Why the study?
Hemodynamic forces analysis can quantify intraventricular pressure gradients, but data regarding its reliability are limited.
Does hemodynamic forces analysis derived from feature-tracking CMR provide reliable measurements in athletes?
Does hemodynamic forces analysis derived from feature-tracking CMR provide reliable measurements in athletes?
Hemodynamic forces parameters derived from feature-tracking CMR demonstrate low inter- and intra-observer variability, supporting their reliable use in research and clinical practice.
Purpose 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. 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. Conclusion 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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Ismailov et al. (2023) studied this question.
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