AI-enabled opportunistic measurement of liver steatosis in coronary artery calcium scans predicts cardiovascular events and all-cause mortality: an AI-CVD study within the Multi-Ethnic Study of Atherosclerosis (MESA).

Journal: BMJ open diabetes research & care
PMID:

Abstract

INTRODUCTION: About one-third of adults in the USA have some grade of hepatic steatosis. Coronary artery calcium (CAC) scans contain more information than currently reported. We previously reported new artificial intelligence (AI) algorithms applied to CAC scans for opportunistic measurement of bone mineral density, cardiac chamber volumes, left ventricular mass, and other imaging biomarkers collectively referred to as AI-cardiovascular disease (CVD). In this study, we investigate a new AI-CVD algorithm for opportunistic measurement of liver steatosis.

Authors

  • Morteza Naghavi
    2 Society for Heart Attack Prevention and Eradication Palo Alto CA.
  • Kyle Atlas
    HeartLung.AI, Houston, TX, USA.
  • Anthony Reeves
    Department of Computer Engineering, Cornell University, Ithaca, NY, USA.
  • Chenyu Zhang
    Academy of Clinical Medicine, Guizhou Medical University, Guiyang 550004, China.
  • Jakob Wasserthal
    Clinic of Radiology and Nuclear Medicine, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland.
  • Thomas Atlas
    Tustin Teleradiology, Tustin, CA, USA.
  • Claudia I Henschke
    Department of Radiology, Icahn School of Medicine at Mount Sinai, New York.
  • David F Yankelevitz
    Department of Radiology, Icahn School of Medicine at Mount Sinai, New York.
  • Javier J Zulueta
    Clinica Universidad de Navarra, University of Navarra School of Medicine, Pamplona, Spain.
  • Matthew J Budoff
    Los Angeles Biomedical Research Institute at Harbor UCLA Medical Center, Torrance, CA, USA. mbudoff@labiomed.org.
  • Andrea D Branch
    Mount Sinai Medical Center, New York, New York, USA.
  • Ning Ma
    Key Laboratory of Preparation and Applications of Environmental Friendly Materials (Jilin Normal University), Ministry of Education, Changchun 130103, PR China.
  • Rowena Yip
    Department of Radiology, Icahn School of Medicine at Mount Sinai, New York.
  • Wenjun Fan
    University of California, Irvine, California, USA.
  • Sion K Roy
    The Lundquist Institute, Torrance, CA, USA.
  • Khurram Nasir
    Houston Methodist DeBakey Heart & Vascular Center, Houston, Texas, US.
  • Sabee Molloi
    University of California, Irvine, California, USA.
  • Zahi Fayad
    BioMedical Engineering and Imaging Institute and Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, New York (Z.F.).
  • Michael V McConnell
    Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California.
  • Ioannis Kakadiaris
    Department of Computer Science, University of Houston, Houston, Texas.
  • David J Maron
    Department of Medicine (Cardiovascular Medicine), Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, California, USA.
  • Jagat Narula
  • Kim Williams
    University of Louisville, Louisville, Kentucky, USA.
  • Prediman K Shah
    Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • George Abela
    Michigan State University, East Lansing, Michigan, USA.
  • Rozemarijn Vliegenthart
    University of Groningen, University Medical Center Groningen, Department of Radiology, Hanzeplein 1, 9713 GZ Groningen, The Netherlands.
  • Daniel Levy
    The Framingham Heart Study, Framingham, MA 01701, USA.
  • Nathan D Wong
    Department of Medicine, University of California at Irvine, CA (N.D.W.).