A new automatic planning approach:clinical practice of Eclipse scripting application programming interface combined with RapidPlan
Lou Zhaoyang1, Cheng Chen2, Lei Hongchang1, Zhu Weihua3, Wang Xiaoshen3, Wang Xingliu3, Zhu Hao3, Zhou Zongkai3, Lan Maoying3, Ge Hong1
1Department of Radiation Oncology, Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Zhengzhou 450008, China; 2Department of Strategy and Healthcare Development, Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Zhengzhou 450008, China; 3Clinical Application Training Department, Varian Medical Systems Inc., Beijing 102600, China
Abstract:Objective To propose an automatic planning approach for Eclipse15.6 planning system based on Eclipse scripting application programming interface (ESAPI) and evaluate its clinical application. Methods 20 patients with nasopharyngeal carcinoma and 20 cases of rectal cancer were selected in the clinical planning. The developed automatic planning script SmartPlan and RapidPlan were used for automatic planning and dosimetric parameters were compared with manual planning. The differences were compared between two groups by using Wilcoxon signed rank test. Results The dosimetric results of automatic and manual plans could meet clinical requirements. There was no significant difference in target coverage in nasopharyngeal carcinoma planning between two groups (P>0.05), and automatic plans were superior to manual plans in organs at risk sparing (P<0.05). Except for the homogeneity index of PTV and the maximum dose of bowel in rectal cancer plans, the other dosimetric parameters of the automatic plans were better than those of the manual plans (all P<0.05). Conclusions Compared with the manual plans, the automatic plans have the same or similar target coverage, similar or better protection of organs at risk, and more convenient implementation. The developed SmartPlan based on ESAPI has clinical feasibility and effectiveness.
Lou Zhaoyang,Cheng Chen,Lei Hongchang et al. A new automatic planning approach:clinical practice of Eclipse scripting application programming interface combined with RapidPlan[J]. Chinese Journal of Radiation Oncology, 2022, 31(1): 49-54.
[1] 陈维军,狄小云,王彬冰,等. Pinnacle 计划系统脚本在调强放疗计划中的应用研究[J]. 中国医学物理学杂志,2010, 27(3):1858-1861. DOI:10.3969/j.issn.1005-202X.2010.03.010.
CHEN WJ, DI XY, WANG BB, et al. Application of pinnacle program system script in intensive radiation program[J]. Chin J Med Phys, 2010, 27(3):1858-1861. DOI:10.3969/j.issn.1005-202X.2010.03.010.
[2] 张建英,孙菁,王芸. RayStation治疗计划系统脚本的初步应用[J]. 中国医疗器械杂志,2013, 37(4):297-300. DOI:10.3969/j.issn.1671-7104.2013.04.018.
ZHANG JY, SUN J, WANG Y. Preliminary application of the RayStation treatment plan system scripts[J]. Chin J Med Dev, 2013, 37(4):297-300. DOI:10.3969/j.issn.1671-7104.2013.04.018.
[3] WU B, RICCHETTI F, SANGUINETI G, et al. Patient geometry-driven information retrieval for IMRT treatment plan quality control[J]. Med Phys, 2009, 36(12):5497-5505. DOI:10.1118/1.3253464.
[4] CHANYAVANICH V, DAS SK, LEE WR, et al. Knowledge-based IMRT treatment planning for prostate cancer[J]. Med Phys, 2011, 38(5):2515-2522. DOI:10.1118/1.3574874.
[5] FAN J, WANG J, CHEN Z, et al. Automatic treatment planning based on three-dimensional dose distribution predicted from deep learning technique[J]. Med Phys, 2019, 46(1):370-381. DOI:10.1002/mp.13271.
[6] KRAYENBUEHL J, DI MARTINO M, GUCKENBERGER M, et al. Improved plan quality with automated radiotherapy planning for whole brain with hippocampus sparing:a comparison to the RTOG 0933 trial[J]. Radiat Oncol, 2017, 12(1):161. DOI:10.1186/s13014-017-0896-7.
[7] LI N, CARMONA R, SIRAK I, et al. Highly efficient training, refinement, and validation of a knowledge-based planning quality-control system for radiation therapy clinical trials[J]. Int J Radiat Oncol Biol Phys, 2017, 97(1):164-172. DOI:10.1016/j.ijrobp.2016.10.005.
[8] CHANG ATY, HUNG AWM, CHEUNG FWK, et al. Comparison of planning quality and efficiency between conventional and knowledge-based algorithms in nasopharyngeal cancer patients using intensity modulated radiation therapy[J]. Int J Radiat Oncol Biol Phys, 2016, 95(3):981-990. DOI:10.1016/j.ijrobp.2016.02.017.
[9] FOGLIATA A, BELOSI F, CLIVIO A, et al. On the pre-clinical validation of a commercial model-based optimisation engine:application to volumetric modulated arc therapy for patients with lung or prostate cancer[J]. Radiother Oncol, 2014, 113(3):385-391. DOI:10.1016/j.radonc.2014.11.009.
[10] TOL JP, DAHELE M, DELANEY AR, et al. Can knowledge-based DVH predictions be used for automated, individualized quality assurance of radiotherapy treatment plans?[J]. Radiat Oncol, 2015, 10(1):234. DOI:10.1186/s13014-015-0542-1.
[11] FEUVRET L, NO$\widetilde{E}$L G, MAZERON JJ, et al. Conformity index:a review[J]. Int J Radiat Oncol Biol Phys, 2006, 64(2):333-342. DOI:10.1016/j.ijrobp.2005.09.028.
[12] PADDICK I, LIPPITZ B. A simple dose gradient measurement tool to complement the conformity index[J]. J Neurosurg, 2006, 105 suppl:194-201. DOI:10.3171/sup.2006.105.7.194.
[13] KATARIA T, SHARMA K, SUBRAMANI V, et al. Homogeneity Index:An objective tool for assessment of conformal radiation treatments[J]. J Med Phys, 2012, 37(4):207-213. DOI:10.4103/0971-6203.103606.
[14] HERNANDEZ-MORALES D, SHAN J, LIU W, et al. Automation of routine elements for spot-scanning proton patient-specific quality assurance[J]. Med Phys, 2019, 46(1):5-14. DOI:10.1002/mp.13246.
[15] LIN TC, LIN CY, LI KC, et al. Automated Hypofractionated IMRT treatment planning for early-stage breast cancer[J]. Radiat Oncol, 2020, 15(1):67. DOI:10.1186/s13014-020-1468-9.
[16] HUANG Y, YUE H, WANG M, et al. Fully automated searching for the optimal VMAT jaw settings based on eclipse scripting application programming interface (ESAPI) and RapidPlan knowledge-based planning[J]. J Appl Clin Med Phys, 2018, 19(3):177-182. DOI:10.1002/acm2.12313.