Program Information
Importance of HU-Mass Density Calibration Technique in Proton Pencil Beam Dose Calculation
S Penfold*, A Miller , University of Adelaide, Adelaide, SA
Presentations
SU-E-T-470 (Sunday, July 12, 2015) 3:00 PM - 6:00 PM Room: Exhibit Hall
Purpose: Stoichiometric calibration of Hounsfield Units (HUs) for conversion to proton relative stopping powers (RStPs) is vital for accurate dose calculation in proton therapy. However proton dose distributions are not only dependent on RStP, but also on relative scattering power (RScP) of patient tissues. RScP is approximated from material density but a stoichiometric calibration of HU-density tables is commonly neglected. The purpose of this work was to quantify the difference in calculated dose of a commercial TPS when using HU-density tables based on tissue substitute materials and stoichiometric calibrated ICRU tissues.
Methods: Two HU-density calibration tables were generated based on scans of the CIRS electron density phantom. The first table was based directly on measured HU and manufacturer quoted density of tissue substitute materials. The second was based on the same CT scan of the CIRS phantom followed by a stoichiometric calibration of ICRU44 tissue materials. The research version of Pinnacle³ proton therapy was used to compute dose in a patient CT data set utilizing both HU-density tables.
Results: The two HU-density tables showed significant differences for bone tissues; the difference increasing with increasing HU. Differences in density calibration table translated to a difference in calculated RScP of -2.5% for ICRU skeletal muscle and 9.2% for ICRU femur. Dose-volume histogram analysis of a parallel opposed proton therapy prostate plan showed that the difference in calculated dose was negligible when using the two different HU-density calibration tables.
Conclusion: The impact of HU-density calibration technique on proton therapy dose calculation was assessed. While differences were found in the calculated RScP of bony tissues, the difference in dose distribution for realistic treatment scenarios was found to be insignificant.
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