Patient‐specific finite element modeling of respiratory lung motion using 4D CT image data

Abstract

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.

Predictive modeling of lung motion over the entire respiratory cycle using measured pressure‐volume data, 4DCT images, and finite‐element analysis

“…In an extension of this work, Didier et al 39 used the same FEM model and investigated the kinematic effects of the ribs on the motion during a breathing cycle by using a finite helical axis ͑FHA͒ method. Extending the work of Zhang et al, 37 Werner et al 34,45 recently proposed a respiratory lung motion model incorporating contact mechanics. Instead of using contact elements, an augmented Lagrangian algorithm was used for the contact formulation in the FEM software COMSOL MULTIPHYSICS ͑COMSOL AB, Sweden͒.…”

A poroelastic model coupled to a fluid network with applications in lung modelling

“…Several parameters for lung tissue elasticity and poroelasticity have been proposed [34,5,35,10,36], although there is no consensus in the values in the literature. In this study, we have chosen parameters as shown in Table 1 …”

“…In this work, we focus on the link between tissue deformation and ventilation. Previous work of whole organ lung models has typically focused on modelling either ventilation or tissue deformation [1,2,3,4,5,6,7,8]. However, the two components are intrinsically linked; evaluating them separately does not necessarily provide an accurate description of lung function.…”

Slipping Objects in Image Registration: Improved Motion Field Estimation with Direction-Dependent Regularization

“…This is especially the case when two objects slip along each other, which can be observed for example in the case of lung- [4] or liver motion [5].…”

“…Arising discontinuities at object boundaries are addressed by several approaches: In [4] finite element methods are used in order to simulate the physiology of respiration dynamics, point-and surface-based registration approaches are used in [6]. While these allow to explicitly or implicitly incorporate boundary conditions, inner-organ information like bronchial or vessel trees are dismissed which results in an inaccurate registration of those structures.…”