3 years ago

Coronary CT Angiography-derived Fractional Flow Reserve.

Invasive coronary angiography (ICA) with measurement of fractional flow reserve (FFR) by means of a pressure wire technique is the established reference standard for the functional assessment of coronary artery disease (CAD) ( 1 , 2 ). Coronary computed tomographic (CT) angiography has emerged as a noninvasive method for direct assessment of CAD and plaque characterization with high diagnostic accuracy compared with ICA ( 3 , 4 ). However, the solely anatomic assessment provided with both coronary CT angiography and ICA has poor discriminatory power for ischemia-inducing lesions. FFR derived from standard coronary CT angiography (FFRCT) data sets by using any of several advanced computational analytic approaches enables combined anatomic and hemodynamic assessment of a coronary lesion by a single noninvasive test. Current technical approaches to the calculation of FFRCT include algorithms based on full- and reduced-order computational fluid dynamic modeling, as well as artificial intelligence deep machine learning ( 5 , 6 ). A growing body of evidence has validated the diagnostic accuracy of FFRCT techniques compared with invasive FFR. Improved therapeutic guidance has been demonstrated, showing the potential of FFRCT to streamline and rationalize the care of patients suspected of having CAD and improve outcomes while reducing overall health care costs ( 7 , 8 ). The purpose of this review is to describe the scientific principles, clinical validation, and implementation of various FFRCT approaches, their precursors, and related imaging tests. (©) RSNA, 2017.

Publisher URL: http://doi.org/10.1148/radiol.2017162641

DOI: 10.1148/radiol.2017162641

You might also like
Never Miss Important Research

Researcher is an app designed by academics, for academics. Create a personalised feed in two minutes.
Choose from over 15,000 academics journals covering ten research areas then let Researcher deliver you papers tailored to your interests each day.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.