Rapid Monte Carlo simulation of detector DQE(f)

Star‐Lack, Josh; Sun, Mengtao; Meyer, Andre S.; Morf, Daniel; Constantin, Dragoş; Fahrig, Rebecca; Abel, Eric

doi:10.1118/1.4865761

Cited by 43 publications

(56 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…flood field correction, line spread function tail fitting etc.). NPS measurements are more straightforward than MTF, and the use of the autocorrelation method described in Star-Lack et al 30 enables fast qNNPS simulations. qNNPS as the first reference for validation of model parameters and optical transport is suggested in computational studies where MTF, NPS and DQE are involved.…”

Section: Discussionmentioning

confidence: 99%

“…Our results indicate that scintillation yield does not have an impact on MTF, in accordance with previous studies. 30 The MTF increase that was observed when optical photons were completely suspended can be attributed to (a) the absence of optical transport that contributes to optical spread and MTF degradation; (b) image formation procedure which relied on electron absorption position rather than integration of optical photons reaching the detector. Each time an electron deposited energy, its position was recorded and converted to a virtual detector pixel index.…”

Section: Discussionmentioning

confidence: 99%

“…Kirkby and Sloboda, 27 have used a scattering length of 17 μm but they did not specify how this value was produced; they employed the DETECT2000 optical tracking code. 39 Star-Lack et al , 30 developed a Geant4-based application. They employed three-parameter HG fitting for optical Mie scattering and isotropic emission with scattering length equal to 17 μm with a relative phosphor/binder refractive index of 1.7.…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

A novel multilayer MV imager computational model for component optimization

et al. 2017

Self Cite

View full text Add to dashboard Cite

Purpose A novel Megavoltage (MV) multi-layer imager (MLI) design featuring higher detective quantum efficiency and lower noise than current conventional MV imagers in clinical use has been recently reported. Optimization of the MLI design for multiple applications including tumor tracking, MV-CBCT and portal dosimetry requires a computational model that will provide insight into the physics processes that affect the overall and individual components’ performance. The purpose of the current work was to develop and validate a comprehensive computational model that can be used for MLI optimization. Methods The MLI model was built using the Geant4 Application for Tomographic Emission (GATE) application. The model includes x-ray and charged particle interactions as well as the optical transfer within the phosphor. A first prototype MLI device featuring a stack of four detection layers was used for model validation. Each layer of the prototype contains a copper buildup sheet, a phosphor screen and photodiode array. The model was validated against measured data of Modulation Transfer Function (MTF), Noise Power Spectrum (NPS) and Detective Quantum Efficiency (DQE). MTF was computed using a slanted slit with 2.3° angle and 0.1 mm width. NPS was obtained using the autocorrelation function technique. DQE was calculated from MTF and NPS data. The comparison metrics between simulated and measured data were the Pearson’s correlation coefficient (r) and the normalized root-mean-square error (NRMSE). Results Good agreement between measured and simulated MTF and NPS values was observed. Pearson’s correlation coefficient for the combined signal from all layers of the MLI was equal to 0.9991 for MTF and 0.9992 for NPS; NRMSE was 0.0121 for MTF and 0.0194 for NPS. Similarly, the DQE correlation coefficient for the combined signal was 0.9888 and the NRMSE was 0.0686. Conclusions A comprehensive model of the novel MLI design was developed using the GATE toolkit and validated against measured MTF, NPS and DQE data acquired with a prototype device featuring four layers. This model will be used for further optimization of the imager components and configuration for clinical radiotherapy applications.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

A novel multilayer MV imager computational model for component optimization

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…The average photon fluence for an SID of r ref = 100 cm was derived from a Monte Carlo model simulating the specific LINAC configuration ( q 0 = 1.42 × 10 − 7 mm − 2 cGy − 1 ) (Star-Lack et al (2014)). To correct for the measurement geometry an inverse square correction was applied, i.e.…”

Section: Methodsmentioning

confidence: 99%

A novel EPID design for enhanced contrast and detective quantum efficiency

et al. 2016

Self Cite

View full text Add to dashboard Cite

Purpose Beams-eye-view imaging applications such as real-time soft-tissue motion estimation are hindered by the inherently low image contrast of electronic portal imaging devices (EPID) currently available for clinical use. We introduce and characterize a novel EPID design that provides substantially increased detective quantum efficiency (DQE), contrast-to-noise ratio (CNR) and sensitivity without degradation in spatial resolution. Methods The prototype design features a stack of four conventional EPID layers combined with low noise integrated readout electronics. Each layer consists of a copper plate, a scintillator (GdO2S2: T b) and a photodiode/TFT-switch (aSi:H). We characterize the prototype’s signal response to a 6 MV photon beam in terms of modulation transfer function (MTF), DQE and contrast-to-noise ratio (CNR). The presampled MTF is estimated using a slanted slit technique, the DQE is calculated from measured normalized noise power spectra (nNPS) and the MTF and CNR is estimated using a Las Vegas contrast phantom. The prototype has been designed and built to be interchangeable with the current clinical EPID on the Varian TrueBeam platform (AS-1200) in terms of size and data output specifications. Performance evaluation is conducted in absolute values as well as in relative terms using the Varian AS-1200 EPID as a reference detector. Results A fivefold increase of DQE(0) to about 6.7% was observed by using the four-layered design versus the AS-1200 reference detector. No substantial differences are observed between each layer’s individual MTF and the one for all four layers operating combined indicating that defocusing due to beam divergence is negligible. Also, using four layers instead of one increases the signal to noise ratio (SNR) by a factor of 1.7. Conclusions A layered EPID design improves the radiation sensitivity while maintaining the spatial resolution and saturation level of a single layer conventional EPID. Experimental characterization of this first 4-layered prototype demonstrates substantially improved DQE and CNR while maintaining a high resolution. Besides overall improved image quality and dosimetric sensitivity, we anticipate that this novel detector design will enable more accurate soft-tissue motion estimations during radiation therapy procedures.

show abstract

“…Nanomaterials have gain ground as radiation detectors with potential to reduce receiving dose by the operators or patients (in case of medical imaging) due to the increased luminescence efficiency and confinement [11,12]. On the other hand, the diffusion and propagation properties of light passing through nanoparticulated phosphors layers are still under investigation with ongoing theoretical and experimental research, devoted to analysis of the physical and structural properties of those materials [13][14][15][16][17][18]. The aim of the current work is to provide a comparative investigation of the imaging performance of Lu 2 O 3 :Eu phosphors screens, prepared with different grain shape and size, and manufactured by the sedimentation method.…”

Section: Introductionmentioning

confidence: 99%