Coronary CT Angiography-derived Fractional Flow Reserve.

Abstract:

: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.

journal_name

Radiology

journal_title

Radiology

authors

Tesche C,De Cecco CN,Albrecht MH,Duguay TM,Bayer RR 2nd,Litwin SE,Steinberg DH,Schoepf UJ

doi

10.1148/radiol.2017162641

subject

Has Abstract

pub_date

2017-10-01 00:00:00

pages

17-33

issue

1

eissn

0033-8419

issn

1527-1315

journal_volume

285

pub_type

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