Multi-center studies are advantageous for enrolling participants of varying pathological and demographical conditions, and especially in neurological studies. Hence stability of the obtained quantitative R2* and susceptibility in multicenter studies is a key issue for their widespread applications. In this work, the stabilities of simultaneously obtained R2* and susceptibility are investigated and compared across 10 sites that are equipped with the same scanner and receiver coil, the same post-processing process was used to achieve consistent experiment setup. Two healthy adult volunteers (one male and female) participated in this study. High intraclass correlation coefficient was obtained for both susceptibility (0.94) and R2* (0.96). The coefficients of variance for all measurements obtained were smaller than 0.1, the largest variations of measurements in all the chosen ROIs fall within ±20% from the median value. Higher level of stability was obtained in R2* as compared to susceptibility at 1 mm resolution (P < 0.05) and at 1.5 mm (P < 0.01).

Background: Patients with nonischemic dilated cardiomyopathy (NIDCM) are prone to arrhythmias, and the cause of mortality in these patients is either end-organ dysfunction due to pump failure or malignant arrhythmia-related death. However, identification of patients with NIDCM at risk of malignant ventricular arrhythmias (VAs) is challenging in clinical practice. The aim of this study was to evaluate whether Cardiovascular magnetic resonance feature tracking (CMR-FT) may help in identification of patients with NIDCM at risk of malignant VAs. Methods: 263 NIDCM patients who underwent both CMR, 24-hour Holter electrocardiography (ECG) and inpatient ECG were retrospectively evaluated. The patients with NIDCM were divided into two subgroups: NIDCM with VAs and NIDCM without VAs. From CMR-FT, the global peak radial strain (GPRS), global longitudinal strain (GPLS), and global peak circumferential strain (GPCS) were calculated respectively from left ventricle (LV) model. We investigated the possible predictors of NIDCM combined with VAs by univariate and multivariate logistic regression analyses. Results: The percent LGE (15.51±3.30 vs. 9.62±2.18, P<0.001) was higher in NIDCM patients with VAs than in NIDCM patients without VAs. Furthermore, the NIDCM patients complicated with VAs had significantly lower GPCS compared with the NIDCM patients without VAs (P< 0.05). Subgroup analysis based on LGE negative, the NIDCM patients complicated with VAs had significantly lower GPRS,GPCS,GPLS compared with the NIDCM patients without VAs (P<0.05 for all). Multivariate analysis showed that both GPCS and % LGE were independent predictors of NIDCM combined with VAs. Conclusions: CMR global strain can early differentiate of NIDCM patients complicated with VAs specifically when LGE was not present. GPCS < −13.19% and % LGE > 10.37% are independent predictors of NIDCM combined with VAs.