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Roadmap on the use of artificial intelligence for imaging of vulnerable atherosclerotic plaque in coronary arteries.
Föllmer, Bernhard; Williams, Michelle C; Dey, Damini; Arbab-Zadeh, Armin; Maurovich-Horvat, Pál; Volleberg, Rick H J A; Rueckert, Daniel; Schnabel, Julia A; Newby, David E; Dweck, Marc R; Guagliumi, Giulio; Falk, Volkmar; Vázquez Mézquita, Aldo J; Biavati, Federico; Isgum, Ivana; Dewey, Marc.
Afiliación
  • Föllmer B; Department of Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany. bernhard.foellmer@charite.de.
  • Williams MC; Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
  • Dey D; Biomedical Imaging Research Institute and Department of Imaging, Medicine and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Arbab-Zadeh A; Division of Cardiology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Maurovich-Horvat P; Department of Radiology, Medical Imaging Center, Semmelweis University, Budapest, Hungary.
  • Volleberg RHJA; Department of Cardiology, Radboud University Medical Center, Nijmegen, Netherlands.
  • Rueckert D; Artificial Intelligence in Medicine and Healthcare, Technical University of Munich, Munich, Germany.
  • Schnabel JA; Department of Computing, Imperial College London, London, UK.
  • Newby DE; School of Biomedical Imaging and Imaging Sciences, King's College London, London, UK.
  • Dweck MR; Institute of Machine Learning in Biomedical Imaging, Helmholtz Munich, Neuherberg, Germany.
  • Guagliumi G; School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.
  • Falk V; Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
  • Vázquez Mézquita AJ; Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
  • Biavati F; Division of Cardiology, IRCCS Galeazzi Sant'Ambrogio Hospital, Milan, Italy.
  • Isgum I; Department of Cardiothoracic and Vascular Surgery, Deutsches Herzzentrum der Charité, Charité Universitätsmedizin, Berlin, Germany.
  • Dewey M; Department of Health Science and Technology, ETH Zurich, Zurich, Switzerland.
Nat Rev Cardiol ; 21(1): 51-64, 2024 01.
Article en En | MEDLINE | ID: mdl-37464183
ABSTRACT
Artificial intelligence (AI) is likely to revolutionize the way medical images are analysed and has the potential to improve the identification and analysis of vulnerable or high-risk atherosclerotic plaques in coronary arteries, leading to advances in the treatment of coronary artery disease. However, coronary plaque analysis is challenging owing to cardiac and respiratory motion, as well as the small size of cardiovascular structures. Moreover, the analysis of coronary imaging data is time-consuming, can be performed only by clinicians with dedicated cardiovascular imaging training, and is subject to considerable interreader and intrareader variability. AI has the potential to improve the assessment of images of vulnerable plaque in coronary arteries, but requires robust development, testing and validation. Combining human expertise with AI might facilitate the reliable and valid interpretation of images obtained using CT, MRI, PET, intravascular ultrasonography and optical coherence tomography. In this Roadmap, we review existing evidence on the application of AI to the imaging of vulnerable plaque in coronary arteries and provide consensus recommendations developed by an interdisciplinary group of experts on AI and non-invasive and invasive coronary imaging. We also outline future requirements of AI technology to address bias, uncertainty, explainability and generalizability, which are all essential for the acceptance of AI and its clinical utility in handling the anticipated growing volume of coronary imaging procedures.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedad de la Arteria Coronaria / Placa Aterosclerótica Tipo de estudio: Guideline Límite: Humans Idioma: En Revista: Nat Rev Cardiol Asunto de la revista: CARDIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedad de la Arteria Coronaria / Placa Aterosclerótica Tipo de estudio: Guideline Límite: Humans Idioma: En Revista: Nat Rev Cardiol Asunto de la revista: CARDIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Alemania