Impact of Microdosimetric Modeling on Computation of Relative Biological Effectiveness for Carbon Ion Radiotherapy
by
, , , ,
Shannon Hartzell
1,*,
Keith M. Furutani
1
,
Alessio Parisi
1,
Tatsuhiko Sato
2,3,
Yuki Kase
4,
Christian Deglow
5,
Thomas Friedrich
5 and
Chris J. Beltran
1 
1
Department of Radiation Oncology, Mayo Clinic, Jacksonville, FL 32224, USA
2
Nuclear Science and Engineering Center, Japan Atomic Energy Agency, Tokai 319-1195, Japan
3
Research Center for Nuclear Physics, Osaka University, Suita 567-0047, Japan
4
B Dot Medical Inc., Edogawa-ku 143-0003, Japan
5
GSI Helmholtzzentrum für Schwerionenforschung GmbH, 64291 Darmstadt, Germany
*
Author to whom correspondence should be addressed.
Radiation 2025, 5(2), 21; https://doi.org/10.3390/radiation5020021
Submission received: 17 April 2025
/
Revised: 8 June 2025
/
Accepted: 9 June 2025
/
Published: 12 June 2025
(This article belongs to the Section Radiation and Its Application in Oncology and Radiation Protection)
Simple Summary
Modeling energy deposition on a microscopic scale is a useful tool for predicting biological outcomes in carbon ion radiotherapy. This study investigates how different approaches to calculating microdosimetric energy deposition influence predictions of biological effectiveness, which impact delivered patient doses. We compared several established models, along with a novel implementation that enables consistent geometrical comparisons among calculation approaches. Our results show that the choice of microdosimetric model can notably affect the calculated biological effectiveness. These results highlight the need to explicitly consider both the computational method and the assumed target geometry to ensure consistent and biologically meaningful predictions in particle therapy.
Abstract
Microdosimetry plays a critical role in particle therapy by quantifying energy deposition within microscopic domains to assess biological effects. This study evaluates the influence of different microdosimetric functions (MFs) and domain geometries (DGs) on relative biological effectiveness (RBE) predictions in carbon ion radiotherapy. Specifically, we compare the analytical microdosimetric function (AMF), calculated for spherical domains and implemented in PHITS, with the Kiefer–Chatterjee (KC) track structure model, which is conventionally applied to cylindrical geometries. To enable a direct comparison, we also introduce a novel implementation of the KC model for spherical domains. Using both models, specific energy distributions were calculated across a range of domain sizes and geometries. These distributions were input into the modified microdosimetric kinetic model (mMKM) to calculate RBE for the HSG cell line and compared against published in vitro data. The results show that both microdosimetric function and domain geometry significantly affect microdosimetric spectra and the resulting RBE, with deviations exceeding 10% when fixed mMKM parameters are used. Parameter optimization within the mMKM enables alignment across models. Our findings emphasize that microdosimetric function and domain geometry selection must be explicitly accounted for in microdosimetry-based RBE modeling, and that model parameters must be tuned accordingly to ensure consistent and biologically accurate predictions.
