Performance of an artificial intelligence tool for multi-step acute stroke imaging: A multicenter diagnostic study.

Thibault Agripnidis¹, Angela Ayobi², Sarah Quenet², Yasmina Chaibi², Christophe Avare², Alexis Jacquier¹, Nadine Girard^1,3, Jean-François Hak^1,4, Anthony Reyre¹, Gilles Brun¹, Ahmed-Ali El Ahmadi⁵

¹APHM, Service de Neuroradiologie Diagnostique et Interventionnelle, Hôpital de la Timone, Marseille 13005, France.

²Avicenna.AI, 375 Avenue du Mistral, La Ciotat, France.

³Institut de Neurosciences de la Timone, UMR 7289, CNRS, Aix-Marseille Université, Marseille 13005, France.

⁴CERIMED (Centre Européen de Recherche en Imagerie Médicale) - Laboratoire d'Imagerie Interventionnelle Expérimentale ( LiiE) - EA4264, Aix-Marseille Université, Marseille 13005, France.

⁵Service d'Imagerie Médicale, Hôpital Nord, Assistance Publique - Hôpitaux de Marseille, Chemin des Bourrely, Marseille 13015, France.

PubMed PMC DOI PDF

Abstract

OBJECTIVE: Several artificial intelligence (AI) tools have been developed to assist in the stroke imaging workflow, which remains a major disease of the 21st century. This study evaluated the combined performance of an FDA-cleared and CE-marked AI-based device with three modules designed to detect intracerebral hemorrhage (ICH), identify large vessel occlusion (LVO), and calculate Alberta Stroke P…

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