Supported by the National Natural Science Foundation of China under Grant Nos.10675013, 10527003, 60672104 (国家自然科学基金); the National Basic Research Program of China under Grant No.2006CB705705 (国家重点基础研究发展计划(973)); the Instrument Upgrade & Conversion Project of the Ministry of Science and Technology of China under Grant No.2006JG1000 (科技部仪器升级改造项目); the Beijing Municipal Natural Science Foundation of China under Grant No.3073019 (北京自然科学基金); the Joint Development Project of Beijing of China under Grant No.JD100010607 (北京市共建项目)
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.