Image Fusion to Guide Decision-Making Towards Minimally Invasive Epilepsy Treatment.

For the work-up of epilepsy surgery candidates, various medical imaging data are acquired for diagnosis. Software applications were designed for multimodality mapping of non-invasive and invasive imaging data to support the decision-making process towards minimally invasive treatment of these candidates. The multi-modal imaging software imports from disparate sources of data the anatomical, functional and structural medical imaging datasets, brings the datasets in the same co-ordinate system and allows the user to browse through the medical imaging datasets obtained with the distinct imaging modalities. Convergence with 3D-mapping of depth electrode or stereo-EEG (SEEG) recordings completes the image fusion that may guide the decision for minimally invasive treatment. Shown are the results of several pre-programmed sequences for creating multi-modal visualizations used to identify epileptic tissue versus functional areas, combining e.g., magnetic resonance images (MRI), Positron Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT), inverse solutions of high-density EEG and functional MRI. Regions of interest can be set to mark abnormalities visible at the images, while integration with depth electrodes translate the neurophysiology recordings into a 3D-space. The applications are designed to provide the clinician with an easy-to-use tool to visualize in a multi-modal fashion the images acquired during the work-up of epilepsy surgery candidates. Integration with visualization of SEEG recordings in a 3D-space completes the decision-making process towards invasive treatment, aimed at rendering a patient seizure free while avoiding damage to eloquent cortex.