Abstract Objective: Accurate dose delivery in the presence of anatomical motion and deformation remains a major challenge in radiation therapy. Real-time dose-guided radiation therapy addresses this challenge by integrating volumetric imaging, dose accumulation, and adaptive treatment in a quasi-continuous manner. Unlike previous studies limited to rigid motion or phantom data, this study employs a motion model to generate real-time volumetric images, enabling deformable dose-guided multileaf collimator (MLC) tracking in lung and liver cancer patients.Approach: Deformable dose-guided MLC tracking was simulated for ten patients (4 lung, 6 liver). The workflow included: (1) training a patient-specific linear regression-based motion model relating external respiratory signals (RPM) to deformation vector fields using planning 4DCT data, (2) generating volumetric images using treatment RPM signals, (3) simulating dose-guided MLC tracking comparing deformable, rigid and no tracking, and (4) evaluating the motion model accuracy using fiducial markers and kV imaging. Dosimetric accuracy was assessed using 3D Gamma analysis (2%/2 mm) and normalized root mean squared error by comparing simulated delivered dose to a motion-compensated baseline. Motion model error was quantified as the distance between predicted and ground truth marker positions.Main results: Deformable tracking significantly outperformed rigid and no tracking (p < 0.001), achieving a mean Gamma passing rate of 95.0 ± 6.0%, compared to 86.3 ± 10.0% and 74.8 ± 15.2%, respectively. Lung patients showed a greater benefit in Gamma passing rate (deformable: 98% vs. rigid: 85%, +13%) than liver patients (93% vs. 89%, +4%). The dosimetric benefit correlated with respiratory amplitude, with larger motion yielding greater improvements. The motion model demonstrated high accuracy, with a mean error of 0.1 ± 2.9 mm. Significance: This study demonstrates the feasibility and dosimetric advantage of deformable dose-guided MLC tracking using motion-model-derived volumetric imaging in patient data. These findings represent a critical step toward the clinical implementation of real-time dose-guided radiation therapy.
Büttgen et al. (Wed,) studied this question.