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Abstract #4938

Implementation of a Data Analysis Pipeline for intraoperative fMRI

Nicolas Weilguny1,2,3, Roxane Licandro3, Matthias Tomschik1, Jonathan Wais1, Cora Hedrich4, Julia Shawarba1, Gregor Kasprian5, Karl Rössler1,6, Christian Dorfer1, and Gilbert Hangel1,2,6
1Department of Neurosurgery, Medical University of Vienna, Vienna, Austria, 2High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, 3Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, 4Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria, 5Department of Radiodiagnostics, Medical University of Vienna, Vienna, Austria, 6Christian Doppler Laboratory for MR Imaging Biomarkers, Vienna, Austria

Synopsis

Keywords: Other Interventional, Software Tools, fMRI Preprocessing

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.

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Keywords