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Implementation of cross-institutional automated planning for esophageal cancer in the absence of commercial license(PDF)

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

Issue:
2022年第7期
Page:
793-798
Research Field:
医学放射物理
Publishing date:

Info

Title:
Implementation of cross-institutional automated planning for esophageal cancer in the absence of commercial license
Author(s):
CHEN Yan1 LIU Hongjia2 WANG Haiyang2HUANG Yuliang2 WANG Jiaqi2 TIAN Hongbo2 WU Hao2 CHEN Chen3 LI Quanfu4 ZHANG Yibao2
1. Department of Radiotherapy, the Third Hospital of Mianyang/Sichuan Mental Health Center, Mianyang 621000, China 2. Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Beijing 100142, China 3. School of Electronics, Peking University, Beijing 100871, China 4. Department of Oncology, Ordos Central Hospital, Ordos 017000, China
Keywords:
Keywords: esophageal cancer Rapidplan multicenter automated planning remote diagnosis and treatment
PACS:
R811.1
DOI:
DOI:10.3969/j.issn.1005-202X.2022.07.001
Abstract:
Abstract: Objective RapidPlan improves efficiency, quality and consistency of treatment planning. However, its application in local hospitals is limited by resources such as version and commercial license of Eclipse system. Taking esophageal cancer as an example, the feasibility and dosimetric performance of cross-intuitional automated planning using RapidPlan based on different treatment techniques are investigated in cases of no commercial license and planning system of lower version, aiming to benefit more patients without extra cost for hospitals. Methods (1) Twenty-six clinical IMRT plans for esophageal cancer of various sections were selected from the Third Hospital of Mianyang (Plan A). These plans were created using Eclipse V10.0 system without RapidPlan commercial license and no support for photon optimization algorithm. All plans were optimized using 6 MV photon, Millennium 120 MLC, dose volume optimizer and anisotropic analytical algorithm. (2) The aforementioned cases were transferred to Peking University Cancer Hospital where RapidPlan model was used to re-optimize these plans without changing the beam, energy and MLC settings. Photon optimization and photon dose calculation algorithms were used for the re-optimization. The automated plans obtained in the normal optimization environment of RapidPlan were taken as the reference (Plan C). (3) As an attempt to apply RapidPlan remotely in the absence of commercial license, the optimization parameters (without including optimization results) predicted by RapidPlan model were transferred to the treatment planning system in the Third Hospital of Mianyang. The plans were reoptimized using dose volume optimizer and anisotropic analytical algorithm of Eclipse system of lower version, without human intervention (Plan B). (4) Dosimetric parameters were compared among plans A, B and C. Results The cross-institutional automated treatment planning in the absence of commercial license was technically feasible. All plans were clinically acceptable, but automated plan performed better in terms of efficiency and consistency. Conclusion Without commercial license, RapidPlan can be applied remotely using treatment planning system of lower version and different treatment techniques, which enhances clinical efficiency of local hospitals, and reduces the inter-regional variabilities of medical service.

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Last Update: 2022-07-15