title: Application programming in C# environment with recorded user software interactions and its application in autopilot of VMAT/IMRT treatment planning.
abstract: An autopilot scheme of volumetric-modulated arc therapy (VMAT)/intensity-modulated radiation therapy (IMRT) planning with the guidance of prior knowl-edge is established with recorded interactions between a planner and a commercial treatment planning system (TPS). Microsoft (MS) Visual Studio Coded UI is applied to record some common planner-TPS interactions as subroutines. The TPS used in this study is a Windows-based Eclipse system. The interactions of our application program with Eclipse TPS are realized through a series of subrou-tines obtained by prerecording the mouse clicks or keyboard strokes of a planner in operating the TPS. A strategy to autopilot Eclipse VMAT/IMRT plan selection process is developed as a specific example of the proposed "scripting" method. The autopiloted planning is navigated by a decision function constructed with a reference plan that has the same prescription and similar anatomy with the case at hand. The calculation proceeds by alternating between the Eclipse optimization and the outer-loop optimization independent of the Eclipse. In the C# program, the dosimetric characteristics of a reference treatment plan are used to assess and modify the Eclipse planning parameters and to guide the search for a clinically sensible treatment plan. The approach is applied to plan a head and neck (HN) VMAT case and a prostate IMRT case. Our study demonstrated the feasibility of application programming method in C# environment with recorded interactions of planner-TPS. The process mimics a planner's planning process and automatically provides clinically sensible treatment plans that would otherwise require a large amount of manual trial and error of a planner. The proposed technique enables us to harness a commercial TPS by application programming via the use of recorded human computer interactions and provides an effective tool to greatly facilitate the treatment planning process.
authors.affiliation: School of Medicine, Stanford University. hwang41@stanford.edu.
authors.forename: Henry
authors.initials: H
authors.lastname: Wang
authors.forename: Lei
authors.initials: L
authors.lastname: Xing
mesh_terms: D001331:Automation; D006258:Head and Neck Neoplasms / Q000532:radiotherapy*; D006801:Humans; D008297:Male; D058958:Organs at Risk / Q000528:radiation effects; D010347:Patient Care Planning; D011471:Prostatic Neoplasms / Q000532:radiotherapy*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*; D012984:Software