Researchers led by Ryan Rava of the University of Buffalo in New York developed an artificial intelligence (AI) algorithm that, when used with CT perfusion imaging, can assess acute ischemic stroke (AIS) patients’ collateral flow, a key indicator of improved functional outcome, according to the team.

The retrospective study included 200 AIS patients between March 2019 and January 2020. “This study demonstrated one of the first artificial intelligence based algorithms capable of accurately and efficiently assessing AIS patients’ collateral flow. This automated method for determining collateral filling could streamline clinical workflow, reduce bias, and aid in clinical decision making for determining reperfusion eligible patients,” concluded the authors.

Sources:

Ryan A. Rava, Samantha E. Seymour, Kenneth V. Snyder, Muhammad Waqas, Jason M. Davies, Elad I. Levy, Adnan H. Siddiqui, Ciprian N. Ionita. Automated Collateral Flow Assessment in Acute Ischemic Stroke Patients using Computed Tomography with Artificial Intelligence Algorithms. World Neurosurgery, 2021, https://doi.org/10.1016/j.wneu.2021.08.136. https://www.sciencedirect.com/science/article/pii/S1878875021013243 Accessed September 14, 2021. 

Yee, Kate. “Use AI with CT to better assess stroke patients’ collateral flow.” AuntMinnie.com September 13, 2021. Accessed September 14, 2021, at https://www.auntminnie.com/index.aspx?sec=sup&sub=cto&pag=dis&ItemID=133465