基于图像的左心室心肌僵硬度估计。
Image-Based Estimation of Left Ventricular Myocardial Stiffness.
机构信息
College of Engineering and Computing, Department of Biomedical Engineering, University of South Carolina, Columbia, SC 29208; College of Engineering and Computing, Department of Mechanical Engineering, University of South Carolina, Columbia, SC 29208; Cardiovascular Translational Research Center, University of South Carolina, Columbia, SC 29208.
College of Engineering and Computing, Department of Biomedical Engineering, University of South Carolina, Columbia, SC 29208.
出版信息
J Biomech Eng. 2025 Jan 1;147(1). doi: 10.1115/1.4066525.
Elevation in left ventricular (LV) myocardial stiffness is a key remodeling-mediated change that underlies the development and progression of heart failure (HF). Despite the potential diagnostic value of quantifying this deterministic change, there is a lack of enabling techniques that can be readily incorporated into current clinical practice. To address this unmet clinical need, we propose a simple protocol for processing routine echocardiographic imaging data to provide an index of left ventricular myocardial stiffness, with protocol specification for patients at risk for heart failure with preserved ejection fraction. We demonstrate our protocol in both a preclinical and clinical setting, with representative findings that suggest sensitivity and translational feasibility of obtained estimates.
左心室（LV）心肌僵硬度升高是心力衰竭（HF）发展和进展的关键重构介导的变化。尽管定量这种确定性变化具有潜在的诊断价值，但缺乏可轻易纳入当前临床实践的可行技术。为了解决这一未满足的临床需求，我们提出了一种简单的方案，用于处理常规超声心动图成像数据，以提供左心室心肌僵硬度指数，并为射血分数保留的心力衰竭风险患者制定了方案规范。我们在临床前和临床环境中展示了我们的方案，代表性结果表明所获得的估计值具有敏感性和转化可行性。
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