Background: This study investigated the prognostic value of cardiovascular magnetic resonance (CMR)-derived global coronary flow reserve (G-CFR) in addition to cardiopulmonary exercise testing (CPET) variables in patients with acute myocardial infarction (AMI).

Methods and Results: We investigated 127 patients with AMI who underwent primary or urgent percutaneous coronary intervention (PCI) and post-intervention CMR and CPET. The incidence of major cardiac and cerebrovascular events (MACCE), defined as all-cause death, recurrent non-fatal myocardial infarction, re-hospitalization due to congestive heart failure, and stroke, was evaluated (median follow-up, 2.8 years). Patients with MACCE (n=14) had lower ejection fraction (EF) (50 [43–59] vs. 58 [51–63]%; P=0.014), lower G-CFR (1.74 [1.19–2.20] vs. 2.40 [1.61–3.66]; P=0.008), and lower peak oxygen consumption (V̇O₂) (15.16±2.64 vs. 17.19±3.70 mL/kg/min; P=0.049) than patients without MACCE. G-CFR<2.33 and peak V̇O₂ <15.65 mL/kg/min (cut-off values derived from receiver operating characteristic curve analyses) were significantly associated with the incidence of MACCE (log-rank test, P=0.01). The combination of low G-CFR and low peak V̇O₂ improved risk discrimination for MACCE when added to the reference clinical model including age, male sex, post-PCI peak creatine kinase, EF, and left anterior descending artery culprit lesion.

Conclusions: G-CFR and peak V̇O₂ showed incremental prognostic information compared with the reference model using historically important clinical risk factors, indicating that this approach may help identify high-risk patients who suffer subsequent adverse events.

The increased utilization of primary percutaneous coronary intervention (PCI) has reduced the mortality rate after acute myocardial infarction (AMI); however, the development of heart failure (HF) after AMI still contributes to the increased risk of mortality.¹ Therefore, prognostication and risk stratification for adverse outcomes after PCI is of utmost interest in patients with AMI.

Cardiopulmonary exercise testing (CPET) is a non-invasive method widely used to estimate exercise capacity and predict outcomes.^2,3 In contrast, recent studies reported the predictive significance of global coronary flow reserve (G-CFR) assessed using non-invasive imaging modalities including positron emission tomography (PET)^4,5 and cardiovascular magnetic resonance (CMR).^6,7 However, the prognostication of combined application of CMR and CPET findings remains to be determined in patients with AMI.

In the present study, we aimed to investigate the prognostic value of CMR-derived G-CFR in addition to CPET variables in patients with AMI.

This retrospective analysis included patients from the institutional AMI registry database enrolled between November 2014 and June 2022 at Tsuchiura Kyodo General Hospital. In this registry, 752 patients with AMI who underwent primary or urgent PCI were screened. Of the total 752 patients screened, 127 patients with AMI who underwent post-intervention CMR and CPET were identified and studied (Figure 1). Diagnosis of AMI included ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI), according to the previously reported definition.⁸ The Global Registry of Acute Coronary Events (GRACE) score was calculated on admission for each patient.⁹ Laboratory data were obtained on admission. In patients with multivessel disease, when significant non-infarct-related artery stenoses were considered as candidates for revascularization by physiological assessment, an ad-hoc procedure at the time of the index primary/urgent PCI or a planned staged procedure during the index hospitalization was performed. Post-intervention CMR and CPET were performed after non-infarct-related lesion revascularization in patients with multivessel disease. Patient characteristics, angiography findings of the culprit lesions, post-PCI peak creatine kinase (CK) values, CMR findings, CPET findings, and the incidence of major cardiac and cerebrovascular events (MACCE) during the follow-up period were evaluated. All patients were managed with optimal medical therapy according to the latest guidelines.^10,11 Representative images of a case presenting with AMI are shown in Figure 2.

Figure 1.

Study flow diagram. AMI, acute myocardial infarction; CMR, cardiovascular magnetic resonance; CPET, cardiopulmonary exercise testing; PCI, percutaneous coronary intervention.

Figure 2.

Representative images of a 56-year-old man who presented with ST-elevation myocardial infarction (STEMI) of the anterior wall. (A) Pre-percutaneous coronary intervention (PCI) angiogram revealed total occlusion in the proximal left anterior descending artery. (B) PCI was successfully performed and Thrombolysis in Myocardial Infarction flow grade 3 was obtained. (C) The proximal coronary sinus was detected in the cross-section on the magnitude and phase-contrast cine-magnetic resonance image (red arrow indicates coronary sinus). The global coronary flow reserve of this patient was 2.31. (D) Cardiopulmonary exercise testing revealed that peak oxygen consumption (V̇O₂) was 15.6 mL/kg/min. (E) This patient suffered from STEMI of the inferior wall 16 months later.

This study was conducted in accordance with the Declaration of Helsinki. The study protocol was approved by the institutional ethics committee on human research of Tsuchiura Kyodo General Hospital (approval number: 2022FY68). All patients provided written informed consent for enrollment in the institutional AMI registry database for potential future investigations. All patient data and procedural details were obtained from their medical records and the institutional AMI registry database.

Each patient underwent selective coronary angiography and primary or urgent PCI via the radial artery with a 6-Fr system. PCI was performed according to the standard technique. The PCI strategy was determined by the interventionist and the use of intravascular imaging was left to the operator’s discretion. All patients were treated with coronary drug-eluting stent implantation and the stent type was selected at the operator’s discretion. Quantitative coronary angiography and intravascular imaging findings were used to help determine the appropriate stent size and obtain optimal stent expansion. The culprit lesion was identified based on angiography findings, electrocardiogram (ECG) changes, and/or left ventricular (LV) wall motion abnormalities. In patients with multiple stenoses, the culprit lesion was identified as the lesion having the most severe stenosis or with evidence of recent plaque disruption such as filling defect suggestive of thrombus on angiogram.

CMR image acquisition was performed using a 1.5-Tesla scanner (Achieva, Philips Medical Systems, Best, The Netherlands) with 32-channel cardiac coils within 30 days after PCI, as previously described.⁷ Late gadolinium enhancement (LGE) images were acquired 15 min after the injection of gadolinium contrast (0.10 mmol/kg). All CMR images were analyzed using a dedicated workstation (Virtual Place, AZE Ltd, Tokyo, Japan) by two independent investigators who were blinded to clinical and angiography data. Microvascular obstruction (MVO) was defined as the hypo-enhanced region within and included in the infarcted myocardium. Quantitative analyses of coronary sinus flow (CSF) by phase contrast (PC) cine-CMR were performed using a dedicated workstation (ViewForum, Philips Medical Systems, Best, The Netherlands) by two independent investigators who were blinded to clinical and angiography data. PC-CMR of the coronary sinus (CS) measurements was performed during maximal hyperemia and at rest. Maximal stable hyperemia was induced by using intravenous adenosine triphosphate (160 μg/kg/min through a central vein). The duration between the end of hyperemia and the resting image acquisition was 10 min. The CS contour was traced on the magnitude images throughout the cardiac cycle. CSF was quantified by integrating the flow rates from each cardiac cycle and multiplying them by the mean heart rate during the acquisition period. The resting CSF values were corrected using rate pressure products as follows: rate pressure product (RPP) = systolic blood pressure (mmHg) × heart rate (beats/min); corrected CSF (mL/min) = (CSF / RPP) × 10,000; and corrected CSF (mL/min/g) = corrected CSF / LV mass (g).^7,12 G-CFR was evaluated by using the corrected CSF reserve, which was calculated as CSF during maximal hyperemia divided by corrected CSF at rest.⁷

CPET was performed on an upright cycle ergometer (StrengthErgo 8, BK-ERG-121; Mitsubishi Electric Engineering, Tokyo, Japan) with an ECG machine (Stress Test System, ML-9000; Fukuda Denshi, Co., Ltd, Tokyo, Japan) within 30 days after PCI. All patients underwent cardiac rehabilitation after AMI, prior to CPET. Anaerobic threshold (AT) and peak oxygen consumption (V̇O₂) were assessed using symptom-limited exercise testing. The ramp CPET protocol included a 4-min rest and a 4-min warm-up period at 0 watt (W), followed by a continuous increase in the work rate by 1 W every 6 s until exhaustion. The increments in work rate level were selected based on the patients’ ability to perform the exercises within 8–12 min. V̇O₂, carbon dioxide production (V̇CO₂), and minute ventilation (V̇E) were measured on a breath-by-breath basis using a gas analyzer (Aeromonitor, AE-310S; Minato Medical Science Co., Ltd, Osaka, Japan). AT was measured using the V-slope method.¹³ V̇E/V̇CO₂ slope was calculated using linear regression of V̇E and V̇CO₂ obtained from the start of incremental exercise to the respiratory compensation point. Peak V̇O₂ was determined as V̇O₂ at the highest work rate. Peak oxygen (O₂) pulse was defined as peak V̇O₂ divided by peak heart rate. The predicted values of peak V̇O₂ and peak O₂ pulse were determined based on the data from a healthy Japanese population.¹⁴

All patients were followed up for the primary outcome of MACCE defined as the composite of all-cause death, recurrent non-fatal myocardial infarction (MI), re-hospitalization due to congestive HF, and stroke. Clinical endpoints were determined by the assessment of hospital records or via telephone interviews. Time to event was calculated as the period between the PCI procedure and the first occurrence of MACCE. Patients without MACCE were censored at the time of last follow-up.

All analyses were performed using R for Windows 4.1.1 (The R Foundation, Vienna, Austria). Categorical data were expressed as absolute frequencies and percentages, and compared using the chi-square test or Fisher’s exact test, as appropriate. Normality of data distribution was assessed using the Shapiro-Wilk test. Continuous variables were expressed as mean±standard deviation for normally distributed variables and as median (interquartile range [IQR]) for non-normally distributed variables, and compared using the Student’s t-test, one-way analysis of variance, or Mann-Whitney test, as appropriate. Correlation was evaluated using the Pearson correlation coefficient. A P value <0.05 was considered statistically significant. The area under the curve (AUC) by receiver operating characteristic (ROC) analysis was used to assess the diagnostic accuracy of G-CFR, peak V̇O₂, and peak O₂ pulse for predicting MACCE. Survival curves using the Kaplan-Meier methods were produced for predicting MACCE based on the cut-off values of G-CFR, peak V̇O₂, and peak O₂ pulse derived from the ROC curve analyses, and they were compared using the log-rank test. Four prediction models were used to determine the incremental discriminatory and reclassification performance for identifying the predictors of MACCE. Clinical model 1 as the reference model included established or historically reported significant factors associated with MACCE (age, male sex, post-PCI peak CK value, LV ejection fraction [LVEF], left anterior descending [LAD] culprit). Clinical model 2 included a combination of Clinical model 1 and G-CFR. Clinical model 3 included a combination of Clinical model 2 and peak V̇O₂. Clinical model 4 included a combination of Clinical model 2 and peak O₂ pulse. The discriminatory abilities of Clinical models 2–4 were assessed by the reclassification performance of each model using the relative integrated discrimination improvement (IDI) and category-free net reclassification improvement (NRI) values.

Of the total 127 patients, the median age was 58 years, and 115 (90.6%) patients were male. Ninety-six (75.6%) patients presented with STEMI. MACCE occurred in 14 (11.0%) patients during the follow-up period (median [IQR], 2.8 [2.0, 4.5] years). Patients’ baseline clinical characteristics and laboratory findings of the study population are described in Table 1. Patients with MACCE had lower LVEF (50 [43, 59] vs. 58 [51, 63] %; P=0.014) than patients without MACCE. There was no significant difference in the angiography findings between patients with and without MACCE (Table 1).

CMR findings are summarized in Table 2. Median time between PCI and CMR was 10 [8, 14] days. Patients with MACCE had lower G-CFR (1.74 [1.19, 2.20] vs. 2.40 [1.61, 3.66]; P=0.008) than those without MACCE. Patients with MACCE had a trend towards greater CSF at rest (129.78 [108.73, 139.29] vs. 99.31 [65.86, 137.41]; P=0.064) compared with those without MACCE.

CPET findings are summarized in Table 3. Median time between PCI and CPET was 11 [8, 14] days. Patients with MACCE had greater V̇E/V̇CO₂ slope (41.44±8.53 vs. 37.38±5.90; P=0.023) and lower workload (46.64±12.79 vs. 58.91±19.19 W; P=0.022) at AT than those without MACCE. Patients with MACCE had lower peak V̇O₂ (15.16±2.64 vs. 17.19±3.70 mL/kg/min; P=0.049), lower peak O₂ pulse (8.73±2.18 vs. 10.36±2.32 mL/beat; P=0.014), and greater minimum V̇E/V̇CO₂ (38.30±7.14 vs. 34.03±5.27 mL/min; P=0.007) than those without MACCE.

During the follow-up period (median [IQR], 2.8 [2.0, 4.5] years), the incidence of MACCE was 11.0%; 3 (2.4%) patients died, 7 (5.5%) patients experienced recurrent non-fatal MI, 3 (2.4%) patients experienced re-hospitalization due to congestive HF, and 3 (2.4%) patients experienced stroke.

ROC curve analysis showed that the best cut-off values of G-CFR, peak V̇O₂, and peak O₂ pulse for predicting MACCE were 2.33 (AUC=0.717; sensitivity, 0.929; specificity, 0.531; accuracy, 0.575), 15.65 mL/kg/min (AUC=0.660; sensitivity, 0.643; specificity, 0.664; accuracy, 0.661), and 9.25 mL/beat (AUC=0.693; sensitivity, 0.714; specificity, 0.673; accuracy, 0.677), respectively. There was no correlation of G-CFR with peak V̇O₂ (r=−0.0008; P=0.993) and peak O₂ pulse (r=−0.060; P=0.506). Survival curves demonstrated that low G-CFR and low peak V̇O₂ were significantly associated with the incidence of MACCE (chi-square=11.2; P=0.01; Figure 3). Low G-CFR and low peak O₂ pulse were also significantly associated with the incidence of MACCE (chi-square=15.8; P=0.001; Supplementary Figure). The combination of low G-CFR and low peak V̇O₂ improved risk discrimination for MACCE when added to the reference clinical model including age, male sex, post-PCI peak CK values, LVEF, and LAD culprit (continuous NRI=0.613; P=0.024; relative IDI=0.026; P=0.244; Table 4). The combination of low G-CFR and low peak O₂ pulse also improved risk discrimination for MACCE when added to the reference clinical model (continuous NRI=0.756; P=0.003; relative IDI=0.056; P=0.039; Supplementary Table).

Figure 3.

Survival curves for predicting major cardiac and cerebrovascular events based on the cut-off values of global coronary flow reserve (G-CFR) and peak oxygen consumption (V̇O₂). ROC, receiver operating characteristic.

The principal findings of the present study are as follows: (1) patients with MACCE had greater GRACE score, lower LVEF, lower G-CFR, lower peak V̇O₂, and lower peak O₂ pulse than patients without MACCE; (2) low G-CFR was significantly and independently associated with the incidence of MACCE; (3) the combination of low G-CFR and low peak V̇O₂ showed significant incremental reclassification ability for predicting the incidence of MACCE when added to the reference clinical model including age, male sex, post-PCI peak CK values, LVEF, and LAD culprit.

The clinical significance of residual microvascular dysfunction after optimal angiography epicardial revascularization is widely recognized in patients with AMI treated with primary/urgent PCI.¹⁵ The mechanisms of residual microvascular dysfunction are likely to be multifactorial. The CFR is affected by epicardial stenosis, diffuse narrowing, and microvascular function.¹⁶ The efficacy of vessel/regional CFR as an indicator of worse prognosis has been shown using various modalities such as Doppler flow velocity-derived coronary flow velocity reserve,^17,18 thermodilution-derived CFR,^19,20 and echocardiography^21,22 in the AMI population. The predictive value of G-CFR assessed using PET^4,5,23–25 and CMR^6,26 has been explored in patients with suspected or known coronary artery disease. Recent studies have shown the prognostic value of CMR-derived G-CFR in patients with AMI.^7,27 Our results demonstrating the association between low G-CFR (<2.33; cut-off value derived from ROC curve analysis) and the incidence of MACCE in the AMI population are in line with these studies using the cut-off values around 2.0, ranging from 1.5^18,24 to 2.88.²⁵ Our results indicate that the low G-CFR is suggestive of residual microvascular dysfunction after PCI, which may lead to the higher incidence of MACCE.

Various studies have shown the feasibility of CPET to estimate exercise capacity and predict outcomes. Several CPET variables such as peak V̇O₂,^3,28,29 % predicted peak V̇O₂,³⁰ peak O₂ pulse,^31,32 and V̇E/V̇CO₂ slope³³ have been utilized as predictors of worse prognosis. CPET variables are affected by several factors, including cardiovascular systems, such as myocardial ischemia, diastolic and/or systolic ventricular dysfunction, and mitral/tricuspid valve regurgitation; and pulmonary, muscular, and cellular oxidative systems.³⁴ Peak V̇O₂ is the gold standard measure of cardiorespiratory fitness and exercise capacity.³⁵ Peak O₂ pulse represents peak V̇O₂ corrected for heart rate and is a non-invasive indicator of stroke volume and arteriovenous oxygen difference at the highest work rate.³¹ Therefore, we focused on peak V̇O₂ and peak O₂ pulse in the present study. Our results indicated that low peak V̇O₂ and peak O₂ pulse were associated with the incidence of MACCE, which were in concordance with previous studies.^{3,28,29,31,32}

Our results explored the clinical significance of non-invasive assessment using CMR and CPET in patients with AMI. Our findings indicated that the combination of CMR-derived G-CFR and CPET-derived peak V̇O₂ can provide better risk stratification in patients with AMI and residual microvascular dysfunction after PCI.

First, this is a retrospective observational study from a single center with a small sample size and therefore has an intrinsic risk of selection bias. Furthermore, since our study population included relatively younger patients who were able to perform cycle ergometer CPET, the present study was merely a hypothesis-generating study with a sample size and number of events too small to draw definitive conclusions. However, our results suggest that the non-invasive assessment using the combination of CPET and CMR may provide significant incremental reclassification ability for predicting MACCE when added to the clinically significant factors. Second, although all patients underwent CPET and were managed with guideline-directed medical therapy after discharge, not all participants were followed up with outpatient cardiac rehabilitation program. Therefore, the association between the improvement of CPET variables during follow-up and prognosis was not evaluated.

CMR-derived G-CFR and CPET-derived peak V̇O₂ showed incremental prognostic information compared with the reference model using historically important clinical risk factors, indicating that this approach may help identify high-risk patients who suffer subsequent adverse events, and thereby need an intensive therapeutic strategy and watchful observation.

The authors thank all the physicians, nurses, heart team members, and patients who were involved in this study.

None.

The authors declare no conflicts of interest.

The study protocol was approved by the institutional ethics committee on human research of Tsuchiura Kyodo General Hospital (approval number: 2022FY68).

The data that support the findings of this study are available from the corresponding author on reasonable request.

Please find supplementary file(s);

https://doi.org/10.1253/circrep.CR-24-0044

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