Abstract

Purpose: Linac quality assurance (QA) can be time consuming involving set up, execution, analysis and subject to user variability. The purpose of this study is to develop qualitative automation tools for mechanical and imaging QA to improve efficiency, consistency, and accuracy. Methods and Materials: Traditionally QA has been performed with graph paper, film, and multiple phantoms. Analysis consists of ruler and vendor provided software. We have developed a single four-phantom method for QA procedures including light-radiation coincidence, imaging quality, table motion and Isocentricity and separately cone beam computed tomography. XML scripts were developed to execute a series of tasks using Varian’s Truebeam Developer Mode. Non-phantom QA procedures have also been developed including field size, dose rate, MLC position, MLC and gantry speed, star shot, Winston-Lutz and Half Beam Block. All analysis is performed using inhouse MATLAB codes. Results: Overall time savings were 2.2 hours per Linac per month. Consistency improvements (standard deviation, STD) were observed for some tests. For example: field size improved from 0.11 mm to 0.04 mm and table motion improved from 0.17 mm to 0.12 mm. CBCT STD improved from 0.99 mm to 0.61 mm for slice thickness. No STD change was observed for Isocentricity test. We noticed an increase in STD from 0.33 mm to 0.41 mm for light-radiation coincidence test. There was a small drop in field size accuracy. Isocentricity showed an increase in measurement accuracy from 0.47 mm to 0.15 mm. Table motion increased in accuracy from 0.20 mm to 0.16 mm. Conclusion: Automation is a viable, accurate and efficient option for monthly and annual QA.

Highlights

  • Specific recommendations have been given in those reports, it is the responsibility of the qualified medical physicist to develop a quality assurance (QA) program that is accurate, sensitive, efficient and meets the needs of the treatment techniques used at the facility

  • The purpose of this study is to develop quantitative automation QA tools by using electronic portal imaging device (EPID), onboard imaging (OBI), Varian Developer Mode and XML-scripting for Varian TrueBeam Linac (Varian Medical System, Palo Alto, CA), and discuss the potential benefit of the new QA tools in terms of efficiency, consistency, and accuracy

  • LR coincidence Figure 3 shows an example of LR coincidence result extracted from the acquired images using in-house MatLab code where profiles are drawn across the image

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Summary

Introduction

The International Commission on Radiation Units and Measurements (ICRU) recommends that the delivered dose be within 5% of the prescribed dose [1]. Several quality assurance (QA) protocols for the linear accelerator have been established in the last couple of decades to achieve this goal [2] [3] [4]. Specific recommendations have been given in those reports, it is the responsibility of the qualified medical physicist to develop a QA program that is accurate, sensitive, efficient and meets the needs of the treatment techniques used at the facility

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