Purpose: To develop patient‐specific lung biomechanical models for simulating lung deformation and predicting the tumor motion position during radiation therapy. Methods: A FEA/CFD (Finite Element Analysis/Computational Fluid Dynamic) model is built to simulate the deformation of the lung. The lung is assumed to behave as a poro‐elastic medium with uniform or heterogeneous elastic property. The method used a fluid‐structure interaction technique to model flow within the airway and deformation of the lobe. A slide boundary condition was applied between the ribcage and the lung surface. The 3D lung geometry is reproduced from the end‐of‐expiration phase of a 4D‐CT scan of a lung cancer patient. Three models of elasticity data (Young's Modulus: YM) distribution are analyzed: 1. Uniform YM distribution; 2. Major Branch YM distribution; 3. Spatial YM distribution calculated from the 4D‐CT. A linear increment air pressure is added to the trachea. The displacements of 135 landmarks at each time step are statistically compared with the manual registrated data from the 4D‐CT images. Results: Without applying the slide boundary conditions between the ribcage and the side lung surface, the standard errors for all these 3 YM models are larger than 4.5 mm. Appling the slide boundary conditions, the standard error of the displacement vector for the uniform YM model is 2.8mm, the standard error is reduced to 2.7 mm for the Major Branch model, and the standard error is further reduced to 2.5 mm for the spatial YM model. Conclusions: The standard error of landmark displacement is significantly reduced by applying sliding boundary conditions. Among three YM models investigated in this study, the spatially distributed YM model derived from 4D‐CT provides highest accuracy in simulating lung respiration process. This work was supported by Cancer Prevention and Research Institute of Texas (CPRIT) RP110562‐p2.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging