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Treatment Delivery Verification Using ELEKTA Versa HD High-Resolution Log Files

H Parenica1*, C Kabat1 , N Kirby1 , K Rasmussen1 , D Saenz1 , P Mavroidis2 , N Papanikolaou1 , S Stathakis1 , (1) UT Health Science Center San Antonio, San Antonio, TX, (2) Univ North Carolina, Chapel Hill, NC


(Sunday, 7/14/2019)  

Room: ePoster Forums

Purpose: To develop a tool for verification of patient plan delivery based on high definition log files from the ELEKTA Versa HD.

Methods: A tool was created in MATLAB that allows for DICOM RP files to be generated based on the parameters of the plan delivered to the patient from the machine log files. Four patients currently undergoing treatment were selected. Each patient’s treatment plan was created in the Pinnacle Treatment Planning System (TPS), and these plans were recalculated in the Monaco TPS using a Monte Carlo algorithm to ensure plan accuracy. For each patient, a single treatment fraction was selected and the machine log files were extracted from that fraction. Using the MATLAB function, a new DICOM RP file was generated containing the machine delivery parameters specific to that treatment fraction (the log file-based plan). These plans were calculated in Monaco and the PTV dose statistics were compared between plans.

Results: The mean PTV dose for each patient’s log file-based plan showed good agreement with the Pinnacle plans and the Pinnacle plans recalculated in Monaco. All mean PTV doses agreed within +/- 2%. The minimum PTV dose (delivered to less than 0.1 cc) showed the largest discrepancies between the Pinnacle plan and the log file-based plan. Overall, the log file-based plans showed the greatest agreement with the Pinnacle plans recalculated in Monaco, likely due to the different algorithm used in Pinnacle.

Conclusion: A new tool for plan delivery verification has been created and successfully generates DICOM RP files that allows for dose calculation based on the machine parameters during a single fraction of treatment. This tool is being further refined for clinical implementation to ensure quality of patient plan delivery throughout treatment.

Funding Support, Disclosures, and Conflict of Interest: This research is supported by the Cancer Prevention and Research Institute of Texas Research Training Award (RP170345).


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