Abstract
BACKGROUND: We introduced a probabilistic treatment planning approach that prospectively incorporates respiratory-induced motion in the treatment plan optimization. The aim of this study was to determine the potential dosimetric benefit by comparing this approach to the use of an internal target volume (ITV). MATERIAL AND METHOD: We retrospectively compared the probabilistic respiratory motion-incorporated (RMI) approach to the ITV approach for 18 pancreatic cancer patients, for seven simulated respiratory amplitudes from 5 to 50 mm in the superior-inferior (SI) direction. For each plan, we assessed the target coverage (required: D98%>/=95% of 50 Gy prescribed dose). For the RMI plans, we investigated whether target coverage was robust against daily variations in respiratory amplitude. We determined the distance between the clinical target volume and the 30 Gy isodose line (i.e. dose gradient steepness) in the SI direction. To investigate the clinical benefit of the RMI approach, we created for each patient an ITV and RMI treatment plan for the three-dimensional (3D) respiratory amplitudes observed on their pretreatment 4D computed tomography (4DCT). We determined Dmean, V30Gy, V40Gy and V50Gy for the duodenum. RESULTS: All treatment plans yielded good target coverage. The RMI plans were robust against respiratory amplitude variations up to 10 mm, as D98% remained >/=95%. We observed steeper dose gradients compared to the ITV approach, with a mean decrease from 25.9 to 19.2 mm for a motion amplitude of 50 mm. For the 4DCT motion amplitudes, the RMI approach resulted in a mean decrease of 0.43 Gy, 1.1 cm3, 1.4 cm3 and 0.9 cm3 for the Dmean, V30Gy, V40Gy and V50Gy of the duodenum, respectively. CONCLUSION: The probabilistic treatment planning approach yielded significantly steeper dose gradients and therefore significantly lower dose to surrounding healthy tissues than the ITV approach. However, the observed dosimetric gain for clinically observed respiratory motion amplitudes for this patient group was limited.
