Generalized DQE analysis of radiographic and dual-energy imaging using flat-panel detectors

Technical note: Characterization, validation, and spectral optimization of a dedicated breast CT system for contrast-enhanced imaging

BACKGROUND

The development of a new imaging modality, such as 4D dynamic contrast-enhanced dedicated breast CT (4D DCE-bCT), requires optimization of the acquisition technique, particularly within the 2D contrast-enhanced imaging modality. Given the extensive parameter space, cascade-systems analysis is commonly used for such optimization.

PURPOSE

To implement and validate a parallel-cascaded model for bCT, focusing on optimizing and characterizing system performance in the projection domain to enhance the quality of input data for image reconstruction.

METHODS

A parallel-cascaded system model of a state-of-the-art bCT system was developed and model predictions of the presampled modulation transfer function (MTF) and the normalized noise power spectrum (NNPS) were compared with empirical data collected in the projection domain. Validation was performed using the default settings of 49 kV with 1.5 mm aluminum filter and at 65 kV and 0.257 mm copper filter. A 10 mm aluminum plate was added to replicate the breast attenuation. Air kerma at the isocenter was measured at different tube current levels. Discrepancies between the measured projection domain metrics and model-predicted values were quantified using percentage error and coefficient of variation (CoV) for MTF and NNPS, respectively. The optimal filtration was for a 5 mm iodine disk detection task at 49, 55, 60, and 65 kV. The detectability index was calculated for the default aluminum filtration and for copper thicknesses ranging from 0.05 to 0.4 mm.

RESULTS

At 49 kV, MTF errors were +5.1% and -5.1% at 1 and 2 cycles/mm, respectively; NNPS CoV was 5.3% (min = 3.7%; max = 8.5%). At 65 kV, MTF errors were -0.8% and -3.2%; NNPS CoV was 13.1% (min = 11.4%; max = 16.9%). Air kerma output was linear, with 11.67 µGy/mA (R2 = 0.993) and 19.14 µGy/mA (R2 = 0.996) at 49 and 65 kV, respectively. For iodine detection, a 0.25 mm-thick copper filter at 65 kV was found optimal, outperforming the default technique by 90%.

CONCLUSION

The model accurately predicts bCT system performance, specifically in the projection domain, under varied imaging conditions, potentially contributing to the enhancement of 2D contrast-enhanced imaging in 4D DCE-bCT.

Xenon-enhanced dual-energy tomosynthesis for functional imaging of respiratory disease-Concept and phantom study

BACKGROUND

Xenon-enhanced dual-energy (DE) computed tomography (CT) and hyperpolarized noble-gas magnetic resonance imaging (MRI) provide maps of lung ventilation that can be used to detect chronic obstructive pulmonary disease (COPD) early in its development and predict respiratory exacerbations. However, xenon-enhanced DE-CT requires high radiation doses and hyper-polarized noble-gas MRI is expensive and only available at a handful of institutions globally.

PURPOSE

To present xenon-enhanced dual-energy tomosynthesis (XeDET) for low-dose, low-cost functional imaging of respiratory disease in an experimental phantom study.

METHODS

We propose using digital tomosynthesis to produce Xe-enhanced low-energy (LE) and high-energy (HE) coronal images. DE subtraction of the LE and HE images is used to suppress soft tissues. We used an imaging phantom to investigate image quality in terms of the area under the reciever operating characteristic curve (AUC) for the Non-PreWhitening model observer with an Eye filter and internal noise (NPWEi). The phantom simulated anatomic clutter due to lung parenchyma and attenuation due to soft tissue and lung tissue. Aluminum slats were used to simulate rib structures. A stepwedge consisting of an acrylic casing with sealed cylindrical air-filled cavities was used to simulate ventilation defects with step thicknesses of 0.5, 1, and 2 cm and cylindrical radii of 0.5, 0.75, and 1 cm. The phantom was ventilated with Xe and projection data were acquired using a flat-panel detector, a tube-voltage combination of 60/140 kV with 1.2  mm of copper filtration on the HE spectrum and an angular range of ± 15 ∘ $\pm 15^{\circ}$ in 1° increments. The AUC of a NPWEi observer that has access only to a single coronal slice was calculated from measurements of the three-dimensional noise power spectrum and signal template. The AUC was calculated as a function of ventilation defect thickness and radius for total patient entrance air kermas ranging from 1.42 to 2.84 mGy with and without rib-simulating Al slats. For the AUC analysis, the observer internal noise level was obtained from an ad hoc calibration to a high-dose data set.

RESULTS

XeDET was able to suppress parenchyma-simulating clutter in coronal images enabling visualization of the simulated ventilation defects, but the limited angle acquisition resulted in residual clutter due to out-of-plane bone-mimmicking structures. The signal power of the defects increased linearly with defect radius and showed a ten-fold to fifteen-fold increase in signal power when the defect thickness increased from 0.5 to 2 cm. These trends agreed with theoretical predictions. Along the depth dimension, the power of the defects decreased exponentially with distance from the center of the defects with full-width half maxima that varied from 1.85 to 2.85 cm depending on the defect thickness and radius. The AUCs of the 1-cm-radius defect that was 2 cm in thickness ranged from good (0.8-0.9) to excellent (0.9-1.0) over the range of air kermas considered.

CONCLUSIONS

Xenon-enhanced DE tomosynthesis has the potential to enable functional imaging of respiratory disease and should be further investigated as a low-cost alternative to MRI-based approaches and a low-dose alternative to CT-based approaches.

Experimental feasibility of xenon-enhanced dual-energy radiography for imaging of lung function

Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide. We experimentally investigated the feasibility of two-dimensional xenon-enhanced dual-energy (XeDE) radiography for imaging of lung function. We optimized image quality under quantum-noise-limited conditions using a chest phantom consisting of a rectangular chamber representing the thoracic volume and PMMA slabs simulating x-ray attenuation by soft tissue. A sealed, air-filled cavity with thin PMMA walls was positioned inside the chamber to simulate a 2 cm thick ventilation defect. The chamber was ventilated with xenon and dual-energy imaging was performed using a diagnostic x-ray tube and a flat-panel detector. The contrast-to-noise ratio of ventilation defects normalized by patient x-ray exposure maximized at a kV-pair of approximately 60/140-kV and when approximately one third of the total exposure was allocated to the HE image. We used the optimized technique to image a second phantom that contained lung-parenchyma-mimicking PMMA clutter, rib-mimicking aluminum slats and an insert that simulated ventilation defects with thicknesses ranging from 0.5 cm to 2 cm and diameters ranging from 1 cm to 2 cm. From the resulting images we computed the area under the receiver operating characteristic curve (AUC) of the non-prewhitening model observer with an eye filter and internal noise. For a xenon concentration of 75%, good AUCs (i.e. 0.8-0.9) to excellent AUCs (i.e. >0.9) were obtained when the defect diameter is greater than 1.3 cm and defect thickness is 1 cm. When the xenon concentration was reduced to 50%, the AUC was ∼0.9 for defects 1.2 cm in diameter and ∼1.5 cm in thickness. Two-dimensional XeDE radiography may therefore enable detection of functional abnormalities associated with early-stage COPD, for which xenon ventilation defects can occupy up to 20% of the lung volume, and should be further developed as a low-cost alternative to MRI-based approaches and a low-dose alternative to CT-based approaches.

Performance evaluation of digital breast tomosynthesis systems: physical methods and experimental data

Digital breast tomosynthesis (DBT) has become a well-established breast imaging technique, whose performance has been investigated in many clinical studies, including a number of prospective clinical trials. Results from these studies generally point to non-inferiority in terms of microcalcification detection and superior mass-lesion detection for DBT imaging compared to digital mammography (DM). This modality has become an essential tool in the clinic for assessment and ad-hoc screening but is not yet implemented in most breast screening programmes at a state or national level. While evidence on the clinical utility of DBT has been accumulating, there has also been progress in the development of methods for technical performance assessment and quality control of these imaging systems. DBT is a relatively complicated ‘pseudo-3D’ modality whose technical assessment poses a number of difficulties. This paper reviews methods for the technical performance assessment of DBT devices, starting at the component level in part one and leading up to discussion of system evaluation with physical test objects in part two. We provide some historical and basic theoretical perspective, often starting from methods developed for DM imaging. Data from a multi-vendor comparison are also included, acquired under the medical physics quality control protocol developed by EUREF and currently being consolidated by a European Federation of Organisations for Medical Physics working group. These data and associated methods can serve as a reference for the development of reference data and provide some context for clinical studies.

In-plane image quality and NPWE detectability index in digital breast tomosynthesis

A rigorous 2D analysis of signal and noise transfer applied to reconstructed planes in digital breast tomosynthesis (DBT) is necessary for system characterization and optimization. This work proposes a method for assessing technical image quality and system detective quantum efficiency (DQE_sys) for reconstructed planes in DBT. Measurements of 2D in-plane modulation transfer function (MTF) and noise power spectrum (NPS) were made on five DBT systems using different acquisition parameters, reconstruction algorithms and plane spacing. This work develops the noise equivalent quanta (NEQ), DQE_sys and detectability index (d') calculated using a non-prewhitening model observer with eye filter (NPWE) for reconstructed DBT planes. The images required for this implementation were acquired using a homogeneous test object of thickness 40 mm poly(methyl) methacrylate plus 0.5 mm Al; 2D MTF was calculated from an Al disc of thickness 0.2 mm and diameter 50 mm positioned within the phantom. The radiant contrast of the MTF disc and the air kerma at the system input were used as normalization factors. The NPWE detectability index was then compared to the in-plane contrast-detail (c-d) threshold measured using the CDMAM phantom. The MTF and NPS measured on the different systems showed a strong anisotropy, consistent with the cascaded models developed in the literature for DBT. Detectability indices calculated from the measured MTF and NPS successfully predicted changes in c-d detectability for details between 0.1 mm and 2.0 mm, for DBT plane spacings between 0.5 mm and 10 mm, and for air kerma values at the system input between 157 µGy and 1170 μGy. The linear Pearson correlation between the detectability index and threshold gold thickness of the CDMAM phantom was -0.996. The method implements a parametric means of assessing the technical image quality of reconstructed DBT planes, providing valuable information for optimization of DBT systems.

Frequency-dependent signal and noise in spectroscopic x-ray imaging

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.

Learning-based deformable image registration: effect of statistical mismatch between train and test images

Convolutional neural networks (CNNs) offer a promising means to achieve fast deformable image registration with accuracy comparable to conventional, physics-based methods. A persistent question with CNN methods, however, is whether they will be able to generalize to data outside of the training set. We investigated this question of mismatch between train and test data with respect to first- and second-order image statistics (e.g., spatial resolution, image noise, and power spectrum). A UNet-based architecture was built and trained on simulated CT images for various conditions of image noise (dose), spatial resolution, and deformation magnitude. Target registration error was measured as a function of the difference in statistical properties between the test and training data. Generally, registration error is minimized when the training data exactly match the statistics of the test data; however, networks trained with data exhibiting a diversity in statistical characteristics generalized well across the range of statistical conditions considered. Furthermore, networks trained on simulated image content with first- and second-order statistics selected to match that of real anatomical data were shown to provide reasonable registration performance on real anatomical content, offering potential new means for data augmentation. Characterizing the behavior of a CNN in the presence of statistical mismatch is an important step in understanding how these networks behave when deployed on new, unobserved data. Such characterization can inform decisions on whether retraining is necessary and can guide the data collection and/or augmentation process for training.

Objective assessment of task performance: a comparison of two FFDM detectors using an anthropomorphic breast phantom

Current digital mammography systems primarily employ one of two types of detectors: indirect conversion, typically using a cesium-iodine scintillator integrated with an amorphous silicon photodiode matrix, or direct conversion, using a photoconductive layer of amorphous selenium (a-Se) combined with thin-film transistor array. The goal of this study was to evaluate a methodology for objectively assessing image quality to compare human observer task performance in detecting microcalcification clusters and extended mass-like lesions achieved with different detector types. The proposed assessment methodology uses a novel anthropomorphic breast phantom fabricated with ink-jet printing. In addition to human observer detection performance, standard linear metrics such as modulation transfer function, noise power spectrum, and detective quantum efficiency (DQE) were also measured to assess image quality. An Analogic Anrad AXS-2430 a-Se detector used in a commercial FFDM/DBT system and a Teledyne Dalsa Xineos-2329 with CMOS pixel readout were evaluated and compared. The DQE of each detector was similar over a range of exposures. Similar task performance in detecting microcalcifications and masses was observed between the two detectors over a range of clinically applicable dose levels, with some perplexing differences in the detection of microcalcifications at the lowest dose measurement. The evaluation approach presented seems promising as a new technique for objective assessment of breast imaging technology.

A Statistical Model for Rigid Image Registration Performance: The Influence of Soft-Tissue Deformation as a Confounding Noise Source

Soft-tissue deformation presents a confounding factor to rigid image registration by introducing image content inconsistent with the underlying motion model, presenting non-correspondent structure with potentially high power, and creating local minima that challenge iterative optimization. In this paper, we introduce a model for registration performance that includes deformable soft tissue as a power-law noise distribution within a statistical framework describing the Cramer-Rao lower bound (CRLB) and root-mean-squared error (RMSE) in registration performance. The model incorporates both cross-correlation and gradient-based similarity metrics, and the model was tested in application to 3D-2D (CT-to-radiograph) and 3D-3D (CT-to-CT) image registration. Predictions accurately reflect the trends in registration error as a function of dose (quantum noise), and the choice of similarity metrics for both registration scenarios. Incorporating soft-tissue deformation as a noise source yields important insight on the limits of registration performance with respect to algorithm design and the clinical application or anatomical context. For example, the model quantifies the advantage of gradient-based similarity metrics in 3D-2D registration, identifies the low-dose limits of registration performance, and reveals the conditions for which the registration performance is fundamentally limited by soft-tissue deformation.

Predicting image properties in penalized-likelihood reconstructions of flat-panel CBCT

PURPOSE

Model-based iterative reconstruction (MBIR) algorithms such as penalized-likelihood (PL) methods exhibit data-dependent and shift-variant properties. Image quality predictors have been derived to prospectively estimate local noise and spatial resolution, facilitating both system hardware design and tuning of reconstruction methods. However, current MBIR image quality predictors rely on idealized system models, ignoring physical blurring effects and noise correlations found in real systems. In this work, we develop and validate a new set of predictors using a physical system model specific to flat-panel cone-beam CT (FP-CBCT).

METHODS

Physical models appropriate for integration with MBIR analysis are developed and parameterized to represent nonidealities in FP projection data including focal spot blur, scintillator blur, detector aperture effect, and noise correlations. Flat-panel-specific predictors for local spatial resolution and local noise properties in PL reconstructions are developed based on these realistic physical models. Estimation accuracy of conventional (idealized) and FP-specific predictors is investigated and validated against experimental CBCT measurements using specialized phantoms.

RESULTS

Validation studies show that flat-panel-specific predictors can accurately estimate the local spatial resolution and noise properties, while conventional predictors show significant deviations in the magnitude and scale of the spatial resolution and local noise. The proposed predictors show accurate estimations over a range of imaging conditions including varying x-ray technique and regularization strength. The conventional spatial resolution prediction is sharper than ground truth. Using conventional spatial resolution predictor, the full width at half maximum (FWHM) of local point spread function (PSF) is underestimated by 0.2 mm. This mismatch is mostly eliminated in FP-specific prediction. The general shape and amplitude of local noise power spectrum (NPS) FP-specific predictions are consistent with measurement, while the conventional predictions underestimated the noise level by 70%.

CONCLUSION

The proposed image quality predictors permit accurate estimation of local spatial resolution and noise properties for PL reconstruction, accounting for dependencies on the system geometry, x-ray technique, and patient-specific anatomy in real FP-CBCT. Such tools enable prospective analysis of image quality for a range of goals including novel system and acquisition design, adaptive and task-driven imaging, and tuning of MBIR for robust and reliable behavior.

Physics considerations in MV-CBCT multi-layer imager design

Megavoltage (MV) cone-beam computed tomography (CBCT) using an electronic portal imaging (EPID) offers advantageous features, including 3D mapping, treatment beam registration, high-z artifact suppression, and direct radiation dose calculation. Adoption has been slowed by image quality limitations and concerns about imaging dose. Developments in imager design, including pixelated scintillators, structured phosphors, inexpensive scintillation materials, and multi-layer imager (MLI) architecture have been explored to improve EPID image quality and reduce imaging dose. The present study employs a hybrid Monte Carlo and linear systems model to determine the effect of detector design elements, such as multi-layer architecture and scintillation materials. We follow metrics of image quality including modulation transfer function (MTF) and noise power spectrum (NPS) from projection images to 3D reconstructions to in-plane slices and apply a task based figure-of-merit, the ideal observer signal-to-noise ratio (d') to determine the effect of detector design on object detectability. Generally, detectability was limited by detector noise performance. Deploying an MLI imager with a single scintillation material for all layers yields improvement in noise performance and d' linear with the number of layers. In general, improving x-ray absorption using thicker scintillators results in improved DQE(0). However, if light yield is low, performance will be affected by electronic noise at relatively high doses, resulting in rapid image quality degradation. Maximizing image quality in a heterogenous MLI detector (i.e. multiple different scintillation materials) is most affected by limiting total noise. However, while a second-order effect, maximizing total spatial resolution of the MLI detector is a balance between the intensity contribution of each layer against its individual MTF. So, while a thinner scintillator may yield a maximal individual-layer MTF, its quantum efficiency will be relatively low in comparison to a thicker scintillator and thus, intensity contribution may be insufficient to noticeably improve the total detector MTF.

Leveraging multi-layer imager detector design to improve low-dose performance for megavoltage cone-beam computed tomography

While megavoltage cone-beam computed tomography (CBCT) using an electronic portal imaging device (EPID) provides many advantages over kilovoltage (kV) CBCT, clinical adoption is limited by its high doses. Multi-layer imager (MLI) EPIDs increase DQE(0) while maintaining high resolution. However, even well-designed, high-performance MLIs suffer from increased electronic noise from each readout, degrading low-dose image quality. To improve low-dose performance, shift-and-bin addition (ShiBA) imaging is proposed, leveraging the unique architecture of the MLI. ShiBA combines hardware readout-binning and super-resolution concepts, reducing electronic noise while maintaining native image sampling. The imaging performance of full-resolution (FR); standard, aligned binned (BIN); and ShiBA images in terms of noise power spectrum (NPS), electronic NPS, modulation transfer function (MTF), and the ideal observer signal-to-noise ratio (SNR)-the detectability index (d')-are compared. The FR 4-layer readout of the prototype MLI exhibits an electronic NPS magnitude 6-times higher than a state-of-the-art single layer (SLI) EPID. Although the MLI is built on the same readout platform as the SLI, with each layer exhibiting equivalent electronic noise, the multi-stage readout of the MLI results in electronic noise 50% higher than simple summation. Electronic noise is mitigated in both BIN and ShiBA imaging, reducing its total by ~12 times. ShiBA further reduces the NPS, effectively upsampling the image, resulting in a multiplication by a sinc² function. Normalized NPS show that neither ShiBA nor BIN otherwise affects image noise. The LSF shows that ShiBA removes the pixilation artifact of BIN images and mitigates the effect of detector shift, but does not quantifiably improve the MTF. ShiBA provides a pre-sampled representation of the images, mitigating phase dependence. Hardware binning strategies lower the quantum noise floor, with 2  ×  2 implementation reducing the dose at which DQE(0) degrades by 10% from 0.01 MU to 0.004 MU, representing 20% improvement in d'.

Dual-energy computed tomography of canine uroliths

OBJECTIVE To determine whether dual-energy CT (DECT) could accurately differentiate the composition of common canine uroliths in a phantom model. SAMPLE 30 canine uroliths with pure compositions. PROCEDURES Each urolith was composed of ≥ 70% struvite (n = 10), urate (8), cystine (5), calcium oxalate (4), or brushite (3) as determined by standard laboratory methods performed at the Canadian Veterinary Urolith Centre. Uroliths were suspended in an agar phantom, and DECT was performed at low (80 kV) and high (140 kV) energies. The ability of low- and high-energy CT numbers, DECT number, and DECT ratio to distinguish uroliths on the basis of composition was assessed with multivariate ANOVA. RESULTS No single DECT measure differentiated all urolith types. The DECT ratio differentiated urate uroliths from all other types of uroliths. The DECT and low-energy CT numbers were able to differentiate between 8 and 7 pairs of urolith types, respectively. CONCLUSIONS AND CLINICAL RELEVANCE Results indicated that DECT was unable to differentiate common types of canine uroliths in an in vitro model; therefore, it is unlikely to be clinically useful for determining urolith composition in vivo. Given that the primary reasons for determining urolith composition in vivo are to predict response to shock wave lithotripsy and develop a treatment plan, future research should focus on the correlation between DECT measurements and urolith fragility rather than urolith composition.

Task-Based Modeling of a 5k Ultra-High-Resolution Medical Imaging System for Digital Breast Tomosynthesis

High-resolution, low-noise X-ray detectors based on CMOS active pixel sensor (APS) technology have demonstrated superior imaging performance for digital breast tomosynthesis (DBT). This paper presents a task-based model for a high-resolution medical imaging system to evaluate its ability to detect simulated microcalcifications and masses as lesions for breast cancer. A 3-D cascaded system analysis for a 50- [Formula: see text] pixel pitch CMOS APS X-ray detector was integrated with an object task function, a medical imaging display model, and the human eye contrast sensitivity function to calculate the detectability index and area under the ROC curve (AUC). It was demonstrated that the display pixel pitch and zoom factor should be optimized to improve the AUC for detecting small microcalcifications. In addition, detector electronic noise of smaller than 300 e^- and a high display maximum luminance (>1000 cd/cm ²) are desirable to distinguish microcalcifications of [Formula: see text] in size. For low contrast mass detection, a medical imaging display with a minimum of 12-bit gray levels is recommended to realize accurate luminance levels. A wide projection angle range of greater than ±30° in combination with the image gray level magnification could improve the mass detectability especially when the anatomical background noise is high. On the other hand, a narrower projection angle range below ±20° can improve the small, high contrast object detection. Due to the low mass contrast and luminance, the ambient luminance should be controlled below 5 cd/ [Formula: see text]. Task-based modeling provides important firsthand imaging performance of the high-resolution CMOS-based medical imaging system that is still at early stage development for DBT. The modeling results could guide the prototype design and clinical studies in the future.

Optimization of contrast-enhanced breast imaging: Analysis using a cascaded linear system model

PURPOSE

Contrast-enhanced (CE) breast imaging involves the injection contrast agents (i.e., iodine) to increase conspicuity of malignant lesions. CE imaging may be used in conjunction with digital mammography (DM) or digital breast tomosynthesis (DBT) and has shown promise in improving diagnostic specificity. Both CE-DM and CE-DBT techniques require optimization as clinical diagnostic tools. Physical factors including x-ray spectra, subtraction technique, and the signal from iodine contrast, must be considered to provide the greatest object detectability and image quality. We developed a cascaded linear system model (CLSM) for the optimization of CE-DM and CE-DBT employing dual energy (DE) subtraction or temporal (TE) subtraction.

METHODS

We have previously developed a CLSM for DBT implemented with an a-Se flat panel imager (FPI) and filtered backprojection (FBP) reconstruction algorithm. The model is used to track image quality metrics - modulation transfer function (MTF) and noise power spectrum (NPS) - at each stage of the imaging chain. In this study, the CLSM is extended for CE breast imaging. The effect of x-ray spectrum (varied by changing tube potential and the filter) and DE and TE subtraction techniques on breast structural noise was measured was studied and included as a deterministic source of noise in the CLSM. From the two-dimensional (2D) and three-dimensional (3D) MTF and NPS, the ideal observer signal-to-noise ratio (SNR), also known as the detectability index (d'), may be calculated. Using d' as a FOM, we discuss the optimization of CE imaging for the task of iodinated contrast object detection within structured backgrounds.

RESULTS

Increasing x-ray energy was determined to decrease the magnitude of structural noise and not its correlation. By performing DE subtraction, the magnitude of the structural noise was further reduced at the expense of increased stochastic (quantum and electronic) noise. TE subtraction exhibited essentially no residual structural noise at the expense of increased quantum noise, even over that of the DE case. For DE subtraction, optimization of dose weighting to the HE view (f_h ) results in the minimization of quantum noise. Both subtraction weighting factor (w_Sub ) and the iodine contrast signal were dependent on the LE and HE x-ray spectra. To best detect a 5 mm Gaussian lesion with 5 mg/ml of iodine within a 4 cm thick breast, it was found that the high energy (HE) view should be acquired with a tube potential of 47 kVp (W/Ti spectrum) and the low energy (LE) view with a potential of 23 kVp (W/Rh spectrum). Due to the complete removal of structural noise, TE subtraction produced much higher d' than DE subtraction both as a function of mean glandular dose and iodine concentration.

CONCLUSIONS

We have shown the effect of increasing x-ray energy as well as projection domain subtraction on breast structural noise. Further, we have exhibited the utility of the CLSM for DE and TE subtraction CE imaging in the optimization of imaging parameters such as x-ray energy, f_h , and w_Sub as well as guiding the understanding of their effects on image contrast and noise.

Technical Note: spektr 3.0-A computational tool for x-ray spectrum modeling and analysis

PURPOSE

A computational toolkit (spektr 3.0) has been developed to calculate x-ray spectra based on the tungsten anode spectral model using interpolating cubic splines (TASMICS) algorithm, updating previous work based on the tungsten anode spectral model using interpolating polynomials (TASMIP) spectral model. The toolkit includes a matlab (The Mathworks, Natick, MA) function library and improved user interface (UI) along with an optimization algorithm to match calculated beam quality with measurements.

METHODS

The spektr code generates x-ray spectra (photons/mm(2)/mAs at 100 cm from the source) using TASMICS as default (with TASMIP as an option) in 1 keV energy bins over beam energies 20-150 kV, extensible to 640 kV using the TASMICS spectra. An optimization tool was implemented to compute the added filtration (Al and W) that provides a best match between calculated and measured x-ray tube output (mGy/mAs or mR/mAs) for individual x-ray tubes that may differ from that assumed in TASMICS or TASMIP and to account for factors such as anode angle.

RESULTS

The median percent difference in photon counts for a TASMICS and TASMIP spectrum was 4.15% for tube potentials in the range 30-140 kV with the largest percentage difference arising in the low and high energy bins due to measurement errors in the empirically based TASMIP model and inaccurate polynomial fitting. The optimization tool reported a close agreement between measured and calculated spectra with a Pearson coefficient of 0.98.

CONCLUSIONS

The computational toolkit, spektr, has been updated to version 3.0, validated against measurements and existing models, and made available as open source code. Video tutorials for the spektr function library, UI, and optimization tool are available.

Tailoring automatic exposure control toward constant detectability in digital mammography

PURPOSE

The automatic exposure control (AEC) modes of most full field digital mammography (FFDM) systems are set up to hold pixel value (PV) constant as breast thickness changes. This paper proposes an alternative AEC mode, set up to maintain some minimum detectability level, with the ultimate goal of improving object detectability at larger breast thicknesses.

METHODS

The default "opdose" AEC mode of a Siemens MAMMOMAT Inspiration FFDM system was assessed using poly(methyl methacrylate) (PMMA) of thickness 20, 30, 40, 50, 60, and 70 mm to find the tube voltage and anode/filter combination programmed for each thickness; these beam quality settings were used for the modified AEC mode. Detectability index (d'), in terms of a non-prewhitened model observer with eye filter, was then calculated as a function of tube current-time product (mAs) for each thickness. A modified AEC could then be designed in which detectability never fell below some minimum setting for any thickness in the operating range. In this study, the value was chosen such that the system met the achievable threshold gold thickness (Tt) in the European guidelines for the 0.1 mm diameter disc (i.e., Tt ≤ 1.10 μm gold). The default and modified AEC modes were compared in terms of contrast-detail performance (Tt), calculated detectability (d'), signal-difference-to-noise ratio (SDNR), and mean glandular dose (MGD). The influence of a structured background on object detectability for both AEC modes was examined using a CIRS BR3D phantom. Computer-based CDMAM reading was used for the homogeneous case, while the images with the BR3D background were scored by human observers.

RESULTS

The default opdose AEC mode maintained PV constant as PMMA thickness increased, leading to a reduction in SDNR for the homogeneous background 39% and d' 37% in going from 20 to 70 mm; introduction of the structured BR3D plate changed these figures to 22% (SDNR) and 6% (d'), respectively. Threshold gold thickness (0.1 mm diameter disc) for the default AEC mode in the homogeneous background increased by 62% in going from 20 to 70 mm PMMA thickness; in the structured background, the increase was 39%. Implementation of the modified mode entailed an increase in mAs at PMMA thicknesses >40 mm; the modified AEC held threshold gold thickness constant above 40 mm PMMA with a maximum deviation of 5% in the homogeneous background and 3% in structured background. SDNR was also held constant with a maximum deviation of 4% and 2% for the homogeneous and the structured background, respectively. These results were obtained with an increase of MGD between 15% and 73% going from 40 to 70 mm PMMA thickness.

CONCLUSIONS

This work has proposed and implemented a modified AEC mode, tailored toward constant detectability at larger breast thickness, i.e., above 40 mm PMMA equivalent. The desired improvement in object detectability could be obtained while maintaining MGD within the European guidelines achievable dose limit. (A study designed to verify the performance of the modified mode using more clinically realistic data is currently underway.).

The effect of amorphous selenium detector thickness on dual-energy digital breast imaging

PURPOSE

Contrast enhanced (CE) imaging techniques for both planar digital mammography (DM) and three-dimensional (3D) digital breast tomosynthesis (DBT) applications requires x-ray photon energies higher than the k-edge of iodine (33.2 keV). As a result, x-ray tube potentials much higher (>40 kVp) than those typical for screening mammography must be utilized. Amorphous selenium (a-Se) based direct conversion flat-panel imagers (FPI) have been widely used in DM and DBT imaging systems. The a-Se layer is typically 200 μm thick with quantum detective efficiency (QDE) >87% for x-ray energies below 26 keV. However, QDE decreases substantially above this energy. To improve the object detectability of either CE-DM or CE-DBT, it may be advantageous to increase the thickness (dSe) of the a-Se layer. Increasing the dSe will improve the detective quantum efficiency (DQE) at the higher energies used in CE imaging. However, because most DBT systems are designed with partially isocentric geometries, where the gantry moves about a stationary detector, the oblique entry of x-rays will introduce additional blur to the system. The present investigation quantifies the effect of a-Se thickness on imaging performance for both CE-DM and CE-DBT, discussing the effects of improving photon absorption and blurring from oblique entry of x-rays.

METHODS

In this paper, a cascaded linear system model (CLSM) was used to investigate the effect of dSe on the imaging performance (i.e., MTF, NPS, and DQE) of FPI in CE-DM and CE-DBT. The results from the model are used to calculate the ideal observer signal-to-noise ratio, d', which is used as a figure-of-merit to determine the total effect of increasing dSe for CE-DM and CE-DBT.

RESULTS

The results of the CLSM show that increasing dSe causes a substantial increase in QDE at the high energies used in CE-DM. However, at the oblique projection angles used in DBT, the increased length of penetration through a-Se introduces additional image blur. The reduced MTF and DQE at high spatial frequencies lead to reduced two-dimensional d'. These losses in projection image resolution may subsequently result in a decrease in the 3D d', but the degree of which is largely dependent on the DBT reconstruction algorithm. For a filtered backprojection (FBP) algorithm with spectral apodization and slice-thickness filters, which dominate the blur for reconstructed images at oblique angles, the effect of oblique entry of x-rays on 3D d' is minimal. Thus, increasing dSe results in an improvement in d' for both CE-DM and CE-DBT with typical FBP reconstruction parameters.

CONCLUSIONS

Increased dSe improves CE breast imaging performance by increasing QDE of detectors at higher energies, e.g., 49 kVp. Although there is additional blur in the oblique angled projections of a DBT scan, the overall 3D d' for DBT is not degraded because the dominant source blur at these angles results from the reconstruction filters of the employed FBP algorithm.

Optimized Detector Angular Configuration Increases the Sensitivity of X-ray Fluorescence Computed Tomography (XFCT)

In this work, we demonstrated that an optimized detector angular configuration based on the anisotropic energy distribution of background scattered X-rays improves X-ray fluorescence computed tomography (XFCT) detection sensitivity. We built an XFCT imaging system composed of a bench-top fluoroscopy X-ray source, a CdTe X-ray detector, and a phantom motion stage. We imaged a 6.4-cm-diameter phantom containing different concentrations of gold solution and investigated the effect of detector angular configuration on XFCT image quality. Based on our previous theoretical study, three detector angles were considered. The X-ray fluorescence detector was first placed at 145 (°) (approximating back-scatter) to minimize scatter X-rays. XFCT image quality was compared to images acquired with the detector at 60 (°) (forward-scatter) and 90 (°) (side-scatter). The datasets for the three different detector positions were also combined to approximate an isotropically arranged detector. The sensitivity was optimized with detector in the 145 (°) back-scatter configuration counting the 78-keV gold Kβ1 X-rays. The improvement arose from the reduced energy of scattered X-ray at the 145 (°) position and the large energy separation from gold K β1 X-rays. The lowest detected concentration in this configuration was 2.5 mgAu/mL (or 0.25% Au with SNR = 4.3). This concentration could not be detected with the 60 (°) , 90 (°) , or isotropic configurations (SNRs = 1.3, 0, 2.3, respectively). XFCT imaging dose of 14 mGy was in the range of typical clinical X-ray CT imaging doses. To our knowledge, the sensitivity achieved in this experiment is the highest in any XFCT experiment using an ordinary bench-top X-ray source in a phantom larger than a mouse ( > 3 cm).

Optimal frequency-based weighting for spectral x-ray projection imaging

The purpose of this work is to derive a weighting scheme that maximizes the frequency-dependent ideal observer signal-difference-to-noise ratio, commonly referred to as detectability index or Hotelling-SDNR, for spectral X-ray projection imaging. Starting from basic statistical decision theory, optimal frequency-dependent weights are derived for a multiple-bin system and the Hotelling-SDNR calculated. A 28% increase in detectability index is found for high frequency objects when applying optimal frequency-dependent weights instead of pixel-based weights to a simplified model of a silicon detector, decreasing towards 0% for low frequency objects. Simulation results indicate a potentially large increase in detectability for high-frequency object imaging using silicon detectors, thus meriting further evaluations on a real system.

Task-based measures of image quality and their relation to radiation dose and patient risk

The theory of task-based assessment of image quality is reviewed in the context of imaging with ionizing radiation, and objective figures of merit (FOMs) for image quality are summarized. The variation of the FOMs with the task, the observer and especially with the mean number of photons recorded in the image is discussed. Then various standard methods for specifying radiation dose are reviewed and related to the mean number of photons in the image and hence to image quality. Current knowledge of the relation between local radiation dose and the risk of various adverse effects is summarized, and some graphical depictions of the tradeoffs between image quality and risk are introduced. Then various dose-reduction strategies are discussed in terms of their effect on task-based measures of image quality.

Task-based strategy for optimized contrast enhanced breast imaging: analysis of six imaging techniques for mammography and tomosynthesis

PURPOSE

The use of contrast agents in breast imaging has the capability of enhancing nodule detectability and providing physiological information. Accordingly, there has been a growing trend toward using iodine as a contrast medium in digital mammography (DM) and digital breast tomosynthesis (DBT). Widespread use raises concerns about the best way to use iodine in DM and DBT, and thus a comparison is necessary to evaluate typical iodine-enhanced imaging methods. This study used a task-based observer model to determine the optimal imaging approach by analyzing six imaging paradigms in terms of their ability to resolve iodine at a given dose: unsubtracted mammography and tomosynthesis, temporal subtraction mammography and tomosynthesis, and dual energy subtraction mammography and tomosynthesis.

METHODS

Imaging performance was characterized using a detectability index d', derived from the system task transfer function (TTF), an imaging task, iodine signal difference, and the noise power spectrum (NPS). The task modeled a 10 mm diameter lesion containing iodine concentrations between 2.1 mg/cc and 8.6 mg/cc. TTF was obtained using an edge phantom, and the NPS was measured over several exposure levels, energies, and target-filter combinations. Using a structured CIRS phantom, d' was generated as a function of dose and iodine concentration.

RESULTS

For all iodine concentrations and dose, temporal subtraction techniques for mammography and tomosynthesis yielded the highest d', while dual energy techniques for both modalities demonstrated the next best performance. Unsubtracted imaging resulted in the lowest d' values for both modalities, with unsubtracted mammography performing the worst out of all six paradigms.

CONCLUSIONS

At any dose, temporal subtraction imaging provides the greatest detectability, with temporally subtracted DBT performing the highest. The authors attribute the successful performance to excellent cancellation of inplane structures and improved signal difference in the lesion.

Noise, sampling, and the number of projections in cone-beam CT with a flat-panel detector

PURPOSE

To investigate the effect of the number of projection views on image noise in cone-beam CT (CBCT) with a flat-panel detector.

METHODS

This fairly fundamental consideration in CBCT system design and operation was addressed experimentally (using a phantom presenting a uniform medium as well as statistically motivated "clutter") and theoretically (using a cascaded systems model describing CBCT noise) to elucidate the contributing factors of quantum noise (σ(Q)), electronic noise (σ(E)), and view aliasing (σ(view)). Analysis included investigation of the noise, noise-power spectrum, and modulation transfer function as a function of the number of projections (N(proj)), dose (D(tot)), and voxel size (b(vox)).

RESULTS

The results reveal a nonmonotonic relationship between image noise and N(proj) at fixed total dose: for the CBCT system considered, noise decreased with increasing N(proj) due to reduction of view sampling effects in the regime N(proj) <~200, above which noise increased with N(proj) due to increased electronic noise. View sampling effects were shown to depend on the heterogeneity of the object in a direct analytical relationship to power-law anatomical clutter of the form κ/f(β)--and a general model of individual noise components (σ(Q), σ(E), and σ(view)) demonstrated agreement with measurements over a broad range in N(proj), D(tot), and b(vox).

CONCLUSIONS

The work elucidates fairly basic elements of CBCT noise in a manner that demonstrates the role of distinct noise components (viz., quantum, electronic, and view sampling noise). For configurations fairly typical of CBCT with a flat-panel detector (FPD), the analysis reveals a "sweet spot" (i.e., minimum noise) in the range N(proj) ~ 250-350, nearly an order of magnitude lower in N(proj) than typical of multidetector CT, owing to the relatively high electronic noise in FPDs. The analysis explicitly relates view aliasing and quantum noise in a manner that includes aspects of the object ("clutter") and imaging chain (including nonidealities of detector blur and electronic noise) to provide a more rigorous basis for commonly held intuition and heurism in CBCT system design and operation.

Cascaded systems analysis of photon counting detectors

PURPOSE

Photon counting detectors (PCDs) are an emerging technology with applications in spectral and low-dose radiographic and tomographic imaging. This paper develops an analytical model of PCD imaging performance, including the system gain, modulation transfer function (MTF), noise-power spectrum (NPS), and detective quantum efficiency (DQE).

METHODS

A cascaded systems analysis model describing the propagation of quanta through the imaging chain was developed. The model was validated in comparison to the physical performance of a silicon-strip PCD implemented on an experimental imaging bench. The signal response, MTF, and NPS were measured and compared to theory as a function of exposure conditions (70 kVp, 1-7 mA), detector threshold, and readout mode (i.e., the option for coincidence detection). The model sheds new light on the dependence of spatial resolution, charge sharing, and additive noise effects on threshold selection and was used to investigate the factors governing PCD performance, including the fundamental advantages and limitations of PCDs in comparison to energy-integrating detectors (EIDs) in the linear regime for which pulse pileup can be ignored.

RESULTS

The detector exhibited highly linear mean signal response across the system operating range and agreed well with theoretical prediction, as did the system MTF and NPS. The DQE analyzed as a function of kilovolt (peak), exposure, detector threshold, and readout mode revealed important considerations for system optimization. The model also demonstrated the important implications of false counts from both additive electronic noise and charge sharing and highlighted the system design and operational parameters that most affect detector performance in the presence of such factors: for example, increasing the detector threshold from 0 to 100 (arbitrary units of pulse height threshold roughly equivalent to 0.5 and 6 keV energy threshold, respectively), increased the f50 (spatial-frequency at which the MTF falls to a value of 0.50) by ∼30% with corresponding improvement in DQE. The range in exposure and additive noise for which PCDs yield intrinsically higher DQE was quantified, showing performance advantages under conditions of very low-dose, high additive noise, and high fidelity rejection of coincident photons.

CONCLUSIONS

The model for PCD signal and noise performance agreed with measurements of detector signal, MTF, and NPS and provided a useful basis for understanding complex dependencies in PCD imaging performance and the potential advantages (and disadvantages) in comparison to EIDs as well as an important guide to task-based optimization in developing new PCD imaging systems.

Feasibility study of dual energy radiographic imaging for target localization in radiotherapy for lung tumors

Purpose

Dual-energy (DE) radiographic imaging improves tissue discrimination by separating soft from hard tissues in the acquired images. This study was to establish a mathematic model of DE imaging based on intrinsic properties of tissues and quantitatively evaluate the feasibility of applying the DE imaging technique to tumor localization in radiotherapy.

Methods

We investigated the dependence of DE image quality on the radiological equivalent path length (EPL) of tissues with two phantoms using a stereoscopic x-ray imaging unit. 10 lung cancer patients who underwent radiotherapy each with gold markers implanted in the tumor were enrolled in the study approved by the hospital's Ethics Committee. The displacements of the centroids of the delineated gross tumor volumes (GTVs) in the digitally reconstructed radiograph (DRR) and in the bone-canceled DE image were compared with the averaged displacements of the centroids of gold markers to evaluate the feasibility of using DE imaging for tumor localization.

Results

The results of the phantom study indicated that the contrast-to-noise ratio (CNR) was linearly dependent on the difference of EPL and a mathematical model was established. The objects and backgrounds corresponding to ΔEPL less than 0.08 are visually indistinguishable in the bone-canceled DE image. The analysis of patient data showed that the tumor contrast in the bone-canceled images was improved significantly as compared with that in the original radiographic images and the accuracy of tumor localization using the DE imaging technique was comparable with that of using fiducial makers.

Conclusion

It is feasible to apply the technique for tumor localization in radiotherapy.

Task-based detectability in CT image reconstruction by filtered backprojection and penalized likelihood estimation

PURPOSE

Nonstationarity is an important aspect of imaging performance in CT and cone-beam CT (CBCT), especially for systems employing iterative reconstruction. This work presents a theoretical framework for both filtered-backprojection (FBP) and penalized-likelihood (PL) reconstruction that includes explicit descriptions of nonstationary noise, spatial resolution, and task-based detectability index. Potential utility of the model was demonstrated in the optimal selection of regularization parameters in PL reconstruction.

METHODS

Analytical models for local modulation transfer function (MTF) and noise-power spectrum (NPS) were investigated for both FBP and PL reconstruction, including explicit dependence on the object and spatial location. For FBP, a cascaded systems analysis framework was adapted to account for nonstationarity by separately calculating fluence and system gains for each ray passing through any given voxel. For PL, the point-spread function and covariance were derived using the implicit function theorem and first-order Taylor expansion according to Fessler ["Mean and variance of implicitly defined biased estimators (such as penalized maximum likelihood): Applications to tomography," IEEE Trans. Image Process. 5(3), 493-506 (1996)]. Detectability index was calculated for a variety of simple tasks. The model for PL was used in selecting the regularization strength parameter to optimize task-based performance, with both a constant and a spatially varying regularization map.

RESULTS

Theoretical models of FBP and PL were validated in 2D simulated fan-beam data and found to yield accurate predictions of local MTF and NPS as a function of the object and the spatial location. The NPS for both FBP and PL exhibit similar anisotropic nature depending on the pathlength (and therefore, the object and spatial location within the object) traversed by each ray, with the PL NPS experiencing greater smoothing along directions with higher noise. The MTF of FBP is isotropic and independent of location to a first order approximation, whereas the MTF of PL is anisotropic in a manner complementary to the NPS. Task-based detectability demonstrates dependence on the task, object, spatial location, and smoothing parameters. A spatially varying regularization "map" designed from locally optimal regularization can improve overall detectability beyond that achievable with the commonly used constant regularization parameter.

CONCLUSIONS

Analytical models for task-based FBP and PL reconstruction are predictive of nonstationary noise and resolution characteristics, providing a valuable framework for understanding and optimizing system performance in CT and CBCT.

Monte Carlo study of the effects of system geometry and antiscatter grids on cone-beam CT scatter distributions

PURPOSE

The proliferation of cone-beam CT (CBCT) has created interest in performance optimization, with x-ray scatter identified among the main limitations to image quality. CBCT often contends with elevated scatter, but the wide variety of imaging geometry in different CBCT configurations suggests that not all configurations are affected to the same extent. Graphics processing unit (GPU) accelerated Monte Carlo (MC) simulations are employed over a range of imaging geometries to elucidate the factors governing scatter characteristics, efficacy of antiscatter grids, guide system design, and augment development of scatter correction.

METHODS

A MC x-ray simulator implemented on GPU was accelerated by inclusion of variance reduction techniques (interaction splitting, forced scattering, and forced detection) and extended to include x-ray spectra and analytical models of antiscatter grids and flat-panel detectors. The simulator was applied to small animal (SA), musculoskeletal (MSK) extremity, otolaryngology (Head), breast, interventional C-arm, and on-board (kilovoltage) linear accelerator (Linac) imaging, with an axis-to-detector distance (ADD) of 5, 12, 22, 32, 60, and 50 cm, respectively. Each configuration was modeled with and without an antiscatter grid and with (i) an elliptical cylinder varying 70-280 mm in major axis; and (ii) digital murine and anthropomorphic models. The effects of scatter were evaluated in terms of the angular distribution of scatter incident upon the detector, scatter-to-primary ratio (SPR), artifact magnitude, contrast, contrast-to-noise ratio (CNR), and visual assessment.

RESULTS

Variance reduction yielded improvements in MC simulation efficiency ranging from ∼17-fold (for SA CBCT) to ∼35-fold (for Head and C-arm), with the most significant acceleration due to interaction splitting (∼6 to ∼10-fold increase in efficiency). The benefit of a more extended geometry was evident by virtue of a larger air gap-e.g., for a 16 cm diameter object, the SPR reduced from 1.5 for ADD = 12 cm (MSK geometry) to 1.1 for ADD = 22 cm (Head) and to 0.5 for ADD = 60 cm (C-arm). Grid efficiency was higher for configurations with shorter air gap due to a broader angular distribution of scattered photons-e.g., scatter rejection factor ∼0.8 for MSK geometry versus ∼0.65 for C-arm. Grids reduced cupping for all configurations but had limited improvement on scatter-induced streaks and resulted in a loss of CNR for the SA, Breast, and C-arm. Relative contribution of forward-directed scatter increased with a grid (e.g., Rayleigh scatter fraction increasing from ∼0.15 without a grid to ∼0.25 with a grid for the MSK configuration), resulting in scatter distributions with greater spatial variation (the form of which depended on grid orientation).

CONCLUSIONS

A fast MC simulator combining GPU acceleration with variance reduction provided a systematic examination of a range of CBCT configurations in relation to scatter, highlighting the magnitude and spatial uniformity of individual scatter components, illustrating tradeoffs in CNR and artifacts and identifying the system geometries for which grids are more beneficial (e.g., MSK) from those in which an extended geometry is the better defense (e.g., C-arm head imaging). Compact geometries with an antiscatter grid challenge assumptions of slowly varying scatter distributions due to increased contribution of Rayleigh scatter.

Cascaded systems analysis of noise and detectability in dual-energy cone-beam CT

PURPOSE

Dual-energy computed tomography and dual-energy cone-beam computed tomography (DE-CBCT) are promising modalities for applications ranging from vascular to breast, renal, hepatic, and musculoskeletal imaging. Accordingly, the optimization of imaging techniques for such applications would benefit significantly from a general theoretical description of image quality that properly incorporates factors of acquisition, reconstruction, and tissue decomposition in DE tomography. This work reports a cascaded systems analysis model that includes the Poisson statistics of x rays (quantum noise), detector model (flat-panel detectors), anatomical background, image reconstruction (filtered backprojection), DE decomposition (weighted subtraction), and simple observer models to yield a task-based framework for DE technique optimization.

METHODS

The theoretical framework extends previous modeling of DE projection radiography and CBCT. Signal and noise transfer characteristics are propagated through physical and mathematical stages of image formation and reconstruction. Dual-energy decomposition was modeled according to weighted subtraction of low- and high-energy images to yield the 3D DE noise-power spectrum (NPS) and noise-equivalent quanta (NEQ), which, in combination with observer models and the imaging task, yields the dual-energy detectability index (d(')). Model calculations were validated with NPS and NEQ measurements from an experimental imaging bench simulating the geometry of a dedicated musculoskeletal extremities scanner. Imaging techniques, including kVp pair and dose allocation, were optimized using d(') as an objective function for three example imaging tasks: (1) kidney stone discrimination; (2) iodine vs bone in a uniform, soft-tissue background; and (3) soft tissue tumor detection on power-law anatomical background.

RESULTS

Theoretical calculations of DE NPS and NEQ demonstrated good agreement with experimental measurements over a broad range of imaging conditions. Optimization results suggest a lower fraction of total dose imparted by the low-energy acquisition, a finding consistent with previous literature. The selection of optimal kVp pair reveals the combined effect of both quantum noise and contrast in the kidney stone discrimination and soft-tissue tumor detection tasks, whereas the K-edge effect of iodine was the dominant factor in determining kVp pairs in the iodine vs bone task. The soft-tissue tumor task illustrated the benefit of dual-energy imaging in eliminating anatomical background noise and improving detectability beyond that achievable by single-energy scans.

CONCLUSIONS

This work established a task-based theoretical framework that is predictive of DE image quality. The model can be utilized in optimizing a broad range of parameters in image acquisition, reconstruction, and decomposition, providing a useful tool for maximizing DE-CBCT image quality and reducing dose.

Comparison between chest digital tomosynthesis and CT as a screening method to detect artificial pulmonary nodules: a phantom study

OBJECTIVES

The objective of this study was to evaluate the imaging capabilities of chest digital tomosynthesis (DT) as a screening method for the detection of artificial pulmonary nodules, and to compare its efficiency with that of CT.

METHODS

DT and CT were used to detect artificial pulmonary nodules (5 mm and 8 mm in diameter, ground-glass opacities) placed in a chest phantom. Using a three-dimensional filtered back-projection algorithm at acquisition angles of 8°, 20°, 30° and 40°, DT images of the desired layer thicknesses were reconstructed from the image data acquired during a single tomographic scan. Both standard and sharp CT reconstruction kernels were used, and the detectability index (DI) valves computed for both the DT scan acquisition angles and CT reconstruction kernel types were considered. For the observer study, we examined 50 samples of artificial pulmonary nodules using both DT and CT imaging. On the basis of evaluations made by five thoracic radiologists, a jackknife free-response receiver operating characteristic (JAFROC) study was performed to compare and assess the differences in detection accuracy between CT and DT imaging.

RESULTS

For each increased acquisition angle, DI obtained by DT imaging was similar to that obtained by CT imaging. The difference in the observer-averaged JAFROC figure of merit for the five readings was 0.0363 (95% confidence interval: -0.18, 0.26; F=0.101; p=0.75).

CONCLUSION

With the advantages of a decreased radiation dose and the practical accessibility of examination, DT may be a useful alternative to CT for the detection of artificial pulmonary nodules.

A dedicated cone-beam CT system for musculoskeletal extremities imaging: design, optimization, and initial performance characterization

PURPOSE

This paper reports on the design and initial imaging performance of a dedicated cone-beam CT (CBCT) system for musculoskeletal (MSK) extremities. The system complements conventional CT and MR and offers a variety of potential clinical and logistical advantages that are likely to be of benefit to diagnosis, treatment planning, and assessment of therapy response in MSK radiology, orthopaedic surgery, and rheumatology.

METHODS

The scanner design incorporated a host of clinical requirements (e.g., ability to scan the weight-bearing knee in a natural stance) and was guided by theoretical and experimental analysis of image quality and dose. Such criteria identified the following basic scanner components and system configuration: a flat-panel detector (FPD, Varian 3030+, 0.194 mm pixels); and a low-power, fixed anode x-ray source with 0.5 mm focal spot (SourceRay XRS-125-7K-P, 0.875 kW) mounted on a retractable C-arm allowing for two scanning orientations with the capability for side entry, viz. a standing configuration for imaging of weight-bearing lower extremities and a sitting configuration for imaging of tensioned upper extremity and unloaded lower extremity. Theoretical modeling employed cascaded systems analysis of modulation transfer function (MTF) and detective quantum efficiency (DQE) computed as a function of system geometry, kVp and filtration, dose, source power, etc. Physical experimentation utilized an imaging bench simulating the scanner geometry for verification of theoretical results and investigation of other factors, such as antiscatter grid selection and 3D image quality in phantom and cadaver, including qualitative comparison to conventional CT.

RESULTS

Theoretical modeling and benchtop experimentation confirmed the basic suitability of the FPD and x-ray source mentioned above. Clinical requirements combined with analysis of MTF and DQE yielded the following system geometry: a -55 cm source-to-detector distance; 1.3 magnification; a 20 cm diameter bore (20 x 20 x 20 cm3 field of view); total acquisition arc of -240 degrees. The system MTF declines to 50% at -1.3 mm(-1) and to 10% at -2.7 mm(-1), consistent with sub-millimeter spatial resolution. Analysis of DQE suggested a nominal technique of 90 kVp (+0.3 mm Cu added filtration) to provide high imaging performance from -500 projections at less than -0.5 kW power, implying -6.4 mGy (0.064 mSv) for low-dose protocols and -15 mGy (0.15 mSv) for high-quality protocols. The experimental studies show improved image uniformity and contrast-to-noise ratio (without increase in dose) through incorporation of a custom 10:1 GR antiscatter grid. Cadaver images demonstrate exquisite bone detail, visualization of articular morphology, and soft-tissue visibility comparable to diagnostic CT (10-20 HU contrast resolution).

CONCLUSIONS

The results indicate that the proposed system will deliver volumetric images of the extremities with soft-tissue contrast resolution comparable to diagnostic CT and improved spatial resolution at potentially reduced dose. Cascaded systems analysis provided a useful basis for system design and optimization without costly repeated experimentation. A combined process of design specification, image quality analysis, clinical feedback, and revision yielded a prototype that is now awaiting clinical pilot studies. Potential advantages of the proposed system include reduced space and cost, imaging of load-bearing extremities, and combined volumetric imaging with real-time fluoroscopy and digital radiography.

Task-based modeling and optimization of a cone-beam CT scanner for musculoskeletal imaging

PURPOSE

This work applies a cascaded systems model for cone-beam CT imaging performance to the design and optimization of a system for musculoskeletal extremity imaging. The model provides a quantitative guide to the selection of system geometry, source and detector components, acquisition techniques, and reconstruction parameters.

METHODS

The model is based on cascaded systems analysis of the 3D noise-power spectrum (NPS) and noise-equivalent quanta (NEQ) combined with factors of system geometry (magnification, focal spot size, and scatter-to-primary ratio) and anatomical background clutter. The model was extended to task-based analysis of detectability index (d') for tasks ranging in contrast and frequency content, and d' was computed as a function of system magnification, detector pixel size, focal spot size, kVp, dose, electronic noise, voxel size, and reconstruction filter to examine trade-offs and optima among such factors in multivariate analysis. The model was tested quantitatively versus the measured NPS and qualitatively in cadaver images as a function of kVp, dose, pixel size, and reconstruction filter under conditions corresponding to the proposed scanner.

RESULTS

The analysis quantified trade-offs among factors of spatial resolution, noise, and dose. System magnification (M) was a critical design parameter with strong effect on spatial resolution, dose, and x-ray scatter, and a fairly robust optimum was identified at M ∼ 1.3 for the imaging tasks considered. The results suggested kVp selection in the range of ∼65-90 kVp, the lower end (65 kVp) maximizing subject contrast and the upper end maximizing NEQ (90 kVp). The analysis quantified fairly intuitive results-e.g., ∼0.1-0.2 mm pixel size (and a sharp reconstruction filter) optimal for high-frequency tasks (bone detail) compared to ∼0.4 mm pixel size (and a smooth reconstruction filter) for low-frequency (soft-tissue) tasks. This result suggests a specific protocol for 1 × 1 (full-resolution) projection data acquisition followed by full-resolution reconstruction with a sharp filter for high-frequency tasks along with 2 × 2 binning reconstruction with a smooth filter for low-frequency tasks. The analysis guided selection of specific source and detector components implemented on the proposed scanner. The analysis also quantified the potential benefits and points of diminishing return in focal spot size, reduced electronic noise, finer detector pixels, and low-dose limits of detectability. Theoretical results agreed quantitatively with the measured NPS and qualitatively with evaluation of cadaver images by a musculoskeletal radiologist.

CONCLUSIONS

A fairly comprehensive model for 3D imaging performance in cone-beam CT combines factors of quantum noise, system geometry, anatomical background, and imaging task. The analysis provided a valuable, quantitative guide to design, optimization, and technique selection for a musculoskeletal extremities imaging system under development.

The effect of angular dose distribution on the detection of microcalcifications in digital breast tomosynthesis

PURPOSE

Substantial effort has been devoted to the clinical development of digital breast tomosynthesis (DBT). DBT is a three-dimensional (3D) x-ray imaging modality that reconstructs a number of thin image slices parallel to a stationary detector plane. Preliminary clinical studies have shown that the removal of overlapping breast tissue reduces image clutter and increases detectability of large, low contrast lesions. However, some studies, as well as anecdotal evidence, suggested decreased conspicuity of small, high contrast objects such as microcalcifications. Several investigators have proposed alternative imaging methods for improving microcalcification detection by delivering half of the total dose to the central view in addition to a separate DBT scan. Preliminary observer studies found possible improvement by either viewing the central projection alone or combining all views with a reconstruction algorithm.

METHODS

In this paper, we developed a generalized imaging theory based on a cascaded linear-system model for DBT to calculate the effect of variable angular dose distribution on the 3D modulation transfer function (MTF) and noise power spectrum (NPS). Using the ideal observer signal-to-noise ratio (SNR), d', as a figure-of-merit (FOM) for a signal embedded in a uniform background, we compared the detectability of objects with different sizes under different imaging conditions (e.g., angular dose distribution and reconstruction filters). Experimental investigation was conducted for three different angular dose schemes (ADS) using a Siemens Novation(TOMO) prototype unit.

RESULTS

Our results show excellent agreement between modeled and experimental measurements of 3D NPS with different angular dose distribution. The ideal observer detectability index for the detection of Gaussian objects with different angular dose distributions depends strongly on the applied reconstruction filter as well as the imaging task. For detection tasks of small calcifications with reconstruction filters used typically in a clinical setting, variable angular dose distribution with more dose delivered to the central views may lead to higher d' than a uniform angular dose distribution.

CONCLUSIONS

The conspicuity of the detection of small calcifications may be improved, under certain imaging conditions, by delivering higher dose toward the central views of a tomosynthesis scan, while also reducing the dose at peripheral angles to keep total administered radiation dose equivalent. The degree of improvement depends on the choice of reconstruction filters as well as the imaging task. The improvement is more substantial for high-frequency imaging tasks and when an aggressive slice-thickness (ST) filter is applied to reduced the high-frequency noise at peripheral angles.