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Dual energy computed tomography (DECT) plays an important role in the application of advanced imaging due to its material decomposition capability. Image domain decomposition can directly invert CT images through by linear matrix, but the decomposed material images will be seriously affected by noise and artifacts. Although various regularization methods have been proposed to solve this problem, they still face two challenges: tedious parameter adjustment and the loss of image details resulted from over-smoothing. Therefore, in this paper we proposes a dual energy CT image material decomposition algorithm based on iterative residual network. Direct inversion is used as the initial base image, and a stacking two-channel convolutional neural network is used to replace the regularization items in the iterative decomposition model to form a deep iterative decomposition network. This method can realize material decomposition and noise suppression simultaneously. Experimental results show that the iterative residual network proposed in this paper is superior to other comparison methods and can effectively suppress noise and artifacts while maintaining the edge details of the base image.

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) remains a malignancy with poor prognosis, appropriate surgical resection and neoadjuvant therapy depend on the accurate identification of pancreatic supplying arteries. We aim to evaluate the ability of monoenergetic images (MEI [+]) of dual-energy CT (DECT) to improve the visualization of pancreatic supplying arteries compared to conventional polyenergetic images (PEI) and investigate the implications of vascular variation in pancreatic surgery and transarterial interventions. Results One hundred patients without pancreatic diseases underwent DECT examinations were retrospectively enrolled in this study. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) at 40-keV MEI (+) were significantly higher than those of PEI (p 0.05). Four types of variations were observed in the origin of DPA and three to five types in the origin of PSPDA, AIPDA and PIPDA. Conclusions 40-keV MEI (+) of DECT improves the visualization and objective and subjective image quality of pancreatic supplying arteries compared to PEI. Pancreatic supplying arteries have great variations, which has important implications for preoperative planning of technically challenging surgeries and transarterial interventions.

Abstract Background Rest/stress myocardial CT perfusion (CTP) has high diagnostic value for coronary artery disease (CAD), but the additional value of resting CTP especially dual-energy CTP (DE-CTP) beyond coronary CT angiography (CCTA) in chest pain triage remains unclear. We aimed to evaluate the diagnostic accuracy of resting myocardial DE-CTP, and additional value in detecting CAD beyond CCTA (obstructive stenosis: ≥ 50%) in patients suspected of CAD. Methods In this prespecified subanalysis of 54 patients, we included patients suspected of CAD referred to invasive coronary angiography (ICA). Diagnostic accuracy of resting myocardial DE-CTP in detecting myocardial perfusion defects was assessed using resting 13N-ammonia positron emission tomography (PET) as the gold standard. Diagnostic accuracy of cardiac dual-energy CT in detecting flow-limiting stenoses (justifying revascularization) by CCTA combined with resting myocardial DE-CTP, using ICA plus resting 13N-ammonia PET as the gold standard. The CCTA and DE-CTP datasets derived from a single-phase scan performed with dual-energy mode. Results For detecting myocardial perfusion defects, DE-CTP demonstrated high diagnostic accuracy with a sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of 95.52%, 85.93%, and 0.907 on a per-segment basis. For detecting flow-limiting stenoses by CCTA alone, sensitivity, specificity, and AUC were 100%, 56.47%, and 0.777 respectively on a per-vessel basis. For detecting flow-limiting stenoses by CCTA combined with resting myocardial DE-CTP, sensitivity, specificity, and AUC were 96.10%, 95.29% and 0.956 respectively on a per-vessel basis. Additionally, CCTA combined with resting myocardial DE-CTP detected five patients (9%) with no obstructive stenosis but with myocardial perfusion defects confirmed by ICA plus 13N-ammonia PET. Conclusions Resting cardiac DE-CTP demonstrates a high diagnostic accuracy in detecting myocardial perfusion defects and provides an additional clinical value by reducing rates of false-positive and false-negative patients beyond CCTA in patients suspected of CAD.

ObjectivesThe aim of this study was to compare the accuracy of existing dual-energy computed tomography (CT) angiography coronary artery calcium scoring methods to those obtained using an experimental tungsten-based contrast material and a recently described contrast material extraction process (CMEP).MethodsPhantom coronary arteries of varied diameters, with different densities and arcs of simulated calcified plaque, were sequentially filled with water, iodine, and tungsten contrast materials and scanned within a thorax phantom at rapid-kVp-switching dual-energy CT. Calcium and contrast density images were obtained by material decomposition (MD) and CMEP. Relative calcium scoring errors among the 4 reconstructed datasets were compared with a ground truth, 120-kVp dataset.ResultsCompared with the 120-kVp dataset, tungsten CMEP showed a significantly lower mean absolute error in calcium score (6.2%, P < 0.001) than iodine CMEP, tungsten MD, and iodine MD (9.9%, 15.7%, and 40.8%, respectively).ConclusionsNovel contrast elements and material separation techniques offer improved coronary artery calcium scoring accuracy and show potential to improve the use of dual-energy CT angiography in a clinical setting.

Objective: Based on pretherapy dual-energy computed tomography (DECT) images, we developed and validated a nomogram combined with clinical parameters and radiomic features to predict the pathologic subtypes of non-small cell lung cancer (NSCLC) -- adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Methods: A total of 129 pathologically confirmed NSCLC patients treated at the Second Affiliated Hospital of Nanchang University from October 2017 to October 2021 were retrospectively analyzed. Patients were randomly divided in a ratio of 7:3 (n=90) into training and validation cohorts (n=39). Patients' pretherapy clinical parameters were recorded. Radiomics features of the primary lesion were extracted from two sets of monoenergetic images (40 keV and 100 keV) in arterial phases (AP) and venous phases (VP). Features were selected successively through the intra-class correlation coefficient (ICC) and the least absolute shrinkage and selection operator (LASSO). Multivariate logistic regression analysis was then performed to establish predictive models. The prediction performance between models was evaluated and compared using the receiver operating characteristic (ROC) curve, DeLong test, and Akaike information criterion (AIC). A nomogram was developed based on the model with the best predictive performance to evaluate its calibration and clinical utility. Results: A total of 87 ADC and 42 SCC patients were enrolled in this study. Among the five constructed models, the integrative model (AUC: Model 4 = 0.92, Model 5 = 0.93) combining clinical parameters and radiomic features had a higher AUC than the individual clinical models or radiomic models (AUC: Model 1 = 0.84, Model 2 = 0.79, Model 3 = 0.84). The combined clinical-venous phase radiomics model had the best predictive performance, goodness of fit, and parsimony; the area under the ROC curve (AUC) of the training and validation cohorts was 0.93 and 0.90, respectively, and the AIC value was 60.16. Then, this model was visualized as a nomogram. The calibration curves demonstrated it's good calibration, and decision curve analysis (DCA) proved its clinical utility. Conclusion: The combined clinical-radiomics model based on pretherapy DECT showed good performance in distinguishing ADC and SCC of the lung. The nomogram constructed based on the best-performing combined clinical-venous phase radiomics model provides a relatively accurate, convenient and noninvasive method for predicting the pathological subtypes of ADC and SCC in NSCLC. [ABSTRACT FROM AUTHOR]

Purpose: To determine whether the spectral attenuation curve on a rapid kilovoltage-switching dual-energy computed tomography (DECT) scan can distinguish enhancing from nonenhancing incidental small (1–4 cm) renal lesions compared with conventional single-energy attenuation changes. Methods: This retrospective study enrolled 46 patients with 78 renal lesions (24 enhancing; 54 nonenhancing) who underwent DECT with DE mode performed during the portovenous or nephrographic phase. Final diagnosis of enhancing and nonenhancing masses was confirmed by pathology or imaging following the established criteria. Virtual monochromatic images (VMI) were reconstructed, and the slopes between the VMI dataset at 40–70 keV (Slope HU40–70), 40–100 keV (Slope HU40–100), and 40–140 keV (Slope HU40–140) were measured. Visual assessment of the curve pattern was recorded. Diagnostic accuracies were calculated with a cross-validated Mann–Whitney U test, and correlations of quantitative spectral parameters and intraclass correlation coefficient (ICC) were calculated using Spearman's rho correlation. Results: All quantitative and qualitative spectral analysis parameters significantly differentiated the enhancing and nonenhancing lesions (P < 0.001). The optimal slope thresholds calculated by cross-validation for Slope HU40–70, Slope HU40–100, and Slope HU40–140 were 3.0, 1.8 and 1.2, respectively for reader 1 and 3.0, 1.9 and 1.15, respectively for reader 2. Using a slope threshold at all datasets yielded a high diagnostic accuracy of 96 for reader 1 and 95 for reader 2. Using a ∆HU threshold of 20 HU yielded an accuracy of 100. Visual analysis of the curve pattern also yielded high accuracy of 94. Conclusions: The spectral attenuation curve on rapid kilovoltage-switching DECT gives excellent diagnostic accuracy differentiating between incidental enhancing and nonenhancing renal lesions. This benefit of DECT will be most helpful when the true unenhanced phase is not performed. [ABSTRACT FROM AUTHOR]

Contrast-enhanced imaging for choroidal malignant melanoma (CMM) is mostly limited to detecting metastatic tumors, possibly due to difficulties in fixing the eye position. We aimed to (1) validate the appropriateness of estimating iodine concentration based on dual-energy computed tomography (DECT) for CMM and optimize the calculation parameters for estimation, and (2) perform a primary clinical validation by assessing the ability of this technique to show changes in CMM after charged-particle radiation therapy. The accuracy of the optimized estimate (eIC_optimized) was compared to an estimate obtained by commercial software (eIC_commercial) by determining the difference from the ground truth. Then, eIC_optimized, tumor volume, and CT values (80 kVp, 140 kVp, and synthesized 120 kVp) were measured at pre-treatment and 3 months and 1.5–2 years after treatment. The difference from the ground truth was significantly smaller in eIC_optimized than in eIC_commercial (p < 0.01). Tumor volume, CT values, and eIC_optimized all decreased significantly at 1.5–2 years after treatment, but only eIC_commercial showed a significant reduction at 3 months after treatment (p < 0.01). eIC_optimized can quantify contrast enhancement in primary CMM lesions and has high sensitivity for detecting the response to charged-particle radiation therapy, making it potentially useful for treatment monitoring. [ABSTRACT FROM AUTHOR]

Background: Steroids have been shown to reduce inflammation, hypoxic pulmonary vasoconstriction (HPV) and lung edema. Based on evidence from clinical trials, steroids are widely used in severe COVID-19. However, the effects of steroids on pulmonary gas volume and blood volume in this group of patients are unexplored.Objective: Profiting by dual-energy computed tomography (DECT), we investigated the relationship between the use of steroids in COVID-19 and distribution of blood volume as an index of impaired HPV. We also investigated whether the use of steroids influences lung weight, as index of lung edema, and how it affects gas distribution.Methods: Severe COVID-19 patients included in a single-center prospective observational study at the intensive care unit at Uppsala University Hospital who had undergone DECT were enrolled in the current study. Patients' cohort was divided into two groups depending on the administration of steroids. From each patient's DECT, 20 gas volume maps and the corresponding 20 blood volume maps, evenly distributed along the cranial-caudal axis, were analyzed. As a proxy for HPV, pulmonary blood volume distribution was analyzed in both the whole lung and the hypoinflated areas. Total lung weight, index of lung edema, was estimated.Results: Sixty patients were analyzed, whereof 43 received steroids. Patients not exposed to steroids showed a more extensive non-perfused area (19% vs 13%, p < 0.01) and less homogeneous pulmonary blood volume of hypoinflated areas (kurtosis: 1.91 vs 2.69, p < 0.01), suggesting a preserved HPV compared to patients treated with steroids. Moreover, patients exposed to steroids showed a significantly lower lung weight (953 gr vs 1140 gr, p = 0.01). A reduction in alveolar-arterial difference of oxygen followed the treatment with steroids (322 ± 106 mmHg at admission vs 267 ± 99 mmHg at DECT, p = 0.04).Conclusions: The use of steroids might cause impaired HPV and might reduce lung edema in severe COVID-19. This is consistent with previous findings in other diseases. Moreover, a reduced lung weight, as index of decreased lung edema, and a more homogeneous distribution of gas within the lung were shown in patients treated with steroids.Trial Registration: Clinical Trials ID: NCT04316884, Registered March 13, 2020. [ABSTRACT FROM AUTHOR]

Background: Dual‐energy CT with virtual noncalcium (VNCa) images allows the evaluation of focal intramedullary bone marrow involvement in patients with multiple myeloma. However, current commercial VNCa techniques suffer from excessive image noise and artifacts due to material decomposition used in synthesizing VNCa images. Objectives: In this work, we aim to improve VNCa image quality for the assessment of focal multiple myeloma, using an Artificial intelligence based Generalizable Algorithm for mulTi‐Energy CT (AGATE) method. Materials and methods: AGATE method used a custom dual‐task convolutional neural network (CNN) that concurrently carries out material classification and quantification. The material classification task provided an auxiliary regularization to the material quantification task. CNN parameters were optimized using custom loss functions that involved cross‐entropy, physics‐informed constraints, structural redundancy in spectral and material images, and texture information in spectral images. For training data, CT phantoms (diameters 30 to 45 cm) with tissue‐mimicking inserts were scanned on a third generation dual‐source CT system. Scans were performed at routine dose and half of the routine dose. Small image patches (i.e., 40 × 40 pixels) of tissue‐mimicking inserts with known basis material densities were extracted for training samples. Numerically simulated insert materials with various shapes increased diversity of training samples. Generalizability of AGATE was evaluated using CT images from phantoms and patients. In phantoms, material decomposition accuracy was estimated using mean‐absolute‐percent‐error (MAPE), using physical inserts that were not used during the training. Noise power spectrum (NPS) and modulation transfer function (MTF) were compared across phantom sizes and radiation dose levels. Five patients with multiple myeloma underwent dual‐energy CT, with VNCa images generated using a commercial method and AGATE. Two fellowship‐trained musculoskeletal radiologists reviewed the VNCa images (commercial and AGATE) side‐by‐side using a dual‐monitor display, blinded to VNCa type, rating the image quality for focal multiple myeloma lesion visualization using a 5‐level Likert comparison scale (−2 = worse visualization and diagnostic confidence, −1 = worse visualization but equivalent diagnostic confidence, 0 = equivalent visualization and diagnostic confidence, 1 = improved visualization but equivalent diagnostic confidence, 2 = improved visualization and diagnostic confidence). A post hoc assignment of comparison ratings was performed to rank AGATE images in comparison to commercial ones. Results: AGATE demonstrated consistent material quantification accuracy across phantom sizes and radiation dose levels, with MAPE ranging from 0.7% to 4.4% across all testing materials. Compared to commercial VNCa images, the AGATE‐synthesized VNCa images yielded considerably lower image noise (50–77% noise reduction) without compromising noise texture or spatial resolution across different phantom sizes and two radiation doses. AGATE VNCa images had markedly reduced area under NPS curves and maintained NPS peak frequency (0.7 lp/cm to 1.0 lp/cm), with similar MTF curves (50% MTF at 3.0 lp/cm). In patients, AGATE demonstrated reduced image noise and artifacts with improved delineation of focal multiple myeloma lesions (all readers comparison scores indicating improved overall diagnostic image quality [scores 1 or 2]). Conclusions: AGATE demonstrated reduced noise and artifacts in VNCa images and ability to improve visualization of bone marrow lesions for assessing multiple myeloma. [ABSTRACT FROM AUTHOR]

The purpose of this study was to evaluate the potential of dual-energy CT (DECT) with virtual unenhanced imaging (VNC) and iodine maps (IM) to differentiate between intraperitoneal hematomas (IH) and bowel structures (BS) compared to linearly blended DECT (DE-LB) images (equivalent to single-energy CT). This retrospective study included the DECT of 30 patients (mean age: 64.5 ± 15.1 years, 19 men) with intraperitoneal hematomas and 30 negative controls. VNC, IM, and DE-LB were calculated. Imaging follow-up and surgical reports were used as references. Three readers assessed diagnostic performance and confidence in distinguishing IH and BS for DE-LB, VNC, and IM. Diagnostic confidence was assessed on a five-point Likert scale. The mean values of VNC, IM, and DE-LB were compared with nonparametric tests. Diagnostic accuracy was assessed by calculating receiver operating characteristics (ROC). The results are reported as medians with interquartile ranges. Subjective image analysis showed higher diagnostic performance (sensitivity: 96.7–100% vs. 88.2–96.7%; specificity: 100% vs. 96.7–100%; p < 0.0001; ICC: 0.96–0.99) and confidence (Likert: 5; IRQ [5–5] vs. 4, IRQ [3–4; 4–5]; p < 0.0001; ICC: 0.80–0.96) for DECT compared to DE-LB. On objective image analysis, IM values for DECT showed significant differences between IH (3.9 HU; IQR [1.6, 8.0]) and BS (39.5 HU; IQR [29.2, 43.3]; p ≤ 0.0001). VNC analysis revealed a significantly higher attenuation of hematomas (50.5 HU; IQR [44.4, 59.4]) than BS (26.6 HU; IQR [22.8, 32.4]; p ≤ 0.0001). DE-LB revealed no significant differences between hematomas (60.5 HU, IQR [52.7, 63.9]) and BS (63.9 HU, IQR [58.0, 68.8]; p > 0.05). ROC analysis revealed the highest AUC values and sensitivity for IM (AUC = 100%; threshold by Youden-Index ≤ 19 HU) and VNC (0.93; ≥34.1 HU) compared to DE-LB (0.64; ≤63.8; p < 0.001). DECT is suitable for accurate discrimination between IH and BS by calculating iodine maps and VNC images. [ABSTRACT FROM AUTHOR]

Objective: To investigate the value of dual-energy CT (DECT) imaging in the diagnosis of nonspecific terminal ileitis (NTI). Materials and methods: This is a retrospective study, enrolling patients with symptomatic terminal ileitis that underwent conventional multidetector CT (MDCT) enterography or DECT enterography. The sensitivity of the diagnosis of NTI between MDCT images and different kinds of DECT images (40–70 kev virtual monoenergetic images (VMIs) and iodine density images) was compared. The iodine concentrations of lesion bowel wall among NTI, Crohn's disease (CD) and intestinal tuberculosis (ITB) in DECT group and the value of lesion-to-non-lesion contrast ratios of all patients were measured. Receiver operator characteristic (ROC) curves for normalized iodine concentration (NIC) for differentiating among the three kinds of disease were drawn. Results: The sensitivity for the diagnosis of NTI in DECT group (including 40 kev, 50 keV VMIs, and iodine density images) were all 89.7%, significantly higher than that in MDCT group (65.1%) (P = 0.026). Statistical analysis did not reveal marked differences between 60 kev, 70 kev VMIs (86.2%) and MDCT images (65.1%) (P = 0.059). The NIC of NTI was (0.15 ± 0.04)100 µg/cm3 and (0.45 ± 0.08)100 µg/cm3, significantly lower than that of CD (0.34 ± 0.09) 100 µg/cm3, (0.85 ± 0.06) 100 µg/cm3 and that of ITB (0.29 ± 0.07) 100 µg/cm3, (0.88 ± 0.07) 100 µg/cm3 at the enteric phase (EP) and portal venous phase (PVP) (P < 0.001, wholly). The area under the ROC curves (AUROCs) of NICEP and NICPVP were 0.910 and 0.980, respectively, for differentiating between NTI and CD. The value of lesion-to-non-lesion contrast ratios is maximum on the 40 keV VMI both EP and PVP. The value of lesion-to-non-lesion contrast ratios of NTI was lower than that of CD and ITB on each image. The AUROCs of NICEP and NICPVP were 0.875 and 0.940, respectively, for differentiating between NTI and ITB. Conclusions: DECT has higher sensitivity in the diagnosis of NTI than MDCT. Low-keV VMI and iodine density images of DECT can clearly show the NTI. DECT imaging can help to differentiate NTI from CD or ITB by comparing the NIC. [ABSTRACT FROM AUTHOR]

For many cancer types, being undetectable from early symptoms or blood tests, or often detected at late stages, medical imaging emerges as the most efficient tool for cancer screening. MRI, ultrasound, X-rays (mammography), and X-ray CT (CT) are currently used in hospitals with variable costs. Diagnostic materials that can detect breast tumors through molecular recognition and amplify the signal at the targeting site in combination with state-of-the-art CT techniques, such as dual-energy CT, could lead to a more precise detection and assist significantly in image-guided intervention. Herein, we have developed a ligand-specific X-ray contrast agent that recognizes α5β1 integrins overexpressed in MDA-MB-231 breast cancer cells for detection of triple (−) cancer, which proliferates very aggressively. In vitro studies show binding and internalization of our nanoprobes within those cells, towards uncoated nanoparticles (NPs) and saline. In vivo studies show high retention of ~3 nm ligand-PEG-S-AuNPs in breast tumors in mice (up to 21 days) and pronounced CT detection, with statistical significance from saline and iohexol, though only 0.5 mg of metal were utilized. In addition, accumulation of ligand-specific NPs is shown in tumors with minimal presence in other organs, relative to controls. The prolonged, low-metal, NP-enhanced spectral-CT detection of triple (−) breast cancer could lead to breakthrough advances in X-ray cancer diagnostics, nanotechnology, and medicine. [ABSTRACT FROM AUTHOR]

Purpose: To compare virtual unenhanced (VUE) attenuation values and their agreement with true unenhanced (TUE) images in patients who underwent dual-layer detector-based dual-energy computed tomography (dlDECT) with single- vs. split-bolus contrast media protocol. Methods: In this HIPAA-compliant, IRB-approved retrospective analysis, a total of 105 patients who underwent nephrographic phase (NP) dlDECT between 07/2018 and 11/2019 were included: 55 patients received single bolus and 50 patients split-bolus examinations. Both scan protocols comprised a TUE and 120-kVp NP acquisition from which VUE images were reconstructed. A radiologist performed ROI-based attenuation measurements of liver parenchyma, main portal vein, aorta, spleen, renal parenchyma, and pelvis on TUE and VUE images. Agreement between TUE and VUE images was determined and compared for both protocols and each anatomic region. Results: VUE attenuation was significantly higher than TUE attenuation in both cohorts in the liver, portal vein, spleen, and renal parenchyma (p < 0.05), while it was similar in the abdominal aorta in both cohorts (p = 0.05, 0.7522, respectively). VUE attenuation was significantly higher than TUE attenuation in the renal pelvis of the split-bolus cohort (p < 0.05). When comparing VUE images between single- and split-bolus protocols, the renal parenchyma yielded a significantly higher VUE attenuation in the single-bolus cohort (single bolus: 38.8 ± 3.3 HU vs. split bolus: 36.8 ± 3.6 HU; p < 0.05), whereas the split-bolus cohort revealed markedly higher VUE attenuation in the renal pelvis (single bolus: 2.3 ± 10.8 HU vs. split bolus: 92.3 ± 76.8; p < 0.05). Mean intra-patient differences between TUE and VUE images were comparable between single- and split-bolus cohorts (p-range 0.09–0.35) except for the renal parenchyma and pelvis: in the first, the single-bolus cohort yielded a higher VUE attenuation, while in the second, attenuation was significantly higher in the split-bolus cohort (p < 0.05). Conclusion: VUE attenuation overestimated TUE attenuation and differed between split- and single-bolus protocols for the renal parenchyma and pelvis, while all other tissues showed comparable VUE attenuation. [ABSTRACT FROM AUTHOR]

Advances in dual-energy CT (DECT) technology and spectral techniques are catalyzing the widespread implementation of this technology across multiple radiology subspecialties. The inclusion of energy- and material-specific datasets has ushered overall improvements in CT image contrast and noise as well as artifacts reduction, leading to considerable progress in radiologists' ability to detect and characterize pathologies in the abdomen. The scope of this article is to provide an overview of various quantitative clinical DECT applications in the abdomen and pelvis. Several of the reviewed applications have not reached mainstream clinical use and are considered investigational. Nonetheless awareness of such applications is critical to having a fully comprehensive knowledge base to DECT and fostering future clinical implementation. [ABSTRACT FROM AUTHOR]

Dual-energy computed tomography (DECT) represents an emerging imaging technique which consists of the acquisition of two separate datasets utilizing two different X-ray spectra energies. Several cardiac DECT applications have been assessed, such as virtual monoenergetic images, virtual non-contrast reconstructions, and iodine myocardial perfusion maps, which are demonstrated to improve diagnostic accuracy and image quality while reducing both radiation and contrast media administration. This review will summarize the technical basis of DECT and review the principal cardiac applications currently adopted in clinical practice, exploring possible future applications. [ABSTRACT FROM AUTHOR]

A major contributing factor to proton range uncertainty is the conversion of computed tomography (CT) Hounsfield units (HU) to proton relative stopping power (RSP). This uncertainty is heightened in the presence of X‐ray beam‐hardening artifact (BHA), which has two manifestations: cupping and streaking, especially in and near bone tissue. This uncertainty can affect the accuracy of proton RSP calculation for treatment planning in proton radiotherapy. Dual‐energy CT (DECT) and iterative beam‐hardening correction (iBHC) both show promise in mitigating CT BHA. This present work attempts to analyze the relative robustness of iBHC and DECT techniques on both manifestations of BHA. The stoichiometric method for HU to RSP conversion was used for single‐energy CT (SECT) and DECT‐based monochromatic techniques using a tissue substitute phantom. Cupping BHA was simulated by measuring the HU of a bone substitute plug in wax/3D‐printed phantoms of increasing size. Streaking BHA was simulated by placing a solid water plug between two bone plugs in a wax phantom. Finally, the effect of varying calibration phantom size on RSP was calculated in an anthropomorphic head phantom. The RSP decreased −0.002 cm–1 as phantom size increased for SECT but remained largely constant when iBHC applied or with DECT techniques. The RSP varied a maximum of 2.60% in the presence of streaking BHA in SECT but was reduced to 1.40% with iBHC. For DECT techniques, the maximum difference was 2.40%, reduced to 0.6% with iBHC. Comparing calibration phantoms of 20‐ and 33‐cm diameter, maximum voxel differences of 5 mm in the water‐equivalent thickness were observed in the skull but reduced to 1.3 mm with iBHC. The DECT techniques excelled in mitigating cupping BHA, but streaking BHA still could be observed. The use of iBHC reduced RSP variation with BHA in both SECT and DECT techniques. [ABSTRACT FROM AUTHOR]

Objective: Contrast agents in CT scans can compromise the accuracy of dose calculations in radiation therapy planning, especially for particle therapy. This often requires an additional non-contrast CT scan, increasing radiation exposure and introducing potential registration errors. Our goal is to resolve these issues by accurately estimating radiotherapy parameters from dual virtual non-contrast (dual-VNC) images generated by contrast-enhanced dual-energy CT (DECT) scans, while accounting for noise and variability in tissue composition.&#xD;Approach: A new Bayesian model is introduced to estimate dual-VNC Hounsfield units from contrast-enhanced DECT data. The model defines a prior distribution that describes tissue variations in terms of elemental compositions and mass densities. Multiple reference tissues are used to estimate variations across human tissues. A likelihood distribution is also defined to model the noise contained in CT data. The model is thoroughly validated in a simulated environment including 12 virtual patients under low and high iodine uptake scenarios, while incorporating noise and beam hardening effects. The eigentissue decomposition (ETD) technique is used to derive elemental compositions and parameters critical for radiotherapy from the dual-VNC images, such as electron density (ρ e ), particle stopping power (SPR), and photon energy absorption coefficient (EAC)&#xD;Main results: The proposed method yields accurate voxelwise estimations for ρ e , SPR, and EAC, with root mean square errors of 3.09%, 3.14%, and 1.34% for highly-enhanced tissues, compared to 5.93%, 6.39%, and 17.11% when the presence of contrast agent is ignored. It also demonstrates robustness to systematic shifts in tissue composition and bandwidth variations in the prior distribution, resulting in overall uncertainties down to 1.13%, 1.33%, and 0.86% for ρ e , SPR, and EAC in soft tissues; 1.17%, 1.32%, and 1.34% in enhanced soft tissues; and 4.34%, 4.00%, and 2.50% in bone.&#xD;Significance: The proposed method accurately derives radiotherapy parameters from contrast-enhanced DECT data and demonstrates robustness against systematic errors in reference data, highlighting its potential for clinical use., (Creative Commons Attribution license.)

Purpose: To build and evaluate a pre-treatment dual-energy CT(DECT)-based clinical-radiomics nomogram for individualized prediction of short-term treatment response to non-surgical treatment in advanced non-small cell lung cancer (NSCLC)., Methods: Pre-treatment DECT images were retrospectively collected from 98 pathologically confirmed NSCLC with clinical stage III or IV. Short-term treatment response was determined with follow-up CT of 4-6 courses of treatment. Quantitative radiomics metrics of the lesion were extracted from dual-energy mixed images at venous phase. Least absolute shrinkage and selection operator and correlation analysis were used to select the most relevant radiomics features. Radiomics model, clinical model and clinical-radiomics model were established by multivariate logistic regression. The model with the best prediction performance was visualized as a nomogram, and the consistency between the probability of the actual occurrence of the outcome and the probability predicted by the model was measured by calibration curves., Results: Clinical stage, difference in electron density in arteriovenous phase, difference in slope of energy spectrum in arteriovenous phase, and slope of energy spectrum in venous phase of the tumor were significant clinical predictors of therapy response (P < 0.05). The clinical-radiomics model showed a higher predictive capability (AUC: 0.87 and 0.85 in training and validation sets, respectively) than the radiomics models and the clinical model. The clinical-radiomics nomogram integrating the DECT radiomics signature with clinical stage and spectrum parameters showed good calibration and discrimination., Conclusion: The clinical-radiomics nomogram based on pre-treatment DECT showed good performance in predicting clinical response to non-surgical therapy in NSCLC., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Multi-material decomposition is an interesting topic in dual-energy CT (DECT) imaging; however, the accuracy and performance may be limited using the conventional algorithms., Purpose: In this work, a novel multi-material decomposition network (MMD-Net) is proposed to improve the multi-material decomposition performance of DECT imaging., Methods: To achieve dual-energy multi-material decomposition, a deep neural network, named as MMD-Net, is proposed in this work. In MMD-Net, two specific convolutional neural network modules, Net-I and Net-II, are developed. Specifically, Net-I is used to distinguish the material triangles, while Net-II predicts the effective attenuation coefficients corresponding to the vertices of the material triangles. Subsequently, the material-specific density maps are calculated analytically through matrix inversion. The new method is validated using in-house benchtop DECT imaging experiments with a solution phantom and a pig leg specimen, as well as commercial medical DECT imaging experiments with a human patient. The decomposition accuracy, edge spreading function, and noise power spectrum are quantitatively evaluated., Results: Compared to the conventional multiple material decomposition (MMD) algorithm, the proposed MMD-Net method is more effective at suppressing image noise. Additionally, MMD-Net outperforms the iterative MMD approach in maintaining decomposition accuracy, image sharpness, and high-frequency content. Consequently, MMD-Net is capable of generating high-quality material decomposition images., Conclusion: A high performance multi-material decomposition network is developed for dual-energy CT imaging., (© 2024 American Association of Physicists in Medicine.)

Purpose: Dual-energy (DE) CT enables material decomposition by using two different x-ray energies and may be combined with PET for improved multimodality imaging. However, this increases radiation dose and may require a hardware upgrade due to the added second x-ray CT scan. The recently proposed PET-enabled DECT method allows dual-energy imaging using a conventional PET/CT scanner without the need to change scanner hardware or increase radiation exposure. Here we demonstrate the first-time physical phantom and patient data evaluation of this method., Methods: The PET-enabled DECT method reconstructs a gamma-ray CT (gCT) image at 511 keV from the time-of-flight PET data with the maximum-likelihood attenuation and activity (MLAA) approach and then combines this image with the low-energy x-ray CT images to form a dual-energy image pair for material decomposition. To improve the image quality of gCT, a kernel MLAA method was developed using the x-ray CT as a priori information. Here we developed a general open-source implementation for gCT reconstruction and used this implementation for the first real data validation using both physical phantom study and human-subject study. Results from PET-enabled DECT were compared using x-ray DECT as the reference. Further, we applied the PET-enabled DECT method in another patient study to evaluate bone lesions., Results: Compared to the standard MLAA, results from the kernel MLAA showed significantly improved image quality. PET-enabled DECT with the kernel MLAA was able to generate fractional images that were comparable to the x-ray DECT, with high correlation coefficients for both the phantom study and human subject study (R > 0.99). The application study also indicates that PET-enabled DECT has potential to characterize bone lesions., Conclusion: Results from this study have demonstrated the feasibility of this PET-enabled method for CT imaging and material decomposition. PET-enabled DECT shows promise to provide comparable results to x-ray DECT., Competing Interests: Declarations Ethical approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. This study was approved by Institution Review Board at University of California, Davis (IRB#: 1374902). Consent to participate Informed consent was obtained from all participants enrolled in the study. Consent for publication Consent to publish has been received from all participants. Conflict of interest UC Davis has a revenue-sharing agreement with United Imaging Healthcare. No other potential conflicts of interest relevant to this article exist., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: To investigate the clinical value of dual-source dual-energy CT (dsDECT) quantitative parameters in evaluating hemodynamics and predicting high-risk gastroesophageal varices in cirrhotic patients., Methods: 98 consecutive patients were collected in this prospectively study and all patients underwent an abdominal triple-phase contrasted-enhanced examination with dsDECT. Iodine concentration (IC) and normalized iodine concentration (NIC) of the liver parenchyma, spleen parenchyma and aorta at different phases were recorded, and arterial iodine fraction (AIF), iodine washout rate (IWR), and extracellular volume (ECV) were calculated. Using upper gastrointestinal endoscopy as the reference standard, patients who met the inclusion and exclusion criteria were divided into groups with varices need treatment (VNT) and non-VNT. The clinical characteristics, traditional CT features and quantitative dsDECT parameters were compared between the VNT group and the non-VNT group using univariate analysis. The binary logistics analysis was used to build a model for diagnosing VNT. The receiver operating characteristic (ROC) curve was used for analysis and the DeLong test was used to compare different ROC curves., Results: Finally, 57 patients were included in this study. Univariate analysis showed statistically significant differences in NIC of the liver at the portal venous phase (NIC-L PVP ), IWR of the liver (IWR-L) and spleen volume between the VNT group and the non-VNT group (p < 0.05). The mixed-CT model was built by binary logistics analysis. The ROC curves of NIC-L PVP , IWR-L, spleen volume and the mixed-CT model were statistically significant (p < 0.05) for predicting VNT in cirrhotic patients, among which the area under the ROC curve of the mixed-CT model was the highest., Conclusion: Dual-source dual-energy CT has added clinical value in evaluating hepatic hemodynamics and diagnosing VNT in patients with liver cirrhosis., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objectives: To suggest an optimal energy level of virtual monochromatic images (VMIs) in dual-energy CT arthrography of the wrist., Methods: This retrospective study included 53 patients with wrist CT arthrography. Conventional polychromatic images and VMIs at four energy levels (40 to 70 keV at 10 keV intervals) were obtained. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured, and qualitative analysis of image quality and diagnostic confidence was performed. For each patient, an energy level with the best image quality was chosen by consensus. Comparisons of quantitative and qualitative parameters between VMI sets were performed., Results: The image noise of bone and muscle were increased with decreasing energy level (p < 0.001). The noise of contrast was highest on 60 keV VMI. SNR and CNR (between contrast and muscle) were increased with decreasing energy level and were markedly increased between 60 and 50 keV (p < 0.001). The 60 keV VMI demonstrated the highest image quality and diagnostic confidence, chosen as the best diagnostic image (n = 31/53). Given that the attenuation of the contrast material was low on the conventional image, the optimal energy level of the best VMI tended to be low., Conclusion: Wrist dual-energy CT arthrography with VMIs at 60 keV or less could improve image quality and diagnostic performance by increasing SNR and CNR in cases with low contrast attenuation., Advances in Knowledge: Wrist dual-energy CT arthrography with VMIs at variable keV could be utilised to enhance SNR and CNR, thereby achieving diagnostic images of high quality., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Institute of Radiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

The objective of the study is to explore the image quality and diagnosis performance of the dual-energy CT-derived slope parameter images (SPI) generated by the algorithm based on the slope function in the diagnosis of Crohn's disease (CD). Seventy-six CD patients and 53 disease-free control group subjects who underwent dual-energy CT enterography were retrospectively collected. Portal venous phase 120kVp-like and virtual monoenergetic images at 40-100 keV (VMI 40-100 ) were reconstructed. SPIs corresponding to the spectral curve between 40 and 100 keV (SPI 40-100 ) were generated using Python. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of normal and abnormal intestinal walls were calculated. Image quality, noise, and contrast were independently scored by two radiologists using a 5-point scale. Four radiologists conducted CD diagnosis with three reading models (120kVp-like, 120kVp-like with optimal VMI, and 120kVp-like with SPI 40-100 ). The diagnostic performances of the three reading models for diagnosing CD were evaluated using receiver operating characteristic (ROC) curves. The CNR in SPI 40-100 was higher than in the other images (P < 0.05). The subjective evaluation showed that there was no statistical difference between the contrast of SPI 40-100 and VMI 40 (P > 0.05), but that of the two images was higher than the other images (P < 0.05). The scoring on the overall image quality of VMI 50 was superior to that of other images (P < 0.05). The combined model of 120kVp-like with SPI 40-100 had the strongest confidence (cases with high confidence: 36, 58, 49, 47 for radiologists 1, 2, 3, 4) and the highest efficiency in diagnosing CD (areas under the ROC curve: 0.973, 0.977, 0.982, 0.991 for radiologists 1, 2, 3, 4). SPI 40-100 generated by the algorithm based on the slope function exhibited good image quality. The combined model of 120kVp-like with SPI 40-100 could improve radiologists' diagnostic efficiency and confidence in diagnosing CD., Competing Interests: Declarations Ethical Approval Institutional Review Board approval was obtained. Informed Consent Written informed consent was waived by the Institutional Review Board. Conflict of Interest The authors declare no competing interests. Study Subjects or Cohorts Overlap No study subjects or cohorts have been previously reported. Guarantor The scientific guarantor of this publication is Xin Yue (Zhongshan Hospital Xiamen University). Statistics and Biometry One of the authors has significant statistical expertise. Methodology Retrospective.Diagnostic or prognostic study.Performed at one institution., (© 2024. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

Objective: This study explores the clinical utility of dual-energy computed tomography (DECT) in discriminating thrombus types in ischemic stroke., Methods: Patients with acute ischemic stroke who underwent brain DECT non-contrast scanning and brain CT perfusion (CTP) before thrombectomy were included, and the thrombus composition was analyzed by postoperative pathology. DECT data was conducted to reconstruct polychromatic images and effective atomic number images. Computed tomography (CT) values, effective atomic numbers, and spectral curve slopes of the thrombus were measured and calculated. Thrombus attenuation increase was obtained from CTP data. Parameters were compared between red blood cell (RBC)-dominant thrombi and fibrin/platelet (F/P)-dominant thrombi. Thresholds, sensitivity, specificity, and area under the curve (AUC) were analyzed to distinguish these thrombi. The associations between DECT parameters and proportion of RBCs were analyzed by Spearman's correlation., Results: Pathological analysis of 42 enrolled patients revealed 24 cases of RBC-dominant thrombi and 18 cases of F/P-dominant thrombi. Effective atomic numbers, spectral curve slopes, and polychromatic images CT values were significantly higher in the RBC-dominant thrombi group compared with the F/P-dominant thrombi group. Although the average thrombus attenuation increase was greater in the F/P-dominant thrombi group, this difference was not statistically significant. Among the DECT parameters, polychromatic images CT values had the greatest AUC at 0.924 (0.848-0.999) for discriminating RBC-dominant and F/P-dominant thrombi, with a threshold of 59 HU, sensitivity of 79.2 %, and specificity of 94.4 %. The combined diagnostic AUC reached 0.938 (0.863-1.012), with 87.5 % sensitivity and 94.4 % specificity. DECT polychromatic images CT values, effective atomic numbers, and spectral curve slopes were significantly correlated with proportion of RBCs (r = 0.673, 0.574, and 0.571, all p < 0.01)., Conclusion: DECT non-contrast scan parameters are associated with thrombus composition, which could be effective in distinguishing between RBC-dominant and F/P-dominant thrombi., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Purpose: This meta-analysis aimed to evaluate the diagnostic efficacy of dual-energy computed tomography (DECT) in detecting cervical lymph node metastasis among papillary thyroid cancer (PTC) patients., Methods: A comprehensive search across PubMed, Embase, and Web of Science databases was conducted to identify pertinent publications up to May 2024. This search focused on studies examining the diagnostic accuracy of DECT in detecting cervical lymph node metastases in PTC patients. We employed a bivariate random-effects model to calculate pooled sensitivity and specificity of DECT. The degree of heterogeneity in the studies was quantified using the I 2 statistic. Furthermore, the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was utilized to evaluate the methodological quality of the included studies., Results: This meta-analysis encompassed 14 articles, collectively involving 1,615 patients. The pooled sensitivity, specificity, and AUC for DECT in detecting cervical lymph node metastases in PTC patients were 0.81 (95% CI: 0.76-0.85), 0.86 (95% CI: 0.80-0.91), and 0.89 (95% CI: 0.86-0.92), respectively. According to Fagan's nomogram, for DECT, with a pre-test probability of 50%, the post-test probability was calculated as 85% for a positive result and 18% for a negative result. Deeks' funnel plot asymmetry test showed no significant publication bias was observed for DECT ( p  = 0.28)., Conclusion: Our meta-analysis indicates that DECT demonstrates superior sensitivity and specificity in cervical lymph node metastasis among PTC patients. To corroborate these findings and evaluate their clinical applicability, further prospective studies are necessary., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Han, Liu, Cai, Xie and Hu.)

Rationale and Objectives: Classification of non-uric acid (NUA) renal stones in dual-energy CT (DECT) is difficult due to their similar CT number ratios (CTRs) and because the CTRs change with patient size and acquisition protocol. In this work, we developed a generalizable framework to estimate correct CTR threshold for different stone types, protocols, and patient sizes and validated the results on two DECT scanners., Materials and Methods: Our framework assumes generic x-ray spectra, estimates the added filtration to match half-value-layer (HVL) measurements, and predicts the CTR of each stone type from the chemical composition and patient size. The framework was validated for four calcium or iodine inserts in two solid water phantom sizes on two DECT scanners, and on 45 human urinary stones of five types (uric acid, cystine, calcium oxalate monohydrate, brushite, and hydroxyapatite) in three different water phantom sizes on a dual-source DECT. All scans were performed at high dose, using routine acquisition parameters. The predicted CTR was compared with the measured CTR., Results: The predicted CTRs for different stone types were consistent with experimentally measured values, with average absolute errors of 2.8% (range 1.3-4.3%), 1.8% (range 0.7-4.4%), and 1.8% (range 0.8-2.4%) for the 30, 40, and 50 cm phantom sizes. The predicted CTR errors of the four inserts were within 6.4%., Conclusion: The developed framework uses easily obtained HVL measurements to predict renal stone CTRs of different compositions for varied patient sizes. With further refinement, it may help classify NUA subtypes in clinical scans., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Cynthia H. McCollough reports a relationship with Siemens Healthineers that includes: funding grants. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Objective. The integration of proton beamlines with x-ray imaging/irradiation platforms has opened up possibilities for image-guided Bragg peak irradiations in small animals. Such irradiations allow selective targeting of normal tissue substructures and tumours. However, their small size and location pose challenges in designing experiments. This work presents a simulation framework useful for optimizing beamlines, imaging protocols, and design of animal experiments. The usage of the framework is demonstrated, mainly focusing on the imaging part. Approach. The fastCAT toolkit was modified with Monte Carlo (MC)-calculated primary and scatter data of a small animal imager for the simulation of micro-CT scans. The simulated CT of a mini-calibration phantom from fastCAT was validated against a full MC TOPAS CT simulation. A realistic beam model of a preclinical proton facility was obtained from beam transport simulations to create irradiation plans in matRad. Simulated CT images of a digital mouse phantom were generated using single-energy CT (SECT) and dual-energy CT (DECT) protocols and their accuracy in proton stopping power ratio (SPR) estimation and their impact on calculated proton dose distributions in a mouse were evaluated. Main results. The CT numbers from fastCAT agree within 11 HU with TOPAS except for materials at the centre of the phantom. Discrepancies for central inserts are caused by beam hardening issues. The root mean square deviation in the SPR for the best SECT (90 kV/Cu) and DECT (50 kV/Al-90 kV/Al) protocols are 3.7% and 1.0%, respectively. Dose distributions calculated for SECT and DECT datasets revealed range shifts <0.1 mm, gamma pass rates (3%/0.1 mm) greater than 99%, and no substantial dosimetric differences for all structures. The outcomes suggest that SECT is sufficient for proton treatment planning in animals. Significance. The framework is a useful tool for the development of an optimized experimental configuration without using animals and beam time., (Creative Commons Attribution license.)

Purpose: Preliminary dual-energy CT studies have shown that low-energy virtual monoenergetic (VMI) + reconstructions can provide superior image quality compared to standard 120 kV CTA series. The purpose of this study is to evaluate the impact of low-energy VMI reconstructions on quantitative and qualitative image quality, vascular contrast, and diagnostic assessability of the carotid artery in patients undergoing photon-counting CTA examinations., Materials and Methods: A total of 122 patients (67 male) who had undergone dual-source photon-counting CTA scans of the carotid artery were retrospectively analyzed in this study. Standard 120 kV CT images and low-keV VMI series from 40 to 100 keV with an interval of 15 keV were reconstructed. Quantitative analyses included the evaluation of vascular CT numbers, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). CT number measurements were performed in the common, external, and internal carotid arteries. Qualitative analyses were performed by three board-certified radiologists independently using five-point scales to evaluate image quality, vascular contrast, and diagnostic assessability of the carotid artery., Results: Mean attenuation, CNR and SNR values were highest in 40 keV VMI reconstructions (HU, 1362.32 ± 457.81; CNR, 33.19 ± 12.86; SNR, 34.37 ± 12.89) followed by 55-keV VMI reconstructions (HU, 736.94 ± 150.09; CNR, 24.49 ± 7.11; SNR, 26.25 ± 7.34); all three mean values at these keV levels were significantly higher compared with the remaining VMI series and standard 120 kV CT series (HU, 154.43 ± 23.69; CNR, 16.34 ± 5.47; SNR, 24.44 ± 7.14) (p < 0.0001). The qualitative analysis showed the highest rating scores for 55 keV VMI reconstructions followed by 40 keV and 70 keV VMI series with a significant difference compared to standard 120 kV CT images series regarding image quality, vascular contrast, and diagnostic assessability of the carotid artery (all comparisons, p < 0.01)., Conclusions: Low-keV VMI reconstructions at a level of 40-55 keV significantly improve image quality, vascular contrast, and the diagnostic assessability of the carotid artery compared with standard CT series in photon-counting CTA., Competing Interests: Declarations Conflict of interest C.B. and I.Y have received speaking fees from Siemens Healthineers. T.D. has received speaking fees from Bracco and Philips. No support or funding was received for this project. The other authors have no potential conflict of interest to disclose. Ethics approval Approval for this study was received by institutional review board at the University Hospital Frankfurt, with a waiver for informed consent of the patients due to the retrospective nature of our study (approval number: 2023–1708). Consent to participate A waiver for informed consent of the patients was provided by the IRB due to the retrospective and observational nature of our study. Consent to publish All authors provided their consent for publication of this study. The authors affirm that human research participants provided informed consent for publication of the radiological images., (© 2024. The Author(s).)

Objective: The purpose of this study was to investigate the impact of different low-energy virtual monochromatic images (VMIs) in dual-energy CT on the performance of radiomics models for predicting muscle invasive status in bladder cancer (BCa)., Materials and Methods: A total of 127 patients with pathologically proven muscle-invasive BCa (n = 49) and non-muscle-invasive BCa (n = 78) were randomly allocated into the training and test cohorts at a ratio of 7:3. Feature extraction was performed on the venous phase images reconstructed at 40, 50, 60 and 70-keV (single-energy analysis) or in combination (multi-energy analysis). Recursive feature elimination (RFE) and the least absolute shrinkage and selection operator (LASSO) were employed to select the most relevant features associated with BCa. Models were built using a support vector machine (SVM) classifier. Diagnostic performance was assessed through receiver operating characteristic curves, evaluating sensitivity, specificity, accuracy, precision, and the area-under-the curve (AUC) values., Results: In the test cohort, the multi-energy model achieved the best diagnostic performance with AUC, sensitivity, specificity, accuracy, and precision of 0.917, 0.800, 0.833, 0.821, and 0.750, respectively. Conversely, the single-energy model exhibited lower AUC and sensitivity in predicting the muscle invasion status., Conclusions: By combining information from VMIs of various energies, the multi-energy model displays superior performance in preoperatively predicting the muscle invasion status of bladder cancer., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objectives: To develop and validate a quantitative model for predicting serosal invasion based on multi-parameters in preoperative dual-energy CT (DECT)., Materials and Methods: A total of 342 LAGC patients who underwent gastrectomy and DECT from six centers were divided into one training cohort (TC), and two validation cohorts (VCs). Dual-phase enhanced DECT-derived iodine concentration (IC), water concentration, and monochromatic attenuation of lesions, along with clinical information, were measured and collected. The independent predictors among these characteristics for serosal invasion were screened with Spearman correlation analysis and logistic regression (LR) analysis. A quantitative model was developed based on LR classifier with fivefold cross-validation for predicting the serosal invasion in LAGC. We comprehensively tested the model and investigated its value in survival analysis., Results: A quantitative model was established using IC, 70 keV, 100 keV monochromatic attenuations in the venous phase, and CT-reported T4a, which were independent predictors of serosal invasion. The proposed model had the area-under-the-curve (AUC) values of 0.889 for TC and 0.860 and 0.837 for VCs. Subgroup analysis showed that the model could well discriminate T3 from T4a groups, and T2 from T4a groups in all cohorts (all p < 0.001). Besides, disease-free survival (DFS) (TC, p = 0.015; and VC1, p = 0.043) could be stratified using this quantitative model., Conclusion: The proposed quantitative model using multi-parameters in DECT accurately predicts serosal invasion for LAGC and showed a significant correlation with the DFS of patients., Critical Relevance Statement: This quantitative model from dual-energy CT is a useful tool for predicting the serosal invasion of locally advanced gastric cancer., Key Points: Serosal invasion is a poor prognostic factor in locally advanced gastric cancer that may be predicted by DECT. DECT quantitative model for predicting serosal invasion was significantly and positively correlated with pathologic T stages. This quantitative model was associated with patient postoperative disease-free survival., (© 2024. The Author(s).)

Background: To explore the value of dual-energy computed tomography (DECT) in differentiating pathological subtypes and the expression of immunohistochemical markers Ki-67 and thyroid transcription factor 1 (TTF-1) in patients with non-small cell lung cancer (NSCLC)., Methods: Between July 2022 and May 2024, patients suspected of lung cancer who underwent two-phase contrast-enhanced DECT were prospectively recruited. Whole-tumor volumetric and conventional spectral analysis were utilized to measure DECT parameters in the arterial and venous phase. The DECT parameters model, clinical-CT radiological features model, and combined prediction model were developed to discriminate pathological subtypes and predict Ki-67 or TTF-1 expression. Multivariate logistic regression analysis was used to identify independent predictors. The diagnostic efficacy was assessed by the area under the receiver operating characteristic curve (AUC) and compared using DeLong's test., Results: This study included 119 patients (92 males and 27 females; mean age, 63.0 ± 9.4 years) who was diagnosed with NSCLC. When applying the DECT parameters model to differentiate between adenocarcinoma and squamous cell carcinoma, ROC curve analysis indicated superior diagnostic performance for conventional spectral analysis over volumetric spectral analysis (AUC, 0.801 vs. 0.709). Volumetric spectral analysis exhibited higher diagnostic efficacy in predicting immunohistochemical markers compared to conventional spectral analysis (both P < 0.05). For Ki-67 and TTF-1 expression, the combined prediction model demonstrated optimal diagnostic performance with AUC of 0.943 and 0.967, respectively., Conclusions: The combined predictive model based on volumetric quantitative analysis in DECT offers valuable information to discriminate immunohistochemical expression status, facilitating clinical decision-making for patients with NSCLC., (© 2024. The Author(s).)

Background: Our study aims to provide an overview of existing evidence regarding the image quality of dual-energy CT (DECT) employing reduced contrast media (CM) volumes, in comparison to single-energy CT (SECT) with standard CM loads. The advantages, indications, and possible applications of DECT were investigated from the perspective of providing better patient care, minimizing CM volume and managing CM shortage. Methods : In this systematic review (PRISMA methodology), PubMed and WOS were searched from January 2010 to January 2023 by two independent reviewers. The scan and CM characteristics, radiation dose, and results of quantitative (contrast to noise ratio, CNR, and signal to noise ratio, SNR) and qualitative assessment of image quality were collected. Sixty non-duplicated records eligible for full-text screening were examined. Results : Finally, 22 articles (1818 patients) were included. The average CM reduction with DECT ranged between 43.4 ± 11%. Despite the wide variability in CT scan protocols, no differences were found in radiation doses between DECT and SECT. Conclusions: DECT scanners allow the employment of lower CM volumes with equal or better image quality evaluated by quantitative and qualitative analyses and similar dose radiation compared to SECT. Using image reconstructions at low monochromatic energy levels, DECT increases iodine conspicuity and attenuation contributing to CM containment measures.

Applications of computed tomography (CT) in arthritis imaging have rapidly expanded in recent years due to ongoing technical developments. Dual-energy CT (DECT) has become indispensable in clinical practice, particularly for diagnosing gouty arthritis and assessing bony structural changes. Technological innovations such as low-dose CT and state-of-the-art reconstruction algorithms reduce radiation exposure while maintaining image quality and short acquisition times. This review explores the growing role of CT in arthritis imaging. Recent innovations have extended DECT's utility beyond gout diagnosis to the detection of inflammatory changes in various arthritic conditions. Postprocessing techniques such as the generation of subtraction images and iodine maps provide valuable insights into tissue perfusion and inflammatory activity, crucial for arthritis management. DECT can distinguish calcium from uric acid crystals, facilitating the differential diagnosis of various crystal arthropathies in a variety of clinical settings. This ability is particularly valuable in distinguishing between different clinical conditions in patients with inflammatory joint changes within a single imaging examination. Moreover, the advent of four-dimensional CT promises a better assessment of dynamic joint instabilities and ligament injuries, especially in the wrist. Overall, DECT offers a comprehensive approach to arthritis imaging, from the detection of structural changes to the assessment of active inflammation in joints and tendons. Continuous advances in CT technology, including photon-counting CT, hold promise for further improving diagnostic accuracy and expanding the role of CT in arthritis imaging and therapy monitoring., (© The Author(s), 2024.)

Multi-energy computed tomography (MECT) offers the opportunity for advanced visualization, detection, and quantification of select elements (e.g., iodine) or materials (e.g., fat) beyond the capability of standard single-energy computed tomography (CT). However, the use of MECT requires careful consideration as substantially different hardware and software approaches have been used by manufacturers, including different sets of user-selected or hidden parameters that affect the performance and radiation dose of MECT. Another important consideration when designing MECT protocols is appreciation of the specific tasks being performed; for instance, differentiating between two different materials or quantifying a specific element. For a given task, it is imperative to consider both the radiation dose and task-specific image quality requirements. Development of a quality control (QC) program is essential to ensure the accuracy and reproducibility of these MECT applications. Although standard QC procedures have been well established for conventional single-energy CT, the substantial differences between single-energy CT and MECT in terms of system implementations, imaging protocols, and clinical tasks warrant QC tests specific to MECT. This task group was therefore charged with developing a systematic QC program designed to meet the needs of MECT applications. In this report, we review the various MECT approaches that are commercially available, including information about hardware implementation, MECT image types, image reconstruction, and postprocessing techniques that are unique to MECT. We address the requirements for MECT phantoms, review representative commercial MECT phantoms, and offer guidance regarding homemade MECT phantoms. We discuss the development of MECT protocols, which must be designed carefully with proper consideration of MECT technology, imaging task, and radiation dose. We then outline specific recommended QC tests in terms of general image quality, radiation dose, differentiation and quantification tasks, and diagnostic and therapeutic applications., (© 2024 American Association of Physicists in Medicine.)

A 74-year-old man was admitted to our emergency department following minor trauma. Plain radiographs and standard computed tomography (CT) scans revealed no signs of fractures. Subsequently, virtual noncalcium (VNCa) images were reconstructed, showing a linear area of bone marrow edema (BME) resembling a femoral neck fracture. Magnetic resonance imaging (MRI) was performed to confirm the presence of BME and an associated intraspongious fracture. In an emergency setting, dual-energy CT (DECT) and VNCa images can successfully identify occult femoral fractures, especially in patients with mild symptoms and minor trauma, thereby preventing misdiagnosis., (© 2024 The Author(s). Journal of Clinical Ultrasound published by Wiley Periodicals LLC.)

Purpose: To non-invasively quantify pancreatic fibrosis and grade severity of chronic pancreatitis (CP) on dual-energy CT (DECT) and multiparametric MRI (mpMRI)., Methods: We included 72 patients (mean age:30years; 59 men) with suspected or confirmed CP from December 2019 to December 2021 graded as equivocal(n = 20), mild(n = 18), and moderate-marked(n = 34) using composite imaging and endoscopic ultrasound criteria. Study patients underwent multiphasic DECT and mpMRI of the abdomen. Normalized iodine concentration(NIC) and fat fraction(FF) on 6-minute delayed DECT, and T1 relaxation time(T1Rt), extracellular volume fraction(ECVf), intravoxel incoherent motion-based perfusion fraction(PF), and magnetization transfer ratio(MTR) on mpMRI of pancreas were compared. 20 renal donors(for DECT) and 20 patients with renal mass(for mpMRI) served as controls., Results: NIC of pancreas in controls and progressive grades of CP were 0.24 ± 0.05, 0.80 ± 0.18, 1.06 ± 0.23, 1.40 ± 0.36, FF were 9.28 ± 5.89, 14.19 ± 5.29, 17.31 ± 5.99, 29.32 ± 12.22, T1Rt were 590.11 ± 61.13, 801.93 ± 211.01, 1006.79 ± 352.18, 1388.01 ± 312.23ms, ECVf were 0.07 ± 0.03, 0.30 ± 0.12, 0.41 ± 0.12, 0.53 ± 0.13, PF were 0.38 ± 0.04, 0.28 ± 0.07, 0.25 ± 0.09, 0.21 ± 0.05 and MTR were 0.12 ± 0.03, 0.15 ± 0.06, 0.21 ± 0.07, 0.26 ± 0.06, respectively. There were significant differences for all quantitative parameters between controls and mild CP; for NIC, PF, and ECVf between controls and progressive CP grades (p < 0.05). Area under curve for NIC, FF, T1Rt, ECVf, PF, and MTR in differentiating controls and mild CP were 1.00, 0.86, 0.95, 1.00, 0.90 and 0.84 respectively and for NIC, FF, ECVf and PF in differentiating controls and equivocal CP were 1.00, 0.76, 0.95 and 0.92 respectively., Conclusion: DECT and mpMRI were useful in quantifying pancreatic fibrosis and grading the severity of CP. NIC was the most accurate marker., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Current CT oral contrast agents improve the conspicuity of and confidence in bowel and peritoneal findings in many clinical scenarios, particularly for outpatient and oncologic abdominopelvic imaging. Yet, existing positive and neutral oral contrast agents may diminish the detectability of certain radiologic findings, frequently in the same scans in which the oral contrast agent improves the detectability of other findings. With ongoing improvements in CT technology, particularly multienergy CT, opportunities are opening for new types of oral contrast agents to further improve anatomic delineation and disease detection using CT. The CT signal of new dark oral contrast agents and of new high- Z oral contrast agents promises to combine the strengths of both positive and neutral oral CT contrast agents by providing distinct CT appearances in comparison with bodily tissues, iodinated IV contrast agents, and other classes of new CT contrast agents. High- Z oral contrast agents will unlock previously inaccessible capabilities of multienergy CT, particularly photon-counting detector CT, for differentiating simultaneously administered IV and oral contrast agents; this technique will allow generation of rich 3D, intuitive, perfectly coregistered, high-resolution image sets with individual contrast agent "colors" that provide compelling clarity for intertwined intraabdominal anatomy and disease processes.

Objective: To assess the value of material density (MD) images generated from a rapid kilovoltage-switching dual-energy CT (rsDECT) in early detection of peritoneal carcinomatosis (PC)., Materials and Methods: Thirty patients (60 ± 13 years; 24 women) with PC detected on multiple abdominal DECT scans were included. Four separate DECTs with varying findings of PC from each patient were used for qualitative/quantitative analysis, resulting in a total of 120 DECT scans (n = 30 × 4). Three radiologists independently reviewed DECT images (65 keV alone and 65 keV + MD) for diagnosis of PC (diagnostic confidence, lesion conspicuity, sharpness/delineation and image quality) using a 5-point Likert scale. Quantitative estimation of contrast-to-noise ratio (CNR) was done. Wilcoxon signed-rank test and Odds ratio calculation were used to compare between the two protocols. Inter-observer agreement was evaluated using Kappa coefficient analysis. P values < 0.05 were considered statistically significant., Results: 65 keV + MD images showed a slightly higher sensitivity (89%[95%CI:84,92]) for PC detection compared with 65 keV images alone without statistical significance (84%[95%CI:78,88], p = 0.11) with the experienced reader showing significant improvement (98%[95%CI:93,100] vs. 90%[95%CI:83,94], p = 0.02). On a per-patient basis, use of MD images allowed earlier diagnosis for PC in an additional 13-23% of patients. On sub-group analysis, earlier diagnosis of PC was particularly beneficial in patients with BMI ≤ 29.9 kg/m 2 . 65 keV + MD images showed higher diagnostic confidence, lesion conspicuity, and lesion sharpness for the experienced reader (p < 0.001). CNR was higher in MD images (1.7 ± 0.5) than 65 keV images (0.1 ± 0.02, p < 0.001). All readers showed moderate interobserver agreement for determining PC by both protocols (κ = 0.58 and κ = 0.47)., Conclusion: MD images allow earlier and improved detection of PC with the degree of benefit varying based on reader experience and patient body habitus., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To determine the efficacy and safety of virtual unenhanced imaging by comparing the attenuation values of virtual and true unenhanced images acquired using third-generation dual-source dual-energy computed tomography (dsDECT)., Methods: Single-energy non-contrast and dual-energy arterial and venous phase images of 97 patients who underwent triphasic abdominal computed tomography (CT) were included in this retrospective study. Virtual unenhanced images were generated for the arterial (a) and venous (v) phases using two dsDECT algorithms. The attenuation values were measured on the true and virtual unenhanced images of the liver, spleen, kidney, gallbladder, paraspinal muscle, aorta, subcutaneous fat, retroperitoneal fat, and renal cysts., Results: A statistically significant difference was observed between the attenuation values ​​of true and virtual unenhanced images for all tissues (p < 0.001-0.025), except the venous phase virtual unenhanced images of the kidney, renal cysts, and gallbladder (p = 0.061-0.325). The proportion of cases with differences of ≥ 10 Hounsfield unit (HU) in the attenuation values between the virtual and true unenhanced images ranged from 3% to 8% for renal parenchyma, renal cysts, and gallbladder using this algorithm; however, this proportion was up to 90% for adipose tissue. No significant correlation was observed between the body mass index and attenuation differences between the true and virtual unenhanced images, except for those of the aorta and paraspinal muscle., Conclusion: Virtual unenhanced images acquired using third-generation dsDECT cannot replace true unenhanced images in clinical practice owing to the difference between the attenuation values and variability of attenuation between true and virtual unenhanced images., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Gazi University Ethics Committee of Clinical Research issued approval 2019/22. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Yalçın et al.)

In recent years, computed tomography (CT) has undergone a number of developments to improve radiological care. The most recent major innovation has been the development of photon-counting detectors. By comparison with the energy-integrating detectors traditionally used in CT, these detectors offer better dose efficiency, eliminate electronic noise, improve spatial resolution and have intrinsic spectral sensitivity. These detectors also allow the energy of each photon to be counted, thus improving the sampling of the X-ray spectrum in multiple energy bins, to better distinguish between photoelectric and Compton attenuation coefficients, resulting in better spectral images and specific color K-edge images. The purpose of this article was to make the reader more familiar with the basic principles and techniques of new photon-counting CT systems equipped with photon-counting detectors and also to describe the currently available devices that could be used in clinical practice., Competing Interests: Declaration of competing interest The authors have no relevant conflict of interest to disclose in relation with this article., (Copyright © 2024 The Author(s). Published by Elsevier Masson SAS.. All rights reserved.)

Objective: To evaluate the prediction value of Dual-energy CT (DECT)-based quantitative parameters and radiomics model in preoperatively predicting muscle invasion in bladder cancer (BCa)., Materials and Methods: A retrospective study was performed on 126 patients with BCa who underwent DECT urography (DECTU) in our hospital. Patients were randomly divided into training and test cohorts with a ratio of 7:3. Quantitative parameters derived from DECTU were identified through univariate and multivariate logistic regression analysis to construct a DECT model. Radiomics features were extracted from the 40, 70, 100 keV and iodine-based material-decomposition (IMD) images in the venous phase to construct radiomics models from individual and combined images using a support vector machine classifier, and the optimal performing model was chosen as the final radiomics model. Subsequently, a fusion model combining the DECT parameters and the radiomics model was established. The diagnostic performances of all three models were evaluated through receiver operating characteristic (ROC) curves and the clinical usefulness was estimated using decision curve analysis (DCA)., Results: The normalized iodine concentration (NIC) in DECT was an independent factor in diagnosing muscle invasion of BCa. The optimal multi-image radiomics model had predictive performance with an area-under-the-curve (AUC) of 0.867 in the test cohort, better than the AUC = 0.704 with NIC. The fusion model showed an increased level of performance, although the difference in AUC (0.893) was not statistically significant. Additionally, it demonstrated superior performance in DCA. For lesions smaller than 3 cm, the fusion model showed a high predictive capability, achieving an AUC value of 0.911. There was a slight improvement in model performance, although the difference was not statistically significant. This improvement was observed when comparing the AUC values of the DECT and radiomics models, which were 0.726 and 0.884, respectively., Conclusion: The proposed fusion model combing NIC and the optimal multi-image radiomics model in DECT showed good diagnostic capability in predicting muscle invasiveness of BCa., (© 2024. The Author(s).)

Background/Objectives: Fragility fractures of the pelvis (FFP) are characterized by inadequate trauma to a structurally compromised bone, primarily in osteoporosis. Conventional CT studies can be inadequate in identifying FFPs. An MRI of the pelvis is considered the gold standard in diagnosing FFPs. Spectral CT or Dual-Energy CT may have comparable diagnostic accuracy. It provides additional insights into associated bone marrow edema. The aim of this prospective monocentric study is to evaluate the diagnostic accuracy of Spectral CT compared to the gold standard MRI in diagnosing FFP. Methods: Over a 2-year period, patients presenting in the emergency department with clinical suspicion of an FFP were consecutively included. They underwent Spectral CT (GE Revolution 16 cm GSI) upon admission, followed by an MRI. The gold standard for diagnosing FFP is pelvic MRI, showing sensitivity and specificity ranging from 97% to 100%. The acquired images were evaluated and classified using the osteoporotic fractures of the pelvis (OFP) classification. Results: Compared to the reference test, which was the MRI pelvis, the sensitivity of the CT pelvis was determined to be 86.8 (95% confidence interval (CI) 71.9-95.6%) with a specificity of 84.6% (95% CI: 54.6-98.1%, p = 0.453). Spectral CT could identify an additional FFP correctly, exhibiting a sensitivity of 89.5% (95% CI: 75.2-97.1%, p = 0.688), while maintaining the same specificity as the conventional CT. The inter-rater reliability assessment for Spectral CT, conducted by four independent raters, resulted in a Fleiss' Kappa value of 0.516 (95% CI: 0.450-0.582, p < 0.001). Conclusion: The sensitivity of Spectral CT in the detection of pelvic ring fragility fractures shows a slightly lower sensitivity compared to MRI. There were no statistically significant differences observed when compared to conventional CT or MRI. In conclusion, Spectral CT may be beneficial in distinguishing FFP, particularly in cases where a definitive diagnosis is uncertain. Level of Evidence: II.

Dual-energy computed tomography (DECT) is an advanced imaging technique that acquires data using two distinct X-ray energy spectra, typically at 80 and 140 kVp, to differentiate materials based on their atomic number and electron density. This capability allows for the enhanced visualisation of various pathologies, including bone marrow oedema (BMO), by providing high-resolution images with notable energy spectral separation while maintaining radiation doses comparable to conventional CT. DECT's ability to create colour-coded virtual non-calcium (VNCa) images has proven particularly valuable in detecting traumatic bone marrow lesions (BMLs) and subtle fractures, offering a reliable alternative or complement to MRI. DECT has emerged as a significant tool in the detection and characterisation of bone marrow pathologies, especially in traumatic injuries. Its ability to generate high-resolution images and distinguish between different tissue types makes it a valuable asset in clinical diagnostics. With its comparable diagnostic accuracy to MRI and the added advantage of reduced examination time and increased availability, DECT represents a promising advancement in the imaging of BMO and related conditions., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Institute of Radiology.)

Rationale and Objectives: To evaluate the value of dual-energy CT (DECT) virtual noncalcium (VNCa) images in the diagnosis of wrist bone marrow edema (BME) in patients with rheumatoid arthritis (RA)., Materials and Methods: 43 patients with wrist involvement in active RA prospectively underwent DECT and MRI. Functional DECT images reconstruction yielded VNCa images. MRI served as the reference standard for diagnosing BME. BME diagnosis differences between VNCa images and MRI were compared. Differences in CT values between BME and normal bone marrow were assessed. The optimal CT value for detecting BME in VNCa images was determined through ROC curve analysis. The correlation between VNCa images scores and RA disease activity was evaluated., Results: There was a high agreement between VNCa images and MRI in diagnosing BME (Kappa=0.831). VNCa images showed a significant difference in CT values between BME and normal bone marrow (P < 0.001). A cut-off value of - 54.8 HU yielded a sensitivity, specificity, and accuracy of 90.72%, 94.30%, and 93.33%, respectively, for detecting BME on VNCa images. The area under the ROC curve was 0.937 for distinguishing BME from normal bone marrow. Conventional CT images showed no statistically significant difference (P = 0.174) in CT values between BME and normal bone marrow. The VNCa images BME scores were positively correlated with RA disease activity (r = 0.399)., Conclusion: The DECT VNCa technique demonstrates its potential for diagnosing wrist BME in patients with RA and provides a valuable tool for assessing disease activity in RA., Important Findings: The DECT VNCa technique has the ability to distinguish between BME and normal bone marrow. The VNCa images BME scores were positively correlated with the disease activity in RA., Competing Interests: Declaration of Competing Interest We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Dual-energy computed tomography (DECT) has emerged as a transformative tool in the past decade. Initially employed in gout within the field of rheumatology to distinguish and quantify monosodium urate crystals through its dual-material discrimination capability, DECT has since broadened its clinical applications. It now encompasses various rheumatic diseases, employing advanced techniques such as bone marrow edema assessment, iodine mapping, and collagen-specific imaging. This review article aims to examine the unique characteristics of DECT, discuss its strengths and limitations, illustrate its applications for accurately evaluating various rheumatic diseases in clinical practice, and propose future directions for DECT in rheumatology., Competing Interests: Disclosure The authors have no conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)