ORIGINAL RESEARCH ADULT BRAIN Evaluation of Artificial Intelligence–Powered Identification of Large-Vessel Occlusions in a Comprehensive Stroke Center A. Yahav-Dovrat, M. Saban, G. Merhav, I. Lankri, E. Abergel, A. Eran, D. Tanne, R.G. Nogueira, and R. Sivan-Hoffmann ABSTRACT BACKGROUND AND PURPOSE: Artiﬁcial intelligence algorithms have the potential to become an important diagnostic tool to opti- mize stroke workﬂow. Viz LVO is a medical product leveraging a convolutional neural network designed to detect large-vessel occlusions on CTA scans and notify the treatment team within minutes via a dedicated mobile application. We aimed to evaluate the detection accuracy of the Viz LVO in real clinical practice at a comprehensive stroke center. MATERIALS AND METHODS: Viz LVO was installed for this study in a comprehensive stroke center. All consecutive head and neck CTAs performed from January 2018 to March 2019 were scanned by the algorithm for detection of large-vessel occlusions. The system results were compared with the formal reports of senior neuroradiologists used as ground truth for the presence of a large-vessel occlusion. RESULTS: A total of 1167 CTAs were included in the study. Of these, 404 were stroke protocols. Seventy-ﬁve (6.4%) patients had a large-vessel occlusion as ground truth; 61 were detected
American Journal of Neuroradiology – American Journal of Neuroradiology
Published: Feb 1, 2021
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