Dual-energy Material Decomposition Research Articles

The utility of dual-energy CT collagen material decomposition technique for the visualization of tendon grafts after knee ligament reconstruction

ObjectiveThe purpose of this article is to assess whether dual-energy CT (DECT) collagen material decomposition technique could reliably depict graft integrity in patients with knee ligament reconstruction. MethodsSeventy patients (mean age, 29.8 years; age range, 15–57 years; 61 men, 9 women) who underwent knee DECT, from June 2016 to January 2018, after knee ligament reconstruction were included in our study. A total of 92 intact tendon grafts (autograft, n = 37; allograft, n = 50), confirmed by MRI and clinical assessment or second-look arthroscopy of the operated knee, were evaluated. The type and number of reconstructed ligaments were as follows: anterior cruciate ligament (ACL) (n = 30), posterior cruciate ligament (PCL) (n = 20), medial collateral ligament (MCL) (n = 12), lateral collateral ligament (LCL) (n = 10), posterolateral ligamentous complex (PLC) (n = 7), anterolateral ligament (ALL) (n = 6), and medial patellofemoral ligament (MPFL) (n = 7). All DECT tendon-specific color mapping images were analyzed by two radiologists independently. Each reconstructed ligament was divided into proximal, middle, and distal portion and rated separately using a three-point scale (0 = absent 'dual-energy color staining'; 1 = partial 'dual-energy color staining'; 2 = full 'dual-energy color staining'). ResultsThe mean of total visualization scores of reconstructed ligaments were 5 or more out of 6 points (PCL: 5.0 ± 0.8; MCL: 5.4 ± 0.7; LCL: 5.5 ± 0.5; PLC: 5.4 ± 1.0; ALL: 5.3 ± 0.6; MPFL: 5.8 ± 0.5), except for ACL (4.3 ± 1.7). No significant difference was observed in the mean of total visualization scores between the autografts and allografts (p > 0.05). The frequency of the score 0 was greater than 10% for the ACL group (15.7%), while less than 5% or 0% for the other groups. Overall, substantial to almost perfect interobserver agreement (range 0.71–0.93) was found for all types of ligaments. ConclusionDECT collagen material decomposition technique could be a valuable tool to qualitatively display tendon grafts in the patients with knee ligament reconstruction, but more caution would be needed to assess ACL graft.

The influence of liver fat deposition on liver iron overload quantitative assessment by fast-kilovolt-peak switching dual-energy CT imaging and material decomposition technique: a vitro experiment study

Objective To investigate the influence of liver fat deposition on the quantification of the liver iron overload using fast-kilovolt-peak switching dual-energy CT imaging and material decomposition technique. Methods A total of 20 healthy SD rats were taken to make 18 PVC tube of homogenate of fresh liver tissue. The dextran with concentration of 50, 40, 30, 20, 10 and 0 mg/ml were mixed with rat liver homogenate and triglyceride with three different concentrations (add fat with volume percentage of 60%, 30%, 10% and to simulate severe, moderate and mild fatty liver respectively). All samples were placed in standard phantom according to the order of iron concentration from high to low and scanned by GE Revolution CT 256 slices scanner in GSI mode with rapid tube voltage switching between 80 and 140 kVp and with tube current 200 mA,320 mA, 485 mA respectively. The images of iron (fat)-based substance pair were reconstructed and the virtual iron concentration (VIC) value were recorded. The correlation between VIC and the actual liver concentration (LIC) of the three sets of tube currents (200, 320, 485 mA) was analyzed by Spearman correlation analysis and linear regression. Results LIC and VIC were highly positively correlated with the liver iron deposition model under different tube currents (r value was 0.900 to 1.000, P<0.05). The presence of fat will result in the decrease of VIC value. In a certain X-ray energy range and certain liver iron concentration, the higher the fat content, the more liver iron concentration underestimation were happened in VIC. At 200, 320 and 485 mA, the crossing points of linear equations for 30% and 10% fatty liver iron deposition models were located at VIC=12.682, 12.470 and 13.447 mg/cm3, respectively. Conclusions The fast-kilovolt-peak switching dual-energy CT imaging and material decomposition techniques can be used for quantitative evaluation of liver iron with hepatic steatosis. The presence of fat will lead to a decrease in VIC measurement. Key words: Tomography, X-ray computed; Substances separation; Liver; Iron; Fat

Low-dose single-energy material decomposition in radiography using a sparse-view computed tomography scan

Dual-energy material decomposition (DEMD) is a well-established theoretical x-ray technique that uses low- and high-kilovoltage radiographs to separate soft tissue and bone in radiography and computed tomography (CT). However, it requires double exposures that result in increased patient radiation doses, causes increases in the execution time, and generates errors due to misregistration attributed to the patient motion between two scans. In this study, we investigated a low-dose, single-energy material decomposition (LSEMD) method in radiography using a sparse-view CT scan where the attenuation length in the object was estimated from the CT image. We performed a systematic simulation and an experiment to demonstrate the feasibility of use of the LSEMD method in radiography. Only 60 projections, far fewer than those required by the Nyquist sampling theory, were acquired at an x-ray tube voltage of 80 kVp, and were used to reconstruct a sparse-view CT image with a state-of-the-art dictionary-learning (DL) algorithm. We investigated the image performance of the LSEMD and compared the elicited results with those obtained with the use of DEMD (80 kVp and 120 kVp were used). Our results indicate that the DL algorithm produced high-quality sparse-view CT images. Accordingly, the LSEMD method yielded material decomposition results that were very similar to the results elicited by the conventional DEMD method in radiography.

Role of dual energy CT to improve diagnosis of non-traumatic abdominal vascular emergencies.

Computed tomography angiography (CTA) is the modality of choice to evaluate abdominal vascular emergencies (AVE). CTA protocols are often complex and require acquisition of multiple phases to enable a variety of diagnosis such as acute bleeding, pseudoaneurysms, bowel ischemia, and dissection. With single energy CT (SECT), differentiating between calcium, coagulated blood, and contrast agents can be challenging based on their attenuation, especially when in small quantity or present as a mixture. With dual-energy CT (DECT), virtual monoenergetic (VM) and material decomposition (MD) image reconstructions enable more robust tissue characterization, improve contrast-enhancement, and reduce beam hardening artifacts. This article will demonstrate how radiologists can utilize DECT for various clinical scenarios in assessment of non-traumatic AVE.

Development of a novel algorithm for metal artifact reduction in digital tomosynthesis using projection-based dual-energy material decomposition for arthroplasty: A phantom study

In this study, a novel dual-energy (DE) material decomposition reconstruction algorithm (DEMDRA) was developed using projection data with the aim of reducing metal artifacts during digital tomosynthesis (DT) for implants. Using the three-material decomposition method and decomposition projection data specific for each material, a novel DEMDRA was implemented to reduce metal artifacts via weighted hybrid reconstructed images [maximum likelihood expectation maximization (MLEM) and shift-and-add (SAA)]. Pulsed X-ray exposures with rapid switching between low and high tube potential kVp were used for DE-DT imaging, and the images were compared using conventional filtered back projection (FBP), MLEM, the simultaneous algebraic reconstruction technique total variation (SART-TV), virtual monochromatic processing, and metal artifact reduction (MAR)-processing algorithms. The reductions in metal artifacts were compared using an artifact index (AI), Gumbel distribution of the largest variations, and the artifact spread functions (ASFs) for prosthesis phantom. The novel DEMDRA yielded an adequately effective overall performance in terms of the AI, and the resulting images yielded good results independently of the type of metal used in the prosthetic phantom, as well as good noise artifact removal, particularly at greater distances from metal objects. Furthermore, the DEMDRA represented the minimum in the model of largest variations. Regarding the ASF analysis, the novel DEMDRA yielded superior metal artifact reduction when compared with conventional reconstruction algorithms with and without MAR processing. Finally, the DEMDRA was particularly useful for reducing high-frequency artifacts.

First Dual MeV Energy X-ray CT for Container Inspection: Design, Algorithm, and Preliminary Experimental Results

Dual-energy mega-electron-volt (MeV) X-ray container radiography has become a well-established technique in customs security application, because of its material discrimination capability. The main difficulty of X-ray radiography is dealing with the materials overlapping problem. When two or more materials exist along the X-ray beam path, its material discrimination performance will be obviously affected. Computed tomography (CT) collects many X-ray measurements taken from different angles surrounding an object to produce cross-sectional (tomographic) images of the scanned object. Therefore, CT can provide real 3-D images inside the object. However, due to the bulky container volume and complex types of cargos, it is very hard to develop such a huge CT system for container inspection. To the best of our knowledge, there has no such commercial X-ray CT system for container inspection yet. This paper presents the design of a dual MeV energy X-ray CT system for cargo container inspection which uses an accelerator with fast 6/9 MeV switching spectra, an arc detector array and rotating mechanism. A dual MeV energy X-ray CT image reconstruction and material decomposition algorithm are developed. An experimental system was built with the same accelerator and detector array as used in the designed container CT system. Experimental results that prove the validity and effectiveness of the algorithm and CT system are presented.

Assessing the Blood Supply Status of the Focal Ground-Glass Opacity in Lungs Using Spectral Computed Tomography.

ObjectiveTo exploit material decomposition analysis in dual-energy spectral computed tomography (CT) to assess the blood supply status of the ground-glass opacity (GGO) in lungs.Materials and MethodsThis retrospective study included 48 patients with lung adenocarcinoma, who underwent a contrast-enhanced dual-energy spectral CT scan before treatment (53 GGOs in total). The iodine concentration (IC) and water content (WC) of the GGO, the contralateral and ipsilateral normal lung tissues were measured in the arterial phase (AP) and their differences were analyzed. IC, normalized IC (NIC), and WC values were compared between the pure ground-glass opacity (pGGO) and the mixed ground-glass opacity (mGGO), and between the group of preinvasive lesions and the minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IA) groups.ResultsThe values of pGGO (IC = 20.9 ± 6.2 mg/mL and WC = 345.1 ± 87.1 mg/mL) and mGGO (IC = 23.8 ± 8.3 mg/mL and WC = 606.8 ± 124.5 mg/mL) in the AP were significantly higher than those of the contralateral normal lung tissues (IC = 15.0 ± 4.9 mg/mL and WC = 156.4 ± 36.8 mg/mL; IC = 16.2 ± 5.7 mg/mL and WC = 169.4 ± 41.0 mg/mL) and ipsilateral normal lung tissues (IC = 15.1 ± 6.2 mg/mL and WC = 156.3 ± 38.8 mg/mL; IC = 15.9 ± 6.0 mg/mL and WC = 174.7 ± 39.2 mg/mL; all p < 0.001). After normalizing the data according to the values of the artery, pGGO (NIC = 0.1 and WC = 345.1 ± 87.1 mg/mL) and mGGO (NIC = 0.2 and WC = 606.8 ± 124.5 mg/mL) were statistically different (p = 0.049 and p < 0.001, respectively), but not for the IC value (p = 0.161). The WC values of the group with preinvasive lesions and MIA (345.4 ± 96.1 mg/mL) and IA (550.1 ± 158.2 mg/mL) were statistically different (p < 0.001).ConclusionUsing dual-energy spectral CT and material decomposition analysis, the IC in GGO can be quantitatively measured which can be an indicator of the blood supply status in the GGO.

Megavoltage cargo radiography with dual energy material decomposition

Megavoltage (MV) radiography has important applications in imaging large cargos for detecting illicit materials. A useful feature of MV radiography is the possibility of decomposing and quantifying materials with different atomic numbers. This can be achieved by imaging cargo at two different X-ray energies, or dual energy (DE) radiography. The performance of both single energy and DE radiography depends on beam energy, beam filtration, radiation dose, object size, and object content. The purpose of this work was to perform comprehensive qualitative and quantitative investigations of the image quality in MV radiography depending on the above parameters. A digital phantom was designed including Fe background with thicknesses of 2cm, 6cm, and 18cm, and materials samples of Polyethylene, Fe, Pb, and U. The single energy images were generated at x-ray beam energies 3.5MV, 6MV, and 9MV. The DE material decomposed images were generated using interlaced low and high energy beams 3.5/6MV and 6/9MV. The X-ray beams were filtered by low-Z (Polyethylene) and high-Z (Pb) filters with variable thicknesses. The radiation output of the accelerator was kept constant for all beam energies. The image quality metrics was signal-to-noise ratio (SNR) of the particular sample over a particular background. It was found that the SNR depends on the above parameters in a complex way, but can be optimized by selecting a particular set of parameters. For some imaging setups increased filter thicknesses, while strongly absorbing the beams, increased the SNR of material decomposed images. Beam hardening due to polyenergetic x-ray spectra resulted in material decomposition errors, but this could be addressed using region of interest decomposition. It was shown that it is not feasible to separate the materials with close atomic numbers using the DE method. Particularly, Pb and U were difficult to decompose, at least at the dose levels allowed by radiation source and safety requirements.

Segmentation-free x-ray energy spectrum estimation for computed tomography using dual-energy material decomposition.

An x-ray energy spectrum plays an essential role in computed tomography (CT) imaging and related tasks. Because of the high photon flux of clinical CT scanners, most of the spectrum estimation methods are indirect and usually suffer from various limitations. In this study, we aim to provide a segmentation-free, indirect transmission measurement-based energy spectrum estimation method using dual-energy material decomposition. The general principle of this method is to minimize the quadratic error between the polychromatic forward projection and the raw projection to calibrate a set of unknown weights, which are used to express the unknown spectrum together with a set of model spectra. The polychromatic forward projection is performed using material-specific images, which are obtained using dual-energy material decomposition. The algorithm was evaluated using numerical simulations, experimental phantom data, and realistic patient data. The results show that the estimated spectrum matches the reference spectrum quite well and the method is robust. Extensive studies suggest that the method provides an accurate estimate of the CT spectrum without dedicated physical phantom and prolonged workflow. This paper may be attractive for CT dose calculation, artifacts reduction, polychromatic image reconstruction, and other spectrum-involved CT applications.

Dual-Energy Computed Tomographic Applications for Differentiation of Intracranial Hemorrhage, Calcium, and Iodine.

This article reviews the physical principles of dual-energy material decomposition and its current implementation. Clinical applications of dual-energy material decomposition including differentiation of calcification from hemorrhage and iodinated contrast from hemorrhage are highlighted, and their applications to neuroimaging are reviewed.

Investigating the feasibility of classifying breast microcalcifications using photon-counting spectral mammography: A simulation study.

A dual-energy material decomposition method using photon-counting spectral mammography was investigated as a non-invasive diagnostic approach to differentiate between Type I calcifications, consisting of calcium oxalate dihydrate or weddellite compounds that are more often associated with benign lesions, and Type II calcifications containing hydroxyapatite that are predominantly associated with malignant tumors. The study was carried out by numerical simulation to assess the feasibility of the proposed approach. A pencil-beam geometry was modeled, and the total number of x-rays transported through a breast embedded with microcalcifications of different types and sizes were simulated by a one-pixel detector. Material decomposition using two energy bins was then applied to characterize the simulated calcifications into hydroxyapatite and weddellite using maximum-likelihood estimation, taking into account the polychromatic source, and the energy dependent attenuation. Simulation tests were carried out for different dose levels, energy windows and calcification sizes for multiple noise realizations. The results were analyzed using receiver operating characteristic (ROC) analysis. Classification between Type I and Type II calcifications achieved by analyzing a single microcalcification showed moderate accuracy. However, simultaneously analyzing several calcifications within the cluster provided area under the ROC curve of greater than 99% for radiation dose greater than 4.8 mGy mean glandular dose. Simulation results indicated that photon-counting spectral mammography with dual energy material decomposition has the potential to be used as a non-invasive method for discrimination between Type I and Type II microcalcifications that can potentially improve early breast cancer diagnosis and reduce the number of negative breast biopsies. Additional studies using breast specimens and clinical data should be performed to further explore the feasibility of this approach.

Interventional dual-energy imaging-Feasibility of rapid kV-switching on a C-arm CT system.

In the last years, dual-energy CT imaging has shown clinical value, thanks to its ability to differentiate materials based on their atomic number and to exploit different properties of images acquired at two different energies. C-arm CT systems are used to guide procedures in the interventional suite. Until now, there are no commercially available systems that employ dual-energy material decomposition. This paper explores the feasibility of implementing a fast kV-switching technique on a clinically available angiographic system for acquiring dual-energy C-arm CT images. As an initial proof of concept, a fast kV-switching approach was implemented on an angiographic C-arm system and the peak tube voltage during 3D rotational scans was measured. The tube voltage measurements during fast kV-switching scans were compared to corresponding measurements on kV-constant scans. Additionally, to prove stability of the requested exposure parameters, the accuracy of the delivered tube current and pulse width were also recorded and compared. In a first phantom experiment, the voxel intensity values of the individual tube voltage components of the fast kV-switching scans were compared to their corresponding kV-constant scans. The same phantom was used for a simple material decomposition between different iodine concentrations and pure water using a fast kV-switching protocol of 81 and 125 kV. In the last experiment, the same kV-switching protocol as in the phantom scan was used in an in vivo pig study to demonstrate the clinical feasibility. During rapid kV-switching acquisitions, the measured tube voltage of the x-ray tube during fast switching scans has an absolute deviation of 0.23 ± 0.13 kV compared to the measured tube voltage produced during kV-constant acquisitions. The stability of the peak tube voltage over different scan requests was about 0.10 kV for the low and 0.46 for the high energy kV-switching scans and less than 0.1 kV for kV-constant scans, indicating slightly lower stability for kV-switching scans. The tube current resulted in a relative deviation of -1.6% for the low and 6.6% overestimation for the high tube voltage of the kV-switching scans compared to the kV-constant scans. The pulse width showed no deviation for the longer pulse width and only minor deviations (0.02 ± 0.02 ms) for the shorter pulse widths compared to the kV-constant scans. The phantom experiment using different iodine concentrations showed an accurate correlation (R2 > 0.99) between the extracted intensity values in the kV-switching and kV-constant reconstructed volumes, and allows for an automatic differentiation between contrast concentration down to 10% (350 mg/ml iodine) and pure water under low-noise conditions. Preliminary results of iodine and soft tissue separation showed also promising results in the first in vivo pig study. The feasibility of dual-energy imaging using a fast kV-switching method on an angiographic C-arm CT system was investigated. Direct measurements of beam quality in the x-ray field demonstrate the stability of the kV-switching method. Phantom and in vivo experiments showed that images did not deviate from those of corresponding kV-constant scans. All performed experiments confirmed the capability of performing fast kV-switching scans on a clinically available C-arm CT system. More complex material decomposition tasks and postprocessing steps will be part of future investigations.

Quantification of breast lesion compositions using low-dose spectral mammography: A feasibility study.

The positive predictive power for malignancy can potentially be improved, if the chemical compositions of suspicious breast lesions can be reliably measured in screening mammography. The purpose of this study is to investigate the feasibility of quantifying breast lesion composition, in terms of water and lipid contents, with spectral mammography. Phantom and tissue samples were imaged with a spectral mammography system based on silicon-strip photon-counting detectors. Dual-energy calibration was performed for material decomposition, using plastic water and adipose-equivalent phantoms as the basis materials. The step wedge calibration phantom consisted of 20 calibration configurations, which ranged from 2 to 8 cm in thickness and from 0% to 100% in plastic water density. A nonlinear rational fitting function was used in dual-energy calibration of the imaging system. Breast lesion phantoms, made from various combinations of plastic water and adipose-equivalent disks, were embedded in a breast mammography phantom with a heterogeneous background pattern. Lesion phantoms with water densities ranging from 0% to 100% were placed at different locations of the heterogeneous background phantom. The water density in the lesion phantoms was measured using dual-energy material decomposition. The thickness and density of the background phantom were varied to test the accuracy of the decomposition technique in different configurations. In addition, an in vitro study was also performed using mixtures of lean and fat bovine tissue of 25%, 50%, and 80% lean weight percentages as the background. Lesions were simulated by using breast lesion phantoms, as well as small bovine tissue samples, composed of carefully weighed lean and fat bovine tissues. The water densities in tissue samples were measured using spectral mammography and compared to measurement using chemical decomposition of the tissue. The thickness of measured and known water contents was compared for various lesion configurations. There was a good linear correlation between the measured and the known values. The root-mean-square errors in water thickness measurements were 0.3 and 0.2 mm for the plastic phantom and bovine tissue backgrounds, respectively. The results indicate that spectral mammography can be used to accurately characterize breast lesion composition in terms of their equivalent water and lipid contents.

Using edge-preserving algorithm with non-local mean for significantly improved image-domain material decomposition in dual-energy CT

Increased noise is a general concern for dual-energy material decomposition. Here, we develop an image-domain material decomposition algorithm for dual-energy CT (DECT) by incorporating an edge-preserving filter into the Local HighlY constrained backPRojection reconstruction (HYPR-LR) framework. With effective use of the non-local mean, the proposed algorithm, which is referred to as HYPR-NLM, reduces the noise in dual-energy decomposition while preserving the accuracy of quantitative measurement and spatial resolution of the material-specific dual-energy images. We demonstrate the noise reduction and resolution preservation of the algorithm with an iodine concentrate numerical phantom by comparing the HYPR-NLM algorithm to the direct matrix inversion, HYPR-LR and iterative image-domain material decomposition (Iter-DECT). We also show the superior performance of the HYPR-NLM over the existing methods by using two sets of cardiac perfusing imaging data. The DECT material decomposition comparison study shows that all four algorithms yield acceptable quantitative measurements of iodine concentrate. Direct matrix inversion yields the highest noise level, followed by HYPR-LR and Iter-DECT. HYPR-NLM in an iterative formulation significantly reduces image noise and the image noise is comparable to or even lower than that generated using Iter-DECT. For the HYPR-NLM method, there are marginal edge effects in the difference image, suggesting the high-frequency details are well preserved. In addition, when the search window size increases from to , there are no significant changes or marginal edge effects in the HYPR-NLM difference images. The reference drawn from the comparison study includes: (1) HYPR-NLM significantly reduces the DECT material decomposition noise while preserving quantitative measurements and high-frequency edge information, and (2) HYPR-NLM is robust with respect to parameter selection.

Dual-Energy CT: Spectrum of Thoracic Abnormalities.

Recent studies have demonstrated that dual-energy computed tomography (CT) can provide useful information in several chest-related clinical indications. Compared with single-energy CT, dual-energy CT of the chest is feasible with the use of a radiation-dose-neutral scanning protocol. This article highlights the different types of images that can be generated by using dual-energy CT protocols such as virtual monochromatic, virtual unenhanced (ie, water), and pulmonary blood volume (ie, iodine) images. The physical basis of dual-energy CT and material decomposition are explained. The advantages of the use of virtual low-monochromatic images include reduced volume of intravenous contrast material and improved contrast resolution of images. The use of virtual high-monochromatic images can reduce beam hardening and contrast streak artifacts. The pulmonary blood volume images can help differentiate various parenchymal abnormalities, such as infarcts, atelectasis, and pneumonias, as well as airway abnormalities. The pulmonary blood volume images allow quantitative and qualitative assessment of iodine distribution. The estimation of iodine concentration (quantitative assessment) provides objective analysis of enhancement. The advantages of virtual unenhanced images include differentiation of calcifications, talc, and enhanced thoracic structures. Dual-energy CT has applications in oncologic imaging, including diagnosis of thoracic masses, treatment planning, and assessment of response to treatment. Understanding the concept of dual-energy CT and its clinical application in the chest are the goals of this article.

A feasibility study for anatomical noise reduction in dual-energy chest digital tomosynthesis

Lung cancer is the leading cause of cancer death worldwide. Thus, early diagnosis is of considerable importance. For early screening of lung cancer, computed tomography (CT) has been used as the gold standard. Chest digital tomosynthesis (CDT) is a recently introduced modality for lung cancer screening with a relatively low radiation dose compared to CT. The dual energy material decomposition method has been proposed for better detection of pulmonary nodules by means of reducing anatomical noise. In this study, the possibility of material decomposition in CDT was tested by both a simulation study and an experimental study using a CDT prototype. The Geant4 application for tomographic emission (GATE) v6 and tungsten anode spectral model using interpolating polynomials (TASMIP) codes were used for the simulation study to create simulated phantom shapes consisting of five inner cylinders filled with different densities of bone and airequivalent materials. Furthermore, the CDT prototype system and human phantom chest were used for the experimental study. CDT scan in both the simulation and experimental studies was performed with linear movement and 21 projection images were obtained over a 30 degree angular range with a 1.5 degree angular interval. To obtain materialselective images, a projectionbased energy subtraction technique was applied to high and low energy images. The resultant simulation images showed that dual-energy reconstruction could achieve an approximately 32% higher contrast to noise ratio (CNR) in images and the difference in CNR value according to bone density was significant compared to single energy CDT. Additionally, image artifacts were effectively corrected in dual energy CDT simulation studies. Likewise the experimental study with dual energy produced clear images of lung fields and bone structure by removing unnecessary anatomical structures. Dual energy tomosynthesis is a new technique; therefore, there is little guidance regarding its integration into clinical practice and this study can be used to improve the diagnostic efficiency of lung field and spinal bone screening using CDT.

MO‐FG‐204‐03: Using Edge‐Preserving Algorithm for Significantly Improved Image‐Domain Material Decomposition in Dual Energy CT

Purpose:To significantly improve dual energy CT (DECT) imaging by establishing a new theoretical framework of image‐domain material decomposition with incorporation of edge‐preserving techniques.Methods:The proposed algorithm, HYPR‐NLM, combines the edge‐preserving non‐local mean filter (NLM) with the HYPR‐LR (Local HighlY constrained backPRojection Reconstruction) framework. Image denoising using HYPR‐LR framework depends on the noise level of the composite image which is the average of the different energy images. For DECT, the composite image is the average of high‐ and low‐energy images. To further reduce noise, one may want to increase the window size of the filter of the HYPR‐LR, leading resolution degradation. By incorporating the NLM filtering and the HYPR‐LR framework, HYPR‐NLM reduces the boost material decomposition noise using energy information redundancies as well as the non‐local mean. We demonstrate the noise reduction and resolution preservation of the algorithm with both iodine concentration numerical phantom and clinical patient data by comparing the HYPR‐NLM algorithm to the direct matrix inversion, HYPR‐LR and iterative image‐domain material decomposition (Iter‐DECT).Results:The results show iterative material decomposition method reduces noise to the lowest level and provides improved DECT images. HYPR‐NLM significantly reduces noise while preserving the accuracy of quantitative measurement and resolution. For the iodine concentration numerical phantom, the averaged noise levels are about 2.0, 0.7, 0.2 and 0.4 for direct inversion, HYPR‐LR, Iter‐ DECT and HYPR‐NLM, respectively. For the patient data, the noise levels of the water images are about 0.36, 0.16, 0.12 and 0.13 for direct inversion, HYPR‐LR, Iter‐DECT and HYPR‐NLM, respectively. Difference images of both HYPR‐LR and Iter‐DECT show edge effect, while no significant edge effect is shown for HYPR‐NLM, suggesting spatial resolution is well preserved for HYPR‐NLM.Conclusion:HYPR‐NLM provides an effective way to reduce the generic magnified image noise of dual–energy material decomposition while preserving resolution.This work is supported in part by NIH grants 7R01HL111141 and 1R01‐EB016777. This work is also supported by the Natural Science Foundation of China (NSFC Grant No. 81201091), Fundamental Research Funds for the Central Universities in China, and Fund Project for Excellent Abroad Scholar Personnel in Science and Technology.

Breast Density Evaluation Using Spectral Mammography, Radiologist Reader Assessment, and Segmentation Techniques: A Retrospective Study Based on Left and Right Breast Comparison

The purpose of this study was to compare the precision of mammographic breast density measurement using radiologist reader assessment, histogram threshold segmentation, fuzzy C-mean segmentation, and spectral material decomposition. Spectral mammography images from a total of 92 consecutive asymptomatic women (aged 50-69years) who presented for annual screening mammography were retrospectively analyzed for this study. Breast density was estimated using 10 radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and spectral material decomposition. The breast density correlation between left and right breasts was used to assess the precision of these techniques to measure breast composition relative to dual-energy material decomposition. In comparison to the other techniques, the results of breast density measurements using dual-energy material decomposition showed the highest correlation. The relative standard error of estimate for breast density measurements from left and right breasts using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and dual-energy material decomposition was calculated to be 1.95, 2.87, 2.07, and 1.00, respectively. The results indicate that the precision of dual-energy material decomposition was approximately factor of two higher than the other techniques with regard to better correlation of breast density measurements from right and left breasts.

Separation of hepatic iron and fat by dual-source dual-energy computed tomography based on material decomposition: an animal study.

ObjectiveTo explore the feasibility of dual-source dual-energy computed tomography (DSDECT) for hepatic iron and fat separation in vivo.Materials and MethodsAll of the procedures in this study were approved by the Research Animal Resource Center of Shanghai Ruijin Hospital. Sixty rats that underwent DECT scanning were divided into the normal group, fatty liver group, liver iron group, and coexisting liver iron and fat group, according to Prussian blue and HE staining. The data for each group were reconstructed and post-processed by an iron-specific, three-material decomposition algorithm. The iron enhancement value and the virtual non-iron contrast value, which indicated overloaded liver iron and residual liver tissue, respectively, were measured. Spearman's correlation and one-way analysis of variance (ANOVA) were performed, respectively, to analyze statistically the correlations with the histopathological results and differences among groups.ResultsThe iron enhancement values were positively correlated with the iron pathology grading (r = 0.729, p<0.001). Virtual non-iron contrast (VNC) values were negatively correlated with the fat pathology grading (r = −0.642,p<0.0001). Different groups showed significantly different iron enhancement values and VNC values (F = 25.308,p<0.001; F = 10.911, p<0.001, respectively). Among the groups, significant differences in iron enhancement values were only observed between the iron-present and iron-absent groups, and differences in VNC values were only observed between the fat-present and fat-absent groups.ConclusionSeparation of hepatic iron and fat by dual energy material decomposition in vivo was feasible, even when they coexisted.

Advances in computed tomography evaluation of skull base diseases.

Introduction Computed tomography (CT) is a key component in the evaluation of skull base diseases. With its ability to clearly delineate the osseous anatomy, CT can provide not only important tips to diagnosis but also key information for surgical planning. Objectives The purpose of this article is to describe some of the main CT imaging features that contribute to the diagnosis of skull base tumors, review recent knowledge related to bony manifestations of these conditions, and summarize recent technological advances in CT that contribute to image quality and improved diagnosis. Data Synthesis Recent advances in CT technology allow fine-detailed evaluation of the bony anatomy using submillimetric sections. Dual-energy CT material decomposition capabilities allow clear separation between contrast material, bone, and soft tissues with many clinical applications in the skull base. Dual-energy technology has also the ability to decrease image degradation from metallic hardwares using some techniques that can result in similar or even decreased radiation to patients. Conclusions CT is very useful in the evaluation of skull base diseases, and recent technological advances can increase disease conspicuity resulting in improved diagnostic capabilities and enhanced surgical planning.