title: Sensitivity of tumor motion simulation accuracy to lung biomechanical modeling approaches and parameters.
abstract: Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the neo-Hookean compressible and uncoupled Mooney-Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney-Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney-Rivlin material model along left-right, anterior-posterior, and superior-inferior directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation.
authors.affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX 75390, USA.
authors.forename: Joubin Nasehi
authors.initials: JN
authors.lastname: Tehrani
authors.forename: Yin
authors.initials: Y
authors.lastname: Yang
authors.forename: Rene
authors.initials: R
authors.lastname: Werner
authors.forename: Wei
authors.initials: W
authors.lastname: Lu
authors.forename: Daniel
authors.initials: D
authors.lastname: Low
authors.forename: Xiaohu
authors.initials: X
authors.lastname: Guo
authors.forename: Jing
authors.initials: J
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D020342:Finite Element Analysis; D056973:Four-Dimensional Computed Tomography / Q000379:methods*; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008954:Models, Biological; D009068:Movement / Q000502:physiology*; D011857:Radiographic Image Interpretation, Computer-Assisted; D015656:Respiratory Mechanics; D055425:Respiratory-Gated Imaging Techniques