TH-CD-207A-01: Evaluation of Lung Tumor Motion Management Strategy with Dynamic MRI

Abstract

Purpose: The purpose of this study is to develop a method to track and examine the correlation between the 3D motion of a lung tumor and an external surrogate with dynamic MRI. Methods: Dynamic MRI was obtained from lung cancer patients. To examine the motion correlation between external surrogates and the tumor, we placed four fiducials on the patient's chest at different locations. We acquired a contiguous multi-slice 2D cine MRI (sagittal) to capture the lung and whole tumor, followed by a two-slice 2D cine MRI (sagittal) to simultaneously track the tumor and fiducials. To extract real-time motion, we first reconstructed a phase-binned 4D-MRI from the multi-slice dataset using body area as the respiratory surrogate and a groupwise registration technique. The reconstructed 4D-MRI provided 3D template tumor volumes. Real-time 3D tumor position was calculated by 3D-2D template matching, registering 3D tumor templates and the cine 2D frames from the two-slice tracking dataset. External surrogate 3D trajectories were derived via matching a 3D geometrical model of the fiducial to image features on the 2D cine (two-slice) tracking datasets. Thus, we could analyze the correlation between the 3D trajectories of the tumor and external fiducials. Results: We tested our method on four lung cancer patients. 3D tumor motion correlated with the external surrogate signal, but showed a noticeable phase mismatch. The 3D tumor trajectory showed significant cycle-to-cycle variation, while the external surrogate was not sensitive enough to capture such variations. Additionally, surrogate signals obtained from fiducials at different locations showed noticeable phase mismatch. Conclusion: Our preliminary data show that external surrogate motion has significant variance in relation to tumor motion. Consequently, surrogate-based therapy should be used with caution. Quantitative evaluation of conventional tumor motion management methods such as the internal-target-volume-based approach as well as external-surrogate-based gating, are underway. This work was supported by NIH/NCI under grant R21CA178455.