(Sunday, 7/12/2020) [Eastern Time (GMT-4)]
Room: AAPM ePoster Library
Purpose:
QA guide lines for IMRT still ask for an independent MU and dose check mostly done with verification measurements. To avoid the time and labor effort, the idea of calculating a risk factor predicting the outcome of such measurements soon arose. The idea did not come to an practical approach so far and therefore the authors, who had developed an prediction algorithm themselves, asked would that work for a larger cohort of cases? This study used 250 QA plans to check predicted QA pass rates.
Methods:
As all prediction methods, the used algorithm adds up uncertainty factors based on field size/complexity/position, MU, MU rate, leaf speed/motion etc. to a field or plan based risk. Our algorithm analyses the DICOM RT file and generates an artificial field uncertainty map. Maps are projected into a 3D volume using a risk “depth” curve, where buildup region, mid and larger depths are assigned risk factors. All factors are 1.0 plus a relative uncertainty and add up in a quadratic function. From the 3-D uncertainty map the total risk factor is calculated as the ratio of all voxel involved to the voxel larger thana limit. For all 250 cases this factor was derived and compared to the originally measured Gamma pass rate (2mm/2% local) found with PTW Octavius 4D while QA plans came from Raystation (Raysearch).
Results:
The predicted pass rates did not show any correlation at all. Gamma pass rates vs risk factor, absolute numbers of voxels and field related evaluations had the same result.
Conclusion:
The calculation of risk maps or volumes is a nice tool to understand possible problems in generating a save treatment plan. The prediction of pass rates as intended might not be possible or is at least overlaid by other (unknown) factors, as our experience shows.
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Taxonomy
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