Timlin C, Warren D R, Rowland B, Madkhali A, Loken J, Partridge M, Jones B, Kruse J, Miller R
Particle Therapy Cancer Research Institute, University of Oxford, Oxfordshire OX1 3RH, United Kingdom and Department of Physics, University of Oxford, Oxfordshire OX1 3RH, United Kingdom.
CRUK/MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford OX3 7DQ, United Kingdom.
Med Phys. 2015 Feb;42(2):866-76. doi: 10.1118/1.4905158.
Tools for comparing relative induced second cancer risk, to inform choice of radiotherapy treatment plan, are becoming increasingly necessary as the availability of new treatment modalities expands. Uncertainties, in both radiobiological models and model parameters, limit the confidence of such calculations. The aim of this study was to develop and demonstrate a software tool to produce a malignant induction probability (MIP) calculation which incorporates patient-specific dose and allows for the varying responses of different tissue types to radiation.
The tool has been used to calculate relative MIPs for four different treatment plans targeting a subtotally resected meningioma: 3D conformal radiotherapy (3DCFRT), volumetric modulated arc therapy (VMAT), intensity-modulated x-ray therapy (IMRT), and scanned protons.
Two plausible MIP models, with considerably different dose-response relationships, were considered. A fractionated linear-quadratic induction and cell-kill model gave a mean relative cancer risk (normalized to 3DCFRT) of 113% for VMAT, 16% for protons, and 52% for IMRT. For a linear no-threshold model, these figures were 105%, 42%, and 78%, respectively. The relative MIP between plans was shown to be significantly more robust to radiobiological parameter uncertainties compared to absolute MIP. Both models resulted in the same ranking of modalities, in terms of MIP, for this clinical case.
The results demonstrate that relative MIP is a useful metric with which treatment plans can be ranked, regardless of parameter- and model-based uncertainties. With further validation, this metric could be used to discriminate between plans that are equivalent with respect to other planning priorities.
随着新治疗方式的不断涌现，用于比较相对诱导二次癌症风险以指导放射治疗计划选择的工具变得愈发必要。放射生物学模型及其参数的不确定性限制了此类计算的可信度。本研究的目的是开发并展示一种软件工具，用于生成恶性诱导概率（MIP）计算，该计算纳入患者特定剂量，并考虑不同组织类型对辐射的不同反应。
该工具已用于计算针对次全切除脑膜瘤的四种不同治疗计划的相对MIP：三维适形放疗（3DCFRT）、容积调强弧形放疗（VMAT）、调强放疗（IMRT）和扫描质子治疗。
考虑了两种具有显著不同剂量反应关系的合理MIP模型。分次线性二次诱导和细胞杀伤模型得出，VMAT的平均相对癌症风险（以3DCFRT为基准归一化）为113%，质子治疗为16%，IMRT为52%。对于线性无阈值模型，这些数字分别为105%、42%和78%。与绝对MIP相比，计划之间的相对MIP对放射生物学参数不确定性的稳健性明显更高。对于该临床病例，两种模型在MIP方面得出的治疗方式排名相同。
结果表明，相对MIP是一种有用的指标，可用于对治疗计划进行排名，而无需考虑基于参数和模型的不确定性。经过进一步验证，该指标可用于区分在其他计划优先级方面等效的计划。
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