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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Medical Physicsarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Medical Physics
Article . 2024 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
Medical Physics
Article . 2024
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LET‐based approximation of the microdosimetric kinetic model for proton radiotherapy

Authors: Alessio, Parisi; Keith M, Furutani; Tatsuhiko, Sato; Chris J, Beltran;

LET‐based approximation of the microdosimetric kinetic model for proton radiotherapy

Abstract

AbstractBackgroundPhenomenological relative biological effectiveness (RBE) models for proton therapy, based on the dose‐averaged linear energy transfer (LET), have been developed to address the apparent RBE increase towards the end of the proton range. The results of these phenomenological models substantially differ due to varying empirical assumptions and fitting functions. In contrast, more theory‐based approaches are used in carbon ion radiotherapy, such as the microdosimetric kinetic model (MKM). However, implementing microdosimetry‐based models in LET‐based proton therapy treatment planning systems poses challenges.PurposeThis work presents a LET‐based version of the MKM that is practical for clinical use in proton radiotherapy.MethodsAt first, we derived an approximation of the Mayo Clinic Florida (MCF) MKM for relatively‐sparsely ionizing radiation such as protons. The mathematical formalism of the proposed model is equivalent to the original MKM, but it maintains some key features of the MCF MKM, such as the determination of model parameters from measurable cell characteristics. Subsequently, we carried out Monte Carlo calculations with PHITS in different simulated scenarios to establish a heuristic correlation between microdosimetric quantities and the dose averaged LET of protons.ResultsA simple allometric function was found able to describe the relationship between the dose‐averaged LET of protons and the dose‐mean lineal energy, which includes the contributions of secondary particles. The LET‐based MKM was used to model the in vitro clonogenic survival RBE of five human and rodent cell lines (A549, AG01522, CHO, T98G, and U87) exposed to pristine and spread‐out Bragg peak (SOBP) proton beams. The results of the LET‐based MKM agree well with the biological data in a comparable or better way with respect to the other models included in the study. A sensitivity analysis on the model results was also performed.ConclusionsThe LET‐based MKM integrates the predictive theoretical framework of the MCF MKM with a straightforward mathematical description of the RBE based on the dose‐averaged LET, a physical quantity readily available in modern treatment planning systems for proton therapy.

Related Organizations
Keywords

Kinetics, Radiotherapy Planning, Computer-Assisted, Proton Therapy, Humans, Animals, Linear Energy Transfer, Radiometry, Monte Carlo Method, Models, Biological, Relative Biological Effectiveness

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
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