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SU‐E‐T‐779: Use of the Varian Eclipse Scripting API to Collect Volumetric Modulated Arc Therapy Plan Data
Author(s) -
Janes L A,
Anderson C J R,
Matuszak M M,
Roberts D A,
Moran J M,
Younge K C
Publication year - 2015
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4925143
Subject(s) - computer science , scripting language , metric (unit) , histogram , interface (matter) , plan (archaeology) , process (computing) , artificial intelligence , programming language , operating system , operations management , archaeology , bubble , maximum bubble pressure method , economics , image (mathematics) , history
Purpose: We have introduced an automated script into the VMAT planning process to visualize and understand plan characteristics in comparison to past plans including number of arcs, arc weighting, and arc modulation. Methods: Varian's Eclipse Scripting Application Programming Interface (API) was used to create a script to compare new VMAT plans to past clinical VMAT plans, during and after the planning process. A graphical user interface was developed to display the results for straightforward analysis and interpretation. Analysis of previously treated plans from the past two years was used to design the data layout and organizational categories. In addition, a method was developed to automatically update the script as new plans are generated. Results: Plan data are represented in a histogram format, which is updateable with additional treatment plans by uploading a comma separated value file with the new patients’ information. The current script has the ability to display the number of arcs, the MU per arc and per control point, and the degree of modulation in each control point compared to all past VMAT plans. The user can filter the histogram by treatment site to easily compare the current plan to other plans of the same site, or to all sites. The histogram also contains the total number of plans being compared, the average value of the metric being examined, and the standard deviation of that metric. The script has been built with a modular framework such that additional plan metrics can be added as they are developed. Conclusions: The script interface provides easy to understand feedback on quality metrics of VMAT plans compared to other plans for the same body site. The script enables dosimetrists to ensure consistent plan quality, and assists physicists in checking plans prior to pre‐treatment quality assurance measurements. This project was supported in part by P01CA059827.