Pregnancy and neurodevelopmental outcomes with in-utero antiepileptic agent exposure. A pilot study.

OBJECTIVE: To assess pregnancy outcomes on women exposed to monotherapy with antiepileptic agents. METHODS: Questionnaires were sent to women with epilepsy in our practice who were pregnant between 2006 and 2011. 62/86 patients (72%) who responded were on monotherapy. 24 fetuses (63%) were exposed to lamotrigine, 11 (28%) to levetiracetam, 2 (5.2%) to topiramate, 1 (2.6%) to gabapentin, 17 (27%) to carbamazepine, 5 to phenytoin and 2 to valproate. RESULTS: There were 55 (88%) live births and 7 unsuccessful pregnancies (miscarriages/stillbirths). Unsuccessful pregnancies were reported in 2/24 gestations exposed to lamotrigine, 2/11 to levetiracetam and 3/17 to carbamazepine. Delayed motor development or speech delay requiring therapy and special programming was noted in 2/24 children prenatally exposed to lamotrigine, 3/17 exposed to carbamazepine and 1/2 children exposed to valproate. CONCLUSION: Our pilot study of children exposed to antiepileptic drug monotherapy in-utero demonstrated a favorable trend for successful pregnancy outcomes and developmental trajectory.

Reconstructing spatially extended brain sources via enforcing multiple transform sparseness.

Accurate estimation of location and extent of neuronal sources from EEG/MEG remain challenging. In the present study, a new source imaging method, i.e. variation and wavelet based sparse source imaging (VW-SSI), is proposed to better estimate cortical source locations and extents. VW-SSI utilizes the L1-norm regularization method with the enforcement of transform sparseness in both variation and wavelet domains. The performance of the proposed method is assessed by both simulated and experimental MEG data, obtained from a language task and a motor task. Compared to L2-norm regularizations, VW-SSI demonstrates significantly improved capability in reconstructing multiple extended cortical sources with less spatial blurredness and less localization error. With the use of transform sparseness, VW-SSI overcomes the over-focused problem in classic SSI methods. With the use of two transformations, VW-SSI further indicates significantly better performance in estimating MEG source locations and extents than other SSI methods with single transformations. The present experimental results indicate that VW-SSI can successfully estimate neural sources (and their spatial coverage) located in close areas while responsible for different functions, i.e. temporal cortical sources for auditory and language processing, and sources on the pre-bank and post-bank of the central sulcus. Meantime, all other methods investigated in the present study fail to recover these phenomena. Precise estimation of cortical source locations and extents from EEG/MEG is of significance for applications in neuroscience and neurology.

Sparse MEG source imaging for reconstructing dynamic sources of interictal spikes in partial epilepsy.

PURPOSE: The present study aimed to test the feasibility of a novel neuroimaging technique, that is, variation-based sparse cortical current density (VB-SCCD) imaging algorithm, in noninvasively estimating location and extent of epileptic sources from interictal magnetoencephalography (MEG) data. METHODS: A total of 108 interictal spikes from 3 partial epilepsy patients were selected to perform VB-SCCD source analysis. Cortical sources were identified at spike peaks, rising phases, and entire spikes, respectively, from all interictal spikes in each patient, to estimate source locations and extents, and validated using presurgical evaluation data. Other source analysis methods, that is, minimum norm estimate and sparse source imaging were also performed for comparison. RESULTS: Cortical sources reconstructed by VB-SCCD that are consistent with clinical presurgical evaluation outcomes have detection rates of 65.8% at spike peaks, 85.1% during rising phases, and 92.6% in entire spikes. Stable spatiotemporal patterns of reconstructed cortical sources were also obtained using VB-SCCD, which provide more insights about the formation and propagation of interictal epileptic activity. CONCLUSIONS: Our present results suggest that the VB-SCCD technique has the capability in estimating location and extent of epileptic sources of interictal spikes and is promising to become a valuable noninvasive tool in assisting presurgical planning for partial epilepsy patients.

Sparse imaging of cortical electrical current densities via wavelet transforms.

While the cerebral cortex in the human brain is of functional importance, functions defined on this structure are difficult to analyze spatially due to its highly convoluted irregular geometry. This study developed a novel L1-norm regularization method using a newly proposed multi-resolution face-based wavelet method to estimate cortical electrical activities in electroencephalography (EEG) and magnetoencephalography (MEG) inverse problems. The proposed wavelets were developed based on multi-resolution models built from irregular cortical surface meshes, which were realized in this study too. The multi-resolution wavelet analysis was used to seek sparse representation of cortical current densities in transformed domains, which was expected due to the compressibility of wavelets, and evaluated using Monte Carlo simulations. The EEG/MEG inverse problems were solved with the use of the novel L1-norm regularization method exploring the sparseness in the wavelet domain. The inverse solutions obtained from the new method using MEG data were evaluated by Monte Carlo simulations too. The present results indicated that cortical current densities could be efficiently compressed using the proposed face-based wavelet method, which exhibited better performance than the vertex-based wavelet method. In both simulations and auditory experimental data analysis, the proposed L1-norm regularization method showed better source detection accuracy and less estimation errors than other two classic methods, i.e. weighted minimum norm (wMNE) and cortical low-resolution electromagnetic tomography (cLORETA). This study suggests that the L1-norm regularization method with the use of face-based wavelets is a promising tool for studying functional activations of the human brain.

Source connectivity analysis from MEG and its application to epilepsy source localization.

We report an approach to perform source connectivity analysis from MEG, and initially evaluate this approach to interictal MEG to localize epileptogenic foci and analyze interictal discharge propagations in patients with medically intractable epilepsy. Cortical activities were reconstructed from MEG using individual realistic geometry boundary element method head models. Directional connectivity among cortical regions of interest was then estimated using directed transfer function. The MEG source connectivity analysis method was implemented in the eConnectome software, which is open-source and freely available at http://econnectome.umn.edu . As an initial evaluation, the method was applied to study MEG interictal spikes from five epilepsy patients. Estimated primary epileptiform sources were consistent with surgically resected regions, suggesting the feasibility of using cortical source connectivity analysis from interictal MEG for potential localization of epileptiform activities.

Evaluations of sparse source imaging and minimum norm estimate methods in both simulation and clinical MEG data.

The aim of the present study is to evaluate the capability of a recently proposed l(1)-norm based regularization method, named as variation-based sparse cortical current density (VB-SCCD) algorithm, in estimating location and spatial coverage of extensive brain sources. Its performance was compared to the conventional minimum norm estimate (MNE) using both simulations and clinical interictal spike MEG data from epilepsy patients. Four metrics were adopted to evaluate two regularization methods for EEG/MEG inverse problems from different aspects in simulation study. Both methods were further compared in reconstructing epileptic sources and validated using results from clinical diagnosis. Both simulation and experimental results suggest VB-SCCD has better performance in localization and estimation of source extents, as well as less spurious sources than MNE, which makes it a promising noninvasive tool to assist presurgical evaluation for surgical treatment in epilepsy patients.

Sparse MEG source imaging in Landau-Kleffner syndrome.

Epilepsy patients with Landau-Kleffner syndrome (LKS) usually have a normal brain structure, which makes it a challenge to identify the epileptogenic zone only based on magnetic resonance imaging (MRI) data. A sparse source imaging technique called variation based sparse cortical current density (VB-SCCD) imaging was adopted here to reconstruct cortical sources of magnetoencephalography (MEG) interictal spikes from an LKS patient. Realistic boundary element (BE) head and cortex models were built by segmenting structural MRI. 148-channel MEG was recorded for 10 minutes between seizures. Total 29 epileptiform spikes were selected for analysis. The primary cortical sources were observed locating at the left intra- and perisylvian cortex. Multiple extrasylvian sources were identified as the secondary sources. The spatio-temporal patterns of cortical sources provide more insights about the neuronal synchrony and propagation of epileptic discharges. Our observations were consistent with presurgical diagnosis for this patient and observation of aphasia in LKS. The present results suggest that the promising of VB-SCCD technique in assisting with presurgical planning and studying the neural network for LKS in determining the lateralization of epileptic origins. It can further be applied to non-invasively localize and/or lateralize eloquent cortex for language for epilepsy patients in general in the future.

Variation-based sparse cortical current density imaging in estimating cortical sources with MEG data.

We investigated the performance of a new sparse neuroimaging method, i.e., Variation-Based Sparse Cortical Current Density (VB-SCCD) using magnetoencephalography (MEG) data to reconstruct extended cortical sources and their spatial distributions on the cortical surface. We conducted Monte Carlo simulation studies to compare the performance of the VB-SCCD method with different number of cortical sources and different number of MEG sensors. Our simulation data suggests that the VB-SCCD method is able to reconstruct extended cortical sources with the overall accuracy, while it has significantly reduced performance when cortical sources are radially oriented to MEG sensors. It has higher accuracy when the number of sensors is large and the source configuration is simple. We further assess the performance of VB-SCCD in real MEG data from an epilepsy patient and reconstructed cortical sources behind interictal spikes from the patient which are consistent with the clinical evaluation outcomes. This data indicate its promising applications in clinical problems related to neurological disorders.

Lateralizing language with magnetic source imaging: validation based on the Wada test.

PURPOSE: Magnetoencephalography (MEG)/magnetic source imaging (MSI) is a noninvasive functional neuroimaging procedure used to localize language-specific regions in the brain. The Wada test, or intracarotid amobarbital procedure (IAP), is the gold standard in determining speech/language lateralization for presurgical planning, although it is invasive and associated with morbidity. The purpose of this study is to provide further validation on the use of MSI for presurgical language lateralization by comparing results against the IAP. METHODS: The sample consisted of 35 patients with epilepsy and/or brain tumor undergoing presurgical evaluation at the Minnesota Epilepsy Group. All patients received both an IAP and MSI to determine hemispheric language dominance. For MSI, a 148-channel MEG system was used to record activation of language-specific cortex by an auditory word-recognition task. RESULTS: The MSI and IAP were concordant in determining language in the hemisphere to be treated in 86% of the cases with sensitivity and specificity values of 80% and 100%, respectively. CONCLUSIONS: The results from this study are consistent with prior research findings comparing functional neuroimaging procedures to the IAP in determining language lateralization in presurgical patients. The current study provides an important replication and support for Papanicolaou et al.'s findings in 2004 using a consecutive clinical sample from a different institution. An unusually high rate of atypical IAP language cases in this sample and differences between the two procedures are believed to explain the noted discrepancies. MSI is a viable noninvasive alternative to the IAP in the presurgical determination of language lateralization.