Journal
EUROPEAN HEART JOURNAL-CARDIOVASCULAR IMAGING
Volume 21, Issue 11, Pages 1262-1272Publisher
OXFORD UNIV PRESS
DOI: 10.1093/ehjci/jeaa057
Keywords
hypertrophic cardiomyopathy; three-dimensional strain; segmental deformation; 2D-3D comparison
Funding
- European Association of Cardiovascular Imaging Research Grant
- Greek State Scholarships Foundation (IKY)
- Research Foundation Flanders
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Aims We aimed at directly comparing three-dimensional (3D) and two-dimensional (2D) deformation parameters in hypertrophic hearts and depict which may best reflect underlying fibrosis in hypertrophic cardiomyopathy (HCM), defined by late gadolinium enhancement (LGE) in cardiac magnetic resonance (CMR). Methods and results We included 40 HCM [54.1 +/- 14.3 years, 82.5% male, maximum wall thickness (MWT) 19.3 +/- 4.8 mm] and 15 hypertensive (HTN) patients showing myocardial hypertrophy (58.1 +/- 15.6 years, 80% male, MWT 12.8 +/- 1.4 mm) who have consecutively undergone 2D-, 3D-speckle tracking echocardiography and LGE CMR. Deformation parameters (2D and 3D) presented overall poor to moderate correlations, with 3D_longitudinal strain (LS) and 3D_circumferential strain (CS) values being constantly higher compared to 2D derivatives. By regression analysis, hypertrophy substrate (HCM vs. hypertension) and hypertrophy magnitude were the parameters to influence 2D3D LS and CS strain correlations (R-2 = 0.66, P< 0.001 and R-2 = 0.5, P= 0.001 accordingly). Among segmental deformation indices, 2D_LS showed the best area under the curve [AUC = 0.78, 95% confidence intervals (CI) (0.750.81), P< 0.0005] to detect fibrosis, with 3D deformation parameters showing similar AUC (0.65) and 3D_LS presenting the highest specificity [93.1%, 95% CI (90.6-95.1)]. Conclusions In hypertrophic hearts, 2D and 3D deformation parameters are not interchangeable, showing modest correlations. Thickness, substrate, and tracking algorithm calculating assumptions seem to induce this variability. Nevertheless, among HCM patients 2D_peak segmental longitudinal strain remains the best strain parameter for tissue characterization and fibrosis detection.
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