FIASs suggest potential applications of PPG monitoring for seizure detection.

OBJECTIVE: Photoplethysmography (PPG) is an optical technique measuring variations of blood perfusion in peripheral tissues. We evaluated alterations in PPG signals in relationship to the occurrence of generalized tonic-clonic seizures (GTCSs) in patients with epilepsy to evaluate the feasibility of seizure detection.

METHODS: During electroencephalographic (EEG) long-term monitoring, patients wore portable wristband sensor(s) on their wrists or ankles recording PPG signals. We analyzed PPG signals during three time periods, which were defined with respect to seizures detected on EEG: (1) baseline (>30 minutes prior to seizure), (2) preseizure period, and (3) postseizure period. Furthermore, we selected five random control segments during seizure-free periods. PPG features, including frequency, amplitude, duration, slope, smoothness, and area under the curve, were automatically calculated. We used a linear mixed-effect model to evaluate changes in PPG features between different time periods in an attempt to identify signal changes that detect seizures.

RESULTS: We prospectively enrolled 174 patients from the epilepsy monitoring unit at Boston Children's Hospital. Twenty-five GTCSs were recorded from 13 patients. Data from the first recorded GTCS of each patient were included in the analysis. We observed an increase in PPG frequency during pre- and postseizure periods that was higher than the changes during seizure-free periods (frequency increase: preseizure = 0.22 Hz, postseizure = 0.58 Hz vs changes during seizure-free period = 0.05 Hz). The PPG slope decreased significantly by 56.71 nW/s during preseizure periods compared to seizure-free periods. Additionally, the smoothness increased significantly by 0.22 nW/s during the postseizure period compared to seizure-free periods.

SIGNIFICANCE: Monitoring of PPG signals may assist in the detection of GTCSs in patients with epilepsy. PPG may serve as a promising biomarker for future seizure detection systems and may contribute to future seizure prediction systems.

OBJECTIVE: To assess the ability of high-density Electroencephalography (HD-EEG) and magnetoencephalography (MEG) to localize interictal ripples, distinguish between ripples co-occurring with spikes (ripples-on-spike) and independent from spikes (ripples-alone), and evaluate their localizing value as biomarkers of epileptogenicity in children with medically refractory epilepsy.

METHODS: We retrospectively studied 20 children who underwent epilepsy surgery. We identified ripples on HD-EEG and MEG data, localized their generators, and compared them with intracranial EEG (icEEG) ripples. When ripples and spikes co-occurred, we performed source imaging distinctly on the data above 80 Hz (to localize ripples) and below 70 Hz (to localize spikes). We assessed whether missed resection of ripple sources predicted poor outcome, separately for ripples-on-spikes and ripples-alone. Similarly, predictive value of spikes was calculated.

RESULTS: We observed scalp ripples in 16 patients (10 good outcome). Ripple sources were highly concordant to the icEEG ripples (HD-EEG concordance: 79%; MEG: 83%). When ripples and spikes co-occurred, their sources were spatially distinct in 83-84% of the cases. Removing the sources of ripples-on-spikes predicted good outcome with 90% accuracy for HD-EEG (P = 0.008) and 86% for MEG (P = 0.044). Conversely, removing ripples-alone did not predict outcome. Resection of spike sources (generated at the same time as ripples) predicted good outcome for HD-EEG (P = 0.036; accuracy = 87%), while did not reach significance for MEG (P = 0.1; accuracy = 80%).

INTERPRETATION: HD-EEG and MEG localize interictal ripples with high precision in children with refractory epilepsy. Scalp ripples-on-spikes are prognostic, noninvasive biomarkers of epileptogenicity, since removing their cortical generators predicts good outcome. Conversely, scalp ripples-alone are most likely generated by non-epileptogenic areas.

OBJECTIVE: To localize the seizure onset zone (SOZ) and irritative zone (IZ) using electric source imaging (ESI) on intracranial EEG (iEEG) and assess their clinical value in predicting epilepsy surgery outcome in children with focal cortical dysplasia (FCD).

METHODS: We analyzed iEEG data from 25 children with FCD-associated medically refractory epilepsy (MRE) who underwent surgery. We performed ESI on ictal onset to localize SOZ (ESI-SOZ) and on interictal discharges to localize IZ (ESI-IZ). We tested whether resection of ESI-SOZ and ESI-IZ predicted good surgical outcome (Engel 1). We further compared the prediction performance of ESI-SOZ and ESI-IZ to those of SOZ and IZ defined using conventional methods, i.e. by identifying iEEG-contacts showing ictal onsets (conventional-SOZ) or being the most interictally active (conventional-IZ).

RESULTS: The proximity of ESI-SOZ (p = 0.043, odds-ratio = 3.9) and ESI-IZ (p = 0.011, odds-ratio = 7.04) to resection has higher effect on patients' outcome than proximity of conventional-SOZ (p = 0.17, odds-ratio = 1.7) and conventional-IZ (p = 0.038, odds-ratio = 2.6). Resection of ESI-SOZ and ESI-IZ presented higher discriminative power in predicting outcome (68% and 60%) than conventional-SOZ and conventional-IZ (48% and 53%).

CONCLUSIONS: Localizing SOZ and IZ via ESI on iEEG offers higher predictive value compared to conventional-iEEG interpretation.

SIGNIFICANCE: iEEG-ESI may help surgical planning and facilitate prognostic assessment of children with FCD-associated MRE.

INTRODUCTION: Patients with medically refractory epilepsy (MRE) need surgical resection of the epileptogenic zone (EZ) to gain seizure-freedom. High-frequency oscillations (HFOs, > 80 Hz) are promising biomarkers of the EZ that are typically localized using intracranial electroencephalography (icEEG). The goal of this study was to localize the cortical generators of HFOs non-invasively using high-density (HD) EEG and magnetoencephalography (MEG) and validate the localization against the gold-standard given by the icEEGdefined HFO-zone.

METHODS: We analyzed simultaneous HDEEG and MEG data from six children with MRE who underwent icEEG and surgery. We detected interictal HFOs (80-160 Hz) on HD-EEG and MEG separately, using an inhouse automatic detector followed by visual human review, and distinguished between HFOs with and without spikes. We localized the cortical generators of each HFO on HD-EEG or MEG using the wavelet Maximum Entropy on the Mean (wMEM). For the HFOs localized in the brain area covered by icEEG, we estimated the localization error (Eloc) with respect to the gold-standard, and classified them as either concordant (Eloc≤15mm) or not.

RESULTS: We found that: (i) HD-EEG presented a higher rate of HFOs than MEG (1 vs 0.5 HFOs/min, p=0.031); (ii) HFOs without spikes were more likely to be localized outside the brain regions of interest (i.e. covered by icEEG) than HFOs with spikes; and (iii) both HD-EEG and MEG showed high precision to the gold-standard (92% and 96%).

CONCLUSION: We reported quantitative evidence that HDEEG and MEG can localize the HFO cortical generators with high precision to the icEEG gold-standard in children with MRE, suggesting that they may possibly limit the need for icEEG prior to surgery. We also showed that HFOs with spikes on HD-EEG/MEG are more likely to be epileptogenic than those independent from spikes, which may represent physiological events from normal brain.

OBJECTIVE: To determine the relationship between nutritive sucking and microstructural integrity of sensorimotor tracts in newborns with brain injury.

STUDY DESIGN: Diffusion imaging was performed in ten newborns with brain injury. Nutritive sucking was assessed using Nfant®. The motor, sensory, and corpus callosum tracts were reconstructed via tractography. Fractional anisotropy, radial, axial, and mean diffusivity were estimated for these tracts. Multiple regression models were developed to test the association between sucking features and diffusion parameters.

RESULTS: Low-sucking smoothness correlated with low-fractional anisotropy of motor tracts (p = 0.0096). High-sucking irregularity correlated with high-mean diffusivity of motor (p = 0.030) and corpus callosum tracts (p = 0.032). For sensory tracts, high-sucking irregularity (p = 0.018) and low-smoothness variability (p = 0.002) correlated with high-mean diffusivity.

INTERPRETATION: We show a correlation between neuroimaging-demonstrated microstructural brain abnormalities and variations in sucking patterns of newborns. The consistency of this relationship should be shown on larger cohorts.

OBJECTIVE: To evaluate the accuracy and clinical utility of conventional 21-channel EEG (conv-EEG), 72-channel high-density EEG (HD-EEG) and 306-channel MEG in localizing interictal epileptiform discharges (IEDs).

METHODS: Twenty-four children who underwent epilepsy surgery were studied. IEDs on conv-EEG, HD-EEG, MEG and intracranial EEG (iEEG) were localized using equivalent current dipoles and dynamical statistical parametric mapping (dSPM). We compared the localization error (ELoc) with respect to the ground-truth Irritative Zone (IZ), defined by iEEG sources, between non-invasive modalities and the distance from resection (Dres) between good- (Engel 1) and poor-outcomes. For each patient, we estimated the resection percentage of IED sources and tested whether it predicted outcome.

RESULTS: MEG presented lower ELoc than HD-EEG and conv-EEG. For all modalities, Dres was shorter in good-outcome than poor-outcome patients, but only the resection percentage of the ground-truth IZ and MEG-IZ predicted surgical outcome.

CONCLUSIONS: MEG localizes the IZ more accurately than conv-EEG and HD-EEG. MSI may help the presurgical evaluation in terms of patient's outcome prediction. The promising clinical value of ESI for both conv-EEG and HD-EEG prompts the use of higher-density EEG-systems to possibly achieve MEG performance.

SIGNIFICANCE: Localizing the IZ non-invasively with MSI/ESI facilitates presurgical evaluation and surgical prognosis assessment.

Despite extensive literature showing damages in the sensorimotor projection fibers of children with hemiplegic cerebral palsy (HCP), little is known about how these damages affect the global brain network. In this study, we assess the relationship between the structural integrity of sensorimotor projection fibers and the integrity of intergyral association white matter connections in children with HCP. Diffusion tensor imaging was performed in 10 children with HCP and 16 typically developing children. We estimated the regional and global white-matter connectivity using a region-of-interest (ROI)-based approach and a whole-brain gyrus-based parcellation method. Using the ROI-based approach, we tracked the spinothalamic (STh), thalamocortical (ThC), corticospinal (CST), and sensorimotor U- (SMU) fibers. Using the whole-brain parcellation method, we tracked the short-, middle-, and long-range association fibers. We observed for the more affected hemisphere of children with HCP: (i) an increase in axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) for the STh and ThC fibers; (ii) a decrease in fractional anisotropy (FA) and an increase in MD and RD for the CST and SMU fibers; in (iii) a decrease in FA and an increase in AD, MD, and RD for the middle- and long-range association fibers; and (iv) an association between the integrity of sensorimotor projection and intergyral association fibers. Our findings indicate that altered structural integrity of the sensorimotor projection fibers disorganizes the intergyral association white matter connections among local and distant regions in children with HCP.