Coverage Policy Manual
Policy #: 2017005
Category: Radiology
Initiated: January 2017
Last Review: October 2018
  Noninvasive Fractional Flow Reserve Using Computed Tomography Angiography

Invasively measured fractional flow reserve (FFR) evaluates the severity of ischemia caused by coronary artery obstructions and can predict when revascularization is beneficial. FFR is not a diagnostic test for ischemic heart disease, but evaluates ischemia resulting from a stenosis. It is now possible to obtain FFR noninvasively using computed tomography angiography (CTA)—so-called FFR-CT (HeartFlow software termed FFRCT; Siemens cFFR) using routinely collected CTA imaging data (Taylor, 2013). The process involves constructing a digital model of coronary anatomy and calculating FFR across the entire vascular tree using computational fluid dynamics. FFR-CT can also be used for “virtual stenting” to simulate how stent placement would be predicted to improve vessel flow (Kim, 2014).  
Randomized controlled trials and observational studies have demonstrated that FFR-guided revascularization can improve cardiovascular outcomes, reduce revascularizations, and decrease costs (Tonino, 2009). For example, the Fractional Flow Reserve versus Angiography for Multivessel Evaluation (FAME) trial randomized 1005 patients with multivessel disease and planned percutaneous coronary intervention (PCI) (Tonino, 2009; Fearon, 2013).  At 1 year, compared with PCI guided by angiography alone, FFR-guided PCI reduced the number of stents placed by approximately 30%—followed by lower rates (13.2% vs 18.3%) of major cardiovascular adverse events (myocardial infarction, death, repeat revascularization) and at a lower cost. The clinical benefit persisted through 2 years, although by 5 years events rates were similar between groups (van Nunen, 2015).
European guidelines for stable coronary artery disease recommend FFR be used “to identify hemodynamically relevant coronary lesion(s) when evidence of ischaemia is not available” (class Ia), and “[r]evascularization of stenoses with FFR <0.80 is recommended in patients with angina symptoms or a positive stress test” (Montalescot, 2013). Guidelines also recommend using “FFR to identify haemodynamically relevant coronary lesion(s) in stable patients when evidence of ischaemia is not available” (class Ia recommendation) (Windecker, 2014). U.S. guidelines state that an FFR of 0.80 or less provides level Ia evidence for revascularization for “significant stenoses amenable to revascularization and unacceptable angina despite guideline directed medical therapy (Fihn, 2012).)
Measuring FFR during invasive coronary angiography (ICA) requires first passing a pressure-sensing guidewire across a stenosis. Coronary hyperemia (increased blood flow) is then induced and pressure distal and proximal to the stenosis is used to calculate flow across it. FFR is the ratio of flow in the presence of a stenosis to flow in its absence. FFR levels less than 0.75 to 0.80 are considered to represent significant ischemia while those 0.94 to 1.0 normal. Measurement is valid in the presence of serial stenoses, is unaffected by collateral blood flow (Pijls, 1995), and reproducibility high (de Bruyne, 1996). Potential complications include adverse events related to catheter use such as vessel wall damage (dissection); the time required to obtain FFR during a typical ICA is less than 10 minutes.  
ICAs are frequently unnecessary in patients with stable ischemic heart disease as evidenced by low diagnostic yields. For example, from a sample of over 132,000 ICAs, Patel and colleagues found 48.8% of elective ICAs performed in patients with stable angina did not detect obstructive coronary artery disease (left main stenosis ≥50% or ≥70% in a major epicardial or branch >2.0mm in diameter ) (Patel, 2010). ICA is clinically useful when patients with stable angina have failed optimal medical therapy and may benefit from revascularization. A test such as FFR-CT that could identify candidates for revascularization—those with significant physiologic obstructions—prior to planned ICA could allow avoiding unnecessary procedures and any adverse consequences.  
Only the HeartFlow FFRCT software has been cleared by the U.S. Food and Drug Administration. Imaging analyses require transmitting data to a central location, taking 1 to 3 days to complete. Other prototype software is workstation-based with onsite analyses. FFR-CT cannot be calculated when images lack sufficient quality13 (11% to 13% in recent studies [Koo, 2011; Min, 2012; Nakazato, 2013; Norgaard, 2014], e.g. in obese individuals (eg, body mass index, >35 kg/m2).
In November 2014, FFRCT simulation software (HeartFlow) was cleared for marketing by the U.S. Food and Drug Administration (FDA) through the de novo 510(k) process (class II, special controls; FDA product code: PJA). In January 2016, the FFRCT v2.0 device was cleared through a subsequent 510(k) process.  
HeartFlow FFRCT postprocessing software is cleared “for the clinical quantitative and qualitative analysis of previously acquired Computed Tomography (CT) DICOM [Digital Imaging and Communications in Medicine] data for clinically stable symptomatic patients with coronary artery disease. It provides FFRCT, a mathematically derived quantity, computed from simulated pressure, velocity and blood flow information obtained from a 3D computer model generated from static coronary CT images. FFRCT analysis is intended to support the functional evaluation of coronary artery disease.” “The results of this analysis [FFRCT] are provided to support qualified clinicians to aid in the evaluation and assessment of coronary arteries. The results of HeartFlow FFRCT are intended to be used by qualified clinicians in conjunction with the patient’s clinical history, symptoms, and other diagnostic tests, as well as the clinician’s professional judgment.”
There is no specific CPT code for Invasively measured fractional flow reserve (FFR).

Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
The use of fractional flow reserve using coronary computed tomography angiography preceding invasive coronary angiography in patients with suspected stable ischemic heart disease does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes:
For members with contracts without primary coverage criteria, the use of fractional flow reserve using coronary computed tomography angiography preceding invasive coronary angiography in patients with suspected stable ischemic heart disease would be considered investigational and not covered for contracts without Primary Coverage Criteria.  Investigational services are an exclusion in the member benefit certificate

This evidence review was originally created in December 2016. MEDLINE database was searched through October 27, 2016 to identify literature assessing the technical performance, diagnostic accuracy, effect of fractional flow reserve using computed tomography angiography (FFR-CT) on patient outcomes, and postadoption studies. HeartFlow also submitted a list of publications and materials for review.
Evidence was organized by phase of diagnostic test development (technical performance, diagnostic accuracy, effect on patient outcomes). Technical performance (phase I) data reported in 2 studies (Johnson, 2015; Guar, 2014) and the Food and Drug Administration (FDA) de novo 510(k) summary were included. Five diagnostic accuracy studies (phase II) were synthesized in 2 2016 meta-analyses. One nonrandomized study and a retrospective cohort study (phase III) have reported effect on patient outcomes. No postadoption use/safety studies (phase IV) were identified.
Data supporting technical performance derive from the test-retest reliability of FFR-CT and invasively measured FFR (reference standard). Other technical performance considerations were summarized in the FDA documentation (HeartFlow, 2011; HeartFlow, 2016).
Johnson and colleagues reported on the repeatability of invasive FFR (Johnson, 2015). Data from 190 paired assessments were analyzed (patients measured twice over 2 minutes). The test-retest coefficient of variation of 2.5% (r2=98.2%) was reported using a “smart minimum” in the analyses (“the lowest average of 5 consecutive cardiac cycles of sufficient quality within a run of 9 consecutive quality beats”). Hulten and Di Carli noted that based on the Johnson results, an FFR of 0.8 would have a 95% confidence interval (CI) of 0.76 to 0.84 (Hulten, 2015). Gaur and colleagues analyzed data from 28 patients (58 vessels) with repeated FFR-CT and invasive FFR measurements (Gaur, 2014). They reported coefficients of variation of 3.4% (95% CI, 1.5% to 4.6%) for FFR-CT and 2.7% (95% CI, 1.8% to 3.3%) for invasive FFR. Although reproducibility was acceptable, whether test-retest reliability over time might be similar is unclear.
The ability to obtain FFR-CT measurements is directly related to the quality of imaging data and values are not calculated for small vessels (<1.8 mm). Nitrate administration is recommended (generally standard practice unless contraindicated) for vasodilatation, and a lack of nitrates can affect FFR-CT results. In addition, the FDA de novo summary lists factors that can adversely impact FFR-CT results including: imaging data quality, incorrect brachial pressure, myocardial dysfunction and hypertrophy, and abnormal physiology (eg, congenital heart disease). Coronary calcium may also have some impact on measurements (Norgaard, 2015).
Section Summary: Technical Performance
The results have indicated that test-retest reliability is acceptable and other known factors can impact variability of FFR-CT results.
Studies Included in Meta-Analyses: Per-Patient Diagnostic Accuracy
Five studies contributed results to two 2016 meta-analyses evaluating the diagnostic accuracy of FFR-CT using patients as the unit of analysis. Only the FDA-cleared HeartFlow software has been evaluated prospectively across multiple sites. Two small retrospective studies have reported per-patient performance characteristics for the prototype Siemens workstation-based software (De Geer, 2016; Renker, 2014). The 3 HeartFlow FFRCT studies used successive software versions with reported improvement in specificity (from 54% to 79%) between versions 1.2 and 1.4 (Koo, 2011; Norgaard, 2014; Min, 2012).  The NXT Trial formed the basis for FDA clearance, and was conducted at 11 sites in 8 countries (Canada, EU, Asia) (Norgaard, 2014). Although not examined in the 2 included meta-analyses, subgroup analyses suggested little variation in results by sex and age (Thompson, 2015). Effectively, the entirety of the data was obtained in patients of white or Asian decent; almost all patients were appropriate for testing according to FDA clearance.
Danad and colleagues included 23 studies published between January 2002 and February 2015 evaluating diagnostic performance of computed tomography angiography (CTA), FFR-CT, single-photon emission computed tomography (SPECT), stress echocardiography (SECHO), magnetic resonance imaging (MRI), or ICA compared with an invasive FFR reference standard (Donad, 2016). The 3 included FFR-CT studies used the HeartFlow software and had performed FFR in at least 75% of patients. A cutoff of 0.75 defined significant stenosis in 8 (32%) studies and in the remainder 0.80 (current standard used in all FFR-CT studies). Per-patient and per-vessel meta-analyses were performed. Study quality was assessed using QUADAS-2 (Whiting, 2011); no significant biases were identified in FFR-CT studies but a high risk of biased patient selection was judged in 10 (43.4%) other studies. HeartFlow funded publication Open Access; 1 author was a consultant to, and another a cofounder of, HeartFlow.
On the patient level, MRI had the highest combined sensitivity (90%; 95% CI, 75% to 97%) and specificity (94%; 95% CI, 79% to 99%) for invasive FFR, but were estimated from only 2 studies (70 patients). FFR-CT had similar sensitivity (90%; 95% CI, 85% to 93%), but lower specificity (71%; 95% CI, 65% to 75%), and accordingly a lower positive likelihood ratio (3.34; 95% CI, 1.78 to 6.25) than MRI (10.31; 95% CI, 3.14 to 33.9). Per-vessel results were similar except for CTA where per-patient results were considerably better (eg, C statistic of 0.85 vs 0.57). The authors noted heterogeneity in many estimates (eg, CTA sensitivity I2 of 80%), as would be anticipated in diagnostic accuracy studies (Macaskill, 2010). Finally, pooled results for specific tests included few studies precluding applying diagnostic meta-analytic approaches30 that account for correlation sensitivities and specificities.
Wu and colleagues identified 7 studies (833 patients, 1377 vessels) comparing FFR-CT with invasively measured FFR from searches of PubMed, Cochrane, EMBASE, Medion, and meeting abstracts through January 2016 (Wu, 2016). Studies included patients with established or suspected stable ischemic heart disease (SIHD). In addition to the 3 FFR-CT studies pooled by Danad and colleagues, 4 additional studies (224 patients) using Siemens cFFR software (not FDA approved or cleared) were identified. An invasive FFR cutoff of 0.80 was the reference standard in all studies. Per-patient (reported in 5 studies) and per-vessel results were pooled. All studies were rated at low risk of bias and without applicability concerns using the QUADAS-2 tool (Whiting, 2011). Appropriate bivariate meta-analyses (accounting for correlated sensitivity and specificity) were used.
As expected given study overlap, FFR-CT performance characteristics were similar to those reported by Danad and colleagues, but with a slightly higher specificity. The pooled per-vessel C statistic was lower (0.86) than the per-patient result (0.90). No evidence of publication bias was detected, but the number of studies was too small to adequately assess. Reviewers noted that, in 2 studies, FFR-CT results were uninterpretable in 12.0% (Norgaard, 2014) and 8.2% (Coenen, 2015) of participants.
We identified 1 observational study and 1 retrospective cohort study that reported outcomes and compared an FFR-CT strategy with usual care (eg, physician choice). We found no studies that compared an FFR-CT strategy with protocol-defined alternative strategies such as one including MRI or perfusion imaging that might be considered currently recommended. No studies were identified using FFR-CT prior to ICA in patients with established coronary artery disease (CAD).
The PLATFORM (Prospective LongitudinAl Trial of FFRCT: Outcome and Resource Impacts) study compared diagnostic strategies with or without FFR-CT in patients with suspected stable angina but without known CAD (Douglas, 2016; Douglas, 2015). The study was conducted at 11 EU sites (ie, practices and ethnicities in the U.S may differ from those in the EU). All testing was nonemergent. Patients were divided into 2 strata according whether the test planned prior to study enrollment was: (1) noninvasive or (2) ICA (the patient population of interest in this evidence review). Patients were enrolled in consecutive cohorts with the first cohort undergoing a usual care strategy followed by a second cohort provided CTA with FFR-CT performed when requested (recommended if stenoses ≥30% were identified). Follow-up was scheduled at 90 days and 6 and 12 months after entry (99.5% of patients had 1-year follow-up data). Funding was provided by HeartFlow and multiple authors reported receiving fees, grants, and/or support from HeartFlow. Data analyses were performed by the Duke Clinical Research Institute.
ICA without obstructive disease at 90 days was the primary end point in patients with planned invasive testing—“(i) invasive FFR ≤0.80 in any segment, regardless of degree of stenosis, or (ii) QCA [quantitative coronary angiography] stenosis ≥50% in a vessel ≥2.0 mm diameter without an invasively measured FFR ≤0.80 in the same distribution.” Secondary end points included ICA without obstructive disease following planned noninvasive testing, and (1) major adverse cardiovascular events (MACE) at 1 year defined as a composite of all-cause mortality, myocardial infarction, and urgent revascularization and (2) MACE and vascular events within 14 days. Quality of life (QOL) was evaluated using the Seattle Angina Questionnaire, and EQ-5D (5-item and 100-point visual analog scale). CTA studies were interpreted by site investigators; quantitative coronary angiography measurements were performed at a central laboratory as was FFR-CT. Cumulative radiation was also assessed. A sample size of 380 patients in the invasive strata yielded 90% power to detect a 50% decrease in the primary end point given a 30% event rate (ICA without obstructive disease) with a usual care strategy and a dropout rate up to 10%.
In the planned invasive stratum, FFR-CT was requested in 134 patients and successfully obtained 117 (87.3%) in the FFR-CT group. At 90 days, 73.3% of those in the usual care group had no obstructive findings on ICA compared with 12.4% in the FFR-CT group based on core laboratory readings (56.7% and 9.3% based on site readings). The difference was similar in a propensity-matched analysis of a subset of participants (n=148 from each group or 78% of the entire sample). Prior noninvasive testing did not appear associated with the rate of nonobstructive findings. MACE rates were low in the planned invasive stratum and did not differ between strategies. Mean level of radiation exposure though 1 year was also similar in both groups with a planned invasive strategy (10.4 and 10.7 mSv with usual care and FFR-CT, respectively). No differences in QOL were found between planned invasive strategy groups (Hlatky, 2015).
In the noninvasive stratum, FFR-CT was requested in 67 patients and obtained in 60 (89.6%) in the FFR-CT group. ICA rates in the usual care and FFR-CT groups were 12.0% and 18.2% respectively. Rates of ICA with no obstructive disease did not differ significantly—usual care group was 6.0% and FFR-CT was 12.5% (difference, -6.5%; 95% CI, -14.4 to 1.4).
Results of the PLATFORM study support the notion that, in patients with planned ICA, FFR-CT can decrease the rate of ICAs and unnecessary procedures (finding no significant obstructive disease) and that FFR-CT may provide clinically useful information to physicians and patients. Study limitations include an observational design, high rate of no obstructive disease with a usual care strategy (73.3%), and somewhat small sample size. Although finding a large effect in patients with planned invasive testing, the observational design limits causal inferences and certainty in the magnitude of effect. The propensity-matched analysis (in a matched subset) offers some reassurance, but the sample size was likely too small to provide robust results. Additionally, approximately half of the patients with planned invasive testing had not undergone noninvasive evaluation. Elective ICA as the initial evaluation of patients with suspected SIHD is infrequently indicated. Finally, the 73.3% rate of ICA without significant obstructive disease in the usual care arm was markedly higher than the 30% rate assumed in the sample size estimates.
Nørgaard and colleagues reported results from symptomatic patients referred for coronary CTA at a single center in Denmark from May 2014 to April 2015 (Norgaard, 2016). All data were obtained from medical records and registries; the study was described as a “review” of diagnostic evaluations and apparently retrospectively conducted. Follow-up through 6 to 18 months was ascertained. From 1248 referred patients, 1173 underwent coronary CTA; 858 received medical therapy, 82 underwent ICA, 44 perfusion imaging, and 189 FFR-CT (185 [98%] obtained successfully). Of the 57 (31%) patients, 1 or more vessels had FFR-CT values of 0.80 or less and 49 (86%) went on to ICA; of the 128 with higher FFR-CT values, only 5 (4%) went on to ICA. The correlation between FFR-CT and invasive FFR was 0.77 from the 51 vessels where both results were obtained; the limit of agreement (95% CI) in FFR values was -0.06 to 0.14.
The authors noted: “This report demonstrates for the first time the real-world feasibility of FFRCT testing in consecutive patients with intermediate-range coronary stenosis.” The implications and generalizability of these single center results are somewhat limited. It is unclear whether ICA was planned in patients undergoing FFR-CT and information on provision and efficacy of medical therapy was unavailable.
Agreement between FFR-CT and invasive FFR appeared similar to the diagnostic studies, but the estimate is subject to verification bias.
Section Summary: Effect on Patient Outcomes
The clinical usefulness of FFR-CT for avoiding ICA has been examined in 1 prospective observational study (PLATFORM) and 1 retrospective cohort study, both conducted outside the United States. Study results support the notion that, for patients with planned ICA, FFR-CT can decrease the rate of ICA and ICA finding no significant obstructive disease, ie, that FFR-CT may provide clinically useful information to clinicians and patients. However, the implications of PLATFORM results must consider its observational design, high rate of no obstructive disease with a usual care strategy (73.3%), limited sample size, EU setting, and generalizability. A single-center Danish retrospective cohort study including 189 patients undergoing FFR-CT was conducted outside investigational settings.  
For individuals who have suspected stable ischemic heart disease and planned invasive coronary angiography (ICA) who receive fractional flow reserve using computed tomography angiography (FFR-CT), the evidence includes studies on test technical performance, 2 meta-analyses of diagnostic accuracy, and 2 studies of patient outcomes. Relevant outcomes are test accuracy and validity, morbid events, quality of life, resource utilization, and treatment-related mortality and morbidity. FFR-CT may offer an effective means to reduce unnecessary ICA with a rationale for a potential role in decision making. Test performance characteristics are consistent with a negative test reducing the probability of significant obstructive disease (eg, vessels with FFR <0.80) and potentially altering a decision to perform ICA. However, outcome data are limited and obtained entirely from nonrandomized studies with comparisons only to usual care. Limitations and uncertainties in body of evidence examining FFR-CT prevent conclusions concerning the net health outcome. The evidence is insufficient to determine the effects of the technology on health outcomes.
Some currently unpublished trials that might influence this review are listed below:
(NCT02805621) Machine leArning Based CT angiograpHy derIved FFR: a Multi-ceNtEr, Registry; planned enrollment 352; projected completion date July 2017.
(NCT02173275) Computed TomoRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia; planned enrollment 618; projected completion date July 2017.
(NCT02208388) Prospective Evaluation fo MyocaRdial PerFUSion CompuEd Tomography Trial; planned enrollment 1000; projected completion date April 2024.
(NCT02499679) Assessing Diagnostic Value of Non-invasive FFRCT in Coronary Care (ADVANCE); planned enrollment 5000; projected completion date February 2021.
2018 Update
A literature search was conducted through September 2018.  There was no new information identified that would prompt a change in the coverage statement.  

0501TNoninvasive estimated coronary fractional flow reserve (FFR) derived from coronary computed tomography angiography data using computation fluid dynamics physiologic simulation software analysis of functional data to assess the severity of coronary artery disease; data preparation and transmission, analysis of fluid dynamics and simulated maximal coronary hyperemia, generation of estimated FFR model, with anatomical data review in comparison with estimated FFR model to reconcile discordant data, interpretation and report
0502TNoninvasive estimated coronary fractional flow reserve (FFR) derived from coronary computed tomography angiography data using computation fluid dynamics physiologic simulation software analysis of functional data to assess the severity of coronary artery disease; data preparation and transmission
0503TNoninvasive estimated coronary fractional flow reserve (FFR) derived from coronary computed tomography angiography data using computation fluid dynamics physiologic simulation software analysis of functional data to assess the severity of coronary artery disease; analysis of fluid dynamics and simulated maximal coronary hyperemia, and generation of estimated FFR model
0504TNoninvasive estimated coronary fractional flow reserve (FFR) derived from coronary computed tomography angiography data using computation fluid dynamics physiologic simulation software analysis of functional data to assess the severity of coronary artery disease; anatomical data review in comparison with estimated FFR model to reconcile discordant data, interpretation and report

References: Coenen A, Lubbers MM, Kurata A, et al.(2015) Fractional flow reserve computed from noninvasive CT angiography data: diagnostic performance of an on-site clinician-operated computational fluid dynamics algorithm. Radiology. Mar 2015;274(3):674-683. PMID 25322342

Danad I, Szymonifka J, Twisk JW, et al.(2016) 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. May 2 2016. PMID 27141095

de Bruyne B, Bartunek J, Sys SU, et al.(1996) Simultaneous coronary pressure and flow velocity measurements in humans. Feasibility, reproducibility, and hemodynamic dependence of coronary flow velocity reserve, hyperemic flow versus pressure slope index, and fractional flow reserve. Circulation. Oct 15 1996;94(8):1842-1849. PMID 8873658

De Geer J, Sandstedt M, Bjorkholm A, et al.(2016) Software-based on-site estimation of fractional flow reserve using standard coronary CT angiography data. Acta Radiol. Oct 2016;57(10):1186-1192. PMID 26691914

Douglas PS, De Bruyne B, Pontone G, et al.(2016) 1-year outcomes of FFRCT-guided care in patients with suspected coronary disease: the PLATFORM Study. J Am Coll Cardiol. Aug 2 2016;68(5):435-445. PMID 27470449

Douglas PS, Pontone G, Hlatky MA, et al.(2015) Clinical outcomes of fractional flow reserve by computed tomographic angiography-guided diagnostic strategies vs. usual care in patients with suspected coronary artery disease: the prospective longitudinal trial of FFR(CT): outcome and resource impacts study. Eur Heart J. Dec 14 2015;36(47):3359-3367. PMID 26330417

Fearon WF, Shilane D, Pijls NH, et al.(2013) Cost-effectiveness of percutaneous coronary intervention in patients with stable coronary artery disease and abnormal fractional flow reserve. Circulation. Sep 17 2013;128(12):1335-1340. PMID 23946263

Fihn SD, Gardin JM, Abrams J, et al.(2012) 2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the diagnosis and management of patients with stable ischemic heart disease: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines, and the American College of Physicians, American Association for Thoracic Surgery, Preventive Cardiovascular Nurses Association, Society for Cardiovascular Angiography and Interventions, and Society of Thoracic Surgeons. J Am Coll Cardiol. Dec 18 2012;60(24):e44-e164. PMID 23182125

Gaur S, Bezerra HG, Lassen JF, et al.(2014) Fractional flow reserve derived from coronary CT angiography: variation of repeated analyses. J Cardiovasc Comput Tomogr. Jul-Aug 2014;8(4):307-314. PMID 25151923

Hlatky MA, De Bruyne B, Pontone G, et al.(2015) Quality-of-life and economic outcomes of assessing fractional flow reserve with computed tomography angiography: PLATFORM. J Am Coll Cardiol. Dec 1 2015;66(21):2315-2323. PMID 26475205

Hulten E, Di Carli MF.(2015) FFRCT: Solid PLATFORM or thin ice? J Am Coll Cardiol. Dec 1 2015;66(21):2324-2328. PMID 26475206

Johnson NP, Johnson DT, Kirkeeide RL, et al.(2015) Repeatability of fractional flow reserve despite variations in systemic and coronary hemodynamics. JACC Cardiovasc Interv. Jul 2015;8(8):1018-1027. PMID 26205441

Kim KH, Doh JH, Koo BK, et al.(2014) A novel noninvasive technology for treatment planning using virtual coronary stenting and computed tomography-derived computed fractional flow reserve. JACC Cardiovasc Interv. Jan 2014;7(1):72-78. PMID 24332418

Koo BK, Erglis A, Doh JH, et al.(2011) 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. Nov 1 2011;58(19):1989-1997. PMID 22032711

Macaskill P, Gatsonis C, Deeks JJ, et al.(2016) Chapter 10: Analysing and Presenting Results. In: Deeks JJ, Bossuyt PM, Gatsonis C (editors). Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy Version 1.0. The Cochrane Collaboration, 2010. 2010;

Min JK, Berman DS, Budoff MJ, et al.(2011) Rationale and design of the DeFACTO (Determination of Fractional Flow Reserve by Anatomic Computed Tomographic AngiOgraphy) study. J Cardiovasc Comput Tomogr. Sep-Oct 2011;5(5):301-309. PMID 21930103

Min JK, Koo BK, Erglis A, et al.(2012) 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. May-Jun 2012;6(3):191-199. PMID 22682261

Min JK, Leipsic J, Pencina MJ, et al.(2012) Diagnostic accuracy of fractional flow reserve from anatomic CT angiography JAMA. Sep 26 2012;308(12):1237-1245. PMID 22922562

Nakazato R, Park HB, Berman DS, et al.(2013) Noninvasive fractional flow reserve derived from computed tomography angiography for coronary lesions of intermediate stenosis severity: results from the DeFACTO study. Circ Cardiovasc Imaging. Nov 2013;6(6):881-889. PMID 24081777

Nørgaard BL, Gaur S, Leipsic J, et al.(2015) Influence of coronary calcification on the diagnostic performance of CT angiography derived FFR in coronary artery disease: a substudy of the NXT Trial. JACC Cardiovasc Imaging. Sep 2015;8(9):1045-1055. PMID 26298072

Nørgaard BL, Hjort J, Gaur S, et al.(2016) Clinical Use of Coronary CTA-Derived FFR for Decision-Making in Stable CAD. JACC Cardiovasc Imaging. Apr 7 2016. PMID 27085447

Nørgaard BL, Leipsic J, Gaur S, et al.(2014) Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: the NXT trial (Analysis of Coronary Blood Flow Using CT Angiography: Next Steps). J Am Coll Cardiol. Apr 1 2014;63(12):1145-1155. PMID 24486266

Patel MR, Peterson ED, Dai D, et al.(2010) Low diagnostic yield of elective coronary angiography. N Engl J Med. Mar 11 2010;362(10):886-895. PMID 20220183

Pijls NH, Van Gelder B, Van der Voort P, et al.(1995) Fractional flow reserve. A useful index to evaluate the influence of an epicardial coronary stenosis on myocardial blood flow. Circulation. Dec 1 1995;92(11):3183-3193. PMID 7586302

Reitsma JB, Glas AS, Rutjes AW, et al.(2005) Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol. Oct 2005;58(10):982-990. PMID 16168343

Renker M, Schoepf UJ, Wang R, et al.(2012) Comparison of diagnostic value of a novel noninvasive coronary computed tomography angiography method versus standard coronary angiography for assessing fractional flow reserve. Am J Cardiol. Nov 1 2014;114(9):1303-1308. PMID 25205628

Task Force Members, Montalescot G, Sechtem U, et al.(2013) 2013 ESC guidelines on the management of stable coronary artery disease: the Task Force on the management of stable coronary artery disease of the European Society of Cardiology. Eur Heart J. Oct 2013;34(38):2949-3003. PMID 23996286

Taylor CA, Fonte TA, Min JK(2013) Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis. J Am Coll Cardiol. Jun 4 2013;61(22):2233-2241. PMID 23562923

Thompson AG, Raju R, Blanke P, et al.(2015) 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. J Cardiovasc Comput Tomogr. Mar-Apr 2015;9(2):120-128. PMID 25819194

Tonino PA, De Bruyne B, Pijls NH, et al.(2009) Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med. Jan 15 2009;360(3):213-224. PMID 19144937

van Nunen LX, Zimmermann FM, Tonino PA, et al.(2015) Fractional flow reserve versus angiography for guidance of PCI in patients with multivessel coronary artery disease (FAME): 5-year follow-up of a randomised controlled trial. Lancet. Nov 7 2015;386(10006):1853-1860. PMID 26333474

Whiting PF, Rutjes AW, Westwood ME, et al.(2011) QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. Oct 18 2011;155(8):529-536. PMID 22007046

Windecker S, Kolh P, Alfonso F, et al.(2014) 2014 ESC/EACTS Guidelines on myocardial revascularization: The Task Force on Myocardial Revascularization of the European Society of Cardiology (ESC) and the European Association for Cardio-Thoracic Surgery (EACTS) Developed with the special contribution of the European Association of Percutaneous Cardiovascular Interventions (EAPCI). Eur Heart J. Oct 1 2014;35(37):2541-2619. PMID 25173339

Wu W, Pan DR, Foin N, et al(2016) Noninvasive fractional flow reserve derived from coronary computed tomography angiography for identification of ischemic lesions: a systematic review and meta-analysis. Sci Rep. 2016;6:29409. PMID 27377422

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