T1-Mapping and Outcome in Nonischemic Cardiomyopathy: All-Cause Mortality and Heart Failure

Objectives: The study sought to examine prognostic relevance of T1 mapping parameters (based on a T1 mapping method) in nonischemic dilated cardiomyopathy (NIDCM) and compare them with conventional markers of adverse outcome.

Background: NIDCM is a recognized cause of poor clinical outcome. NIDCM is characterized by intrinsic myocardial remodeling due to complex pathophysiological processes affecting myocardium diffusely. Lack of accurate and noninvasive characterization of diffuse myocardial disease limits recognition of early cardiomyopathy and effective clinical management in NIDCM. Cardiac magnetic resonance (CMR) supports detection of diffuse myocardial disease by T1 mapping.

Methods: This is a prospective observational multicenter longitudinal study in 637 consecutive patients with dilated NIDCM (mean age 50 years [interquartile range: 37 to 76 years]; 395 males [62%]) undergoing CMR with T1 mapping and late gadolinium enhancement (LGE) at 1.5-T and 3.0-T. The primary endpoint was all-cause mortality. A composite of heart failure (HF) mortality and hospitalization was a secondary endpoint.

Results: During a median follow-up period of 22 months (interquartile range: 19 to 25 months), we observed a total of 28 deaths (22 cardiac) and 68 composite HF events. T1 mapping indices (native T1 and extracellular volume fraction), as well as the presence and extent of LGE, were predictive of all-cause mortality and HF endpoint (p < 0.001 for all). In multivariable analyses, native T1 was the sole independent predictor of all-cause and HF composite endpoints (hazard ratio: 1.1; 95% confidence interval: 1.06 to 1.15; hazard ratio: 1.1; 95% confidence interval: 1.05 to 1.1; p < 0.001 for both), followed by the models including the extent of LGE and right ventricular ejection fraction, respectively.

Conclusions: Noninvasive measures of diffuse myocardial disease by T1 mapping are significantly predictive of all-cause mortality and HF events in NIDCM. We provide a basis for a novel algorithm of risk stratification in NIDCM using a complementary assessment of diffuse and regional disease by T1 mapping and LGE, respectively.