Correspondence model-based 4D VMAT dose simulation for analysis of local metastasis recurrence after extracranial SBRT.

The purpose of this study is to introduce a novel approach to incorporate patient-specific breathing variability information into 4D dose simulation of volumetric arc therapy (VMAT)-based stereotactic body radiotherapy (SBRT) of extracranial metastases. Feasibility of the approach is illustrated by application to treatment planning and motion data of lung and liver metastasis patients. The novel 4D dose simulation approach makes use of a regression-based correspondence model that allows representing patient motion variability by breathing signal-steered interpolation and extrapolation of deformable image registration motion fields. To predict the internal patient motion during treatment with only external breathing signal measurements being available, the patients' internal motion information and external breathing signals acquired during 4D CT imaging were correlated. Combining the correspondence model, patient-specific breathing signal measurements during treatment and time-resolved information about dose delivery, reconstruction of a motion variability-affected dose becomes possible. As a proof of concept, the proposed approach is illustrated by a retrospective 4D simulation of VMAT-based SBRT treatment of ten patients with 15 treated lung and liver metastases and known clinical endpoints for the individual metastases (local metastasis recurrence yes/no). Resulting 4D-simulated dose distributions were compared to motion-affected dose distributions estimated by standard 4D CT-only dose accumulation and the originally (i.e. statically) planned dose distributions by means of GTV [Formula: see text] indices (dose to 98% of the GTV volume). A potential linkage of metastasis-specific endpoints to differences between GTV [Formula: see text] indices of planned and 4D-simulated dose distributions was analyzed.

Real time tracking in liver SBRT: comparison of CyberKnife and Vero by planning structure-based γ-evaluation and dose-area-histograms.

The purpose of this study was to evaluate and compare two clinical tracking systems for radiosurgery with regard to their dosimetric and geometrical accuracy in liver SBRT: the robot-based CyberKnife and the gimbal-based Vero. Both systems perform real-time tumour tracking by correlating internal tumour and external surrogate motion. CyberKnife treatment plans were delivered to a high resolution 2D detector array mounted on a 4D motion platform, with the platform simulating (a) tumour motion trajectories extracted from the corresponding CyberKnife predictor log files and (b) the tumour motion trajectories with superimposed baseline-drift. Static reference and tracked dose measurements were compared and dosimetric as well as geometrical uncertainties analyzed by a planning structure-based evaluation. For (a), γ-passing rates inside the CTV (γ-criteria of 1% / 1 mm) ranged from 95% to 100% (CyberKnife) and 98% to 100% (Vero). However, dosimetric accuracy decreases in the presence of the baseline-drift. γ-passing rates for (b) ranged from 26% to 92% and 94% to 99%, respectively; i.e. the effect was more pronounced for CyberKnife. In contrast, the Vero system led to maximum dose deviations in the OAR between +1.5 Gy to +6.0 Gy (CyberKnife: +0.5 Gy to +3.5 Gy). Potential dose shifts were interpreted as motion-induced geometrical tracking errors. Maximum observed shift ranges were -1.0 mm to +0.7 mm (lateral) /-0.6 mm to +0.1 mm (superior-inferior) for CyberKnife and -0.8 mm to +0.2 mm /-0.8 mm to +0.4 mm for Vero. These values illustrate that CyberKnife and Vero provide high precision tracking of regular breathing patterns. Even for the modified motion trajectory, the obtained dose distributions appear to be clinical acceptable with regard to literature QA γ-criteria of 3% / 3 mm.