http://nova.newcastle.edu.au/vital/access/services/Feed ${session.getAttribute("locale")} 5 http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:8344 The fluence exiting a patient during beam delivery can be used as treatment delivery quality assurance, either by direct comparison with expected exit fluences or by backprojection to reconstruct the patient dose. Multiple possible sources of measured exit fluence deviations exist, including changes in the beam delivery and changes in the patient anatomy. The purpose of this work is to compare the deviations caused by these sources. Machine delivery-related variability is measured by acquiring multiple dosimetric portal images (DPIs) of several test fields without a patient/phantom in the field over a time period of 2 months. Patient anatomy-related sources of fluence variability are simulated by computing transmission DPIs for a prostate patient using the same incident fluence for 11 different computed tomography (CT) images of the patient anatomy. The standard deviation (SD) and maximum deviation of the exit fluence, averaged over 5 mm x 5 mm square areas, is calculated for each test set. Machine delivery fluence SDs as large as 1% are observed for a sample patient field and as large as 2.5% for a picket-fence dMLC test field. Simulations indicate that day-to-day patient anatomy variations induce exit fluence SDs as large as 3.5%. The largest observed machine delivery deviations are 4% for the sample patient field and 7% for the picket-fence field, while the largest difference for the patient anatomy-related source is 8.5%. Since daily changes in patient anatomy can result in substantial exit fluence deviations, care should be taken when applying fluence back-projection to ensure that such deviations are properly attributed to their source. 2011-09-13T00:00:09.137Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:7816 The aim of this study is to present an efficient method to generate imager-specific Monte Carlo (MC)-based dose kernels for amorphous silicon-based electronic portal image device dose prediction and determine the effective backscattering thicknesses for such imagers. EPID field size-dependent responses were measured for five matched Varian accelerators from three institutions with 6 MV beams at the source to detector distance (SDD) of 105 cm. For two imagers, measurements were made with and without the imager mounted on the robotic supporting arm. Monoenergetic energy deposition kernels with 0–2.5 cm of water backscattering thicknesses were simultaneously computed by MC to a high precision. For each imager, the backscattering thickness required to match measured field size responses was determined. The monoenergetic kernel method was validated by comparing measured and predicted field size responses at 150 cm SDD, 10×10 cm² multileaf collimator (MLC) sliding window fields created with 5, 10, 20, and 50 mm gaps, and a head-and-neck (H&N) intensity modulated radiation therapy (IMRT) patient field. Field size responses for the five different imagers deviated by up to 1.3%. When imagers were removed from the robotic arms, response deviations were reduced to 0.2%. All imager field size responses were captured by using between 1.0 and 1.6 cm backscatter. The predicted field size responses by the imager-specific kernels matched measurements for all involved imagers with the maximal deviation of 0.34%. The maximal deviation between the predicted and measured field size responses at 150 cm SDD is 0.39%. The maximal deviation between the predicted and measured MLC sliding window fields is 0.39%. For the patient field, gamma analysis yielded that 99.0% of the pixels have γ<1 by the 2%, 2 mm criteria with a 3% dose threshold. Tunable imager-specific kernels can be generated rapidly and accurately in a single MC simulation. The resultant kernels are imager position independent and are able to predict fields with varied incident energy spectra and a H&N IMRT patient field. The proposed adaptive EPID dose kernel method provides the necessary infrastructure to build reliable and accurate portal dosimetry systems. 2011-06-02T06:00:19.996Z ]]>