A biomechanical approach for in vivo lung tumor motion prediction during external beam radiation therapy

The most common cause of cancer death in both men and women is lung cancer. External Beam Radiation Therapy (EBRT) is one of the primary treatment methods used for lung cancer. However, dosimetric accuracy is often compromised due to respiration-induced tumor motion. Real-time tumor tracking is a common approach for lung tumor motion compensation as it allows for fast and accurate radiation delivery. Recently, we have proposed a novel biomechanics-based approach for real-time tumor tracking during EBRT. The proposed method consists of two steps. First, the chest surface motion data is used to estimate the ribcage and diaphragm motion via a correlation model. Next, the ribcage and diaphragm motion are used to drive a lung biomechanical model and obtain the tumor motion and deformation. The DICE similarity coefficient between the actual and biomechanical model generated tumor volumes ranged from 0.83 to 0.94 when the lung boundary conditions were obtained from 4D CT images. In order to obtain the lung boundary conditions from the chest motion data, we developed a correlation model between the motion of an optimal number of external chest markers and the lung boundary conditions (i.e., diaphragm and ribcage motion). Our preliminary results indicated that by using an optimal number of external chest markers, a robust and strong relationship (R-squared = 0.97) can be established between the chest surface motion and lung boundary conditions. As such, the proposed tracking algorithm can be used for accurate tracking of lung tumors during EBRT.