Prospective Evaluation of Artificial Intelligence Imaging Support Software for Acute Ischemic Stroke in the Mayo Clinic Telestroke Network

Objective: To explore the real-world impact of artificial intelligence-driven decision support imaging software for patients with acute ischemic stroke in a mature telestroke network in the United States.

Patients and Methods: We conducted a prospective evaluation of stroke imaging support software in a robust, predominantly rural telestroke network (17 sites in Minnesota and Wisconsin). Data was collected from all patients who underwent video telestroke evaluation in a 3-month preimplementation period and a 3-month postimplementation period. Primary outcome measures were treatment rates and time to treatment for intravenous thrombolysis (IVT) and endovascular therapy (EVT).

Results: Total of 444 telestroke cases were included in the preimplementation period, and 463 in the postimplementation period. The rate of IVT treatment delivery rose from 26.6% to 35.0% of potentially eligible patients (P=.24), whereas EVT treatment delivery remained at 31%. Time to IVT delivery reduced from 47 minutes to 41 minutes. Survey results reported good user satisfaction with algorithm performance and image viewing.

Conclusions: The study did show numerical improvements in IVT treatment rates and treatment times, but not EVT rates or treatment times, and survey feedback from clinical end users was positive, highlighted by high level of trust and user satisfaction with the software. More robust studies are needed to determine the real-world impact of this AI imaging software in an established telestroke network.