Publications

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.

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.

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.

OBJECTIVE: In patients with medically refractory epilepsy (MRE), interictal ripples (80-250Hz) are observed in large brain areas whose resection may be unnecessary for seizure freedom. This limits their utility as epilepsy biomarkers for surgery. We assessed the spatiotemporal propagation of interictal ripples on intracranial electroencephalography (iEEG) in children with MRE, compared it with the propagation of spikes, identified ripples that initiated propagation (onset-ripples), and evaluated their clinical value as epilepsy biomarkers.

METHODS: Twenty-seven children who underwent epilepsy surgery were studied. We identified propagation sequences of ripples and spikes across multiple iEEG contacts and calculated each ripple or spike latency from the propagation onset. We classified ripples and spikes into categories (ie, onset, spread, and isolated) based on their spatiotemporal characteristics and correlated their mean rate inside and outside resection with outcome (good outcome, Engel 1 versus poor outcome, Engel≥2). We determined, as onset-zone, spread-zone, and isolated-zone, the areas generating the corresponding ripple or spike category and evaluated the predictive value of their resection.

RESULTS: We observed ripple propagation in all patients and spike propagation in 25 patients. Mean rate of onset-ripples inside resection predicted the outcome (odds ratio = 5.37; p = 0.02) and correlated with Engel class (rho = -0.55; p = 0.003). Resection of the onset-ripple-zone was associated with good outcome (p = 0.047). No association was found for the spread-ripple-zone, isolated-ripple-zone, or any spike-zone.

INTERPRETATION: Interictal ripples propagate across iEEG contacts in children with MRE. The association between the onset-ripple-zone resection and good outcome indicates that onset-ripples are promising epilepsy biomarkers, which estimate the epileptogenic tissue better than spread-ripples or onset-spikes. Ann Neurol 2018;84:331-346.

INTRODUCTION: This study evaluates magnetoencephalographic (MEG) spike population as compared with intracranial electroencephalographic (IEEG) spikes using a quantitative method based on distributed source analysis.

METHODS: We retrospectively studied eight patients with medically intractable epilepsy who had an MEG and subsequent IEEG monitoring. Fifty MEG spikes were analyzed in each patient using minimum norm estimate. For individual spikes, each vertex in the source space was considered activated when its source amplitude at the peak latency was higher than a threshold, which was set at 50% of the maximum amplitude over all vertices. We mapped the total count of activation at each vertex. We also analyzed 50 IEEG spikes in the same manner over the intracranial electrodes and created the activation count map. The location of the electrodes was obtained in the MEG source space by coregistering postimplantation computed tomography to MRI. We estimated the MEG- and IEEG-active regions associated with the spike populations using the vertices/electrodes with a count over 25.

RESULTS: The activation count maps of MEG spikes demonstrated the localization associated with the spike population by variable count values at each vertex. The MEG-active region overlapped with 65 to 85% of the IEEG-active region in our patient group.

CONCLUSIONS: Mapping the MEG spike population is valid for demonstrating the trend of spikes clustering in patients with epilepsy. In addition, comparison of MEG and IEEG spikes quantitatively may be informative for understanding their relationship.

BACKGROUND: The purpose of this study is to clarify the source distribution patterns of magnetoencephalographic spikes correlated with postsurgical seizure-free outcome in pediatric patients with focal cortical dysplasia.

PATIENTS AND METHODS: Thirty-two patients with pathologically confirmed focal cortical dysplasia were divided into seizure-free and seizure-persistent groups according to their surgical outcomes based on Engel classification. In each patient, presurgical magnetoencephalography was reviewed. Dipole sources of magnetoencephalographic spikes were calculated according to a single dipole model. We obtained the following quantitative indices for evaluating dipole distribution: maximum distance over all pairs of dipoles, standard deviation of the distances between each dipole and the mean coordinate of all dipoles, average nearest neighbor distance, the rate of dipoles located within 10, 20, and 30 mm from the mean coordinate, and the rate of dipoles included in the resection. These indices were compared between the two patient groups.

RESULTS: Average nearest neighbor distance was significantly smaller in the seizure-free group than in the seizure-persistent group (P = 0.008). The rates of dipoles located within 10, 20, and 30 mm from the mean coordinate were significantly higher in the seizure-free group (P = 0.001, 0.001, 0.005, respectively). The maximum distance, standard deviation, and resection rate of dipoles did not show a significant difference between the two groups.

CONCLUSIONS: A spatially restricted dipole distribution of magnetoencephalographic spikes is correlated with postsurgical seizure-free outcomes in patients with focal cortical dysplasia. The distribution can be assessed by quantitative indices that are clinically useful in the presurgical evaluation of these patients.

Neonatal feeding has been traditionally understudied so guidelines and evidence-based support for common feeding practices are limited. A major contributing factor to the paucity of evidence-based practice in this area has been the lack of simple-to-use, low-cost tools for monitoring sucking performance. We describe new methods for quantifying neonatal sucking performance that hold significant clinical and research promise. We present early results from an ongoing study investigating neonatal sucking as a marker of risk for adverse neurodevelopmental outcomes. We include quantitative measures of sucking performance to better understand how movement variability evolves during skill acquisition. Results showed the coefficient of variation of suck duration was significantly different between preterm neonates at high risk for developmental concerns (HRPT) and preterm neonates at low risk for developmental concerns (LRPT). For HRPT, results indicated the coefficient of variation of suck smoothness increased from initial feeding to discharge and remained significantly greater than healthy full-term newborns (FT) at discharge. There was no significant difference in our measures between FT and LRPT at discharge. Our findings highlight the need to include neonatal sucking assessment as part of routine clinical care in order to capture the relative risk of adverse neurodevelopmental outcomes at discharge.

Up to one-third of patients with epilepsy are medically intractable and need resective surgery. To be successful, epilepsy surgery requires a comprehensive preoperative evaluation to define the epileptogenic zone (EZ), the brain area that should be resected to achieve seizure freedom. Due to lack of tools and methods that measure the EZ directly, this area is defined indirectly based on concordant data from a multitude of presurgical non-invasive tests and intracranial recordings. However, the results of these tests are often insufficiently concordant or inconclusive. Thus, the presurgical evaluation of surgical candidates is frequently challenging or unsuccessful. To improve the efficacy of the surgical treatment, there is an overriding need for reliable biomarkers that can delineate the EZ. High-frequency oscillations (HFOs) have emerged over the last decade as new potential biomarkers for the delineation of the EZ. Multiple studies have shown that HFOs are spatially associated with the EZ. Despite the encouraging findings, there are still significant challenges for the translation of HFOs as epileptogenic biomarkers to the clinical practice. One of the major barriers is the difficulty to detect and localize them with non-invasive techniques, such as magnetoencephalography (MEG) or scalp electroencephalography (EEG). Although most literature has studied HFOs using invasive recordings, recent studies have reported the detection and localization of HFOs using MEG or scalp EEG. MEG seems to be particularly advantageous compared to scalp EEG due to its inherent advantages of being less affected by skull conductivity and less susceptible to contamination from muscular activity. The detection and localization of HFOs with MEG would largely expand the clinical utility of these new promising biomarkers to an earlier stage in the diagnostic process and to a wider range of patients with epilepsy. Here, we conduct a thorough critical review of the recent MEG literature that investigates HFOs in patients with epilepsy, summarizing the different methodological approaches and the main findings. Our goal is to highlight the emerging potential of MEG in the non-invasive detection and localization of HFOs for the presurgical evaluation of patients with medically refractory epilepsy (MRE).

Crucial to the success of epilepsy surgery is the availability of a robust biomarker that identifies the Epileptogenic Zone (EZ). High Frequency Oscillations (HFOs) have emerged as potential presurgical biomarkers for the identification of the EZ in addition to Interictal Epileptiform Discharges (IEDs) and ictal activity. Although they are promising to localize the EZ, they are not yet suited for the diagnosis or monitoring of epilepsy in clinical practice. Primary barriers remain: the lack of a formal and global definition for HFOs; the consequent heterogeneity of methodological approaches used for their study; and the practical difficulties to detect and localize them noninvasively from scalp recordings. Here, we present a methodology for the recording, detection, and localization of interictal HFOs from pediatric patients with refractory epilepsy. We report representative data of HFOs detected noninvasively from interictal scalp EEG and MEG from two children undergoing surgery. The underlying generators of HFOs were localized by solving the inverse problem and their localization was compared to the Seizure Onset Zone (SOZ) as this was defined by the epileptologists. For both patients, Interictal Epileptogenic Discharges (IEDs) and HFOs were localized with source imaging at concordant locations. For one patient, intracranial EEG (iEEG) data were also available. For this patient, we found that the HFOs localization was concordant between noninvasive and invasive methods. The comparison of iEEG with the results from scalp recordings served to validate these findings. To our best knowledge, this is the first study that presents the source localization of scalp HFOs from simultaneous EEG and MEG recordings comparing the results with invasive recordings. These findings suggest that HFOs can be reliably detected and localized noninvasively with scalp EEG and MEG. We conclude that the noninvasive localization of interictal HFOs could significantly improve the presurgical evaluation for pediatric patients with epilepsy.

The assessment of oral-motor behavior (OMB) represents one the earliest noninvasive ways to evaluate newborns' well-being and neuromotor behavior. This work aimed at developing a new low-cost, easy-to-use and noninvasive system for a technology-aided assessment of newborns' OMB during bottle feeding. A SUcking MOnitoring Device (SUMOD) was designed and developed to be easily integrated on a typical feeding bottle. A software system was developed to automatically treat and analyze the acquired data: proper algorithms for a fully automatic segmentation and features extraction are proposed and implemented. A set of measures of motor control and coordination are introduced and implemented for the specific application to the OMB analysis. Experimental data were collected on two groups of newborns (healthy versus low birth weight) with the SUMOD in a clinical setting.