Project Grant R01NS138765

This $1,079,194 federal Project Grant award from the National Institute of Neurological Disorders and Stroke (NINDS) under the Extramural Research Programs in the Neurosciences and Neurological Disorders (CFDA 93.853) program aims to address the paradox of poor outcomes despite successful recanalization in stroke patients treated with endovascular stroke therapy (EVT).

The award will fund a multi-year research effort to: 1) create a longitudinal clinical and imaging dataset to evaluate the role of final infarct volume on patient outcomes; 2) develop and validate a novel classification system to identify patients with persistent disability despite successful reperfusion; and 3) create deep learning models to predict clinical outcomes in EVT patients using imaging and clinical data. The goal is to generate an improved understanding of the gap between successful recanalization and good clinical outcomes, and develop a machine learning tool to help identify the most vulnerable stroke patients who may require additional treatments beyond EVT. The award was made to the University of Texas Health Science Center at Houston, a prominent academic research institution with extensive federal funding experience.