Zhang Zhijun, Zhu Meihua, Ashraf Muhammad, Broberg Craig S, Sahn David J, Song Xubo
Department of Biomedical Engineering, Oregon Health and Science University, Portland, Oregon 97239.
Department of Pediatric Cardiology, Oregon Health and Science University, Portland, Oregon 97239.
Med Phys. 2014 Dec;41(12):122902. doi: 10.1118/1.4901253.
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.
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.
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.
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.
右心室（RV）运动的定量分析对于先天性和后天性疾病机制的研究至关重要。与左心室（LV）不同，由于右心室形状复杂且心肌较薄，其运动估计更为困难。尽管在磁共振成像上使用有限元模型以及在超声心动图上进行斑点追踪在右心室应变分析方面已显示出有前景的结果，但由于未考虑运动的时间平滑性，这些方法仍可改进。
作者在其早期工作中提出了一种时间微分同胚运动估计方法，其中通过优化速度场的配准能量泛函来估计时空变换。所提出的运动估计方法是针对一般图像序列的全自动过程。作者将该方法与半自动心肌分割方法相结合，应用于五只开胸猪在不同稳态下的三维（3D）超声心动图序列的右心室应变分析。
作者将其方法得出的峰值两点应变与从超声微测法估计的应变进行比较，结果表明它们具有高度相关性。通过节段应变研究右心室游离壁的运动。基线序列结果表明，其方法中的节段应变与通过其他图像模态（如MRI）获得的结果一致。起搏稳态的图像序列表明，应变变化最大的节段与起搏部位一致。
其方法在不同稳态下的峰值两点应变与超声微测法具有高度相关性，表明其右心室运动估计具有很高的准确性。其方法的节段应变与MRI的节段应变接近，表明其方法在利用三维超声心动图研究右心室功能方面的可行性。起搏稳态的应变分析表明其方法在右心室疾病研究中的潜在效用。
