Martin Buschmann1, Yvette Seppenwoolde2, Tilo Wiezorek3, Kirsten Weibert3, Dietmar Georg2. 1. Department of Radiation Oncology, Comprehensive Cancer Center, Medical University of Vienna/AKH Wien, Vienna, Austria; Christian Doppler Laboratory for Medical Radiation Research for Radiation Oncology, Medical University of Vienna, Vienna, Austria. Electronic address: martin.buschmann@meduniwien.ac.at. 2. Department of Radiation Oncology, Comprehensive Cancer Center, Medical University of Vienna/AKH Wien, Vienna, Austria; Christian Doppler Laboratory for Medical Radiation Research for Radiation Oncology, Medical University of Vienna, Vienna, Austria. 3. Department of Radiation Oncology, University Hospital Jena, Jena, Germany.
Abstract
PURPOSE: Radiation treatment planning inherently involves multiple conflicting planning goals, which makes it a suitable application for multicriteria optimization (MCO). This study investigates a MCO algorithm for VMAT planning (VMAT-MCO) for prostate cancer treatments including pelvic lymph nodes and uses standard inverse VMAT optimization (sVMAT) and Tomotherapy planning as benchmarks. METHODS: For each of ten prostate cancer patients, a two stage plan was generated, consisting of a stage 1 plan delivering 22Gy to the prostate, and a stage 2 plan delivering 50.4Gy to the lymph nodes and 56Gy to the prostate with a simultaneous integrated boost. The single plans were generated by three planning techniques (VMAT-MCO, sVMAT, Tomotherapy) and subsequently compared with respect to plan quality and planning time efficiency. RESULTS: Plan quality was similar for all techniques, but sVMAT showed slightly better rectum (on average Dmean -7%) and bowel sparing (Dmean -17%) compared to VMAT-MCO in the whole pelvic treatments. Tomotherapy plans exhibited higher bladder dose (Dmean +42%) in stage 1 and lower rectum dose (Dmean -6%) in stage 2 than VMAT-MCO. Compared to manual planning, the planning time with MCO was reduced up to 12 and 38min for stage 1 and 2 plans, respectively. CONCLUSION: MCO can generate highly conformal prostate VMAT plans with minimal workload in the settings of prostate-only treatments and prostate plus lymph nodes irradiation. In the whole pelvic plan manual VMAT optimization led to slightly improved OAR sparing over VMAT-MCO, whereas for the primary prostate treatment plan quality was equal.
PURPOSE: Radiation treatment planning inherently involves multiple conflicting planning goals, which makes it a suitable application for multicriteria optimization (MCO). This study investigates a MCO algorithm for VMAT planning (VMAT-MCO) for prostate cancer treatments including pelvic lymph nodes and uses standard inverse VMAT optimization (sVMAT) and Tomotherapy planning as benchmarks. METHODS: For each of ten prostate cancerpatients, a two stage plan was generated, consisting of a stage 1 plan delivering 22Gy to the prostate, and a stage 2 plan delivering 50.4Gy to the lymph nodes and 56Gy to the prostate with a simultaneous integrated boost. The single plans were generated by three planning techniques (VMAT-MCO, sVMAT, Tomotherapy) and subsequently compared with respect to plan quality and planning time efficiency. RESULTS: Plan quality was similar for all techniques, but sVMAT showed slightly better rectum (on average Dmean -7%) and bowel sparing (Dmean -17%) compared to VMAT-MCO in the whole pelvic treatments. Tomotherapy plans exhibited higher bladder dose (Dmean +42%) in stage 1 and lower rectum dose (Dmean -6%) in stage 2 than VMAT-MCO. Compared to manual planning, the planning time with MCO was reduced up to 12 and 38min for stage 1 and 2 plans, respectively. CONCLUSION: MCO can generate highly conformal prostate VMAT plans with minimal workload in the settings of prostate-only treatments and prostate plus lymph nodes irradiation. In the whole pelvic plan manual VMAT optimization led to slightly improved OAR sparing over VMAT-MCO, whereas for the primary prostate treatment plan quality was equal.
Authors: Martin Buschmann; Abdul Wahab M Sharfo; Joan Penninkhof; Yvette Seppenwoolde; Gregor Goldner; Dietmar Georg; Sebastiaan Breedveld; Ben J M Heijmen Journal: Strahlenther Onkol Date: 2017-12-21 Impact factor: 3.621