MODELING OF TIME-DOSE RESPONSE OF HUMAN TUMORS AND NORMAL TISSUES

在临床放射治疗中， 参数：总时间、分次次数、每次分次剂量， 分数的时间间隔，仍然主要基于 体验. 本项目开发了一种形式主义来描述 随着时间的推移， 正常组织功能的（间接）反应术语 与干细胞对辐射损伤的反应有关 或过渡细胞。 通常有一个稳定的状态， 功能细胞的正常磨损的替代。 这 平衡状态被辐射致命伤害所破坏， 敏感的干细胞和过渡细胞。 充分或可容忍 功能的恢复取决于 干细胞群体，损伤随时间的分布，以及 组织动力学特征。 类似的考虑适用 到肿瘤。 本模型使用线性二次型 或者说是弱势群体即时生存的双成分模型 正常组织或克隆性肿瘤细胞。 它需要选择 组织特征，例如整体正常组织的周转率 时间，急性干细胞倍增时间，亚致死损伤恢复 时间和公差水平功能，以便计算机- 生成与实际临床一致的时间-剂量反应曲线 反应模式，观察与传统的方案。 为 肿瘤，需要类似的选择，以及一个标准， 治愈率 成功的选择，然后测试与已知的 替代方案。 最终目的是开发可靠的 临床放射治疗的预测规则。

In clinical radiotherapy, the choice of the fractionation parameters: total time, number of fractions, dose per fraction, time-spacing of the fractions, is still largely based on experience. The present project develops a formalism to describe the normal tissue reactions to irradiation regimens over time in terms of the (indirect) reactions of the functions of normal tissue in relation to the reaction to radiation damage to the stem cells or transition cells. Normally there is a steady state of regular replacement of the normal attrition of functioning cells. This equilibrium condition is upset by radiation lethal damage to sensitive stem cells and transition cells. Full or tolerable recovery of functionality depends on the level of damage to the stem cell population, the distribution of damage over time, and on the tissue kinetic characteristics. Similar considerations apply to the tumor. The present model uses either the Linear-Quadratic or the Two-Component model for the immediate survival of vulnerable normal tissue or clonogenic tumor cells. It requires selection of tissue characteristics such as overall normal tissue turn-over time, acute stem cell doubling time, sublethal damage recovery time, and tolerance level functionality, in order to computer- generate time-dose response curves consistent with actual clinical response patterns, observed with conventional regimens. For tumors, similar selections are needed, as well as a criterion for cure rate. Successful selections are then tested with known alternative schemes. The ultimate aim is to develop reliable predictive rules for clinical radiation therapy.