Impact of physiological and biomechanical parameters on lung deformation and the accuracy of lung tumor motion estimation

Patient-specific biomechanical models of the respiratory system can enhance the prediction of lung tumor positions and deformations for radiation therapy. To achieve this, we have developed a patient-specific biomechanical model of the entire respiratory system. However, the accuracy of the simulation is highly influenced by mechanical behavior as well as biomechanical and physiological properties. In this study, we have investigated the impact of simplification and variability in mechanical and physiological property uncertainties on lung tumor motion prediction. Specifically, we have evaluated and compared the most commonly used values of the lung tissue Young's modulus and Poisson's ratio found in the literature. Furthermore, we have examined the effect of a simple and fast linear compliance model versus a nonlinear, personalized physiological lung compliance model in computing lung and diaphragm strain. We have also explored the impact of different nonlinear behavior models to identify the most suitable mechanical model for respiratory simulation. To this end, we have conducted a study on four widely referenced hyperelastic models. Numerical simulations were performed on public datasets using the Neo-Hooke, Yeoh, Mooney-Rivlin, and St. Venant-Kirchhoff hyperelastic models. We have observed that nonlinear personalized compliance enhances accuracy and yields better results compared to linear compliance. The simulations in this study showed minimal and negligible variations with different values of Young's modulus. In contrast, variations in Poisson's ratio significantly impacted the simulation results. In our simulations, the Saint-Venant-Kirchhoff and Mooney-Rivlin models demonstrated the highest accuracy for simulating lung tissue across all phases of respiration, with an average landmark error of 2.1±1.3mm. This model has the potential to provide precise tumor motion predictions, helping physicians reduce safety margins and minimize damage to healthy tissues during radiation therapy.