Johansen Safora, Danielsen Turi, Olsen Dag Rune
Department of Medical Physics, Rikshospitalet-Radiumhospitalet Medical Centre, Oslo, Norway.
Acta Oncol. 2008;47(3):391-6. doi: 10.1080/02841860701846152.
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.
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.
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).
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.
促进关于剂量异质性对用与原发性乳腺照射相关的线性和非线性模型预测的对侧继发性乳腺癌(CB)风险影响的讨论。
使用折叠圆锥算法为8名患者计算的CB剂量体积统计数据用于预测CB中癌症诱发的超额相对风险(ERR)。采用了线性和非线性模型。本研究还包括一项敏感性分析,展示不同参数值对8名患者计算出的ERR的影响。
建立了比例假设,以使线性和非线性模型的计算具有可比性。线性模型预测的继发性癌症ERR在患者之间差异很大,而使用非线性模型对相同患者预测的ERR变化非常小。对于小剂量,即低于约3 Gy时,两种模型预测的ERR难以区分。敏感性分析表明,对于较低剂量水平,辐射诱导的癌前细胞项的二次分量可忽略不计。ERR对α(1)和α(2)的值高度敏感。
乳腺癌放射治疗的优化,其中也考虑到对侧乳腺中辐射诱发继发性恶性肿瘤的风险,需要可靠且有效的风险评估。线性剂量-风险模型没有考虑辐射暴露后继发性恶性肿瘤发生机制的复杂性;在估计与高度异质剂量分布相关的风险时,这一点尤为重要,就像接受乳腺癌照射的女性对侧乳腺的情况一样。