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Purpose: The modulation transfer function (MTF) and detective quantum efficiency (DQE) of x-ray detectors are key Fourier metrics of performance, valid only for linear and shift-invariant (LSI) systems and generally measured following IEC guidelines requiring the use of raw (unprocessed) image data. However, many detectors incorporate processing in the imaging chain that is difficult or impossible to disable, raising questions about the practical relevance of MTF and DQE testing. We investigate the impact of convolution-based embedded processing on MTF and DQE measurements. Approach: We use an impulse-sampled notation, consistent with a cascaded-systems analysis in spatial and spatial-frequency domains to determine the impact of discrete convolution (DC) on measured MTF and DQE following IEC guidelines. Results: We show that digital systems remain LSI if we acknowledge both image pixel values and convolution kernels represent scaled Dirac δ-functions with an implied sinc convolution of image data. This enables use of the Fourier transform (FT) to determine impact on presampling MTF and DQE measurements. Conclusions: It is concluded that: (i) the MTF of DC is always an unbounded cosine series; (ii) the slanted-edge method yields the true presampling MTF, even when using processed images, with processing appearing as an analytic filter with cosine-series MTF applied to raw presampling image data; (iii) the DQE is unaffected by discrete-convolution-based processing with a possible exception near zero-points in the presampling MTF; and (iv) the FT of the impulse-sampled notation is equivalent to the Z transform of image data.

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Computed tomography (CT) total-airway-count (TAC) and airway wall-thickness differ across chronic obstructive pulmonary disease (COPD) severities, but longitudinal insights are lacking. The aim of this study was to evaluate longitudinal CT airway measurements over three-years in ex-smokers. In this prospective convenience sample study, ex-smokers with (n = 50; 13 female; age = 70 ± 9 years; pack-years = 43 ± 26) and without (n = 40; 17 female; age = 69 ± 10 years; pack-years = 31 ± 17) COPD completed CT, 3He magnetic resonance imaging (MRI), and pulmonary function tests at baseline and three-year follow-up. CT TAC, airway wall-area (WA), lumen-area (LA), and wall-area percent (WA%) were generated. Emphysema was quantified as the relative-area-of-the-lung with attenuation < -950 Hounsfield-units (RA950). MRI ventilation-defect-percent (VDP) was also quantified. Differences over time were evaluated using paired-samples t tests. Multivariable prediction models using the backwards approach were generated. After three-years, forced-expiratory-volume in 1-second (FEV1) was not different in ex-smokers with (p = 0.4) and without (p = 0.5) COPD, whereas RA950 was (p < 0.001, p = 0.02, respectively). In ex-smokers without COPD, there was no change in TAC (p = 0.2); however, LA (p = 0.009) and WA% (p = 0.01) were significantly different. In ex-smokers with COPD, TAC (p < 0.001), WA (p = 0.04), LA (p < 0.001), and WA% (p < 0.001) were significantly different. In all ex-smokers, TAC was related to VDP (baseline: ρ = -0.30, p = 0.005; follow-up: ρ = -0.33, p = 0.002). In significant multivariable models, baseline airway wall-thickness was predictive of TAC worsening. After three-years, in the absence of FEV1 worsening, TAC diminished only in ex-smokers with COPD and airway walls were thinner in all ex-smokers. These longitudinal findings suggest that the evaluation of CT airway remodeling may be a useful clinical tool for predicting disease progression and managing COPD.Clinical trial registration: www.clinicaltrials.gov NCT02279329.

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BACKGROUND: X-ray coronary angiography is a sub-optimal vascular imaging technique because it cannot suppress un-enhanced anatomy that may obscure the visualization of coronary artery disease. PURPOSE: The purpose of this paper is to evaluate the theoretical image quality of energy-resolved x-ray angiography (ERA) implemented with spectroscopic x-ray detectors (SXDs), which may overcome limitations of x-ray coronary angiography. METHODS: We modeled the large-area signal-difference-to-noise (SDNR) of contrast-enhanced vasculature in ERA images and compared with that of digital-subtraction angiography (DSA), which served as a gold standard vascular imaging technique. To this end, we used calibrated numerical models of the response of cadmium telluride SXDs including the effects of charge sharing, electronic noise, and energy thresholding. Our models assumed zero scatter, no pulse pile up and small signals such that image contrast is approximately linear in the area density of contrast agents. For DSA, we similarly modeled x-ray detection by cesium iodide energy-integrating detectors using validated numerical models. For ERA, we investigated iodine and gadolinium (Gd) contrast agents, two-material and three-material decompositions, analog charge summing for charge sharing correction, and optimized image quality with respect to the tube voltage and energy thresholds assuming cadmium telluride SXDs with three energy bins. RESULTS: Our analysis reveals that a three-material decomposition using iodine contrast agents will require x-ray exposures that are approximately 400 times those of DSA to achieve the same SDNR as DSA in coronary applications, and is therefore not feasible in a clinical setting. However, three-material decompositions with Gd contrast agents have the potential to provide SDNR that is ∼45% of that of DSA for matched patient air kerma. For two-material decompositions that suppress soft-tissue, ERA has the potential to produce images with SDNR that is 50%-75% of that of DSA for matched patient air kermas but lower levels of tube loading. Achieving these SDNR levels will require the use of analog charge summing for charge sharing correction, which increased SDNR by up to a factor of 1.7 depending on the contrast agent and whether or not a two-material or three-material decomposition was assumed. CONCLUSIONS: We conclude that three-material ERA implemented with Gd contrast agents and two-material ERA implemented with either iodine or Gd contrast agents, should be investigated as alternatives to DSA in situations where motion artifacts preclude the use of DSA, such as in coronary imaging.

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PURPOSE: We present a new framework for theoretical analysis of the noise power spectrum (NPS) of photon-counting x-ray detectors, including simple photon-counting detectors (SPCDs) and spectroscopic x-ray detectors (SXDs), the latter of which use multiple energy thresholds to discriminate photon energies. METHODS: We show that the NPS of SPCDs and SXDs, including spatio-energetic noise correlations, is determined by the joint probability density function (PDF) of deposited photon energies, which describes the probability of recording two photons of two different energies in two different elements following a single-photon interaction. We present an analytic expression for this joint PDF and calculate the presampling and digital NPS of CdTe SPCDs and SXDs. We calibrate our charge sharing model using the energy response of a cadmium zinc telluride (CZT) spectroscopic x-ray detector and compare theoretical results with Monte Carlo simulations. RESULTS: Our analysis shows that charge sharing increases pixel signal-to-noise ratio (SNR), but degrades the zero-frequency signal-to-noise performance of SPCDs and SXDs. In all cases considered, this degradation was greater than 10%. Comparing the presampling NPS with the sampled NPS showed that degradation in zero-frequency performance is due to zero-frequency noise aliasing induced by charge sharing. CONCLUSIONS: Noise performance, including spatial and energy correlations between elements and energy bins, are described by the joint PDF of deposited energies which provides a method of determining the photon-counting NPS, including noise-aliasing effects and spatio-energetic effects in spectral imaging. Our approach enables separating noise due to x-ray interactions from that associated with sampling, consistent with cascaded systems analysis of energy-integrating systems. Our methods can be incorporated into task-based assessment of image quality for the design and optimization of spectroscopic x-ray detectors.

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PURPOSE: Single-photon-counting (SPC) and spectroscopic x-ray detectors are under development in academic and industry laboratories for medical imaging applications. The spatial resolution of SPC and spectroscopic x-ray detectors is an important design criterion. The purpose of this article was to extend the cascaded systems approach to include a description of the spatial resolution of SPC and spectroscopic x-ray imaging detectors. METHODS: A cascaded systems approach was used to model reabsorption of characteristic x rays, Coulomb repulsion, and diffusion in SPC and spectroscopic x-ray detectors. In addition to reabsorption, diffusion, and Coulomb repulsion, the model accounted for x-ray conversion to electron-hole (e-h) pairs, integration of e-h pairs in detector elements, electronic noise, and energy thresholding. The probability density function (PDF) describing the number of e-h pairs was propagated through each stage of the model and was used to derive new theoretical expressions for the large-area gain and modulation transfer function (MTF) of CdTe SPC x-ray detectors, and the energy bin sensitivity functions and MTFs of CdTe spectroscopic detectors. Theoretical predictions were compared with the results of MATLAB-based Monte Carlo (MC) simulations and published data. Comparisons were also made with the MTF of energy-integrating systems. RESULTS: Under general radiographic conditions, reabsorption, diffusion, and Coulomb repulsion together artificially inflate count rates by 20% to 50%. For thicker converters (e.g. 1000 µm) and larger detector elements (e.g. 500 µm pixel pitch) these processes result in modest inflation (i.e. ∼10%) in apparent count rates. Our theoretical and MC analyses predict that SPC MTFs will be degraded relative to those of energy-integrating systems for fluoroscopic, general radiographic, and CT imaging conditions. In most cases, this degradation is modest (i.e., ∼10% at the Nyquist frequency). However, for thicker converters, the SPC MTF can be degraded by up to 25% at the Nyquist frequency relative to EI systems. Additionally, unlike EI systems, the MTF of spectroscopic systems is strongly dependent on photon energy, which results in energy-bin-dependent spatial resolution in spectroscopic systems. CONCLUSIONS: The PDF-transfer approach to modeling signal transfer through SPC and spectroscopic x-ray imaging systems provides a framework for understanding system performance. Application of this approach demonstrated that charge sharing artificially inflates the SPC image signal and degrades the MTF of SPC and spectroscopic systems relative to energy-integrating systems. These results further motivate the need for anticharge-sharing circuits to mitigate the effects of charge sharing on SPC and spectroscopic x-ray image quality.

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PURPOSE: The AAPM Task Group 162 aimed to provide a standardized approach for the assessment of image quality in planar imaging systems. This report offers a description of the approach as well as the details of the resultant software bundle to measure detective quantum efficiency (DQE) as well as its basis components and derivatives. METHODS: The methodology and the associated software include the characterization of the noise power spectrum (NPS) from planar images acquired under specific acquisition conditions, modulation transfer function (MTF) using an edge test object, the DQE, and effective DQE (eDQE). First, a methodological framework is provided to highlight the theoretical basis of the work. Then, a step-by-step guide is included to assist in proper execution of each component of the code. Lastly, an evaluation of the method is included to validate its accuracy against model-based and experimental data. RESULTS: The code was built using a Macintosh OSX operating system. The software package contains all the source codes to permit an experienced user to build the suite on a Linux or other *nix type system. The package further includes manuals and sample images and scripts to demonstrate use of the software for new users. The results of the code are in close alignment with theoretical expectations and published results of experimental data. CONCLUSIONS: The methodology and the software package offered in AAPM TG162 can be used as baseline for characterization of inherent image quality attributes of planar imaging systems.

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PURPOSE: Acquisition of high-quality x-ray images using low patient exposures requires detectors with high detective quantum efficiency (DQE). We describe a novel apodized-aperture pixel (AAP) design that increases high-frequency modulation transfer function (MTF) and DQE values. The AAP design makes a separation of physical sensor elements from image pixels by using very small sensor elements (e.g., 0.010-0.025 mm) to synthesize desired larger image pixels (e.g., 0.1-0.2 mm). METHODS: A cascaded systems model of signal and noise propagation is developed to describe the benefits of the AAP approach in terms of the MTF, Wiener noise power spectrum (NPS), and DQE. The theoretical model was validated experimentally using a CMOS/CsI detector with 0.05 mm sensor elements to synthesize 0.20 mm image pixels and a clinical Se detector with 0.07 mm sensor elements to synthesize 0.28 mm pixels. A Monte Carlo study and x-ray images of a star-pattern and rat leg are used to visually compare AAP images. RESULTS: When used with a high-resolution converter layer and sensor elements one quarter the size of image pixels, the MTF is increased by 53% and the DQE by a factor of 2.3× at the image sampling cut-off frequency. Both simulated and demonstration images show improved detectability of high-frequency content and removal of aliasing artifacts. Evidence of Gibbs ringing is sometimes seen near high-contrast edges. CONCLUSIONS: It is shown that the AAP approach preserves the MTF of the small sensor elements and attenuates frequencies above the image sampling cut-off frequency. This has the double benefit of improving the MTF while reducing both signal and noise aliasing, resulting in an increase of the DQE at high spatial frequencies. For optimal implementation, the converter layer must have very high spatial resolution and the detector must have low readout noise.

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GOAL: We investigate the signal and noise performance of an x-ray microtomography system that incorporates a complementary metal-oxide-semiconductor flat-panel detector as a projection image receptor. METHODS: Signal and noise performance is analyzed in the Fourier domain using modulation-transfer function (MTF), noise-power spectrum (NPS), and noise-equivalent number of quanta (NEQ) with respect to magnification and different convolution kernels for image reconstruction. RESULTS: Higher magnification provides lower NPS, and thus, higher NEQ performance in the transaxial planes from microtomography. A window function capable of smoothing the ramp filter edge to below one-half of the Nyquist limit results in better performance in terms of NPS and NEQ. The characteristics of convolution kernels do not affect signal and noise performance in longitudinal planes; hence, MTF performance mainly dominates the NEQ performance. The signal and noise performances investigated in this study are demonstrated with images obtained from the contrast phantom and postmortem mouse. CONCLUSION: The results of our study could be helpful in developing x-ray microtomography systems based on flat-panel detectors.

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PURPOSE: X-ray digital subtraction angiography (DSA) is widely used for vascular imaging. However, motion artifacts render it largely unsuccessful for some applications including cardiac imaging. Dual-energy imaging using fast kV switching was proposed in the past to provide the benefits of DSA with fewer motion artifacts, but image quality was inferior to DSA. This study compares the iodine Rose SNR that can be achieved using dual-energy methods, called energy-subtraction angiography (ESA), with that of DSA and examines the technical conditions required to achieve near-optimal SNR. METHODS: A Rose SNR model is described, experimentally validated, and used to compare ESA with DSA. The model considers detector quantum efficiency, readout noise (quantum-limit exposure), and scatter-to-primary ratio. RESULTS: The theoretical Rose SNR showed excellent agreement with experimental results for both ESA and DSA images, and shows that near-optimal SNR is harder to achieve with ESA than DSA. In comparison to DSA, ESA requires: (1) high detector quantum efficiency at a higher energy (120 kV); (2) lower detector readout noise by a factor of four (approximately 0.005 µGy air KERMA or lower); and (3) lower scatter-to-primary ratio by a factor of three (approximately 0.05 or lower). These conditions were not achievable in the past, and remain difficult but not impossible to achieve at present. CONCLUSIONS: ESA and DSA can provide similar iodine Rose SNR for the same patient exposure, but only when satisfying the above conditions. This may explain why dual-energy methods have been unsuccessful in the past and suggests ESA methods may offer a viable alternative to DSA when implemented under optimal conditions.

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We propose a new design of a stacked three-layer flat-panel x-ray detector for dual-energy (DE) imaging. Each layer consists of its own scintillator of individual thickness and an underlying thin-film-transistor-based flat-panel. Three images are obtained simultaneously in the detector during the same x-ray exposure, thereby eliminating any motion artifacts. The detector operation is two-fold: a conventional radiography image can be obtained by combining all three layers' images, while a DE subtraction image can be obtained from the front and back layers' images, where the middle layer acts as a mid-filter that helps achieve spectral separation. We proceed to optimize the detector parameters for two sample imaging tasks that could particularly benefit from this new detector by obtaining the best possible signal to noise ratio per root entrance exposure using well-established theoretical models adapted to fit our new design. These results are compared to a conventional DE temporal subtraction detector and a single-shot DE subtraction detector with a copper mid-filter, both of which underwent the same theoretical optimization. The findings are then validated using advanced Monte Carlo simulations for all optimized detector setups. Given the performance expected from initial results and the recent decrease in price for digital x-ray detectors, the simplicity of the three-layer stacked imager approach appears promising to usher in a new generation of multi-spectral digital x-ray diagnostics.

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Pulmonary vascular disease is a common complication of chronic obstructive pulmonary disease (COPD), and an important risk factor for COPD exacerbations and death. We explored the relationship between pulmonary artery volumes measured using thoracic computed tomography (CT) and lung structure-function measured using spirometry, CT and magnetic resonance imaging (MRI) in 124 ex-smokers with (n = 68) and without (n = 56) airflow obstruction, and a control group of 35 never-smokers. We observed significantly greater main (p = .01), right (p = .001) and total (p = .003) pulmonary artery volumes in ex-smokers with airflow obstruction as compared to ex-smokers without airflow obstruction. There were also significantly greater pulmonary artery volumes in both ex-smoker subgroups, compared to the never-smoker subgroup (p = .008). For all participants, there were significant correlations for pulmonary artery volumes with the ratio of the forced expiratory volume in 1 s to forced vital capacity (FEV1/FVC), the diffusing capacity of the lung for carbon monoxide (DLCO%pred), airway count, MRI ventilation defect percent and MRI apparent diffusion coefficients. In ex-smokers, ventilation defect percent was significantly correlated with right (r = 0.27, p = .02) and total (r = 0.25, p = .03) pulmonary artery volumes. Multivariate zero-inflated Poisson regression analysis showed that FEV1%pred (p = .004), DLCO%pred (p = .03), the six minute walk distance (p = .04) and total pulmonary artery volume (p = .03) were significant predictors of acute exacerbations of COPD, while the number of previous exacerbations was not. In conclusion, pulmonary artery enlargement measured using thoracic CT was observed even in ex-smokers without airflow obstruction and was predictive of COPD exacerbations in ex-smokers with airflow obstruction.

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PURPOSE: Single-photon-counting (SPC) x-ray imaging has the potential to improve image quality and enable novel energy-dependent imaging methods. Similar to conventional detectors, optimizing image SPC quality will require systems that produce the highest possible detective quantum efficiency (DQE). This paper builds on the cascaded-systems analysis (CSA) framework to develop a comprehensive description of the DQE of SPC detectors that implement adaptive binning. METHODS: The DQE of SPC systems can be described using the CSA approach by propagating the probability density function (PDF) of the number of image-forming quanta through simple quantum processes. New relationships are developed to describe PDF transfer through serial and parallel cascades to accommodate scatter reabsorption. Results are applied to hypothetical silicon and selenium-based flat-panel SPC detectors including the effects of reabsorption of characteristic/scatter photons from photoelectric and Compton interactions, stochastic conversion of x-ray energy to secondary quanta, depth-dependent charge collection, and electronic noise. Results are compared with a Monte Carlo study. RESULTS: Depth-dependent collection efficiency can result in substantial broadening of photopeaks that in turn may result in reduced DQE at lower x-ray energies (20-45 keV). Double-counting interaction events caused by reabsorption of characteristic/scatter photons may result in falsely inflated image signal-to-noise ratio and potential overestimation of the DQE. CONCLUSIONS: The CSA approach is extended to describe signal and noise propagation through photoelectric and Compton interactions in SPC detectors, including the effects of escape and reabsorption of emission/scatter photons. High-performance SPC systems can be achieved but only for certain combinations of secondary conversion gain, depth-dependent collection efficiency, electronic noise, and reabsorption characteristics.

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The absorbed energy distribution (AED) in X-ray imaging detectors is an important factor that affects both energy resolution and image quality through the Swank factor and detective quantum efficiency. In the diagnostic energy range (20-140 keV), escape of characteristic photons following photoelectric absorption and Compton scatter photons are primary sources of absorbed-energy dispersion in X-ray detectors. In this paper, we describe the development of an analytic model of the AED in compound X-ray detector materials, based on the cascaded-systems approach, that includes the effects of escape and reabsorption of characteristic and Compton-scatter photons. We derive analytic expressions for both semi-infinite slab and pixel geometries and validate our approach by Monte Carlo simulations. The analytic model provides the energy-dependent X-ray response function of arbitrary compound materials without time-consuming Monte Carlo simulations. We believe this model will be useful for correcting spectral distortion artifacts commonly observed in photon-counting applications and optimal design and development of novel X-ray detectors.

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PURPOSE: Single-photon counting (SPC) x-ray imaging has the potential to improve image quality and enable new advanced energy-dependent methods. The purpose of this study is to extend cascaded-systems analyses (CSA) to the description of image quality and the detective quantum efficiency (DQE) of SPC systems. METHODS: Point-process theory is used to develop a method of propagating the mean signal and Wiener noise-power spectrum through a thresholding stage (required to identify x-ray interaction events). The new transfer relationships are used to describe the zero-frequency DQE of a hypothetical SPC detector including the effects of stochastic conversion of incident photons to secondary quanta, secondary quantum sinks, additive noise, and threshold level. Theoretical results are compared with Monte Carlo calculations assuming the same detector model. RESULTS: Under certain conditions, the CSA approach can be applied to SPC systems with the additional requirement of propagating the probability density function describing the total number of image-forming quanta through each stage of a cascaded model. Theoretical results including DQE show excellent agreement with Monte Carlo calculations under all conditions considered. CONCLUSIONS: Application of the CSA method shows that false counts due to additive electronic noise results in both a nonlinear image signal and increased image noise. There is a window of allowable threshold values to achieve a high DQE that depends on conversion gain, secondary quantum sinks, and additive noise.

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PURPOSE: Theoretical models of the detective quantum efficiency (DQE) of x-ray detectors are an important step in new detector development by providing an understanding of performance limitations and benchmarks. Previous cascaded-systems analysis (CSA) models accounted for photoelectric interactions only. This paper describes an extension of the CSA approach to incorporate coherent and incoherent interactions, important for low-Z detectors such as silicon and selenium. METHODS: A parallel-cascade approach is used to describe the three types of x-ray interactions. The description of incoherent scatter required developing expressions for signal and noise transfer through an "energy-labeled reabsorption" process where the parameters describing reabsorption are random functions of the scatter photon energy. The description of coherent scatter requires the use of scatter form factors that may not be accurate for some crystalline detector materials. The model includes the effects of scatter reabsorption and escape, charge collection, secondary quantum sinks, noise aliasing, and additive noise. Model results are validated by Monte Carlo calculations for Si and Se detectors assuming free-atom atomic form factors. RESULTS: The new signal and noise transfer expressions were validated by showing agreement with Monte Carlo results. Coherent and incoherent scatter can degrade the DQE of Si and sometimes Se detectors depending on detector thickness and incident-photon energy. Incoherent scatter can produce a substantial low-frequency drop in the modulation transfer function and DQE. CONCLUSIONS: A generally useful CSA model of the DQE is described that is believed valid for any single-Z material up to 10 cycles/mm at both mammographic and radiographic energies within the limitations of Fourier-based linear-systems models and the use of coherent-scatter form factors. The model describes a substantial low-frequency drop in the DQE of Si systems due to incoherent scatter above 20-40 keV.

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RATIONALE AND OBJECTIVES: High-resolution computed tomography (CT) measurements of emphysema typically use Hounsfield unit (HU) density histogram thresholds or observer scores based on regions of low x-ray attenuation. Our objective was to develop an automated measurement of emphysema using principal component analysis (PCA) of the CT density histogram. MATERIALS AND METHODS: Ninety-seven ex-smokers, including 53 subjects with chronic obstructive pulmonary disease (COPD) and 44 asymptomatic subjects (AEs), provided written informed consent to imaging as well as plethysmography and spirometry. We applied PCA to the CT density histogram to generate whole lung and regional density histogram principal components including the first and second components and the sum of both principal components (density histogram principal component score [DHPCS]). Significant relationships for DHPCS with single HU thresholds, pulmonary function measurements, an expert's emphysema score, and hyperpolarized (3)He magnetic resonance imaging apparent diffusion coefficients (ADCs) were determined using linear regression and Pearson coefficients. Receiver operator characteristics analysis was performed using forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC) as the independent diagnostic. RESULTS: There was a significant difference (P < .0001) between AE and COPD subjects for DHPCS; FEV1/FVC; diffusing capacity of lung for carbon monoxide%predicted; attenuation values below -950, -910, and -856 HU; and (3)He ADCs. There were significant correlations for DHPCS with FEV1/FVC (r = -0.85, P < .0001); diffusing capacity of lung for carbon monoxide%predicted (r = -0.67, P < .0001); attenuation values below -950/-910/-856 HU (r = 0.93/0.96/0.76, P < .0001); and (3)He ADCs (r = 0.85, P < .0001). Receiver operator characteristics analysis showed a 91% classification rate for DHPCS. CONCLUSIONS: We generated an automated emphysema score using PCA of the CT density histogram with a 91% COPD classification rate that showed strong and significant correlations with pulmonary function tests, single HU thresholds, and (3)He magnetic resonance imaging ADCs.

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Dual-energy computed tomography (CT) enables 3-dimensional,noninvasive, and nondestructive imaging with material separation. Dual-energy CT is generally used to segment hydrated tissues within the clinical context. We apply dual-energy CT to an ancient Egyptian mummy and present several techniques designed to separate bone from desiccated tissue and resin. Automated and semiautomated dual-energy CT techniques are compared to manual segmentation and thresholding-based techniques. Semiautomated techniques enable substantial reductions in operator time compared to manual segmentation.

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PURPOSE: This study investigates the fundamental signal and noise performance limitations imposed by the stochastic nature of x-ray interactions in selected photoconductor materials, such as Si, a-Se, CdZnTe, HgI(2), PbI(2), PbO, and TlBr, for x-ray spectra typically used in mammography. METHODS: It is shown how Monte Carlo simulations can be combined with a cascaded model to determine the absorbed energy distribution for each combination of photoconductor and x-ray spectrum. The model is used to determine the quantum efficiency, mean energy absorption per interaction, Swank noise factor, secondary quantum noise, and zero-frequency detective quantum efficiency (DQE). RESULTS: The quantum efficiency of materials with higher atomic number and density demonstrates a larger dependence on convertor thickness than those with lower atomic number and density with the exception of a-Se. The mean deposited energy increases with increasing average energy of the incident x-ray spectrum. HgI(2), PbI(2), and CdZnTe demonstrate the largest increase in deposited energy with increasing mass loading and a-Se and Si the smallest. The best DQE performances are achieved with PbO and TlBr. For mass loading greater than 100 mg cm(-2), a-Se, HgI(2), and PbI(2) provide similar DQE values to PbO and TlBr. CONCLUSIONS: The quantum absorption efficiency, average deposited energy per interacting x-ray, Swank noise factor, and detective quantum efficiency are tabulated by means of graphs which may help with the design and selection of materials for photoconductor-based mammography detectors. Neglecting the electrical characteristics of photoconductor materials and taking into account only x-ray interactions, it is concluded that PbO shows the strongest signal-to-noise ratio performance of the materials investigated in this study.

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PURPOSE: X-ray digital subtraction angiography (DSA) is widely used for vascular imaging. However, the need to subtract a mask image can result in motion artifacts and compromised image quality. The current interest in energy-resolving photon-counting (EPC) detectors offers the promise of eliminating motion artifacts and other advanced applications using a single exposure. The authors describe a method of assessing the iodine signal-to-noise ratio (SNR) that may be achieved with energy-resolved angiography (ERA) to enable a direct comparison with other approaches including DSA and dual-energy angiography for the same patient exposure. METHODS: A linearized noise-propagation approach, combined with linear expressions of dual-energy and energy-resolved imaging, is used to describe the iodine SNR. The results were validated by a Monte Carlo calculation for all three approaches and compared visually for dual-energy and DSA imaging using a simple angiographic phantom with a CsI-based flat-panel detector. RESULTS: The linearized SNR calculations show excellent agreement with Monte Carlo results. While dual-energy methods require an increased tube heat load of 2× to 4× compared to DSA, and photon-counting detectors are not yet ready for angiographic imaging, the available iodine SNR for both methods as tested is within 10% of that of conventional DSA for the same patient exposure over a wide range of patient thicknesses and iodine concentrations. CONCLUSIONS: While the energy-based methods are not necessarily optimized and further improvements are likely, the linearized noise-propagation analysis provides the theoretical framework of a level playing field for optimization studies and comparison with conventional DSA. It is concluded that both dual-energy and photon-counting approaches have the potential to provide similar angiographic image quality to DSA.

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PURPOSE: Energy-resolved x-ray imaging has the potential to improve contrast-to-noise ratio by measuring the energy of each interacting photon and applying optimal weighting factors. The success of energy-resolving photon-counting (EPC) detectors relies on the ability of an x-ray detector to accurately measure the energy of each interacting photon. However, the escape of characteristic emissions and Compton scatter degrades spectral information. This article makes the theoretical connection between accuracy and imprecision in energy measurements with the x-ray Swank factor for a-Se, Si, CdZnTe, and HgI2-based detectors. METHODS: For a detector that implements adaptive binning to sum all elements in which x-ray energy is deposited for a single interaction, energy imprecision is shown to depend on the Swank factor for a large element with x rays incident at the center. The response function for each converter material is determined using Monte Carlo methods and used to determine energy accuracy, Swank factor, and relative energy imprecision in photon-energy measurements. RESULTS: For each material, at energies below the respective K edges, accuracy is close to unity and imprecision is only a few percent. Above the K-edge energies, characteristic emission results in a drop in accuracy and precision that depends on escape probability. In Si, and to some extent a-Se, Compton-scatter escape also degrades energy precision with increasing energy. The influence of converter thickness on energy accuracy and imprecision is modest for low-Z materials but becomes important when using high-Z materials at energies greater than the K-edge energies. CONCLUSIONS: Accuracy and precision in energy measurements by EPC detectors are determined largely by the energy-dependent x-ray Swank factor. Modest decreases in the Swank factor (5%-15%) result in large increases in relative imprecision (30%-40%).

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