Comparison of Machine Learning Computed Tomography-Based Fractional Flow Reserve and Coronary CT Angiography-Derived Plaque Characteristics with Invasive Resting Full-Cycle Ratio

Comparison of Machine Learning Computed Tomography-Based Fractional Flow Reserve and Coronary CT Angiography-Derived Plaque Characteristics with Invasive Resting Full-Cycle Ratio

Background: The aim is to compare the machine learning-based coronary-computed tomography fractional flow reserve (CT-FFR<sub>ML</sub>) and coronary-computed tomographic morphological plaque characteristics with the resting full-cycle ratio (RFR<sup>TM</sup>) as a novel invas...

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Bibliographic Details
Main Authors: Stefan Baumann, Markus Hirt, Christina Rott, Gökce H. Özdemir, Christian Tesche, Tobias Becher, Christel Weiss, Svetlana Hetjens, Ibrahim Akin, Stefan O. Schoenberg, Martin Borggrefe, Sonja Janssen, Daniel Overhoff, Dirk Lossnitzer
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Journal of Clinical Medicine
Subjects:
atherosclerosis
coronary artery disease
coronary ct angiography
fractional flow reserve derived from coronary computed tomography angiography
coronary physiology
invasive coronary angiography
myocardial infarction
resting full-cycle ratio
revascularization
Online Access:https://www.mdpi.com/2077-0383/9/3/714

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https://www.mdpi.com/2077-0383/9/3/714

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