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High-Energy Photon Standard Dosimetry Data: A Quality Assurance Tool


J Lowenstein

J Lowenstein*, S Kry, A Molineu, P Alvarez, J Aguirre, P Summers, D Followill, UT MD Anderson Cancer Center, Houston, TX

SU-E-T-223 Sunday 3:00:00 PM - 6:00:00 PM Room: Exhibit Hall

Purpose: Describe the Radiological Physics Center's (RPC) extensive standard dosimetry data set determined from on-site audits measurements.

Method and Materials: Measurements were made during on-site audits to institutions participating in NCI funded cooperative clinical trials for 44 years using a 0.6cc cylindrical ionization chamber placed within the RPC's water tank. Measurements were made on Varian, Siemens, and Elekta/Philips accelerators for 11 different energies from 68 models of accelerators. We have measured percent depth dose, output factors, and off-axis factors for 123 different accelerator model/energy combinations for which we have 5 or more sets of measurements. The RPC analyzed these data and determined the 'standard data' for each model/energy combination. The RPC defines 'standard data' as the mean value of 5 or more sets of dosimetry data or agreement with published depth dose data (within 2%).

Results: The analysis of these standard data indicates that for modern accelerator models, the dosimetry data for a particular model/energy are within ï±2%. The RPC has always found accelerators of the same make/model/energy combination have the same dosimetric properties in terms of depth dose, field size dependence and off-axis factors. Because of this consistency, the RPC can assign standard data for percent depth dose, average output factors and off-axis factors for a given combination of energy and accelerator make and model.

Conclusions: The RPC standard data can be used as a redundant quality assurance tool to assist Medical Physicists to have confidence in their clinical data to within 2%. The next step is for the RPC to provide a way for institutions to submit data to the RPC to determine if their data agrees with the standard data as a redundant check.

This work was supported by PHS grants CA10953 awarded by NCI, DHHS.


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