Algorithm for an automatic treatment planning system using a single‐arc VMAT for prostate cancer. Issue 12 (8th October 2021)

• Record Type: Journal Article
• Authors: Kodama, Takumi; Kudo, Shigehiro; Hatanaka, Shogo; Hariu, Masatsugu; Shimbo, Munefumi; Takahashi, Takeo
• Is Part Of: Journal of applied clinical medical physics. Volume 22:Issue 12(2021)
• Page Start: 27
• Page End: 36
• Publication Date: 2021-10-08
• Subjects: automated treatment planning -- Monaco -- optimization -- prostate -- VMAT; Medical physics -- Periodicals; Clinical medicine -- Periodicals; Health Physics; Clinical Medicine; Electronic journals; Periodicals; Periodicals; Fulltext; Internet Resources; 610.153
• DOI: 10.1002/acm2.13442
• Languages: English
• ISSNs: 1526-9914

Abstract

Abstract: Optimization process in treatment planning for intensity‐modulated radiation therapy varies with the treatment planner. Therefore, a large variation in the quality of dose distribution is usually observed. To reduce variation, an automatic optimizing toolkit was developed for the Monaco treatment planning system (Elekta AB, Stockholm, Sweden) for prostate cancer using volumetric‐modulated arc therapy (VMAT). This toolkit was able to create plans automatically. However, most plans needed two arcs per treatment to ensure the dose coverage for targets. For prostate cancer, providing a plan with a single arc was advisable in clinical practice because intrafraction motion management must be considered to irradiate accurately. The purpose of this work was to develop an automatic treatment planning system with a single arc per treatment for prostate cancer using VMAT. We designed the new algorithm for the automatic treatment planning system to use one arc per treatment for prostate cancer in Monaco. We constructed the system in two main steps: (1) Determine suitable cost function parameters for each case before optimization, and (2) repeat the calculation and optimization until the conditions for dose indices are fulfilled. To evaluate clinical suitability, the plan quality between manual planning and the automatic planning system was compared. Our system created the plans automatically in all patients within a few iterations. Statistical differences between the plans were not observed for the target and organ at risk. It created the plans with no human input other than the initial template setting and system initiation. This system offers improved efficiency in running the treatment planning system and human resources while ensuring high‐quality outputs.