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Session: Therapy General ePoster Viewing [Return to Session]

Variance in DVHs Based On Machine Repeatability

C Kabat*, H Parenica, N Papanikolaou, S Stathakis, UT Health San Antonio MD Anderson Cancer Center, San Antonio, Texas


PO-GePV-T-383 (Sunday, 7/25/2021)   [Eastern Time (GMT-4)]

Purpose: Dose volume histogram (DVH) data presented during the treatment planning process generates discrete values for structures. Patient movement, daily alignment variation, and deviations in machine delivery parameters generate uncertainty in the expected dose distribution within the patient. Quantifying how these variables impact plan delivery can help to produce more realistic DVHs. In this study, we assess the differences in DVHs generated from multiple patient deliveries.

Methods: Log files produced from three Elekta Versa HD linacs were collected from ten unique head and neck patients. Each patient underwent at least 30 fractions. Each log file was used to generate a new radiation plan (RP) file that mirrored dose rates, gantry and collimator angles, and MLC locations. New RP files were used in conjunction with the original patient CT and structures to recalculate dose distributions and DVHs for each fraction of a patient’s delivery using the Monaco treatment planning system. Dose distributions were exported and interpreted using the original structures in MATLAB.

Results: Normal tissue volumes were found to have an average DVH variation of 25 cGy, and target volumes had 60.5 cGy. Deviations occurred most often for structures receiving higher doses to a lower normalized volume. There was no correlation between total structure volume and DVH variance. No specific region (i.e. PTV or OAR) demonstrated significant deviation due to machine delivery from the planned dose.

Conclusion: DVHs generated from treatment delivery log files on the Elekta Versa HD linear accelerator maintain tight tolerances for delivery reproducibility. All deviations were within 1% of their expected value. The DVHs generated in this study provide valuable insight into how delivered dose correlates to a planned dose based on machine reproducibility. We plan to incorporate daily CBCTs for dose calculation to study how alignment variability and machine delivery impact treatment quality.



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