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.
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Introduction: Patients with cancer receiving radio- or chemotherapy undergo many immunological stressors. Chronic regular exercise has been shown to positively influence the immune system in several populations, while exercise overload may have negative effects. Exercise is currently recommended for all patients with cancer. However, knowledge regarding the effects of exercise on immune markers in patients undergoing chemo- or radiotherapy is limited. The aim of this study is to systematically review the effects of moderate- and high-intensity exercise interventions in patients with cancer during chemotherapy or radiotherapy on immune markers. Methods: For this review, a search was performed in PubMed and EMBASE, until March 2023. Methodological quality was assessed with the PEDro tool and best-evidence syntheses were performed both per immune marker and for the inflammatory profile. Results: Methodological quality of the 15 included articles was rated fair to good. The majority of markers were unaltered, but observed effects included a suppressive effect of exercise during radiotherapy on some proinflammatory markers, a preserving effect of exercise during chemotherapy on NK cell degranulation and cytotoxicity, a protective effect on the decrease in thrombocytes during chemotherapy, and a positive effect of exercise during chemotherapy on IgA. Conclusion: Although exercise only influenced a few markers, the results are promising. Exercise did not negatively influence immune markers, and some were positively affected since suppressed inflammation might have positive clinical implications. For future research, consensus is needed regarding a set of markers that are most responsive to exercise. Next, differential effects of training types and intensities on these markers should be further investigated, as well as their clinical implications.
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Abstract Background: We studied the relationship between trismus (maximum interincisor opening [MIO] ≤35 mm) and the dose to the ipsilateral masseter muscle (iMM) and ipsilateral medial pterygoid muscle (iMPM). Methods: Pretreatment and post-treatment measurement of MIO at 13 weeks revealed 17% of trismus cases in 83 patients treated with chemoradiation and intensity-modulated radiation therapy. Logistic regression models were fitted with dose parameters of the iMM and iMPM and baseline MIO (bMIO). A risk classification tree was generated to obtain optimal cut-off values and risk groups. Results: Dose levels of iMM and iMPM were highly correlated due to proximity. Both iMPM and iMM dose parameters were predictive for trismus, especially mean dose and intermediate dose volume parameters. Adding bMIO, significantly improved Normal Tissue Complication Probability (NTCP) models. Optimal cutoffs were 58 Gy (mean dose iMPM), 22 Gy (mean dose iMM) and 46 mm (bMIO). Conclusions: Both iMPM and iMM doses, as well as bMIO, are clinically relevant parameters for trismus prediction.
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