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Abstract #0898

Identifying Individual Motor Function Using Machine Learning Predication Based on Resting-State fMRI for Presurgical Mapping in Patients with Brain Tumor

Chen Niu1, Elizabeth Zakszewski2, Alexander Cohen2, Xiao Ling1, Ming Zhang1, Maode Wang1, and Yang Wang2

1First Affiliated Hospital of Xi'An Jiaotong University, Shaanxi Xi'an, China, 2Medical College of Wisconsin, Milwaukee, WI, United States

A novel machine learning model was developed using resting-state and task fMRI on healthy subjects. This study applied this novel model to clinical patients. Preliminary data on 25 patients with space-occupying brain tumors suggested our approach could accurately predict hand functional area at the individual level in patients with brain tumors, even in cases where patients had displacement of brain tissue and reorganization of brain motor functional network. Our methods implicated the great potential for clinical application of presurgical mapping.

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