合成超声图像为基于超声心动图的生物力学提供基准

Tanmay Mukherjee, Sunder Neelakantan, Kyle Myers, Carl Tong, Reza Avazmohammadi
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摘要

亮度模式(B 型)超声是临床评估多种心血管疾病的常用成像模式。射血分数(EF)和冲程容积(SV)等基于超声的功能指数在诊断晚期心血管疾病中的作用已被广泛描述。此外,通过分析心脏运动获得的结构指数在早期评估肥厚型心肌病和心肌梗塞等结构性心脏病时也非常重要。通过 B 型超声成像估计心脏运动的异质性变化是患者护理的重要组成部分。尽管这种成像技术好处多多,但由于缺乏基准运动量,运动估计算法很容易受到供应商之间差异的影响。与此相反,心脏生物力学的有限元(FE)模拟则利用成熟的心肌构成模型来确保可重复性。在这项研究中,我们开发了一种从有限元模拟中创建合成 B 型超声图像的方法。所提出的方法能详细呈现左心室在复杂的小鼠特定加载方案下的位移和应变。合成图像和 FE 模拟之间的比较显示了位移模式的定性相似性,从而为改进运动估计算法的可重复性提供了基准量。因此,该研究提供了一种方法来创建一个描述复杂运动模式的广泛图像库,以促进提高心脏运动分析的可重复性。
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Synthetic ultrasound images to benchmark echocardiography-based biomechanics
Brightness mode (B-mode) ultrasound is a common imaging modality in the clinical assessment of several cardiovascular diseases. The utility of ultrasound-based functional indices such as the ejection fraction (EF) and stroke volume (SV) is widely described in diagnosing advanced-stage cardiovascular diseases. Additionally, structural indices obtained through the analysis of cardiac motion have been found to be important in the early-stage assessment of structural heart diseases, such as hypertrophic cardiomyopathy and myocardial infarction. Estimating heterogeneous variations in cardiac motion through B-mode ultrasound imaging is a crucial component of patient care. Despite the benefits of such imaging techniques, motion estimation algorithms are susceptible to variability between vendors due to the lack of benchmark motion quantities. In contrast, finite element (FE) simulations of cardiac biomechanics leverage well-established constitutive models of the myocardium to ensure reproducibility. In this study, we developed a methodology to create synthetic B-mode ultrasound images from FE simulations. The proposed methodology provides a detailed representation of displacements and strains under complex mouse-specific loading protocols of the LV. A comparison between the synthetic images and FE simulations revealed qualitative similarity in displacement patterns, thereby yielding benchmark quantities to improve the reproducibility of motion estimation algorithms. Thus, the study provides a methodology to create an extensive repository of images describing complex motion patterns to facilitate the enhanced reproducibility of cardiac motion analysis.
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