Reliability of left ventricular hemodynamic forces derived from feature-tracking cardiac magnetic resonance

Abstract

BACKGROUND: Hemodynamic forces (HDF) analysis has been proposed as a method to quantify intraventricular pressure gradients, however data on its reliability are still scanty. Thus, the aim of this study is to assess the reliability of HDF parameters derived from cardiac magnetic resonance (CMR). METHODS: CMR studies of 25 athletes were analysed by two independent observers and then re-analysed by the same observer one week apart. Intraclass Correlation Coefficient (ICC [95% CI]) and Bland-Altman plots were used to assess association, agreement, and bias of the longitudinal (A-B) HDF, transverse (L-S) HDF, and Impulse Angle. The sample size required to detect a relative change in the HDF parameters was also calculated. RESULTS: In terms of inter-observer variability, there was a good correlation for the A-B and L-S (ICC 0.85 [0.67-0.93] and 0.86 [0.69-0.94]; p<0.001 for both, respectively) and a moderate correlation for the Impulse Angle (ICC 0.73 [0.39-0.87]; p = 0.001). For intra-observer variability, A-B and L-S showed excellent correlation (ICC 0.91 [0.78-0.93] and 0.93 [0.83-0.97]; p<0.001 for both, respectively). Impulse Angle presented good correlation (ICC 0.80 [0.56-0.90]; p<0.001). Frame selection and aortic valve area measurements were the most vulnerable step in terms of reliability of the method. Sample size calculation to detect relative changes ranged from n = 1 to detect a 15% relative change in Impulse Angle to n = 171 for the detection of 10% relative change in A-B HDF. CONCLUSIONS: The results of this study showed a low inter- and intra-observer variability of HDF parameters derived from feature-tracking CMR. This provides the fundamental basis for their use both in research and clinical practice, which could eventually lead to the detection of significant changes at follow-up studies.

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