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Verfasst von:Wittmayer, Lisa [VerfasserIn]   i
 Rinaldi, Ilaria [VerfasserIn]   i
Titel:Extension of TOPAS for the simulation of proton radiation effects considering molecular and cellular endpoints
Verf.angabe:Lisa Polster, Jan Schuemann, Ilaria Rinaldi, Lucas Burigo, Aimee L. McNamara, Robert D. Stewart, Andrea Attili, David J. Carlson, Tatsuhiko Sato, José Ramos Méndez, Bruce Faddegon, Joseph Perl, Harald Paganetti
E-Jahr:2015
Jahr:10 June 2015
Umfang:18 S.
Teil:volume:60
 year:2015
 number:13
 pages:5053-5070
 extent:18
Fussnoten:Gesehen am 22.03.2017
Titel Quelle:Enthalten in: Physics in medicine and biology
Ort Quelle:Bristol : IOP Publ., 1956
Jahr Quelle:2015
Band/Heft Quelle:60(2015), 13, Seite 5053-5070
ISSN Quelle:1361-6560
Abstract:The aim of this work is to extend a widely used proton Monte Carlo tool, TOPAS, towards the modeling of relative biological effect (RBE) distributions in experimental arrangements as well as patients. TOPAS provides a software core which users configure by writing parameter files to, for instance, define application specific geometries and scoring conditions. Expert users may further extend TOPAS scoring capabilities by plugging in their own additional C++ code. This structure was utilized for the implementation of eight biophysical models suited to calculate proton RBE. As far as physics parameters are concerned, four of these models are based on the proton linear energy transfer, while the others are based on DNA double strand break induction and the frequency-mean specific energy, lineal energy, or delta electron generated track structure. The biological input parameters for all models are typically inferred from fits of the models to radiobiological experiments. The model structures have been implemented in a coherent way within the TOPAS architecture. Their performance was validated against measured experimental data on proton RBE in a spread-out Bragg peak using V79 Chinese Hamster cells. This work is an important step in bringing biologically optimized treatment planning for proton therapy closer to the clinical practice as it will allow researchers to refine and compare pre-defined as well as user-defined models.
DOI:doi:10.1088/0031-9155/60/13/5053
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext ; Verlag: http://dx.doi.org/10.1088/0031-9155/60/13/5053
 Volltext: http://stacks.iop.org/0031-9155/60/i=13/a=5053
 DOI: https://doi.org/10.1088/0031-9155/60/13/5053
Datenträger:Online-Ressource
Sprache:eng
K10plus-PPN:1555827985
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