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Local weighting of nanometric track structure properties in macroscopic voxel geometries for particle beam treatment planning.
Alexander, F; Villagrasa, C; Rabus, H; Wilkens, J J.
  • Alexander F; Department of Radiation Oncology, Technische Universität München, Klinikum rechts der Isar, Ismaninger Straße 22, 81675 München, Germany.
Phys Med Biol ; 60(23): 9145-56, 2015 Dec 07.
Article en En | MEDLINE | ID: mdl-26562133
ABSTRACT
The research project BioQuaRT within the European Metrology Research Programme aimed at correlating ion track structure characteristics with the biological effects of radiation and developed measurement and simulation techniques for determining ion track structure on different length scales from about 2 nm to about 10 µm. Within this framework, we investigated methods to translate track-structure quantities derived on a nanometre scale to macroscopic dimensions. Here we make use of parameterizations that link the energy of the projectile to the ionization pattern of the track using nanodosimetric ionization cluster size distributions. They were defined with data generated by simulations of ion tracks in liquid water using the Geant4 Monte Carlo toolkit with the Geant4-DNA processes. For the clinical situation with a mixed radiation field, where particles of various energies hit a cell from several directions, we have to find macroscopic relevant mean values. They can be determined by appropriate local weighting functions for the identified parameterization. We show that a stopping power weighted mean value of the mentioned track structure properties can describe the overall track structure in a cell exposed to a mixed radiation field. The parameterization, together with the presented stopping power weighting approach, show how nanometric track structure properties could be integrated into treatment planning systems without the need to perform time consuming simulations on the nanometer level for each individual patient.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Planificación de la Radioterapia Asistida por Computador / ADN / Nanotecnología / Terapia de Protones / Neoplasias Tipo de estudio: Health_economic_evaluation / Prognostic_studies Límite: Humans Idioma: En Año: 2015 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Planificación de la Radioterapia Asistida por Computador / ADN / Nanotecnología / Terapia de Protones / Neoplasias Tipo de estudio: Health_economic_evaluation / Prognostic_studies Límite: Humans Idioma: En Año: 2015 Tipo del documento: Article