Purpose: To facilitate a discussion about the impact of dose heterogeneity on the risk for secondary contralateral breast (CB) cancer predicted with linear and non linear models associated with primary breast irradiation.
Methods and materials: Dose volume statistics of the CB calculated for eight patients using a collapsed cone algorithm were used to predict the excess relative risk (ERR) for cancer induction in CB. Both linear and non-linear models were employed. A sensitivity analysis demonstrating the impact of different parameter values on calculated ERR for the eight patients was also included in this study.
Results: A proportionality assumption was established to make the calculations with a linear and non-linear model comparable. ERR of secondary cancer predicted by the linear model varied considerably between the patients, while the predicted ERR for the same patients using the non-linear model showed very small variation. The predicted ERRs by the two models were indistinguishable for small doses, i.e. below approximately 3 Gy. The sensitivity analysis showed that the quadratic component of the radiation-induction pre-malignant cell term is negligible for lower dose level. The ERR is highly sensitive to the value of alpha(1) and alpha(2).
Conclusions: Optimization of breast cancer radiation therapy, where also the risk for radiation induced secondary malignancies in the contralateral breast is taken into account, requires robust and valid risk assessment. The linear dose-risk model does not account for the complexity in the mechanisms underlying the development of secondary malignancies following exposure to radiation; this is particularly important when estimating risk associated with highly heterogeneous dose distributions as is the case in the contralateral breast of women receiving breast cancer irradiation.