中华放射医学与防护杂志

杨晓喻,赵于前,杨振,李书舟,邵其刚,曹瑛.基于元启发策略的肿瘤调强放疗自动计划方法[J].中华放射医学与防护杂志,2023,43(1):15-22

基于元启发策略的肿瘤调强放疗自动计划方法

A metaheuristics-based automatic planning method for intensity-modulated radiation therapy

投稿时间：2022-10-12

DOI：10.3760/cma.j.cn112271-20221012-00406

英文关键词:Radiation therapy Automatic planning Optimization

基金项目:国家自然科学基金(12005306,62076256,61906215);湖南省自然科学基金(2021JJ40960,2021JJ40966,2022JJ30976)

作者	单位	E-mail
杨晓喻	中南大学湘雅医院肿瘤科国家老年疾病临床医学研究中心, 长沙 410008
赵于前	中南大学自动化学院, 长沙 410083
杨振	中南大学湘雅医院肿瘤科国家老年疾病临床医学研究中心, 长沙 410008
李书舟	中南大学湘雅医院肿瘤科国家老年疾病临床医学研究中心, 长沙 410008
邵其刚	中南大学湘雅医院肿瘤科国家老年疾病临床医学研究中心, 长沙 410008
曹瑛	中南大学湘雅医院肿瘤科国家老年疾病临床医学研究中心, 长沙 410008	yingcao@csu.edu.cn

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中文摘要:

目的提出一种基于元启发策略的放疗自动计划方法(ATP-STAR),并验证其有效性。方法 ATP-STAR方法的主要过程为先对优化参数进行向量化编码,采用高斯卷积修正优化参数,再利用模拟退火选择备选优化参数向量集,结合射野通量优化,并行探索最优的优化参数组合,实现计划自动试错。选取20例肿瘤个体化差异较大的病例进行方法测试。邀请具备5年以上临床工作经验的物理师进行人工计划设计。人工计划和ATP-STAR计划均基于开源matRad计划系统完成,射野及处方剂量与临床治疗计划保持一致。分析不同病种ATP-STAR与人工计划的靶区和危及器官剂量学差异。结果对靶区而言,ATP-STAR计划的均匀性优于人工计划(脑瘤:z=2.28,P=0.022;肺癌:z=2.29,P=0.022;肝癌:z=2.11,P=0.035),脑瘤和肝癌ATP-STAR计划的适形性与人工计划相当,肺癌ATP-STAR计划的适形性略差于人工计划(z=2.29,P=0.022)。对脑瘤的危及器官而言,相比于人工计划,ATP-STAR计划的左眼晶状体D_mean平均受量由2.19Gy降至1.76Gy(z=2.28,P=0.022),左视神经D_mean由11.36Gy降至10.22Gy(z=2.28,P=0.022),右视神经D_max由32.92Gy降至29.97Gy(z=2.10,P=0.036),垂体D_max由39.53Gy降至35.21Gy(z=2.29,P=0.022)。对肺癌的危及器官而言,ATP-STAR计划的脊髓D_max平均受量由38Gy降至31.17Gy(z=2.12,P=0.034),双肺D_mean由8.51Gy降至8.07Gy(z=2.29,P=0.022),心脏D_mean由3.21Gy降至2.69Gy(z=2.29,P=0.022)。对肝癌的危及器官而言,ATP-STAR计划的脊髓D_max由18.19Gy降至14.76Gy(z=2.11,P=0.035),肝脏D_mean由15.61Gy降至14.45Gy(z=2.11,P=0.035),肾脏D_mean由4.76Gy降至4.04Gy(z=2.10,P=0.036)。结论 ATP-STAR方法较少依赖人工计划设计经验,易于推广,有望改善调强放疗计划质量及一致性,并节省临床人力和时间成本。

英文摘要:

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 D_mean from 2.19 Gy to 1.76 Gy (z=2.28, P=0.022), decreased left optic nerve D_mean from 11.36 Gy to 10.22 Gy (z=2.28, P=0.022), decreased right optic nerve D_max from 32.92 Gy to 29.97 Gy (z=2.10, P=0.036), and decreased pituitary D_max 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 D_max from 38.00 Gy to 31.17 Gy (z=2.12, P=0.034), decreased the bilateral lungs D_mean from 8.51 Gy to 8.07 Gy (z=2.29, P=0.022), and decreased cardiac D_mean 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 D_max from 18.19 Gy to 14.76 Gy (z=2.11, P=0.035), decreased liver D_mean from 15.61 Gy to 14.45 Gy (z=2.11, P=0.035), and decreased kidneys D_mean 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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