Implementation of automated resting-state presurgical fMRI analysis pipelines with patient-based probabilistic functional atlases

Motivation: To develop clinical software for automated localization of critical functional networks with presurgical resting-state (rs) functional MRI (fMRI). Goal(s): To develop analysis pipelines integrating patient-based probabilistic functional atlases and evaluate their effectiveness for mapping motor (hand, tongue, foot), visual, and language networks. Approach: The software implemented motor, visual, and language atlases, created using presurgical tb-fMRI of brain tumor patients, for seed-based correlation and independent component analysis on rs-fMRI patient data. The results were compared to tb-fMRI. Results: The distances between the resulting functional connectivity peaks and tb-fMRI activation peaks were equivalent to those obtained by seeding based on tb-fMRI activation. Impact: This work developed software that automates rs-fMRI analysis by implementing probabilistic functional atlases in SBC and ICA pipelines. It supports routine clinical use of rs-fMRI for presurgical mapping of motor, visual, and language areas for patients undergoing brain tumor resection.