Optimization of image acquisition techniques for dual-energy imaging of the chest

Correlation Between Contrast-Detail Analysis and Clinical Image Quality Assessment of Intrapulmonary Lesions in Dual-Energy Subtraction Chest Radiography Using the Two-Shot Method: A Phantom Study

RATIONALE AND OBJECTIVES

Dual-energy subtraction (DES) imaging constitutes a technique that has demonstrated efficacy in enhancing the detectability of pulmonary nodules on chest radiographs. However, a simple and quantitative methodology for evaluating the clinical image quality of DES images is currently lacking. The objective of this study was to investigate the applicability of contrast-detail (C-D) phantom analysis to the visual clinical image quality evaluation of chest DES images.

MATERIALS AND METHODS

We employed a custom-made phantom incorporating the C-D phantom and a multipurpose anthropomorphic adult chest phantom. Two phantom sizes were utilized to simulate standard- and large-bodied adult patients for each phantom. The custom-made phantom images were scored automatically using dedicated software, yielding an inverse image quality figure (IQFinv) value. The multipurpose anthropomorphic adult chest phantom was employed in a visual grading analysis (VGA) study that was conducted by two experienced radiologists and five radiological technologists. Each nodule placed in the chest phantom image was rated on a 4-point Likert scale.

RESULTS

A statistically significant correlation was observed between the VGA scores of the seven observers and the obtained IQFinv values.

CONCLUSION

The findings of this study suggest that DES image analysis of the C-D phantom possesses the potential to be utilized for the evaluation of clinical DES image quality based on chest lesion detectability.

Experimental optimization of single-exposure dual-energy angiography with photon-counting x-ray detectors

BACKGROUND

Photon-counting x-ray detectors may enable single-exposure dual-energy (DE) x-ray angiography.

PURPOSE

The purpose of this paper is to experimentally optimize the energy thresholds and tube voltage for single-exposure DE x-ray angiography.

METHODS

We optimized single-exposure DE x-ray angiography using the iodine signal-difference-to-noise ratio (SDNR) per root patient air kerma (κ) as a figure of merit. We measured the iodine SDNR by imaging an iodine stepwedge immersed in a water tank with a depth of 30 cm in the direction of x-ray propagation. The stepwedge was imaged using tube voltages ranging from 90 to 150 kV and a cadmium telluride (CdTe) x-ray detector with two energy bins and analog charge summing for charge sharing suppression. The energy threshold that separates the two energy bins was varied from approximately 35 keV to approximately 75% of the maximum energy of the x-ray beam. Curve fitting was used to determine the threshold that maximized SDNR / κ $\mathrm{SDNR}/\sqrt {\kappa }$ . The effect of scatter was determined from measurements of the scatter-to-primary ratios (SPRs) of the low-energy and high-energy images and a semi-empirical model of the relationship between SDNR and SPR. Using the optimal parameters, we imaged a phantom with vessel-simulating structures and background clutter.

RESULTS

The optimal energy thresholds increased monotonically from ∼50 to ∼85 keV over the range of tube voltages considered. For tube voltages greater than 90 kV, the optimal energy thresholds consistently allocated approximately two thirds of all detected primary photons to the low energy bin; this ratio was preserved without scatter. Consistent with prior modeling studies, SDNR / κ $\mathrm{SDNR}/\sqrt {\kappa }$ increased monotonically with tube voltage from 90 to 150 kV; SDNR / κ $\mathrm{SDNR}/\sqrt {\kappa }$ at 150 kV was approximately 38% higher than that at 90 kV for an iodine area density of ∼50 mg/cm² . Scatter reduced SDNR by approximately 25% for SPRs of ∼1 and 0.4 in low-energy and high-energy images, respectively.

CONCLUSIONS

Achieving optimal image quality in single-exposure DE angiography with photon-counting x-ray detectors will require high tube voltages (i.e., >130 kV) and, for thick patients, energy thresholds that allocate approximately two thirds of all primary photons to the low-energy image. Future work will compare the image quality of singe-exposure photon-counting and kV-switching approaches to DE x-ray angiography.

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.

Effect of high- and low-energy entrance surface dose allocation ratio for two-shot dual-energy subtraction imaging on low-contrast resolution

INTRODUCTION

Dual-energy subtraction (DES) imaging can obtain chest radiographs with high contrast between nodules and healthy lung tissue, and evaluating of chest radiography and evaluating exposure conditions is crucial to obtain a high-quality diagnostic image. This study aimed to investigate the effect of the dose allocation ratio of entrance surface dose (ESD) between high- and low-energy projection in low-contrast resolution of soft-tissue images for two-shot DES imaging in digital radiography using a contrast-detail phantom (CD phantom).

METHODS

A custom-made phantom mimicking a human chest that combined a CD phantom, polymethylmethacrylate square plate, and an aluminum plate (1-3 mm) was used. The tube voltage was 120 kVp (high-energy) and 60 kVp (low-energy). The ESD was changed from 0.1 to 0.5 mGy in 0.1 mGy increments. Dose allocation ratio of ESD between 120 kVp and 60 kVp projection was set at 1:1, 1:2, 1:3, and 2:1. Inverse image quality figure (IQF_inv) was calculated from the custom-made phantom images.

RESULTS

When the total ESD and aluminum thickness were constant, no significant difference in IQF_inv was observed under most conditions of varied dose allocation ratio. Similarly, when the total ESD and the dose allocation ratio were constant, there was no significant difference in IQF_inv based on the aluminum plate thickness.

CONCLUSION

Using IQF_inv to evaluate the quality of the two-shot DES image suggested that dose allocation ratio did not have a significant effect on low-contrast resolution of soft-tissue images.

IMPLICATIONS FOR PRACTICE

The present results provide useful information for determining exposure conditions for two-shot DES imaging.

Value of low-keV virtual monoenergetic plus dual-energy computed tomographic imaging for detection of acute pulmonary embolism

Objective

To compare diagnostic values between the 40 keV virtual monoenergetic plus (40 keV VMI+) dual source dual energy computed tomography (DSDECT) pulmonary angiography images and the standard mixed (90 and 150 kV) images for the detection of acute pulmonary embolism (PE).

Methods

Chest DSDECTs of 64 patients who were suspected of having acute PE were retrospectively reviewed by two independent reviewers. The assessments of acute PE of all patients on a per-location basis were compared between the 40 keV VMI+ and the standard mixed datasets (reference standard) with a two-week interval.

Results

This study consisted of 64 patients (33 women and 31 men; mean age, 60.2 years; range 18–90 years), with a total of 512 locations. The interobserver agreement (Kappa) for detection of acute PE using the 40 keV VMI+ images and the standard mixed CT images were 0.7478 and 0.8750 respectively. The area under receiver operating characteristics (AuROC) for diagnosis of acute PE using the 40 keV VMI+ was 0.882. Four locations (0.78%) revealed a false negative result. Hypodense filling defects were identified in twelve locations (1.95%) in the 40 keV VMI+ images but had been interpreted as a negative study in the standard mixed CT images. The repeated reviews revealed that each location contained a hypodense filling defect but was overlooked on the standard mixed CT images.

Conclusions

Low-energy VMI + DSDECT images have beneficial in improving the diagnostic value of acute PE in doubtful or disregarded standard mixed images.

Adaptive dual-energy algorithm based on pre-calibrated weighting factors for chest radiography

Objective. To develop a dual-energy (DE) algorithm with spatially varying weighting factors for material selection and noise suppression. Approach. Calibration step-phantoms, with overlapping slabs of solid water and bone with different thicknesses, were used to obtain the pre-calibrated material selection and noise reduction weighting factors. The Material selection weighting factors were calculated by finding a zero of contrast-to-noise-ratio (CNR) between regions with two overlapping materials and regions of only target material, while noise suppression weighting factors were determined by maximizing signal-to-noise ratio for overlapping regions. The pre-calibrated weighting factors were fitted with low and high energy radiograph of two Rando phantoms to create maps of material selection and noise suppression weighting factors, which used with DE algorithm and anti-correlated noise reduction (ACNR) algorithm to generate DE images. Three different implementations, including two different sizes of Rando phantoms and two different orientations (oblique and anterior-posterior), were investigated. Soft-tissue and bone only images of Rando phantoms were obtained with five combinations of DE algorithms and CNR, contrast, and noise values of selected regions of interest were compared to evaluate the performance of the novel method: simple log subtraction (SLS), SLS with uniform ACNR, adaptive DE (aDE), aDE with uniform ACNR, and aDE and adaptive ACNR (aACNR). Main results. Compared to SLS, the aDE algorithm demonstrated improved image quality in all three orientations. CNR increased with better contrast for both soft-tissue and bone images. Implementation of aACNR algorithm resulted in further reduction of image noise and improvements in CNR at the cost of contrast. However, aACNR algorithm showed better contrast compared to ACNR method. Significance. A novel DE algorithm was proposed, which showed improved material selection and noise suppression as compared to the conventional DE techniques and can be easily implemented in a clinical environment for real-time DE image generation.

Method of determining technique from weight and height to achieve targeted detector exposures in portable chest and abdominal digital radiography

This study presents a methodology to develop an X-ray technique chart for portable chest and abdomen imaging which utilizes patient data available in the modality worklist (MWL) to reliably achieve a predetermined exposure index (EI) at the detector for any patient size. The method assumes a correlation between the patients' tissue equivalent thickness and the square root of the ratio of the patient's weight to height. To assess variability in detector exposures, the EI statistics for 75 chest examinations and 99 abdominal portable X-ray images acquired with the new technique chart were compared to those from a single portable unit (chest: 3877 images; abdomen: 200 images) using a conventional technique chart with three patient sizes, and to a stationary radiography room utilizing automatic exposure control (AEC) (chest: 360 images; abdomen: 112 images). The results showed that when using the new technique chart on a group of portable units, the variability in EI was significantly reduced (p < 0.01) for both AP chest and AP abdomen images compared to the single portable using a standard technique chart with three patient sizes. The variability in EI for the images acquired with the new chart was comparable to the stationary X-ray room with an AEC system (p > 0.05). This method could be used to streamline the entire imaging chain by automatically selecting an X-ray technique based on patient demographic information contained in the MWL to provide higher quality examinations to clinicians by eliminating outliers. In addition, patient height and weight can be used to estimate the patients' tissue equivalent thickness.

The potential application of dual-energy subtraction radiography for COVID-19 pneumonia imaging

X-ray imaging plays a crucial role in the confirmation of COVID-19 pneumonia. Chest X-ray radiography and CT are two major imaging techniques that are currently adopted in the diagnosis of COVID-19 pneumonia. However, dual-energy subtraction radiography is hardly discussed as potential COVID-19 imaging application. More advanced X-ray radiography equipment often supports dual-energy subtraction X-ray radiography. Dual-energy subtraction radiography enables the calculation of pseudo-radiographs, in which bones are removed and only soft-tissues are highlighted. In this commentary, the author would like to draw the attention to the potential use of dual-energy subtraction X-ray radiography (i.e. soft-tissue pseudo-radiography) for the assessment and the longitudinal follow-up of COVID-19 pneumonia.

Optimization of a calibration phantom for quantitative radiography

OBJECTIVE

Dual energy radiography (DER) makes it possible to obtain separate images for soft-tissue and bony structures (tissue maps) based on the acquisition of two radiographs at different source peak-kilovoltage values. Current DER studies are based on the weighted subtraction method, which requires either manual tuning or the use of precomputed tables, or on decomposition methods, which make use of a calibration to model soft-tissue and bone components. In this study, we examined in depth the optimum method to perform this calibration.

METHODS

We used simulations to optimize the calibration protocol and evaluated the effect of the material and size of a calibration phantom composed of two wedges and its positioning in the system. Evaluated materials were water, PMMA and A-150 as soft-tissue equivalent, and Teflon, B-100 and aluminum as bone equivalent, with sizes from 5 to 30 cm. Each material combination was compared with an ideal phantom composed of soft tissue and bone. Our simulation results enabled us to propose four designs that were tested with the NOVA FA X-ray system with a realistic thorax phantom.

RESULTS

Calibration based on a very simple and inexpensive phantom with no strict requirements in its placement results in appropriate separation of the spine (a common focus in densitometry studies) and the identification of nodules as small as 6 mm, which have been reported to have a low rate of detection in radiography.

CONCLUSION

The proposed method is completely automatic, avoiding the need for a radiology technician with expert knowledge of the protocol, as is the case in densitometry exams. The method provides real mass thickness values, enabling quantitative planar studies instead of relative comparisons.

Adaptive noise reduction for dual-energy x-ray imaging based on spatial variations in beam attenuation

PURPOSE

The main goal of this work is to improve the previously proposed patient-specific pixel-based dual-energy (PP-DE) algorithm by developing an adaptive anti-correlated noise reduction (ACNR) method, resulting in reduced image noise.

METHODS

Theoretical models of contrast-to-noise (CNR) and signal-to-noise (SNR) ratio were developed as functions of weighting factors for DE bone ω _Bn or soft tissue ω _ST cancellation. These analytical expressions describe CNR and SNR properties of dual-energy (DE) images, obtained with both simple log subtraction (SLS) and ACNR algorithms, and allow for a direct comparison between experimental and theoretical results. The theoretical models demonstrate the importance of ACNR weighting factor (ω _A ) optimization leading to the maximization of the SNR of the final image. A step phantom was constructed, which consisted of overlapping slabs of solid water (0-30 cm) and bone-mimicking material (0-6 cm), resulting in a total of 7 × 7 regions. High-energy (HE) and low-energy (LE) images were acquired at 140 kVp and 60 kVp with a clinical ExacTrac imaging system. The CNR and SNR were obtained for the DE images as functions of ω _Bn,ST and noise reduction weighting factor ω _A for different combinations of thicknesses. Weighting factors for bone cancellation were optimized for each region of interest (ROI) by finding zeros of CNR function for DE images between soft tissue only and soft tissue plus bone regions (and vice versa for soft tissue cancellation). The weighting factor for the ACNR algorithm ω _A was then optimized by maximizing the SNR function for each ROI. HE and LE images for an anthropomorphic Rando phantom were obtained with the same acquisition parameters as for the step phantom. DE images for bone only and soft tissue only were obtained with three algorithms: SLS and PP-DE with conventional ACNR (uniform ω _A ), and PP-DE with adaptive ACNR (region-varying ω _A ). Weighting factor maps for PP-DE and adaptive ACNR methods were obtained for Rando phantom geometry (which was determined from its CT scans) by interpolation (or extrapolation) of weighting factors for the step phantom. CNR values were calculated for different regions.

RESULTS

The CNR and SNR characteristics as functions of material cancellation and noise reduction weighting factors were obtained from theoretical models and experimental data from the step phantom. This showed a good qualitative validation of the models. For the ANCR algorithm, both the theory and experiment demonstrated that the material cancellation weighting factors (ω _Bn,ST ) can be optimized independently of the noise cancellation weighting factors (ω _A ), which can be optimized by maximizing SNR. For each ROI (with different overlapping bone and soft tissue thicknesses) the weighting factors ω _Bn,ST were determined as well as corresponding optimal weighting factors ω _A for noise reduction. For the Rando phantom, CNR values for regions representing different anatomical structures (ribs, spine, and tumor) were evaluated. It was shown that the proposed adaptive ACNR further improves image quality, compared to the conventional ACNR algorithm. The improvement is maximized for regions with bones (ribs or spine), where the largest attenuation is observed.

CONCLUSION

The ACNR weighting factors are dependent on the material thicknesses due to varying beam attenuation leading to different levels of quantum noise. This was shown with the derived theoretical expressions of the CNR and SNR functions and was validated by experimental data. The adaptive ANCR DE algorithm was developed, which allows for an increase in image quality by spatially varying weighting factors for noise reduction. This algorithm complements the previously developed PP-DE algorithm to obtain better quality DE images.

Spectral Computed Tomography: Fundamental Principles and Recent Developments

CT is a diagnostic tool with many clinical applications. The CT voxel intensity is related to the magnitude of X-ray attenuation, which is not unique to a given material. Substances with different chemical compositions can be represented by similar voxel intensities, making the classification of different tissue types challenging. Compared to the conventional single-energy CT, spectral CT is an emerging technology offering superior material differentiation, which is achieved using the energy dependence of X-ray attenuation in any material. A specific form of spectral CT is dual-energy imaging, in which an additional X-ray attenuation measurement is obtained at a second X-ray energy. Dual-energy CT has been implemented in clinical settings with great success. This paper reviews the theoretical basis and practical implementation of spectral/dual-energy CT.

Luminescence Efficiency of Cadmium Tungstate (CdWO4) Single Crystal for Medical Imaging Applications

Background: In this study, the light output of a cadmium tungstate (CdWO4) single crystal was measured under various X-ray radiographic energies. Methods: A CdWO4 single crystal (10 × 10 × 10 mm3) was exposed to X-rays in the 50–130 kVp range. Measurements were evaluated against published data for single crystals of equal dimensions (CaF2:Eu and Lu3Al5O12:Ce). Since the crystal was examined for application in medical imaging detectors, the emitted optical spectrum was classified with respect to the spectral compatibility of numerous commercial optical sensors. Results: The luminescence efficiency (LE) was found to constantly increase with X-ray energy and was higher than that of CaF2:Eu for energies above 90 kVp. However, the efficiency of the previously published Lu3Al5O12:Ce was found to be constantly higher than that of CdWO4. The light emitted from CdWO4 can be optimally detected by certain charge-coupled devices (CCDs), amorphous silicon photodiodes, and photocathodes. Conclusions: The high density (7.9 g/cm3) of CdWO4 and the luminescence signal of this material make it suitable for medical imaging (such as dual energy), high-energy physics or for applications of scintillators in harsh environments.

Technical Principles of Dual-Energy Cone Beam Computed Tomography and Clinical Applications for Radiation Therapy

PURPOSE

Medical imaging is an indispensable tool in radiotherapy for dose planning, image guidance and treatment monitoring. Cone beam CT (CBCT) is a low dose imaging technique with high spatial resolution capability as a direct by-product of using flat-panel detectors. However, certain issues such as x-ray scatter, beam hardening and other artifacts limit its utility to the verification of patient positioning using image-guided radiotherapy.

METHODS AND MATERIALS

Dual-energy (DE)-CBCT has recently demonstrated promise as an improved tool for tumor visualization in benchtop applications. It has the potential to improve soft-tissue contrast and reduce artifacts caused by beam hardening and metal. In this review, the practical aspects of developing a DE-CBCT based clinical and technical workflow are presented based on existing DE-CBCT literature and concepts adapted from the well-established library of work in DE-CT. Furthermore, the potential applications of DE-CBCT on its future role in radiotherapy are discussed.

RESULTS AND CONCLUSIONS

Based on current literature and an investigation of future applications, there is a clear potential for DE-CBCT technologies to be incorporated into radiotherapy. The applications of DE-CBCT include (but are not limited to): adaptive radiotherapy, brachytherapy, proton therapy, radiomics and theranostics.

Patient-specific pixel-based weighting factor dual-energy x-ray imaging system using a priori CT data

PURPOSE

The purpose of this study was to develop a novel patient-specific pixel-based weighting factor dual-energy (PP-DE) algorithm to effectively suppress bone throughout the image and overcome the limitation of the conventional DE algorithm with constant weighting factor which is restricted to regions with uniform patient thickness. Additionally, to derive theoretical expressions to describe the dependence of the weighting factors on several imaging parameters and validate them with measurement.

METHODS

A step phantom was constructed consisting of slabs of solid water and bone materials. Thicknesses of bone ranged [0-6] cm in one direction and solid water [5-30] cm in the other direction. Projection images at 60 and 140 kVp were acquired using a clinical imaging system. Optimal weighting factors were found by iteratively varying it in the range [0-1.4], where bone and soft-tissue contrast-to-noise ratio (CNR) reached zero. Bone and soft-tissue digitally reconstructed thicknesses were created using computed tomography (CT) images of a Rando phantom and ray tracing techniques. A weighting factor image (ω) was calculated using digitally reconstructed thicknesses (DRTs) and precalculated weighting factors from the step phantom. This ω image was then used to generate a PP-DE image. The PP-DE image was compared to the conventional DE image which uses a constant weighting factor throughout the image. The effect of the misaligned ω image on PP-DE images was investigated by acquiring LE and HE images at various shifts of Rando phantom. A rigid registration was used based on mutual information algorithm in Matlab. The signal-to-noise ratios (SNR) were calculated in the step phantom for the PP-DE image and compared to that of conventional DE technique. Analytical expressions for theoretical weighting factors were derived which included various effects such as beam hardening, scatter, and detector response. The analytical expressions were simulated in Spektr3.0 for different bone and solid water thicknesses as per the step phantom. A tray of steel pins was constructed and used with the step phantom to remove the scattered radiation. The simulated theoretical weighting factors were validated by comparing to those from the step phantom measurement.

RESULTS

Optimal weighting factor values for the step phantom varied from 0.633 to 1.372 depending on region thickness. Thicker regions required larger weighting factors for bone cancellation. The PP-DE image of the Rando phantom favorably cancelled both ribs and spine, whereas in the conventional DE image, only one could be cancelled at a time. The misaligned ω image was less effective in removing all bones indicating the importance of alignment as part of the PP-DE algorithm implementation. The SNRs for the PP-DE image was larger than those of the conventional DE images for regions which required smaller weighting factors for bone suppression. Comparisons of measured and simulated weighting factors demonstrated a 3% agreement for all bone overlapped regions except for the thickest region with 30 cm of solid water overlapped with 6 cm bone where the signal was lost due to excess attenuation.

CONCLUSIONS

A novel PP-DE algorithm was developed which can create higher quality DE images with enhanced bone cancellation and improved noise characteristics compared to conventional DE technique. In addition, theoretical weighting factor expressions were derived and validated against measurement.

Model evaluation of rapid 4-dimensional lung tomosynthesis

Purpose

This is an investigation of a lung motion digital tomosynthesis (DTS) model using combined stationary detector and stationary cold cathode x-ray sources at projection acquisition rates that exceed the present norms. The intent is to reduce anatomical uncertainties from artifacts inherent in thoracic 4-dimensional computed tomography (CT).

Methods and materials

Parameters necessary to perform rapid lung 4-dimensional DTS were studied using a conventional radiographic system with linear motion of the x-ray source and a simple hypothetical hardware performance model. Hypothetical rapid imaging parameters of sweep duration, projections per second, pulse duration, and tube current (mA) were derived on the basis of 0.5 mm and 1 mm motion captures per phase, 10 and 15 breaths per minute (bpm), 10 to 40 mm breathing amplitude, and 2 signal-to-noise ratio (SNR) levels. Anterior-posterior and lateral projection images of a normal size anthropomorphic thorax phantom with iodine contrast inserts were collected and reconstructed with an algebraic algorithm to study the effects of reduced x-ray output associated with field emission cold cathodes composed of carbon nanotubes or metal Spindt-type. Radiographic projections were collected at 3 SNR levels that were set at standard clinical DTS milliampere-seconds (mAs) and reduced corresponding to 50% and 25% standard DTS mAs to simulate a reduced x-ray output.

Results

The DTS SNR of the inserts was superior in all reconstructions at clinical mAs versus automatic exposure-control radiographs and superior in 3 of 4 at the 50% and 25% mAs levels. The most demanding performance parameters corresponding to 40 mm amplitude, 15 bpm, 0.5 mm motion capture limit, and 61 projections were sweep duration (10.4 msec), projection rate (5862 projections per second), pulse duration (0.161 msec), current 189 mA anterior-posterior, and 653 mA lateral.

Conclusions

Feasibility depends on the output performance of stationary cold cathode hardware being developed for DTS. Present image receptor technology can accommodate frame acquisition rates.

Evaluation of a template-based algorithm for markerless lung tumour localization on single- and dual-energy kilovoltage images

OBJECTIVE

To evaluate a template-based matching algorithm on single-energy (SE) and dual-energy (DE) radiographs for markerless localization of lung tumours.

METHODS

A total of 74 images from 17 patients with Stages IA-IV lung cancer were considered. At the time of radiotherapy treatment, gated end-expiration SE radiographs were obtained at 60 and 120 kVp at different gantry angles (33° anterior and 41° oblique), from which soft-tissue-enhanced DE images were created. A template-based matching algorithm was used to localize individual tumours on both SE and DE radiographs. Tumour centroid co-ordinates obtained from the template-matching software on both SE and DE images were compared with co-ordinates defined by physicians.

RESULTS

The template-based matching algorithm was able to successfully localize the gross tumor volume within 5 mm on 70% (52/74) of the SE images vs 91% (66/74) of the DE images (p < 0.01). The mean vector differences between the co-ordinates of the template matched by the algorithm and the co-ordinates of the physician-defined ground truth were 3.2 ± 2.8 mm for SE images vs 2.3 ± 1.7 mm for DE images (p = 0.03).

CONCLUSION

Template-based matching on DE images was more accurate and precise than using SE images. Advances in knowledge: This represents, to the authors' knowledge, the largest study evaluating template matching on clinical SE and DE images, considering not only anterior gantry angles but also oblique angles, suggesting a novel lung tumour matching technique using DE subtraction that is reliable, accurate and precise.

Using dual-energy x-ray imaging to enhance automated lung tumor tracking during real-time adaptive radiotherapy

PURPOSE

Real-time, markerless localization of lung tumors with kV imaging is often inhibited by ribs obscuring the tumor and poor soft-tissue contrast. This study investigates the use of dual-energy imaging, which can generate radiographs with reduced bone visibility, to enhance automated lung tumor tracking for real-time adaptive radiotherapy.

METHODS

kV images of an anthropomorphic breathing chest phantom were experimentally acquired and radiographs of actual lung cancer patients were Monte-Carlo-simulated at three imaging settings: low-energy (70 kVp, 1.5 mAs), high-energy (140 kVp, 2.5 mAs, 1 mm additional tin filtration), and clinical (120 kVp, 0.25 mAs). Regular dual-energy images were calculated by weighted logarithmic subtraction of high- and low-energy images and filter-free dual-energy images were generated from clinical and low-energy radiographs. The weighting factor to calculate the dual-energy images was determined by means of a novel objective score. The usefulness of dual-energy imaging for real-time tracking with an automated template matching algorithm was investigated.

RESULTS

Regular dual-energy imaging was able to increase tracking accuracy in left-right images of the anthropomorphic phantom as well as in 7 out of 24 investigated patient cases. Tracking accuracy remained comparable in three cases and decreased in five cases. Filter-free dual-energy imaging was only able to increase accuracy in 2 out of 24 cases. In four cases no change in accuracy was observed and tracking accuracy worsened in nine cases. In 9 out of 24 cases, it was not possible to define a tracking template due to poor soft-tissue contrast regardless of input images. The mean localization errors using clinical, regular dual-energy, and filter-free dual-energy radiographs were 3.85, 3.32, and 5.24 mm, respectively. Tracking success was dependent on tumor position, tumor size, imaging beam angle, and patient size.

CONCLUSIONS

This study has highlighted the influence of patient anatomy on the success rate of real-time markerless tumor tracking using dual-energy imaging. Additionally, the importance of the spectral separation of the imaging beams used to generate the dual-energy images has been shown.

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.

Dual-energy cone-beam CT with a flat-panel detector: effect of reconstruction algorithm on material classification

PURPOSE

Cone-beam CT (CBCT) with a flat-panel detector (FPD) is finding application in areas such as breast and musculoskeletal imaging, where dual-energy (DE) capabilities offer potential benefit. The authors investigate the accuracy of material classification in DE CBCT using filtered backprojection (FBP) and penalized likelihood (PL) reconstruction and optimize contrast-enhanced DE CBCT of the joints as a function of dose, material concentration, and detail size.

METHODS

Phantoms consisting of a 15 cm diameter water cylinder with solid calcium inserts (50-200 mg/ml, 3-28.4 mm diameter) and solid iodine inserts (2-10 mg/ml, 3-28.4 mm diameter), as well as a cadaveric knee with intra-articular injection of iodine were imaged on a CBCT bench with a Varian 4343 FPD. The low energy (LE) beam was 70 kVp (+0.2 mm Cu), and the high energy (HE) beam was 120 kVp (+0.2 mm Cu, +0.5 mm Ag). Total dose (LE+HE) was varied from 3.1 to 15.6 mGy with equal dose allocation. Image-based DE classification involved a nearest distance classifier in the space of LE versus HE attenuation values. Recognizing the differences in noise between LE and HE beams, the LE and HE data were differentially filtered (in FBP) or regularized (in PL). Both a quadratic (PLQ) and a total-variation penalty (PLTV) were investigated for PL. The performance of DE CBCT material discrimination was quantified in terms of voxelwise specificity, sensitivity, and accuracy.

RESULTS

Noise in the HE image was primarily responsible for classification errors within the contrast inserts, whereas noise in the LE image mainly influenced classification in the surrounding water. For inserts of diameter 28.4 mm, DE CBCT reconstructions were optimized to maximize the total combined accuracy across the range of calcium and iodine concentrations, yielding values of ∼ 88% for FBP and PLQ, and ∼ 95% for PLTV at 3.1 mGy total dose, increasing to ∼ 95% for FBP and PLQ, and ∼ 98% for PLTV at 15.6 mGy total dose. For a fixed iodine concentration of 5 mg/ml and reconstructions maximizing overall accuracy across the range of insert diameters, the minimum diameter classified with accuracy >80% was ∼ 15 mm for FBP and PLQ and ∼ 10 mm for PLTV, improving to ∼ 7 mm for FBP and PLQ and ∼ 3 mm for PLTV at 15.6 mGy. The results indicate similar performance for FBP and PLQ and showed improved classification accuracy with edge-preserving PLTV. A slight preference for increased smoothing of the HE data was found. DE CBCT discrimination of iodine and bone in the knee was demonstrated with FBP and PLTV at 6.2 mGy total dose.

CONCLUSIONS

For iodine concentrations >5 mg/ml and detail size ∼ 20 mm, material classification accuracy of >90% was achieved in DE CBCT with both FBP and PL at total doses <10 mGy. Optimal performance was attained by selection of reconstruction parameters based on the differences in noise between HE and LE data, typically favoring stronger smoothing of the HE data, and by using penalties matched to the imaging task (e.g., edge-preserving PLTV in areas of uniform enhancement).

Optimization of dual-energy subtraction chest radiography by use of a direct-conversion flat-panel detector system

We aimed to optimize the exposure conditions in the acquisition of soft-tissue images using dual-energy subtraction chest radiography with a direct-conversion flat-panel detector system. Two separate chest images were acquired at high- and low-energy exposures with standard or thick chest phantoms. The high-energy exposure was fixed at 120 kVp with the use of an auto-exposure control technique. For the low-energy exposure, the tube voltages and entrance surface doses ranged 40-80 kVp and 20-100 % of the dose required for high-energy exposure, respectively. Further, a repetitive processing algorithm was used for reduction of the image noise generated by the subtraction process. Seven radiology technicians ranked soft-tissue images, and these results were analyzed using the normalized-rank method. Images acquired at 60 kVp were of acceptable quality regardless of the entrance surface dose and phantom size. Using a repetitive processing algorithm, the minimum acceptable doses were reduced from 75 to 40 % for the standard phantom and to 50 % for the thick phantom. We determined that the optimum low-energy exposure was 60 kVp at 50 % of the dose required for the high-energy exposure. This allowed the simultaneous acquisition of standard radiographs and soft-tissue images at 1.5 times the dose required for a standard radiograph, which is significantly lower than the values reported previously.

Prospective evaluation of dual-energy imaging in patients undergoing image guided radiation therapy for lung cancer: initial clinical results

PURPOSE

A prospective feasibility study was conducted to investigate the utility of dual-energy (DE) imaging compared to conventional x-ray imaging for patients undergoing kV-based image guided radiation therapy (IGRT) for lung cancer.

METHODS AND MATERIALS

An institutional review board-approved feasibility study enrolled patients with lung cancer undergoing IGRT and was initiated in September 2011. During daily setup, 2 sequential respiration-gated x-ray images were obtained using an on-board imager. Imaging was composed of 1 standard x-ray image at 120 kVp (1 mAs) and a second image obtained at 60 kVp (4 mAs). Weighted logarithmic subtraction of the 2 images was performed offline to create a soft tissue-selective DE image. Conventional and DE images were evaluated by measuring relative contrast and contrast-to-noise ratios (CNR) and also by comparing spatial localization, using both approaches. Imaging dose was assessed using a calibrated ion chamber.

RESULTS

To date, 10 patients with stage IA to IIIA lung cancer were enrolled and 57 DE images were analyzed. DE subtraction resulted in complete suppression of overlying bone in all 57 DE images, with an average improvement in relative contrast of 4.7 ± 3.3 over that of 120 kVp x-ray images (P<.0002). The improvement in relative contrast with DE imaging was seen for both smaller (gross tumor volume [GTV] ≤5 cc) and larger tumors (GTV >5 cc), with average relative contrast improvement ratios of 3.4 ± 4.1 and 5.4 ± 3.6, respectively. Moreover, the GTV was reliably localized in 95% of the DE images versus 74% of the single energy (SE images, (P=.004). Mean skin dose per DE image set was 0.44 ± 0.03 mGy versus 0.43 ± 0.03 mGy, using conventional kV imaging parameters.

CONCLUSIONS

Initial results of this feasibility study suggest that DE thoracic imaging may enhance tumor localization in lung cancer patients receiving kV-based IGRT without increasing imaging dose.

Dual energy imaging using a clinical on-board imaging system

Dual energy (DE) imaging consists of obtaining kilovoltage (kV) x-ray images at two different diagnostic energies and performing a weighted subtraction of these images. A third image is then produced that highlights soft tissue. DE imaging has been used by radiologists to aid in the detection of lung malignancies. However, it has not been used clinically in radiotherapy. The goal of this study is to assess the feasibility of performing DE imaging using a commercial on-board imaging system. Both a simple and an anthropomorphic phantom were constructed for this analysis. Planar kV images of the phantoms were obtained using varied imaging energies and mAs. Software was written to perform DE subtraction using empirically determined weighting factors. Tumor detectability was assessed quantitatively using the signal-difference-to-noise ratio (SDNR). Overall DE subtraction suppressed high density objects in both phantoms. The optimal imaging technique, providing the largest SDNR with a dose less than our reference technique was 140 kVp, 1.0 mAs and 60 kVp, 3.2 mAs. Based on this analysis, DE subtraction imaging is feasible using a commercial on-board imaging system and may improve the visualization of tumors in lung cancer patients undergoing image-guided radiotherapy.

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.

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.

Imaging of nanoparticles with dual-energy computed tomography

A simulation study was performed to determine the feasibility and performance of imaging nanoparticles as contrast agents in dual-energy computed tomography. An analytical simulation model was used to model the relevant signal-to-noise ratio (SNR) in dual-energy imaging for the specific case of a three-material patient phantom consisting of water, calcium hydroxyapatite and contrast agent. Elemental gold and iodine were both considered as contrast agents. Simulations were performed for a range of monoenergetic (20-150 keV) and polyenergetic (20-150 kVp) beam spectra. A reference configuration was defined with beam energies of 80 and 140 kVp to match current clinical practice. The effect of adding a silver filter to the high-energy beam was also studied. A figure of merit (FOM), which normalized the dual-energy SNR to the square root of the patient integral dose, was calculated for all cases. The units of the FOM were keV(-1/2). A simple Rose model of detectability was used to estimate the minimum concentration of either elements needed to be detected (SNR > 5). For monoenergetic beams, the peak FOM of gold was 6.4 × 10(-6) keV(-1/2), while the peak FOM of iodine was 3.1 × 10(-6) keV(-1/2), a factor of approximately 2 greater for gold. For polyenergetic spectra, at the reference energies of 80 and 140 kVp, the FOM for gold and iodine was 1.65 × 10(-6) and 5.0 × 10(-7) keV(-1/2), respectively, a factor of approximately 3.3 greater. Also at these energies, the minimum detectable concentration of gold was estimated to be 58.5 mg mL(-1), while iodine was estimated to be 117.5 mg mL(-1). The results suggest that the imaging of a gold nanoparticle contrast agent is well suited to current conditions used in clinical imaging. The addition of a silver filter of 800 µm further increased the image quality of the gold signal by approximately 50% for the same absorbed dose to the patient.

Dual-source dual-energy CT with additional tin filtration: Dose and image quality evaluation in phantoms and in vivo

OBJECTIVE

The objective of this study was to investigate the effect on radiation dose and image quality of the use of additional spectral filtration for dual-energy CT using dual-source CT (DSCT).

MATERIALS AND METHODS

A commercial DSCT scanner was modified by adding tin filtration to the high-kV tube, and radiation output and noise were measured in water phantoms. Dose values for equivalent image noise were compared between the dual-energy mode with and without tin filtration and the single-energy mode. To evaluate dual-energy CT material discrimination, the material-specific dual-energy ratio for calcium and that for iodine were determined using images of anthropomorphic phantoms. Data were additionally acquired from imaging a 38-kg pig and an 87-kg pig, and the noise of the linearly mixed images and virtual noncontrast images was compared between dual-energy modes. Finally, abdominal dual-energy CT images of two patients of similar sizes undergoing clinically indicated CT were compared.

RESULTS

Adding tin filtration to the high-kV tube improved the dual-energy contrast between iodine and calcium as much as 290%. Data from our animal study showed that tin filtration had no effect on noise in the dual-energy CT mixed images but decreased noise by as much as 30% in the virtual noncontrast images. Virtual noncontrast images of patients acquired using 100 and 140 kV with added tin filtration had improved image quality relative to those generated using 80 and 140 kV without tin filtration.

CONCLUSION

Tin filtration of the high-kV tube of a DSCT scanner increases the ability of dual-energy CT to discriminate between calcium and iodine without increasing dose relative to single-energy CT. Furthermore, the use of 100- and 140-kV tube potentials allows improved dual-energy CT imaging of large patients.

Diagnostic performance of a prototype dual-energy chest imaging system ROC analysis

RATIONALE AND OBJECTIVES

To assess the performance of an experimental prototype dual-energy (DE) chest imaging system in comparison to digital radiography (DR) in detection and characterization of lung lesions using receiver-operating characteristic (ROC) tests.

MATERIALS AND METHODS

A cohort of 129 patients (80 M, 49 F; mean age, 64.8 years) was drawn from a trial of patients referred for percutaneous biopsy of a lung lesion. DR and DE images were acquired of each patient (posteroanterior view) before biopsy using a prototype system developed in our laboratory. The system incorporated a flat-panel detector and previously reported imaging techniques optimized such that the total dose for the DE image was equivalent to that of a DR acquisition. Each DE image was decomposed to three components (soft-tissue, bone, and composite "equivalent radiograph") by log subtraction with optimized noise reduction techniques. ROC tests were performed to evaluate the diagnostic performance of DR imaging in comparison to DE for nodule detection, with 258 left/right "half-chest" images derived from the 129 cases to give a roughly equal number of disease and normal cases. Five chest radiologists scored 258 half-chest DE and 258 half-chest DR (516 in total) images on a 5-point scale, and results (including ROC and area under the curve [AUC]) were analyzed using the ROCkit toolkit. Statistical significance in the observed differences was evaluated in terms of P values determined by a z test. Performance was analyzed for all cases pooled (258 DE vs. 258 DR images) and by retrospective stratification of the data according to nodule size, density, gender, lung region, and chest thickness.

RESULTS

For results pooled over the entire cohort, there was no significant difference in ROC performance between DE and DR (AUC(DE) = 0.795 AUC(DR) = 0.789; P = .696). This finding is believed to be due to a large portion of lesions that were fairly conspicuous in either modality. In retrospective analysis of subgroups, a significant advantage was measured for DE imaging of small nodules (<1 cm diameter; AUC(DE) = 0.778; AUC(DR) = 0.706; P = .056), for nodules located in the right upper lobe (AUC(DE) = 0.836; AUC(DR) = 0.779; P = .003), and nodules located in right lower lobe (AUC(DE) = 0.804; AUC(DR) = 0.752; P = .054). DE imaging provided a clinically significant differential diagnosis in approximately one third of patients (49/158) (ie, disease cases in which the lesion was correctly identified in DE [(ROC rating > or =3], but missed in DR [ROC rating < or =2]). DE imaging also appeared to provide more definitive diagnosis (ie, a greater proportion of ROC ratings = 5 and 1 for identification of disease and normal cases, respectively), which presumably translates to increased confidence and a steeper ROC curve (even if the AUC are the same).

CONCLUSIONS

DE imaging at dose equivalent to DR exhibited similar overall ROC performance to DR, although the radiologists noted qualitatively improved visualization (eg, improved characterization of lesion margins, visibility of calcifications and rib fractures). DE imaging demonstrated significant improvement in diagnostic performance for specific subgroups, including subcentimeter lung lesions and lesions in the right upper lobe, each of which is a potentially important factor in detecting early-stage malignancy.

Improved dual-energy material discrimination for dual-source CT by means of additional spectral filtration

The use of additional spectral filtration for dual-energy (DE) imaging using a dual-source CT (DSCT) system was investigated and its effect on the material-specific DE(ratio) was evaluated for several clinically relevant materials. The x-ray spectra, data acquisition, and reconstruction processes for a DSCT system (Siemens Definition) were simulated using information provided by the system manufacturer, resulting in virtual DE images. The factory-installed filtration for the 80 kV spectrum was left unchanged to avoid any further reductions in tube output, and only the filtration for the high-energy spectrum was modified. Only practical single-element filter materials within the atomic number range of 40 < or = Z < or = 83 were evaluated, with the aim of maximizing the separation between the two spectra, while maintaining similar noise levels for high- and low-energy images acquired at the same tube current. The differences between mean energies and the ratio of the 140 and 80 kV detector signals, each integrated below 80 keV, were evaluated. The simulations were performed for three attenuation scenarios: Head, body, and large body. The large body scenario was evaluated for the DE acquisition mode using the 100 and 140 kV spectra. The DE(ratio) for calcium hydroxyapatite (simulating bone or calcifications), iodine, and iron were determined for CT images simulated using the modified and factory-installed filtration. Several filter materials were found to perform well at proper thicknesses, with tin being a good practical choice. When image noise was matched between the low- and high-energy images, the spectral difference in mean absorbed energy using tin was increased from 25.7 to 42.7 keV (head), from 28.6 to 44.1 keV (body), and from 20.2 to 30.2 keV (large body). The overlap of the signal spectra for energies below 80 keV was reduced from 78% to 31% (head), from 93% to 27% (body), and from 106% to 79% (large body). The DE(ratio) for the body attenuation scenario increased from 1.45 to 1.91 (calcium), from 1.84 to 3.39 (iodine), and from 1.73 to 2.93 (iron) with the additional tin filtration compared to the factory filtration. This use of additional filtration for one of the x-ray tubes used in dual-source DECT dramatically increased the difference between material-specific DE ratios, e.g., from 0.39 to 1.48 for calcium and iodine or from 0.28 to 1.02 for calcium and iron. Because the ability to discriminate between different materials in DE imaging depends primarily on the differences in DE ratios, this increase is expected to improve the performance of any material-specific DECT imaging task. Furthermore, for the large patient size and in conjunction with a 100/140 kV acquisition, the use of additional filtration decreased noise in the low-energy images and increased contrast in the DE image relative to that obtained with 80/140 kV and no additional filtration.

Multiscale deformable registration for dual-energy x-ray imaging

Dual-energy (DE) imaging of the chest improves the conspicuity of subtle lung nodules through the removal of overlying anatomical noise. Recent work has shown double-shot DE imaging (i.e., successive acquisition of low- and high-energy projections) to provide detective quantum efficiency, spectral separation (and therefore contrast), and radiation dose superior to single-shot DE imaging configurations (e.g., with a CR cassette). However, the temporal separation between high-energy (HE) and low-energy (LE) image acquisition can result in motion artifacts in the DE images, reducing image quality and diminishing diagnostic performance. This has motivated the development of a deformable registration technique that aligns the HE image onto the LE image before DE decomposition. The algorithm reported here operates in multiple passes at progressively smaller scales and increasing resolution. The first pass addresses large-scale motion by means of mutual information optimization, while successive passes (2-4) correct misregistration at finer scales by means of normalized cross correlation. Evaluation of registration performance in 129 patients imaged using an experimental DE imaging prototype demonstrated a statistically significant improvement in image alignment. Specific to the cardiac region, the registration algorithm was found to outperform a simple cardiac-gating system designed to trigger both HE and LE exposures during diastole. Modulation transfer function (MTF) analysis reveals additional advantages in DE image quality in terms of noise reduction and edge enhancement. This algorithm could offer an important tool in enhancing DE image quality and potentially improving diagnostic performance.

Development of a high-performance dual-energy chest imaging system: initial investigation of diagnostic performance

RATIONALE AND OBJECTIVES

The aim of this study was to assess the performance of a newly developed dual-energy (DE) chest radiographic system in comparison to digital radiographic (DR) imaging in the detection and characterization of lung nodules.

MATERIALS AND METHODS

An experimental prototype was developed for high-performance DE chest imaging, with total dose equivalent to a single posterior-anterior DR image. Projections at low and high peak kilovoltage were used to decompose DE soft tissue and bone images. A cohort of 55 patients (31 men, 24 women; mean age, 65.6 years) was drawn from an ongoing trial involving patients referred for percutaneous computed tomography-guided biopsy of suspicious lung nodules. DE and DR images were acquired of each patient prior to biopsy. Image quality was assessed by means of human observer tests involving five radiologists independently rating the detection and characterization of lung nodules on a nine-point scale. Results were analyzed in terms of the fraction of cases at or above a given rating, and statistical significance was evaluated using Wilcoxon's signed-rank test. Performance was analyzed for all cases pooled as well as by stratification of nodule size, density, lung region, and chest thickness.

RESULTS

The studies demonstrated a significant performance advantage for DE imaging compared to DR imaging (P < .001) in the detection and characterization of lung nodules. DE imaging improved the detection of both small and large nodules and exhibited the most significant improvement in regions of the upper lobes, where overlying anatomic noise (ribs and clavicles) are believed to reduce nodule conspicuity on DR imaging.

CONCLUSIONS

DE imaging outperformed DR imaging overall, particularly in the detection of small, solid nodules. DE imaging also performed better in regions dominated by anatomic noise, such as the lung apices. The potential for improved nodule detection and characterization at radiation doses equivalent to DR imaging is encouraging and could augment the broader use of DE imaging. Future studies will extend the initial cohort and rating scale tests to a larger cohort evaluated by receiver-operating characteristic analysis and will evaluate DE imaging in comparison and as an adjuvant to low-dose computed tomography.

Comparison of model and human observer performance for detection and discrimination tasks using dual-energy x-ray images

Model observer performance, computed theoretically using cascaded systems analysis (CSA), was compared to the performance of human observers in detection and discrimination tasks. Dual-energy (DE) imaging provided a wide range of acquisition and decomposition parameters for which observer performance could be predicted and measured. This work combined previously derived observer models (e.g., Fisher-Hotelling and non-prewhitening) with CSA modeling of the DE image noise-equivalent quanta (NEQ) and imaging task (e.g., sphere detection, shape discrimination, and texture discrimination) to yield theoretical predictions of detectability index (d') and area under the receiver operating characteristic (Az). Theoretical predictions were compared to human observer performance assessed using 9-alternative forced-choice tests to yield measurement of Az as a function of DE image acquisition parameters (viz., allocation of dose between the low- and high-energy images) and decomposition technique [viz., three DE image decomposition algorithms: standard log subtraction (SLS), simple-smoothing of the high-energy image (SSH), and anti-correlated noise reduction (ACNR)]. Results showed good agreement between theory and measurements over a broad range of imaging conditions. The incorporation of an eye filter and internal noise in the observer models demonstrated improved correspondence with human observer performance. Optimal acquisition and decomposition parameters were shown to depend on the imaging task; for example, ACNR and SSH yielded the greatest performance in the detection of soft-tissue and bony lesions, respectively. This study provides encouraging evidence that Fourier-based modeling of NEQ computed via CSA and imaging task provides a good approximation to human observer performance for simple imaging tasks, helping to bridge the gap between Fourier metrics of detector performance (e.g., NEQ) and human observer performance.

Cascaded systems analysis of noise reduction algorithms in dual-energy imaging

An important aspect of dual-energy (DE) x-ray image decomposition is the incorporation of noise reduction techniques to mitigate the amplification of quantum noise. This article extends cascaded systems analysis of imaging performance to DE imaging systems incorporating linear noise reduction algorithms. A general analytical formulation of linear DE decomposition is derived, with weighted log subtraction and several previously reported noise reduction algorithms emerging as special cases. The DE image noise-power spectrum (NPS) and modulation transfer function (MTF) demonstrate that noise reduction algorithms impart significant, nontrivial effects on the spatial-frequency-dependent transfer characteristics which do not cancel out of the noise-equivalent quanta (NEQ). Theoretical predictions were validated in comparison to the measured NPS and MTF. The resulting NEQ was integrated with spatial-frequency-dependent task functions to yield the detectability index, d', for evaluation of DE imaging performance using different decomposition algorithms. For a 3 mm lung nodule detection task, the detectability index varied from d' < 1 (i.e., nodule barely visible) in the absence of noise reduction to d' > 2.5 (i.e., nodule clearly visible) for "anti-correlated noise reduction" (ACNR) or "simple-smoothing of the high-energy image" (SSH) algorithms applied to soft-tissue or bone-only decompositions, respectively. Optimal dose allocation (A*, the fraction of total dose delivered in the low-energy projection) was also found to depend on the choice of noise reduction technique. At fixed total dose, multi-function optimization suggested a significant increase in optimal dose allocation from A* = 0.32 for conventional log subtraction to A* = 0.79 for ACNR and SSH in soft-tissue and bone-only decompositions, respectively. Cascaded systems analysis extended to the general formulation of DE image decomposition provided an objective means of investigating DE imaging performance across a broad range of acquisition and decomposition algorithms in a manner that accounts for the spatial-frequency-dependent imaging task.