Quantitative Perfusion
Wasim Javed, MBChB, MRes
Cardiology Clinical Research Fellow/ Registrar
Leeds Institute of Cardiovascular and Metabolic Medicine, United Kingdom
Wasim Javed, MBChB, MRes
Cardiology Clinical Research Fellow/ Registrar
Leeds Institute of Cardiovascular and Metabolic Medicine, United Kingdom
Ze Goh
Academic Foundation Programme Trainee
University of Leeds, United Kingdom
Mubien Shabi
Cardiology Imaging Fellow
University of Leeds, United Kingdom
Noor Sharrack, MBChB, MRCP, DTM&H
Clinical Research Fellow
University of Leeds, England, United Kingdom
Miroslawa Gorecka
Cardiology
University of Leeds, United Kingdom
Hui Xue, PhD
Director, Imaging AI Program
National Institutes of Health
Bethesda, Maryland, United States
Erica Dall’Armellina
Associate Professor and Honorary Consultant Cardiologist
University of Leeds, England, United Kingdom
Eylem Levelt, PhD
Associate Professor and Honorary Consultant
University of Leeds
Leeds, England, United Kingdom
Peter Kellman, PhD
Senior Scientist
National Institutes of Health, Maryland, United States
John P. Greenwood, PhD
Professor
University of Leeds
Leeds, England, United Kingdom
Sven Plein, MD, PhD
Professor
University of Leeds
Leeds, England, United Kingdom
Peter P. Swoboda, PhD
Consultant Cardiologist & Senior Lecturer
University of Leeds
Leeds, England, United Kingdom
Myocardial perfusion reserve (MPR) is the ratio of global myocardial blood flow (MBF) at stress compared with rest. It is independently associated with major adverse events in coronary artery disease (CAD). (1) Whilst MPR is also reduced in dilated cardiomyopathy (DCM), its prognostic significance is unclear. (2)
Methods:
Patients with a recent diagnosis of heart failure with left ventricular ejection fraction (LVEF) < 50% on echocardiogram were recruited. Exclusion criteria included prior history of CAD, myocardial infarction (MI), coronary revascularisation or symptoms of angina.
They underwent clinical assessment along with quantitative stress-perfusion cardiac magnetic resonance imaging (CMR). Only patients with increased LV end-diastolic volume indexed (LVEDVI), LVEF< 50% and no visual evidence of MI or ischaemia on CMR were included in this study. They were followed up for a minimum of 12 months via medical record review for major adverse cardiovascular events (MACE) including cardiovascular death, heart failure hospitalisation and ventricular arrhythmia. Statistical analysis included receiver operator curve (ROC) analysis to determine the optimum MPR cut-off to predict MACE and univariable and multivariable Cox regression.
Results:
Of 160 patients (median follow up 2.2 years), MACE occurred in 16 (10%) patients (first event n= 12 heart failure hospitalisation, n= 2 ventricular arrhythmia, n= 2 cardiovascular death). The optimum cut-off to predict MACE was MPR< 2.06, which identified 42 patients. On log-rank testing, patients with MPR< 2.06 demonstrated a significantly higher probability of MACE (Figure 1, chi-squared = 12.3, P< 0.001).
Univariate regression showed LVEDVI, LVEF, right ventricular ejection fraction (RVEF) and MPR were significantly associated with MACE (Table 1). Stress MBF was associated with MACE (HR 0.30, 95% confidence interval (CI) 0.12-0.79, P= 0.015) but rest MBF was not (P= 0.067). MPR< 2.06 was associated with increased likelihood of MACE (HR 5.1, 95% CI 1.85-14.04, P= 0.002).
Stepwise multivariate regression analysis included LVEF, RVEF LVEDVI and MPR< 2.06. RVEF was removed from the model and MPR< 2.06, when corrected for LVEDVI and LVEF, was still associated with MACE (HR 4.14, 95% CI 1.45 to 11.84, P= 0.008).
Conclusion: In DCM, reduced MPR was independently associated with increased MACE after correcting for LVEF and LVEDV. Future studies are needed to reproduce this finding in larger, more varied cohorts and establish whether it can be altered by medical therapy