Monte Carlo modeling of the Elekta Versa HD and patient dose calculation with EGSnrc/BEAMnrc.

INTRODUCTION: Numerous studies have proven the Monte Carlo method to be an accurate means of dose calculation. Although there are several commercial Monte Carlo treatment planning systems (TPSs), some clinics may not have access to these resources. We present a method for routine, independent patient dose calculations from treatment plans generated in a commercial TPS with our own Monte Carlo model using free, open-source software. MATERIALS AND METHODS: A model of the Elekta Versa HD linear accelerator was developed using the EGSnrc codes. A MATLAB script was created to take clinical patient plans and convert the DICOM RTP files into a format usable by EGSnrc. Ten patients' treatment plans were exported from the Monaco TPS to be recalculated using EGSnrc. Treatment simulations were done in BEAMnrc, and doses were calculated using Source 21 in DOSXYZnrc. Results were compared to patient plans calculated in the Monaco TPS and evaluated in Verisoft with a gamma criterion of 3%/2 mm. RESULTS: Our Monte Carlo model was validated within 1%/1-mm accuracy of measured percent depth doses and profiles. Gamma passing rates ranged from 82.1% to 99.8%, with 7 out of 10 plans having a gamma pass rate over 95%. Lung and prostate patients showed the best agreement with doses calculated in Monaco. All statistical uncertainties in DOSXYZnrc were less than 3.0%. CONCLUSION: A Monte Carlo model for routine patient dose calculation was successfully developed and tested. This model allows users to directly recalculate DICOM RP files containing patients' plans that have been exported from a commercial TPS.

Investigation of error detection capabilities of phantom, EPID and MLC log file based IMRT QA methods.

A patient specific quality assurance (QA) should detect errors that originate anywhere in the treatment planning process. However, the increasing complexity of treatment plans has increased the need for improvements in the accuracy of the patient specific pretreatment verification process. This has led to the utilization of higher resolution QA methods such as the electronic portal imaging device (EPID) as well as MLC log files and it is important to know the types of errors that can be detected with these methods. In this study, we will compare the ability of three QA methods (Delta4 ®, MU-EPID, Dynalog QA) to detect specific errors. Multileaf collimator (MLC) errors, gantry angle, and dose errors were introduced into five volumetric modulated arc therapy (VMAT) plans for a total of 30 plans containing errors. The original plans (without errors) were measured five times with each method to set a threshold for detectability using two standard deviations from the mean and receiver operating characteristic (ROC) derived limits. Gamma passing percentages as well as percentage error of planning target volume (PTV) were used for passing determination. When applying the standard 95% pass rate at 3%/3 mm gamma analysis errors were detected at a rate of 47, 70, and 27% for the Delta4 , MU-EPID and Dynalog QA respectively. When using thresholds set at 2 standard deviations from our base line measurements errors were detected at a rate of 60, 30, and 47% for the Delta4 , MU-EPID and Dynalog QA respectively. When using ROC derived thresholds errors were detected at a rate of 60, 27, and 47% for the Delta4 , MU-EPID and Dynalog QA respectively. When using dose to the PTV and the Dynalog method 11 of the 15 small MLC errors were detected while none were caught using gamma analysis. A combination of the EPID and Dynalog QA methods (scaling Dynalog doses using EPID images) matches the detection capabilities of the Delta4 by adding additional comparison metrics. These additional metrics are vital in relating the QA measurement to the dose received by the patient which is ultimately what is being confirmed.

Code of ethics for the American Association of Physicists in Medicine (Revised): Report of Task Group 109.

The American Association of Physicists in Medicine (AAPM) has established a comprehensive Code of Ethics for its members. The Code is a formal part of AAPM governance, maintained as Professional Policy 24, and includes both principles of ethical practice and the rules by which a complaint will be adjudicated. The structure and content of the Code have been crafted to also serve the much broader purpose of giving practical ethical guidance to AAPM members for making sound decisions in their professional lives. The Code is structured in four major parts: a Preamble, a set of ten guiding Principles, Guidelines that elucidate the application of the Principles in various practice settings, and the formal Complaint process. Guidelines have been included to address evolving social and cultural norms, such as the use of social media and the broadening scope of considerations important in an evolving workplace. The document presented here is the first major revision of the AAPM Code of Ethics since 2008. This revision was approved by the Board of Directors to become effective 1 January 2019.