| Yang Xiaoyu,Zhao Yuqian,Yang Zhen,et al.A metaheuristics-based automatic planning method for intensity-modulated radiation therapy[J].Chinese Journal of Radiological Medicine and Protection,2023,43(1):15-22 |
| A metaheuristics-based automatic planning method for intensity-modulated radiation therapy |
| Received:October 12, 2022 |
| DOI：10.3760/cma.j.cn112271-20221012-00406 |
| KeyWords:Radiation therapy Automatic planning Optimization |
| FundProject:国家自然科学基金(12005306,62076256,61906215);湖南省自然科学基金(2021JJ40960,2021JJ40966,2022JJ30976) |
| Author Name | Affiliation | E-mail | | Yang Xiaoyu | Oncology Department and National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China | | | Zhao Yuqian | School of Automation, Central South University, Changsha 410083, China | | | Yang Zhen | Oncology Department and National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China | | | Li Shuzhou | Oncology Department and National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China | | | Shao Qigang | Oncology Department and National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China | | | Cao Ying | Oncology Department and National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China | yingcao@csu.edu.cn |
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| Abstract:: |
| Objective To establish a metaheuristics-based automatic radiotherapy treatment planning method (ATP-STAR) and verify its effectiveness.Methods The main process of the ATP-STAR method was as follows. First, the optimization parameters were vectorized for encoding and corrected using Gaussian convolution. Then, the candidate optimization parameter vector set was selected through simulated annealing. Finally, the optimal combination of optimization parameters was determined by combining the field fluence optimization to achieve automatic trial-and-error. Twenty cases with large individual differences in tumors were selected for testing. Clinical physicists with more than five years of experience were invited to perform manual planning. Both the manual and ATP-STAR plans were made utilizing the matRad open source software for radiation treatment planning, with the fields and prescribed doses consistent with those of the clinical treatment plans. The dosimetric differences of target volumes and organs at risk between the ATP-STAR and manual plans for different diseases were analyzed.Results For the target volumes, the ATP-STAR plans showed superior homogeneity compared with the manual plans (brain tumors: z=2.28, P=0.022; lung cancers: z=2.29, P=0.022; liver cancers: z=2.11, P=0.035). The conformability of the ATP-STAR plans was comparable to that of the manual plans for brain tumors and liver cancer and was slightly lower than that of the manual plans for lung cancer (z=2.29, P=0.022). The comparison result of doses to organs at risk (OARs) between the manual plans and STAR plans were as follows. For OARs of brain tumors, the ATP-STAR plans decreased the mean left lens Dmean from 2.19 Gy to 1.76 Gy (z=2.28, P=0.022), decreased left optic nerve Dmean from 11.36 Gy to 10.22 Gy (z=2.28, P=0.022), decreased right optic nerve Dmax from 32.92 Gy to 29.97 Gy (z=2.10, P=0.036), and decreased pituitary Dmax from 39.53 Gy to 35.21 Gy (z=2.29, P=0.022). For OARs of lung cancer, the ATP-STAR plans decreased the mean spinal cord Dmax from 38.00 Gy to 31.17 Gy (z=2.12, P=0.034), decreased the bilateral lungs Dmean from 8.51 Gy to 8.07 Gy (z=2.29, P=0.022), and decreased cardiac Dmean from 3.21 Gy to 2.69 Gy (z =2.29, P=0.022). For OARs of liver cancer, the ATP-STAR plans decreased spinal cord Dmax from 18.19 Gy to 14.76 Gy (z=2.11, P=0.035), decreased liver Dmean from 15.61 Gy to 14.45 Gy (z=2.11, P=0.035), and decreased kidneys Dmean from 4.76 Gy to 4.04 Gy (z=2.10, P=0.036).Conclusions The proposed ATP-STAR method relies little on the experience of manual planning and thus is easy to be widely applied. This method is expected to improve the quality and consistency of IMRT plans and save clinical labor and time costs. |
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