Impact of machine-learning-based coronary computed tomography angiography–derived fractional flow reserve on decision-making in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement

被引:0
作者
Verena Brandt
U. Joseph Schoepf
Gilberto J. Aquino
Raffi Bekeredjian
Akos Varga-Szemes
Tilman Emrich
Richard R. Bayer
Florian Schwarz
Thomas J. Kroencke
Christian Tesche
Josua A. Decker
机构
[1] Medical University of South Carolina,Division of Cardiovascular Imaging, Department of Radiology and Radiological Science
[2] Robert-Bosch-Hospital,Department of Cardiology and Angiology
[3] University Medical Center Mainz,Department of Diagnostic and Interventional Radiology
[4] German Center for Cardiovascular Research (DZHK),Department of Diagnostic and Interventional Radiology
[5] Partner Site Rhine-Main,Department of Cardiology
[6] University Hospital Augsburg,Department of Cardiology, Munich University Clinic
[7] Clinic Augustinum Munich,undefined
[8] Ludwig-Maximilians-University,undefined
来源
European Radiology | 2022年 / 32卷
关键词
Multidetector computed tomography; Coronary artery disease; Angiography; Transcatheter aortic valve replacement; Fractional flow reserve;
D O I
暂无
中图分类号
学科分类号
摘要
引用
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页码:6008 / 6016
页数:8
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