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Coronary artery calcification is a significant predictor of cardiovascular disease, with current detection methods like Agatston scoring having limitations in sensitivity. This study aimed to evaluate the effectiveness of a novel CAC quantification method using dual-energy material decomposition, particularly its ability to detect low-density calcium and microcalcifications. A simulation study was conducted comparing the dual-energy material decomposition technique against the established Agatston scoring method and the newer volume fraction calcium mass technique. Detection accuracy and calcium mass measurement were the primary evaluation metrics. The dual-energy material decomposition technique demonstrated fewer false negatives than both Agatston scoring and volume fraction calcium mass, indicating higher sensitivity. In low-density phantom measurements, material decomposition resulted in only 7.41% false-negative (CAC = 0) measurements compared to 83.95% for Agatston scoring. For high-density phantoms, false negatives were removed (0.0%) compared to 20.99% in Agatston scoring. The dual-energy material decomposition technique presents a more sensitive and reliable method for CAC quantification. [ABSTRACT FROM AUTHOR]

The extension of conventional computed tomography known as spectral computed tomography involves utilizing the variations in X-ray attenuation, driven by spectral and material dependencies. This technique enables the virtual decomposition of scanned objects, revealing their elemental constituents. The resultant images provide quantitative information, such as material concentration within the scanned volume. Enhancements in results are achievable through methods that capitalize on the strong correlation among decomposed images, effectively minimizing noise and artifacts. The Rigaku nano3DX submicron tomograph uses a dual-target source, which allows the generation of two distinct X-ray spectra through different target materials. This configuration holds promise for high-resolution applications in spectral tomography, particularly for low-Z materials, where it offers high contrast in the acquired images. The potential of this setup in the context of spectral computed tomography is explored in this contribution, delving into its applications for materials characterized by low atomic numbers. [ABSTRACT FROM AUTHOR]

Modern photon counting detectors allow the calculation of virtual monoenergetic or material decomposed X-ray images but are not yet used for dental panoramic radiography systems. To assess the diagnostic potential and image quality of photon counting detectors in dental panoramic radiography, ethics approval from the local ethics committee was obtained for this retrospective study. Conventional CT scans of the head and neck region were segmented into bone and soft tissue. The resulting datasets were used to calculate panoramic equivalent thickness bone and soft tissue images by forward projection, using a geometry like that of conventional panoramic radiographic systems. The panoramic equivalent thickness images were utilized to generate synthetic conventional panoramic radiographs and panoramic virtual monoenergetic radiographs at various energies. The conventional, two virtual monoenergetic images at 40 keV and 60 keV, and material-separated bone and soft tissue panoramic equivalent thickness X-ray images simulated from 17 head CTs were evaluated in a reader study involving three experienced radiologists regarding their diagnostic value and image quality. Compared to conventional panoramic radiographs, the material-separated bone panoramic equivalent thickness image exhibits a higher image quality and diagnostic value in assessing the bone structure p <. 001 and details such as teeth or root canals p <. 001 . Panoramic virtual monoenergetic radiographs do not show a significant advantage over conventional panoramic radiographs. The conducted reader study shows the potential of spectral X-ray imaging for dental panoramic imaging to improve the diagnostic value and image quality. [ABSTRACT FROM AUTHOR]

Purpose: While dual-energy computed tomography (DECT) images provide clinically useful information than single-energy CT (SECT), SECT remains the most widely used CT system globally, and only a few institutions can use DECT. This study aimed to establish an artificial intelligence (AI)-based image-domain material decomposition technique using multiple keV-output learning of virtual monochromatic images (VMIs) to create DECT-equivalent images from SECT images. Methods: This study involved 82 patients with head and neck cancer. Of these, the AI model was built with data from the 67 patients with only DECT scans, while 15 patients with both SECT and DECT scans were used for SECT testing. Our AI model generated VMI50keV and VMI100keV from VMI70keV equivalent to 120-kVp SECT images. We introduced a loss function for material density images (MDIs) in addition to the loss for VMIs. For comparison, we trained the same model with the loss for VMIs only. DECT-equivalent images were generated from SECT images and compared with the true DECT images. Results: The prediction time was 5.4 s per patient. The proposed method with the MDI loss function quantitatively provided more accurate DECT-equivalent images than the model trained with the loss for VMIs only. Using real 120-kVp SECT images, the trained model produced precise DECT images of excellent quality. Conclusion: In this study, we developed an AI-based material decomposition approach for head and neck cancer patients by introducing the loss function for MDIs via multiple keV-output learning. Our results suggest the feasibility of AI-based image-domain material decomposition in a conventional SECT system without a DECT scanner. [ABSTRACT FROM AUTHOR]

Material decomposition (MD) is an application of dual-energy computed tomography (DECT) that decomposes DECT images into specific material images. However, the direct inversion method used in MD often amplifies noise in the decomposed material images, resulting in lower image quality. To address this issue, we propose an image-domain MD method based on the concept of deep image prior (DIP). DIP is an unsupervised learning method that can perform different tasks without using a large training dataset with known targets (i.e., basis material images). We retrospectively recruited patients who underwent non-contrast brain DECT scans and investigated the feasibility of using the proposed DIP-based method to decompose DECT images into two (i.e., bone and soft tissue) and three (i.e., bone, soft tissue, and fat) basis materials. We evaluated the decomposed material images in terms of signal-to-noise ratio (SNR) and modulation transfer function (MTF). The proposed DIP-based method showed greater improvement in SNR in the decomposed soft-tissue images compared to the direct inversion method and the iterative method. Moreover, the proposed method produced similar MTF curves in both two- and three-material decompositions. Additionally, the proposed DIP-based method demonstrated better separation ability than the other two studied methods in the case of three-material decomposition. Our results suggest that the proposed DIP-based method is capable of unsupervisedly generating high-quality basis material images from DECT images. [ABSTRACT FROM AUTHOR]

Purpose: The present study aimed to determine whether the water content change in the medullary cavity of occult rib fractures by spectral computed tomography (CT). Methods: The material decomposition (MD) images were reconstructed using the water-hydroxyapatite basis material pairs from spectral CT. The water contents of the medullary cavity in subtle or occult rib fractures and the symmetrical sites of the contralateral ribs were measured, and their difference was calculated. The absolute value of the water content difference was compared to patients without trauma. An independent samples t-test was adopted to compare the consistency of the water content in the medullary cavity of the normal ribs. Intergroup and pairwise comparisons were applied to the difference in water content among the subtle/occult fractures and normal ribs, followed by receiver operating characteristic curve calculations. p < 0.05 was considered to have a statistically significant difference. Results: A total of 100 subtle fractures, 47 occult fractures, and 96 pairs of normal ribs were included in this study. The water content of the medullary cavity in the subtle and occult fractures was both higher than that in their symmetrical sites with the difference value of 31.06 ± 15.03 mg/cm3 and 27.83 ± 11.40 mg/cm3, respectively. These difference values between the subtle and occult fractures were not statistically significant (p = 0.497). For the normal ribs, the bilateral water contents were not statistically different (p > 0.05) with a difference value of 8.05 ± 6.13 mg/cm3. The increased water content of fractured ribs was higher than that of normal ribs (p < 0.001). According to the classification based on whether the ribs were fractured, the area under the curve was 0.94. Conclusions: The water content measured on MD images in spectral CT in the medullary cavity increased as a response to subtle/occult rib fractures. [ABSTRACT FROM AUTHOR]

Thermal ablation procedures, such as high intensity focused ultrasound and radiofrequency ablation, are often used to eliminate tumors by minimally invasively heating a focal region. For this task, real-time 3D temperature visualization is key to target the diseased tissues while minimizing damage to the surroundings. Current computed tomography (CT) thermometry is based on energy-integrated CT, tissue-specific experimental data, and linear relationships between attenuation and temperature. In this paper, we develop a novel approach using photon-counting CT for material decomposition and a neural network to predict temperature based on thermal characteristics of base materials and spectral tomographic measurements of a volume of interest. In our feasibility study, distilled water, 50 mmol/L CaCl2, and 600 mmol/L CaCl2 are chosen as the base materials. Their attenuations are measured in four discrete energy bins at various temperatures. The neural network trained on the experimental data achieves a mean absolute error of 3.97 °C and 1.80 °C on 300 mmol/L CaCl2 and a milk-based protein shake respectively. These experimental results indicate that our approach is promising for handling non-linear thermal properties for materials that are similar or dissimilar to our base materials. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We investigated the accuracy of the computed tomography (CT) numbers of virtual non-contrast (VNC) images for two different material decomposition algorithms using the same image data for different diluted contrast agent concentrations. A container filled with contrast agents was inserted into a cylindrical phantom and scanned with dual-energy protocols (80/Sn140 kV, 100/Sn140 kV) using a dual-source CT. VNC images were generated by the 2-material decomposition (MD) algorithm using the energy of each tube voltage and the linear attenuation coefficient, calculated from the theoretical spectral curve of the agent and the CT number of the image, respectively. Furthermore, VNC images using 3-material decomposition (3-MD) algorithm were produced by applying LiverVNC, an analysis parameter implemented in the scanner. The robustness of both the algorithms was verified by investigating the CT numbers of the agents in the VNC. The closer the CT number is to 0 HU, the more robust the algorithm. Without beam-hardening correction, the CT numbers increased with an increase in concentration in both the algorithms, maximal at 50 mg/ml concentration, with CT numbers of 38 HU for 2-MD, 86 HU for 3-MD. With correction, CT numbers were ± 10 HU or less for both the algorithms up to 30 mg/ml concentration, whereas, for concentrations above 40 mg/ml, the maximal averaged CT number was 12 HU for 2-MD, 22 HU for 3-MD. For both the algorithms, the accuracy of the CT numbers was maintained in the low-concentration range; parameter adjustment was necessary to maintain the accuracy at concentrations higher than clinically expected. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Dual-energy CT, the object is scanned at two different energies, makes it possible to identify the characteristics of materials that cannot be evaluated on conventional single-energy CT images. This imaging method can be used to perform material decomposition based on differences in the material-attenuation coefficients at different energies. Dual-energy analyses can be classified as image data-based- and raw data-based analysis. The beam-hardening effect is lower with raw data-based analysis, resulting in more accurate dual-energy analysis. On virtual monochromatic images, the iodine contrast increases as the energy level decreases; this improves visualization of contrast-enhanced lesions. Also, the application of material decomposition, such as iodine- and edema images, increases the detectability of lesions due to diseases encountered in daily clinical practice. In this review, the minimal essentials of dual-energy CT scanning are presented and its usefulness in daily clinical practice is discussed. [ABSTRACT FROM AUTHOR]

Reflecting the growing interest in early diagnosis of non-alcoholic fatty liver disease in recent years, the development of noninvasive and reliable fat quantification methods is needed. Dual-energy computed tomography (DE-CT) is a quantitative diagnostic imaging method that estimates the composition of the imaging target using a material decomposition technique based on the X-ray absorption characteristics peculiar to substances from DE-CT scanning using X-rays generated with different energies (tube voltage). In this review article, we first explain the basic principles and technical aspects of DE-CT. Then, we will present the current diagnostic ability of DE-CT and the factors influencing the quantitative evaluation of liver steatosis using DE-CT as compared to multi-modal methods including ultrasound and magnetic resonance imaging-based methods. In brief, DE-CT may have comparable diagnostic performance to the modern US-based liver fat measurement methods. However, the current material decomposition technique using DE-CT does not seem to have added value to the simple quantitative assessment of liver steatosis, because DE-CT measurement does not improve the accuracy of fat quantification over conventional single-energy computed tomography (SE-CT) attenuation. The most significant influencing factor for the quantitative assessment of liver steatosis using DE-CT can be hepatic iron deposition. An iron-specific multi-material decomposition algorithm correcting for the influences of iron in the liver has been under development. The current material decomposition algorithm can still have added value in a specific situation such as the quantitative assessment of liver steatosis using contrast-enhanced DE-CT. However, there is a lack of evidence for the influence of liver fibrosis in the quantitative assessment of liver steatosis using DE-CT. [ABSTRACT FROM AUTHOR]

Purpose: To determine whether multiphasic dual-energy (DE) CT iodine quantitation correlates with the severity of chronic liver disease. Methods: We retrospectively included 40 cirrhotic and 28 non-cirrhotic patients who underwent a multiphasic liver protocol DECT. All three phases (arterial, portal venous (PVP), and equilibrium) were performed in DE mode. Iodine (I) values (mg I/ml) were obtained by placing regions of interest in the liver, aorta, common hepatic artery, and portal vein (PV). Iodine slopes (λ) were calculated as follows: (Iequilibrium–Iarterial)/time and (Iequilibrium–IPVP)/time. Spearman correlations between λ and MELD scores were evaluated, and the area under the curve of the receiver operating characteristic (AUROC) was calculated to distinguish cirrhotic and non-cirrhotic patients. Results: Cirrhotic and non-cirrhotic patients had significantly different λequilibrium-arterial [IQR] for the caudate (λ = 2.08 [1.39–2.98] vs 1.46 [0.76–1.93], P = 0.007), left (λ = 2.05 [1.50–2.76] vs 1.51 [0.59–1.90], P = 0.002) and right lobes (λ = 1.72 [1.12–2.50] vs 1.13 [0.41–0.43], P = 0.003) and for the PV (λ = 3.15 [2.20–5.00] vs 2.29 [0.85–2.71], P = 0.001). λequilibrium-PVP were significantly different for the right (λ = 0.11 [− 0.45–1.03] vs − 0.44 [− 0.83–0.12], P = 0.045) and left lobe (λ = 0.30 [− 0.25–0.98] vs − 0.10 [− 0.35–0.24], P = 0.001). Significant positive correlations were found between MELD scores and λequilibrium-arterial for the caudate lobe (ρ = 0.34, P = 0.004) and λequilibrium-PVP for the caudate (ρ = 0.26, P = 0.028) and right lobe (ρ = 0.33, P = 0.007). AUROC in distinguishing cirrhotic and non-cirrhotic patients were 0.72 (P = 0.002), 0.71 (P = 0.003), and 0.75 (P = 0.001) using λequilibrium-arterial for the left lobe, right lobe, and PV, respectively. The λequilibrium-PVP AUROC of the right lobe was 0.73 (P = 0.001). Conclusion: Multiphasic DECT iodine quantitation over time is significantly different between cirrhotic and non-cirrhotic patients, correlates with the MELD score, and it could potentially serve as a non-invasive measure of cirrhosis and disease severity with acceptable diagnostic accuracy. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Spectral CT can separate basis materials, and thus it can provide information on material characterization and quantification. Such information can benefit various clinical applications. However, the presence of non-ideal effects in X-ray imaging systems limits the accuracy of basis images. To achieve high accuracy of material decomposition and high quality of basis images, a novel direct iterative basis material image reconstruction based on maximum a posteriori expectation–maximization algorithm (MAP-EM-DD) is proposed. Furthermore, by incorporating polar coordinate transformation into MAP-EM-DD, MAP-EM-PT-DD is proposed. The iterative formulas of MAP-EM-DD and MAP-EM-PT-DD are derived. To evaluate the proposed methods, a simulated cylinder phantom with inserts that contain polyethylene, hydroxyapatite, salt water, air, and aluminum is established. The methods are quantitatively evaluated for comparative studies. Results show that the proposed methods can remarkably reduce the noise of basis images and error of material decomposition and improve the contrast-to-noise ratios (CNRs) of each material-specific region. Compared with the image domain material decomposition based on FBP algorithm (FBP-IDD), MAP-EM-DD can reduce the noise levels of basis images ranging from 57.4 to 63.6% and the error levels of each material-specific region from 31.7 to 62.1%. Simultaneously, the CNRs of each material-specific region are improved ranging from 63.8 to 237.3%. Compared with MAP-EM-DD, MAP-EM-PT-DD can reduce the noise levels of basis images ranging from 21.4 to 23.6%, the error levels of each material-specific region ranging from 1.9 to 36.3%, and the reconstruction time of basis images by 14.1%. [ABSTRACT FROM AUTHOR]

To investigate the feasibility of quantifying the chemical composition of coronary artery plaque in terms of water, lipid, protein, and calcium contents using dual-energy computed tomography (CT) in a simulation study. A CT simulation package was developed based on physical parameters of a clinical CT scanner. A digital thorax phantom was designed to simulate coronary arterial plaques in the range of 2–5 mm in diameter. Both non-calcified and calcified plaques were studied. The non-calcified plaques were simulated as a mixture of water, lipid, and protein, while the calcified plaques also contained calcium. The water, lipid, protein, and calcium compositions of the plaques were selected to be within the expected clinical range. A total of 95 plaques for each lesion size were simulated using the CT simulation package at 80 and 135 kVp. Half-value layer measurements were made to make sure the simulated dose was within the range of clinical dual energy scanning protocols. Dual-energy material decomposition using a previously developed technique was performed to determine the volumetric fraction of water, lipid, protein, and calcium contents in each plaque. For non-calcified plaque, the total volume conservation provides the third constrain for three-material decomposition with dual energy CT. For calcified plaque, a fourth criterion was introduced from a previous report suggesting a linear correlation between water and protein contents in soft tissue. For non-calcified plaque, the root mean-squared error (RMSE) of the image-based decomposition was estimated to be 0.7%, 1.5%, and 0.3% for water, lipid, and protein contents, respectively. As for the calcified plaques, the RMSE of the 5 mm plaques were estimated to be 5.6%, 5.7%, 0.2%, and 3.1%, for water, lipid, calcium, and protein contents, respectively. The RMSE increases as the plaque size reduces. The simulation results indicate that chemical composition of coronary arterial plaques can be quantified using dual-energy CT. By accurately quantifying the content of a coronary plaque lesion, our decomposition method may provide valuable insight for the assessment and stratification of coronary artery disease. [ABSTRACT FROM AUTHOR]

Dual-energy CT (DECT) can be defined as the use of two different energy levels to identify and quantify material composition. Since its inception, DECT has benefited from remarkable improvements in hardware and clinical applications. DECT enables accurate identification and quantification of multiple materials, including fat, iron, and iodine. As a consequence, multiple studies have investigated the potential role of DECT in the assessment of diffuse liver diseases. While this role is evolving, this article aims to review the most relevant literature on use of DECT for assessment of diffuse liver diseases. Moreover, the basic concepts on DECT techniques, types of image reconstruction, and DECT-dedicated software will be described, focusing on the areas that are most relevant for the evaluation of diffuse liver diseases. Also, we will review the evidence of added value of DECT in detection and assessment of hepatocellular carcinoma which is a known risk in patients with diffuse liver disease. [ABSTRACT FROM AUTHOR]

Purpose: To assess the diagnostic image quality and material decomposition characteristics of portal venous phase abdominal CT scans performed on rapid kVp-switching DECT (rsDECT) in patients with large body habitus. Methods: We retrospectively included consecutive patients with large body habitus (≥ 90 kg) undergoing portal venous phase abdominal CT scans on rsDECT scanners between Sep 2014 and March 2018. Qualitative and quantitative assessment of the DECT data sets [65 keV monoenergetic, material density iodine (MD-I) and material density water (MD-W) images] was performed for determination of image quality (IQ) and image noise. Correlation of qualitative assessment scores with weight, BMI and patients' diameter were calculated using Pearson correlation test. Optimal thresholds were calculated using AUC and Youden index to define most appropriate size cut off, below which the IQ of material density images is largely acceptable. Results: The 65 keV monoenergetic images were of diagnostic quality (diagnostic acceptability, DA ≥ 3) in 97.8% of patients (n = 91/93). However, there was significant IQ degradation of MD-I images in 20.4% (n = 19/93, DA < 3) of patients. Similarly, there was significant degradation (DA < 3) of MD-W images in 26.9% (25/92). Clinically significant artifacts (PA ≥ 3/4) were seen in 31% (n = 29/93) and 32.3% (30/93) of MD-I and MD-W images respectively. Optimal threshold for diagnostic acceptability of MD-I images were 110 kg for weight and 33.5 kg/m2 for BMI. Conclusion: Rapid kVp-switching DECT provides diagnostically acceptable monoenergetic images for patients with large body habitus (≥ 90 kg). There is degradation of IQ in the material density specific images particularly in patients weighing > 110 kg and with BMI > 33.5 kg/m2, due to higher number of artifacts. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the accuracy of bone mineral density (BMD) quantification using dual-layer spectral detector CT (SDCT) at various scan protocols.Methods: Two validated anthropomorphic phantoms containing inserts of 50-200 mg/cm3 calcium hydroxyapatite (HA) were scanned using a 64-slice SDCT scanner at various acquisition protocols (120 and 140 kVp, and 50, 100 and 200 mAs). Regions of interest (ROIs) were placed in each insert and mean attenuation profiles at monochromatic energy levels (90-200 keV) were constructed. These profiles were fitted to attenuation profiles of pure HA and water to calculate HA concentrations. For comparison, one phantom was scanned using dual energy X-ray absorptiometry (DXA).Results: At both 120 and 140 kVp, excellent correlations (R = 0.97, P < 0.001) were found between true and measured HA concentrations. Mean error for all measurements at 120 kVp was -5.6 ± 5.7 mg/cm3 (-3.6 ± 3.2%) and at 140 kVp -2.4 ± 3.7 mg/cm3 (-0.8 ± 2.8%). Mean measurement errors were smaller than 6% for all acquisition protocols. Strong linear correlations (R2 ≥ 0.970, P < 0.001) with DXA were found.Conclusions: SDCT allows for accurate BMD quantification and potentially opens up the possibility for osteoporosis evaluation and opportunistic screening in patients undergoing SDCT for other clinical indications. However, patient studies are needed to extend and translate our findings.Key Points: • Dual-layer spectral detector CT allows for accurate bone mineral density quantification. • BMD measurements on SDCT are strongly linearly correlated to DXA. • SDCT, acquired for several indications, may allow for evaluation of osteoporosis. • This potentially opens up the possibility for opportunistic osteoporosis screening. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study was to evaluate the feasibility and accuracy of dual-layer spectral detector CT (SDCT) for the quantification of clinically encountered gadolinium concentrations.Methods: The cardiac chamber of an anthropomorphic thoracic phantom was equipped with 14 tubular inserts containing different gadolinium concentrations, ranging from 0 to 26.3 mg/mL (0.0, 0.1, 0.2, 0.4, 0.5, 1.0, 2.0, 3.0, 4.0, 5.1, 10.6, 15.7, 20.7 and 26.3 mg/mL). Images were acquired using a novel 64-detector row SDCT system at 120 and 140 kVp. Acquisitions were repeated five times to assess reproducibility. Regions of interest (ROIs) were drawn on three slices per insert. A spectral plot was extracted for every ROI and mean attenuation profiles were fitted to known attenuation profiles of water and pure gadolinium using in-house-developed software to calculate gadolinium concentrations.Results: At both 120 and 140 kVp, excellent correlations between scan repetitions and true and measured gadolinium concentrations were found (R > 0.99, P < 0.001; ICCs > 0.99, CI 0.99-1.00). Relative mean measurement errors stayed below 10% down to 2.0 mg/mL true gadolinium concentration at 120 kVp and below 5% down to 1.0 mg/mL true gadolinium concentration at 140 kVp.Conclusion: SDCT allows for accurate quantification of gadolinium at both 120 and 140 kVp. Lowest measurement errors were found for 140 kVp acquisitions.Key Points: • Gadolinium quantification may be useful in patients with contraindication to iodine. • Dual-layer spectral detector CT allows for overall accurate quantification of gadolinium. • Interscan variability of gadolinium quantification using SDCT material decomposition is excellent. [ABSTRACT FROM AUTHOR]

The objective of this study is to compare in vivo, the accuracy of single-energy CT (SECT) and dual-energy CT (DECT) in renal stone characterization. Retrospective study approved by the IRB. 30 patients with symptomatic urolithiasis who underwent CT on a second-generation dual-source scanner with a protocol that included low-dose 120 kV scan followed by 100/Sn140 kV dual-energy scan have been included. Stone composition was classified as uric acid, cystine or calcium oxalates, and phosphates according to attenuation values at 120 kV and to 100/Sn140 kV attenuation ratios and compared with the infrared spectroscopy analysis. 50 stones were detected in 30 patients. SECT correctly assessed stone composition in 52 % of the cases, DECT in 90 %. Sensitivity, specificity, positive predictive value, and negative predictive value in differentiating uric acid vs. non-uric acid stones were 0.94, 0.72, 0.64, and 0.96 for SECT and 1.00, 0.94, 1.00, and 0.96 for DECT, respectively. DECT significantly performs better than SECT in characterising renal stones in vivo, and may represent a useful tool for treatment planning. [ABSTRACT FROM AUTHOR]

While conventional ultrasound and laboratory testing can differentiate most thyroid conditions and malignancies, spectral dual-energy computed tomography (DECT) provides molecular data potentially useful in differential diagnosis of small, complex, and partially obscured hemorrhaged nodules with recent bleeding. To demonstrate that Gemstone Spectral Imaging (GSI) analysis of DECT data differentiates challenging benign thyroid nodule conditions in patients with intranodular hemorrhages. A retrospective study was conducted of 30 intranodular hemorrhage patients from 2010 to 2013, including 18 that underwent surgery and provided thyroid tissues for prospective histological analysis. Iodine and water content were determined in patient CT scans and ex vivo tissue specimen scans by reconstruction of raw CT data at 65 keV (optimal contrast). Slope of spectral curve ( λ), effective atomic number ( Z), and final pathological diagnosis were recorded. Iodine content, water content, Z, and λ significantly varied by region (intranodular hemorrhage, solid thyroid nodule, and adjacent margins) in patients and tissue specimens ( P < 0.05). Intranodular hemorrhage exhibited elevated water concentrations (~1100 mg/mL), suggesting a practical threshold of 1075 mg/mL for differentiating intra-plaque hemorrhage and solid nodular regions. Spectral CT provided diagnostic information in 14 thyroid adenomas and four goiters (histologically confirmed in donor specimens), and eight thyroid adenomas and four nodular goiters based on clinical diagnosis. Diagnostically useful regional characteristic of intranodular hemorrhage in the thyroid was visualized via spectral CT employing material decomposition, potentially yielding additional molecular data about complex lesion characteristics no apparent in conventional imaging or laboratory methods. [ABSTRACT FROM AUTHOR]

Innovations in image acquisition and reconstruction technologies have greatly expanded the range of CT applications available in the routine clinical setting. CT images of sub-millimeter resolution can now be acquired of entire body regions in a few seconds or even sub-second time, allowing depiction of fine anatomical detail uncompromised by motion artifact. With sophisticated visualization software, image data can be processed into multiplanar, volume-rendered, cine and other formats to better display anatomical abnormalities and facilitate newer applications such as CT angiography, enterography, urography, tracheobronchography and cardiac CT. Newer applications including dual-energy material decomposition CT are furthering the transition of CT from a purely morphological to a combined anatomical, functional and metabolic imaging technique. These newer applications have largely been pioneered in adult populations, and heightened concern of the risk of carcinogenesis from ionizing radiation tempers dissemination of their use in children. Similar information can often be gleaned from alternative imaging modalities without ionizing radiation exposure, such as MRI and US, and what is most appropriate in children will depend on relative diagnostic efficacy, cost, availability and local expertise. [ABSTRACT FROM AUTHOR]

X-ray spectral CT appears as a new promising imaging modality for the quantitative measurement of materials in an object, compared to conventional energy-integrating CT or dual energy CT. We consider material decomposition in spectral CT as an overcomplete ill-conditioned inverse problem. To solve the problem, we make full use of multi-dimensional nature and high correlation of multi-energy data and spatially neighboring pixels in spectral CT. Meanwhile, we also exploit the fact that material mass density has limited value. The material decomposition is then achieved by using bounded mass density, local joint sparsity and structural low-rank (DSR) in image domain. The results on numerical phantom demonstrate that the proposed DSR method leads to more accurate decomposition than usual pseudo-inverse method with singular value decomposition (SVD) and current popular sparse regularization method with ℓ1-norm constraint. [ABSTRACT FROM AUTHOR]