Using beam quality Q to model relative biological effectiveness
Beam quality Q, defined as the ratio between the ion charge squared and the ion energy, is an alternative to the conventionally used linear energy transfer (LET) to model the relative biological effectiveness (RBE) of ions.
The Q concept is ion-independent, i.e. different ions with similar Q have similar RBE values. Therefore, it could help to transfer clinical RBE knowledge from better-studied ion types, like Carbon, to other ions. However, the validity of the Q concept has so far only been demonstrated for low LET values.
Comparison between the predicted RBE2Gy (Q, αx/βx) and experimentally derived RBE2Gy values for the test dataset. The ion type is color coded. The reference red line demonstrates y=x, i.e. the ideal case that the prediction equals the corresponding experiment. © The authors
Former OMA Fellow Liheng Tian and Armin Lühr from TU Dortmund University have explored the Q concept in a broad LET range, including the so-called overkilling region.
The researchers used the particle irradiation data ensemble (PIDE) as experimental in vitro dataset. Data-driven models, i.e. neural network (NN) models with low complexity, were built to predict RBE values for H, He, C and Ne ions at different in vitro endpoints taking different combinations of clinically available candidate inputs: LET, Q and linear-quadratic photon parameter αx/βx.
Tian and his colleague compared the models in terms of prediction power and ion dependence. The optimal model was compared to published model data using the local effect model (LEM IV).
They found that the NN models performed best for the prediction of RBE at reference photon doses between 2 and 4 Gy, or RBE near 10% cell survival, using only αx/βx and Q instead of LET as input. The Q model was not significantly ion dependent (p>0.5) and its prediction power was comparable to that of LEM IV.
In conclusion, Liheng Tian and his collaborator demonstrated the validity of the Q concept in a clinically relevant LET range including overkilling. They proposed a data-driven Q model and observed that it has an RBE prediction power comparable to a mechanistic model regardless of particle type.
The Q concept provides the possibility of reducing RBE uncertainty in treatment planning for protons and ions in the future by transferring clinical RBE knowledge between ions.
The work was published in Physics in Medicine & Biology.
Liheng Tian and Armin Lühr, “Data-driven ion-independent relative biological effectiveness modelling using the beam quality Q”, Physics in Medicine & Biology 68, 105009 (2023).
https://doi.org/10.1088/1361-6560/acc9f9