Lung tumor motion prediction during lung brachytherapy using finite element model

Zahra Shirzadi; Ali Sadeghi Naini; Abbas Samani

doi:10.1117/12.906511

17 February 2012 Lung tumor motion prediction during lung brachytherapy using finite element model

Zahra Shirzadi, Ali Sadeghi Naini, Abbas Samani

Proceedings Volume 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling; 83160I (2012) https://doi.org/10.1117/12.906511
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

A biomechanical model is proposed to predict deflated lung tumor motion caused by diaphragm respiratory motion. This model can be very useful for targeting the tumor in tumor ablative procedures such as lung brachytherapy. To minimize motion within the target lung, these procedures are performed while the lung is deflated. However, significant amount of tissue deformation still occurs during respiration due to the diaphragm contact forces. In the absence of effective realtime image guidance, biomechanical models can be used to estimate tumor motion as a function of diaphragm's position. To develop this model, Finite Element Method (FEM) was employed. To demonstrate the concept, we conducted an animal study of an ex-vivo porcine deflated lung with a tumor phantom. The lung was deformed by compressing a diaphragm mimicking cylinder against it. Before compression, 3D-CT image of this lung was acquired, which was segmented and turned into FE mesh. The lung tissue was modeled as hyperelastic material with a contact loading to calculate the lung deformation and tumor motion during respiration. To validate the results from FE model, the motion of a small area on the surface close to the tumor was tracked while the lung was being loaded by the cylinder. Good agreement was demonstrated between the experiment results and simulation results. Furthermore, the impact of tissue hyperelastic parameters uncertainties in the FE model was investigated. For this purpose, we performed in-silico simulations with different hyperelastic parameters. This study demonstrated that the FEM was accurate and robust for tumor motion prediction.

Citation Download Citation

Zahra Shirzadi, Ali Sadeghi Naini, and Abbas Samani "Lung tumor motion prediction during lung brachytherapy using finite element model", Proc. SPIE 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, 83160I (17 February 2012); https://doi.org/10.1117/12.906511

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