CT Angiography (CTA) and Diagnostic Performance of Noninvasive Fractional Flow Reserve: Results From the Determination of Fractional Flow Reserve by Anatomic CTA (DeFACTO) Study
Abstract
OBJECTIVE. Fractional flow reserve (FFR) computed from standard coronary CT scans (FFRCT) is a novel noninvasive method for determining the functional significance of coronary artery lesions. Compared with CT alone, FFRCT significantly improves diagnostic accuracy and discrimination for patients with and without hemodynamically significant coronary artery stenoses. To date, the impact of CT image quality on diagnostic performance of FFRCT is unknown. We evaluated the impact of patient preparation, CT scan protocol, and factors related to image quality on the diagnostic accuracy of FFRCT.
SUBJECTS AND METHODS. We studied stable patients with suspected coronary artery disease (CAD), enrolled from 17 centers, who underwent CT, invasive coronary angiography, FFR, and FFRCT. The accuracy of CT and FFRCT for diagnosis of ischemia was compared against an invasive FFR reference standard. Anatomically obstructive CAD was defined by a stenosis value of at least 50 by CT or invasive coronary angiography, whereas ischemia was defined by an FFR or FFRCT of up to 0.80. Ischemia was assessed at the per-patient and per-vessel levels. Diagnostic performance of FFRCT was then evaluated in relation to patient preparation, including administration before CT of a β-blocker or nitroglycerin, as well as in relation to imaging characteristics, including misalignment, noise, motion, and coronary artery calcium.
RESULTS. Among 252 study participants, 137 (54.0%) had an abnormal FFR. Administration of a β-blocker increased FFRCT specificity (51.0% vs 66.0%; p = 0.03) with lower bias (–0.084 vs −0.048; p = 0.008), whereas nitroglycerin pretreatment within 30 minutes of CT was associated with improved specificity (54.0% vs 75.0%; p = 0.013). Misalignment artifacts resulted in impaired sensitivity (43.0% vs 86.0%; p = 0.001) with resultant reductions in overall accuracy (56.0% vs 71.0%; p = 0.03). No differences in diagnostic performance of FFRCT were noted in the presence of coronary motion or increasing coronary artery calcium score.
CONCLUSION. Use of β-blockade and nitroglycerin administration before CT improve diagnostic performance of FFRCT. Diagnostic accuracy of FFRCT is significantly reduced in the setting of misalignment artifacts.
Fractional flow reserve (FFR) computed from standard coronary CT scans (FFRCT) is a novel noninvasive method for determining the functional significance of coronary artery lesions. Although coronary CT angiography (CTA) alone can accurately detect obstructive coronary artery disease (CAD) when compared with invasive coronary angiography [1], coronary CTA cannot define the hemodynamic significance of CAD. This results in poor positive predictive value owing to an unreliable relationship between a simplistic measure of reduction in coronary artery diameter and ischemia [2, 3]. The diagnostic performance of FFRCT compared with coronary CTA alone using invasively measured FFR as the reference standard has recently been published [3]. The Determination of Fractional Flow Reserve by Anatomic CTA (DeFACTO) study showed improved diagnostic accuracy and improved discriminatory power of FFRCT as compared with coronary CTA alone for the diagnosis of lesion-specific ischemia in stable patients with CAD [3]. The DeFACTO study represented the first large-scale validation of the application of computational fluid dynamics for the derivation of FFR from a typically acquired coronary CTA. Importantly, the sensitivity and negative predictive value of FFRCT were high, suggesting a low rate of false-negative studies. The overall accuracy of FFRCT was, however, limited by more modest specificity.
Patient preparation for coronary CTA has long been emphasized in societal guidelines to help ensure image data optimization and achieve optimal diagnostic accuracy [4]. Beta-blockade and sublingual nitroglycerin administration are recommended [4, 5], because the use of both enhances image quality and diagnostic accuracy in coronary CTA [6, 7]. Moreover, these agents may also affect coronary motion (owing to inadequately controlled heart rates) and luminal diameter (from inadequate vasodilation of the coronary artery), both of which may influence the fluid dynamic models used to calculate FFRCT because it depends on accurate image input data to assign correct boundary conditions for physiologic computations. In addition to these medications, CT scan protocols may also affect coronary CTA image quality—with tube current and kilovoltage being the most commonly adjusted parameters—and that may have profound effects on image artifacts, including motion, misalignment artifact, and visualization of severe coronary artery calcifications.
The impact that adherence to best practices in coronary CTA has on the diagnostic performance of FFRCT has not yet been established.
In a substudy of the prospective multicenter international DeFACTO study, we thus sought to evaluate the influence of technical factors related to coronary CTA acquisition, patient preparation, and image artifacts on the diagnostic performance of FFRCT as compared with invasive coronary angiography.
Subjects and Methods
Study Design
The rationale and design of the DeFACTO study has been previously described [8]. Briefly, the De-FACTO study was designed to evaluate the accuracy of FFRCT to diagnose hemodynamically significant CAD, as defined by an invasive FFR reference standard, in patients with suspected native CAD who were referred for clinically indicated nonemergent invasive coronary angiography within 60 days of coronary CTA. All patients provided written informed consent. The per-patient and per-segment results of this study have recently been published [3].
Study Population
Enrolled patients were adults with suspected or known CAD who underwent clinically indicated invasive coronary angiography after coronary CTA with no intervening coronary event. Patients were not eligible if they met any of the following criteria: history of coronary artery bypass graft surgery; prior percutaneous coronary intervention with suspected in-stent restenosis; contraindication to administration of adenosine; suspicion of or recent acute coronary syndrome; complex congenital heart disease; prior pacemaker or defibrillator; prosthetic heart valve; significant arrhythmia; serum creatinine level greater than 1.5 mg/dL; allergy to iodinated contrast material; pregnant state; body mass index (weight in kilograms divided by the square of height in meters) greater than 35; evidence of active clinical instability or life-threatening disease; or inability to adhere to study procedures.
Protocol for Coronary CT Angiography and Coronary Artery Calcium Scoring
Each center performed coronary CTA acquisition using a variety of different CT scan platforms (LightSpeed VCT, GE Healthcare; Somatom Sensation and Definition CT; Brilliance 256 and Brilliance 64, Philips Healthcare; and Aquilion One and Aquilion 64, Toshiba), with trial recommendation to adhere to the guidelines of the Society of Cardiovascular CT [4] and the American College of Radiology [5]. The minimum requirement for participation in the trial was use of a 64-slice cardiac-capable CT scanner. However, the exact protocol for the performance of coronary CTA was at the discretion of each site, including the use of β-blockade and nitroglycerin administration. IV or oral metoprolol was recommended for any patient with a heart rate of 65 beats/min or higher. It was also recommended that 0.2 mg nitroglycerin be administered sublingually before image acquisition. During acquisition, 80–100 mL of contrast material (Isovue 370 mg/dL, Bracco; Omnipaque 350 mg/dL, GE Healthcare; or Visipaque 320 mg/dL, GE Healthcare) was injected IV, followed by a saline flush. Helical or axial scan data were obtained with retrospective ECG gating or prospective ECG triggering, respectively. Image acquisition was prescribed to include the coronary arteries, left ventricle, and proximal ascending aorta. The scan parameters were as follows: collimation, 64 × 0.625/0.750 mm; tube voltage, 100 or 120 mV; effective tube current, 400–650 mA. Radiation dose reduction strategies were employed when feasible, with body mass index and heart rate as the respective recommended factors for decision-making with regard to increasing tube current or kilovoltage and acquiring images using retrospective ECG-gated helical or prospective ECG-triggered axial scan. Radiation dose for coronary CTA was determined by the dose-length product, and this was converted to millisieverts through multiplication by the conversion factor of 0.014 mSv/(mGy · cm) [9].
Noninvasive Coronary Artery Analysis by CT
Coronary CTAs were analyzed in blinded fashion by an independent core laboratory (LA BioMed, at Harbor-UCLA Medical Center) in accordance with the Society of Cardiovascular CT guidelines on CT interpretation [7]. CT images were evaluated using 3D workstations (Vitrea, Vital Images; or Ziosoft, Qi). CTs were visualized by any postprocessing method, including axial, multiplanar reformat, maximum intensity projection, and cross-sectional analysis. Coronary artery calcium scoring was performed using customary acquisition protocols as previously described [4].
Coronary segments were scored using an 18-segment Society of Cardiovascular CT model [10]. In each segment, atherosclerosis was defined as the presence of tissue structures greater than 1 mm2 in diameter within the coronary artery lumen or adjacent to the coronary artery lumen that could be discriminated from pericardial tissue, epicardial fat, or the vessel lumen itself. Coronary lesions were classified by luminal diameter stenosis severity as 0%, 1–29%, 30–49%, 50–69%, 70–90%, subtotally (> 90%–99%), or totally (100%) occluded. Per-patient and per-vessel CAD stenoses were the maximal stenoses identified in all segments in an individual subject or in all segments within a vessel distribution, respectively. Vessel distributions were categorized for the left anterior descending artery (distribution including the first and second diagonal branches), left circumflex coronary artery (distribution including the ramus intermediate, first and second obtuse marginal branches, and left posterolateral branch), and right coronary artery (distribution including the right posterolateral branch and posterior descending artery). Coronary artery calcium score was measured by the method of Agatston et al. [11], with patient subsets categorized as 0, 1–10, 11–99, 100–399, and 400 or more, respectively. No patient was excluded from analysis on the basis of a set calcium score threshold. All coronary CTA examinations (in 252 of 285 subjects) deemed interpretable by the coronary CTA core laboratory were evaluated by the FFRCT core laboratory using an intention-to-diagnose protocol.
CT Image Quality Analysis
All CT scans were reviewed in a blinded fashion on per-patient and per-vessel bases for overall image quality, which was judged as excellent, good, adequate, or nondiagnostic, as previously described [12]. For each coronary vessel, this Likert scale included documentation of image artifacts and other factors affecting scan quality, including motion, misalignment, image noise, and severe coronary artery calcification. If multiple artifacts were present, the artifact judged as having the greatest impact on image interpretability was recorded.
Artifacts were deemed present when significant enough to impair accurate qualitative interpretation of the coronary CTA examinations.
Invasive Coronary Angiography Image Acquisition and Fractional Flow Reserve Performance
Selective invasive coronary angiography was performed by standard catheterization techniques in accordance with the guidelines of the American College of Cardiology [13]. Two projections were obtained per major epicardial vessel, with angles of projection optimized on the basis of cardiac position. FFR was determined in vessels as clinically indicated but was not determined for subtotal (≤ 99% stenosis) lesions. After administration of nitroglycerin, a pressure-monitoring guidewire (PressureWire Certus, St. Jude Medical Systems; or ComboWire, Volcano) was advanced past the stenosis. Hyperemia was achieved by administration of IV adenosine (140 mcg/kg/min; n = 252). The position of the distal pressure sensor was recorded to enable the calculation of FFRCT from the same point as the measured FFR. FFR was calculated by dividing the mean distal coronary artery pressure by the mean aortic pressure during hyperemia. FFR was considered diagnostic of ischemia at a threshold of up to 0.80 on per-patient and per-vessel bases [14].
Interpretation of Fractional Flow Reserve Computed From Standard Coronary CT Scans
FFRCT was performed in blinded fashion by core laboratory analysts at HeartFlow by the postprocessing of normally acquired coronary CTAs. Importantly, all studies deemed interpretable by the independent coronary CTA core laboratory were evaluated by the FFRCT core laboratory. Because coronary artery flow and pressure are unknown a priori, physiologic models of the heart and microcirculation and blood flow simulation using computational fluid dynamics were applied to 3D anatomic models of the coronary arteries [15]. Custom methods were applied to blinded CT data to extract a quantitative 3D model of the epicardial coronary artery tree. The volume of the ventricular myocardium was calculated from CT and was used to establish demand for coronary blood flow under resting conditions. Lumped parameter models were applied to the outflow boundaries of the 3D coronary artery model, and morphometry laws relating vessel size to resting flow rate and simulated response to adenosine were used to model hyperemic resistance to flow for each coronary artery branch. Finite element methods were then applied to solve incompressible Navier-Stokes equations for blood flow and pressure [15]. FFRCT was calculated as the ratio of distal over proximal pressure at all locations in the coronary artery tree; an FFRCT of up to 0.80 was considered diagnostic of lesion-specific ischemia.
Statistical Analyses
Categoric variables are presented as frequencies and percentages, and continuous variables are presented as mean ± SD. Diagnostic measures on per-patient and per-vessel bases were calculated, including sensitivity, specificity, and accuracy. All analyses were performed using SAS proprietary software, version 9.2 (SAS Institute).
Results
Patient Characteristics
The study population consisted of 252 patients, with 407 vessels undergoing evaluation by CT, FFRCT, and invasive FFR. The median estimated effective dose from the coronary CTA examinations was 6.4 ± 1.8 mSv. Characteristics of the study population are shown in Table 1.
| Characteristic | Result |
|---|---|
| No. of patients | 252 |
| Age (y), mean ± SD | 63 ± 9 |
| Sex ratio (M: F) | 71:29 |
| Ethnicity | |
| White | 67 |
| Asian | 31 |
| Black or African American | 2 |
| American Indian or Alaska Native | 0.4 |
| Pertinent medical history | |
| Diabetes mellitus | 21 |
| Hypertension | 71 |
| Hyperlipidemia | 80 |
| Family history of coronary artery disease | 20 |
| Current smoker | 18 |
| Prior myocardial infarction | 6 |
| Prior percutaneous coronary intervention | 7 |
| Angina within the past month | 77 |
Note—Except where otherwise indicated, values are given as percentages.
Effect of β-Blockade Before Coronary CT Angiography on Diagnostic Performance of Fractional Flow Reserve Computed From Standard Coronary CT Scans
Of 407 vessels examined, 295 (72%) were within patients who received β-blockade before CT scan image acquisition, and 112 (28%) were within patients who did not receive β-blockade. Beta-blockade resulted in improved specificity but had no significant impact on sensitivity or overall accuracy (Table 2). Use of β-blockers before coronary CTA was associated with less error for FFRCT, as compared with nonuse (–0.048 vs −0.084, respectively; p = 0.008) (Fig. 1). There was no significant difference in diagnostic performance of FFRCT when stratified among subjects with heart rates of below 65 and those with 65 beats/min or higher (Table 2). In subjects who received β-blockade and nitroglycerin, the mean heart rate was 62.7 beats/min before and 55.7 beats/min during the examination (p < 0.001).
| Variable | N | Sensitivity (%) | p | Specificity (%) | p | Accuracy(%) | p |
|---|---|---|---|---|---|---|---|
| β-Blockade | 0.37 | 0.03 | 0.58 | ||||
| Yes | 295 | 77.5 | 66.4 | 70.5 | |||
| No | 112 | 86.3 | 51.4 | 65.1 | |||
| Heart rate | 0.18 | 0.44 | 0.34 | ||||
| < 65 Beats/min | 284 | 76.9 | 60.7 | 66.6 | |||
| ≥ 65 Beats/min | 123 | 87.2 | 66.6 | 74.5 | |||
| Sublingual nitroglycerin | 0.09 | 0.05 | 0.97 | ||||
| Yes | 307 | 86.2 | 65.0 | 69.3 | |||
| No | 100 | 93.9 | 55.2 | 68.0 | |||
| Nitroglycerin given before CCTA | 0.15 | 0.01 | 0.09 | ||||
| ≤ 30 min | 103 | 84.2 | 75.3 | 78.6 | |||
| > 30 min | 204 | 92.8 | 53.8 | 67.5 | |||
| Overall | 307 | 87.7 | 66.1 | 73.7 |
Note—Values are given as percentages. CCTA = coronary CT angiography.
Effect of Nitroglycerin Administration Before Coronary CT Angiography on Diagnostic Performance of Fractional Flow Reserve Computed From Standard Coronary CT Scans
Of 407 vessels examined, 307 (75%) were within patients who received sublingual nitroglycerin before CT image acquisition, and 100 (25%) were within patients who did not receive sublingual nitroglycerin. Use of sublingual nitroglycerin was associated with improved specificity of FFRCT but no overall improvement in diagnostic accuracy (Table 2). Improved diagnostic performance of FFRCT after sublingual administration of nitroglycerin was most notable when it was given within 30 minutes of coronary CTA examination (Table 2), with improvements in specificity and a trend toward improved diagnostic accuracy. Case examples of subjects examined with and without sublingual nitroglycerin administration before CT are shown in Figure 2.
Fig. 2A —Case examples show effect of sublingual nitroglycerin on coronary CT angiography (CCTA) and modeling of fractional flow reserve (FFR) computed from standard coronary CT scans (FFRCT).
A, Computational FFRCT model of 51-year-old man who underwent coronary CT without sublingual (SL) administration of nitroglycerin. Coronary arteries are smaller in caliber than seen on coronary angiographic images after intracoronary administration of nitroglycerin. FFR measured in distal right coronary artery was 0.86; FFRCT in corresponding location was 0.73, most likely owing to increased resistance of long, tapering vessel in absence of nitroglycerin.
Fig. 2B —Case examples show effect of sublingual nitroglycerin on coronary CT angiography (CCTA) and modeling of fractional flow reserve (FFR) computed from standard coronary CT scans (FFRCT).
B, Computational FFRCT model of 65-year-old man who received sublingual nitroglycerin before coronary CT. FFR was measured after intracoronary administration of nitroglycerin at three locations in left coronary system, with good concordance of FFRCT at those same locations.
Effect of Image Artifact, CT Scan Platform, CT Scan Mode, and Tube Potential on the Diagnostic Accuracy of Fractional Flow Reserve Computed From Standard Coronary CT Scans
The four most common image artifacts identified by the coronary CTA core laboratory—motion, misalignment, image noise, and severe coronary artery calcification—were studied for their effect on FFRCT diagnostic performance. The presence of misalignment resulted in a reduction in diagnostic accuracy (Table 3) when comparing vessels that were not affected by misalignment artifact. When stratified by method of ECG gating, no differences in diagnostic accuracy of FFRCT were noted between prospective ECG-triggered axial and retrospective ECG-gated helical (71.0% vs 67.5%, respectively; p = 0.61) coronary CTAs. Similarly, artifacts related to motion did not have a significant impact in the measures of diagnostic performance (Table 3). Increasing coronary artery calcium score was not associated with differences in FFRCT diagnostic performance (Table 3).
| Variable | N | Sensitivity (%) | p | Specificity (%) | p | Accuracy(%) | p |
|---|---|---|---|---|---|---|---|
| Misalignment | 0.001 | 0.98 | 0.03 | ||||
| Yes | 64 | 43.0 | 63.0 | 56.0 | |||
| No | 343 | 86.0 | 62.0 | 71.0 | |||
| Motion | 0.08 | 0.92 | 0.26 | ||||
| Yes | 72 | 71.0 | 63.0 | 65.0 | |||
| No | 333 | 82.0 | 62.0 | 72.0 | |||
| Coronary artery calcium score | 0.49 | 0.49 | 0.68 | ||||
| 0-99 | 98 | 59.1 | 59.1 | 67.5 | |||
| 100-399 | 137 | 80.1 | 80.1 | 76.9 | |||
| ≥ 400 | 106 | 64.2 | 64.2 | 70.4 |
Note—Values are given as percentages.
No differences were observed for performance of FFRCT by CT scanner manufacturer (ANOVA p = 0.334) (Fig. 3).
Discussion
The present results, derived from a large multinational prospective study, suggest that whereas FFRCT provides superior diagnostic performance over coronary CTA alone across a broad range of image quality and patient preparation methods, significant improvements in diagnostic performance of FFRCT can be expected with adherence to best practices for CT image acquisition. These include the use of β-blockade and nitroglycerin administration and coronary CTA scan protocol optimization to reduce misalignment artifacts.
The integration of computational fluid dynamics to typically acquired coronary CTA provides a unique opportunity to define the physiologic significance of CAD without the need for either additional studies or radiation (or both) [3, 15–17]. This extends the potential of coronary CTA to not only detect obstructive disease but also help identify those patients who may benefit from an invasive strategy with intended revascularization. Although FFRCT has previously been shown to be relatively impervious to issues of image quality [12], the current data suggest that there are significant opportunities to improve accuracy and specificity of FFRCT by adhering to established best practices of cardiac CTA as defined by guidelines produced by specialty societies [4, 5]. Given that FFR is the only physiologic method for ischemia detection that has been shown to be useful in improving short-term freedom from unplanned intervention [14], the ability to predict FFR from a noninvasive test renders FFRCT a potentially “disruptive” technology—offering for the first time the opportunity to identify those specific lesions that cause ischemia by using a single imaging test that is performed at rest. Given this potential, it is vital to determine the potential variables of coronary CTA acquisition, image quality, and interpretation to ensure optimal computation of FFRCT.
It has been previously established that the diagnostic performance of coronary CTA as compared with invasive coronary angiography is improved by both β-blockade and nitroglycerin administration [17]. Approximately 3–5 minutes after the administration of nitroglycerin, the coronary arteries are significantly larger in both diameter and area, which allows more accurate assessment of anatomic details [18]. As a further benefit, nitroglycerin administration appears also to improve the assessment of FFRCT, probably because its computation is based on an anatomic model of the epicardial coronary arteries created from CT data that is assumed to match the degree of vasodilation that might be induced during intracoronary administration of nitroglycerin at the time of FFR measurement. The pressure loss along an epicardial artery is approximately equal to the product of the flow and the segmental resistance of the coronary artery. The segmental resistance is approximately inversely proportional to the fourth power of the radius; thus, a 10% increase in the radius of the vessel attainable by administration of nitroglycerin before coronary CTA acquisition will reduce resistance by approximately 30%.
The use of β-blockade for coronary CTA is also supported by best-practice recommendations [4, 5]. Recent real-world published data suggest that adherence to these recommended guidelines is variable [19]. A number of potential explanations exist for this finding, including the time needed for administration and effect of β-blockers and the perception of limited additional value. Given the opportunity to realize the benefit of accurate physiologic data when CT examinations are performed in accordance to societal guidelines, our data support that adherence to these guidelines will improve diagnostic performance, both for anatomic stenosis and for FFRCT. Interestingly, in our analysis, heart rate at the time of the scan did not affect the accuracy of FFRCT. This finding may be explained, in part, by other effects of β-blockers beyond heart rate lowering, including reduction in heart rate variability or reduced ectopy during coronary CTA. This potential benefit of β-blockade is often underappreciated by those performing coronary CTA, and as a result, a β-blocker is often not administered when the heart rate is below specified thresholds at presentation. Our data provide further support for the use of β-blockade in coronary CTA, particularly given the growing evidence suggesting the potential to provide information regarding the hemodynamic significance of an anatomic lesion identified on coronary CTA.
Recently, FFRCT has been shown to be less sensitive to issues of image quality than coronary CTA alone [12]. Unlike coronary CTA, which relies only on the image quality in any individual segment, FFRCT is determined through the solving of millions of equations thousands of times throughout the cardiac cycle, relying on a significantly larger pool of data that includes not only a specific coronary segment in question but also the remainder of the coronary vasculature, myocardium, and the proximal aorta. Although this added complexity adds to the robustness of FFRCT, our data suggest that image artifacts commonly seen in the setting of suboptimal patient preparation may significantly reduce the accuracy of FFRCT. These data constitute evidence that guidelines-based CT acquisition and performance should be adhered to for optimal derivation of FFRCT.
This study is not without limitations. The present results are a post hoc analysis of the DeFACTO trial. Although the trial is large and multicenter in nature, some of the presented subanalyses are limited by small sample size. However, the differences that we identified in the diagnostic performance of FFRCT were statistically significant and can be explained by the premises of the FFRCT methods. The findings were meant as exploratory, with the aim of deriving important clues for the optimization of accuracy of FFRCT, and in the future, larger studies should be performed to confirm the findings of the present study. In addition, we lack baseline data about the number of patients who received β-blockade at the time of CT. Further, the coronary CTAs were acquired using various scan platforms without a difference in diagnostic performance; however, we recognize that the use of varied scan platforms somewhat limits our analysis. The importance of β-blockade before coronary CTA acquisition is emphasized in this article. We do not, however, have complete baseline β-blockade use in all patients, which we acknowledge to be a limitation of our assessment. Nevertheless, our analysis does suggest incremental improvement in diagnostic performance of FFRCT. Our data suggest that the diagnostic performance of FFRCT is stable in the setting of coronary motion. It is important, however, to recognize that the coronary CTA examinations included in the DeFACTO study were deemed interpretable by the coronary CTA core laboratory and that the impact of severe coronary motion that would render a coronary CTA uninterpretable has not been evaluated in our study. Finally, we recognize that our analysis did not adjust for all potential confounders. Although this is a limitation given the large number of variables that could potentially impact diagnostic performance of FFRCT—including that one individual performed the invasive FFR and another performed the FFRCT analysis—we do not think it is feasible to create an appropriate multivariable model.
Conclusion
Our secondary analysis of the prospective multicenter DeFACTO study reveals that there is a significant impact on diagnostic accuracy of FFRCT by the use of β-blockade and nitroglycerin administration, as well as by misalignment artifacts within coronary CTA images. Importantly, other image-related artifacts—such as noise, motion, and coronary artery calcium—appear to have no significant impact on the diagnostic performance of FFRCT.
Footnote
This study was funded by HeartFlow. HeartFlow was not involved in study design, data analysis, manuscript preparation or review, or authorization for submission for publication.
References
1.
Min JK, Shaw LJ, Berman DS. The present state of coronary computed tomography angiography: a process in evolution. J Am Coll Cardiol 2010; 55:957–965
2.
Budoff MJ, Dowe D, Jollis JG, et al. Diagnostic performance of 64-multidetector row coronary computed tomographic angiography for evaluation of coronary artery stenosis in individuals without known coronary artery disease: results from the prospective multicenter ACCURACY (Assessment by Coronary Computed Tomographic Angiography of Individuals Undergoing Invasive Coronary Angiography) trial. J Am Coll Cardiol 2008; 52:1724–1732
3.
Min JK, Leipsic J, Pencina MJ, et al. Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA 2012; 308:1237–1245
4.
Abbara S, Arbab-Zadeh A, Callister TQ, et al. SCCT guidelines for performance of coronary computed tomographic angiography: a report of the Society of Cardiovascular Computed Tomography Guidelines Committee. J Cardiovasc Comput Tomogr 2009; 3:190–204
5.
Jacobs JE, Boxt LM, Desjardins B, et al. ACR practice guideline for the performance and interpretation of cardiac computed tomography (CT). J Am Coll Radiol 2006; 3:677–685
6.
Decramer I, Vanhoenacker PK, Sarno G et al. Effects of sublingual nitroglycerin on coronary lumen diameter and number of visualized septal branches on 64-MDCT angiography. AJR 2008; 190:219–225
7.
Zeiher AM, Schächinger V, Minners J. Long-term cigarette smoking impairs endothelium-dependent coronary arterial vasodilator function. Circulation 1995; 92:1094–1100
8.
Min JK, Berman DS, Budoff MJ, et al. Rationale and design of the DeFACTO (Determination of Fractional Flow Reserve by Anatomic Computed Tomographic Angiography) study. J Cardiovasc Comput Tomogr 2011; 5:301–309
9.
Shrimpton PC. Assessment of patient dose in CT. In Bongartz G, Golding SJ, Jurik AG, et al. European guidelines for multislice computed tomography. www.msct.eu/PDF_FILES/Appendix%20paediatric%20CT%20Dosimetry.pdf. March 2004. Accessed January 20, 2014
10.
Raff GL, Abidov A, Achenbach S, et al. SCCT guidelines for the interpretation and reporting of coronary computed tomographic angiography. J Cardiovasc Comput Tomogr 2009; 3:122–136
11.
Agatston AS, Janowitz WR, Hildner FJ, et al. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol 1990; 15:827–832
12.
Min JK, Koo BK, Erglis A, et al. Effect of image quality on diagnostic accuracy of noninvasive fractional flow reserve: results from the prospective multicenter international DISCOVER-FLOW study. J Cardiovasc Comput Tomogr 2012; 6:191–199
13.
Naidu SS, Rao SV, Blankenship J, et al. Clinical expert consensus statement on best practices in the cardiac catheterization laboratory: Society for Cardiovascular Angiography and Interventions. Catheter Cardiovasc Interv 2012; 80:456–464
14.
Tonino PA, De Bruyne B, Pijls NH, et al. Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med 2009; 360:213–224
15.
Taylor CA, Fonte TA, Min JK. Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis. J Am Coll Cardiol 2013; 61:2233–2241
16.
Koo BK, Erglis A, Doh JH, et al. Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms: results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained via Noninvasive Fractional Flow Reserve) study. J Am Coll Cardiol 2011; 58:1989–1997
17.
Chun EJ, Lee W, Choi YH, et al. Effects of nitroglycerin on the diagnostic accuracy of electrocardiogram-gated coronary computed tomography angiography. J Comput Assist Tomogr 2008; 32:86–92
18.
Feldman RL, Pepine CJ, Curry RC Jr, et al. Coronary arterial responses to graded doses of nitroglycerin. Am J Cardiol 1979; 43:91–97
19.
Chinnaiyan KM, Peyser P, Goraya TY, et al. Impact of a continuous quality improvement initiative on appropriate use of coronary CT angiography: results from a multicenter, statewide registry, the Advanced Cardiovascular Imaging Consortium. J Am Coll Cardiol 2012; 60:1185–1191
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Submitted: June 24, 2013
Accepted: August 31, 2013
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