Modeling lung deformation: A combined deformable image registration method with spatially varying Young's modulus estimates
Modeling lung deformation: A combined deformable image registration method with spatially varying Young's modulus estimates
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DOI：
10.1118/1.4812419
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发表时间：
2013-08-01
期刊：
影响因子：
3.8
通讯作者：
Guerrero, Thomas
中科院分区：
文献类型：
--
作者：
Li, Min;Castillo, Edward;Guerrero, Thomas
目的：呼吸运动引起的肿瘤位置和肺变形的不确定性，这往往导致胸部放射治疗中的剂量分布计算困难。可变形图像配准（DIR）能够描述呼吸引起的肺部变形，放射治疗技术可以向肿瘤提供高剂量，同时减少周围正常组织的辐射。作者的目标是提出一种新的方法来克服以前的肺变形生物力学模型的两个主要挑战，即，方法：与生物力学建模中的典型方法不同，本文的方法假设肺组织是非均匀的。因此，作者提出了一种将变强度流（VF）块匹配算法与有限元法（FEM）相结合的方法，用于从呼气末阶段到吸气末阶段的肺变形。具体地，肺变形被公式化为应力-应变问题，对于该应力-应变问题，从VF块匹配算法获得边界条件，并且通过用拟牛顿法求解优化问题来估计元件特定的杨氏模量分布。作者测量他们的非均匀模型的空间精度，以及一个标准的统一模型，通过应用这两种方法，四维计算机断层扫描图像的6名患者。使用大量（>1000）专家确定的标志点对计算配准产生的空间误差。结果：在左右、前后和上下方向上，由标准均匀有限元模型产生的平均误差（标准偏差）为1.42（1.42）、1.06（1.05）和1.98而作者提出的非均匀模型将这些误差降低到0.59（0.61）、0.52（0.51）和0.78（0.89）mm。总体3D平均误差为3.05（2.36）和1.30（0.97）mm的均匀和非均匀模型，分别。结果表明，所提出的非均匀模型可以通过空间变化的杨氏模量估计来模拟患者特异性和位置特异性肺变形，其与均匀模型相比提高了配准精度，因此是肺变形的更合适的描述。(C)2013年美国医学物理学家协会。
Purpose: Respiratory motion introduces uncertainties in tumor location and lung deformation, which often results in difficulties calculating dose distributions in thoracic radiation therapy. Deformable image registration (DIR) has ability to describe respiratory-induced lung deformation, with which the radiotherapy techniques can deliver high dose to tumors while reducing radiation in surrounding normal tissue. The authors' goal is to propose a DIR method to overcome two main challenges of the previous biomechanical model for lung deformation, i.e., the requirement of precise boundary conditions and the lack of elasticity distribution.Methods: As opposed to typical methods in biomechanical modeling, the authors' method assumes that lung tissue is inhomogeneous. The authors thus propose a DIR method combining a varying intensity flow (VF) block-matching algorithm with the finite element method (FEM) for lung deformation from end-expiratory phase to end-inspiratory phase. Specifically, the lung deformation is formulated as a stress-strain problem, for which the boundary conditions are obtained from the VF block-matching algorithm and the element specific Young's modulus distribution is estimated by solving an optimization problem with a quasi-Newton method. The authors measure the spatial accuracy of their nonuniform model as well as a standard uniform model by applying both methods to four-dimensional computed tomography images of six patients. The spatial errors produced by the registrations are computed using large numbers (>1000) of expert-determined landmark point pairs.Results: In right-left, anterior-posterior, and superior-inferior directions, the mean errors (standard deviation) produced by the standard uniform FEM model are 1.42(1.42), 1.06(1.05), and 1.98(2.10) mm whereas the authors' proposed nonuniform model reduces these errors to 0.59(0.61), 0.52(0.51), and 0.78(0.89) mm. The overall 3D mean errors are 3.05(2.36) and 1.30(0.97) mm for the uniform and nonuniform models, respectively.Conclusions: The results indicate that the proposed nonuniform model can simulate patient-specific and position-specific lung deformation via spatially varying Young's modulus estimates, which improves registration accuracy compared to the uniform model and is therefore a more suitable description of lung deformation. (C) 2013 American Association of Physicists in Medicine.