Design and validation of a MV/kV imaging‐based markerless tracking system for assessing real‐time lung tumor motion. Issue 12 (13th November 2018) - Zhang, Pengpeng
Abstract : Purpose: Localizing lung tumors during treatment delivery is critical for managing respiratory motion, ensuring tumor coverage, and reducing toxicities. The purpose of this project is to develop a real‐time system that performs markerless tracking of lung tumors using simultaneously acquired MV and kV images during radiotherapy of lung cancer with volumetric modulated arc therapy. Method: Continuous MV/kV images were simultaneously acquired during dose delivery. In the subsequent analysis, a gantry angle‐specific region of interest was defined according to the treatment aperture. After removing imaging artifacts, processed MV/kV images were directly registered to the corresponding daily setup cone‐beam CT (CBCT) projections that served as reference images. The registration objective function consisted of a sum of normalized cross‐correlation, weighted by the contrast‐to‐noise ratio of each MV and kV image. The calculated 3D shifts of the tumor were corrected by the displacements between the CBCT projections and the planning respiratory correlated CT (RCCT) to generate motion traces referred to a specific respiratory phase. The accuracy of the algorithm was evaluated on both anthropomorphic phantom and patient studies. The phantom consisted of localizing a 3D printed tumor, embedded in a thorax phantom, in an arc delivery. In an IRB‐approved study, data were obtained from VMAT treatments of two lung cancer patients with three electromagnetic (Calypso) beacon transponders implanted in airways near the lung tumor. Result: In the phantom study, the root mean square error (RMSE) between the registered and actual (programmed couch movement) target position was 1.2 mm measured by the MV/kV imaging system, which was smaller compared to the MV or kV alone, of 4.1 and 1.3 mm, respectively. In the patient study, the mean and standard deviation discrepancy between electromagnetic‐based tumor position and the MV/KV‐markerless approach was −0.2 ± 0.6 mm, 0.2 ± 1.0 mm, and −1.2 ± 1.5 mm along the superior‐inferior, anterior‐posterior, and left‐right directions, respectively; resulting in a 3D displacement discrepancy of 2.0 ± 1.1 mm. Poor contrast around the tumor was the main contribution to registration uncertainties. Conclusion: The combined MV/kV imaging system can provide real‐time 3D localization of lung tumor, with comparable accuracy to the electromagnetic‐based system when features of tumors are detectable. Careful design of a registration algorithm and a VMAT plan that maximizes the tumor visibility are key elements for a successful MV/KV localization strategy.