Computational Fluid Dynamics Applied to Cardiac Computed Tomography for Noninvasive Quantification of Fractional Flow Reserve

Abstract

Coronary computed tomography angiography (CTA) has emerged as a noninvasive method for direct visualization of coronary artery disease, with previous studies demonstrating high diagnostic performance of CTA compared with invasive coronary angiography. However, CTA assessment of coronary stenoses tends toward overestimation, and even among CTA-identified severe stenosis confirmed at the time of invasive coronary angiography, only a minority are found to be ischemia causing. Recent advances in computational fluid dynamics and image-based modeling now permit determination of rest and hyperemic coronary flow and pressure from CTA scans, without the need for additional imaging, modification of acquisition protocols, or administration of medications. These techniques have been used to noninvasively compute fractional flow reserve (FFR), which is the ratio of maximal coronary blood flow through a stenotic artery to the blood flow in the hypothetical case that the artery was normal, using CTA images. In the recently reported prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study and the DeFACTO (Determination of Fractional Flow Reserve by Anatomic Computed Tomographic Angiography) trial, FFR derived from CTA was demonstrated as superior to measures of CTA stenosis severity for determination of lesion-specific ischemia. Given the significant interest in this novel method for determining the physiological significance of coronary artery disease, we herein present a review on the scientific principles that underlie this technology.

Myocardial Perfusion Imaging Versus Computed Tomography Angiography–Derived Fractional Flow Reserve Testing in Stable Patients With Intermediate‐Range Coronary Lesions: Influence on Downstream Diagnostic Workflows and Invasive Angiography Findings

“…Recent advances in individual image‐based modeling and computational fluid dynamics allow for estimation of coronary blood flow and pressure from coronary CTA images 3. Based on these techniques, noninvasive fractional flow reserve (FFR) can be computed 3, 4, 5, 6.…”

“…Based on these techniques, noninvasive fractional flow reserve (FFR) can be computed 3, 4, 5, 6. In studies including patients with known or suspected stable CAD and blinded comparison to FFR, coronary CTA‐derived FFR (FFR CT ) has shown high diagnostic performance 4, 5, 6.…”

Diagnostic accuracy and discrimination of ischemia by fractional flow reserve CT using a clinical use rule: Results from the Determination of Fractional Flow Reserve by Anatomic Computed Tomographic Angiography study

“…Importantly, these issues are accounted for in FFR CT modeling through the anatomic model of the coronary arteries and the segmentation of the left ventricular myocardial mass. 29 Although there is evidence that the pathophysiology of CAD and angina in men and women may be different, 30 these issues remain the focus of much investigation; the relevance of lesion-specific ischemia by invasive FFR to help guide revascularization decisions is, however, well solidified. In fact, FFR-guided revascularization has recently received class 1A guideline support, 31 and therefore, a noninvasive test that accurately provides anatomy and lesion-specific ischemia would be of significant clinical value.…”

CT Determination of Fractional Flow Reserve in Coronary Lesions

“…The second one is an on-site workstation by Siemens (Forchheim, Germany), which provides 1D anatomical and functional analysis. 22 The calculation for FFRCT requires: (A) a patient-specific anatomic model of the coronary artery system, obtained and processed (with segmentation algorithms, luminal boundary extraction of the main and side branches, identifying and analyzing coronary plaques in every artery, followed by generation of a geometric modeling mash fitted to the segmented data) from the recorded CCTA images; 23,24 (B) a physiological model of the coronary blood flow, which requires the CCTA determination of the myocardial wall volume, the coronary resistance of each vessel (which is inversely proportional to the dimension of the artery), the pressure in the aorta (approximated from the average brachial artery pressure), and simulation of a maximum hyperemic state, when the resting microcirculation resistance is reduced; (C) a numerical equation to analyze the laws that govern fluid dynamics. These computations can be done by modeling fluid dynamics using the NavierStokes equations.…”