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 22 Gy to the prostate, and a stage 2 plan delivering 50.4 Gy to the lymph nodes and 56 Gy 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 38 min 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.
| Original language | English |
|---|---|
| Pages (from-to) | 465-473 |
| Number of pages | 9 |
| Journal | Physica Medica |
| Volume | 32 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 1 Mar 2016 |
| Externally published | Yes |
Bibliographical note
Funding Information:The financial support by the Austrian Federal Ministry of Science, Research and Economy and the National Foundation for Research, Technology and Development is gratefully acknowledged.
Publisher Copyright:
© 2016 Associazione Italiana di Fisica Medica.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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