See Bernasconi (doi:10.1093/brain/awx229) for a scientific commentary on this article. Drug-resistant localization-related epilepsies are now recognized as network diseases. However, the exact relationship between the organization of the epileptogenic network and brain anatomy overall remains incompletely understood. To better understand this relationship, we studied structural connectivity obtained from diffusion weighted imaging in patients with epilepsy using both stereo-electroencephalography (SEEG)-determined epileptic brain regions and whole-brain analysis. High resolution structural connectivity analysis was applied in 15 patients with drug-resistant localization-related epilepsies and 36 healthy control subjects to study structural connectivity changes in epilepsy. Two different methods of structural connectivity analysis were carried out using diffusion weighted imaging, one focusing on the relationship between epileptic regions determined by SEEG investigations and one blinded to epileptic regions looking at whole-brain connectivity. First, we performed zone-based analysis comparing structural connectivity findings in patients and controls within and between SEEG-defined zones of interest. Next, we performed whole-brain structural connectivity analysis in all subjects and compared findings to the same SEEG-defined zones of interest. Finally, structural connectivity findings were correlated against clinical features. Zone-based analysis revealed no significant decreased structural connectivity within nodes of the epilepsy network at the group level, but did demonstrate significant structural connectivity differences between nodes of the epileptogenic network (regions involved in seizures generation and propagation) and the remaining of the brain in patients compared to controls. Whole-brain analyses showed a total of 133 clusters of significantly decreased structural connectivity across all patients. One cluster of significantly increased structural connectivity was identified in a single patient. Clusters of decreased structural connectivity showed topographical preference for both the salience and default mode networks despite clinical heterogeneity within our patient sample. Correlation analysis did not reveal any significant findings regarding either the effect of age at disease onset, disease duration or post-surgical outcome on structural connectivity. Taken together, this work demonstrates that structural connectivity disintegration targets distributed functional networks while sparing the epilepsy network.
Functional magnetic resonance imaging (fMRI) is an important tool for pre-surgical evaluation of eloquent cortex. Classic task-based paradigms require patient participation and individual imaging sequence acquisitions for each functional domain that is being assessed. Resting state fMRI (rs-fMRI), however, enables functional localization without patient participation and can evaluate numerous functional domains with a single imaging session. To date, post-processing of this resting state data has been resource intensive, which limits its widespread application for routine clinical use. Through a novel automated algorithm and advanced imaging IT structure, we report the clinical application and the large-scale integration of rs-fMRI into routine neurosurgical practice. One hundred and ninety one consecutive patients underwent a 3T rs-fMRI, 83 of whom also underwent both motor and language task-based fMRI. Data were processed using a novel, automated, multi-layer perceptron algorithm and integrated into stereotactic navigation using a streamlined IT imaging pipeline. One hundred eighty-five studies were performed for intracranial neoplasm, 14 for refractory epilepsy and 33 for vascular malformations or other neurological disorders. Failure rate of rs-fMRI of 13% was significantly better than that for task-based fMRI (38.5%,) (p <0.001). In conclusion, at Washington University in St. Louis, rs-fMRI has become an integral part of standard imaging for neurosurgical planning. Resting state fMRI can be used in all patients, and due to its lower failure rate than task-based fMRI, it is useful for patients who are unable to cooperate with task-based studies.
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