Incremental Prognostic Impact of Combining Quantitative Stress Perfusion CMR and T1 Mapping in Patients with Heart Failure

Presenting Author(s)

• 

  Masafumi Takafuji, MD, PhD

  Clinical Research Fellow
  Leeds Institute of Cardiovascular and Metabolic Medicine
  Leeds, England, United Kingdom

Primary Author(s)

• 

  Masafumi Takafuji, MD, PhD

  Clinical Research Fellow
  Leeds Institute of Cardiovascular and Metabolic Medicine
  Leeds, England, United Kingdom

Co-Author(s)

• CS

  Ching-Hui Sia, MD

  Dr
  Leeds Institute of Cardiovascular and Metabolic Medicine, United Kingdom
• TA

  Thomas Anderton, MB

  CRF
  LICAMM
  Leeds, England, United Kingdom
• 

  Bradley Chambers

  Clinical Research Fellow
  University of Leeds
  Harewood, England, United Kingdom
• 

  Maryum Farooq, MB

  Research Fellow
  Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds
  Leeds, England, United Kingdom
• CS

  Chin Soo, MB

  CRF
  LICAMM
  Leeds, England, United Kingdom
• MA

  Mehak Asad, MD, MPH

  Clinical research fellow
  University of Leeds, Multidisciplinary Cardiovascular Research Centre and Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, LS2 9JT, United Kingdom
  Leeds, England, United Kingdom
• ML

  May Lwin, MD

  Clinical Research Fellow
  University of Leeds
  Leeds, England, United Kingdom
• ED

  Erica Dall'Armellina, PhD

  Associate Professor and Honorary Consultant Cardiologist
  University of Leeds, England, United Kingdom
• 

  John Greenwood, MD, PhD, FSCMR

  Director
  Baker Heart and Diabetes Institute
  Melbourne, Victoria, Australia
• 

  Peter Kellman, PhD

  Senior Scientist
  National Institutes of Health
  Bethesda, Maryland, United States
• 

  Pankaj Garg, MD, PhD

  Consultant Clinical Associate Professor
  University of East Anglia, United Kingdom
• 

  Sven Plein, MD, PhD

  Professor of Cardiology
  Leeds Institute of Cardiovascular and Metabolic Medicine
  Leeds, England, United Kingdom
• 

  Peter P. Swoboda, PhD

  Consultant Cardiologist
  Leeds Institute of Cardiovascular and Metabolic Medicine
  Leeds, England, United Kingdom

Background: Alterations in myocardial perfusion and myocardial fibrosis are key components in the pathophysiology of heart failure (HF). CMR T1 mapping and extracellular volume (ECV) quantification have enabled the noninvasive assessment of diffuse myocardial fibrosis. Quantitative perfusion (QP) CMR allows quantification of myocardial blood flow (MBF) and perfusion reserve (MPR). The aim of this study was to evaluate the incremental prognostic value of QP-CMR and T1 mapping in patients with HF.

Methods: A total of 677 patients presenting with HF were prospectively recruited. The CMR protocol consisted of cine-CMR, pre- and post-contrast T1 mapping, stress/rest QP-CMR, and late gadolinium enhancement (LGE). Stress/rest MBF and MPR were calculated using QP-CMR. ECV was calculated using pre- and post-contrast T1 mapping, with ischemic LGE segments excluded. The primary endpoints were defined as a composite of HF hospitalization (HFH) and all-cause mortality. Associations of CMR parameters with the primary endpoint were assessed using Cox regression and Kaplan-Meier curves with the log-rank test. Cox regression analysis was used to estimate the hazard ratios (HR) for each quantitative perfusion parameter in relation to the primary endpoints and was subsequently adjusted for age, sex, left ventricular ejection fraction (LVEF), presence of inducible ischemia and ischemic LGE as covariates. The incremental value of a predictor over another predictor was evaluated by calculating global chi-square values.

Results: During a median follow-up of 3.5 years, 109 events occurred (59 deaths and 50 HFH) of the 677 patients. Baseline CMR characteristics of all patients and in relation to the primary outcome are shown in Table 1. In Cox regression analysis, lower tertile of MPR (p=0.005), higher tertile of native T1 (p=0.007), and ECV (p< 0.001) were associated with the occurrence of the primary outcome on univariate and multivariable analysis (Table 2). Kaplan-Meier analysis revealed a significant difference in event-free survival between tertiles for MPR (p< 0.001), native T1 (p< 0.001) and ECV (p< 0.001). The combination of MPR and native T1, and MPR and ECV improved risk stratification (both p< 0.001) (Figure 1). Adding ECV to age, sex, LVEF, presence of inducible ischemia and ischemic LGE significantly increased the global chi-square value from to 33.79 to 50.34 (p< 0.001). Further addition of MPR also significantly increased the global chi-square value to 57.78 (p=0.006).

Conclusion: Quantitative perfusion CMR and T1 mapping provide incremental, complementary prognostic information for predicting adverse outcomes in patients with HF. Impaired myocardial perfusion may be an important marker for risk stratification in addition to myocardial fibrosis in patients with HF.

Table 1. Baseline CMR characteristics of the patients in relation to the primary outcome

Variable  median (IQR)	All (n=677)	Event (n=109)	No event (n=568)
LV EDV index (mL/m2)	103 (85–128)	106 (89–141)	102 (85–125)
LV ESV index (mL/m2)	61 (44–87)	70 (43–93)	60 (44–85)
LVEF (%)	40 (30–49)	38 (26–49)	41 (31–49)
LV mass index (g/m2)	65 (54–79)	71 (57–85)	64 (53–78)
Inducible ischemia, n (%)	48 (7.1)	10 (9.2)	38 (6.7)
LGE, n (%)	322 (47.8)	67 (61.5)	255 (45.1)
Ischemic LGE, n (%)	131 (19.4)	35 (32.1)	96 (17.0)
Non-ischemic LGE, n (%)	207 (30.7)	37 (33.9)	170 (30.1)
Native T1 (ms)	1321 (1292–1355)	1333 (1304–1366)	1320 (1290–1352)
ECV (%)	26.0 (23.4–29.3)	26.8 (24.1–29.7)	25.9 (23.3–29.3)
Rest MBF (mL/g/min)	0.61 (0.51–0.73)	0.67 (0.54–0.85)	0.60 (0.50–0.73)
Stress MBF (mL/g/min)	1.59 (1.24–1.99)	1.47 (1.16–1.91)	1.61 (1.27–2.01)
MPR	2.57 (1.97–3.23)	2.20 (1.61–2.76)	2.64 (2.03–3.32)

ECV, extracellular volume; EDV, endo-diastolic volume, ESV, endo-systolic volume, LGE, late gadolinium enhancement, LV, left ventricular; LVEF, left ventricular ejection fraction; MBF, myocardial blood flow; MPR, myocardial perfusion reserve.Table 2. Cox regression for quantitative CMR parameters and the primary endpoint.

	Primary outcome: Composite of Death or HFH
Predictor	Unadjusted HR (95% CI)	P value	Adjusted HR* (95%CI)	P value
MPR†	2.10 (1.44–3.06)	< 0.001	1.74 (1.18–2.56)	0.005
Native T1‡	1.92 (1.31–2.82)	< 0.001	1.74 (1.16–2.59)	0.007
ECV‡	2.38 (1.61–3.51)	< 0.001	2.35 (1.58–3.49)	< 0.001

*Model adjusted for age, sex, LVEF and presence of ischemia and ischemic LGE. ^†lower tertile, ^‡higher tertile.Figure 1: Kaplan–Meier survival curves for combinations of MPR with native T1 or ECV for the primary outcome.