Native T1 mapping in early diffuse and limited systemic sclerosis, and its association with diastolic function.

BACKGROUND

Systemic sclerosis (SSc) is divided into diffuse and limited cutaneous SSc (dcSSc and lcSSc). The dcSSc subtype has more severe internal organ damage. This study aimed to assess whether cardiovascular magnetic resonance (CMR) parametric mapping could detect early cardiac involvement and evaluate differences between these two subtypes.

METHODS

Eighty SSc patients (37 dcSSc and 43 lcSSc) underwent CMR at 3.0 T (Philips Healthcare, Best, The Netherlands) in our hospital between July 2018 and July 2021. We analyzed myocardial damage by CMR parametric mapping and compared it with clinical data.

RESULTS

The median duration of the disease was 10.2 months. The left ventricular ejection fraction was preserved in both groups. DcSSc had significantly higher native T1 (1333.4 ± 71.2 ms vs. 1295.0 ± 42.7 ms, p = 0.006) and extracellular volume fraction (32.6 ± 4.1 % vs. 30.3 ± 4.0 %, p = 0.018) in the mid-ventricular septum as compared to lcSSc, although there were no differences in T2 values. Native T1 values were positively correlated with the E/e' ratio and left atrial volume indices evaluated by transthoracic echocardiography in overall SSc and dcSSc, but not in lcSSc. Logistic regression analysis revealed that native T1 was an independent predictor of left ventricular diastolic dysfunction in SSc patients (odds ratio, 1.194; 95 % confidence interval, 1.021-1.396; p = 0.026). Native T1 was higher in SSc patients with progressive skin lesions. Additionally, there were positive correlations between brain natriuretic peptide, New York Heart Association functional classification, and native T1.

CONCLUSIONS

CMR parametric mapping is a useful tool for detecting myocardial changes. Native T1 was the most sensitive parameter for identifying diffuse myocardial changes in the early stages of SSc and was associated with left ventricular diastolic function. DcSSc had more severe myocardial involvement than lcSSc; therefore, the use of CMR parametric mapping may aid in its prediction.