Coronary Computed Tomography Angiography Derived Fractional Flow Reserve and Plaque Stress
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Fractional flow reserve (FFR) measured during invasive coronary angiography is an independent prognosticator in patients with coronary artery disease and the gold standard for decision making in coronary revascularization. The integration of computational fluid dynamics and quantitative anatomic and physiologic modeling now enables simulation of patient-specific hemodynamic parameters including blood velocity, pressure, pressure gradients, and FFR from standard acquired coronary computed tomography (CT) datasets. In this review article, we describe the potential impact on clinical practice and the science behind noninvasive coronary computed tomography (CT) angiography derived fractional flow reserve (FFRCT) as well as future applications of this technology in treatment planning and quantifying forces on atherosclerotic plaques.
KeywordsAtherosclerosis Axial plaque stress Computational fluid dynamics Coronary artery disease Coronary computed tomography angiography Coronary plaque Fractional flow reserve Invasive coronary angiography Myocardial ischemia Noninvasive cardiac imaging Noninvasive diagnostic testing Prognosis Wall shear stress
Axial plaque stress
Coronary artery disease
Computed tomography angiography
Computed tomography perfusion
Fractional flow reserve
Fractional flow reserve derived from coronary computed tomography angiography
Invasive coronary angiography
Negative predictive value
Positive predictive value
Wall shear stress
Coronary computed tomography angiography (CTA) is well established as the noninvasive standard for anatomic assessment of coronary artery disease (CAD) [1, 2]. With improvements in spatial and temporal resolution, both mechanical and software-based, as well as implementation of large detector scanners the field of coronary CTA has seen progressive improvements over the last 10 years [3, 4, 5]. In addition to image quality improvements, multiple scanner advances in both image acquisition and reconstruction have enabled coronary CTA to be performed consistently with radiation dose exposure in the 1–5 mSv range [6, 7, 8]. Despite the rapid technology progression, resting coronary CTA remains a strictly anatomic test and, as such, similar to conventional invasive angiography (ICA), it lacks the necessary data to guide revascularization decision making, which mandates objective evidence of ischemia [9, 10]. Accordingly, the recent “Outcomes of Anatomic vs Functional testing for Coronary Artery Disease” (PROMISE) trial, compared coronary CTA with frontline noninvasive ischemia testing and demonstrated an almost 50 % increase in downstream referrals to ICA and a doubling in coronary revascularization rate which, however, did not translate into improved outcomes [11••]. These findings emphasize the need of accurate noninvasive gatekeeping to the catheterization laboratory beyond anatomic assessment. The latter gap in noninvasive diagnostic testing may be addressed through a strategy combining anatomic and functional data . The introduction of pharmacologic stress CT perfusion has resulted in significant interest with strong early results compared with both noninvasive and invasive measures of ischemia [4, 13]. Although a promising technique, CT perfusion requires the administration of a pharmacologic stress agent and a repeat CT acquisition, thereby increasing both the time required and the radiation exposure to the patient. Furthermore, CT perfusion provides data analogous to coronary flow reserve, which has known limitations in isolating epicardial coronary disease that is treatable with revascularization from microvascular disease without any established therapy. Fractional flow reserve (FFR) as measured during ICA is broadly recognized as the gold standard for the discrimination of lesion-specific ischemia. FFR, which assesses the ratio of flow across a stenosis to putative flow in the absence of stenosis, is strongly associated to the clinical outcome in a continuous manner [14••]. Moreover, FFR has been shown in multiple randomized trials to guide revascularization in a cost-effective manner compared with both angiographic-guided revascularization and medical therapy [15, 16, 17]. Although a robust tool for the adjudication of the hemodynamic significance of a stenosis, FFR is limited by its invasiveness and cost, and hence in real-world practice it is used for coronary revascularization decision-making in a minority of patients [18, 19]. With recent technological and scientific advancements, noninvasive methods to calculate FFR have been developed. The integration of computational fluid dynamics and quantitative anatomic and physiologic modeling now enables simulation of patient-specific hemodynamic parameters including blood velocity, pressure, pressure gradients, and FFR from standard acquired coronary CT datasets [20••]. We herein describe the science behind, clinical evidence supporting, and future applications related to coronary CTA derived FFR (FFRCT).
Coronary CT Angiography Derived FFR (FFRCT)
Science and Diagnostic Performance
FFR can be derived from coronary CTA image data acquired using standard acquisition protocols without the need for additional imaging, medication, or radiation. FFRCT analysis uses mathematical models of blood flow derived from patient-specific data extracted from coronary CTA images and solved on high-performance computers. Any mathematical model of blood flow in the circulation includes at least 3 elements: first, a description of the anatomic region of interest; second, the mathematical “governing equations” enumerating the physical laws of blood flow within the region of interest; and third, “boundary conditions” to define physiologic relationships between variables at the boundaries of the region of interest . Although the anatomic region of interest and the boundary conditions are unique to each patient and the specific vascular territory, the governing equations describing velocity and pressure are universal and apply in different patients and other arterial beds. The extraction of the patient-specific anatomic model from image data is performed using image processing algorithms [22, 23]. The basic physiologic principles behind FFRCT have previously been described in detail [20••]. The first principle is that the total coronary blood flow (which is proportional to the myocardial oxygen demand) at rest can be quantified from the myocardial mass as assessed by CT. The second principle is that the microcirculatory vascular resistance at rest is inversely proportional to the size of the coronary arteries supplying the myocardium, and thus the caliber of both healthy and diseased vessels adapt to the amount of flow they carry. The third principle states that the vasodilatory response of the coronary microcirculation to adenosine infusion is predictable, allowing computational modeling of the maximal hyperemic state. Integration of these patient-specific mathematical models of coronary physiology to 3D computational fluid models enable computation of coronary flow and pressure at each point in the coronary tree under hyperemic conditions. Finally, FFRCT is calculated from the ratio of coronary pressure to aortic pressure under simulated maximal hyperemic conditions.
Diagnostic performance of FFRCT
Study name [ref]
N Patients / vessels
FFRct Diagnostic performance
Sens/spec (95 % CI)
PPV/NPV (95 % CI)
AUC (95 % CI)
Sens/spec (95 % CI)
PPV/NPV (95 % CI)
AUC (95 % CI)
103 / 159
First FFRCT analysis software (v1.0). 4 centers. Patients with suspected or known CAD who underwent coronary CTA, ICA and FFR. Blinded coronary CTA and FFRCT core-lab analyses. FFR measured in all vessels.
93 (82–98)/ 82 (68–91)
85 (75–93) / 91 (78–98)
0.92 (95 % CI), NR
88 (77–95) / 82 (73–89)
74 (62–84) / 92 (85–97)
0.90 (95 % CI), NR
252 / 407
FFRCT analysis v1.2. 17 centers. Patients with suspected or known CAD who underwent clinically indicated ICA after coronary CTA (<60 days), and with at least one ICA stenosis 30-90 %. Blinded coronary CTA and FFRCT core-lab analyses. FFR measured in all vessels.
90 (84–95) / 54 (46–83)
67 (74–90) / 84 (74–90)
80 (73–86)/ 61 (54–67)
FFRct analysis v1.4. 10 centers. Patients suspected of CAD who underwent coronary CTA and ICA within <60 days. FFR measured in 97 % of all vessels. Site-read coronary CTA. Blinded FFRCT and FFR core-lab analyses
86 (77–92) / 79 (72–84)
65 (56–74) / 93 (87–96)
84 (75–89)/ 86 (82–89)
61 (53–69) / 95 (53–69)
FFRCT Diagnostic Performance in Specific Subpopulations
FFRCT has high diagnostic performance in the presence of coronary calcification (Fig. 1) . In a NXT trial substudy including 214 patients (333 vessels), there was no difference in diagnostic accuracy, sensitivity, or specificity of FFRCT across Agatston score quartiles, including the highest quartile of patients with Agatston scores ranging between 416 and 3599 . In vessels with the highest Agatston scores, FFRCT showed significant improved discrimination of ischemia compared with coronary CTA alone (0.91 vs 0.71, P = 0.004), corresponding to 60 % correct reclassification of cases when moving from coronary CTA to FFRCT. The apparent robustness of FFRCT in the event of coronary calcification is most likely a result of the FFRCT computation process, including information on the global coronary and myocardial anatomy . In contrast, coronary CTA stenosis assessment relies on identification of segmental changes with resultant reduction in lumen interpretability and, for this reason, the presence of artifacts may have a greater impact on interpretation.
In a recent substudy from the NXT trial of vessels with serial multiple lesions (n = 18), FFRCT values were co-registered with measured FFR across the lesions, and trans-lesional differences between FFRCT and FFR were compared . The mean values of the most distal FFR and FFRCT in the same regions were 0.72 ± 0.10 and 0.69 ± 0.11, wheeas FFR and FFRCT were ≤0.80 in 13 and 14 vessels, respectively. The coefficient of correlation between trans-lesional delta FFR and FFRCT in each segment was excellent (0.92, P < 0.001).
The diagnostic performance of FFRCT has been studied only in patients suspected of stable CAD, and thus the generalizability of FFRCT to other patient categories is currently unknown. These patients include those with left ventricular hypertrophy, diabetes, previous myocardial infarction, or patients with coronary stents or by-pass grafts.
Comparison to Conventional Ischemia Testing Modalities
Current guidelines recommend noninvasive functional imaging testing (eg, stress echocardiography, single photon emission computed tomography, or cardiac magnetic resonance) as the first line diagnostic strategy in patients suspected of CAD . In meta-analyses, using ICA stenosis severity as the reference standard, noninvasive functional testing has shown high diagnostic performance for detection or exclusion of obstructive CAD . However, when these diagnostic tests are evaluated using measured FFR rather than ICA stenosis as the reference standard, diagnostic performance diminishes . Most published studies utilizing FFR as the reference standard were small and single center-based, and in many of these studies FFR was often not measured in all vessels, with FFR values assigned to vessels (and vascular perfusion territories) on the basis of the angiographic findings in a significant proportion of patients (vessels) . This strategy may lead to misadjudication since patients with stenosis severity >50 % or even >70 % often have FFR values >0.80 [9, 10, 36, 37, 38], whereas patients with <50 % stenosis may have FFR values ≤ 0.80 [36, 37, 38, 39]. Hitherto no studies have compared head-to-head the diagnostic performance of conventional noninvasive functional testing modalities vs FFRCT using FFR as the reference standard.
Clinical Utility, Cost Effectiveness, and Quality of Life
In the context of rising global healthcare costs, greater attention is focused on cost-effectiveness of procedures. The field of noninvasive diagnostic testing comprises a bewildering array of test choices often resulting in 2 separate tests for assessment of coronary anatomy and ischemia . Despite the extensive use of noninvasive testing, ICA continues to play a major role in the assessment of patients suspected of CAD. As a result of inaccurate diagnostic discrimination associated with the use of current noninvasive testing modalities, 60 % or more of patients referred for ICA on a suspicion of CAD do not have obstructive disease , and the majority of patients having revascularization performed do not have evidence of ischemia . Moreover, patients with a positive ischemia testing result are only slightly more likely to have obstructive CAD at ICA than those who do not undergo testing .
Resource utilization and clinical outcome related to the clinical use of FFRCT in symptomatic patients with suspected CAD have been evaluated in the prospective, multicenter “Prospective Longitudinal Trial of FFRCT: Outcome and Resource impacts” (PLATFORM) trial [43••]. This study examined the clinical effectiveness impact of a strategy using FFRCT to guide management compared with the usual testing strategy in 11 European centers. A total of 584 patients (mean age 61 years, 40 % women) with new-onset chest pain, no prior history of CAD, and an intermediate pre-test likelihood of obstructive CAD were enrolled. Patients referred for noninvasive testing were enrolled in a separate stratum than patients referred for invasive testing. Each stratum was further subdivided into usual care or FFRCT-guided care. The primary endpoint was the rate of finding no obstructive stenosis among those with planned ICA, as defined by ≥50 % in any coronary artery by quantitative coronary angiography (QCA, core laboratory measurement) or invasive FFR < 0.80. Secondary endpoints included clinical outcomes, downstream testing and treatment, resource utilization, and quality of life measures [43••]. Study results showed high rates of finding no obstructive CAD by ICA in both the planned noninvasive and planned ICA groups. In the planned ICA group, 73 % of usual care patients had no obstructive CAD compared with only 12 % of patients guided by FFRCT, an 83 % reduction (P < 0.0001). Although clinicians in the PLATFORM study were not protocol-driven to utilize FFRCT test results, in 61 % of patients with planned ICA, the angiogram was cancelled after receiving FFRCT results. Nonetheless, there was no difference in coronary revascularization rates (32 % in usual care and 29 % in FFRCT, P = ns) and there was a 90 % increase in the number of patients with both functional and anatomic information prior to revascularization. Among patients intended for noninvasive testing, there was no difference in the rate of finding no obstructive CAD at ICA between usual care (6 %) and FFRCT (13 %, P = 0.95). There were no adverse clinical events among patients in whom ICA was cancelled on the basis of FFRCT, and there was no difference in clinical outcome between the usual care and FFRCT-guided groups at 90 days. The latter findings are in accordance with a recent single-center real-world study comprising 185 consecutive patients with stable CAD and intermediate range coronary lesions showing a favorable 12-month follow-up clinical outcome in patients with FFRCT > 0.80 (69 % of the study cohort) being deferred from ICA [44•].
Simulation analyses based on historic data indicate that FFRCT guidance for selection of ICA and decision-making on coronary revascularization may reduce costs in stable CAD [45, 46]. The effects of using FFRCT instead of usual care on costs and quality of life (QOL) in the PLATFORM study have been recently published [47••]. Total medical costs were derived from the number of diagnostic tests, invasive procedures, hospitalizations, and medications during 90-day follow-up multiplied by summed US cost weights. Changes in QOL were assessed using the Seattle Angina Questionnaire, the EuroQOL, and a visual analog scale. Among patients with planned ICA, mean costs were 32 % lower among the FFRCT group than among the usual care group ($7343 vs $10,734, P < 0.0001). Among patients with planned noninvasive testing, mean costs were not significantly different between the FFRCT group and the usual care group ($2679 vs $2137, P = 0.26). Each of the QOL scores improved in the overall study population (P < 0.0001). At 90 days, in the planned noninvasive testing stratum, QOL scores were significantly higher in FFRCT patients than in usual care patients, whereas in the planned ICA stratum the improvements in QOL were similar in the FFRCT and usual care patients.
FFRCT Testing and Interpretation in Clinical Practice
Potential FFRCT interpretation approach
Downstream diagnostic work-up
No additional testing, OMTb
Ambulatory follow-up, OMTb
Limitations of FFRCT Testing
Although no special imaging protocols are required for FFRCT assessment, significant CT imaging artifacts such as motion, low contrast, or blooming from coronary calcification may impair the diagnostic performance of coronary CTA and thus of FFRCT. In the DeFACTO and NXT trials, 11 % and 13 % of the patients had nonevaluable coronary CTA images [25••, 26••]. In contrast, in the aforementioned real-world report of consecutive patients having FFRCT performed, only 2 % of the patients failed to meet the image quality requirements for FFRCT analysis, and in the total cohort comprising more than 1200 patients referred for coronary CTA, a conclusive CT-based anatomic or anatomic-physiological result was available in >90 % [44•]. Issues of CT uninterpretability can be minimized by adhering to coronary CTA image acquisition guidelines, particularly by administration of heart-rate lowering medication and sublingual nitrates before image acquisition [27•, 28, 44•, 50]. Although it has been shown that FFRCT seems to provide significant diagnostic improvement compared with coronary CTA even at lower levels of coronary CTA image quality , noncompliance with societal guidelines on best coronary CTA acquisition practice  is associated with impaired FFRCT diagnostic performance [27•]. In the DeFACTO trial, administration of a pre-scan beta-blocker increased FFRCT diagnostic specificity from 51 % to 66 % (P = 0.03), whereas nitroglycerin pretreatment within 30 minutes of CT was associated with improved specificity from 54 % to 75 % (P = 0.01).
Currently, FFRCT testing requires offsite computer processing requiring 2–6 hours. However, significantly faster FFRCT-testing processing times resulting from software improvements are expected in the near future. Concerns on the perceived loss of control of local assessment and the current processing time associated with FFRCT testing have driven renewed interest in past generations of reduced order computational fluid modeling versions that are less computationally intense and when coupled with less comprehensive anatomic modeling enables on-site analysis with reduced analysis times, but an unknown impact on diagnostic performance. Thus, while noninvasive on-site and fast (<1 hour) CT-derived FFR has shown interesting results in small, single-center, retrospective studies [52, 53], further investigations in prospective multicenter trials are needed in order to determine the actual diagnostic performance of this technique . The relative long-term prognosis and cost-efficiency of FFRCT testing compared with conventional ischemia testing modalities is not known, but studies are ongoing. In the Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia (CREDENCE) trial (ClinicalTrials.gov Identifier:NCT02173275), which is a prospective, multicenter, cross-sectional study of patients scheduled to undergo clinically indicated nonemergent ICA, the diagnostic performance of FFRCT vs myocardial imaging perfusion assessment (SPECT, positron emission tomography and magnetic resonance myocardial imaging) is compared using FFR as the reference standard.
Future Applications of Coronary CTA Derived Computational Fluid Dynamic Modeling
Predicting Outcomes of Cardiovascular Interventions
A particular strength of the computational methods used to derive FFRCT lies in the possibility of altering the patient anatomic or physiological model to predict the anticipated benefit of treatments. The potential use of this technology for planning PCI procedures was explored in a pilot study including 44 patients who had coronary CT and FFRCT before catheterization and measured FFR before and after PCI . FFRCT was performed in a blinded fashion prior to and after virtual stenting of the lesions treated invasively. The diagnostic accuracy of FFRCT to predict ischemia (FFR ≤ 0.8) after stenting was 96 %. Further developments in predicting the potential benefit of alternate revascularization strategies are on the horizon.
Quantifying Biomechanical Forces Acting on Blood Vessels
There are a variety of different biomechanical forces that act on blood vessels arising from internal pressure and flow and external tissue support. These applied forces result in stress acting on the surface or within blood vessels, where stress is defined as force per unit area. In addition to external applied forces, blood vessels have intrinsic, or residual, stresses emanating from growth and remodeling . These residual stresses are present even in the absence of external applied forces. An example of a residual stress manifests when a vessel is transected and retracts or shortens due to the longitudinal tension in the vessel wall. A detailed discussion of all of the intrinsic and extrinsic forces and stresses in blood vessels is beyond the scope of this review, and herein we focus on forces resulting from internal flow and pressure acting on blood vessels and atherosclerotic plaques. Wall shear stress (WSS) is defined as the tangential force per unit area acting on the luminal surface. Axial plaque stress (APS) is defined as the axial component of the hemodynamic stress acting on stenotic lesions [57•]. APS and WSS both result from hemodynamic forces acting on the luminal surface, but have important differences. APS is strongly related to the absolute pressure on the surface of the plaque, whereas WSS is independent of the absolute pressure but closely coupled to flow and the pressure-gradient. APS is much larger than WSS (ie, approximately 40 times larger than the maximum WSS even in tight stenoses and under hyperemic conditions where WSS is maximal [57•]). Both WSS and APS can be derived from the velocity and pressure fields calculated by patient-specific modeling of coronary blood flow derived from CT data. Image-based computational methods have been used to compute wall shear stress noninvasively in the human abdominal aorta [58, 59], the extracranial and intracranial cerebral arteries [60, 61, 62, 63], and the pulmonary arteries [64, 65].
Plaque Initiation and Progression
WSS plays a role in maintaining endothelial function and is likely to influence plaque initiation and progression [66, 67, 68, 69]. WSS is the product of the blood viscosity and the gradient of the velocity field at the luminal surface. WSS is sensed by the endothelium and in turn influences normal endothelial function, as well as atherosclerosis localization and progression. Image-based modeling techniques have also been used to evaluate wall shear stress in the human coronary arteries based on invasive data [70, 71, 72, 73, 74], and to a lesser extent using noninvasive data [75, 76]. The future application of image-based modeling derived from CT data holds great promise for understanding the relationship between WSS and CAD.
Plaque Evolution, Destabilization, and Rupture
FFRCT is a novel noninvasive method that uses computational fluid dynamics for calculation of FFR by using patient-specific modeling derived from standard acquired coronary CTA datasets. During the last 5 years, FFRCT has undergone remarkable advancements in technology, and its support in the clinical community challenging conventional coronary CTA and ischemia testing. Moreover, the clinical potential of combining computational fluid dynamics with CT to derive informantion that may enable prediction of the outcomes of coronary interventions or assessment of plaque vulnerability is emerging.
Compliance with Ethical Standards
Conflicts of Interest
Bjarne Linde Nørgaard has received institutional research support from Edwards Lifesciences, Siemens and HeartFlow. Jonathon Leipsic has received speaker’s honorarium from GE, and is consultant to and has received institutional research support from HeartFlow. Bon-Kwon Koo has received institutional research support from St. Jude and HeartFlow. Christopher K. Zarins and Charles A. Taylor are co-founders, employees and shareholders of HeartFlow, Inc., which provides the FFRCT service. Jesper Møller Jensen has received speaker’s honorarium from Bracco Imaging. Niels Peter Sand declares that he has no conflicts of interest.
Human and Animal Rights and Informed Consent
This article does not contain any animal or human studies that would need informed consent.
Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
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