Value of Machine Learning-based Coronary CT Fractional Flow Reserve Applied to Triple-Rule-Out CT Angiography in Acute Chest Pain.
Simon S MartinDomenico MastrodicasaMarly van AssenCarlo N De CeccoRichard R BayerChristian TescheAkos Varga-SzemesAndreas M FischerBrian E JacobsPooyan SahbaeeL Parkwood GriffithAndrew J MatuskowitzThomas Joseph VoglJoseph Uwe SchoepfPublished in: Radiology. Cardiothoracic imaging (2020)
CT FFR derived from triple-rule-out CT angiography was a better predictor for coronary revascularization and MACE and showed better agreement with additional diagnostic testing than triple-rule-out CT angiography. Therefore, CT FFR may improve the specificity in identifying patients with ACP with significant CAD in the ED setting and reduce unnecessary downstream testing.© RSNA, 2020See also the commentary by Ihdayhid and Ben Zekry in this issue.
Keyphrases
- coronary artery disease
- image quality
- dual energy
- computed tomography
- machine learning
- contrast enhanced
- coronary artery
- positron emission tomography
- emergency department
- percutaneous coronary intervention
- magnetic resonance imaging
- liver failure
- respiratory failure
- artificial intelligence
- magnetic resonance
- intensive care unit
- transcatheter aortic valve replacement
- hepatitis b virus
- drug induced
- left ventricular
- aortic valve
- extracorporeal membrane oxygenation