Program Information
An Efficient Method of 3D Patient Dose Reconstruction Based On EPID Measurements for Pre-Treatment Patient Specific QA
R David1,2*, B Zwan1 , J Hindmarsh1 , E Seymour1 , K Kandasamy1 , G Arthur1 , C Lee1,2 , P Greer2,3 , (1) Central Coast Cancer Centre, Gosford, NSW, (2) Calvary Mater Newcastle, Newcastle,(3) University of Newcastle, Newcastle, NSW.
Presentations
MO-FG-CAMPUS-TeP1-1 (Monday, August 1, 2016) 4:30 PM - 5:00 PM Room: ePoster Theater
Purpose:
To demonstrate an efficient and clinically relevant patient specific QA method by reconstructing 3D patient dose from 2D EPID images for IMRT plans. Also to determine the usefulness of 2D QA metrics when assessing 3D patient dose deviations.
Methods:
Using the method developed by King et al (Med Phys 39(5),2839-2847), EPID images of IMRT fields were acquired in air and converted to dose at 10 cm depth (SAD setup) in a flat virtual water phantom. Each EPID measured dose map was then divided by the corresponding treatment planning system (TPS) dose map calculated with an identical setup, to derive a 2D “error matrix”. For each field, the error matrix was used to adjust the doses along the respective ray lines in the original patient 3D dose. All field doses were combined to derive a reconstructed 3D patient dose for quantitative analysis. A software tool was developed to efficiently implement the entire process and was tested with a variety of IMRT plans for 2D (virtual flat phantom) and 3D (in-patient) QA analysis.
Results:
The method was tested on 60 IMRT plans. The mean (± standard deviation) 2D gamma (2%,2mm) pass rate (2D-GPR) was 97.4±3.0% and the mean 2D gamma index (2D-GI) was 0.35±0.06. The 3D PTV mean dose deviation was 1.8±0.8%. The analysis showed very weak correlations between both the 2D-GPR and 2D-GI when compared with PTV mean dose deviations (R2=0.3561 and 0.3632 respectively).
Conclusion:
Our method efficiently calculates 3D patient dose from 2D EPID images, utilising all of the advantages of an EPID-based dosimetry system. In this study, the 2D QA metrics did not predict the 3D patient dose deviation. This tool allows reporting of the 3D volumetric dose parameters thus providing more clinically relevant patient specific QA.
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