一种量化分析放射生物响应的新型数学模型

A Novel Mathematical Model for Quantitatively Analyzing Radiobiological Response

目的提出适合临床常规分割分次放疗应用的肿瘤体积变化简捷模型,为临床肿瘤治疗过程中治疗方案的设计调整、治疗效果的预估评价提供参考信息。方法采用综合了乏氧、DNA单链损伤、潜在致死损伤等因素的修正因子结合传统细胞存活曲线模型建立新模型,以实现对传统细胞存活曲线的完善;在Chvetsov等提出的四级细胞增殖模型中去除不便于临床获取的肿瘤乏氧率和再氧合率,使模型更加简捷、更具临床实用性;采用取自郑传城等已经发表的对肺癌和宫颈癌病人在肿瘤常规分割分次放疗中体积变化研究的9例临床数据对新模型的有效性进行验证。结果在9例临床数据中该模型能够较好地拟合6例病人的实际测量数据,相关指数R2均大于传统模型拟合的相关指数R。结论基于四级细胞增殖模型,本文提出了一个更加适合实际应用的细胞存活曲线新模型,以便更好地模拟常规分割分次放疗过程中肿瘤体积的变化。该新模型对进一步的放射生物学研究以及临床肿瘤的个性化治疗具有较好的参考价值。

Objective To develop a clinically viable mathematical model that could quantitatively predict tumor volume changes during conventional fractionated radiotherapy so as to provide treatment response assessment for prognosis, treatment planning optimization and adaptation. Methods The correction factors which considered hypoxia, DNA single strand breaks, potentially lethal damage and other factors were used to develop an improved cell survival model based on the popular linear-quadratic model of cell survival in radiation therapy. The four-level cell population model proposed by Chvetsov et al was further simplified by removing the initial hypoxic fraction and reoxygenation parameter, which were hard to obtain in routine clinics, such that an easyto-use model could be developed for clinical applications. Our new model was validated with the published clinical data of 9 lung and cervical cancer patients. Results Out of the 9 lung and cervical cases, the new model could predict the tumor volume changes in 6 of them with correlation index R2 larger than the traditional model＇s correlation index R2. Conclusion Based on a four-level cell population model, a more practical and simplified cell survival curve is proposed to model the tumor volume changes during conventional fractionated radiotherapy. The validation results with 9 cancer patients demonstrate the feasibility and the clinical usefulness of the new mathematical model in predicting tumor volume changes in conventional fractionated radiotherapy.