Right ventricular strain analysis from three‐dimensional echocardiography by using temporally diffeomorphic motion estimation. Issue 12 (14th November 2014)

• Record Type: Journal Article
• Authors: Zhang, Zhijun; Zhu, Meihua; Ashraf, Muhammad; Broberg, Craig S.; Sahn, David J.; Song, Xubo
• Is Part Of: Medical physics. Volume 41:Issue 12(2014)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2014-11-14
• Subjects: biomedical MRI -- diseases -- echocardiography -- finite element analysis -- image segmentation -- image sequences -- medical image processing -- motion estimation -- optimisation -- spatiotemporal phenomena; Functional imaging -- Ultrasonography -- Diseases -- Finite element calculations -- Finite‐element and Galerkin methods -- Magnetic resonance imaging -- Segmentation; Involving electronic [emr] or nuclear [nmr] magnetic resonance, e.g. magnetic resonance imaging -- Echo‐tomography -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general -- Analysis of motion; motion estimation -- strain analysis -- 3D echocardiography -- temporally diffeomorphic registration; Motion estimation -- Medical imaging -- Cardiac dynamics -- Sequence analysis -- Eigenvalues -- Magnetic resonance imaging -- Three dimensional image processing -- Speckle; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4901253
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: Quantitative analysis of right ventricle (RV) motion is important for study of the mechanism of congenital and acquired diseases. Unlike left ventricle (LV), motion estimation of RV is more difficult because of its complex shape and thin myocardium. Although attempts of finite element models on MR images and speckle tracking on echocardiography have shown promising results on RV strain analysis, these methods can be improved since the temporal smoothness of the motion is not considered. Methods: The authors have proposed a temporally diffeomorphic motion estimation method in which a spatiotemporal transformation is estimated by optimization of a registration energy functional of the velocity field in their earlier work. The proposed motion estimation method is a fully automatic process for general image sequences. The authors apply the method by combining with a semiautomatic myocardium segmentation method to the RV strain analysis of three‐dimensional (3D) echocardiographic sequences of five open‐chest pigs under different steady states. Results: The authors compare the peak two‐point strains derived by their method with those estimated from the sonomicrometry, the results show that they have high correlation. The motion of the right ventricular free wall is studied by using segmental strains. The baseline sequence results show that the segmental strains in their methods are consistent with results obtained by other image modalities such as MRI. The image sequences of pacing steady states show that segments with the largest strain variation coincide with the pacing sites. Conclusions: The high correlation of the peak two‐point strains of their method and sonomicrometry under different steady states demonstrates that their RV motion estimation has high accuracy. The closeness of the segmental strain of their method to those from MRI shows the feasibility of their method in the study of RV function by using 3D echocardiography. The strain analysis of the pacing steady states shows the potential utility of their method in study on RV diseases.