Comparison of magnetic resonance feature tracking with harmonic phase imaging analysis (CSPAMM) for assessment of global and regional diastolic function

Aims: Complex post-processing is required for strain-derived assessment of diastolic dysfunction (DD) using CMR-tagging (TAG). Feature-tracking (FT), allows for rapid systolic strain assessment using conventional steady-state free precession (SSFP)-Cine sequences. Aim of this study was to investigate whether FT may be employed for the clinically applicable quantification of DD. Methods and Results: 40 individuals (20 patients with DD I-III degrees, 20 controls) were investigated. CSPAMM and SSFP-Cine sequences were acquired in identical short-axis locations. Global and regional early diastolic strain rate (EDSR), peak diastolic strain rate (PDSR), twist, untwist and torsion were calculated from tagged and SSFP-Cine datasets. DD indices were compared, intra- as well inter-observer variability assessed. Results: for global EDSR correlated strongly (r = 0.94), revealed good agreement and no significant differences between both methods. Correlation for regional EDSR was lower, results differed significantly in the anterior wall (p < 0.05). Correlation for PDSR was moderate (r = 0.63), results in the healthy control group differed significantly (p < 0.05). FT derived rotational indices correlated poorly with TAG (twist: r=0.28; untwist: r=0.02; torsion: r = 0.26), subgroup analysis revealed significant differences (p < 0.05). Intra- and inter-observer variability for FT derived global EDSR and PDSR were comparable to TAG, but significantly higher for regional EDSR and rotational indices. Conclusion: FT derived global EDSR allows for rapid clinical determination of diastolic dysfunction, revealing good agreement with TAG and low intra- as well as interobserver variability. However, TAG analysis not only yields higher accuracy and reproducibility of global- and regional diastolic strain, but also delivers reliable information about diastolic rotational and untwisting dynamics. (C) 2014 Elsevier Ireland Ltd. All rights reserved.