Toward quantitative quasistatic elastography with a gravity-induced deformation source for image-guided breast surgery.
Toward quantitative quasistatic elastography with a gravity-induced deformation source for image-guided breast surgery.
复制标题
面向图像引导乳房手术的具有重力引起变形源的定量准静态弹性成像。
DOI：
10.1117/1.jmi.5.1.015003
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Miga,MichaelI
中科院分区：
文献类型：
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作者：
Griesenauer,RebekahH;Weis,JaredA;Arlinghaus,LoriR;Meszoely,IngridM;Miga,MichaelI
乳腺生物力学模型已被应用于图像配准和诊断分析、隆胸模拟以及手术和活检指导。准确地应用乳房内组织的应力-应变关系可以提高试图模拟乳房变形的生物力学模型的准确性。据报道，脂肪、腺体和癌组织类型的硬度值差异很大。已报道的僵硬特性的变化归因于测试方法和假设的差异、测量误差以及患者之间组织弹性的自然差异。因此，能够确定患者特定的活体组织特性对于这些程序应用是有利的。虽然一些活体弹性成像方法不是定量的，另一些方法不能测量在变形条件下的材料特性，这适合于所关注的应用，在这项研究中，我们开发了一种弹性估计方法，该方法使用具有仰卧位治疗过程的变形来执行。更具体地说，通过迭代拟合仰卧位乳房形态发生变形之前和之后的两个解剖图像，重建适合于仰卧位肿块切除术的标准护理的机械特性。提出的方法是工作流友好的，定量的，并使用了非接触的重力诱导的变形源。
Biomechanical breast models have been employed for applications in image registration and diagnostic analysis, breast augmentation simulation, and for surgical and biopsy guidance. Accurate applications of stress–strain relationships of tissue within the breast can improve the accuracy of biomechanical models that attempt to simulate breast deformations. Reported stiffness values for adipose, glandular, and cancerous tissue types vary greatly. Variations in reported stiffness properties have been attributed to differences in testing methodologies and assumptions, measurement errors, and natural interpatient differences in tissue elasticity. Therefore, the ability to determine patient-specificin vivobreast tissue properties would be advantageous for these procedural applications. While somein vivoelastography methods are not quantitative and others do not measure material properties under deformation conditions that are appropriate to the application of concern, in this study, we developed an elasticity estimation method that is performed using deformations representative of supine therapeutic procedures. More specifically, reconstruction of mechanical properties appropriate for the standard-of-care supine lumpectomy was performed by iteratively fitting two anatomical images before and after deformations taking place in the supine breast configuration. The method proposed is workflow-friendly, quantitative, and uses a noncontact, gravity-induced deformation source.