Value of Feature-Tracking CMR in Dilated Cardiomyopathy

Study Questions:

What is the prognostic value of cardiac magnetic resonance (CMR) feature-tracking–derived global longitudinal strain (GLS) in dilated cardiomyopathy?

Methods:

The study cohort was comprised of consecutive patients undergoing CMR with ejection fraction (EF) <50% and ischemic or nonischemic dilated cardiomyopathy at four US medical centers. The study authors calculated feature-tracking GLS from three long-axis cine-views. The primary endpoint was all-cause mortality. Cox proportional hazards regression modeling was used to examine the association between GLS and mortality. The incremental prognostic value of GLS was assessed in nested models.

Results:

The final study cohort was comprised of 1,012 patients (505 ischemic and 507 nonischemic), of whom 133 died during a median follow-up of 4.4 years. The mean age of the study population was 60 ±16 years. Sixty-five percent of patients were male, and 31% had diabetes mellitus. The mean EF was 33.7 ± 10.0%. Mean GLS for the population was -10.9%. Median GLS was -11.0% (interquartile range, -7.8 to -14.0%). Using Kaplan-Meier analysis, the investigators found that the risk of death increased significantly with worsening GLS tertiles (log-rank p < 0.0001). There was an 89.1% increased risk of death with each 1% worsening in GLS after adjusting for clinical and imaging risk factors including age, body mass index, diabetes, hyperlipidemia, left ventricular end-diastolic volume index, EF, and late gadolinium enhancement (LGE) (hazard ratio [HR], 1.891 per %; p < 0.001). There was a significant improvement in the C-statistic with addition of GLS in this model (0.628-0.867; p < 0.0001). Continuous net reclassification improvement was 1.148 (95% confidence interval, 0.996-1.318). In patients with ischemic cardiomyopathy, each 1% worsening in GLS was associated with a 94.2% increased risk of death after adjustment for clinical and imaging risk factors (HR, 1.942 per %; p < 0.001). Similarly, in patients with nonischemic dilated cardiomyopathy, GLS remained significantly associated with death after adjustment for clinical and imaging risk factors (HR, 2.101 per %; p < 0.001).

Conclusions:

The study authors concluded that CMR feature-tracking–derived GLS is a powerful independent predictor of mortality in a multicenter population of patients with ischemic or nonischemic dilated cardiomyopathy, incremental to common clinical and CMR risk factors including EF and LGE.

Perspective:

This is an important study, which demonstrates that feature-tracking CMR (FT-CMR) adds incremental value to current parameters such as EF and LGE. If other studies can reproduce these important findings, FT-CMR should emerge as the gold standard in the assessment of cardiac function.

Keywords: Cardiomyopathy, Dilated, Diabetes Mellitus, Diagnostic Imaging, Gadolinium, Heart Failure, Magnetic Resonance Imaging, Magnetic Resonance Spectroscopy, Ischemia, Risk Factors, Stroke Volume, Ventricular Function, Left


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