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

Development of treatment planning algorithm for the discrete spot scanning system

Meeting Abstract

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  • R. Fujimoto - Energy and Environmental Systems Laboratory, Hitachi, Ltd., Hitachi-shi, Japan
  • S. Fujitaka - Energy and Environmental Systems Laboratory, Hitachi, Ltd., Hitachi-shi, Japan
  • K. Hiramoto - Energy and Environmental Systems Laboratory, Hitachi, Ltd., Hitachi-shi, Japan

PTCOG 48. Meeting of the Particle Therapy Co-Operative Group. Heidelberg, 28.09.-03.10.2009. Düsseldorf: German Medical Science GMS Publishing House; 2009. Doc09ptcog067

DOI: 10.3205/09ptcog067, URN: urn:nbn:de:0183-09ptcog0677

Published: September 24, 2009

© 2009 Fujimoto et al.
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Outline

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Background: The spot scanning method makes it possible to produce various dose distributions flexibly by modulating weights of thousands of spots. In the discrete spot scanning system, the process for planning irradiation parameters has three steps, 1) Select spot positions, 2) Optimize weights (MU) for each spot, 3) Rearrange the resultant spot weights. In the third step, the typical processing is calculation of the number of repainting for each spot under a constraint of maximum/minimum value of MU per spot. These irradiation parameters influence the performance of the scanning system such as the dose uniformity and the irradiation time. As a consequence, the performance depends on not only the hardware ability but also these parameters.

Methods: We have developed treatment planning algorithm to evaluate the performance for the discrete spot scanning system. In this method, the irradiation parameters can be determined and examined as the following steps. 1) Select spot positions: Spot positions should be selected in order to cover a whole target along some rules. In the usual case, a lateral spot spacing is set to a fixed value in the target. We change the spacing flexibly depending on the spot size to shorten the irradiation time. 2) Optimize weights: The values of MU for each spot are determined by an iterative optimization process. We adopt the quasi-Newton method. Since the MU per spot is limited by performance of the hardware, the optimization is performed in consideration of the condition. The spots which have MU less than the minimum value are eliminated in the iteration. 3) Rearrange the spot weights: The number of repainting is calculated such that each MU does not exceed the maximum value, which is followed by the selection of a scanning sequence. 4) Evaluate the results: Using parameters such as the scanning sequence and the number of repainting, we can estimate the irradiation time as well as the dose distribution according to the hardware conditions.

Results: We have developed the treatment planning algorithm in order to investigate the performance of the scanning system. The analysis result will be presented.