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Modeling Procedures for Breast Cancer Diagnosis based on Clinical Elastography Images

机译:基于临床弹性成像图像的乳腺癌诊断建模程序

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Nowadays, breast cancer is considered the second cause common cancer type of women death. To determine the proper therapeutic procedures before cancer spreading, early detection of cancer is a definitive step. Ultrasound elastography is considered one of the early effective noninvasive diagnostic tools. It has many advantages as low cost, its safety and the highly increasing development in various medical imaging applications.In this work, 3D modelling and simulations using virtual phantoms that were designed based on realistic in-vivo experimental results. The models were constructed for each in-vivo individual case assuring the biomechanical features of the breast tissue. The models are integrated several breast tumor's parameters including size, shape, and position. In particular, mathematical and computational analyses were used to compare this work's results by assorted specifics of in-vivo elastograms. Tumor discrimination; either malignant or benign, was performed depending on the non-linear biomechanical properties of breast tumors. To calculate the main classification parameters, tissue deformations and strain differences among the suspected mass and the normal surrounding background tissue were analyzed and empirically fitted. The results show a kindly agreement between the model outputs and the in-vivo diagnostics elastograms. Generally, the introduced finite element modeling method can be considered as a non-invasive diagnostic procedure in an early stage to preceding classify breast tumors. The 3D simulation results can assure a more theoretical insight on the behavior of nonlinear biomechanical properties that might not be obvious or convenient using clinical experimentations.
机译:如今,乳腺癌被认为是导致女性死亡的第二大常见癌症类型。为了在癌症扩散之前确定适当的治疗程序,癌症的早期发现是必不可少的步骤。超声弹性成像被认为是早期有效的非侵入性诊断工具之一。它具有低成本,安全性以及在各种医学成像应用中的快速发展等诸多优点。在这项工作中,使用了基于真实体内实验结果设计的虚拟体模进行3D建模和仿真。针对每个体内个案构建模型,以确保乳房组织的生物力学特征。这些模型集成了多个乳腺肿瘤的参数,包括大小,形状和位置。特别是,通过体内弹性成像的各种细节,使用了数学和计算分析来比较这项工作的结果。肿瘤歧视;根据乳腺肿瘤的非线性生物力学特性,进行恶性或良性的检查。为了计算主要分类参数,分析并凭经验拟合了可疑肿块与正常周围背景组织之间的组织变形和应变差异。结果表明,模型输出与体内诊断弹性成像图之间具有良好的一致性。通常,引入的有限元建模方法可以被认为是早期对乳腺肿瘤进行分类的非侵入性诊断程序。 3D仿真结果可以确保对非线性生物力学特性的行为有更多的理论了解,而使用临床实验可能并不明显或不方便。

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