Monte Carlo-based adaptive EPID dose kernel accounting for different field size responses of imagers.
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 x 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 gamma < 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.
Wang
Song
S
Department of Radiation Oncology, Medical College of Virginia Hospitals, Virginia Commonwealth University, Richmond, Virginia 23298, USA. swang@mcvh-vcu.edu
Gardner
Joseph K
JK
Gordon
John J
JJ
Li
Weidong
W
Clews
Luke
L
Greer
Peter B
PB
Siebers
Jeffrey V
JV
D000465:Algorithms; D055615:Electrical Equipment and Supplies; D006258:Head and Neck Neoplasms / Q000532:radiotherapy; D006801:Humans; D009010:Monte Carlo Method; D011829:Radiation Dosage; D011874:Radiometry / Q000295:instrumentation* / Q000379:methods; D012542:Scattering, Radiation; D012825:Silicon
D012825:Silicon