Patient-specific finite element modeling of respiratory lung motion using 4D CT image data
Patient-specific finite element modeling of respiratory lung motion using 4D CT image data
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DOI：
10.1118/1.3101820
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发表时间：
2009-05-01
期刊：
影响因子：
3.8
通讯作者：
Handels, Heinz
中科院分区：
文献类型：
--
作者：
Werner, Rene;Ehrhardt, Jan;Handels, Heinz
开发和优化胸椎肿瘤放射治疗中充分考虑呼吸运动的方法需要详细了解呼吸动力学及其对相应剂量分布的影响。因此，呼吸运动的计算机辅助建模和仿真变得越来越重要。本文描述了一种模拟呼吸肺运动的生物物理方法：将肺通气过程的主要方面表述为弹性理论的接触问题，并用有限元方法求解；肺组织被认为是各向同性的、均匀的和线性弹性的。本文的主要重点是评估生物力学参数（弹性常数值）对建模过程的影响，并评估建模准确性。基于12例肺肿瘤患者的4D CT数据生成患者特异性模型。将肺内标志的模拟运动模式与4D CT数据中观察到的相应运动模式进行比较。在CT数据集中观察到的基于模型的预测地标运动和相应的呼吸诱导地标位移之间的平均绝对差异为3mm（呼气结束到吸气结束）和2mm（呼气结束到呼吸中期）。建模精度随着肿瘤大小的增加而降低，无论是局部（肿瘤附近的标志）还是全局（肺其他部位的标志）。弹性常数值的影响似乎很小。结果表明，建模方法是预测肺通气引起的肺动力学的适当策略。然而，在大肿瘤的情况下，预测质量下降，需要进一步研究肺肿瘤对整体和局部肺弹性特性的影响。
Development and optimization of methods for adequately accounting for respiratory motion in radiation therapy of thoracic tumors require detailed knowledge of respiratory dynamics and its impact on corresponding dose distributions. Thus, computer aided modeling and simulation of respiratory motion have become increasingly important. In this article a biophysical approach for modeling respiratory lung motion is described: Major aspects of the process of lung ventilation are formulated as a contact problem of elasticity theory which is solved by finite element methods; lung tissue is assumed to be isotropic, homogeneous, and linearly elastic. A main focus of the article is to assess the impact of biomechanical parameters (values of elastic constants) on the modeling process and to evaluate modeling accuracy. Patient-specific models are generated based on 4D CT data of 12 lung tumor patients. Simulated motion patterns of inner lung landmarks are compared with corresponding motion patterns observed in the 4D CT data. Mean absolute differences between model-based predicted landmark motion and corresponding breathing-induced landmark displacements as observed in the CT data sets are in the order of 3 mm (end expiration to end inspiration) and 2 mm (end expiration to midrespiration). Modeling accuracy decreases with increasing tumor size both locally (landmarks close to tumor) and globally (landmarks in other parts of the lung). The impact of the values of the elastic constants appears to be small. Outcomes show that the modeling approach is an adequate strategy in predicting lung dynamics due to lung ventilation. Nevertheless, the decreased prediction quality in cases of large tumors demands further study of the influence of lung tumors on global and local lung elasticity properties.