Liver fat volume fraction measurements based on multi-material decomposition algorithm in patients with nonalcoholic fatty liver disease: the influences of blood vessel, location, and iodine contrast.

BACKGROUND: In recent years, spectral CT-derived liver fat quantification method named multi-material decomposition (MMD) is playing an increasingly important role as an imaging biomarker of hepatic steatosis. However, there are various measurement ways with various results among different researches, and the impact of measurement methods on the research results is unknown. The aim of this study is to evaluate the reproducibility of liver fat volume fraction (FVF) using MMD algorithm in nonalcoholic fatty liver disease (NAFLD) patients when taking blood vessel, location, and iodine contrast into account during measurement. METHODS: This retrospective study was approved by the institutional ethics committee, and the requirement for informed consent was waived because of the retrospective nature of the study. 101 patients with NAFLD were enrolled in this study. Participants underwent non-contrast phase (NCP) and two-phase enhanced CT scanning (late arterial phase (LAP) and portal vein phase (PVP)) with spectral mode. Regions of interest (ROIs) were placed at right posterior lobe (RPL), right anterior lobe (RAL) and left lateral lobe (LLL) to obtain FVF values on liver fat images without and with the reference of enhanced CT images. The differences of FVF values measured under different conditions (ROI locations, with/without enhancement reference, NCP and enhanced phases) were compared. Friedman test was used to compare FVF values among three phases for each lobe, while the consistency of FVF values was assessed between each two phases using Bland-Altman analysis. RESULTS: Significant difference was found between FVF values obtained without and with the reference of enhanced CT images. There was no significant difference about FVF values obtained from NCP images under the reference of enhanced CT images between any two lobes or among three lobes. The FVF value increased after the contrast injection, and there were significant differences in the FVF values among three scanning phases. Poor consistencies of FVF values between each two phases were found in each lobe by Bland-Altman analysis. CONCLUSION: MMD algorithm quantifying hepatic fat was reproducible among different lobes, while was influenced by blood vessel and iodine contrast.

No gadolinium K-edge detected on the first clinical photon-counting computed tomography scanner.

PURPOSE: This study aimed to elucidate whether gadolinium contrast in clinically relevant doses can be used with photon-counting computed tomography (PCCT) as an alternative contrast agent in clinical applications. MATERIAL/METHODS: A CTDI phantom with 3D printed rods filled with different concentrations of gadolinium and iodine contrast was scanned in a PCCT and an energy-integrated computed tomography (EICT). Attenuation values at different monoenergetic steps were extracted for each contrast concentration. RESULTS: For PCCT, gadolinium reached an attenuation >100 HU (103 HU) at 40 keV with a concentration 5 mmol/L whereas the same level was reached at 50 keV (118 HU) for 10 mmol/L and 90 keV (114 HU) for 25 mmol/L. For iodine, the same level of attenuation was reached at 100 keV (106 HU) with a concentration 8.75 mg I/mL. For EICT the lowest gadolinium contrast concentration needed to reach >100 HU (108 HU) was 10 mmol/L at 50 keV. For 25 mmol/L 100 HU was reached at 100 keV. For iodine contrast 108 HU was reached at 110 keV for 8.75 mg I/mL. CONCLUSION: No K-edge potential or difference in attenuation curves between iodine and gadolinium contrast is detected on the first clinical available PCCT. Clinically relevant attenuation levels were barely achieved in this setting with gadolinium concentrations approved for human use. The results of this study suggest that, given current scanning technology, gadolinium is not a clinically useful contrast agent for computed tomography because no K-edge was detected.

Performance evaluation of quantitative material decomposition in slow kVp switching dual-energy CT.

BACKGROUND: Slow kVp switching technique is an important approach to realize dual-energy CT (DECT) imaging, but its performance has not been thoroughly investigated yet. OBJECTIVE: This study aims at comparing and evaluating the DECT imaging performance of different slow kVp switching protocols, and thus helps determining the optimal system settings. METHODS: To investigate the impact of energy separation, two different beam filtration schemes are compared: the stationary beam filtration and dynamic beam filtration. Moreover, uniform tube voltage modulation and weighted tube voltage modulation are compared along with various modulation frequencies. A model-based direct decomposition algorithm is employed to generate the water and iodine material bases. Both numerical and physical experiments are conducted to verify the slow kVp switching DECT imaging performance. RESULTS: Numerical and experimental results demonstrate that the material decomposition is less sensitive to beam filtration, voltage modulation type and modulation frequency. As a result, robust material-specific quantitative decomposition can be achieved in slow kVp switching DECT imaging. CONCLUSIONS: Quantitative DECT imaging can be implemented with slow kVp switching under a variety of system settings.

Study on the scanning protocols for measuring bone mineral density by gemstone CT spectral imaging based on European spine phantom.

BACKGROUND: Gemstone spectral computed tomography (GSCT) has been used to measure bone mineral density (BMD) in human vertebrae and animal models gradually. PURPOSE: To investigate the effect of scanning protocols for BMD measurements by GSCT using the European spine phantom (ESP) and its accuracy and precision. MATERIAL AND METHODS: The ESP number 145 containing three hydroxyapatite (HAP) inserts with densities of 50, 100, and 200 mg/cm3 were labeled as L1, L2, and L3, respectively. Quantitative CT (QCT) protocol and 14 groups of scanning protocols configured by GSCT were used to repeatedly scan the ESP 10 times. Their measurements were compared with the true values of ESP and their relative standard deviation and relative error were calculated. RESULTS: The measured values of the three inserts at different exposure levels were statistically significant (P < 0.05). The measured values in the 0.8 s/r 260 mA group, 0.5 s/r 630 mA group, and 0.6 s/r 640 mA group were not significantly different from the actual ESP values for L1 and L2. However, the measured values at all the parameters were significantly different from the actual values for the L3. CONCLUSION: CT gemstone spectral imaging can accurately and quantitatively measure the HAP value of ESP, but the results of BMD will be affected by the scanning protocols. The best scanning parameter of ESP measured by GSCT was 0.8 s/r 260 mA, taking dose into consideration, and the measurement accuracy of vertebrae with low BMD was higher than that of QCT under this parameter.

Noise correlation and its impact on the performance of multi-material decomposition-based spectral imaging in photon-counting CT.

PURPOSE: It has been known that noise correlation plays an important role in the determination of the performance of spectral imaging based on two-material decomposition (2-MD). To further understand the basics of spectral imaging in photon-counting CT toward optimal design and implementation, we study the noise correlation in multi-MD (m-MD) and its impact on the performance of spectral imaging. METHOD: We derive the equations that characterize the noise and noise correlation in the material-specific (basis) images in m-MD, followed by a simulation study to verify the derived equations and study the noise correlation's impact on the performance of spectral imaging. Using a specially designed digital phantom, the study of noise correlation runs over the cases of two-, three-, and four-MD (2-MD, 3-MD, and 4-MD). Then, the noise correlation's impact on the performance of spectral imaging in photon-counting CT is investigated, using a modified Shepp-Logan phantom. RESULTS: The results in 2-MD show that, in-line with what has been reported in the literature, the noise correlation coefficient between the material-specific images corresponding to the basis materials approaches -1. The results in m-MD (m ≥ 3) are more complicated and interesting, as the noise correlation coefficients between a pair of the material-specific images alternate between ±1, and so do in the case of 4-MD. The m-MD data show that the noise in virtual monochromatic imaging (a form of spectral imaging) is moderate even though the noises in material-specific (basis) images vary drastically. CONCLUSIONS: The observation of noise correlation in 3-MD, 4-MD, and beyond (i.e., m-MD) is informative to the community. The relationship between noise correlation and the performance of spectral imaging revealed in this work may help clinical medical physicists understand the fundamentals of spectral imaging based on MD and optimize the performance of spectral imaging in photon-counting CT and other X-ray imaging modalities.

Dual Energy Computed Tomography Collagen Material Decomposition for Detection of Lumbar Spine Disc Extrusion and Sequestration: A Comparative Study With Greyscale Computed Tomography.

Purpose: To assess value of dual energy computed tomography (DECT) collagen material decomposition algorithm when combined with standard computed tomography (CT) in detection of lumbar disc extrusion and sequestration. Materials and Methods: Retrospective analysis of all patients with acute low back pain who had a diagnosis of lumbar spine disc extrusion and/or sequestration on Magnetic Resonance Imaging (MRI) (reference standard), and had undergone non-contrast DECT of the lumbar spine within 60 days of the MRI. Age and sex-matched control patients (n = 42) were included. Patients were grouped into standard, grey-scale CT only group and standard CT + DECT tendon images group. Two double-blinded radiologists reviewed both groups for presence of extrusion or sequestration. They also rated their diagnostic confidence on Likert 5-point scale. McNemar Chi-square test was used to compare diagnostic accuracy, unpaired t-test to compare reviewers diagnostic confidence, and Cohen's k (kappa) test for interobserver agreement. Results: The combined group showed higher overall sensitivity (96.6% vs 87.2%), specificity (99% vs 95.4%), and diagnostic accuracy (98.7% vs 94.5%) with a lower false positive rate (1.1% vs 4.6%). McNemar Chi-square test confirmed statistical significance (P = .03 and P = .02 for Reviewers R1 and R2, respectively). The mean diagnostic confidence was also significantly higher on combined group (R1: 3.74 ± 1.1 vs 3.47 ± 1.15 (P < .01) and R2: 3.91 ± 1.15 vs 3.72 ± 1.16 [mean ± SD] (P = .02)). Conclusion: Utilizing MRI as a reference standard, DECT tendon application combined with standard CT increases the sensitivity, specificity, and accuracy of detection of lumbar spine disc extrusion and sequestration, when compared to standard CT alone.

Mineral quantitative characterization method based on basis material decomposition model by dual-energy computed tomography.

BACKGROUND: Dual-energy computed tomography (DECT) can reconstruct electron density ρe and effective atomic number Zeff distribution for material discrimination. Image-domain basis material decomposition (IBMD) method is a widely used DECT method. However, IBMD method cannot be used for mineral identification directly due to limitations of complex basis material determination, beam hardening artifacts, and inherent errors caused by approximate empirical formulas. OBJECTIVE: This study proposes an improved IBMD (IIBMD) method to overcome the above limitations. METHODS: In IIBMD method, the composition of basis material is optimized to obtain accurate decomposition coefficients, which enables accurate ρe and Zeff distribution. Moreover, the thickness of basis material is optimized to reduce the effect of beam hardening. Furthermore, two formulas in place of empirical formulas are proposed to calculate ρe and Zeff. Finally, a threshold technique is applied to separate different mineral phases. RESULTS: Numerical simulations and practical experiments using a photon-counting detector CT system are implemented to verify IIBMD method. Results show that the relative errors of ρe and Zeff for seven common minerals are down to 5%, lower than most of the existing DECT methods for rocks. Reasonable volume fraction results of mineral phases are thus obtained through threshold segmentation. CONCLUSIONS: This study demonstrates that the proposed IIBMD method has high practical value in mineralogical identification.

Research on accuracy of material identification based on photon counting spectral CT.

BACKGROUND: Photon counting spectral CT is a significant direction in the development of CT technology and material identification is an important application of spectral CT. However, spectrum estimation in photon counting spectral CT is highly complex and may affect quantification accuracy of material identification. OBJECTIVE: To address the problem of energy spectrum estimation in photon-counting spectral CT, this study investigates empirical material decomposition algorithms to achieve accurate quantitative decomposition of the effective atomic number. METHODS: The spectrum is first calibrated using the empirical dual-energy calibration (EDEC) method and the effective atomic number is then quantitatively estimated based on the EDEC method. The accuracy of estimating the effective atomic number of materials under different calibration conditions is investigated by designing different calibration phantoms, and accurate quantitation is achieved using suitable calibration settings. Last, the validity of this method is verified through simulations and experimental studies. RESULTS: The results demonstrate that the error in estimating the effective atomic number is reduced to within 4% for low and medium Z materials, thereby enabling accurate material identification. CONCLUSION: The empirical dual-energy correction method can solve the problem of energy spectrum estimation in photon counting spectral CT. Accurate effective atomic number estimation can be achieved with suitable calibration.

The added value of radiomics from dual-energy spectral CT derived iodine-based material decomposition images in predicting histological grade of gastric cancer.

BACKGROUND: The histological differentiation grades of gastric cancer (GC) are closely related to treatment choices and prognostic evaluation. Radiomics from dual-energy spectral CT (DESCT) derived iodine-based material decomposition (IMD) images may have the potential to reflect histological grades. METHODS: A total of 103 patients with pathologically proven GC (low-grade in 40 patients and high-grade in 63 patients) who underwent preoperative DESCT were enrolled in our study. Radiomic features were extracted from conventional polychromatic (CP) images and IMD images, respectively. Three radiomic predictive models (model-CP, model-IMD, and model-CP-IMD) based on solely CP selected features, IMD selected features and CP coupled with IMD selected features were constructed. The clinicopathological data of the enrolled patients were analyzed. Then, we built a combined model (model-Combine) developed with CP-IMD and clinical features. The performance of these models was evaluated and compared. RESULTS: Model-CP-IMD achieved better AUC results than both model-CP and model-IMD in both cohorts. Model-Combine, which combined CP-IMD radiomic features, pT stage, and pN stage, yielded the highest AUC values of 0.910 and 0.912 in the training and testing cohorts, respectively. Model-CP-IMD and model-Combine outperformed model-CP according to decision curve analysis. CONCLUSION: DESCT-based radiomics models showed reliable diagnostic performance in predicting GC histologic differentiation grade. The radiomic features extracted from IMD images showed great promise in terms of enhancing diagnostic performance.

Diagnostic accuracy of a dual-energy computed tomography-based post-processing method for imaging bone marrow edema following an acute ligamentous knee injury.

OBJECTIVE: This study evaluated the ability of a custom dual-energy CT (DECT) post-processing material decomposition method to image bone marrow edema after acute knee injury. Using an independent validation cohort, the DECT method was compared to gold-standard, fluid-sensitive MRI. By including both quantitative voxel-by-voxel validation outcomes and semi-quantitative radiologist scoring-based assessment of diagnostic accuracy, we aimed to provide insight into the relationship between quantitative metrics and the clinical utility of imaging methods. MATERIALS AND METHODS: Images from 35 participants with acute anterior cruciate ligament injuries were analyzed. DECT material composition was applied to identify bone marrow edema, and the DECT result was quantitatively compared to gold-standard, registered fluid-sensitive MRI on a per-voxel basis. In addition, two blinded readers rated edema presence in both DECT and fluid-sensitive MR images for evaluation of diagnostic accuracy. RESULTS: Semi-quantitative assessment indicated sensitivity of 0.67 and 0.74 for the two readers, respectively, at the tibia and 0.55 and 0.57 at the femur, and specificity of 0.87 and 0.89 for the two readers at the tibia and 0.58 and 0.89 at the femur. Quantitative assessment of edema segmentation accuracy demonstrated mean dice coefficients of 0.40 and 0.16 at the tibia and femur, respectively. CONCLUSION: The custom post-processing-based DECT method showed similar diagnostic accuracy to a previous study that assessed edema associated with ligamentous knee injury using a CT manufacturer-provided, built-in edema imaging application. Quantitative outcome measures were more stringent than semi-quantitative scoring methods, accounting for the low mean dice coefficient scores.

Improving radiation physics, tumor visualisation, and treatment quantification in radiotherapy with spectral or dual-energy CT.

Over the past decade, spectral or dual-energy CT has gained relevancy, especially in oncological radiology. Nonetheless, its use in the radiotherapy (RT) clinic remains limited. This review article aims to give an overview of the current state of spectral CT and to explore opportunities for applications in RT. In this article, three groups of benefits of spectral CT over conventional CT in RT are recognized. Firstly, spectral CT provides more information of physical properties of the body, which can improve dose calculation. Furthermore, it improves the visibility of tumors, for a wide variety of malignancies as well as organs-at-risk OARs, which could reduce treatment uncertainty. And finally, spectral CT provides quantitative physiological information, which can be used to personalize and quantify treatment.

Quantification of bone marrow edema using dual-energy CT at fracture sites in trauma.

PURPOSE: The purpose of our study was to analyze the change in water and fat density within the bone marrow using the GE Revolution dual-energy computed tomography (DECT) platform using two-material decomposition analyses at extremity, spine, and pelvic fracture sites compared to normal bone marrow at equivalent anatomic sites in adult patients who sustained blunt trauma. METHODS: This retrospective study included 26 consecutive adults who sustained blunt torso trauma and an acute fracture of the thoracolumbar vertebral body, pelvis, or upper and lower extremities with a total of 32 fractures evaluated. Two-material decomposition images were analyzed for quantitative analysis. Statistical analysis was performed using the paired t-test and Shapiro-Wilk test for normality. RESULTS: There were statistically significant differences in the water and fat densities in the bone marrow at the site of an extremity, vertebral body, or pelvic fracture when compared to the normal anatomic equivalent (p < 0.01). CONCLUSION: In this preliminary study, DECT basis material images, using water (calcium) and fat (calcium) decomposition illustrated significant differences in water and fat content between fracture sites and normal bone in a variety of anatomical sites.

The Detection of Foreign Items in Laundry Industry by Dual-Energy X-ray Transmission-Advantages and Limits.

Firefighters, paramedics, nursing staff, and other occupational groups are in constant need of fast and proper cleaning of their professional workwear, not only during a pandemic. Thus, laundry technology needs to become more efficient and automated. Unfortunately, some steps of the cleaning process, such as finding and removing foreign items from pockets or belts, are still completed manually. This is not just time-consuming but potentially dangerous for the workers due to the hazardous nature of items such as scissors, scalpels, or syringes. Additionally, some items may damage the garments by staining or harm the laundry machines, causing malfunctions and process failure. On the one hand, these foreign items are often hidden inside the clothes, making detection very challenging with conventional superficial sensors. On the other hand, these items can be diverse and cannot be detected by metal detectors alone. X-ray transmission has proven to be a powerful tool for detecting items inside of objects. The dual-energy approach (DE-XRT) even allows obtaining quantitative information about the chemical composition of the measured materials. In this study, working garments were accompanied and filled with realistic foreign items. The potential of DE-XRT to detect those items was successfully shown.

Projection decomposition via univariate optimization for dual-energy CT.

Dual-energy computed tomography (DECT) acquires two x-ray projection datasets with different x-ray energy spectra, performs material-specific image reconstruction based on the energy-dependent non-linear integral model, and provides more accurate quantification of attenuation coefficients than single energy spectrum CT. In the diagnostic energy range, x-ray energy-dependent attenuation is mainly caused by photoelectric absorption and Compton scattering. Theoretically, these two physical components of the x-ray attenuation mechanism can be determined from two projection datasets with distinct energy spectra. Practically, the solution of the non-linear integral equation is complicated due to spectral uncertainty, detector sensitivity, and data noise. Conventional multivariable optimization methods are prone to local minima. In this paper, we develop a new method for DECT image reconstruction in the projection domain. This method combines an analytic solution of a polynomial equation and a univariate optimization to solve the polychromatic non-linear integral equation. The polynomial equation of an odd order has a unique real solution with sufficient accuracy for image reconstruction, and the univariate optimization can achieve the global optimal solution, allowing accurate and stable projection decomposition for DECT. Numerical and physical phantom experiments are performed to demonstrate the effectiveness of the method in comparison with the state-of-the-art projection decomposition methods. As a result, the univariate optimization method yields a quality improvement of 15% for image reconstruction and substantial reduction of the computational time, as compared to the multivariable optimization methods.

A generalized simultaneous algebraic reconstruction technique (GSART) for dual-energy X-ray computed tomography.

BACKGROUND: Dual-energy computed tomography (DECT) is a widely used and actively researched imaging modality that can estimate the physical properties of an object more accurately than single-energy CT (SECT). Recently, iterative reconstruction methods called one-step methods have received attention among various approaches since they can resolve the intermingled limitations of the conventional methods. However, the one-step methods typically have expensive computational costs, and their material decomposition performance is largely affected by the accuracy in the spectral coefficients estimation. OBJECTIVE: In this study, we aim to develop an efficient one-step algorithm that can effectively decompose into the basis material maps and is less sensitive to the accuracy of the spectral coefficients. METHODS: By use of a new loss function that employs the non-linear forward model and the weighted squared errors, we propose a one-step reconstruction algorithm named generalized simultaneous algebraic reconstruction technique (GSART). The proposed algorithm was compared with the image-domain material decomposition and other existing one-step reconstruction algorithm. RESULTS: In both simulation and experimental studies, we demonstrated that the proposed algorithm effectively reduced the beam-hardening artifacts thereby increasing the accuracy in the material decomposition. CONCLUSIONS: The proposed one-step reconstruction for material decomposition in dual-energy CT outperformed the image-domain approach and the existing one-step algorithm. We believe that the proposed method is a practically very useful addition to the material-selective image reconstruction field.

Early prediction of final infarct volume with material decomposition images of dual-energy CT after mechanical thrombectomy.

PURPOSE: Evaluation of water material density images (wMDIm) of dual-energy CT (DECT) for earlier prediction of final infarct volume (fiV) in follow-up single-energy CT (SECT) and correlation with clinical outcome. METHODS: Fifty patients (69 years, ± 12.1, 40-90, 50% female) with middle cerebral artery (MCA) occlusions were included. Early infarct volumes were analyzed in monoenergetic images (MonoIm) and wMDIm at 60 keV and compared with the fiV in SECT 4.9 days (± 4) after thrombectomy. Association between infarct volume and functional outcome was tested by linear regression analysis. RESULTS: wMDIm shows a prior visible infarct demarcation (60.7 ml, ± 74.9 ml) compared with the MonoIm (37.57 ml, ± 76.7 ml). Linear regression analysis, Bland-Altman plots and Pearson correlation coefficients show a close correlation of infarct volume in wMDIm to the fiV in SECT (r = 0.86; 95% CI 0.76-0.92), compared with MonoIm and SECT (r = 0.81; 95% CI 0.69-0.89). The agreement with SECT is substantially higher in patients with infarct volumes < 70 ml (n = 33; 66%). Coefficients were smaller with r = 0.59 (95% CI 0.31; 0.78) for MonoIm and SECT compared with r = 0.77 (95% CI 0.57; 0.88) for wMDIm and SECT. At admission, the mean NIHSS score and mRS were 17.02 (± 4.7) and 4.9 (± 0.2). mRS ≤ 2 was achieved in 56% at 90 days with a mean mRS of 2.5 (± 0.8) at discharge. CONCLUSION: Material decomposition allows earlier visibility of the final infarct volume. This promises an earlier evaluation of the dimension and severity of infarction and may lead to faster initiation of secondary stroke prophylaxis.

Lower limit of iron quantification using dual-energy CT - a phantom study.

PURPOSE: Dual-energy computed tomography (DECT) has been proposed for quantification of hepatic iron concentration (IC). However, the lower limit of quantification (LLOQ) has not been established, limiting the clinical adoption of this technology. In this study, we aim to (a) establish the LLOQ using phantoms and (b) investigate the effects of patient size, dose level, energy combination, and reconstruction method. METHODS: Three phantom sizes and eight vials of ferric nitrate solution with IC ranging from 0 to 10 mg/ml were used. DECT scans were performed at 80/140 and 100/140Sn kVp, and using five different levels of CT dose index (CTDI). An image-domain three-material-decomposition algorithm was used to calculate the IC. The LLOQ was determined based on the coefficient of variation from repeated measurements. RESULTS: The measured IC correlated strongly with the true IC in the small and medium phantoms (R2 of linear regression > 0.99) and moderately in the large phantom (0.8 < R2 <0.9). The LLOQ improved with increased CTDI. At 30 mGy, the LLOQ was found to be 0.50/1.73/6.25 mg/ml in the small/medium/large phantoms, respectively. 80/140Sn kVp resulted in superior LLOQ for all phantom sizes compared to 100/140Sn kVp, primarily due to the difference in their iron enhancement ratios (1.94 and 1.55, respectively). Iterative reconstruction was found to further improve the LLOQ (by ~ 11%), whereas reconstruction kernel smoothness had negligible effect. The LLOQ of iron was significantly higher than that of iodine due to its lack of a useful k-edge and lower enhancement ratio. CONCLUSION: Iron quantification at clinically important levels was achieved in a small- and a medium-sized phantom using DECT, but proved challenging in a large phantom. Wide spectral separation and accurate calibration were found to be critical to the success of the technology.

Impact of iron deposit on the accuracy of quantifying liver fat fraction using multi-material decomposition algorithm in dual-energy spectral computed tomography.

OBJECTIVES: To investigate the accuracy of using multi-material decomposition (MMD) algorithm in dual-energy spectral computed tomography (CT) for quantifying fat fraction (FF) in the presence of iron. MATERIALS: Nine tubes with various proportions of fat and iron were prepared. FF were divided into three levels (10%, 20%, and 30%), recorded as references (FFref ). Iron concentrations (in mg/100 g) were divided into three ranges (25.25-25.97, 50.38-51.55 and 75.57-77.72). The nine-tube phantom underwent dual-energy CT and MR. CT attenuation was measured and FF were determined using MMD in CT (FFCT ) and Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation (IDEAL-IQ) in MR (FFMR ) for each tube. Statistical analyses used were: Spearman rank correlation for correlations between FFref and CT attenuation, FFCT , and FFMR ; one-way ANOVA, and one-sample t-test for the differences between FFCT and FFref and between FFMR and FFref . A multivariate linear regression model was established to analyze the differences between the corresponding values with different iron concentrations under the same FFref . RESULTS: Fat fraction on CT (FFCT) and FFMR were positively correlated with FFref (all p < 0.001), while the CT attenuation was negatively correlated with FFref in the three iron concentration ranges. For a given FFref , FFCT decreased and FFMR increased as the iron concentration increased. The mean difference between FFCT and FFref over the nine tube measurements was 0.25 ± 2.45%, 5.7% lower the 5.98 ± 3.33% value between FFMR and FFref (F = 310.017, p < 0.01). CONCLUSION: The phantom results indicate that MMD in dual-energy CT can directly quantify volumetric FF and is less affected by iron concentration than MR IDEAL-IQ method.

Potential of Dual and Multi Energy XRT and CT Analyses on Iron Formations.

Dual and multi energy X-ray transmission imaging (DE-/ME-XRT) are powerful tools to acquire quantitative material characteristics of diverse samples without destruction. As those X-ray imaging techniques are based on the projection onto the imaging plane, only two-dimensional data can be obtained. To acquire three-dimensional information and a complete examination on topology and spatial trends of materials, computed tomography (CT) can be used. In combination, these methods may offer a robust non-destructive testing technique for research and industrial applications. For example, the iron ore mining and processing industry requires the ratio of economic iron minerals to siliceous waste material for resource and reserve estimations, and for efficient sorting prior to beneficiation, to avoid equipment destruction due to highly abrasive quartz. While XRT provides information concerning the thickness, areal density and mass fraction of iron and the respective background material, CT may deliver size, distribution and orientation of internal structures. Our study shows that the data provided by XRT and CT is reliable and, together with data processing, can be successfully applied for distinguishing iron oxide rich parts from waste. Furthermore, heavy element bearing minerals such as baryte, uraninite, galena and monazite can be detected.

Statistical image-based material decomposition for triple-energy computed tomography using total variation regularization.

BACKGROUND: Triple-energy computed tomography (TECT) can obtain x-ray attenuation measurements at three energy spectra, thereby allowing identification of different material compositions with same or very similar attenuation coefficients. This ability is known as material decomposition, which can decompose TECT images into different basis material image. However, the basis material image would be severely degraded when material decomposition is directly performed on the noisy TECT measurements using a matrix inversion method. OBJECTIVE: To achieve high quality basis material image, we present a statistical image-based material decomposition method for TECT, which uses the penalized weighted least-squares (PWLS) criteria with total variation (TV) regularization (PWLS-TV). METHODS: The weighted least-squares term involves the noise statistical properties of the material decomposition process, and the TV regularization penalizes differences between local neighboring pixels in a decomposed image, thereby contributing to improving the quality of the basis material image. Subsequently, an alternating optimization method is used to minimize the objective function. RESULTS: The performance of PWLS-TV is quantitatively evaluated using digital and mouse thorax phantoms. The experimental results show that PWLS-TV material decomposition method can greatly improve the quality of decomposed basis material image compared to the quality of images obtained using the competing methods in terms of suppressing noise and preserving edge and fine structure details. CONCLUSIONS: The PWLS-TV method can simultaneously perform noise reduction and material decomposition in one iterative step, and it results in a considerable improvement of basis material image quality.