Collaborative Research: Optimization of Intensity Modulated Radiation Therapy with Time Varying Delivery Plans and Fraction Constraints

超过一半的癌症病例都采用放射治疗。现代调强放疗（IMRT）使用多个非均匀光束来调整每天30-60次的剂量分布，称为分数。分离利用肿瘤和正常组织对每次剂量敏感性的相对差异。本研究扩展了仅对整个治疗过程中累积剂量限制进行优化的IMRT计划方法，也包括对每部分剂量的期望限制。挑战在于如何以一种计算效率高的方式完成这一任务，因为在整个时期内的规划已经使现代优化工具不堪重负。该策略是将治疗分为一系列相同分数的时代。方法要么是在静态条件下计算所有的计划，要么是在包含变化的环境和波束角度集的滚动视界中逐步计算时代。肿瘤剂量每增加1%，可使局部控制提高约1.5%，如果能满足器官耐受极限，可能会为数千名患者带来有意义的收益。一个障碍是同时满足总剂量和每组分剂量的规则。如果计划仅针对累积剂量进行优化，然后均匀地分成每日疗程，则可能出现肿瘤中大量剂量不足或违反分数大小限制的情况。时变的解决方案需要满足分馏约束和响应在处理过程中不断变化的条件。时变优化的成功为在整个治疗过程中记录组织几何变化的图像引导放射治疗的新兴方法打开了大门。

Radiation therapy is prescribed for over half of cancer cases. Modern intensity modulated radiotherapy (IMRT) uses multiple non-homogeneous beams to tailor the dose distribution delivered over 30-60 daily sessions called fractions. Fractionation exploits relative differences in the sensitivities of tumor and normal tissues to the dose per session. This research extends IMRT planning methods which optimize only over constraints on dose accumulated over the entire treatment, to include also desired limits on dose per fraction. The challenge is to do this in a computationally efficient way given planning over one entire period already taxes modern optimization tools. The strategy is to divide treatment into a series of epochs of identical fractions. Methods will either compute all plans assuming static conditions or step through epochs with a rolling horizon that can incorporate changing circumstances and beam angle sets.Each 1% rise in tumor dose can improve local control by about 1.5%, potentially offering meaningful gains to thousands of patients if organ tolerance limits can be satisfied. An obstacle is satisfying rules on total dose and dose per fraction simultaneously. Substantial dose shortfalls in tumor or violations of fraction size limits can appear if plans are optimized with respect only to cumulative dose and then evenly divided into daily sessions. Time varying solutions are required to meet fractionation constraints and respond to changing conditions over the treatment course. Success with time-varying optimization opens the door to emerging methods of image guided radiotherapy recording changes in tissue geometry throughout the treatment course.