Deep learning analysis of left ventricular myocardium in CT angiographic intermediate-degree coronary stenosis improves the diagnostic accuracy for identification of functionally significant stenosis-Reference-Cited by-同舟云学术

Deep learning analysis of left ventricular myocardium in CT angiographic intermediate-degree coronary stenosis improves the diagnostic accuracy for identification of functionally significant stenosis

Published:2018-11-12 Issue:5 Volume:29 Page:2350-2359
ISSN:0938-7994
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

van Hamersvelt Robbert W.^ORCID,Zreik Majd,Voskuil Michiel,Viergever Max A.,Išgum Ivana,Leiner Tim

Funder

ZonMw

Philips Healthcare

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

http://link.springer.com/content/pdf/10.1007/s00330-018-5822-3.pdf

Reference29 articles.

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2. Meijboom WB, Van Mieghem CA, van Pelt N et al (2008) Comprehensive assessment of coronary artery stenoses: computed tomography coronary angiography versus conventional coronary angiography and correlation with fractional flow reserve in patients with stable angina. J Am Coll Cardiol 52:636–643. https://doi.org/10.1016/j.jacc.2008.05.024

3. Ko BS, Wong DT, Cameron JD et al (2014) 320-row CT coronary angiography predicts freedom from revascularisation and acts as a gatekeeper to defer invasive angiography in stable coronary artery disease: a fractional flow reserve-correlated study. Eur Radiol 24:738–747. https://doi.org/10.1007/s00330-013-3059-8

4. Tonino PA, De Bruyne B, Pijls NH et al (2009) Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med 360:213–224. https://doi.org/10.1056/NEJMoa0807611

5. Tesche C, De Cecco CN, Albrecht MH et al (2017) Coronary CT angiography–derived fractional flow reserve. Radiology 285:17–33. https://doi.org/10.1148/radiol.2017162641

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