Copenhagen, Denmark
Onsite/Online

ESTRO 2022

Session Item

Optimisation and algorithms for photon and electron treatment planning
7008
Poster (digital)
Physics
Linear approximation of variable RBE models using only LET
Dirk Wagenaar, The Netherlands
PO-1747

Abstract

Linear approximation of variable RBE models using only LET
Authors:

Dirk Wagenaar1, Johannes Langendijk1, Stefan Both1

1University Medical Center Groningen, Radiation Oncology, Groningen, The Netherlands

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Purpose or Objective

Variable relative biological effectiveness (RBE) models based on the linear-quadratic model for cell survival depend on the tissue-specific α/β value, fraction dose and the dependence on the dose-weighted average linear energy transfer (LETd). The relation between RBE-LETd is often proposed to be nonlinear, but linearity is often implied in normal tissue complication probability (NTCP) modelling and LETd optimization. In this study we aim to investigate the linearity of the RBE-LET relation using two commonly used variable RBE models.

Material and Methods

This study was conducted in  three sets of 20 consecutive head & neck, breast and brain cancer patients resulting in a total sample of 60 patients. The RBE weighted dose (DRBE) was calculated for the Wedenberg (WED) and McNamara (MCN) RBE models using an α/β value between 1 and 10 Gy. A linear fit was made for each RBE model based on the average DRBE and LETd to the target and all relevant organs-at-risk (OARs). The DRBE for clinically relevant dosimetric parameters was then calculated and compared using the WED and MCN models as well as the linear fits of the RBE models.

Results

The average DRBE parameters models plotted against the DLETd are shown in figure 1 for selected α/β values. For the average DRBE of OARs, the coefficient of determination (R2) was between 0.94 and 1.00  and between 0.87 and 0.99 for the MCN and WED models respectively, with lower R2 values occurring for low α/β values (figure 2). The R2 for an α/β of 2 Gy or higher was higher than 0.92 for both models. For clinically relevant dosimetric parameters, the mean absolute error (MAE) between the WED and MCN model decreased with increasing α/β. The MAE between the MCN model with an α/β of 2 Gy and its linear estimate was 1.57, 0.44 and 0.64 Gy for HNC, breast and brain patients, respectively. The MAE between the MCN and WED model with an α/β of 2 Gy was 0.73, 0.22 and 0.32 Gy for HNC, breast and brain patients respectively. The MAE between an RBE model and its linear fit was of a similar order of magnitude as the MAE between two RBE models.

Conclusion

Both considered RBE models are more linear for high α/β values which are typically observed for acutely responding tissues and the MCN model was more linear than the WED model. The  linear fits to estimate mean DRBE parameter generated good fits with high (>0.90) R2 values for α/β of 2 Gy and very high (>0.95) for α/β of 3 Gy or higher. Using a linear RBE-LETd relation does not clinically meaningfully contribute to the uncertainty of the DRBE when considering clinically relevant dosimetric parameters.