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Cardiovascular magnetic resonance assessment of coronary flow reserve improves risk stratification in heart failure with preserved ejection fraction
Journal of Cardiovascular Magnetic Resonance volume 23, Article number: 112 (2021)
Coronary microvascular dysfunction (CMD) has been proposed as a novel mechanism for the pathophysiology of heart failure (HF) with preserved ejection fraction (HFpEF). Recent studies have suggested the potential utility of coronary flow reserve (CFR) as a marker of CMD in patients with HFpEF. Phase contrast (PC) cine cardiovascular magnetic resonance (CMR) of the coronary sinus has emerged as a non-invasive method to quantify CFR. We aimed to investigate the prognostic value of CMR-derived CFR in patients with HFpEF.
Data from 163 HFpEF patients (73 ± 9 years; 86 [53%] female) were retrospectively analyzed. Coronary sinus blood flow was measured in all patients, and myocardial blood flow was calculated as coronary sinus blood flow divided by left ventricular mass. CFR was calculated as the myocardial blood flow during adenosine triphosphate infusion divided by that at rest. Adverse events were defined as all-cause death and hospitalization due to HF exacerbation. Event-free survival stratified according to CFR < 2.0 was estimated with Kaplan–Meier survival methods and Log-rank test.
During a median follow-up of 4.1 years, 26 patients (16%) experienced adverse events. CMR-derived CFR was significantly lower in HFpEF with adverse events compared with those without (1.93 ± 0.38 vs. 2.67 ± 0.52, p < 0.001). On a Kaplan Meier curve, the rates of adverse events were significantly higher in HFpEF patients with CFR < 2.0 compared with HFpEF with CFR ≥ 2.0 (p < 0.001). The area under the curve of CFR for predicting adverse events was significantly higher than that of LGE (0.881 vs. 0.768, p = 0.037) and GLS (0.881 vs. 0.747, p = 0.036).
CFR assessed using coronary sinus PC cine CMR may be useful as a non-invasive prognostic marker for HFpEF patients.
Heart failure (HF) with preserved ejection fraction (HFpEF) is as prevalent as HF with reduced ejection fraction (HFrEF) [1,2,3,4]; the prognosis of HFpEF is poor, similar to that of HFrEF [1, 5]. The prevalence of HFpEF will continue to increase as life expectancy increases [5,6,7]. However, effective treatment for HFpEF has not been identified because its precise pathophysiology has not been fully elucidated . Coronary microvascular dysfunction (CMD) has been proposed as a novel mechanism for the pathophysiology of HFpEF [9,10,11,12,13]. Recent studies have suggested the potential utility of coronary flow reserve (CFR) as a marker of CMD in patients with HFpEF. The PROMIS-HFpEF (PRevalence of Microvascular dySfunction in Heart Failure with Preserved Ejection Fraction) is a prospective multicenter study that includes a large number of HFpEF patients and has shown a significant correlation between echo-derived CFR and indices of systemic endothelial function, including the reactive hyperemia index and urinary albumin-to-creatinine ratio . Moreover, an autopsy study showed that coronary microvascular rarefaction is a key factor in the pathophysiology of HFpEF . This evidence suggests the potential utility of CFR for evaluating disease severity in patients with HFpEF.
Phase contrast (PC) cine cardiovascular magnetic resonance (CMR) of the coronary sinus has emerged as a non-invasive means to quantify CFR [15,16,17,18,19]. Recent studies have shown the prognostic implication of CMR-derived CFR for coronary artery disease [20, 21] or diabetes mellitus [22, 23]. Regarding HFpEF, the CMR-derived CFR has been found to be significantly lower compared with that in hypertensive left ventricular (LV) hypertrophy and controls, and was correlated with serum brain natriuretic peptide (BNP) level . Thus far, the prognostic value of CMR-derived CFR for HFpEF patients remains unknown. Therefore, this study aimed to investigate the prognostic value of CMR-derived CFR for the development of future adverse events in patients with HFpEF.
This retrospective, observational study included a total of HFpEF who underwent vasodilator stress CMR imaging between 2009 and 2017 in Kanagawa Cardiovascular and Respiratory Center, Yokohama, Kanagawa, Japan. The inclusion criteria included HFpEF patients who completed stress CMR tests including cine CMR, PC cine CMR of the coronary sinus, stress perfusion CMR, and late gadolinium enhancement (LGE). Indication of CMR for this study is screening of myocardial ischemia. We applied the diagnostic criteria of the European Society of Cardiology guidelines for the diagnosis of HFpEF . Briefly, we defined HFpEF as follows: (1) patients with symptoms and signs of HF, (2) preserved left ventricular ejection fraction (LVEF) (LVEF > 50% on echocardiography), (3) elevated serum levels of BNP (> 35 pg/mL), and (4) objective evidence of other cardiac functional and structural alterations underlying HF (left atrial volume index (LAVI) > 34 mL/m2 or a LV mass index (LVMI) ≥ 115 g/m2 for men and ≥ 95 g/m2 for women, or E/e’ ≥ 13 and a mean e’ septal and lateral wall < 9 cm/s). Exclusion criteria included patients with history of prior myocardial infarction, myocarditis, hypertrophic cardiomyopathy, Anderson-Fabry disease and amyloidosis. Any evidence of persistent left-sided vena cava and low-quality CMR images were also excluded. There were 82 patients overlapping with our previous study . Prognostic information was obtained using electronic medical records. Adverse events were defined as the occurrence of all-cause death and hospitalization due to HF exacerbation. Follow-up duration was defined as time of CMR scan to adverse event for HFpEF patients with events, and time of CMR scan to last follow-up for HFpEF patients without events. Clinical characteristics and echocardiography findings are information at the time of CMR scan. This study was approved by the institutional review board, and written informed consent was waived because of the retrospective design.
CMR image acquisition
Patient scanning was performed using a 1.5-T CMR scanner equipped with 32-channel cardiac coils (Achieva, Philips Healthcare, Best, The Netherlands). The CMR protocol consisted of cine CMR, rest-stress perfusion CMR, rest-stress PC cine CMR, and LGE. Using an electrocardiogram (ECG) gated, breath-hold balanced steady-state free precession sequence, vertical long-axis, horizontal long-axis, and short-axis cine images of the LV were acquired (repetition time, 4.1 ms; echo time, 1.7 ms; flip angle, 55°; field of view, 350 × 350 mm2; acquisition matrix, 128 × 128; and number of phases per cardiac cycle, 20). To detect the location of the coronary sinus, axial plane cine CMR was obtained through the atrioventricular groove. The imaging plane for blood flow measurement was positioned perpendicular to the coronary sinus 1.5 cm from its ostium. During breath-holding, PC cine CMR of the coronary sinus was acquired using a vector ECG-triggered gradient echo sequence (repetition time, 7.3 ms; echo time, 4.4 ms; flip angle, 10°; field of view, 240 × 194 mm2; acquisition matrix, 128 × 128; number of phases per cardiac cycle, 20; velocity encoding, 50 cm/sec; and slice thickness, 6 mm). Pharmacological stress was achieved by continuous injection of adenosine triphosphate (140 μg /kg/min). First-pass myocardial perfusion CMR images were acquired with a turbo field echo sequence (4 short-axis slices/2 RR intervals; repetition time, shortest; echo time, shortest; flip angle, 40°; field of view, 360 × 324 mm2; acquisition matrix, 192 × 172; reconstruction matrix, 256 × 230; and slice thickness, 8 mm). After scanning of the perfusion CMR sequence was started, gadolinium contrast (Gadopentetate dimeglumine, Magnevist, Schering, Berlin, Germany or Meglumine Gadoterate, Magnescope, Guerbet, Paris, France) was injected into the right antecubital vein at a dose of 0.05 mmol/kg and a flow rate of 4 mL/s, followed by a 20-mL saline flush. All patients were asked to refrain from caffeinated beverages for at least 24 h prior to CMR. After the acquisition of rest perfusion, gadolinium contrast was injected in a total dose of 0.15 mmol/kg. Fifteen minutes after the injection, LGE images were acquired in the same planes as the cine images using an inversion recovery-prepared gradient echo sequence (repetition time, 4.3 ms; echo time, 1.3 ms; flip angle, 15°; field of view, 380 × 380 mm2; acquisition matrix, 256 × 180; and slice thickness, 10 mm).
CMR image analysis
Commercially available software (Extend MR WorkSpace workstation, Philips Healthcare) was used to analyze the cine, PC, and LGE images. For the feature tracking strain analysis, dedicated software was used (Vitrea, Canon Medical Systems Corporation, Otawara, Tochigi, Japan). To assess the amount of fibrosis on LGE, enhanced myocardium was defined using the planimetry method [26, 27]. A strain analysis was performed to determine the endocardial and epicardial borders of the myocardial tissue in each cine image, and peak global radial strain (GRS) and peak global circumferential strain (GCS) were calculated using short-axis cine CMR. The peak global longitudinal strain (GLS) was calculated from the vertical long-axis and horizontal long-axis images. To calculate the right ventricular (RV) longitudinal strain, a 4-chamber view of the cine CMR images was analyzed. To quantify the blood flow in the coronary sinus, the contours of the coronary sinus were manually traced on each frame of all PC images (Fig. 1A–C). For phase-offset correction, we drew the region of interest on the myocardium separately for each cardiac phase. Coronary sinus blood flow was calculated by integrating the product of the cross-sectional area and mean velocity in the coronary sinus (Fig. 1D).
We calculated myocardial blood flow (MBF) according to the previous study .
MBF (ml/min/g): Coronary sinus blood flow (mL/min) / LV mass (g).
CFR: MBF during ATP infusion (mL/min/g) / MBF at rest (mL/min/g)
Data were analyzed using SPSS software (version 17.0, Statistical Package for the Social Sciences, International Business Machines, Inc., Armonk, New York, USA), MedCalc for Windows (version 14.8.1, MedCalc Software, Ostend, Belgium), and R (version 3.6.3, The R Foundation for Statistical Computing, Vienna, Austria). Continuous values were presented as means ± standard deviation, and categorical values were presented as numbers (%). Normality was determined using the Shapiro–Wilk test. Normally distributed values were compared using an unpaired t-test, and non-normally distributed values were compared using the Mann–Whitney U test. The significance of differences in categorical variables was calculated using the Chi-squared test. The relationship between CFR and GCS, CFR and GLS, CFR and RV strain, CFR, and BNP were assessed using Pearson’s correlation coefficient. Event-free survival stratified according to CFR < 2.0 was estimated with Kaplan–Meier survival methods, and Log-rank test was used to assess the significance of difference of 2 groups. Cut-off value of CFR of 2.0 was derived according to a previous study . A 2-sided p value < 0.05 was considered significant.
Of the 171 patients with a confirmed diagnosis of HFpEF, 163 were analyzed in this study. We excluded 1 patient with persistent left side vena cava, 3 with low image quality of CMR, and 4 without follow-up information (Fig. 2). Patient characteristics are summarized in Table 1. The mean age was 73 ± 9 years, BNP was 114 ± 80 pg/mL, and 34% of patients had a history of HF hospitalization. HFpEF patients with events had higher heart rate, high rate of history of HF hospitalization, low estimated glomerular filtration rate, and higher LAVI than those without events (all p < 0.05) (Table 1). There was no significant difference in period from diagnosis of HFpEF to CMR scan between patients without events and those with events (5.4 ± 2.1 months vs. 5.7 ± 1.7 months, p = 0.30). Fifty of 163 (31%) patients had atrial fibrillation. There was no significant difference in the prevalence of AF between patients with events and those without events (42% vs 28%, p = 0.16). CMR parameters are presented in Table 2. The mean LVEF was 64.4 ± 7.3%, and the prevalence of LGE was 45%. All hyperenhancement was located in the mid-wall or epicardial side of the LV. No patients had myocardial ischemia on perfusion CMR. HFpEF patients with events had higher %LGE, higher GCS, higher GLS, and higher RV strain compared to those without events (all p value < 0.05) (Table 2). There were significant difference in CFR (1.93 ± 0.38 vs. 2.67 ± 0.52, p < 0.001) and prevalence of CFR < 2.0 (42% vs. 3%, p < 0.001) between HFpEF with events and those without events (Table 2).
Correlation between CFR and strain parameters, BNP, %LGE
Figure 3 shows the correlation between CFR and strain values and CFR and BNP. Significant negative correlations were found between CFR and GCS (r = − 0.29, p < 0.001), CFR and CLS (r = − 0.33, p < 0.001), CFR and RV longitudinal strain (r = − 0.26, p < 0.001), CFR, and serum BNP level (r = − 0.32, p < 0.001), respectively. In addition, significant negative correlation was found between %LGE and CFR (r = − 0.27, p < 0.001). Figure 4 illustrated scatter plot of CFR between HFpEF patients with adverse event and those without. CFR was significantly lower in HFpEF patients with adverse events compared with those without (1.93 ± 0.38 vs. 2.67 ± 0.52, p < 0.001).
Prognostic value of CFR in HFpEF patients
Twenty-six (16%) patients experienced adverse events over a median follow-up period of 4.1 years (cardiovascular death, n = 13; HF hospitalization, n = 13). Figure 5 illustrates Kaplan–Meier event-free survival curves for adverse events in HFpEF patients stratified by a CFR cutoff of 2.0. The rates of adverse events were significantly higher in patients with CFR < 2.0 (p < 0.001) (Fig. 5). Figure 6 shows the ROC curves of LGE%, GLS, and CFR for predicting events. The area under the ROC curve (AUC) of CFR for predicting adverse events was significantly higher than that of LGE (0.881 vs. 0.768, p = 0.037) and GLS (0.881 vs. 0.747, p = 0.036).
The main findings of this study are as follows. (1) CMR-derived CFR was significantly lower in HFpEF patients with adverse events compared with those without, (2) The prevalence of impaired CFR (< 2.0) was significantly higher in HFpEF with events than in those without, (3) AUC of CFR for predicting events was significantly higher than that of LGE% and GLS. These results indicate the potential utility of CMR-derived CFR for risk stratification in HFpEF patients.
In the past, several studies have suggested that CMD is an important pathophysiology of HFpEF [9,10,11,12,13]. In an autopsy study including 124 patients with HFpEF, HFpEF had increased mass (median, 538 g versus 335 g), more LV fibrosis (median % area fibrosis, 9.6 versus 7.1), and lower microvascular density (median 961 versus 1316 vessels/mm2) compared with age-matched control subjects (P < 0.0001 for all). Myocardial fibrosis increased with decreasing microvascular density in both the controls (r = − 0.28, p = 0.004) and HFpEF (r = − 0.26, p = 0.004) . These results indicate that coronary microvascular rarefaction may be a key factor in the pathophysiology of HFpEF. As we excluded patients with the history of myocardial infarction, all the hyperenhancement was located in the mid-wall or epicardial side of the LV, suggesting non-ischemic etiology. Although precise mechanisms of LGE remains unclear, we believe that this LGE represents myocardial fibrosis observed in previous autopsy study of HFpEF patients . PROMIS-HFpEF is a prospective multicenter study that included the largest number of 202 HFpEF patients . This study has shown a high prevalence of CMD in HFpEF patients (prevalence 75%, CMD defined as CFR < 2.5 by Doppler echocardiography of the left anterior descending artery), and CFR was correlated with indices of systemic endothelial function, such as reactive hyperemia index and urinary albumin-to-creatinine ratio. These results indicated an indirect but close link between CFR and CMD in patients with HFpEF. Other small studies also showed a high prevalence of CMD in HFpEF patients (prevalence range from 37 to 76%) [24, 28,29,30]. In another study including suspected coronary artery disease (CAD) patients with normal LVEF who underwentpositron emission tomography) PET, impairment of PET-derived CFR is associated with diastolic function and future development of HFpEF hospitalization . To date, limited data are available regarding the prognostic value of CFR for the development of adverse cardiac events in HFpEF patients. In our study, cut-off value of CFR < 2.0 showed good discrimination of HFpEF with adverse event and those without event, indicating that optimal cut-off value of CFR may be different by each modality.
PC cine CMR of the coronary sinus has emerged as a non-invasive method to quantify CFR. Theoretically, global LV blood flow can be estimated by measuring blood flow in the coronary sinus, as the coronary sinus drains approximately 96% of the total LV MBF . Validation studies of this imaging technique have been performed using phantom models , animal experimental models using flow probes  and PET . Recent studies have shown the prognostic importance of CMR-derived CFR for atherosclerotic diseases, such as CAD [20, 21] or diabetes mellitus [22, 23]. Additionally, this method is potentially useful for evaluating reduced CFR in patients with non-atherosclerotic diseases, including hypertrophic cardiomyopathy [15, 34], dilated cardiomyopathy  and HFpEF . In HFpEF, CMR-derived CFR was significantly lower compared with hypertensive LV hypertrophy and controls subjects and correlated with serum BNP levels . Although the precise mechanisms for alterations of CFR in HFpEF patients remain unclear, possible explanations include abnormal vascular function , endothelial dysfunction , cardiac inflammation , and microscopic hypertrophy and fibrosis . These vascular and myocardial abnormalities observed in patients with HFpEF might be associated with impairment of CFR. In our study, significant difference of CFR was found between HFpEF with adverse event and those without, however, substantial overlap was demonstrated between 2 groups (Fig. 4). This may be explained by co-morbidities, such as hypertension, diabetes, dyslipidemia and smoking also affect the CFR value.
Recently, several CMR prognostic factors have been proposed for patients with HFpEF, such as focal fibrosis on LGE , diffuse fibrosis on ECV with native T1 mapping , RV function , and GLS using the feature tracking [4, 41]. Regarding GLS, a significant correlation between GLS and diffuse fibrosis quantified based on ECV with T1 mapping was found, and HFpEF with a GLS above the median of -8.5% had a higher event rate . In our study, a significant correlation was found between CFR and GLS, CFR and GCS, CFR and RV longitudinal strain, CFR, and serum BNP level (Fig. 3). As most of the coronary blood flow perfuse the myocardium, correlation of CFR and LV myocardial strains could be explained by the impaired function of LV myocardial fiber due to poor perfusion. Regarding the correlation of CFR and RV strain, precise mechanism is unclear, but presumably related to pulmonary hypertension. Significant negative correlation between %LGE and CFR suggested that the link between myocardial fibrosis and coronary microvascular function in HFpEF patients. Moreover, the area under the curve of CFR was higher than that of GLS or %LGE (Fig. 5). These results indicate the clinical importance of CFR in HFpEF patients.
PC cine CMR of the coronary sinus is a non-invasive method that does not require contrast injection or radiation exposure. In this regard, this method has advantages over myocardial positron emission tomography. Even in young patients and patients with renal dysfunction, prognostic information can be obtained using this method. Additionally, because of its non-invasiveness, acquisition of PC cine CMR of the coronary sinus can be performed many times. Therefore, we can assess serial changes in the global CFR, monitoring the effectiveness of medical therapy using this method.
Our study has several ljmitations. First, this was a single-center, observational study with a limited number of patients. Therefore, a larger, multicenter, and more diverse study is desirable to confirm our observations. Second, the exact mechanism relating the non-invasive measurement of global CFR to increased cardiac mortality cannot be determined from this study. Third, diffuse myocardial fibrosis by T1 mapping was not performed in all subjects; therefore, the relationship between CFR and ECV was not presented in this study. Fourth, X-ray coronary angiography was not performed in all patients. However, patients with untreated CAD were excluded, and all study subjects did not have significant regional ischemia on stress perfusion CMR. Therefore, CFR would represent microvascular function rather than ischemia due to CAD in our study population. Fifth, as this study was a retrospective study, selection bias was not negligible. Although there are 82 patients overlapping with our previous paper, the target disease is totally different, HFpEF in the current study and suspected or known CAD in the previous study .
CFR assessed using PC cine CMR of the coronary sinus may be useful as a non-invasive prognostic marker for HFpEF patients.
Availability of data and materials
The datasets during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Area under the curve
Brain natriuretic peptide
Coronary artery disease
Coronary blood flow
Coronary flow reserve
Coronary microvascular dysfunction
Cardiovascular magnetic resonance
Global circumferential strain
Global longitudinal strain
Global radial strain
Heart failure with preserved ejection fraction
Heart failure with reduced ejection fraction
Left atrial volume index
Left ventricle/left ventricular
Left ventricular end-diastolic volume
Left ventricular ejection fraction
Left ventricular end-systolic volume
Left ventricular mass index
Myocardial blood flow
Positron emission tomography
Right ventricle/right ventricular
Bhatia RS, Tu JV, Lee DS, et al. Outcome of heart failure with preserved ejection fraction in a population-based study. N Engl J Med. 2006;355:260–9.
Redfield MM, Jacobsen SJ, Burnett JC Jr, Mahoney DW, Bailey KR, Rodeheffer RJ. Burden of systolic and diastolic ventricular dysfunction in the community: appreciating the scope of the heart failure epidemic. JAMA. 2003;289:194–202.
Udelson JE. Heart failure with preserved ejection fraction. Circulation. 2011;124:e540–3.
Kammerlander AA, Dona C, Nitsche C, et al. Feature tracking of global longitudinal strain by using cardiovascular MRI improves risk stratification in heart failure with preserved ejection fraction. Radiology. 2020;296:290–8.
Owan TE, Hodge DO, Herges RM, Jacobsen SJ, Roger VL, Redfield MM. Trends in prevalence and outcome of heart failure with preserved ejection fraction. N Engl J Med. 2006;355:251–9.
Borlaug BA, Paulus WJ. Heart failure with preserved ejection fraction: pathophysiology, diagnosis, and treatment. Eur Heart J. 2011;32:670–9.
Lee DS, Gona P, Vasan RS, et al. Relation of disease pathogenesis and risk factors to heart failure with preserved or reduced ejection fraction: insights from the Framingham heart study of the national heart, lung, and blood institute. Circulation. 2009;119:3070–7.
Borlaug BA. The pathophysiology of heart failure with preserved ejection fraction. Nat Rev Cardiol. 2014;11:507–15.
Ahmed A. 1 year mortality after first hospital admission for heart failure was similar in patients with preserved or reduced ejection fraction. Evid Based Med. 2006;11:185.
Lam CS, Brutsaert DL. Endothelial dysfunction: a pathophysiologic factor in heart failure with preserved ejection fraction. J Am Coll Cardiol. 2012;60:1787–9.
Lam CS, Lund LH. Microvascular endothelial dysfunction in heart failure with preserved ejection fraction. Heart. 2016;102:257–9.
Mohammed SF, Hussain S, Mirzoyev SA, Edwards WD, Maleszewski JJ, Redfield MM. Coronary microvascular rarefaction and myocardial fibrosis in heart failure with preserved ejection fraction. Circulation. 2015;131:550–9.
Paulus WJ, Tschope C. A novel paradigm for heart failure with preserved ejection fraction: comorbidities drive myocardial dysfunction and remodeling through coronary microvascular endothelial inflammation. J Am Coll Cardiol. 2013;62:263–71.
Shah SJ, Lam CSP, Svedlund S, et al. Prevalence and correlates of coronary microvascular dysfunction in heart failure with preserved ejection fraction: PROMIS-HFpEF. Eur Heart J. 2018;39:3439–50.
Kawada N, Sakuma H, Yamakado T, et al. Hypertrophic cardiomyopathy: MR measurement of coronary blood flow and vasodilator flow reserve in patients and healthy subjects. Radiology. 1999;211:129–35.
Schwitter J, DeMarco T, Kneifel S, et al. Magnetic resonance-based assessment of global coronary flow and flow reserve and its relation to left ventricular functional parameters: a comparison with positron emission tomography. Circulation. 2000;101:2696–702.
van Rossum AC, Visser FC, Hofman MB, Galjee MA, Westerhof N, Valk J. Global left ventricular perfusion: noninvasive measurement with cine MR imaging and phase velocity mapping of coronary venous outflow. Radiology. 1992;182:685–91.
Lund GK, Wendland MF, Shimakawa A, et al. Coronary sinus flow measurement by means of velocity-encoded cine MR imaging: validation by using flow probes in dogs. Radiology. 2000;217:487–93.
Watzinger N, Lund GK, Saeed M, et al. Myocardial blood flow in patients with dilated cardiomyopathy: quantitative assessment with velocity-encoded cine magnetic resonance imaging of the coronary sinus. J Magn Reson Imaging. 2005;21:347–53.
Kato S, Saito N, Nakachi T, et al. Stress perfusion coronary flow reserve versus cardiac magnetic resonance for known or suspected CAD. J Am Coll Cardiol. 2017;70:869–79.
Indorkar R, Kwong RY, Romano S et al. global coronary flow reserve measured during stress cardiac magnetic resonance imaging is an independent predictor of adverse cardiovascular events. JACC Cardiovasc Imaging. 2019;12:1686–95.
Kato S, Fukui K, Kodama S, et al. Incremental prognostic value of coronary flow reserve determined by phase-contrast cine cardiovascular magnetic resonance of the coronary sinus in patients with diabetes mellitus. J Cardiovasc Magn Reson. 2020;22:73.
Kato S, Fukui K, Saigusa Y, et al. Coronary flow reserve by cardiac magnetic resonance imaging in patients with diabetes mellitus. JACC Cardiovasc Imaging. 2019;12:2579–80.
Kato S, Saito N, Kirigaya H et al. Impairment of coronary flow reserve evaluated by phase contrast cine-magnetic resonance imaging in patients with heart failure with preserved ejection fraction. J Am Heart Assoc. 2016;5:e002649.
Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J. 2016;37:2129–200.
Kim RJ, Wu E, Rafael A, et al. The use of contrast-enhanced magnetic resonance imaging to identify reversible myocardial dysfunction. N Engl J Med. 2000;343:1445–53.
Im DJ, Hong SJ, Park EA, et al. Guidelines for cardiovascular magnetic resonance imaging from the Korean Society of Cardiovascular Imaging—Part 3: perfusion, delayed enhancement, and T1- and T2 mapping. Korean J Radiol. 2019;20:1562–82.
Srivaratharajah K, Coutinho T, deKemp R et al. Reduced myocardial flow in heart failure patients with preserved ejection fraction. Circ Heart Fail 2016;9.
Dryer K, Gajjar M, Narang N, et al. Coronary microvascular dysfunction in patients with heart failure with preserved ejection fraction. Am J Physiol Heart Circ Physiol. 2018;314:H1033–42.
Sucato V, Evola S, Novo G, et al. Angiographic evaluation of coronary microvascular dysfunction in patients with heart failure and preserved ejection fraction. Microcirculation. 2015;22:528–33.
Taqueti VR, Solomon SD, Shah AM, et al. Coronary microvascular dysfunction and future risk of heart failure with preserved ejection fraction. Eur Heart J. 2018;39:840–9.
Setoguchi M, Hashimoto Y, Sasaoka T, Ashikaga T, Isobe M. Risk factors for rehospitalization in heart failure with preserved ejection fraction compared with reduced ejection fraction. Heart Vessels. 2015;30:595–603.
Arheden H, Saeed M, Tornqvist E, et al. Accuracy of segmented MR velocity mapping to measure small vessel pulsatile flow in a phantom simulating cardiac motion. J Magn Reson Imaging. 2001;13:722–8.
Gyllenhammar T, Fernlund E, Jablonowski R, et al. Young patients with hypertrophic cardiomyopathy, but not subjects at risk, show decreased myocardial perfusion reserve quantified with CMR. Eur Heart J Cardiovasc Imaging. 2014;15:1350–7.
Borlaug BA, Olson TP, Lam CS, et al. Global cardiovascular reserve dysfunction in heart failure with preserved ejection fraction. J Am Coll Cardiol. 2010;56:845–54.
Akiyama E, Sugiyama S, Matsuzawa Y, et al. Incremental prognostic significance of peripheral endothelial dysfunction in patients with heart failure with normal left ventricular ejection fraction. J Am Coll Cardiol. 2012;60:1778–86.
Paterson I, Michelakis ED. The role of Doppler echocardiography in pulmonary artery hypertension: the importance of proving the obvious. Chest. 2011;139:973–5.
Kato S, Saito N, Kirigaya H, et al. Prognostic significance of quantitative assessment of focal myocardial fibrosis in patients with heart failure with preserved ejection fraction. Int J Cardiol. 2015;191:314–9.
Duca F, Kammerlander AA, Zotter-Tufaro C, et al. Interstitial fibrosis, functional status, and outcomes in heart failure with preserved ejection fraction: insights from a prospective cardiac magnetic resonance imaging study. Circ Cardiovasc Imaging. 2016. https://doi.org/10.1161/CIRCIMAGING.116.005277.
Aschauer S, Kammerlander AA, Zotter-Tufaro C, et al. The right heart in heart failure with preserved ejection fraction: insights from cardiac magnetic resonance imaging and invasive haemodynamics. Eur J Heart Fail. 2016;18:71–80.
Romano S, Judd RM, Kim RJ, et al. Feature-tracking global longitudinal strain predicts mortality in patients with preserved ejection fraction: a multicenter study. JACC Cardiovasc Imaging. 2020;13:940–7.
We are grateful for Masanori Ito, RT and Yuki Yoshimura, RT with their effort for CMR image acquisition.
Research Grant, Japan Society for the Promotion of Science: Grant-in-Aid for Early-Career Scientists.
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This study was approved by the institutional review board, and the need for written informed consent was waived because of the retrospective design.
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Kato, S., Fukui, K., Kodama, S. et al. Cardiovascular magnetic resonance assessment of coronary flow reserve improves risk stratification in heart failure with preserved ejection fraction. J Cardiovasc Magn Reson 23, 112 (2021). https://doi.org/10.1186/s12968-021-00807-3
- Heart failure with preserved ejection fraction
- Coronary flow reserve
- Heart failure