Abstract #1194

Modular changes in functional connectivity associated with clinical symptoms in mild traumatic brain injury (mTBI)

Radhika Madhavan¹, Hariharan Ravishankar¹, Suresh E Joel¹, Rakesh Mullick¹, Sumit Niogi², John A Tsiouris², Luca Marinelli³, and Teena Shetty⁴

¹GE Global Research, Bangalore, India, ²Weill Cornell Medical College, New York, NY, United States, ³GE Global Research, Niskayuna, NY, United States, ⁴Hospital for Special Surgery, New York City, NY, United States

Although most mTBI patients recover by 3-6 months, they suffer serious short and long term effects. Additionally, multiple mTBIs may have serious long-term consequences. Here, we correlated brain network-level connectivity features derived from resting state functional magnetic resonance imaging (rs-fMRI) with clinical symptoms, in order to identify neuroimaging biomarkers of mTBI as patients recover over 3 months. We used a machine-learning framework to select connectivity features associated with symptoms and identified functional regions with altered connectivity. These modular network-level features can be used as diagnostic tools for predicting disease severity and recovery profiles.

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