Implementation of a Data Analysis Pipeline for intraoperative fMRI

Motivation: Immediate changes in functionality during brain surgery in tumor and epilepsy patients are worth investigating in order to improve prediction of surgical outcomes. Goal(s): We want to implement a preprocessing-pipeline for pre- and post-resection data that allows comparison between both scans and the application of further analysis methods. Approach: We propose a two-step approach, where we first pre-register the anatomical data to MNI-space with consideration of the resection area and then use this data in a second step for preprocessing of fMRI data. Results: The preprocessing gives satisfactory results that enable further analysis of intraoperative fMRI data, such as PICA. Impact: We showed that the difficult case of pre- and post-resection data preprocessing is feasible and allows analysis of intraoperative fMRI data. This enables further investigation of changes in brain functionality during surgery which might lead to improvements in neurosurgery.