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需要进行放射治疗。 现代调强放射治疗（IMRT）使用多个非均匀射束来定制在30-60个每日疗程（称为分次）中递送的剂量分布。 分级利用肿瘤和正常组织对每次剂量的敏感性的相对差异。这项研究扩展了调强放射治疗计划方法，优化只有在整个治疗过程中累积的剂量的限制，也包括所需的限制剂量每部分。挑战是以计算效率高的方式完成这一任务，因为整个周期的规划已经对现代优化工具造成了负担。 该策略是将治疗分为一系列相同部分的时期。 方法将计算所有的计划假设静态条件或逐步通过一个滚动的地平线，可以结合不断变化的情况和光束角度sets. Every 1%的肿瘤剂量上升可以提高局部控制约1.5%，潜在的提供有意义的收益数以千计的患者，如果器官耐受极限可以满足。一个障碍是同时满足总剂量和每部分剂量的规则。 如果计划仅针对累积剂量进行优化，然后平均分为每日疗程，则可能出现肿瘤中的大量剂量不足或违反分数大小限制。 需要时变解决方案来满足分级限制并响应治疗过程中的变化条件。 时变优化的成功为记录整个治疗过程中组织几何形状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.