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Uncertainty quantification and numerical methods in charged particle radiation therapy

Stammer, Pia ORCID iD icon 1
1 Scientific Computing Center (SCC), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Radiation therapy is applied in approximately 50% of all cancer treatments. To eliminate the tumor
without damaging organs in the vicinity, optimized treatment plans are determined. This requires the
calculation of three-dimensional dose distributions in a heterogeneous volume with a spatial resolution of 2-3mm. Current planning techniques use multiple beams with optimized directions and energies to
achieve the best possible dose distribution. Each dose calculation however requires the discretization of
the six-dimensional phase space of the linear Boltzmann transport equation describing complex particle
dynamics. Despite the complexity of the problem, dose calculation errors of less than 2% are clinically
recommended and computation times cannot exceed a few minutes. Additionally, the treatment reality often differs from the computed plan due to various uncertainties, for example in patient
positioning, the acquired CT image or the delineation of tumor and organs at risk. Therefore, it is essential to include uncertainties in the planning process to determine a robust treatment plan. This entails a realistic mathematical model of uncertainties, quantification of their effect on the dose distribution using appropriate propagation methods as well as a robust or probabilistic optimization of treatment parameters to account for these effects.
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Volltext §
DOI: 10.5445/IR/1000158316
Veröffentlicht am 04.05.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte und Numerische Mathematik (IANM)
Institut für Stochastik (STOCH)
Scientific Computing Center (SCC)
Publikationstyp Hochschulschrift
Publikationsdatum 04.05.2023
Sprache Englisch
Identifikator KITopen-ID: 1000158316
HGF-Programm 46.21.02 (POF IV, LK 01) Cross-Domain ATMLs and Research Groups
Verlag Karlsruher Institut für Technologie (KIT)
Umfang vii, 185 S.
Art der Arbeit Dissertation
Fakultät Fakultät für Mathematik (MATH)
Institut Institut für Angewandte und Numerische Mathematik (IANM)
Prüfungsdatum 22.03.2023
Projektinformation HIDSS4Health (HGF, HGF IVF2016 STRATPART, HIDSS-0008)
Schlagwörter uncertainty quantification, numerical methods, radiation therapy, radiative transport, Monte Carlo, particle therapy, proton therapy, dynamical low-rank approximation
Referent/Betreuer Frank, Martin
Trabs, Mathias
Jäkel, Oliver
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