Toward real-time dose-guided radiation therapy: deformable multileaf collimator tracking using motion-model-derived volumetric images in lung and liver cancer patients
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 (RPMs) 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%/2mm) 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%,…
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