Effects of scattered radiation and veiling glare in dual‐energy tissue–bone imaging: A theoretical analysis

Shaw, Chorng-Gang; Plewes, Donald B.

doi:10.1118/1.595975

Cited by 11 publications

(8 citation statements)

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“…When using images which contain phantom scatter, the accuracy of material decomposition is 20% and 35% for PMMA and aluminum, respectively. The impact of scatter in basis material decomposition has been observed in previous studies 30,31 . Similar to the observations from this study, Johns and Beauregard 30 show that scatter leads to an underestimation and overestimation of acrylic and aluminum basis materials respectively.…”

Section: Discussionsupporting

confidence: 90%

Monte Carlo model of a prototype flat‐panel detector for multi‐energy applications in radiotherapy

Ozoemelam,

Myronakis,

Harris

et al. 2023

Medical Physics

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BackgroundThe incorporation of multi‐energy capabilities into radiotherapy flat‐panel detectors offers advantages including enhanced soft tissue visualization by reduction of signal from overlapping anatomy such as bone in 2D image projections; creation of virtual monoenergetic images for 3D contrast enhancement, metal artefact reduction and direct acquisition of relative electron density. A novel dual‐layer on‐board imager offering dual energy processing capabilities is being designed. As opposed to other dual‐energy implementation techniques which require separate acquisition with two different x‐ray spectra, the dual‐layer detector design enables simultaneous acquisition of high and low energy images with a single exposure. A computational framework is required to optimize the design parameters and evaluate detector performance for specific clinical applications.PurposeIn this study, we report on the development of a Monte Carlo (MC) model of the imager including model validation.MethodsThe stack‐up of the dual‐layer imager (DLI) was implemented in GEANT4 Application for Tomographic Emission (GATE). The DLI model has an active area of 43×43 cm2, with top and bottom Cesium Iodide (CsI) scintillators of 600 and 800 μm thickness, respectively. Measurement of spatial resolution and imaging of dedicated multi‐material dual‐energy (DE) phantoms were used to validate the model. The modulation transfer function (MTF) of the detector was calculated for a 120 kVp x‐ray spectrum using a 0.5 mm thick tantalum edge rotated by 2.5o. For imaging validation, the DE phantom was imaged using a 140 kVp x‐ray spectrum. For both validation simulations, corresponding measurements were done using an initial prototype of the imager. Agreement between simulations and measurement was assessed using normalized root mean square error (NRMSE) and 1D profile difference for the MTF and phantom images respectively. Further comparison between measurement and simulation was made using virtual monoenergetic images (VMIs) generated from basis material images derived using precomputed look‐up tables.ResultsThe MTF of the bottom layer of the dual‐layer model shows values decreasing more quickly with spatial frequency, compared to the top layer, due to the thicker bottom scintillator thickness and scatter from the top layer. A comparison with measurement shows NRMSE of 0.013 and 0.015 as well as identical MTF50 of 0.8 mm1 and 1.0 mm1 for the top and bottom layer respectively. For the DE imaging of the DE‐phantom, although a maximum deviation of 3.3% is observed for the 10 mm aluminum and Teflon inserts at the top layer, the agreement for all other inserts is less than 2.2% of the measured value at both layers. Material decomposition of simulated scatter‐free DE images gives an average accuracy in PMMA and aluminum composition of 4.9% and 10.3% for 11–30 mm PMMA and 1–10 mm aluminum objects respectively. A comparison of decomposed values using scatter containing measured and simulated DE images shows good agreement within statistical uncertainty.ConclusionValidation using both MTF and phantom imaging shows good agreement between simulation and measurements. With the present configuration of the digital prototype, the model can generate material decomposed images and virtual monoenergetic images.

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Section: Discussionsupporting

confidence: 90%

Monte Carlo model of a prototype flat‐panel detector for multi‐energy applications in radiotherapy

Ozoemelam,

Myronakis,

Harris

et al. 2023

Medical Physics

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“…The latter is called veiling glare and is an important scatter contribution in image intensifier. [27][28][29] Investigation of the veiling glare effect in a digital flat-panel detector needs thorough knowledge of scintillation light conversion and spreading, and it is beyond the scope of this study.…”

Section: Discussionmentioning

confidence: 99%

Characterization of scatter in cone‐beam CT breast imaging: Comparison of experimental measurements and Monte Carlo simulation

et al. 2009

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It is commonly understood that scattered radiation in x-ray computed tomography (CT) degrades the reconstructed image. As a precursor to developing scatter compensation methods, it is important to characterize this scatter using both empirical measurements and Monte Carlo simulations. Previous studies characterizing scatter using both experimental measurements and Monte Carlo simulations have been reported in diagnostic radiology and conventional mammography. The emerging technology of cone-beam CT breast imaging (CTBI) differs significantly from conventional mammography in the breast shape and imaging geometry, aspects that are important factors impacting the measured scatter. This study used a bench-top cone-beam CTBI system with an indirect flat-panel detector. A cylindrical phantom with equivalent composition of 50% fibroglandular and 50% adipose tissues was used, and scatter distributions were measured by beam stop and aperture methods. The GEANT4-based simulation package GATE was used to model x-ray photon interactions in the phantom and detector. Scatter to primary ratio (SPR) measurements using both the beam stop and aperture methods were consistent within 5% after subtraction of nonbreast scatter contributions and agree with the low energy electromagnetic model simulation in GATE. The validated simulation model was used to characterize the SPR in different CTBI conditions. In addition, a realistic, digital breast phantom was simulated to determine the characteristics of various scatter components that cannot be separated in measurements. The simulation showed that the scatter distribution from multiple Compton and Rayleigh scatterings, as well as from the single Compton scattering, has predominantly low-frequency characteristics. The single Rayleigh scatter was observed to be the primary contribution to the spatially variant scatter component.

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“…The framework employed above provides a description of DE imaging performance accounting not only for quantum and electronic noise as factors for system optimization but also anatomical noise and imaging task. Other factors that warrant consideration are part of future work that incorporates scatter 26,[52][53][54][55] and noise reduction algorithms [56][57][58] in description of the DQE and NEQ. Such noise reduction algorithms include filtering of the high-energy imaging, correlated noise reduction, and noise clipping-outside the scope of the present analysis but certainly within the scope of this framework and an important consideration in assessing the full potential of DE imaging.…”

Section: Discussionmentioning

confidence: 99%

Optimization of dual‐energy imaging systems using generalized NEQ and imaging task

2006

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Dual-energy (DE) imaging is a promising advanced application of flat-panel detectors (FPDs) with a potential host of applications ranging from thoracic and cardiac imaging to interventional procedures. The performance of FPD-based DE imaging systems is investigated in this work by incorporating the noise-power spectrum associated with overlying anatomical structures ("anatomical noise" modeled according to a 1/f characteristic) into descriptions of noise-equivalent quanta (NEQ) to yield the generalized NEQ (GNEQ). Signal and noise propagation in the DE imaging chain is modeled by cascaded systems analysis. A Fourier-based description of the imaging task is integrated with the GNEQ to yield a detectability index used as an objective function for optimizing DE image reconstruction, allocation of dose between low- and high-energy images, and selection of low- and high-kVp. Optimal reconstruction and acquisition parameters were found to depend on dose; for example, optimal kVp varied from [60/150] kVp at typical radiographic dose levels (approximately 0.5 mGy entrance surface dose, ESD) but increased to [90/150] kVp at high dose (ESD approximately 5.0 mGy). At very low dose (ESD approximately 0.05 mGy), detectability index indicates an optimal low-energy technique of 60 kVp but was largely insensitive to the choice of high-kVp in the range 120-150 kVp. Similarly, optimal dose allocation, defined as the ratio of low-energy ESD and the total ESD, varied from 0.2 to 0.4 over the range ESD=(0.05-5.0) mGy. Furthermore, two applications of the theoretical framework were explored: (i) the increase in detectability for DE imaging compared to conventional radiography; and (ii) the performance of single-shot vs double-shot DE imaging, wherein the latter is found to have a DQE approximately twice that of the former. Experimental and theoretical analysis of GNEQ and task-based detectability index provides a fundamental understanding of the factors governing DE imaging performance and offers a framework for system design and optimization.

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Effects of scattered radiation and veiling glare in dual‐energy tissue–bone imaging: A theoretical analysis

Cited by 11 publications

References 0 publications

Monte Carlo model of a prototype flat‐panel detector for multi‐energy applications in radiotherapy

Monte Carlo model of a prototype flat‐panel detector for multi‐energy applications in radiotherapy

Characterization of scatter in cone‐beam CT breast imaging: Comparison of experimental measurements and Monte Carlo simulation

Optimization of dual‐energy imaging systems using generalized NEQ and imaging task

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