Association between extracellular matrix expansion quantified by cardiovascular magnetic resonance and short-term mortality

Abstract

Background: Extracellular matrix expansion may be a fundamental feature of adverse myocardial remodeling, it appears to be treatable, and its measurement may improve risk stratification. Yet, the relationship between mortality and extracellular matrix is not clear because of difficulties with its measurement. To assess its relationship with outcomes, we used novel, validated cardiovascular magnetic resonance techniques to quantify the full spectrum of extracellular matrix expansion not readily detectable by conventional cardiovascular magnetic resonance.

Methods and results: We recruited 793 consecutive patients at the time of cardiovascular magnetic resonance without amyloidosis or hypertrophic cardiomyopathy as well as 9 healthy volunteers (ages 20-50 years). We measured the extracellular volume fraction (ECV) to quantify the extracellular matrix expansion in myocardium without myocardial infarction. ECV uses gadolinium contrast as an extracellular space marker based on T1 measures of blood and myocardium pre- and post-gadolinium contrast and hematocrit measurement. In volunteers, ECV ranged from 21.7% to 26.2%, but in patients it ranged from 21.0% to 45.8%, indicating considerable burden. There were 39 deaths over a median follow-up of 0.8 years (interquartile range 0.5-1.2 years), and 43 individuals who experienced the composite end point of death/cardiac transplant/left ventricular assist device implantation. In Cox regression models, ECV related to all-cause mortality and the composite end point (hazard ratio, 1.55; 95% confidence interval, 1.27-1.88 and hazard ratio, 1.48; 95% confidence interval, 1.23-1.78, respectively, for every 3% increase in ECV), adjusting for age, left ventricular ejection fraction, and myocardial infarction size.

Conclusions: ECV measures of extracellular matrix expansion may predict mortality as well as other composite end points (death/cardiac transplant/left ventricular assist device implantation).

Figure 1

Myocardial and blood pool T1 relaxation curves from a surviving individual who had a normal extracellular volume fraction (ECV). Signal intensity for myocardium and blood pool in the thumbnail images are plotted against inversion time, and T1 values are derived from a 3 parameter fit. The accumulation of Gd contrast is reflected by the (nonlinear) shift of T1 curves, i.e., ΔR1 (arrow). T1 data can be measured from regions of interest taken from individual thumbnail images or from a T1 map (inset) where the curve fitting occurs on a pixelwise basis from motion corrected, registered images (see text for details). With a hematocrit of 45.2%, the ECV was computed at 22.8%.

Figure 2

Myocardial and blood pool T1 relaxation curves from an individual with a high extracellular volume fraction (ECV) who died unexpectedly. Despite a longer post contrast myocardial T1 value compared to the individual from Figure 1, with a hematocrit of 25.0%, ECV was computed at 35.5% which is considerably higher than the individual from Figure 1. The increased ECV is not apparent from the images unless a parametric “ECV” map is created from fully co-registered images that also incorporate hematocrit data.

Figure 3

Simplified schematic diagram indicating how extracellular matrix expansion increases the extracellular volume fraction (ECV) with accumulation of Gd contrast in the myocardial extracellular matrix relative to the plasma. Erythrocytes, plasma, myocytes, myocardial capillaries, collagen and extracellular matrix, and molecules of gadolinium (Gd) contrast are shown. The top panels are analogous to the individual from Figure 1 with a low ECV, and the lower panels are analogous to the individual from Figure 2 with a high ECV. Computational steps are also defined.

Figure 4

The 39 individuals who died had higher extracellular volume fraction (ECV) in myocardium without MI. Frequency histograms of ECV in 793 consecutive patients referred for clinical CMR exams are shown according to whether they survived (panel A) or died (panel B). Based on 9 healthy volunteers without evident cardiovascular disease or risk factors whose ECV ranged 21.7%–26.2%, an ECV > 28.5% was estimated to be “abnormally elevated” (i.e., beyond the 99^th percentile assuming a normal distribution) represented by the black vertical lines (Panel A). Among surviving individuals, a considerable burden of extracellular matrix expansion reflected by ECV appears evident for a significant proportion, suggesting risk for adverse outcomes.

Figure 5

Extracellular volume fraction (ECV) in myocardium without MI is associated with all cause mortality (Panel A) and also a composite endpoint of death, cardiac transplant, or left ventricular assist device (Panel B). When the sample was divided into tertiles based on quantitative ECV measures, those with higher ECV experienced a significantly higher incidence of adverse events. The relationship between ECV and adverse outcomes remained significant after risk adjustment in multivariable models (see text).

Figure 6

To demonstrate the sequence in which information becomes clinically available for risk stratification, the global Wald χ² are shown for separate Cox regression models predicting death (panel A) or death/VAD/cardiac transplant (panel B) whereby age, coronary disease (myocardial infarction or prior revascularization), left ventricular ejection fraction (EF), and finally the extracellular volume fraction (ECV) are each added in succession (p<0.01 for all global Wald χ² for each model). The incremental Wald χ² (type 3 tests) and p values attributable to the addition of the new variable are also shown in the shaded gray boxes to demonstrate the magnitude of incremental information introduced by each additional variables in the model accounting for the variables already present in the model. EF and ECV each add significant additional prognostic information beyond the variables that preceded them.