Purpose/Objective: Most dose-escalation trials in glioblastoma patients integrate the escalated dose throughout the standard course by targeting a specific subvolume. We hypothesize that anatomical changes during irradiation may affect the dose coverage of this subvolume for both proton- and photon-based radiotherapy. Material and Methods: For 24 glioblastoma patients a photon- and proton-based dose escalation treatment plan (of 75 Gy/30 fr) was simulated on the dedicated radiotherapy planning MRI obtained before treatment. The escalated dose was planned to cover the resection cavity and/or contrast enhancing lesion on the T1w post-gadolinium MRI sequence. To analyze the effect of anatomical changes during treatment, we evaluated on an additional MRI that was obtained during treatment the changes of the dose distribution on this specific high dose region. Results: The median time between the planning MRI and additional MRI was 26 days (range 16–37 days). The median time between the planning MRI and start of radiotherapy was relatively short (7 days, range 3–11 days). In 3 patients (12.5%) changes were observed which resulted in a substantial deterioration of both the photon and proton treatment plans. All these patients underwent a subtotal resection, and a decrease in dose coverage of more than 5% and 10% was observed for the photon- and proton-based treatment plans, respectively. Conclusion: Our study showed that only for a limited number of patients anatomical changes during photon or proton based radiotherapy resulted in a potentially clinically relevant underdosage in the subvolume. Therefore, volume changes during treatment are unlikely to be responsible for the negative outcome of dose-escalation studies.
Background and purpose: Treatment plan verification of intensity modulated radiotherapy (IMRT) is generally performed with the gamma index (GI) evaluation method, which is difficult to extrapolate to clinical implications. Incorporating Dose Volume Histogram (DVH) information can compensate for this. The aim of this study was to evaluate DVH-based treatment plan verification in addition to the GI evaluation method for head and neck IMRT.Materials and methods: Dose verifications of 700 subsequent head and neck cancer IMRT treatment plans were categorised according to gamma and DVH-based action levels. Fractionation dependent absolute dose limits were chosen. The results of the gamma- and DVH-based evaluations were compared to the decision of the medical physicist and/or radiation oncologist for plan acceptance.Results: Nearly all treatment plans (99.7%) were accepted for treatment according to the GI evaluation combined with DVH-based verification. Two treatment plans were re-planned according to DVH-based verification, which would have been accepted using the evaluation alone. DVH-based verification increased insight into dose delivery to patient specific structures increasing confidence that the treatment plans were clinically acceptable. Moreover, DVH-based action levels clearly distinguished the role of the medical physicist and radiation oncologist within the Quality Assurance (QA) procedure.Conclusions: DVH-based treatment plan verification complements the GI evaluation method improving head and neck IMRT-QA.
Background and purpose: Automatic approaches are widely implemented to automate dose optimization in radiotherapy treatment planning. This study systematically investigates how to configure automatic planning in order to create the best possible plans. Materials and methods: Automatic plans were generated using protocol based automatic iterative optimization. Starting from a simple automation protocol which consisted of the constraints for targets and organs at risk (OAR), the performance of the automatic approach was evaluated in terms of target coverage, OAR sparing, conformity, beam complexity, and plan quality. More complex protocols were systematically explored to improve the quality of the automatic plans. The protocols could be improved by adding a dose goal on the outer 2 mm of the PTV, by setting goals on strategically chosen subparts of OARs, by adding goals for conformity, and by limiting the leaf motion. For prostate plans, development of an automated post-optimization procedure was required to achieve precise control over the dose distribution. Automatic and manually optimized plans were compared for 20 head and neck (H&N), 20 prostate, and 20 rectum cancer patients. Results: Based on simple automation protocols, the automatic optimizer was not always able to generate adequate treatment plans. For the improved final configurations for the three sites, the dose was lower in automatic plans compared to the manual plans in 12 out of 13 considered OARs. In blind tests, the automatic plans were preferred in 80% of cases. Conclusions: With adequate, advanced, protocols the automatic planning approach is able to create high-quality treatment plans.
