3 research outputs found

    An individual data-driven virtual resection model based on epileptic network dynamics in children with intractable epilepsy: a magnetoencephalography interictal activity application

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    Epilepsy surgery continues to be a recommended treatment for intractable (medication-resistant) epilepsy; however, 30–70% of epilepsy surgery patients can continue to have seizures. Surgical failures are often associated with incomplete resection or inaccurate localization of the epileptogenic zone. This retrospective study aims to improve surgical outcome through in silico testing of surgical hypotheses through a personalized computational neurosurgery model created from individualized patient’s magnetoencephalography recording and MRI. The framework assesses the extent of the epileptic network and evaluates underlying spike dynamics, resulting in identification of one single brain volume as a candidate for resection. Dynamic-locked networks were utilized for virtual cortical resection. This in silico protocol was tested in a cohort of 24 paediatric patients with focal drug-resistant epilepsy who underwent epilepsy surgery. Of 24 patients who were included in the analysis, 79% (19 of 24) of the models agreed with the patient's clinical surgery outcome and 21% (5 of 24) were considered as model failures (accuracy 0.79, sensitivity 0.77, specificity 0.82). Patients with unsuccessful surgery outcome typically showed a model cluster outside of the resected cavity, while those with successful surgery showed the cluster model within the cavity. Two of the model failures showed the cluster in the vicinity of the resected tissue and either a functional disconnection or lack of precision of the magnetoencephalography–MRI overlapping could explain the results. Two other cases were seizure free for 1 year but developed late recurrence. This is the first study that provides in silico personalized protocol for epilepsy surgery planning using magnetoencephalography spike network analysis. This model could provide complementary information to the traditional pre-surgical assessment methods and increase the proportion of patients achieving seizure-free outcome from surgery.Depto. de Radiología, Rehabilitación y FisioterapiaFac. de MedicinaTRUEpu

    Effects of spaceflight on the EEG alpha power and functional connectivity

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    Abstract Electroencephalography (EEG) can detect changes in cerebral activity during spaceflight. This study evaluates the effect of spaceflight on brain networks through analysis of the Default Mode Network (DMN)'s alpha frequency band power and functional connectivity (FC), and the persistence of these changes. Five astronauts' resting state EEGs under three conditions were analyzed (pre-flight, in-flight, and post-flight). DMN’s alpha band power and FC were computed using eLORETA and phase-locking value. Eyes-opened (EO) and eyes-closed (EC) conditions were differentiated. We found a DMN alpha band power reduction during in-flight (EC: p < 0.001; EO: p < 0.05) and post-flight (EC: p < 0.001; EO: p < 0.01) when compared to pre-flight condition. FC strength decreased during in-flight (EC: p < 0.01; EO: p < 0.01) and post-flight (EC: ns; EO: p < 0.01) compared to pre-flight condition. The DMN alpha band power and FC strength reduction persisted until 20 days after landing. Spaceflight caused electrocerebral alterations that persisted after return to earth. Periodic assessment by EEG-derived DMN analysis has the potential to become a neurophysiologic marker of cerebral functional integrity during exploration missions to space

    Neuroimaging Pearls from the MDS Congress Video Challenge. Part 2: Acquired Disorders

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    The MDS Video Challenge continues to be the one of most widely attended sessions at the International Congress. Although the primary focus of this event is the presentation of complex and challenging cases through videos, a number of cases over the years have also presented an unusual or important neuroimaging finding related to the case. We reviewed the previous Video Challenge cases and present here a selection of those cases which incorporated such imaging findings. We have compiled these “imaging pearls” into two anthologies. The first focuses on pearls where the underlying diagnosis was a genetic condition. This second anthology focuses on imaging pearls in cases where the underlying condition was acquired. For each case we present brief clinical details along with neuroimaging findings, the characteristic imaging findings of that disorder and, finally, the differential diagnosis for the imaging findings seen.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/171975/1/mdc313415_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/171975/2/mdc313415.pd
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