Association Between 3D-Angiography Based Fractional Flow Reserve and Non-Invasive Myocardial Ischemia Testing: The FAST ISCHEMIA Study

Abstract

Background. In order to facilitate fractional flow reserve (FFR)-guided lesion assessment, several 3-dimensional (3D)-angiography-based physiological indices have been recently validated. Thus far, limited data are available on the association of these indices with conventional forms of ischemia testing. Aim. The aim of the study was to determine the association between 3D-angiography-based vessel-FFR (vFFR) and myocardial ischemia as assessed by exercise electrocardiography (ECG) testing, dobutamine stress echocardiography, single photon emission computed tomography myocardial perfusion imaging (SPECT-MPI), and stress cardiovascular magnetic resonance imaging (stress CMR). Methods. FAST ISCHEMIA is a retrospective, single-center cohort study including  patients who underwent non-invasive myocardial ischemia testing and subsequent coronary angiography (≤3 months). A total of 145 patients (340 vessels) were analyzed. The overall patient-based sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), and negative likelihood ratio (LR-) of vFFR ≤0.80 in any vessel for ischemia was 64% (95% confidence interval [CI], 53-74), 71% (95% CI, 54-84), 83% (95% CI, 72-91), 46% (95% CI, 33-60), 2.16 (95% CI, 1.25-3.74), and 0.52 (95% CI, 0.36-0.74), respectively. Multivariable logistic regression showed that vFFR ≤0.80 was significantly associated with ischemia on a patient level (odds ratio, 8.13; 95% CI, 2.51-30.06; P<.001) and on a vascular territory level (odds ratio, 2.75; 95% CI, 1.17-6.44; P<.01). Conclusion. Our study suggests that vFFR ≤0.80 has a modest association with non-invasive myocardial ischemia testing using either exercise ECG or stress imaging modalities. After correcting for independent confounders, vFFR was independently associated with ischemia on a non-invasive myocardial ischemia detection test.

Keywords: 3D coronary angiography, functional ischemia testing, myocardial ischemia, SPECT, stress-CMR, vFFR, vessel fractional flow reserve

The rationale for restricting coronary revascularization to those lesions causing significant impairment in distal coronary pressure has been widely demonstrated and current guidelines recommend inducible myocardial ischemia detection preceding elective interventions.^1,2 Moreover, fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) has been shown to improve clinical outcomes and long-term cost-effectiveness as compared with angiography-guided PCI on top of optimal medical therapy.^3-5 In order to further facilitate FFR-guided hemodynamic lesion assessment, several novel adenosine-free coronary pressure indices have been validated and proved to reduce procedure time and eliminate adverse reactions to hyperemic agents.^6-9 More recently, 3-dimensional (3D)-angiography-based FFR showed a strong correlation with pressure-wire-based invasive FFR measurement and may further enhance the uptake of physiological lesion assessment by eliminating the need for a pressure wire or microcatheter.^10-19 Thus far, validation of these 3D-angiography-based FFR data against conventional forms of ischemia testing is limited. In this study, we aimed to determine the association between 3D-angiography-based vessel-FFR (vFFR) and myocardial ischemia as assessed by exercise electrocardiography (ECG) test, dobutamine stress echocardiography, single photon emission computed tomography myocardial perfusion imaging (SPECT-MPI), and stress cardiovascular magnetic resonance imaging (stress CMR).

Methods

Study population. In this observational, retrospective, single-center cohort study, all patients undergoing non-invasive myocardial ischemia detection between February 2014 and January 2019 at the Erasmus University Medical Center were included. Inclusion criteria were: age ≥18 years; presentation with stable angina (Canadian Cardiovascular Society II or higher); availability of a non-invasive myocardial ischemia test (including exercise ECG test, dobutamine stress echocardiography, SPECT-MPI, and stress CMR); and coronary angiography within 3 months post myocardial ischemia testing.

Exclusion criteria included: inconclusive non-invasive myocardial ischemia tests (negative test with a lack of achieving target heart rate); previous coronary artery bypass grafting; previous heart transplantation; severe valvular heart disease; congenital heart disease; and insufficient quality of angiogram precluding vFFR computation (ie, absence of a minimum of 2 angiographic projections with views at least 25° apart, substantial foreshortening or overlap of the vessel, aorto-ostial left main coronary artery or right coronary artery [RCA] stenosis, or inadequate contrast flush). In addition, patients undergoing exercise ECG test with incomplete vFFR values (defined as ≥1 incomputable vessel with no vFFR ≤0.80 in any vessel) were excluded.

Non-invasive myocardial ischemia tests included exercise ECG, dobutamine stress echocardiography, SPECT-MPI, and stress CMR. Test results were provided by dedicated local staff physicians. In patients with multiple non-invasive myocardial ischemia detection tests, the most recent test was used.

The ethics committee of the Erasmus University Medical Center provided approval for the current study (MEC-2022-0530).

Non-invasive myocardial ischemia detection. Exercise ECG testing was performed at an initial workload of 10 W or 20 W, while the workload was gradually increased with 10 W or 20 W, respectively.²⁰ A 12-lead ECG was recorded continuously. Tests were considered positive if either a new ST-segment elevation of at least 1 mm or 2 mm in males and females, respectively, or 1.5 mm in the leads V2-V3, occurred at the J-point in 2 subsequent leads, or when new horizontal or downsloping ST-depression of at least 0.5 mm occurred in 2 subsequent leads.

Dobutamine stress echocardiography was performed with continuous infusion of intravenous dobutamine at 10 μg per kilogram body weight per minute and was increased every 3 minutes until wall-motion abnormalities on transthoracic echocardiography occurred or an infusion rate of 40 μg per kilogram body weight per minute was reached. Atropine, up to a maximum dose of 2.0 mg, was administered intravenously in patients who did not reach the predefined threshold of 85% of their age-adjusted maximum heart rate. Akinesia and hypokinesia on echocardiography were regarded as signs of inducible ischemia. Echocardiographic wall-motion abnormalities were evaluated as previously described.²¹

SPECT-MPI scans were performed by SPECT/computed tomography (CT) camera systems (Siemens Symbia TruePoint SPECT-CT) while administering 500 MBq or 700 MBq (>100 kg body weight) 99mTc-Sestamibi during rest and stress. Stress was either achieved through dobutamine or adenosine infusion and/or exercise. First, the isotope uptake was recorded over stress. In cases with normal uptake during stress, no subsequent isotope uptake during rest was recorded. The acquired images were evaluated as described previously.²² In brief, the isotope uptake was scored in rest and stress as 0 (= normal uptake), 1 (= mild reduction), 2 (= moderate reduction), 3 (= severe reduction), or 4 (= no uptake) across 17 segments. The difference between scores in rest and stress was then calculated as the summed difference score for each segment. Ischemia was defined as a summed difference score ≥2 in a vascular territory. All of the obtained images were evaluated on site by experienced nuclear medicine physicians.

Adenosine stress-perfusion CMRs were performed on a 1.5-T clinical magnetic resonance imaging (MRI) scanner (Discovery MR450 or Signa Artist; GE Healthcare). The protocol consisted of ventricular function (standard long- and short-axis cine), stress and rest myocardial perfusion, and late gadolinium enhancement. After administration of adenosine at a constant rate of 140 μg/kg/min for at least 3 minutes, gadobutrol contrast-enhanced first-pass perfusion imaging of 3 parallel short-axis slices of the left ventricle was performed. Rest perfusion was performed at least 10 minutes later. Perfusion images were assessed visually, with stress and rest images displayed simultaneously. Reversible ischemia was defined as a perfusion defect without the presence of late gadolinium enhancement or a perfusion deficit that extended beyond the area of late gadolinium enhancement.²³

vFFR computation. Computation of vFFR was performed offline using CAAS workstation 8.2 (Pie Medical Imaging) by trained study personnel (IK, MT) blinded to the specific non-invasive test results and subsequent treatment. Within CAAS 8.2, the pressure drop is calculated instantaneously by applying physical laws including viscous resistance and separation loss effects present in coronary flow behavior.¹⁶

Two orthogonal 2-dimensional angiograms with visualization of the RCA, left anterior descending (LAD), or left circumflex (LCX) were exported and loaded into the software, taking into account overlapping and foreshortening to create a 3D reconstruction of the coronary artery as accurately as possible. Temporal alignment of the 2 view phases in the cardiac cycle was performed automatically by ECG triggering. End-diastolic frames were identified automatically, but manual frame selection was allowed in case of suboptimal contrast opacification or overlap.¹⁶ Contour detection was performed semiautomatically, delineating the vessel contour from the ostium up to at least 2 cm after the most distal stenosis and at best up to a lumen diameter of 2 mm.

Percent diameter stenosis, minimal lumen diameter (MLD), reference lumen diameter, and lesion length were derived from the same 3D model as the one upon which the vFFR calculation was based.

Lesions in side branches with a diameter ≥2 mm were designated to the epicardial coronary artery from which they originated (ie, diagonal branches were designated to the LAD, lesions in the obtuse marginal and intermediate branches were designated to the LCX, and lesions in the posterolateral and descending posterior branches were designated either to the LCX or RCA). In case of more than 1 stenosis in an epicardial coronary artery and/or side branches, the vFFR and 3D quantative coronary angiography (3D-QCA) values of the stenosis with the highest stenosis percentage was used. In epicardial coronary arteries and side branches without stenosis, 3D-QCA and vFFR were computed over the MLD. Patients were defined as non-ischemic only with all 3 vFFR values >0.80 and ischemic with ≥1 vFFR value ≤0.80.

Statistical analysis. Distribution of continuous variables was evaluated using Q-Q plots and the Shapiro-Wilk test. Normally distributed continuous variables are presented as mean ± standard deviation. Non-normally distributed continuous variables are presented as median and interquartile range (IQR; 25th-75th percentile. Categorical variables are shown as counts and percentages. We calculated the sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), positive likelihood ratio (LR+), and negative likelihood ratio (LR-) of vFFR ≤0.80 with ischemia on a stress test as the reference standard. First, we assessed the association between vFFR and ischemia as diagnosed by a non-invasive test by means of a vessel-based analysis. For this purpose a generalized linear mixed model was run with vFFR ≤0.80 as the independent variable, detection of ischemia by non-invasive test as the dependent variable, and a random intercept for patient to account for assessment of multiple vessels per patient. However, using a model with a random intercept did not significantly improve the fit of the model compared with a model with only a fixed intercept. In addition, the variance of the random intercept was <.0001. Consequently, we deemed a binary logistic regression was tenable and applied this on a vessel level and patient level. The odds ratio (OR) and 95% confidence interval (CI) were calculated for each variable in the analysis. Significant variables from previous research were tested for significance in a univariable analysis; those with P<.05 were entered in the multivariable analysis. Variables were entered in a hierarchical fashion, with vFFR entered in the first block, and age, sex, diabetes, severe calcification, and in-stent restenosis in the second block. The OR and 95% CI were calculated for each variable in the analysis.

All statistical analyses were performed with SPSS, version 25.0 (SPSS, Inc) and R, version 2019 (RStudio Team, Inc). A 2-sided P-value of <.05 was considered statistically significant.

Results

A total of 396 patients with a non-invasive myocardial ischemia test and subsequent coronary angiography within 3 months were screened, and 145 patients were included in the study (Figure 1). Mean age was 64 ± 10 years and 84 (58%) were male. A total of 39 patients (27%) underwent invasive functional lesion assessment with a FFR pressure wire at the time of the coronary angiography. Exercise ECG testing was performed in 57 patients (39%), dobutamine stress echocardiography in 4 patients (3%), SPECT-MPI in 78 patients (54%), and stress CMR in 6 patients (4%). Non-invasive ischemia testing revealed signs of ischemia in 105 cases (72%) (Table 1).

In these 145 patients, a total of 435 vessels were then screened for vFFR computability. Of the 435 vessels, 95 were excluded due to insufficient quality of the angiogram to compute vFFR (n = 52), total occlusion of the vessel (n = 35), ostial stenosis (n = 4), distal stenosis (n = 2), reference vessel diameter of <2 mm (n = 1), and aberrant origin of the vessel (n = 1). Finally, 340 vessels (78%) were considered amenable for vFFR computation. Mean reference vessel diameter was 2.8 mm (IQR, 2.5-3.3) and 3D-QCA based percent diameter stenosis was 32% (IQR, 19-46) (Table 2). In 59 patients (41%), a vFFR ≤0.80 in any vessel was computed.

Discriminative ability of vFFR for ischemia based on non-invasive tests. Using a cut-off of ≤0.80 for vFFR on a patient level, sensitivity, specificity, PPV, NPV, LR+, and LR- were 64% (95% CI, 53-74), 71% (95% CI, 54-84), 83% (95% CI, 72-91), 46% (95% CI, 33-60), 2.16 (95% CI, 1.25-3.74), and 0.52 (95% CI, 0.36-0.74), respectively.

Discriminative ability of vFFR for ischemia on exercise ECG testing. Using a cut-off of ≤0.80 for vFFR on a patient level, sensitivity, specificity, PPV, NPV, LR+, and LR- were 74% (95% CI, 57-86), 74% (95% CI, 54-89), 81% (95% CI, 65-92), 65% (95% CI, 46-82), 2.82 (95% CI, 1.38-5.77), and 0.36 (95% CI, 0.19-0.66), respectively. Of the 34 patients with positive exercise ECG testing, revascularization was performed in 23 (68%). All 23 revascularized patients had at least 1 vessel with a vFFR ≤0.80. Conversely, 28/31 patients (90%) with a vFFR ≤0.80 underwent revascularization (Table 3).

Agreement between vFFR and stress imaging modalities. A total of 88 patients underwent dobutamine stress echocardiography, SPECT-MPI, or CMR, resulting in 264 coronary artery territories. Of the 264 territories, 71 (27%) were excluded due to insufficient quality of the angiogram to compute vFFR (n = 40), total occlusion (n = 28), distal location of stenosis (n = 2), and aberrant origin of vessel (n = 1), resulting in 193 vascular territories included in the final analysis. Using a cut-off of ≤0.80 for vFFR, sensitivity, specificity, PPV, NPV, LR+, LR-, and overall diagnostic accuracy were 25% (95% CI, 16-36), 88% (95% CI, 81-93), 55% (95% CI, 38-71), 66% (95% CI, 59-73), 1.62 (95% CI, 1.11-2.36), 0.69 (95% CI, 0.47-1.01), and 64%, respectively.

Of the 72 vascular territories suspected of having ischemia on stress imaging testing, only 25 territories (35%) underwent coronary revascularization. Of the 25 vascular territories that were revascularized, 18 territories (72%) had a vFFR ≤0.80. Conversely, 28/33 territories (85%) with a vFFR ≤0.80 were revascularized (Table 4).

Relationship between vFFR and ischemia on non-invasive ischemia tests. Multivariable logistic regression demonstrated that in patients who underwent exercise ECG testing, vFFR ≤0.80 in any vessel was closely associated with inducibility of ischemia (OR, 8.13; 95% CI, 2.51-30.06; P<.001) (Table 5). In the patients who underwent a stress imaging modality, multivariable logistic regression showed that vFFR ≤0.80 was significantly associated with ischemia in the respective vascular territory (OR, 2.75; 95% CI, 1.17-6.44; P<.01) (Table 5).

Discussion

In the present study, we determined the association between vFFR and myocardial ischemia as assessed by several non-invasive ischemia tests. Overall, on a patient level, we found a modest correlation between vFFR and non-invasive myocardial ischemia testing, with a diagnostic accuracy of 66% of vFFR ≤0.80 for presence of ischemia. However, in multivariable analyses, vFFR ≤0.80 proved to be significantly associated with ischemia as diagnosed by ECG testing on a patient level, and with ischemia as diagnosed by stress imaging modalities on a vascular territory level.

For the present study, we decided to include both exercise ECG testing and stress imaging modalities. Given its continuous widespread use, we included exercise ECG testing as a reference for vFFR assessment on a patient level. In 1995, De Bruyne et al already demonstrated a weak correlation with FFR despite using a subset of 60 selected patients with angiographically confirmed single coronary artery disease.²⁴ We demonstrated a sensitivity, specificity and diagnostic accuracy of 74% of vFFR to detect a positive exercise ECG test in patients with stable angina. This figure concurs with numerous reviews and meta-analyses reporting relatively low sensitivity rates for exercise ECG tests to detect and localize significant coronary artery disease. Following these findings, current guidelines recommend a step back from exercise ECG testing.²

Stress imaging modalities conversely detect and localize functional significance of coronary artery disease at a vascular territory level by means of inducible wall-motion abnormalities (defined as hypokinesia, akinesia, or dyskinesia), relative reduced regional myocardial tracer uptake, and/or low contrast signal areas of low perfusion during physiological or pharmacological stress, with normalization during resting state. Previous validation data with FFR were summarized in a meta-analysis of 21 studies reporting a sensitivity and specificity of 76% with invasive FFR ≤0.75 compared with SPECT-MPI and dobutamine stress echocardiography on a vessel level.²⁵ However, a more recent pooled analysis of 23 studies comparing various types of cardiac imaging modalities with FFR reported moderate sensitivity and specificity figures of SPECT-MPI to identify patients with a FFR ≤0.80 (70% and 78%, respectively), while on a vessel level the sensitivity of SPECT dropped to 57% along with a specificity of 75%.²⁶ In a comparison between stress CMR and SPECT-MPI for detection of coronary artery disease, stress CMR showed a higher sensitivity compared with SPECT (0.67 vs 0.59, respectively; P=.02) and a lower specificity (0.61 vs 0.72, respectively; P=.04).²⁷

When comparing the latter data with the present work, fundamental differences between FFR and 3D-angiography-based vFFR should be acknowledged. Whereas FFR achieves hyperemic blood flow directly through infusion of a hyperemic agent, with a subsequent effect influenced by individual patient characteristics such as microvascular resistance, vFFR computes hyperemic blood flow based on empirical methods from clinical data and is not influenced by specific patient characteristics. Similar confounding issues should be acknowledged for SPECT-MPI, which can be hampered by the presence of balanced ischemia in patients with multivessel disease, anatomical anomalies, absence of attenuation-corrected reconstructions, and microvascular dysfunction.²⁶

We found a modest association between stress imaging testing and vFFR with an accuracy of 64%, whereas sensitivity and specificity figures of vFFR ≤0.80 to predict ischemia in a vascular territory were 25% and 88%, respectively.

As this is the first direct comparison between vFFR and various non-invasive myocardial ischemia tests, our study adds to recent work by Smit and colleagues, who assessed the potential of contrast-flow quantitative flow ratio (cQFR) values to detect ischemia on SPECT-MPI in 224 coronary arteries from 85 patients.²² Smit et al found an independent association between cQFR and ischemia on SPECT-MPI (OR per 0.01 decrease of cQFR, 1.10; 95% CI, 1.04-1.18; P=.002) as did the present study in which we found an OR of 2.75 for vFFR ≤0.80 to predict ischemia on a vascular territory level.

To put our results into clinical perspective, final revascularization strategy was taken into account. While we found a poor association between non-invasive ischemia testing and final revascularization at a vascular territory level, a significantly better association to vessels with vFFR ≤0.80 was observed. As such, we found 15 vessels with negative stress imaging test results and a vFFR ≤0.80, in which revascularization was performed in 80% of the cases. Conversely, in 54 vessels with a normal vFFR and positive stress imaging test results, revascularization was performed in merely 17% of the cases.

Future studies are needed to assess the clinical impact of the discordance between coronary artery revascularization guidance by either non-invasive ischemia testing or vFFR.

Study limitations. This study has several limitations. First, it is a single-center, retrospective cohort with all its inherent limitations. The results might not be generalizable for the whole study population, as inclusion was restricted to those with a non-invasive ischemia detection test and a subsequent coronary angiogram of sufficient quality, following the prespecified inclusion and exclusion criteria. Due to mainly positive ischemia test results being referred for coronary angiography, the specificity of the vFFR might have been undermined. Second, selection of coronary angiograms was restricted to those with adequate contrast opacification, lack of significant overlap, foreshortening or aorto-ostial lesions, and adequate orthogonal angiograms to allow vFFR computation.

Conclusion

In conclusion, vFFR ≤0.80 has a modest association to non-invasive myocardial ischemia testing using either exercise ECG or stress imaging modalities. After correcting for independent confounders, vFFR was independently associated with ischemia on a non-invasive myocardial ischemia detection test.

Affiliations and Disclosures

From the ¹Department of Cardiology and ²Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.

Disclosure: The authors have completed and returned the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Daemen reports institutional grant/research support from Astra Zeneca, Abbott Vascular, Boston Scientific, ACIST Medical, Medtronic, Pie Medical, and ReCor Medical; consultant and speaker fees from Abbott Vascular, Abiomed, ACIST Medical, Boston Scientific, PulseCath, Pie Medical, and Siemens. Dr van Mieghem reports institutional research grant support from Abbott Vascular, Biotronik, Boston Scientific, Medtronic, Edwards LifeSciences, and Daiichi Sankyo; consultant fees from Abbott, Boston Scientific, Medtronic, Abiomed, PulseCath BV, Daiichi Sankyo, and Teleflex. Dr Tomaniak reports funding as the laureate of the European Society of Cardiology Research and Training Program in the form of the ESC 2018 Grant (T-2018-19628). The remaining authors report no conflicts of interest regarding the content herein.

Manuscript accepted September 15, 2022.

Address for correspondence: Dr J. Daemen, Department of Cardiology, Room Rg-628, Erasmus University Medical Center, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands. Email: j.daemen@erasmusmc.nl

References

1. Gada H, Kirtane AJ, Kereiakes DJ, et al. Meta-analysis of trials on mortality after percutaneous coronary intervention compared with medical therapy in patients with stable coronary heart disease and objective evidence of myocardial ischemia. Am J Cardiol. 2015;115(9):1194-1199. Epub 2015 Feb 12. doi:10.1016/j.amjcard.2015.01.556

2. Neumann FJ, Sousa-Uva M, Ahlsson A, et al. 2018 ESC/EACTS Guidelines on myocardial revascularization. Eur Heart J. 2019;40(2):87-165. doi:10.1093/eurheartj/ehy394

3. Zimmermann FM, Omerovic E, Fournier S, et al. Fractional flow reserve-guided percutaneous coronary intervention vs. medical therapy for patients with stable coronary lesions: meta-analysis of individual patient data. Eur Heart J. 2019;40(2):180-186. doi:10.1093/eurheartj/ehy812

4. Fearon WF, Nishi T, De Bruyne B, et al. Clinical outcomes and cost-effectiveness of fractional flow reserve-guided percutaneous coronary intervention in patients with stable coronary artery disease: three-year follow-up of the FAME 2 trial (fractional flow reserve versus angiography for multivessel evaluation). Circulation. 2018;137(5):480-487. Epub 2017 Nov 2. doi:10.1161/CIRCULATIONAHA.117.031907

5. 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(3):213-224. doi:10.1056/NEJMoa0807611

6. Escaned J, Echavarría-Pinto M, Garcia-Garcia HM, et al. Prospective assessment of the diagnostic accuracy of instantaneous wave-free ratio to assess coronary stenosis relevance: results of ADVISE II international, multicenter study (ADenosine Vasodilator Independent Stenosis Evaluation II). JACC Cardiovasc Interv. 2015;8(6):824-833. doi:10.1016/j.jcin.2015.01.029

7. Sen S, Escaned J, Malik IS, et al. Development and validation of a new adenosine-independent index of stenosis severity from coronary wave-intensity analysis: results of the ADVISE (adenosine vasodilator independent stenosis evaluation) study. J Am Coll Cardiol. 2012;59(15):1392-1402. Epub 2011 Dec 7. doi:10.1016/j.jacc.2011.11.003

8. Westra J, Andersen BK, Campo G, et al. Diagnostic performance of in-procedure angiography-derived quantitative flow reserve compared to pressure-derived fractional flow reserve: the FAVOR II Europe-Japan study. J Am Heart Assoc. 2018;7(14):e009603. doi:10.1161/JAHA.118.009603

9. Xu B, Tu S, Qiao S, et al. Diagnostic accuracy of angiography-based quantitative flow ratio measurements for online assessment of coronary stenosis. J Am Coll Cardiol. 2017;70(25):3077-3087. Epub 2017 Oct 31. doi:10.1016/j.jacc.2017.10.035

10. Neleman T, Masdjedi K, Van Zandvoort LJC, et al. Extended validation of novel 3D quantitative coronary angiography-based software to calculate vFFR: the FAST EXTEND study. JACC Cardiovasc Imaging. 2021;14(2):504-506. Epub 2020 Sep 30. doi:10.1016/j.jcmg.2020.08.006

11. Ligthart J, Masdjedi K, Witberg K, et al. Validation of resting diastolic pressure ratio calculated by a novel algorithm and its correlation with distal coronary artery pressure to aortic pressure, instantaneous wave-free ratio, and fractional flow reserve. Circ Cardiovasc Interv. 2018;11(12):e006911. doi:10.1161/CIRCINTERVENTIONS.118.006911

12. Svanerud J, Ahn JM, Jeremias A, et al. Validation of a novel non-hyperaemic index of coronary artery stenosis severity: the resting full-cycle ratio (VALIDATE RFR) study. EuroIntervention. 2018;14(7):806-814. doi:10.4244/EIJ-D-18-00342

13. Douglas PS, De Bruyne B, Pontone G, et al. 1-Year outcomes of FFRCT-guided care in patients with suspected coronary disease: the PLATFORM study. J Am Coll Cardiol. 2016;68(5):435-445. doi:10.1016/j.jacc.2016.05.057

14. Fearon WF, Achenbach S, Engstrom T, et al. Accuracy of fractional flow reserve derived from coronary angiography. Circulation. 2019;139(4):477-484. doi:10.1161/CIRCULATIONAHA.118.037350

15. 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(19):1989-1997. doi:10.1016/j.jacc.2011.06.066

16. Masdjedi K, van Zandvoort LJC, Balbi MM, et al. Validation of a three-dimensional quantitative coronary angiography-based software to calculate fractional flow reserve: the FAST study. EuroIntervention. 2020;16(7):591-599. doi:10.4244/EIJ-D-19-00466

17. Pellicano M, Lavi I, De Bruyne B, et al. Validation study of image-based fractional flow reserve during coronary angiography. Circ Cardiovasc Interv. 2017;10(9). doi:10.1161/CIRCINTERVENTIONS.116.005259

18. Tu S, Westra J, Yang J, et al. Diagnostic accuracy of fast computational approaches to derive fractional flow reserve from diagnostic coronary angiography: the international multicenter FAVOR pilot study. JACC Cardiovasc Interv. 2016;9(19):2024-2035. doi:10.1016/j.jcin.2016.07.013

19. Masdjedi K, Tanaka N, Van Belle E, et al. Vessel fractional flow reserve (vFFR) for the assessment of stenosis severity: the FAST II study. EuroIntervention. 2022;17(18):1498-1505. doi:10.4244/EIJ-D-21-00471

20. Rautaharju PM, Surawicz B, Gettes LS, et al. AHA/ACCF/HRS recommendations for the standardization and interpretation of the electrocardiogram: part IV: the ST segment, T and U waves, and the QT interval: a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society. Endorsed by the International Society for Computerized Electrocardiology. J Am Coll Cardiol. 2009;53(11):982-991. doi:10.1016/j.jacc.2008.12.014

21. Pellikka PA, Nagueh SF, Elhendy AA, et al; for the American Society of Echocardiography. American Society of Echocardiography recommendations for performance, interpretation, and application of stress echocardiography. J Am Soc Echocardiogr. 2007;20(9):1021-1041. doi:10.1016/j.echo.2007.07.003

22. Smit JM, Koning G, van Rosendael AR, et al. Relationship between coronary contrast-flow quantitative flow ratio and myocardial ischemia assessed by SPECT MPI. Eur J Nucl Med Mol Imaging. 2017;44(11):1888-1896. doi:10.1007/s00259-017-3769-2

23. Klem I, Heitner JF, Shah DJ, et al. Improved detection of coronary artery disease by stress perfusion cardiovascular magnetic resonance with the use of delayed enhancement infarction imaging. J Am Coll Cardiol. 2006;47(8):1630-1638. Epub 2006 Mar 27. doi:10.1016/j.jacc.2005.10.074

24. De Bruyne B, Bartunek J, Sys SU, Heyndrickx GR. Relation between myocardial fractional flow reserve calculated from coronary pressure measurements and exercise-induced myocardial ischemia. Circulation. 1995;92(1):39-46. doi:10.1161/01.cir.92.1.39

25. Christou MA, Siontis GC, Katritsis DG, Ioannidis JP. Meta-analysis of fractional flow reserve versus quantitative coronary angiography and noninvasive imaging for evaluation of myocardial ischemia. Am J Cardiol. 2007;99(4):450-456. Epub 2006 Dec 20. doi:10.1016/j.amjcard.2006.09.092

26. Danad I, Szymonifka J, Twisk JWR, et al. Diagnostic performance of cardiac imaging methods to diagnose ischaemia-causing coronary artery disease when directly compared with fractional flow reserve as a reference standard: a meta-analysis. Eur Heart J. 2017;38(13):991-998. doi:10.1093/eurheartj/ehw095

27. Schwitter J, Wacker CM, Wilke N, et al. MR-IMPACT II: magnetic resonance imaging for myocardial perfusion assessment in coronary artery disease trial: perfusion-cardiac magnetic resonance vs. single-photon emission computed tomography for the detection of coronary artery disease: a comparative multicentre, multivendor trial. Eur Heart J. 2013;34(10):775-781. Epub 2012 Mar 4. doi:10.1093/eurheartj/ehs022