Impact of machine-learning CT-derived fractional flow reserve for the diagnosis and management of coronary artery disease in the randomized CRESCENT trials.

Journal: European radiology
Published Date:

Abstract

OBJECTIVE: To determine the potential impact of on-site CT-derived fractional flow reserve (CT-FFR) on the diagnostic efficiency and effectiveness of coronary CT angiography (CCTA) in patients with obstructive coronary artery disease (CAD) on CCTA.

Authors

  • Fay M A Nous
    Department of Radiology & Nuclear Medicine, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
  • Ricardo P J Budde
    Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands.
  • Marisa M Lubbers
    Department of Radiology & Nuclear Medicine, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
  • Yuzo Yamasaki
    Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi Ward, Fukuoka, 812-8582, Japan.
  • Isabella Kardys
    Department of Radiology & Nuclear Medicine, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
  • Tobias A Bruning
    Department of Cardiology, Maasstad Ziekenhuis, Maasstadweg 21, 3079 DZ, Rotterdam, The Netherlands.
  • Jurgen M Akkerhuis
    Department of Cardiology, Sint Franciscus Gasthuis, Kleiweg 500, 3045 PM, Rotterdam, The Netherlands.
  • Marcel J M Kofflard
    Department of Cardiology, Albert Schweitzer Ziekenhuis, Albert Schweitzerplaats 25, 3318 AT, Dordrecht, The Netherlands.
  • Bas Kietselaer
    Department of Cardiology, Zuyderland Medical Center, H. Dunantstraat 5, 6419 PC, Heerlen, The Netherlands.
  • Tjebbe W Galema
    Department of Radiology & Nuclear Medicine, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
  • Koen Nieman
    Department of Cardiology (A.C., M.L.L., J.D., K.N.).