gms | German Medical Science

48th Meeting of the Particle Therapy Co-Operative Group

Particle Therapy Co-Operative Group (PTCOG)

28.09. - 03.10.2009, Heidelberg

The influence of starting conditions on the robustness of intensity modulated proton therapy plans

Meeting Abstract

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  • F. Albertini - Center for proton radiation therapy, Paul Scherrer Institute, Villigen, Switzerland
  • A. Lomax - Center for proton radiation therapy, Paul Scherrer Institute, Villigen, Switzerland
  • E. Hug - Center for proton radiation therapy, Paul Scherrer Institute, Villigen, Switzerland

PTCOG 48. Meeting of the Particle Therapy Co-Operative Group. Heidelberg, 28.09.-03.10.2009. Düsseldorf: German Medical Science GMS Publishing House; 2009. Doc09ptcog004

DOI: 10.3205/09ptcog004, URN: urn:nbn:de:0183-09ptcog0041

Published: September 24, 2009

© 2009 Albertini et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en). You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.


Outline

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Background: Intensity modulated proton therapy (IMPT) consists of the simultaneous optimization of all 3D distributed Bragg peaks (spots) from all field directions. Therefore, due to the large number of parameters available and the relatively basic goal of radiotherapy, the problem to be solved by the optimization algorithm is highly degenerate: that is, there are many fluence profiles meeting the planning aim. Thus the result of the optimization will generally depend on the starting conditions. We studied how results of IMPT plans can be ‘steered’ by the user such as to provide plans more robust to range errors (i.e. safer to be delivered).

Material and methods: IMPT plans have been optimized starting with four different ‘flavors’ of initial spots weights: (a)all spots set with an initial constant weigh, delivering a gradient from the proximal to the distal edge of the target-PTV (wedge approach); (b) weights reduced from the distal to the proximal aspect of the PTV to deliver a flat ‘Spread-Out-Bragg-Peak’(SOBP approach); (c) weights calculated to deliver a gradient from the distal (maximal dose) to the proximal edge of the PTV (inverse wedge); (d) weights set to zero everywhere but the most distal one, for each given lateral direction (i.e. distal-edge-tracking technique, DET). All cases studied had a dose limiting critical structure in the middle or abutting the PTV. An analysis of robustness to range errors has been performed by recalculating plans, assuming a systematic 3% error in the CT values. Results were compared by looking at the change in EUD values between the nominal and error dose calculations as a function of the ‘a’ parameter in the generalized EUD (gEUD) model.

Results: Results show that IMPT plans optimized with the wedge approach (a) were very sensitive to range errors, as, for the cases here studied, the organs-at-risk (OAR) were spared by patching the lateral and distal fall-offs of Bragg peaks, the last ones being strongly sensitive to range errors. Interestingly it has been found that, in case of stringent dose-volume constraints to OAR, both the DET (d) and the inverse wedge (c) approaches provide a plan pretty robust to range errors. For both approaches the dose around the OAR was, in fact, shaped mainly through the use of the lateral and the proximal aspects of Bragg peaks, with a limited use of the distal fall-off. Finally, in case of low-dose constraints to OAR the initial flat SOBP approach (b) provide a very robust plan.

Conclusion: These results seem in contrast to the work previously published by our group (Lomax 2008), which showed that generally DET is less robust than the flat SOBP method. However, in that work it was also found that, as IMPT plans become more highly modulated (due to overlap of dose limiting OAR), the flat SOBP method tends towards DET. This work extends and confirms those results. It also shows that, by adequately selecting starting conditions, it is possible to ‘steer’ the solutions to more robust plans.