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A maximum likelihood approach to diffeomorphic speckle tracking for 3D strain estimation in echocardiography

机译：超声心动图中3D应变估计的最大似然散斑跟踪方法

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The strain and strain-rate measures are commonly used for the analysis and assessment of regional myocardial function. In echocardiography (EC), the strain analysis became possible using Tissue Doppler Imaging (TDI). Unfortunately, this modality shows an important limitation: the angle between the myocardial movement and the ultrasound beam should be small to provide reliable measures. This constraint makes it difficult to provide strain measures of the entire myocardium. Alternative non-Doppler techniques such as Speckle Tracking (ST) can provide strain measures without angle constraints. However, the spatial resolution and the noisy appearance of speckle still make the strain estimation a challenging task in EC. Several maximum likelihood approaches have been proposed to statistically characterize the behavior of speckle, which results in a better performance of speckle tracking. However, those models do not consider common transformations to achieve the final B-mode image (e.g. interpolation). This paper proposes a new maximum likelihood approach for speckle tracking which effectively characterizes speckle of the final B-mode image. Its formulation provides a diffeomorphic scheme than can be efficiently optimized with a second-order method. The novelty of the method is threefold: First, the statistical characterization of speckle generalizes conventional speckle models (Rayleigh, Nakagami and Gamma) to a more versatile model for real data. Second, the formulation includes local correlation to increase the efficiency of frame-to-frame speckle tracking. Third, a probabilistic myocardial tissue characterization is used to automatically identify more reliable myocardial motions. The accuracy and agreement assessment was evaluated on a set of 16 synthetic image sequences for three different scenarios: normal, acute ischemia and acute dyssynchrony. The proposed method was compared to six speckle tracking methods. Results revealed that the proposed method is the most accurate method to measure the motion and strain with an average median motion error of 0.42 mm and a median strain error of 2.0 +/- 0.9%, 2.1 +/- 1.3% and 7.1 +/- 4.9% for circumferential, longitudinal and radial strain respectively. It also showed its capability to identify abnormal segments with reduced cardiac function and timing differences for the dyssynchrony cases. These results indicate that the proposed diffeomorphic speckle tracking method provides robust and accurate motion and strain estimation. (C) 2015 Elsevier B.V. All rights reserved.
机译：应变和应变率测量通常用于区域心肌功能的分析和评估。在超声心动图（EC）中，使用组织多普勒成像（TDI）进行应变分析成为可能。不幸的是，这种方式显示出一个重要的局限性：心肌运动和超声束之间的角度应较小，以提供可靠的措施。该约束使得难以提供整个心肌的应变测量。诸如斑点跟踪（ST）之类的替代性非多普勒技术可以提供不受角度限制的应变测量。然而，空间分辨率和斑点的嘈杂外观仍然使应变估计成为EC中一项具有挑战性的任务。已经提出了几种最大似然方法来统计地表征斑点的行为，这导致更好的斑点跟踪性能。但是，这些模型不考虑实现最终B模式图像的通用转换（例如插值）。本文提出了一种用于斑点跟踪的新的最大似然方法，该方法可以有效地表征最终B模式图像的斑点。它的公式提供了一个变态方案，而该方案可以用二阶方法有效地优化。该方法的新颖性有三方面：第一，散斑的统计表征将常规的散斑模型（瑞利，中上和伽玛）推广到用于实际数据的更通用的模型。其次，该公式包括局部相关性，以提高帧间斑点跟踪的效率。第三，概率性心肌组织表征用于自动识别更可靠的心肌运动。准确性和一致性评估是针对三种不同情况的一组16个合成图像序列进行评估的：正常，急性缺血和急性不同步。将该方法与六种斑点跟踪方法进行了比较。结果表明，该方法是测量运动和应变的最准确方法，平均中位运动误差为0.42 mm，中位应变误差为2.0 +/- 0.9％，2.1 +/- 1.3％和7.1 +/-圆周应变，纵向应变和径向应变分别为4.9％。对于不同步病例，它还具有识别心功能降低和时间差异减少的异常节段的能力。这些结果表明，提出的微晶斑点跟踪方法提供了鲁棒且准确的运动和应变估计。 （C）2015 Elsevier B.V.保留所有权利。

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