T2 mapping predicts clinical outcome over a wide range of clinical indications in heart failure but is not independent of native T1

Julia-Mareen Treiber (Bad Nauheim)1, J. S. Wolter (Bad Nauheim)1, S. Kriechbaum (Bad Nauheim)1, U. Fischer-Rasokat (Frankfurt am Main)2, T. Keller (Bad Nauheim)3, M. Weferling (Bad Nauheim)1, C. W. Hamm (Gießen)4, S. T. Sossalla (Gießen)4, A. Rolf (Bad Nauheim)1

1Kerckhoff Klinik GmbH Abteilung für Kardiologie Bad Nauheim, Deutschland; 2Kardiologie-am-Main Privatpraxis für Kardiologie Frankfurt am Main, Deutschland; 3Justus-Liebig-Universität Giessen Franz-Groedel-Institut (FGI) Bad Nauheim, Deutschland; 4Universitätsklinikum Gießen und Marburg GmbH Medizinische Klinik I - Kardiologie und Angiologie Gießen, Deutschland


Background: Myocardial inflammation triggers adverse remodelling and plays a crucial role in the evolution of both ischemic and non-ischemic cardiomyopathies. Inflammatory activity can be quantified using cardiac magnetic resonance (CMR) T2 mapping. Its diagnostic potential has been validated in several studies; however, its prognostic power is still a matter of debate and has only been shown for small, specific cohorts.

Objective: To assess the prognostic potential of T2 mapping in a large cohort of routine patients from a tertiary care center registry and various heart failure (HF) states ranging from no HF to HF with reduced ejection fraction. 

Methods: Patients with clinically indicated CMR were enrolled in an all-comers, single-center registry and followed up for one year. 

The primary endpoint was defined as a combination of all-cause mortality and HF hospitalization (1), and the secondary endpoint was all-cause mortality (2). 

Patients were categorized as no HF, HF with preserved (HFpEF), mildly reduced (HFmrEF), or reduced (HFpEF) ejection fraction (EF), and their tissue morphology was compared with that of controls and patients without HF by T1 and T2 mapping. Univariate and multivariable Cox regression analysis were used to evaluate the predictive power of T2 for the specified endpoints. Global longitudinal strain (GLS), left ventricular (LV) EF, LV end-diastolic volume (EDV), amount of late enhancement (LGE%), native T1, and extracellular volume (ECV) were included as covariates for multivariable analysis. As a rule of thumb one covariate per ten events was included in a stepwise fashion beginning with the covariate with highest Wald test value.

Results: A total of 3157 patients were enrolled, of which 1575 patients completed a one-year follow-up and were available for this analysis. 

All HF categories exhibited elevated T2 values compared with controls and patients without HF. Patients with HFmrEF (n = 163) and HFpEF (n = 440) had higher T2 values compared with those with HFrEF (n = 295) (38.7 ± 2.9 ms vs. 38.6 ± 2.8 ms vs. 38.1 ± 2.8 ms; p < 0.001). 

Of the patients with one-year follow-up data, 56 reached endpoint (1) and 27 endpoint (2). In univariate analysis T2 was found to be a significant predictor of the combined endpoint (1) with a hazard ratio (HR) 1.16, confidence interval (CI) 1.06 – 1.26 (p < 0.001) and endpoint (2) with HR 1.161, 95% CI 1.029 – 1.312 (p = 0.016). 

The number of events allowed for four and two covariates in multivariable analysis, respectively. In a multivariable analysis including GLS, ESVi, ECV and age, T2 was independently predictive of endpoint (1) (HR 1.18, 95%-CI 1.07 – 1.3; p < 0.001); however, once T1 was included, T2 lost its predictive power. In multivariable analysis including age for endpoint (2), T2 was not independently predictive. 

In Kaplan Meier analysis the strata with both elevated T1 and T2 had the worst prognosis.

Conclusion: T2 mapping predicts the combined endpoint of all-cause mortality and HF hospitalizations, but this is not independent of T1. However, T2 adds prognostic value to T1, as patients with both elevated T1 and T2 values had the worst prognosis. 

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