Use of AI in Cardiac CT and MRI: A Scientific Statement from the ESCR, EuSoMII, NASCI, SCCT, SCMR, SIIM, and RSNA

Domenico Mastrodicasa¹, Marly van Assen¹, Merel Huisman¹+7

• ¹From the Department of Radiology, University of Washington, UW Medical Center-Montlake, Seattle, Wash (D.M.); Department of Radiology, OncoRad/Tumor Imaging Metrics Core (TIMC), University of Washington, Seattle, Wash (D.M.); Department of Radiology and Imaging Sciences, Emory University, Atlanta, Ga (M.v.A.); Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (M.H.); Department of Radiology, Mayo Clinic, Rochester, Minn (T.L., E.E.W.); Departments of Cardiology and Radiology, Royal Brompton Hospital, London, United Kingdom (E.D.N.); School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom (E.D.N.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (B.D.A.); Department of Radiology, University of Cagliari, Cagliari, Italy (L.S.); Department of Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1 Postbus 30 001, 9700 RB Groningen, the Netherlands (R.V.); Department of Medical Imaging, University Medical Imaging Toronto, University of Toronto, Toronto, Ontario, Canada (K.H.); and Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.H.).