Robust radiotherapy planning

Jan Unkelbach, Markus Alber, Mark Bangert, Rasmus Bokrantz, Timothy C Y Chan, Joseph O Deasy, Albin Fredriksson, Bram L Gorissen, Marcel van Herk, Wei Liu, Houra Mahmoudzadeh, Omid Nohadani, Jeffrey V Siebers, Marnix Witte, Huijun Xu

Research output: Contribution to journalArticlepeer-review

Abstract

Motion and uncertainty in radiotherapy is traditionally handled via margins. The clinical target volume (CTV) is expanded to a larger planning target volume (PTV), which is irradiated to the prescribed dose. However, the PTV concept has several limitations, especially in proton therapy. Therefore, robust and probabilistic optimization methods have been developed that directly incorporate motion and uncertainty into treatment plan optimization for intensity modulated radiotherapy (IMRT) and intensity modulated proton therapy (IMPT). Thereby, the explicit definition of a PTV becomes obsolete and treatment plan optimization is directly based on the CTV. Initial work focused on random and systematic setup errors in IMRT. Later, inter-fraction prostate motion and intra-fraction lung motion became a research focus. Over the past ten years, IMPT has emerged as a new application for robust planning methods. In proton therapy, range or setup errors may lead to dose degradation and misalignment of dose contributions from different beams - a problem that cannot generally be addressed by margins. Therefore, IMPT has led to the first implementations of robust planning methods in commercial planning systems, making these methods available for clinical use. This paper first summarizes the limitations of the PTV concept. Subsequently, robust optimization methods are introduced and their applications in IMRT and IMPT planning are reviewed.

Original languageEnglish
Pages (from-to)22TR02
JournalPhysics in Medicine and Biology
Volume63
Issue number22
Early online date12 Nov 2018
DOIs
Publication statusPublished - 13 Nov 2018

Research Beacons, Institutes and Platforms

  • Manchester Cancer Research Centre

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