A network approach to investigate the bi-hemispheric synchrony in absence epilepsy

\u3cp\u3eObjective: Our objective was to unravel the dynamics underlying spike-and-wave discharges (SWDs) characteristic for childhood absence epilepsy. Methods: SWDs were recorded for a cohort of 28 children using magnetoencephalography. Non-linear association analyses and a graph theoretical metric of local connectedness (LoC) were utilized in a sliding window starting one s before till four s after ictal onset. Results: A focal pattern of bilateral frontal and parietal areas with high LoC during the spikes alternated by generalized patterns during the waves was found for all children studied during generalization of the SWDs. In the interval preceding the generalization a focal parietal region was most often (16/28) encountered and less often an occipital (4/28), temporal (5/28) or frontal (3/28) region. 55% of the children with a parietal/occipital focal onset became seizure free after the administration of two anti-epileptic drugs, and only 12.5% with a temporal/frontal focal onset. Conclusions: The transition from the interictal to the ictal state is for some of the children characterized by dominant LoC at either the parietal/occipital and for others at the frontal/temporal region. Significance: The focal onset of the SWDs varies in location among the children with a clinical similar profile, who, however, seemingly are differing with regard to seizure control.\u3c/p\u3

Multi-modal brain imaging software for guiding invasive treatment of epilepsy

Purpose:\u3cbr/\u3eThe surgical treatment of patients with complex epilepsies is\u3cbr/\u3echanging more and more from open, invasive surgery towards minimally\u3cbr/\u3einvasive, image guided treatment. Multi-modal brain imaging procedures\u3cbr/\u3eare developed to delineate preoperatively the region of the brain which is\u3cbr/\u3eresponsible for the epilepsy of a patient and delimit the functional areas\u3cbr/\u3erelative to this region. The ultimate aim is to provide the neurosurgeon\u3cbr/\u3ewith a clear and intuitive image of the targeted epileptogenic region in\u3cbr/\u3eorder to render the patient seizure free, while avoiding damage to elo-\u3cbr/\u3equent cortex.\u3cbr/\u3eMethod:\u3cbr/\u3eA software product (SP) is developed for multi-modality map-\u3cbr/\u3eping of the analysis results of non-invasive and invasive epilepsy record-\u3cbr/\u3eings and visualization of these results against brain anatomy. The SP\u3cbr/\u3econtains several pre-programmed sequences for creating the most com-\u3cbr/\u3emonly used multi-modality brain images that can be used to delineate the\u3cbr/\u3eepileptic tissue versus functional areas, like visualization of inverse solu-\u3cbr/\u3etions of high density EEG and MEG, EEG informed functional MRI\u3cbr/\u3e(fMRI) visualizations and functional Near-Infrared Spectroscopy\u3cbr/\u3e(fNIRS) projections.\u3cbr/\u3eResults:\u3cbr/\u3eThe SP is optimized for intuitive and clinical usage to interac-\u3cbr/\u3etively explore the different modalities in relation to the available anatom-\u3cbr/\u3eical and structural MRI data. The distinct modalities can be combined by\u3cbr/\u3e3D-fusion of the images and visualized in 2D- and 3D-MRI viewports\u3cbr/\u3eagainst the implanted depth electrodes and the brain mapping results of\u3cbr/\u3ethe invasive EEG recordings.\u3cbr/\u3eConclusion:\u3cbr/\u3eMulti-modal functional and structural brain imaging\u3cbr/\u3eapplied on data of the individual patient can be used for guiding surgical\u3cbr/\u3eresections with minimal disruption of brain anatomy, while rendering a\u3cbr/\u3epatient seizure free.\u3cbr/\u3eAcknowledgement:\u3cbr/\u3eThis study is part of the project\u3cbr/\u3e“\u3cbr/\u3eAdvancing Smart\u3cbr/\u3eOptical Imaging and Sensing for Health (ASTONISH)\u3cbr/\u3e”\u3cbr/\u3ethat has received\u3cbr/\u3efunding from ECSEL Joint Undertaking (grant no. 692470).\u3cbr/\u3

The influence of construction methodology on structural brain network measures:a review

Structural brain networks based on diffusion MRI and tractography show robust attributes such as small-worldness, hierarchical modularity, and rich-club organization. However, there are large discrepancies in the reports about specific network measures. It is hypothesized that these discrepancies result from the influence of construction methodology. We surveyed the methodological options and their influences on network measures. It is found that most network measures are sensitive to the scale of brain parcellation, MRI gradient schemes and orientation model, and the tractography algorithm, which is in accordance with the theoretical analysis of the small-world network model. Different network weighting schemes represent different attributes of brain networks, which makes these schemes incomparable between studies. Methodology choice depends on the specific study objectives and a clear understanding of the pros and cons of a particular methodology. Because there is no way to eliminate these influences, it seems more practical to quantify them, optimize the methodologies, and construct structural brain networks with multiple spatial resolutions, multiple edge densities, and multiple weighting schemes

Burden of disease of people with epilepsy during an optimized diagnostic trajectory:costs and quality of life

\u3cp\u3eBackground: Diagnosing epilepsy can be lengthy and stressful, potentially leading to increased use of healthcare resources and a reduction in quality of life. Aim: This study aims to determine cost and quality of life before and after an optimized diagnostic procedure for people suspected of having epilepsy from a societal perspective with a follow-up of 12 months. In addition, this study aims to differentiate between people diagnosed with epilepsy during the follow-up of the study and the people who are diagnosed as not having epilepsy or for whom diagnosis is still uncertain. Methods: A questionnaire regarding the use of healthcare resources was used accompanied by the EQ-5D-3 L. Multiple imputations by chained equations with predictive mean matching was used to account for missing data. To investigate the uncertainty of the results, non-parametric bootstrapped (1000 times) was used. Results: In total, 116 people were included in the study. Total average costs per patient made in the previous 3 months had decreased from €4594 before the optimized diagnostic trajectory to €2609 in the 12 months after the optimized diagnostic trajectory. Healthcare costs were the largest expense group (52–66%) and had decreased significantly from baseline measurement to 12 months after baseline (€2395 vs €1581). Productivity costs had decreased from €1367 to €442 per 3 months. Total annual costs were similar between people diagnosed with epilepsy during the follow-up of the study and the people who are diagnosed as not having epilepsy or for whom diagnosis is still uncertain. Quality of Life had significantly increased over the course of 12 months from 0.80 to 0.84 (Dutch tariff). Discussion: This study indicates that an optimized diagnostic trajectory has positively influenced the use of healthcare resources and the quality of life in people with epilepsy. As chronic care patients make diverse costs, future research should identify the long-term costs after an optimized diagnostic trajectory for patients with epilepsy, possibly identifying patients who are at high risk of becoming high-cost users in the future for early intervention.\u3c/p\u3

Modeling of intracerebral interictal epileptic discharges : evidence for network interactions

Purpose:\u3cbr/\u3eStereotactic EEG (SEEG) recordings are considered to be the best choice for preoperative invasive evaluation when the epilepsy of the patient is suspected to originate in deep-sited anatomical structures and standard electro-clinical examinations are not conclusive. The interictal epileptic discharges (IEDs) occurring in these recordings in general are abundant compared to ictal discharges, but difficult to interpret due to\u3cbr/\u3ecomplex underlying network interactions.\u3cbr/\u3eMethod:\u3cbr/\u3eA framework is developed to model the spatiotemporal net-work interactions underlying the IEDs. To identify the highly synchronized neural activity underlying these discharges, the variation in correlation over time of the SEEG signals is related to the occurrence of the IEDs using the general linear model [van Houdt et al., 2012]. Subsequently, it is assessed whether the brain regions that reflect highly synchronized neural activity are either independent or interacting within an epileptic network. Independent component analysis is applied followed by clustering of the spatial distributions of the independent components.\u3cbr/\u3eThe spatial distributions of the spike clusters are visualized together with the estimated time delays against the patients’ brain anatomy [Meesters et al., 2015].\u3cbr/\u3eResults:\u3cbr/\u3eThe analysis framework was evaluated for five patients who underwent SEEG recordings prior to successful epilepsy surgery. The spatial distribution of the spike cluster that was related to the MRI-visible brain lesions coincided with the seizure onset zone of these patients.\u3cbr/\u3eUnraveling of the complex network interactions underlying the IEDs of two more patients without satisfactory surgical outcome indicated that an alternative and plausible resection strategy could have been considered.\u3cbr/\u3eConclusion:\u3cbr/\u3eThe analysis framework applied to IEDs is considered a valuable additional tool to the current seizure assessment approach, which might lead to a more successful outcome of epilepsy surgery.\u3cbr/\u3eAcknowledgement:\u3cbr/\u3eThis study is part of the DeNeCor-project that has received funding from the ENIAC Joint Undertaking (grant no. 324257).\u3cbr/\u3

Automated identification of intracranial depth electrodes in computed tomography data

Intracranial depth electrodes are commonly used to identify the regions of the brain that are responsible for epileptic seizures. Knowledge of the exact location of the electrodes is important as to properly interpret the EEG in relation to the anatomy. In order to provide fast and accurate identification of these electrodes, a procedure has been developed for automatic detection and localization in computed tomography data. Results indicate that in the vast majority of cases the depth electrodes can be automatically found. The localization of the electrodes versus the anatomy showed an acceptably small error when compared to manual positioning. Furthermore, interactive visualization software is developed to show the detected electrodes together with pre-operative MRI images, which enables the physician to confirm that the electrode is placed at the expected anatomical location

Modeling of intracerebral interictal epileptic discharges:evidence for network interactions

\u3cp\u3eObjective: The interictal epileptic discharges (IEDs) occurring in stereotactic EEG (SEEG) recordings are in general abundant compared to ictal discharges, but difficult to interpret due to complex underlying network interactions. A framework is developed to model these network interactions. Methods: To identify the synchronized neuronal activity underlying the IEDs, the variation in correlation over time of the SEEG signals is related to the occurrence of IEDs using the general linear model. The interdependency is assessed of the brain areas that reflect highly synchronized neural activity by applying independent component analysis, followed by cluster analysis of the spatial distributions of the independent components. The spatiotemporal interactions of the spike clusters reveal the leading or lagging of brain areas. Results: The analysis framework was evaluated for five successfully operated patients, showing that the spike cluster that was related to the MRI-visible brain lesions coincided with the seizure onset zone. The additional value of the framework was demonstrated for two more patients, who were MRI-negative and for whom surgery was not successful. Conclusions: A network approach is promising in case of complex epilepsies. Significance: Analysis of IEDs is considered a valuable addition to routine review of SEEG recordings, with the potential to increase the success rate of epilepsy surgery.\u3c/p\u3