Author + information
- Received July 3, 2018
- Revision received July 27, 2018
- Accepted August 1, 2018
- Published online November 5, 2018.
- Raksha Indorkar, MDa,
- Raymond Y. Kwong, MDb,
- Simone Romano, MDc,
- Brent E. White, MDa,
- Richard C. Chia, MDa,
- Michael Trybula, MDa,
- Kaleigh Evans, MDa,
- Chetan Shenoy, MDd and
- Afshin Farzaneh-Far, MD, PhDa,e,∗ (, )@afshinfarzan
- aDivision of Cardiology, Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
- bDivision of Cardiology, Department of Medicine, Brigham & Women’s Hospital, Harvard Medical School, Boston, Massachusetts
- cDepartment of Medicine, University of Verona, Verona, Italy
- dDivision of Cardiology, Department of Medicine, University of Minnesota, Minneapolis, Minnesota
- eDivision of Cardiology, Department of Medicine, Duke University, Durham, North Carolina
- ↵∗Address for correspondence:
Dr. Afshin Farzaneh-Far, Division of Cardiology, University of Illinois at Chicago, 840 South Wood Street, M/C 715, Suite 920 S, Chicago, Illinois 60612.
Objectives The aim of this study was to evaluate the incremental prognostic value of global coronary flow reserve (CFR) in patients with known or suspected coronary artery disease who were undergoing stress cardiac magnetic resonance (CMR) imaging.
Background Coronary microvascular dysfunction results in impaired global CFR and is implicated in the development of both atherosclerosis and heart failure. Although noninvasive assessment of CFR with positron emission tomography provides independent prognostic information, the incremental prognostic value of CMR-derived CFR remains unclear.
Methods Consecutive patients undergoing stress perfusion CMR were prospectively enrolled (n = 507). Coronary sinus flow was measured using phase-contrast imaging at baseline (pre) and immediately after stress (peak) perfusion. CFR was calculated as the ratio of peak to pre-flow. Patients were followed for major adverse cardiac events (MACE): death, nonfatal myocardial infarction, heart failure hospitalization, sustained ventricular tachycardia, and late revascularization. Cox proportional hazards regression modeling was used to examine the association between CFR and MACE. The incremental prognostic value of CFR was assessed in nested models.
Results Over a median follow-up of 2.1 years, 80 patients experienced MACE. By Kaplan-Meier analysis, the risk of MACE was significantly higher in patients with CFR lower than the median (2.2) (log-rank p < 0.001); this remained significant after adjustment for the presence of ischemia and late gadolinium enhancement (LGE) (log-rank p < 0.001). CFR was significantly associated with the risk of MACE after adjustment for clinical and imaging risk factors, including ischemia extent, ejection fraction, and LGE size (hazard ratio: 1.238; p = 0.018). Addition of CFR in this model resulted in significant improvement in the C-index (from 0.70 to 0.75; p = 0.0087) and a continuous net reclassification improvement of 0.198 (95% confidence interval: 0.120 to 0.288).
Conclusions CMR-derived CFR is an independent predictor of MACE in patients with known or suspected coronary artery disease, incremental to common clinical and CMR risk factors. These findings suggest a role for CMR-derived CFR in identifying patients at risk of adverse events following stress CMR, even in the absence of ischemia and LGE.
- cardiac magnetic resonance imaging
- coronary artery disease
- coronary flow reserve
- coronary microvascular function
- stress testing
The current paradigm for management of coronary artery disease (CAD) primarily revolves around detection and treatment of stenosis in the epicardial coronary arteries. However, these arteries represent only a tiny fraction of the overall coronary circulation, which extends from the large epicardial arteries through pre-arterioles, arterioles, and capillaries before eventually draining back through the venous system into the coronary sinus (CS) (1,2). Moreover, both animal and human data have implicated abnormalities of coronary microvascular function in a broad range of cardiac diseases, including CAD and heart failure (1,2).
Global coronary flow reserve (CFR) is the ratio of total myocardial blood flow at stress to total myocardial blood flow at rest. CFR depends primarily on the ability of the coronary microvasculature to dilate and also on trans-stenotic pressure gradients of the epicardial arteries and thus stenosis severity. Hence, the ability to measure CFR quantitatively allows a more comprehensive assessment of the entire coronary circulation, beyond the current paradigm of the epicardial arteries. Moreover, it has been shown that noninvasive measurement of global CFR using positron emission tomography (PET) provides independent prognostic information in patients with known or suspected CAD (3,4).
Stress cardiac magnetic resonance (CMR) imaging now allows rapid assessment of global CFR by using CS flow measurement (5). However, the incremental prognostic value of CMR-derived CFR remains unclear (6). Therefore, the aim of this study was to evaluate prospectively the incremental prognostic value of CFR in patients with known or suspected CAD who were undergoing stress CMR.
Consecutive patients undergoing stress perfusion CMR for evaluation of known or suspected CAD were prospectively enrolled (n = 507). Of these patients, 38 had uninterpretable image quality for CFR assessment or an inability to complete the full stress protocol, thus leaving 469 patients. The study was approved by the local Institutional Review Board, and all patients provided signed informed consent.
Images were acquired on a 3-T scanner (Philips Achieva, Philips Medical Systems, Best, The Netherlands) using a 6-element phased-array receiver coil. The stress protocol is shown in Figure 1. Steady-state free-precession cine images were acquired in multiple short-axis and 3 long-axis views (repetition time, 3.0 ms; echo time, 1.5 ms; flip angle, 40°; slice thickness, 6 mm). Short-axis views were obtained every 1 cm to cover the entire left ventricle.
The patient table was then partially pulled outside the scanner bore to allow direct observation of the patient and full access. A 0.4-mg bolus of regadenoson (Lexiscan, Astellas Pharma, Northbrook, Illinois) was infused under continuous electrocardiography. Approximately 1 min after regadenoson administration, the perfusion sequence was applied, and gadolinium contrast (0.075 mmol/kg) followed by a saline flush (30 ml) was infused (4.5 ml/s) through an antecubital vein. On the console, the perfusion images were observed as they were acquired, with breath-holding starting from the appearance of contrast in the right ventricular cavity. Imaging was completed 10 to 15 s after the gadolinium bolus had transited the left ventricular myocardium. Perfusion images consisted of 3 to 4 short-axis slices obtained every heartbeat with a saturation-recovery, gradient-echo sequence (repetition time, 2.8 ms; echo time, 1.1 ms; flip angle, 20°; voxel size, 2.5 × 2.5 × 8 mm). Aminophylline, 100 mg intravenously, was administered immediately after stress perfusion imaging. Rest perfusion images were acquired 15 min after stress imaging with an additional contrast bolus (0.075 mmol/kg) using identical sequence parameters. Five minutes after rest perfusion, late gadolinium enhancement (LGE) imaging was performed with a 2-dimensional segmented gradient-echo phase-sensitive inversion-recovery sequence in the same views as cine CMR. Inversion delay times were typically 280 to 360 ms.
Coronary sinus imaging
The CS was identified in the atrioventricular groove, on the basal slices of the short-axis stack (Figure 2A). The plane for flow measurement was prescribed parallel to the long-axis of the heart on the 4-chamber view and perpendicular to the direction of flow in the CS, approximately 0.5 cm from the ostium (Figure 2B). Velocity-encoded images were acquired with retrospective electrocardiographic gating during 12- to 18-s breath-holds (slice thickness, 6 mm; in-plane resolution, 1.3 × 1.3 mm; temporal resolution, 35 to 55 ms; and velocity encoding, 60 cm/s) (Figures 2C and 2D). These images were acquired in the baseline (“pre”) state, as well as immediately after stress (peak) perfusion (Figures 2E and 2F).
CMR analysis and CFR assessment
LGE and perfusion images were blindly interpreted by standard methods, as described previously (7–14). LGE was scored visually on a 17-segment model with a 5-point scale for each segment (0 = no LGE; 1 = 1% to 25%; 2 = 26% to 50%; 3 = 51% to 75%; 4 = 76% to 100%). LGE extent as a percentage of left ventricular myocardium was calculated by summing the regional scores, each weighted by the LGE range midpoint (i.e., 1 = 13%; 2 = 38%; 3 = 63%; 4 = 88%) and dividing by 17 (7–10). Stress perfusion CMR images were evaluated according to a 16-segment model (American Heart Association 17-segment model minus the apical segment). The analysis of perfusion images was done visually by applying criteria similar to those used in many prior stress CMR studies (11–14). An ischemic segment was defined as follows: The myocardium appears dark for ≥3 frames after peak myocardial enhancement and is >1 pixel wide and resides in viable (LGE-negative) myocardium and conforms to the distribution territory of 1 or more coronary arteries. The total number of ischemic segments was calculated for each patient.
Blinded quantitative analysis of CS flow was performed on standard commercial workstations (Precession, HeartIT, Durham, North Carolina). The contour of the CS was traced on the phase-contrast magnitude images throughout the cardiac cycle (Figure 2). CS flow was calculated at baseline (pre) and immediately after stress (peak) perfusion. Measurements were performed manually by a single physician, who was blinded to patients’ outcomes and information.
Patients were followed up for the combined primary outcome of major adverse cardiac events (MACE): death, nonfatal myocardial infarction (MI), hospitalization for heart failure, sustained ventricular tachycardia (VT), and late revascularization (>90 days after CMR). Two cardiologists blinded to CMR results performed all standardized follow-up procedures. Clinical follow-up was obtained by review of the electronic medical records. In cases where records were not found in the medical chart, treating physicians and patients were contacted using a standardized questionnaire. Nonfatal MI was defined by the presentation of an acute coronary syndrome and elevation of cardiac biomarkers (>99th percentile of the upper limit of normal), temporally consistent with an acute injury. The definition of heart failure hospitalization required the presence of an elevated B-type natriuretic peptide (BNP) level in addition to signs and symptoms of heart failure. The Social Security Death Index was used to confirm all cases of death. Time to event was calculated as the period between the CMR study and the first occurrence of MACE. Patients who did not experience MACE were censored at time of last follow-up.
Normally distributed data were expressed as mean ± SD. Differences in baseline characteristics were compared with Student’s t-test for continuous variables and the chi-square test for dichotomous variables. Interobserver variability of CFR was analyzed using the Bland-Altman method in a random sample of 50 patients measured by a second blinded physician. In addition, a kappa value was calculated to assess interobserver agreement in categorizing CFR as normal or abnormal (normal was defined as equal to or greater than the median value obtained in the entire study group). Kaplan-Meier methods were used to evaluate the relationship between CFR and time to the primary outcome of MACE. We used Cox proportional hazards regression modeling to examine the association between CFR and MACE. Models were assessed for collinearity and proportional hazards assumption. For the multivariable models, clinical and imaging risk factors which were univariate predictors (at p ≤ 0.10) were considered as covariates. Two multivariate analyses were performed. In model 1, continuous variables were used for LGE size and ischemia extent, whereas in model 2 ischemia and LGE were introduced as dichotomous variables according to the Youlden index after using receiver-operating characteristic (ROC) curves to determine the optimal cutoff for prediction of MACE (12). To assess the added prognostic value of CFR, the final model was compared with a model in which CFR was not included. Model discrimination was compared by calculating the C-index (15). Risk reclassification analyses were conducted with calculation of continuous net reclassification improvement (NRI) (16). A p value of <0.05 was considered statistically significant. Analyses were performed using STATA software (StataCorp, College Station, Texas).
Table 1 summarizes baseline patient characteristics stratified by CFR higher and lower than the median (2.2). The mean age of the study participants was 58.4 ± 12.9 years. Forty-five percent of patients were male, and 34.5% had diabetes mellitus. The mean ejection fraction (EF) was 59.8 ± 12.0%, and LGE was present in 17.3% of patients. Primary indications for stress testing were chest pain (68%), dyspnea (16%) and pre-operative evaluation (11%), with about 11% for a mixture of other indications, including abnormal electrocardiogram, nonsustained VT, premature ventricular contractions, syncope, and new cardiomyopathy. Some patients had more than 1 indication for stress testing.
Bland-Altman analysis of interobserver repeatability for CFR showed a bias of –0.014. Ninety-five percent limits of agreement were –0.313 to 0.342. The Bland-Altman plot showed no systematic bias (Online Figure 1). The interobserver agreement for detection of abnormal CFR was very good (kappa = 0.93, SD = 0.1413; p < 0.001).
Of the 469 patients who completed the protocol, 80 (17%) had MACE during a median follow-up of 2.1 years (interquartile range: 0.7 to 3.9 years) (death, 19; MI, 21; heart failure hospitalization, 13; sustained VT, 2; late revascularization, 25).
Outcomes stratified by CFR
When stratified by the median value of CFR (2.2), Kaplan-Meier analysis showed significantly increased risk of MACE in participants with CFR lower than the median (log-rank p < 0.001) (Figure 3). Similarly, when using only the endpoints of death, MI, heart failure hospitalization, and VT (i.e., excluding late revascularization), Kaplan-Meier analysis still showed significantly increased risk of MACE in participants with CFR lower than the median (log-rank p = 0.005) (Online Figure 2). The optimal CFR cutoff on the basis of ROC curves was 2.2 (sensitivity, 55%; specificity, 70%), which was the same as the median value.
Annualized event rates stratified by CFR in the presence or absence of ischemia or LGE are shown in Figure 4. This shows that in patients with no ischemia, those with CFR lower than the median had a significantly higher annualized event rate compared with those with CFR greater than or equal to the median (8.6% vs. 3.8%; p = 0.002). Moreover, in patients with no LGE, those with CFR lower than the median had a significantly higher annualized event rate compared with those with CFR greater than or equal to the median (9.3% vs. 3.9%; p = 0.001). The Kaplan-Meier analysis in Figure 5 shows that, after adjustment for presence of ischemia and LGE, there is still significantly greater risk of MACE in those patients with CFR lower than the median compared with those with CFR greater than or equal to the median (stratified log-rank p < 0.001). Similarly, when using only the endpoints of death, MI, heart failure hospitalization, and VT (i.e., excluding late revascularization), Kaplan-Meier analysis still showed significantly increased risk of MACE in those patients with CFR lower than the median after adjustment for presence of ischemia and LGE (stratified log-rank p = 0.006) (Online Figure 3).
Multivariable analysis and incremental prognostic value
After adjustment for clinical and imaging risk factors, which were univariate predictors at p ≤ 0.10 (sex, diabetes, hyperlipidemia, history of MI, heart rate, left ventricular end-systolic volume index, ischemia extent, LGE size, EF), CFR remained a significant independent predictor of MACE (hazard ratio: 1.238 per unit decrease; p = 0.018); that is, each unit decrement in CFR was associated with a 23.8% increase risk of MACE (Table 2, model 1). Addition of CFR into the model with clinical and imaging predictors resulted in significant increase in the C-index (from 0.70 to 0.75; p = 0.0087) and a continuous NRI of 0.198 (95% confidence interval: 0.120 to 0.288). When using ischemia extent ≥6.25% and LGE size ≥1% as dichotomized variables (on the basis of optimal cutoffs from ROC curves), CFR remained a significant independent predictor of MACE (hazard ratio: 1.227 per unit decrease; p = 0.027); that is, each unit decrement in CFR was associated with a 22.7% increase risk of MACE (Table 2, model 2). Addition of CFR into the model with clinical and imaging predictors resulted in significant increase in the C-index (from 0.70 to 0.75; p = 0.0070) and a continuous NRI of 0.078 (95% confidence interval: 0.054 to 0.118).
This study shows that global CFR derived from CS flow measurements is a powerful independent predictor of MACE in patients with known or suspected CAD who are undergoing stress CMR. We have demonstrated that CFR provides prognostic information incremental to common clinical and CMR risk factor, including EF, ischemia, and LGE. Its measurement requires no specialized pulse sequences or ionizing radiation. These findings suggest a role for CMR-derived CFR in identifying patients at risk of MACE following stress CMR, even in the absence of ischemia and LGE.
Several studies have shown that noninvasive measurement of global CFR with PET provides significant additive prognostic information during stress perfusion imaging in patients with known or suspected CAD (3,4,17,18). PET also allows regional measurement of CFR, thus permitting localization to particular arterial territories. However, PET imaging uses ionizing radiation and requires an on-site rubidium-82 generator (4). Therefore other modalities may be useful in some centers. Quantitative perfusion mapping by CMR also allows assessment of both local and global CFR, although to date these methods have had limited uptake because of their relatively time-consuming post-processing, which has prohibited easy integration into clinical work flows (19–21). Recent development of automated analysis techniques may hold future promise in improving ease of clinical use for these CMR perfusion mapping methods (22).
We and others have previously reported an alternative, simple CMR method for measurement of CFR by quantifying change in CS flow by using phase-contrast imaging (5,23–29). The CS drains approximately 96% of total myocardial blood flow and provides a potentially convenient location for measurement of global myocardial blood flow (30). This method has been validated against both invasive and PET techniques in animals, healthy volunteers, and patients with CAD (24,25,27,28). We have previously shown that acquisition of CS flow is readily feasible in most patients within a typical stress perfusion CMR protocol, adding approximately 2 to 3 min to overall scanning time, and it has good interobserver reproducibility (5). In the current study we have again demonstrated good interobserver reproducibility with a bias of −0.014. Ninety-five percent limits of agreement were −0.313 to 0.342. The Bland-Altman plot showed no systematic bias (Online Figure 1), and interobserver agreement for detection of abnormal CFR was very good (kappa = 0.93, SD = 0.1413; p < 0.001).
Recently, Kato et al. (6) assessed the prognostic value of CFR derived from CS phase-contrast CMR in 276 patients with known CAD and 400 patients with suspected CAD. Over a follow-up of 2.3 years, there were 22 MACE in patients with known CAD and 25 in patients with suspected CAD. These investigators showed that CFR was associated with MACE in both groups by using unadjusted analyses. However, the area under the curve for prediction of MACE was not significantly different between CFR and stress perfusion. Moreover, their multivariable models were very significantly overfitted (22 events with 13 variables for patients with known CAD; and 25 events with 11 variables for patients with suspected CAD). Thus that study did not demonstrate any significant independent or additive value of CS-derived CFR over clinical and imaging predictors (6).
In our study we have demonstrated for the first time that CS-derived CFR provides prognostic information incremental to common clinical and CMR risk factors, including EF, ischemia extent, and LGE size (hazard ratio: 1.238 per unit decrease; p = 0.018). Moreover, addition of CFR in this model resulted in significant improvement in the C-index (0.70 to 0.75; p = 0.0087) and a continuous NRI of 0.198 (95% confidence interval: 0.120 to 0.288). Figures 4 and 5, as well as Online Figure 3, suggest a role for CMR-derived CFR in identifying patients at risk of adverse events following stress CMR, particularly those patients with normal stress perfusion and no LGE.
Potential mechanisms linking CFR to prognosis
Both animal and human data have implicated abnormalities of coronary microvascular function in the pathogenesis of a broad range of cardiac diseases, including CAD and heart failure (1,2). Consistent with this, we have shown in this study that impaired global CFR is independently associated with both adverse coronary and heart failure events. Although CFR is determined primarily by coronary microvascular function, it can also be affected by epicardial vessel stenosis epicardial and diffuse atherosclerosis. Because we showed that the prognostic value of CFR was independent of ischemia, it is likely that abnormalities of microvascular function are important drivers of impaired CFR in this study. Such abnormalities have been described in early stages of atherogenesis in patients without overt CAD or angiographically normal coronary arteries, and they have been linked to disease progression and adverse cardiovascular events, including sudden cardiac death, MI, and coronary revascularization (2,4).
Some studies have suggested a role for microvascular dysfunction in the pathogenesis of heart failure, even in the absence of epicardial coronary disease (31–34). Impaired CFR has been demonstrated in patients with heart failure with both reduced and preserved ejection (31,33,35). Moreover, impaired CFR measured by PET appears to be associated with increased risk of adverse events in these patients (31,33,35). Some of the proposed mechanisms for alterations in CFR in patients with heart failure include autonomic nervous system dysfunction, microvascular obstruction, changes in myocardial capillary density, and alterations in extravascular compressive forces (2,32).
Studies have shown the high diagnostic accuracy of stress CMR for the detection of epicardial CAD (14). The addition of a simple, rapid method of CFR measurement provides another prognostic tool in the CMR armamentarium that integrates the hemodynamic effects of epicardial coronary stenosis, diffuse atherosclerosis, and microvascular dysfunction on myocardial tissue perfusion. In patients with normal stress CMR perfusion, abnormalities of CFR are most likely the result of microvascular dysfunction and diffuse atherosclerosis, rather than epicardial coronary stenosis. Clinically, our findings may be useful in patients without ischemia or scar, who typically may be discharged from follow-up after “normal” stress CMR. Our results suggest that in the presence of impaired CFR such patients are at significantly greater risk of adverse clinical events and may need continued close follow-up and perhaps aggressive risk factor modification. Clearly, future studies are needed to support such an approach by showing improved clinical outcomes. However, at the present time it is not clear whether and how the finding of impaired CFR should direct specific therapy.
On a broader scale, currently there are no randomized data supporting the use of any stress imaging modality for selection of patients for revascularization or for guidance of medical therapy. Observational data have suggested a paradigm that patients with greater degrees of ischemia on noninvasive imaging are more likely to benefit from revascularization, but this approach awaits prospective confirmation (36). Having a simple tool to easily measure and follow CFR by CMR may provide insights into optimizing treatment strategies, and this is an area of active investigation. For example, a recent single-center PET study has suggested that early revascularization is associated with a more favorable prognosis only in patients with a low global CFR, and that patients with a low CFR may benefit more from coronary artery bypass grafting than from percutaneous coronary intervention (37).
This was a single-center study and may therefore be subject to referral bias, and it carries all of the inherent limitations of that study design. Moreover, because this was a CMR study, there is further selection bias related to being able to undergo a CMR examination, thus resulting in exclusion of patients with large body size, severe renal impairment, severe claustrophobia, or with pacemakers and implantable cardioverter-defibrillators.
There are a number of technical limitations to our study that must be borne in mind. The normal adult CS diameter has been reported as being around 8.3 ± 2.5 mm at mid-diastole (30). With the current in-plane resolution of 1.3 × 1.3 mm, only a limited number of voxels will be located within the lumen of the vessel, thereby resulting in partial volume errors. Moreover, the CS is a mobile structure resulting in errors from through-plane and in-plane motion. Misalignment of the imaging plane is another potential source of error. Another potential cause of concern is phase-offset errors, particularly given the low velocities in the CS. We did not use phantoms or stationary correction schemes for this study, partly to keep scanning and post-processing times within the limits of a typical clinical protocol.
There is also considerable anatomic variation in cardiac venous anatomy. In particular, the insertion of the medial cardiac vein may be very close to the orifice of the CS, and thus its contribution to flow volume may be missed. Of the 507 patients recruited in this study, 38 (7%) had uninterpretable image quality for CFR assessment or an inability to complete the full stress protocol. Because our stress CS flow images were obtained during a typical stress perfusion protocol, the post-contrast (peak flow) images may have higher signal-to-noise compared with the resting flow images. Thus, our CFR values could have been slightly different if both rest and stress acquisitions had been obtained without contrast. Additionally, in this study we prospectively decided to measure the simplest possible parameters and did not make pressure-product adjustments to baseline CS flow. We strongly believe that simple, rapid techniques are more likely to be used in busy clinical laboratories. Moreover, our results stand on their own and clearly demonstrate that this simple CFR measurement is an important independent predictor of adverse events, incremental to standard clinical and imaging variables.
In this prospective, single-center study, global CFR derived from CS flow measurements is a significant independent predictor of adverse cardiovascular events in patients with known or suspected CAD, incremental to common clinical and imaging risk factors including EF, ischemia extent, and LGE size. Our findings suggest a role for CMR-derived CFR in identifying patients at risk of adverse events following stress CMR, even those patients with normal stress perfusion and no LGE. Further work is required to investigate whether and how quantitative measurements of CFR may direct therapy.
COMPETENCY IN MEDICAL KNOWLEDGE: Global CFR derived from CS flow during stress CMR is a significant independent predictor of adverse cardiovascular events, incremental to common clinical and imaging risk factors.
TRANSLATIONAL OUTLOOK: Additional studies are needed to validate these findings in a multicenter setting and to test whether CS flow−derived CFR can help guide therapies to improve outcomes.
Dr. Shenoy was supported by National Institutes of Health grant K23HL132011. Dr. Farzaneh-Far has received partial funding support from Astellas Pharma, but the company had no input on study design, endpoint adjudication, cardiac magnetic resonance interpretation, data analysis, or manuscript writing. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
Dudley Pennell, MD, served as Guest Editor for this paper.
- Abbreviations and Acronyms
- coronary artery disease
- coronary flow reserve
- cardiac magnetic resonance
- coronary sinus
- ejection fraction
- late gadolinium enhancement
- major adverse cardiac events
- myocardial infarction
- net reclassification improvement
- positron emission tomography
- ventricular tachycardia
- Received July 3, 2018.
- Revision received July 27, 2018.
- Accepted August 1, 2018.
- 2018 American College of Cardiology Foundation
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