基于约束优先级列表的调强放疗自动多目标优化方法

Constraint priority list-based multi-objective optimization for intensity-modulated radiation therapy

本研究提出一种可将临床偏好量化为优先级列表,并在此基础上建立自动调整约束并生成该条件下优化解的IMRT多目标优化方法。本优化方法由计划剂量学约束自动调整机制和约束下的基于体素权重因子的自动FMO模型嵌套组成。剂量约束的自动调整需首先根据临床对各感兴趣区域剂量约束的重视程度提炼为约束优先级列表,后以列表为依据,分步对剂量约束进行调整,使各约束随迭代进行时逐步达到最佳设置状态。剂量约束每调整1次,紧随调用基于体素权重因子的FMO模型,解得满足当前约束的全局最优计划。为验证本优化方法的可行性与有效性,临床收集6例已治宫颈癌IMRT计划,使用本文方法对其重新自动生成优化的计划,并比较原始(临床)计划和优化计划的质量,含计划DVH曲线和临床关注的剂量约束指征项的具体数值,查看其计划质量提高成效。6例临床IMRT计划表明,使用本文方法生成的优化计划较原始计划可得到相当PTV覆盖率、均匀性的同时,有效减少OAR受量,提高计划质量。其中,优化计划直肠的平均V45从原始计划的(41.99±13.31)%降到(32.55±22.27)%;膀胱的平均V45从(44.37±4.08)%降到(28.99±15.25)%。计划优化过程可实现基本自动化。

In intensity-modulated radiation therapy（IMRT）, it is time-consuming to repeatedly adjust the objectives manually to obtain the best tradeoff between the prescribed dose of the planning target volume and sparing the organs-at-risk. Here we propose a new method to realize automatic multi-objective IMRT optimization, which quantifies the clinical preferences into the constraint priority list and adjusts the dose constraints based on the list to obtain the optimal solutions under the dose constraints. This method contains automatic adjustment mechanism of the dose constraint and automatic voxel weighting factor-based FMO model. Every time the dose constraint is adjusted, the voxel weighting factor-based FMO model is launched to find a global optimal solution that satisfied the current constraints. We tested the feasibility and effectiveness of this method in 6 cases of cervical cancer with IMRT by comparing the original plan and the automatic optimization plan generated by this method. The results showed that with the same PTV coverage and uniformity, the automatic optimization plan had a better a dose sparing of the organs-at-risk and a better plan quality than the original plan, and resulted in obvious reductions of the average V45 of the rectum from（41.99±13.31）% to（32.55±22.27）% and of the bladder from（44.37±4.08）% to（28.99±15.25）%.