Uniform-Structure-Based Parallel Hybrid Optimization Strategy in Radiotherapy Planning

为了满足适形调强放疗对治疗计划逆向优化计算的需要,针对靶区定义的复杂情况构造了新的目标函数.以模拟退火算法和遗传算法优势组合为例,研究了逆向放射治疗计划并行混合优化策略,给出了基于统-结构的并行广义邻域搜索混合优化算法,并在多CPU,多核计算机上实现了这-算法.描述了用该并行混合优化算法计算的数字体模和5个临床病例的例子,获得了满意的结果.结果表明,这种优化算法有效、实用,为开发新型并行混合优化算法建立了平台,为把商业化的三维适形放疗计划系统进-步发展为生物导向的放疗计划打下了基础.In order to meet the requirement for conformal intensity modulation inverse radiotherapy planning optimization processing, a new objective function is structured to target at the well defined objective area. This paper studies the parallel hybrid optimization strategy for inverse radiotherapy planning with the example of predominance combination of hybrid optimization strategy of simulation annealing and genetic algorithms, which formed a parallel general neighborhood searching hybrid optimization algorithm based on the uniform structure, and realizes the algorithm in a computer with multiple CPUs and multiple nuclei. It describes the dose distributions got with the algorithm for a virtual phantom and 5 clinical cases with the satisfying results. The results proves that this algorithm is effective and practical, which is a good platform for further research in parallel hybrid algorithm and the base for further development of the treatment planning system using biology guided radiotherapy technologies. ? by Institute of Software, the Chinese Academy of Sciences. All rights reserved.国家自然科学基金; 国家重点基础研究发展规划(973计划); 科技部仪器升级改造项目; 北京市自然科学基金; 北京市共建项目EI中文核心期刊要目总览(PKU)中国科技核心期刊(ISTIC)中国科学引文数据库(CSCD)051116-11222