Monte Carlo aided design of an improved well-type ionization chamber for low energy brachytherapy sources.
The determination of the air kerma strength of a brachytherapy seed is necessary for effective treatment planning. Well-type ionization chambers are used on site at therapy clinics to determine the air kerma strength of seeds. In this work, an improved well-type ionization chamber for low energy, low dose rate brachytherapy sources is designed using Monte Carlo transport calculations to aid in the design process. The design improvements are the elimination of the air density induced over-response effect seen in other air-communicating chambers for low energy photon sources, and a larger signal strength (response or current) for 103Pd and 125I based seeds. A prototype well chamber based on the Monte Carlo aided design but using graphite coated acrylic walls rather than the design basis air equivalent plastic (C-552) walls was constructed and experimentally evaluated. The prototype chamber produced an 85% stronger signal when measuring a commonly used 103Pd seed and a 26% stronger signal when measuring a commonly used 125I seed when compared to another commonly used well chamber. The normalized PTP corrected chamber response is, at most, 1.3% and 2.4% over unity for air densities/pressures corresponding to an elevation of 3048 m (10000 feet) above sea level for the commonly used 103Pd and 125I based seeds respectively. Comparing calculated and measured chamber responses for common 103Pd and 125I based brachytherapy seeds show agreement within 0.6% and 0.2%, respectively. We conclude that Monte Carlo transport calculations accurately model the response of this new well chamber and in general can be used to predict the response of well chambers. The prototype chamber built in this work responds as predicted by the Monte Carlo calculations.
Bohm
Tim D
TD
Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA. tdbohm@wisc.edu
Micka
John A
JA
DeWerd
Larry A
LA
D001918:Brachytherapy / Q000295:instrumentation* / Q000379:methods; D003198:Computer Simulation; D017076:Computer-Aided Design; D004867:Equipment Design; D019544:Equipment Failure Analysis / Q000379:methods; D015233:Models, Statistical; D009010:Monte Carlo Method; D011874:Radiometry / Q000295:instrumentation* / Q000379:methods; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity