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Treatment planning for heavy-ion radiotherapy: physical beam model and dose optimization

Open access
Krämer, M, Jäkel, O, Haberer, T, Kraft, G, Schardt, D, Weber, U·2000·Physics in Medicine and Biology

Abstract

We describe a novel code system, TRiP, dedicated to the planning of radiotherapy with energetic ions, in particular 12C. The software is designed to cooperate with three-dimensional active dose shaping devices like the GSI raster scan system. This unique beam delivery system allows us to select any combination from a list of 253 individual beam energies, 7 different beam spot sizes and 15 intensity levels. The software includes a beam model adapted to and verified for carbon ions. Inverse planning techniques are implemented in order to obtain a uniform target dose distribution from clinical input data, i.e. CT images and patient contours. This implies the automatic generation of intensity modulated fields of heavy ions with as many as 40000 raster points, where each point corresponds to a specific beam position, energy and particle fluence. This set of data is directly passed to the beam delivery and control system. The treatment planning code has been in clinical use since the start of the GSI pilot project in December 1997. Forty-eight patients have been successfully planned and treated.

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Metadata

Authors
Krämer, M., Jäkel, O., Haberer, T., Kraft, G., Schardt, D., & Weber, U.
Venue
Physics in Medicine and Biology
Published
2000-10-23
Volume
45
Issue
11
Pages
3299-3317
ISSN
  • 0031-9155 (ISSN-L)
  • 1361-6560
OpenAlex
W1991938051
Cited by
505
References
0
FWCI
6.87
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Treatment planning for heavy-ion radiotherapy: physical beam model and dose optimization. https://app.cochat.ai/papers/10.1088/0031-9155/45/11/313
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Krämer, M., Jäkel, O., Haberer, T., Kraft, G., Schardt, D., & Weber, U. (2000). Treatment planning for heavy-ion radiotherapy: physical beam model and dose optimization. Physics in Medicine and Biology. https://doi.org/10.1088/0031-9155/45/11/313

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.