Purpose: Relative biological effectiveness (RBE) uncertainties have been a concern for treatment planning in proton therapy, particularly for treatment sites that are near organs at risk (OARs). In such a clinical situation, the utilization of variable RBE models is preferred over constant RBE model of 1.1. The problem, however, lies in the exact choice of RBE model, especially when current RBE models are plagued with a host of uncertainties. This paper aims to determine the influence of RBE models on treatment planning, specifically to improve the understanding of the influence of the RBE models with regard to the passing and failing of treatment plans. This can be achieved by studying the RBE-weighted dose uncertainties across RBE models for OARs in cases where the target volume overlaps the OARs. Multi-field optimization (MFO) and single-field optimization (SFO) plans were compared in order to recommend which technique was more effective in eliminating the variations between RBE models.
Methods: Fifteen brain tumor patients were selected based on their profile where their target volume overlaps with both the brain stem and the optic chiasm. In this study, 6 RBE models were analyzed to determine the RBE-weighted dose uncertainties. Both MFO and SFO planning techniques were adopted for the treatment planning of each patient. RBE-weighted dose uncertainties in the OARs are calculated assuming of 3 Gy and 8 Gy. Statistical analysis was used to ascertain the differences in RBE-weighted dose uncertainties between MFO and SFO planning. Additionally, further investigation of the linear energy transfer (LET) distribution was conducted to determine the relationship between LET distribution and RBE-weighted dose uncertainties.
Results: The results showed no strong indication on which planning technique would be the best for achieving treatment planning constraints. MFO and SFO showed significant differences ( <.05) in the RBE-weighted dose uncertainties in the OAR. In both clinical target volume (CTV)-brain stem and CTV-chiasm overlap region, 10 of 15 patients showed a lower median RBE-weighted dose uncertainty in MFO planning compared with SFO planning. In the LET analysis, 8 patients (optic chiasm) and 13 patients (brain stem) showed a lower mean LET in MFO planning compared with SFO planning. It was also observed that lesser RBE-weighted dose uncertainties were present with MFO planning compared with SFO planning technique.
Conclusions: Calculations of the RBE-weighted dose uncertainties based on 6 RBE models and 2 different revealed that MFO planning is a better option as opposed to SFO planning for cases of overlapping brain tumor with OARs in eliminating RBE-weighted dose uncertainties. Incorporation of RBE models failed to dictate the passing or failing of a treatment plan. To eliminate RBE-weighted dose uncertainties in OARs, the MFO planning technique is recommended for brain tumor when CTV and OARs overlap.
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http://dx.doi.org/10.1016/j.adro.2021.100844 | DOI Listing |
Radiat Res
January 2025
Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota.
Variable relative biological effectiveness (RBE) of carbon radiotherapy may be calculated using several models, including the microdosimetric kinetic model (MKM), stochastic MKM (SMKM), repair-misrepair-fixation (RMF) model, and local effect model I (LEM), which have not been thoroughly compared. In this work, we compared how these four models handle carbon beam fragmentation, providing insight into where model differences arise. Monoenergetic and spread-out Bragg peak carbon beams incident on a water phantom were simulated using Monte Carlo.
View Article and Find Full Text PDFPhys Imaging Radiat Oncol
January 2025
Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, Switzerland.
Background And Purpose: In proton therapy, a relative biological effectiveness (RBE) of 1.1 is used to convert proton dose into an equivalent photon dose. However, RBE varies with tissue type, fraction dose, and beam quality parameters beyond dose such as linear energy transfer (LET) raising concerns about increased local effectiveness and potential toxicity.
View Article and Find Full Text PDFFront Genet
January 2025
Ifremer, Ressources Biologiques et Environnement (RBE)-ASIM, La Tremblade, France.
Introduction: The blue mussel is one of the major aquaculture species worldwide. In France, this species faces a significant threat from infectious disease outbreaks in both mussel farms and the natural environment over the past decade. Diseases caused by various pathogens, particularly spp.
View Article and Find Full Text PDFSci Rep
January 2025
Radiation Biophysics and Radiobiology Laboratory, Physics Department, University of Pavia, Pavia, Italy.
We present new developments for an ab-initio model of the neutron relative biological effectiveness (RBE) in inducing specific classes of DNA damage. RBE is evaluated as a function of the incident neutron energy and of the depth inside a human-sized reference spherical phantom. The adopted mechanistic approach traces neutron RBE back to its origin, i.
View Article and Find Full Text PDFMed Phys
January 2025
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, USA.
Purpose: In locations where the proton energy spectrum is broad, lineal energy spectrum-based proton biological effects models may be more accurate than dose-averaged linear energy transfer (LET) based models. However, the development of microdosimetric spectrum-based biological effects models is hampered by the extreme computational difficulty of calculating microdosimetric spectra. Given a precomputed library of lineal energy spectra for monoenergetic protons, a weighted summation can be performed which yields the lineal energy spectrum of an arbitrary polyenergetic beam.
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