Modeling Uncertainty of Strain Ratio Measurements in Ultrasound Breast Strain Elastography: A Factorial Experiment.
Modeling Uncertainty of Strain Ratio Measurements in Ultrasound Breast Strain Elastography: A Factorial Experiment.
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DOI：
10.1109/tuffc.2019.2942821
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发表时间：
2020-02
期刊：
影响因子：
--
通讯作者：
Jiang J
中科院分区：
文献类型：
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作者：
Rosen D;Jiang J
应变弹性成像（SE）是一种技术，其中局部组织应变的图像用于检测组织的相对刚度。SE在乳腺良恶性病变鉴别诊断中的应用已得到广泛研究。背景和乳腺肿瘤之间的应变比已经被使用，其结果是混合的。由于组织弹性的复杂性质及其与SE中测量的应变场的关系，确切原因尚不清楚。在这项研究中，我们采用了一种新的设计实验为基础的元建模方法，在人类乳房SE的机械模拟。据我们所知，在超声SE文献中尚未报道此类研究。更具体地说，我们首先进行筛选研究，以确定最强烈地确定应变比的生物力学因素/模拟输入。然后，我们将响应面实验设计应用于这些因素，以产生应变比作为所述因素的函数的元模型。筛选研究的结果表明，应变比测量主要受3个因素的影响：病变的初始剪切模量，病变的弹性非线性和采集过程中施加的预压。为了研究这些结果的影响，将与恶性和良性病例相关的这3个因素的随机输入应用于所得响应曲面。由此产生的最佳临界值、灵敏度和特异性通常与文献中19项临床试验中的大多数（> 60%）一致。
Strain elastography (SE) is a technique in which images of localized tissue strains are used to detect the relative stiffness of tissues. The application of SE in differentiating malignant breast lesions from benign ones has been broadly investigated. The strain ratio between the background and the breast tumor has been used and its results have been mixed. Due to the complex nature of tissue elasticity and how it relates to the strain fields measured in SE, the exact reason is not known. In this study, we apply a novel design-of-experiments based meta-modeling approach to mechanical simulation of SE in the human breast. To our knowledge, such a study has not been reported in the ultrasound SE literature. More specifically, we first conduct a screening study to identify the biomechanical factors/simulation inputs that most strongly determine strain ratio. We then apply a response surface experimental design to these factors to produce a meta-model of strain ratio as a function of said factors. Results from the screening study suggest that the strain ratio measurements are primarily influenced by 3 factors: the initial shear modulus of the lesion, the elastic nonlinearity of the lesion and the precompression applied during acquisition. In order to investigate the implications of these results, stochastic inputs for these 3 factors associated with malignant and benign cases were applied to the resulting response surface. The resulting optimal cut-offs, sensitivity, and specificity were generally in line with a majority (> 60%) of 19 clinical trials in the literature.