Department of Biomedical Engineering, Amirkabir University of Technology (AUT), Tehran 15875-4413, Iran.
Faculty of Medical Sciences and Technologies, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran.
J Healthc Eng. 2019 Jan 6;2019:2374645. doi: 10.1155/2019/2374645. eCollection 2019.
Various elastography techniques have been proffered based on linear or nonlinear constitutive models with the aim of detecting and classifying pathologies in soft tissues accurately and noninvasively. Biological soft tissues demonstrate behaviors which conform to nonlinear constitutive models, in particular the hyperelastic ones. In this paper, we represent the results of our steps towards implementing ultrasound elastography to extract hyperelastic constants of a tumor inside soft tissue.
Hyperelastic parameters of the unknown tissue have been estimated by applying the iterative method founded on the relation between stress, strain, and the parameters of a hyperelastic model after (a) simulating the medium's response to a sinusoidal load and extracting the tissue displacement fields in some instants and (b) estimating the tissue displacement fields from the recorded/simulated ultrasound radio frequency signals and images using the cross correlation-based technique.
Our results indicate that hyperelastic parameters of an unidentified tissue could be precisely estimated even in the conditions where there is no prior knowledge of the tissue, or the displacement fields have been approximately calculated using the data recorded by a clinical ultrasound system.
The accurate estimation of nonlinear elastic constants yields to the correct cognizance of pathologies in soft tissues.
各种弹性成像技术都是基于线性或非线性本构模型提出的，旨在准确、无创地检测和分类软组织病变。生物软组织表现出符合非线性本构模型的行为，特别是超弹性模型。在本文中，我们展示了我们在实施超声弹性成像以提取软组织内肿瘤超弹性常数方面的步骤的结果。
通过应用基于应力、应变和超弹性模型参数之间关系的迭代方法，对未知组织的超弹性参数进行了估计：（a）模拟介质对正弦载荷的响应，并在某些瞬间提取组织位移场；（b）使用基于互相关的技术，从记录/模拟的超声射频信号和图像中估计组织位移场。
我们的结果表明，即使在没有组织先验知识的情况下，或者使用临床超声系统记录的数据近似计算位移场，也可以精确估计未识别组织的超弹性参数。
准确估计非线性弹性常数有助于正确认识软组织中的病变。
