During radiotherapy of lung tumors, the respiratory motion must be tracked to reduce radiation of healthy tissue. This is usually done by using a respiratory surrogate, but with limited accuracy. We investigate how patient-specific finite element models (FEM) of respiratory mechanics can predict the motion of the lungs. First, the anatomical models of the lungs and thorax are extracted from CT images automatically. Then, a biomechanical model is used to simulate the respiratory motion based on a novel thorax/lung interaction force that simulates the pleural cavity. Our model is not driven by image forces but by thoracic pressures personalized using a multivariate optimizer. The proposed model is validated on three DIR-Lab datasets, yielding a promising internal land- mark error of 3.33 ± 0.60 mm. Our model may represent a tool for lung deformation prediction and therapy guidance.
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During radiotherapy of lung tumors, the respiratory motion must be tracked to reduce radiation of healthy tissue. This is usually done by using a respiratory surrogate, but with limited accuracy. We investigate how patient-specific finite element models (FEM) of respiratory mechanics can predict the motion of the lungs. First, the anatomical models of the lungs and thorax are extracted from CT images automatically. Then, a biomechanical model is used to simulate the respiratory motion based on a...
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