Luise A Künzel1, Oliver S Dohm2, Markus Alber3, Daniel Zips2,4, Daniela Thorwarth5,6. 1. Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, 72076, Tübingen, Germany. 2. Department of Radiation Oncology, University Hospital Tübingen, 72076, Tübingen, Germany. 3. Radiation Oncology, University Hospital Heidelberg, 69120, Heidelberg, Germany. 4. German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany. 5. Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, 72076, Tübingen, Germany. daniela.thorwarth@med.uni-tuebingen.de. 6. German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany. daniela.thorwarth@med.uni-tuebingen.de.
Abstract
PURPOSE: To investigate a new automatic template-based replanning approach combined with constrained optimization, which may be highly useful for a rapid plan transfer for planned or unplanned machine breakdowns. This approach was tested for prostate cancer (PC) and head-and-neck cancer (HNC) cases. METHODS: The constraints of a previously optimized volumetric modulated arc therapy (VMAT) plan were used as a template for automatic plan reoptimization for different accelerator head models. All plans were generated using the treatment planning system (TPS) Hyperion. Automatic replanning was performed for 16 PC cases, initially planned for MLC1 (4 mm MLC) and reoptimized for MLC2 (5 mm) and MLC3 (10 mm) and for 19 HNC cases, replanned from MLC2 to MLC3. EUD, Dmean, D2%, and D98% were evaluated for targets; for OARs EUD and D2% were analyzed. Replanning was considered successful if both plans fulfilled equal constraints. RESULTS: All prostate cases were successfully replanned. The mean relative target EUD deviation was -0.15% and -0.57% for replanning to MLC2 and MLC3, respectively. OAR sparing was successful in all cases. Replanning of HNC cases from MLC2 to MLC3 was successful in 16/19 patients with a mean decrease of -0.64% in PTV60 EUD. In three cases target doses were substantially decreased by up to -2.58% (PTV60) and -3.44% (PTV54), respectively. Nevertheless, OAR sparing was always achieved as planned. CONCLUSIONS: Automatic replanning of VMAT plans for a different treatment machine by using pre-existing constraints as a template for a reoptimization is feasible and successful in terms of equal constraints.
PURPOSE: To investigate a new automatic template-based replanning approach combined with constrained optimization, which may be highly useful for a rapid plan transfer for planned or unplanned machine breakdowns. This approach was tested for prostate cancer (PC) and head-and-neck cancer (HNC) cases. METHODS: The constraints of a previously optimized volumetric modulated arc therapy (VMAT) plan were used as a template for automatic plan reoptimization for different accelerator head models. All plans were generated using the treatment planning system (TPS) Hyperion. Automatic replanning was performed for 16 PC cases, initially planned for MLC1 (4 mm MLC) and reoptimized for MLC2 (5 mm) and MLC3 (10 mm) and for 19 HNC cases, replanned from MLC2 to MLC3. EUD, Dmean, D2%, and D98% were evaluated for targets; for OARs EUD and D2% were analyzed. Replanning was considered successful if both plans fulfilled equal constraints. RESULTS: All prostate cases were successfully replanned. The mean relative target EUD deviation was -0.15% and -0.57% for replanning to MLC2 and MLC3, respectively. OAR sparing was successful in all cases. Replanning of HNC cases from MLC2 to MLC3 was successful in 16/19 patients with a mean decrease of -0.64% in PTV60 EUD. In three cases target doses were substantially decreased by up to -2.58% (PTV60) and -3.44% (PTV54), respectively. Nevertheless, OAR sparing was always achieved as planned. CONCLUSIONS: Automatic replanning of VMAT plans for a different treatment machine by using pre-existing constraints as a template for a reoptimization is feasible and successful in terms of equal constraints.
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