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A Monte Carlo-based treatment-planning tool for ion beam therapy
Stockholm University, Faculty of Science, Department of Physics. Karolinska Institutet.
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2013 (English)In: Journal of radiation research, ISSN 0449-3060, E-ISSN 1349-9157, Vol. 54, 77-81 p.Article in journal (Refereed) Published
Abstract [en]

Ion beam therapy, as an emerging radiation therapy modality, requires continuous efforts to develop and improve tools for patient treatment planning (TP) and research applications. Dose and fluence computation algorithms using the Monte Carlo (MC) technique have served for decades as reference tools for accurate dose computations for radiotherapy. In this work, a novel MC-based treatment-planning (MCTP) tool for ion beam therapy using the pencil beam scanning technique is presented. It allows single-field and simultaneous multiple-fields optimization for realistic patient treatment conditions and for dosimetric quality assurance for irradiation conditions at state-of-the-art ion beam therapy facilities. It employs iterative procedures that allow for the optimization of absorbed dose and relative biological effectiveness (RBE)-weighted dose using radiobiological input tables generated by external RBE models. Using a re-implementation of the local effect model (LEM), the MCTP tool is able to perform TP studies using ions with atomic numbers Z < 8. Example treatment plans created with the MCTP tool are presented for carbon ions in comparison with a certified analytical treatment-planning system. Furthermore, the usage of the tool to compute and optimize mixed-ion treatment plans, i.e. plans including pencil beams of ions with different atomic numbers, is demonstrated. The tool is aimed for future use in research applications and to support treatment planning at ion beam facilities.

Place, publisher, year, edition, pages
2013. Vol. 54, 77-81 p.
Keyword [en]
ion beam therapy, treatment planning, Monte Carlo, FLUKA
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:su:diva-92766DOI: 10.1093/jrr/rrt050ISI: 000321463900011OAI: oai:DiVA.org:su-92766DiVA: diva2:641929
Note

AuthorCount:8;

Available from: 2013-08-20 Created: 2013-08-20 Last updated: 2017-12-06Bibliographically approved

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