Physical validation of UF-RIPSA: A rapid in-clinic peak skin dose mapping algorithm for fluoroscopically guided...

The purpose of this study was to experimentally validate UF-RIPSA, a rapid in-clinic peak skin dose mapping algorithm developed at the University of Florida using optically stimulated luminescent dosimeters (OSLDs) and tissue-equivalent phantoms.

The OSLDs used in this study were InLight^TM Nanodot dosimeters by Landauer, Inc. The OSLDs were exposed to nine different beam qualities while either free-in-air or on the surface of a tissue equivalent phantom. The irradiation of the OSLDs was then modeled using Monte Carlo techniques to derive correction factors between free-in-air exposures and more complex irradiation geometries. A grid of OSLDs on the surface of a tissue equivalent phantom was irradiated with two fluoroscopic x ray fields generated by the Siemens Artis zee bi-plane fluoroscopic unit. The location of each OSLD within the grid was noted and its dose reading compared with UF-RIPSA results.

With the use of Monte Carlo correction factors, the OSLD's response under complex irradiation geometries can be predicted from its free-in-air response. The predicted values had a percent error of -8.7% to +3.2% with a predicted value that was on average 5% below the measured value. Agreement within 9% was observed between the values of the OSLDs and RIPSA when irradiated directly on the phantom and within 14% when the beam first traverses the tabletop and pad.

The UF-RIPSA only computes dose values to areas of irradiated skin determined to be directly within the x ray field since the algorithm is based upon ray tracing of the reported reference air kerma value, with subsequent corrections for air-to-tissue dose conversion, x ray backscatter, and table/pad attenuation. The UF-RIPSA algorithm thus does not include the dose contribution of scatter radiation from adjacent fields. Despite this limitation, UF-RIPSA is shown to be fairly robust when computing skin dose to patients undergoing fluoroscopically guided interventions.