Design and optimization of an automatic deep learning-based cerebral reperfusion scoring (TICI) using thrombus localization.

Journal: Journal of neuroradiology = Journal de neuroradiologie
Published Date: Jun 26, 2025

Abstract

BACKGROUND: The Thrombolysis in Cerebral Infarction (TICI) scale is widely used to assess angiographic outcomes of mechanical thrombectomy despite significant variability. Our objective was to create and optimize an artificial intelligence (AI)-based classification model for digital subtraction angiography (DSA) TICI scoring.

Authors

  • Arthur Folcher
    Neuroradiology Department, Brest University Hospital, Brest, France. Electronic address: arthur.folcher@chu-brest.fr.
  • Jérémy Piters
    Neuroradiology Department, Brest University Hospital, Brest, France.
  • Daphné Wallach
    Research and Development Department, Intradys, Brest, France.
  • Gwenael Guillard
    Research and Development Department, Intradys, Brest, France.
  • Julien Ognard
    Neuroradiology, University Hospital of Brest, boulevard Tanguy-Prigent, 29609 Brest cedex, France; Laboratory of medical information processing - LaTIM, Inserm UMR 1101, CS 93837, Université de Bretagne Occidentale, 22, avenue Camille-Desmoulins, 29238 Brest cedex 3, France.
  • Jean-Christophe Gentric
    University of Brest, GETBO, INSERM UMR1304, Neuroradiology, University Hospital of Brest, Brest, France.

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