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Automated Vessel Occlusion Software in Acute Ischemic Stroke: Pearls and Pitfalls

Year: 2025
Type: article
Abstract: Software programs leveraging artificial intelligence to detect vessel occlusions are now widely available to aid in stroke triage. Given their proprietary use, there is a surprising lack of information regarding how the software works, who is using the software, and their performance in an unbiased real-world setting. In this educational review of automated vessel occlusion software, we discuss emerging evidence of their utility, underlying algorithms, real-world diagnostic performance, and limitations. The intended audience includes specialists in stroke care in neurology, emergency medicine, radiology, and neurosurgery. Practical tips for onboarding and utilization of this technology are provided based on the multidisciplinary experience of the authorship team.
Source: Stroke
DOI: 10.1161/strokeaha.124.049555
Authors: Yasmin N. Aziz, Aakanksha Sriwastwa, Kambiz Nael, Pablo Harker, Eva A. Mistry, Pooja Khatri, Arindam R. Chatterjee, Jeremy J. Heit, Ashutosh Jadhav, Vivek Yedavalli, Achala S. Vagal
Institutions: University of Cincinnati, University of California, San Francisco, Washington University in St. Louis, Stanford Medicine, Stanford University, Barrow Neurological Institute, Johns Hopkins University, Johns Hopkins Medicine
Language: English
Subfield: Epidemiology
Field: Medicine
Open Access status: green
OpenAlex ID: W4411157437
FWCI: 1.219
Cites: 37
Cited by: 2
Related to: 10