A biomechanical model of mammographic compressions
A biomechanical model of mammographic compressions
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DOI：
10.1007/s10237-006-0074-6
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发表时间：
2008-02-01
影响因子：
3.5
通讯作者：
Nash, M. P.
中科院分区：
文献类型：
--
作者：
Chung, J. H.;Rajagopal, V.;Nash, M. P.
已经提出了许多生物力学模型来改进多模态乳房图像对准的非刚性配准技术。可变形乳房模型也可能有助于克服解释 3D 体积（乳房组织）的 2D X 射线投影（乳房 X 光照片）的困难。如果可变形模型能够准确预测乳房 X 光检查期间乳房发生的形状变化，那么该模型可以用于定位空载状态下的可疑肿块（在乳房 X 光检查中可见），或进一步研究所需的任何其他变形状态（例如活检或其他医学成像方式）。在本文中，我们提出了一项验证研究，该研究的目的是开发基于完善的连续介质力学理论（接触力学的有限弹性理论）的生物力学模型，并展示其在该应用中的用途。使用凝胶模型进行实验研究，以测试预测类似乳腺X线摄影的变形的准确性。使用非线性优化过程估计凝胶体模的材料特性，通过调整与新胡克本构关系相关的参数，最大限度地减少实验和模型预测表面数据之间的误差。对模型进行两次压缩（相当于颅尾和内侧乳房 X 光检查），并使用 MRI 扫描仪记录相应的变形。使用具有适当边界条件的估计材料特性进行有限元模拟来模拟实验。模拟结果与变形体模的实验记录相匹配，每个压缩状态的均方根误差为亚毫米。现在验证了我们的乳房压缩有限元模型，下一阶段是将模型应用于临床图像。
A number of biomechanical models have been proposed to improve nonrigid registration techniques for multimodal breast image alignment. A deformable breast model may also be useful for overcoming difficulties in interpreting 2D X-ray projections (mammograms) of 3D volumes (breast tissues). If a deformable model could accurately predict the shape changes that breasts undergo during mammography, then the model could serve to localize suspicious masses (visible in mammograms) in the unloaded state, or in any other deformed state required for further investigations (such as biopsy or other medical imaging modalities). In this paper, we present a validation study that was conducted in order to develop a biomechanical model based on the well-established theory of continuum mechanics (finite elasticity theory with contact mechanics) and demonstrate its use for this application.Experimental studies using gel phantoms were conducted to test the accuracy in predicting mammographic-like deformations. The material properties of the gel phantom were estimated using a nonlinear optimization process, which minimized the errors between the experimental and the model-predicted surface data by adjusting the parameter associated with the neo-Hookean constitutive relation. Two compressions (the equivalent of cranio-caudal and medio-lateral mammograms) were performed on the phantom, and the corresponding deformations were recorded using a MRI scanner. Finite element simulations were performed to mimic the experiments using the estimated material properties with appropriate boundary conditions. The simulation results matched the experimental recordings of the deformed phantom, with a sub-millimeter root-mean-square error for each compression state. Having now validated our finite element model of breast compression, the next stage is to apply the model to clinical images.