A Monte Carlo study of the impact of phosphor optical properties on EPID imaging performance. (20th August 2018)

• Record Type: Journal Article
• Authors: Shi, Mengying; Myronakis, Marios; Hu, Yue-Houng; Morf, Daniel; Rottmann, Joerg; Berbeco, Ross
• Is Part Of: Physics in medicine & biology. Volume 63:Number 16(2018:Aug.)
• Publication Date: 2018-08-20
• Subjects: electronic portal imaging device (EPID) -- Monte Carlo simulation -- noise-power spectrum (NPS) -- modulation transfer function (MTF) -- optical properties; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/1361-6560/aad647
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: We have developed a Monte Carlo computational model of a clinically employed electronic portal imaging device (EPID), and demonstrated the impact of phosphor optical properties on the imaging performance. The EPID model was built with Geant4 application for tomographic emission. Both radiative and optical transport were included in the model. Modulation transfer function (MTF), normalized noise-power spectrum times the incident x-ray fluence (qNNPS), and detective quantum efficiency (DQE) were calculated for simulated and measured data, and their agreement was quantified by the normalized root-mean-square error (NRMSE). MTF was computed using a 100 µ m wide slit tilted by 1.5° and qNNPS was estimated using the Fujita–Lubberts–Swank method. DQE was calculated from MTF and qNNPS data. The NRMSE value was 0.0467 for MTF, 0.0217 for qNNPS, and 0.0885 for DQE, showing good agreement between measurement and simulation. Five major optical properties, phosphor grain size, phosphor thickness, phosphor refractive index, binder refractive index, and packing ratio were tested for their influence on the qNNPS, MTF, and DQE(0) of the model. Generally, the effect on the qNNPS is greater than MTF, and no impact on DQE(0), except from phosphor thickness, was observed. Multiple applications, such as imager design optimization and investigations of the dosimetric performance, are expected to benefit from the validated model.