Search

Purpose: To demonstrate the feasibility of simultaneous dual‐contrast imaging in a large animal using a newly developed dual‐source energy‐integrating detector (EID)‐based multi‐energy computed tomography (MECT) system. Methods: Two imaging tasks that may have potential clinical applications were investigated: head/neck (HN) CT angiography (CTA)/CT venography (CTV) with iodine and gadolinium, and small bowel imaging with iodine and bismuth in domestic swine. Dual‐source X‐ray beam configurations of 70 kV + Au120/Sn120 kV and 70 kV + Au140/Sn140 kV were used for the HN‐CTA/CTV and small bowel imaging studies, respectively. A test bolus scan was performed for each study. The regions of interest (ROIs) in the carotid artery and jugular vein for HN‐CTA/CTV imaging and abdominal aorta for small bowel imaging were used to determine the time‐attenuation curves, based on which the timing for contrast injection and the CT scan was determined. In the HN‐CTA/CTV study, an MECT scan was performed at the time point corresponding to the optimal arterial enhancement by iodine and the optimal venous enhancement by gadolinium. In the small bowel imaging study, an MECT scan was performed at the optimal time point to simultaneously capture the mesenteric arterial enhancement of iodine and the enteric enhancement of bismuth. Image‐based material decomposition was performed to decompose different materials for each study. To quantitatively characterize contrast material separation and misclassification, two ROIs on left common carotid artery and left internal jugular vein in HN‐CTA/CTV imaging and three ROIs on superior mesenteric artery, ileal lumen, and collapsed ileum (ileal wall) in small bowel imaging were placed to measure the mean concentration values and the standard deviations. Results: In the HN‐CTA/CTV study, common carotid arteries containing iodine and internal/external jugular veins containing gadolinium were clearly delineated from each other. Fine vessels such as cephalic veins and branches of external jugular veins were noticeable but clear visualization was hindered by image noise in gadolinium‐specific (CTV) images, as reviewed by a neuroradiologist. In the small bowel imaging study, the mesenteric arteries and collapsed bowel wall containing iodine and the small bowel loops containing bismuth were clearly distinctive from each other in the iodine‐ and bismuth‐specific images after material decomposition, as reviewed by an abdominal radiologist. Quantitative analyses showed that the misclassifications between the two contrast materials were less than 1.7 and 0.1 mg/ml for CTA/CTV and small bowel imaging studies, respectively. Conclusions: Feasibility of simultaneous CTA/CTV imaging in head and neck with iodine and gadolinium and simultaneous imaging of arterial and enteric phases of small bowel with iodine and bismuth, using a dual‐source EID‐MECT system, was demonstrated in a swine study. Compared to iodine and gadolinium in CTA/CTV, better delineation and classification of iodine and bismuth in small bowel imaging were achieved mainly due to wider separation between the corresponding two K‐edge energies. [ABSTRACT FROM AUTHOR]

We assessed the correlation between liver fat percentage using dual-energy CT (DECT) and Hounsfield unit (HU) measurements in contrast and non-contrast CT. This study included 177 patients in two patient groups: Group A (n = 125) underwent whole body non-contrast DECT and group B (n = 52) had a multiphasic DECT including a conventional non-contrast CT. Three regions of interest were placed on each image series, one in the left liver lobe and two in the right to measure Hounsfield Units (HU) as well as liver fat percentage. Linear regression analysis was performed for each group as well as combined. Receiver operating characteristic (ROC) curve was generated to establish the optimal fat percentage threshold value in DECT for predicting a non-contrast threshold of 40 HU correlating to moderate-severe liver steatosis. We found a strong correlation between fat percentage found with DECT and HU measured in non-contrast CT in group A and B individually (R2 = 0.81 and 0.86, respectively) as well as combined (R2 = 0.85). No significant difference was found when comparing venous and arterial phase DECT fat percentage measurements in group B (p = 0.67). A threshold of 10% liver fat found with DECT had 95% sensitivity and 95% specificity for the prediction of a 40 HU threshold using non-contrast CT. In conclusion, liver fat quantification using DECT shows high correlation with HU measurements independent of scan phase. [ABSTRACT FROM AUTHOR]

Purpose: Dual-energy computed tomography (DECT) has been used to derive relative stopping power (RSP) maps by obtaining the energy dependence of photon interactions. The DECT-derived RSP maps could potentially be compromised by image noise levels and the severity of artifacts when using physics-based mapping techniques. This work presents a noise-robust learning-based method to predict RSP maps from DECT for proton radiation therapy. Materials and Methods: The proposed method uses a residual attention cycle-consistent generative adversarial network to bring DECT-to-RSP mapping close to a 1-to-1 mapping by introducing an inverse RSP-to-DECT mapping. To evaluate the proposed method, we retrospectively investigated 20 head-and-neck cancer patients with DECT scans in proton radiation therapy simulation. Ground truth RSP values were assigned by calculation based on chemical compositions and acted as learning targets in the training process for DECT datasets; they were evaluated against results from the proposed method using a leave-one-out cross-validation strategy. Results: The predicted RSP maps showed an average normalized mean square error of 2.83% across the whole body volume and an average mean error less than 3% in all volumes of interest. With additional simulated noise added in DECT datasets, the proposed method still maintained a comparable performance, while the physics-based stoichiometric method suffered degraded inaccuracy from increased noise level. The average differences from ground truth in dose volume histogram metrics for clinical target volumes were less than 0.2 Gy for D95% and Dmax with no statistical significance. Maximum difference in dose volume histogram metrics of organs at risk was around 1 Gy on average. Conclusion: These results strongly indicate the high accuracy of RSP maps predicted by our machine-learning–based method and show its potential feasibility for proton treatment planning and dose calculation.

Pulmonary nodules (PNs) arising in the lung transplant recipient pose a diagnostic challenge for providers. Conventional computed tomography (CT) has improved our ability to detect PNs in this population, but establishing a confident diagnosis with imaging alone remains difficult. Dual-energy spectral detector CT is a novel, emerging technology that provides insight into the radiographic behavior of PNs, and has potential in differentiating benign from malignant morphologies. Herein, we report a case of a PN in a lung transplant recipient whose initial diagnostic work-up was inconclusive, but then had the diagnosis rendered using a spectral detector CT.

Abstract Background To investigate the correlation between iodine-related attenuation in contrast-enhanced dual-energy computed tomography (DE-CT) and the postoperative prognosis of surgically resected solid-type small-sized lung cancers. Methods We retrospectively reviewed the DE-CT findings and postoperative course of solid-type lung cancers ≤3 cm in diameter. After injection of iodinated contrast media, arterial phases were scanned using 140-kVp and 80-kVp tube voltages. Three-dimensional iodine-related attenuation (3D-IRA) of primary tumors at the arterial phase was computed using the “lung nodule” application software. The corrected 3D-IRA normalized to the patient’s body weight and contrast medium concentration was then calculated. Results A total of 120 resected solid-type lung cancers ≤3 cm in diameter were selected for analysis (82 males and 38 females; mean age, 67 years). During the observation period (median, 47 months), 32 patients showed postoperative recurrence. Recurrent tumors had significantly lower 3D-IRA and corrected 3D-IRA at early phase compared to non-recurrent tumors (p = 0.046 and p = 0.027, respectively). The area under the receiver operating characteristic curve for postoperative recurrence was 0.624 for the corrected 3D-IRA at early phase (p = 0.025), and the cutoff value was 5.88. Kaplan–Meier curves for disease-free survival indicated that patients showing tumors with 3D-IRA > 5.88 had a significantly better prognosis than those with tumors showing 3D-IRA

Abstract Background Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and Ki67 are the most useful immunohistochemical biomarkers of invasive breast cancer. The purpose of this study is to investigate the possibility of quantitative parameters derived from dual-energy CT (DECT) to discriminate immunohistochemical biomarkers of invasive breast cancer. Methods This prospective study enrolled 120 patients with invasive breast cancer who underwent preoperative contrast-enhanced DECT for staging purposes from June 2019 to January 2020. DECT quantitative parameters, including normalized iodine concentration (NIC), the slope of the spectral Hounsfield unit curve (λHu), and the normalized effective atomic number (nZeff), were obtained from reconstructed images. DECT quantitative parameters were compared with the expression status, and the correlations with the value of immunohistochemical biomarkers were evaluated. Inter-observer reproducibility analysis was performed to assess the measurement reproducibility of quantitative parameters. The diagnostic performance of the quantitative parameters was analyzed by receiver operating characteristic curve. Results The ER-negative group tended to display higher venous phase NIC and nZeff compared with the ER-positive group (individually, p = 0.003, 0.011; area under the curve [AUC] of 0.65, 0.60). The PR-negative group demonstrated higher arterial and venous phase NIC compared with the PR-positive group (individually, p = 0.022, 0.005; AUC of 0.63, 0.65). NIC was correlated negatively with the value of ER and PR expression (r = − 0.175 ~ − 0.265, p = 0.002 ~ 0.042). The HER2-positive group tended to display higher venous phase nZeff than the HER2-negative group (p = 0.022; AUC of 0.59). The Ki67 high-proliferation group demonstrated higher arterial phase, venous phase NIC and nZeff than the Ki67 low-proliferation group (p

Abstract Background The purpose of this study was to analyze if the use of texture analysis on spectral detector CT (SDCT)-derived iodine maps (IM) in addition to conventional images (CI) improves lung nodule differentiation, when being applied to a k-nearest neighbor (KNN) classifier. Methods 183 cancer patients who underwent contrast-enhanced, venous phase SDCT of the chest were included: 85 patients with 146 benign lung nodules (BLN) confirmed by either prior/follow-up CT or histopathology and 98 patients with 425 lung metastases (LM) verified by histopathology, 18F-FDG-PET-CT or unequivocal change during treatment. Semi-automatic 3D segmentation of BLN/LM was performed, and volumetric HU attenuation and iodine concentration were acquired. For conventional images and iodine maps, average, standard deviation, entropy, kurtosis, mean of the positive pixels (MPP), skewness, uniformity and uniformity of the positive pixels (UPP) within the volumes of interests were calculated. All acquired parameters were transferred to a KNN classifier. Results Differentiation between BLN and LM was most accurate, when using all CI-derived features combined with the most significant IM-derived feature, entropy (Accuracy:0.87; F1/Dice:0.92). However, differentiation accuracy based on the 4 most powerful CI-derived features performed only slightly inferior (Accuracy:0.84; F1/Dice:0.89, p=0.125). Mono-parametric lung nodule differentiation based on either feature alone (i.e. attenuation or iodine concentration) was poor (AUC=0.65, 0.58, respectively). Conclusions First-order texture feature analysis of contrast-enhanced staging SDCT scans of the chest yield accurate differentiation between benign and metastatic lung nodules. In our study cohort, the most powerful iodine map-derived feature slightly, yet insignificantly increased classification accuracy compared to classification based on conventional image features only.

ObjectivesTo build a radiomics model and combined model based on dual-energy CT (DECT) for diagnosing serosal invasion in gastric adenocarcinoma.Materials and methods231 gastric adenocarcinoma patients were enrolled and randomly divided into a training (n = 132), testing (n = 58), and independent validation (n = 41) cohort. Radiomics features were extracted from the rectangular ROI of the 120-kV equivalent mixed images and iodine map (IM) images in the venous phase of DECT, which was manually delineated perpendicularly to the gastric wall in the deepest location of tumor infiltration, including the peritumoral adipose tissue within 5 mm outside the serosa. The random forest algorithm was used for radiomics model construction. Traditional features were collected by two radiologists. Univariate and multivariate logistic regression was used to construct the clinical model and combined model. The diagnostic efficacy of the models was evaluated using ROC curve analysis and compared using the Delong’s test. The calibration curves were used to evaluate the calibration performance of the combined model.ResultsBoth the radiomics model and combined model showed high efficacy in diagnosing serosal invasion in the training, testing and independent validation cohort, with AUC of 0.90, 0.90, and 0.85 for radiomics model; 0.93, 0.93, and 0.89 for combined model. The combined model outperformed the clinical model (AUC: 0.76, 0.76 and 0.81).ConclusionThe radiomics model and combined model constructed based on tumoral and peritumoral radiomics features derived from DECT showed high diagnostic efficacy for serosal invasion in gastric adenocarcinoma.

Objective: To investigate the effect of radiomics models obtained from dual-energy CT (DECT) material decomposition images and virtual monoenergetic images (VMIs) in predicting the pathological grading of bladder urothelial carcinoma (BUC)., Materials and Methods: A retrospective analysis of preoperative DECT examination was conducted on 112 patients diagnosed with BUC. This cohort included 76 cases of high-grade urothelial carcinoma and 36 cases of low-grade urothelial carcinoma. DECT can provide material decomposition images of venous phase Iodine maps and Water maps based on the differences in attenuation of substances, as well as VMIs at 40 to 140 keV (interval 10 keV). A total of 13 image sets were obtained, and radiomics features were extracted and analyzed from each set to achieve preoperative prediction of BUC. The best features related to BUC were identified by recursive feature elimination (RFE), the Minimum Redundancy Maximum Relevance (mRMR), and the Least Absolute Shrinkage and Selection Operator (LASSO) in order. A five-fold cross-validation method was used to divide the samples into training and testing sets, and models for pathological prediction of BUC grading were constructed by a random forest (RF) classifier. Receiver operating curves (ROC) were plotted to evaluate the performance of 13 models obtained from each image set., Results: Despite the notable differences in the best radiomics features chosen from each image set, all the features selected from 40 to 100 keV VMIs included the Dependence Variance of the GLDM feature set. There were no statistically significant differences in the area under the curve (AUC) between the training set and the testing set for all 13 models. In the testing set, the AUCs of the models established through 40 keV to 140 keV (interval of 10 keV) image sets were 0.895, 0.874, 0.855, 0.889, 0.841, 0.868, 0.852, 0.847, 0.889, 0.887 and 0.863 respectively. The AUCs for the models established using the Iodine maps and Water maps image sets were 0.873 and 0.852, respectively., Conclusion: Despite the differences in the selected radiomic features from DECT multi-parameter images, the performance of radiomics models in predicting the pathological grading of BUC was not affected by the variations in the types of images used for model training., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

To assess the ability of dual-energy CT (DECT) to separate intravenous contrast of bowel wall from intraluminal contrast, we scanned 16 rabbits on a clinical DECT scanner: n = 3 using only iodinated intravenous contrast, and n = 13 double-contrast enhanced scans using iodinated intravenous contrast and experimental enteric non-iodinated contrast agents in the bowel lumen (five bismuth, four tungsten, and four tantalum based). Representative image pairs from conventional CT images and DECT iodine density maps of small bowel (116 pairs from 232 images) were viewed by four abdominal imaging attending radiologists to independently score each comparison pair on a visual analog scale (-100 to +100%) for (1) preference in small bowel wall visualization and (2) preference in completeness of intraluminal enteric contrast subtraction. Median small bowel wall visualization was scored 39 and 42 percentage points (95% CI 30-44% and 36-45%, both p

ObjectiveThe purpose of this study is to describe the appearance and frequency of gas interface artifacts in the jejunum that may mimic severe bowel disease on iodine-density images generated from rapid-voltage-switching dual-energy CT (DECT) scans.Materials and methodsTwo readers retrospectively reviewed 108 consecutive abdominal rapid-voltage-switching DECT scans to record the presence of image artifacts in jejunal segments with different degrees of gaseous luminal filling, classified as full, partial, or absent. Readers viewed iodine-density images and corresponding 140-kVp and 65-keV virtual monochromatic images and classified the jejunal artifacts on iodine-density images as pseudostratified appearance of the bowel wall, pseudopneumatosis, pseudohyperenhancement, or pseudohypoenhancement. We correlated the presence of the artifacts with clinical features suggesting bowel disease.ResultsImage artifacts were found in 91 of 108 scans (84.3%), appeared in 148 of 265 jejunal segments (55.8%), and included each type except for pseudohypoenhancement. Artifacts occurred exclusively when gas was present in the bowel lumen and were seen in 59 of 59 (100%) fully gas-distended segments, 89 of 98 (90.8%) partially gas-distended segments, and none of 108 gas-absent segments (p < 0.0001). In fully and partially gas-distended jejunal segments (n = 157), 148 (94.3%) segments had two or more artifacts. None of the patients was found to have clinical bowel-related injury on follow-up of medical records.ConclusionPseudostratified appearance, pseudopneumatosis, and pseudohyperenhancement, but not pseudohypoenhancement, artifacts are common in gas-filled jejunal segments on iodine-density images generated from rapid-voltage-switching DECT scans and are not seen in the corresponding 140-kVp or 65-keV images. Knowledge of the appearance of such iodine-density image artifacts will avoid potential examination interpretation pitfalls.

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. [ABSTRACT FROM AUTHOR]

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). All subjective MEI (+) scores were significantly higher than those of PEI (p < 0.05). The visualization rates were significantly higher for posterior superior pancreaticoduodenal artery (PSPDA), anterior and posterior inferior pancreaticoduodenal artery (AIPDA, PIPDA), anterior and posterior pancreaticoduodenal arcade (APAC, PPAC), transverse and caudal pancreatic artery (TPA, PCA) at 40-keV MEI (+) than those of PEI (p < 0.05). However, there were no significant differences for visualizing anterior superior pancreaticoduodenal artery (ASPDA), inferior pancreaticoduodenal artery (IPDA), dorsal and magnificent pancreatic artery (DPA, MPA) between 40-keV MEI (+) and 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 FROM AUTHOR]

Purpose: The purpose of this paper is to present an end‐to‐end deep convolutional neural network to improve the dual‐energy CT (DECT) material decomposition performance. Methods: In this study, we proposes a unified mutual‐domain (sinogram domain and CT domain) material decomposition network (DIRECT‐Net) for DECT imaging. By design, the DIRECT‐Net has immediate access to mutual‐domain data, and utilizes stacked convolution neural network layers for noise reduction and material decomposition. The training data are numerically generated following the fundamental DECT imaging physics. Numerical simulation of the XCAT digital phantom, experiments of a biological specimen, a calcium chloride phantom and an iodine solution phantom are carried out to evaluate the performance of DIRECT‐Net. Comparisons are performed with different DECT decomposition algorithms. Results: Results demonstrate that the proposed DIRECT‐Net can generate water and bone basis images with less artifacts compared to the other decomposition methods. Additionally, the quantification errors of the calcium chloride (75‐375 mg/cm3) and the iodine (2‐20 mg/cm3) are less than 4%. Conclusions: An end‐to‐end material decomposition network is proposed for quantitative DECT imaging. The qualitative and quantitative results demonstrate that this new DIRECT‐Net has promising benefits in improving the DECT image quality. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to evaluate and compare the quantitative material decomposition performance of the dual‐energy CT (DECT) and differential phase contrast CT (DPCT) via numerical observer studies. Methods: The electron density (ρe$\rho _{{\rm e}}$) and the effective atomic number (Zeff$Z_{{\rm eff}}$) are selected as the decomposition bases. The image domain based decomposition algorithms with certain noise suppression are used to extract the ρe$\rho _{{\rm e}}$ and Zeff$\text{Z}_{{\rm eff}}$ information under three different spatial resolutions (0.3 mm, 0.1 mm, and 0.03 mm). The contrast‐to‐noise‐ratio (CNR) and the numerical human observer model which is sensitive to the noise textures are investigated to compare the quantitative imaging performance of DECT and DPCT under varied radiation dose levels. Results: The model observer results show that the DECT is superior to DPCT at 0.3 mm spatial resolution (300 mm object size); the DECT and DPCT show similar quantitative imaging performance at 0.1 mm spatial resolution (100 mm object size); and the DPCT outperforms the DECT by approximately 1.5 times for the 0.3 mm sized imaging target at 0.03 mm spatial resolution (30 mm object size). Conclusions: In conclusion, the DECT would be recommended to obtain ρe$\rho _{{\rm e}}$ and Zeff$Z_{{\rm eff}}$ for the low spatial resolution quantitative imaging applications such as the diagnostic CT imaging. Whereas, the DPCT would be recommended for ultra high spatial resolution imaging tasks of small objects such as the micro‐CT imaging. This study provides a reference to determine the most appropriate quantitative X‐ray CT imaging method for a certain radiation dose level. [ABSTRACT FROM AUTHOR]

The investigation of acute pulmonary embolism is a common task for radiologists in Canada. Technical image quality and reporting quality must be excellent; pulmonary embolism is a life-threatening disease that should not be missed but overdiagnosis and unnecessary treatment should be avoided. The most frequently performed imaging investigation, computed tomography pulmonary angiogram (CTPA), can be limited by poor pulmonary arterial opacification, technical artifacts and interpretative errors. Image quality can be affected by patient factors (such as body habitus, motion artifact and cardiac output), intravenous (IV) contrast protocols (including the timing, rate and volume of IV contrast administration) and common physics artifacts (including beam hardening). Mimics of acute pulmonary embolism can be seen in normal anatomic structures, disease in non-vascular structures and pulmonary artery filling defects not related to acute pulmonary emboli. Understanding these pitfalls can help mitigate error, improve diagnostic quality and optimize patient outcomes. Dual energy computed tomography holds promise to improve imaging diagnosis, particularly in clinical scenarios where routine CTPA may be problematic, including patients with impaired renal function and patients with altered cardiac anatomy. [ABSTRACT FROM AUTHOR]

Purpose: To compare dual-energy (DE) lung perfused blood volume generated by subtraction of virtual monoenergetic images (Lung Mono) with images obtained by three-compartment decomposition (Lung PBV).Material and Methods: The study included 58 patients (28 patients with and 30 patients without PE) with reconstruction of Lung PBV images (i.e., the reference standard) and Lung Mono images. The inter-technique comparison was undertaken at a patient and segment level.Results: The distribution of scores of subjective image noise (patient level) significantly differed between the two reconstructions (p<0.0001), with mild noise in 58.6% (34/58) of Lung Mono images vs 25.9% (15/58) of Lung PBV images. Detection of perfusion defects (segment level) was concordant in 1104 segments (no defect: n=968; defects present: n=138) and discordant in 2 segments with a PE-related defect only depicted on Lung Mono images. Among the 28 PE patients, the distribution of gradient of attenuation between perfused areas and defects was significantly higher on Lung Mono images compared to Lung PBV (median= 73.5 HU (QI=65.0; Q3=86.0) vs 24.5 HU (22.0; 30.0); p<0.0001). In all patients, fissures were precisely identified in 77.6% of patients (45/58) on Lung Mono images while blurred (30/58; 51.7%) or not detectable (28/58; 48.3%) on Lung PBV images.Conclusion: Lung Mono perfusion imaging allows significant improvement in the overall image quality and improved detectability of PE-type perfusion defects. [ABSTRACT FROM AUTHOR]

To investigate the feasibility and to optimize the parameters of nonlinear blending technique in dual-energy CT on solitary pulmonary nodules (SPN). The simulated enhanced SPN were used the mixture of nonionic iodinated contrast agent (Iopromide 370mgI/100 ml) and normal saline and then randomly placed inside an anthropomorphic chest phantom. The phantom was examined on SOMATOM definition flash with dual mode (80/140 kV) and single energy mode (120 kV) (the same CTDIvol). Nonlinear blending images and linear blending images with a weighting factor of 0.3 were generated and the image qualities were analyzed. For different simulated density SPN, when 0 HU was chosen as the Blending Center (BC) and 0 to 30 HU were chosen as the Blending width (BW), the nonlinear blending images yielded a higher contrast-to-noise (CNR). There were significant differences in the image noise and signal-to-noise (SNR) of different simulated density SPN at non-linear blending images, linear blending images and 120 kV images (p <.05); But the differences of CNR between the three groups were not statistically significant (p >.05). The SNR of different simulated density SPN at non-linear blending images was significantly increased compared with it at linear blending images and 120 kV images (p <.05); And the image noise at non-linear blending was lower than it at linear blending images (p <.05). Nonlinear blending technique in dual-energy CT can increase the SNR of enhanced SPN, and it is helpful in diagnosis of SPN. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To investigate feasibility of the quantitative parameters of dual-energy computed tomography (DECT) to assess therapy response in advanced non-small cell lung cancer (NSCLC) compared with the traditional enhanced CT parameters based on the Response Evaluation Criteria in Solid Tumors (RECIST) guidelines. METHODS: Forty-five patients with unresectable locally advanced NSCLC who underwent DECT before and after chemotherapy or concurrent chemoradiotherapy (cCRT) were prospectively enrolled. By comparing baseline studies with follow-up, patients were divided into two groups according to RECIST guidelines as follows: disease control (DC, including partial response and stable disease) and progressive disease (PD). The diameter (D), attenuation, iodine concentration and normalized iodine concentration of arterial and venous phases (ICA, ICv, NICA, NICv) and the percentage of these changes pre- and post-therapy were measured and calculated. The Pearson correlation was used to analyze correlation between various quantitative parameters. The receiver operating characteristic (ROC) curves were used to evaluate accuracy of therapy response prediction. RESULTS: The change percentages of Attenuation (Δ-Attenuation-A and Δ-Attenuation-V), IC (ΔICA and ΔICV) and NIC (ΔNICA and ΔNICV) pre- and post-therapy correlate with the change percentage of D (ΔD). Among these, ΔICA strongly correlates with ΔD (r = 0.793, P < 0.001). The areas under ROC curves generated using Δ-Attenuation-A, ΔICA, and ΔNICA are 0.796, 0.900, and 0.880 with the corresponding cutoff value of 9.096, −15.692, and −4.7569, respectively, which are significantly different (P < 0.001). CONCLUSIONS: The quantitative parameters of DECT iodine map, especially iodine concentration, in arterial phase provides a new quantitative image marker to predict therapy response of patients diagnosed with advanced NSCLC. [ABSTRACT FROM AUTHOR]

Copyright of CT Theory & Applications is the property of Editorial Department of CT Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background/Aim: This study evaluated the calculation accuracy of the stopping power ratio (SPR) using dual-energy computed tomography with fast kilovoltage switching (FKSCT) for particle therapy. Materials and Methods: A tissue characterization phantom with various reference materials was scanned to obtain single-energy computed tomography (SECT) images and generate virtual monochromatic images at 77 keV (VMI77keV) and 140 keV (VMI140keV), water density (WD) images, and effective Z (Zeff) images. For SECT, VMI77keV and VMI140keV lookup tables were generated to convert the measured Hounsfield value into the theoretical SPR for a normal phantom size. Subsequently, the reference materials were scanned in small and large phantoms. The SPR was calculated using the lookup tables of SECT (SPRSECT) images, VMI77keV (SPR77keV), and VMI140keV (SPR140keV), and it was derived from the WD and Zeff (SPRWD). Results: In the normal-sized phantom, the overall mean difference between SPRWD and theoretical SPR was −0.3%, and remained below 2% for most reference materials. For the large phantom, the overall mean absolute difference for SPR140keV (3.0%, p=0.006) and SPRWD (3.2%, p=0.002) for the reference materials was significantly lower than that for SPRSECT (5.9%). For the small phantom, a significant reduction in the mean difference in the SPR calculation was observed in SPR77keV (1.0%, p=0.001) and SPR140keV (1.1%, p=0.013) compared with SPRSECT (2.2%). Conclusion: VMI140keV generated using FKSCT significantly improves the estimation accuracy of SPR compared with SECT. Thus, FKSCT may be used to improve the dose calculation accuracy for treatment planning of particle therapy. [ABSTRACT FROM AUTHOR]

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

Background: To examine the value of energetic-spectrum computed tomography (spectral CT) quantitative parameters in renal cell carcinoma (RCC) microvascular angiogenesis. Methods: The authors evaluated 32 patients with pathologically confirmed RCC who underwent triple-phase contrast-enhanced CT with spectral CT imaging mode from January 2017 to December 2019. Quantitative parameters include parameters derived from iodine concentration (IC) and water concentration (WC) of 120 keV monochromatic images. All specimens were evaluated including the microvascular density (MVD), microvascular area (MVA) and so on. The correlation between IC and WC (including average values and random values) with microvascular parameters were analyzed with Pearson or Spearman rank correlation coefficients. Results: The MVD of all tumors was 26.00 (15.00–43.75) vessels per field at × 400 magnification. The MVD of RCC correlated positively with the mean IC, mean WC, mean NWC, mean NIC, random IC, random NIC in renal cortical phase, WCD1, WCD2, NWCD2 and ICD1 (Spearman rank correlation coefficients, r range, 0.362–0.533; all p < 0.05). The MVA of all tumors was (16.16 ± 8.98) % per field at × 400 magnification. The MVA of RCC correlated positively with the mean IC, mean WC, mean NWC, mean NIC, random IC, random NIC in renal cortical, mean WC and mean NWC in renal parenchymal phase, WCD1, WCD2, WCD3, NWCD2, and NWCD3 (Pearson or Spearman rank correlation coefficients, r range, 0.357–0.576; all p < 0.05). Microvascular grading correlated positively with the mean NWC, mean NIC and random NIC in renal cortical phase, mean NWC in renal parenchymal phase, NWCD2, WCD3, NWCD3, NICD2 and NICD3 (Spearman rank correlation coefficients, r range, 0.367–0.520; all p < 0.05). As for tumor diameter (55.19 ± 19.15), μm, only NWCD3 was associated with it (Spearman rank correlation coefficients, r = 0.388; p < 0.05). Conclusions: ICD and WCD of spectral CT have a potential for evaluating RCC microvascular angiogenesis. MVD, MVA and microvascular grade showed moderate positive correlation with ICD and WCD. ICD displayed more relevant than that of WCD. The parameters of renal cortical phase were the best in three phases. NICD and NWCD manifested stronger correlation with microvascular parameters than that of ICD and WCD. [ABSTRACT FROM AUTHOR]

Purpose: The dual-energy CT (DECT) LiverVNC application class in the Siemens Syngo.via software has been used to perform non-iodine material decompositions.However, the LiverVNC application is designed with an optional size-specific calibration based on iodine measurements. This work investigates the effects of this iodine-based size-specific calibration on non-iodine material decomposition and benchmarks alternative methods for size-specific calibrations. Methods: Calcium quantification was performed with split-filter and sequentialscanning DECT techniques on the Siemens SOMATOM Definition Edge CT scanner. Images were acquired of the Gammex MECT abdomen and head phantom containing calcium inserts with concentrations ranging from 50--300 mgCa/ml. Several workflows were explored investigating the effects of sizespecific dual-energy ratios (DERs) and the beam hardening correction (BHC) function in the LiverVNC application. Effects of image noise were also investigated by varying CTDIvol and using iterative reconstruction (ADMIRE). Results: With the default BHC activated, Syngo.via underestimated the calcium concentrations in the abdomen for sequential-scanning acquisitions, leaving residual calcium in the virtual non-contrast images and underestimating calcium in the enhancement images for all DERs. Activation of the BHC with split-filter images resulted in a calcium over- or underestimation depending on the DER.With the BHC inactivated, the use of a single DER led to an under- or overestimate of calcium concentration depending on phantom size and DECT modality. Optimal results were found with BHC inactivated using size-specific DERs. CTDIvol levels and ADMIRE had no significant effect on results. Conclusion: When performing non-iodine material decomposition in the LiverVNC application class, it is important to understand the implications of the BHC function and to account for patient size appropriately. The BHC in the LiverVNC application is specific to iodine and leads to inaccurate quantification of other materials. The inaccuracies can be overcome by deactivating the BHC function and using size-specific DERs, which provided the most accurate calcium quantification. [ABSTRACT FROM AUTHOR]

Abstract Background Dual-energy CT (DECT) can acknowledge differences in tissue compositions and can colour-code tissues with specific features including monosodium urate (MSU) crystals. However, when evaluating gout patients, DECT frequently colour-codes material not truly representing MSU crystals and this might lead to misinterpretations. The characteristics of and variations in properties of colour-coded DECT lesions in gout patients have not yet been systematically investigated. The objective of this study was to evaluate the properties and locations of colour-coded DECT lesions in gout patients. Methods DECT of the hands, knees and feet were performed in patients with suspected gout using factory default gout settings, and colour-coded DECT lesions were registered. For each lesion, properties [mean density (mean of Hounsfield Units (HU) at 80 kV and Sn150kV), mean DECT ratio and size] and location were determined. Subgroup analysis was performed post hoc evaluating differences in locations of lesions when divided into definite MSU depositions and possibly other lesions. Results In total, 4033 lesions were registered in 27 patients (23 gout patients, 3918 lesions; 4 non-gout patients, 115 lesions). In gout patients, lesions had a median density of 160.6 HU and median size of 6 voxels, and DECT ratios showed an approximated normal distribution (mean 1.06, SD 0.10), but with a right heavy tail consistent with the presence of smaller amounts of high effective atomic number lesions (e.g. calcium-containing lesions). The most common locations of lesions were 1st metatarsophalangeal (MTP1), knee and midtarsal joints along with quadriceps and patella tendons. Subgroup analyses showed that definite MSU depositions (large volume, low DECT ratio, high density) had a similar distribution pattern, whereas possible calcium-containing material (high DECT ratio) and non-gout MSU-imitating lesions (properties as definite MSU depositions in non-gout patients) were primarily found in some larger joints (knee, midtarsal and talocrural) and tendons (Achilles and quadriceps). MTP1 joints and patella tendons showed only definite MSU depositions. Conclusion Colour-coded DECT lesions in gout patients showed heterogeneity in properties and distribution. MTP1 joints and patella tendons exclusively showed definite MSU depositions. Hence, a sole focus on these regions in the evaluation of gout patients may improve the specificity of DECT scans.

Abstract Background To investigate the potential value of volumetric iodine quantification using preoperative dual-energy computed tomography (DECT) for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Methods This retrospective study included patients with single HCC treated through surgical resection who underwent preoperative DECT. Quantitative DECT features, including normalized iodine concentration (NIC) to the aorta and mixed-energy CT attenuation value in the arterial phase, were three-dimensionally measured for peritumoral and intratumoral regions: (i) layer-by-layer analysis for peritumoral layers (outer layers 1 and 2; numbered in close order from the tumor boundary) and intratumoral layers (inner layers 1 and 2) with 2-mm layer thickness and (ii) volume of interest (VOI)-based analysis with different volume coverage (tumor itself; VOIO1, tumor plus outer layer 1; VOIO2, tumor plus outer layers 1 and 2; VOII1, tumor minus inner layer 1; VOII2, tumor minus inner layers 1 and 2). In addition, qualitative CT features, including peritumoral enhancement and tumor margin, were assessed. Qualitative and quantitative CT features were compared between HCC patients with and without MVI. Diagnostic performance of DECT parameters of layers and VOIs was assessed using receiver operating characteristic curve analysis. Results A total of 36 patients (24 men, mean age 59.9 ± 8.5 years) with MVI (n = 14) and without MVI (n = 22) were included. HCCs with MVI showed significantly higher NICs of outer layer 1, outer layer 2, VOIO1, and VOIO2 than those without MVI (P = 0.01, 0.04, 0.02, 0.02, respectively). Among the NICs of layers and VOIs, the highest area under the curve was obtained in outer layer 1 (0.747). Qualitative features, including peritumoral enhancement and tumor margin, and the mean CT attenuation of each layer and each VOI were not significantly different between HCCs with and without MVI (both P > 0.05). Conclusions Volumetric iodine quantification of peritumoral and intratumoral regions in arterial phase using DECT may help predict the MVI of HCC.

Metastatic pulmonary calcification is an underdiagnosed metabolic lung disease characterized by diffuse calcium deposition in the lungs, often associated with secondary hyperparathyroidism due to chronic renal failure. A 31-year-old man with chronic renal failure initially presented with diffuse pain symptoms, deterioration of general condition, and respiratory insufficiency. Noncontrast-enhanced computed tomography of the chest was performed using a spectral-detector-based dual-energy CT. It showed multiple, centrilobular, ground-glass opacities, and nodules, ultimately leading to the diagnosis. Calcium suppression proved to be highly useful to classify the pulmonary alterations.

Background: MRI is the preferred imaging technique for the identification of osteomyelitis. The key element for diagnosis is the presence of bone marrow edema (BME). Dual-energy CT (DECT) is an alternative tool which is able to identify BME in the lower limb. Purpose: To compare the diagnostic performance of DECT and MRI for osteomyelitis, using clinical, microbiological, and imaging data as reference standards. Materials and Methods: This prospective single-center study enrolled consecutive patients with suspected bone infections undergoing DECT and MRI imaging from December 2020 to June 2022. Four blinded radiologists with various experience levels (range of 3-21 years) evaluated the imaging findings. Osteomyelitis was diagnosed in the presence of BMEs, abscesses, sinus tracts, bone reabsorption, or gaseous elements. The sensitivity, specificity, and AUC values of each method were determined and compared using a multi-reader multi-case analysis. A p value < 0.05 was considered significant. Results: In total, 44 study participants (mean age 62.5 years ± 16.5 [SD], 32 men) were evaluated. Osteomyelitis was diagnosed in 32 participants. For the MRI, the mean sensitivity and specificity were 89.1% and 87.5%, while for the DECT they were 89.0% and 72.9%, respectively. The DECT demonstrated a good diagnostic performance (AUC = 0.88), compared with the MRI (AUC = 0.92) (p = 0.12). When considering each imaging finding alone, the best accuracy was achieved by considering BME (AUC for DECT 0.85 versus AUC of MRI of 0.93, with p = 0.07), followed by the presence of bone erosions (AUC 0.77 for DECT and 0.53 for MRI, with p = 0.02). The inter-reader agreement of the DECT (k = 88) was similar to that of the MRI (k = 90). Conclusion: Dual-energy CT demonstrated a good diagnostic performance in detecting osteomyelitis.

Due to its high morbidity and mortality, myocardial infarction is the leading cause of death worldwide. Against this background, rapid diagnosis is of immense importance. Especially in case of an atypical course, the correct diagnosis may be delayed and thus lead to increased mortality rates. In this report, we present a complex case of acute coronary syndrome. A triple-rule-out CT examination was performed in dual-energy CT (DECT) mode. While pulmonary artery embolism and aortic dissection could be ruled out with conventional CT series, the presence of anterior wall infarction was only detectable on DECT reconstructions. Subsequently, adequate and rapid therapy was then initiated leading to survival of the patient.

Background: To assess the ability of low-dose dual-energy computed tomography (ld-DECT) virtual non-calcium (VNCa) images for detecting bone marrow pathologies of the sacroiliac joints (SIJs) in patients with axial spondyloarthritis (axSpA). Material and Methods: Sixty-eight patients with suspected or proven axSpA underwent ld-DECT and MRI of the SIJ. VNCa images were reconstructed from DECT data and scored for the presence of osteitis and fatty bone marrow deposition by two readers with different experience (beginner and expert). Diagnostic accuracy and correlation (Kohen’s k) with magnetic resonance imaging (MRI) as the reference standard were calculated for the overall and for each reader separately. Furthermore, quantitative analysis was performed using region-of-interest (ROI) analysis. Results: Twenty-eight patients were classified as positive for osteitis, 31 for fatty bone marrow deposition. DECT’s sensitivity (SE) and specificity (SP) were 73.3% and 44.4% for osteitis and 75% and 67.3% for fatty bone lesions, respectively. The expert reader achieved higher diagnostic accuracy for both osteitis (SE 93.33%; SP: 51.85%) and fatty bone marrow deposition (SE: 65%; SP: 77.55%) than the beginner (SE: 26.67%; SP: 70.37% for osteitis; SE: 60%; SP: 44.9% for fatty bone marrow deposition). Overall correlation with MRI was moderate (r = 0.25, p = 0.04) for osteitis and fatty bone marrow deposition (r = 0.25, p = 0.04). Fatty bone marrow attenuation in VNCa images (mean: −129.58 HU; ±103.61 HU) differed from normal bone marrow (mean: 118.84 HU, ±99.91 HU; p < 0.01) and from osteitis (mean: 172 HU, ±81.02 HU; p < 0.01) while osteitis did not differ significantly from normal bone marrow (p = 0.27). Conclusion: In our study, low-dose DECT failed to detect osteitis or fatty lesions in patients with suspected axSpA. Thus, we conclude that higher radiation might be needed for DECT−based bone marrow analysis.

Purpose: Pancreatic duct variation can affect the secretory function of the pancreas. We aimed to explore the pancreatic duct variation, observed using low-keV monoenergetic images [MEI (+)] of dual-energy CT (DECT), and its relationship with related diseases. We further sought to compare pancreatic duct imaging using low-keV MEI (+) of DECT and magnetic resonance cholangiopancreatography (MRCP). Materials and Methods: The DECT and MRCP images of 854 patients were evaluated retrospectively. The 808 patients’ pancreatic duct types were classified according to the anatomy and the opening of the pancreatic ducts, and the correlation with related diseases was analyzed. The DECT and MRCP images of 852 patients were graded according to the sharpness of the pancreatic ducts for evaluation. Results: A higher prevalence of acute pancreatitis (AP), chronic pancreatitis (CP), and duodenal papillary carcinoma (DPC) was observed in the variant group. Of the 27 AP cases in the variant group, 9 patients (33.3%) were Type 3c. Additionally, Type 4a was significantly correlated with AP and CP (p < 0.05). Low-keV MEI (+) of DECT outperformed the MRCP images in the sharpness of the pancreatic ducts in 852 patients. Conclusions: Pancreatic duct variation is associated with AP, CP, and DPC. Low-keV MEI (+) DECT is an effective method to observe the pancreatic duct system.

Objective. Proton therapy administers a highly conformal dose to the tumour region, necessitating accurate prediction of the patient's 3D map of proton relative stopping power (RSP) compared to water. This remains challenging due to inaccuracies inherent in single-energy computed tomography (SECT) calibration. Recent advancements in spectral x-ray CT (xCT) and proton CT (pCT) have shown improved RSP estimation compared to traditional SECT methods. This study aims to provide the first comparison of the imaging and RSP estimation performance among dual-energy CT (DECT) and photon-counting CT (PCCT) scanners, and a pCT system prototype. Approach. Two phantoms were scanned with the three systems for their performance characterisation: a plastic phantom, filled with water and containing four plastic inserts and a wood insert, and a heterogeneous biological phantom, containing a formalin-stabilised bovine specimen. RSP maps were generated by converting CT numbers to RSP using a calibration based on low- and high-energy xCT images, while pCT utilised a distance-driven filtered back projection algorithm for RSP reconstruction. Spatial resolution, noise, and RSP accuracy were compared across the resulting images. Main results. All three systems exhibited similar spatial resolution of around 0.54 lp/mm for the plastic phantom. The PCCT images were less noisy than the DECT images at the same dose level. The lowest mean absolute percentage error (MAPE) of RSP,(0.28±0.07)%, was obtained with the pCT system, compared to MAPE values of(0.51±0.08)%and(0.80±0.08)%for the DECT- and PCCT-based methods, respectively. For the biological phantom, the xCT-based methods resulted in higher RSP values in most of the voxels compared to pCT. Significance. The pCT system yielded the most accurate estimation of RSP values for the plastic materials, and was thus used to benchmark the xCT calibration performance on the biological phantom. This study underlined the potential benefits and constraints of utilising such a novel ex-vivo phantom for inter-centre surveys in future., (Creative Commons Attribution license.)

Background: The challenge of early and rapid diagnosis of periprosthetic joint infection (PJI) remains important. This study aimed to assess the efficacy of dual-energy computed tomography (DECT) iodine maps for diagnosing PJI in total hip arthroplasty., Methods: We prospectively enrolled 68 patients who had postoperative joint pain after hip arthroplasty. All patients underwent preoperative DECT iodine imaging to quantify iodine concentration (IC) in periprosthetic tissues during arterial and venous phases. The diagnostic efficacy of DECT iodine maps was evaluated by constructing receiver operating characteristic curves according to the Musculoskeletal Infection Society criteria., Results: Compared with erythrocyte sedimentation rate (area under the curve [AUC] = 0.837), polymorphonuclear cell percentage (AUC = 0.703), and C-reactive protein (AUC = 0.837), periprosthetic tissue venous-phase IC (AUC = 0.970) and arterial-phase IC (AUC = 0.964) exhibited outstanding discriminative capability between PJI and aseptic failure. The PJI cut-off point was venous IC = 1.225 mg/mL, with a sensitivity of 92.31% and specificity of 90.48%; for arterial IC = 1.065 mg/mL, the sensitivity was 96.15% and specificity was 90.70%., Conclusions: This study demonstrates the great potential of DECT iodine maps for the diagnosis of PJI around hip arthroplasty, which helps to differentiate between periprosthetic infection and aseptic failure after hip arthroplasty., (Copyright © 2024 Elsevier Inc. All rights reserved.)

We examined the association between texture features using three-dimensional (3D) io-dine density histogram on delayed phase of dual-energy CT (DECT) and expression of programmed death-ligand 1 (PD-L1) using immunostaining methods in non-small cell lung cancer. Consecutive 37 patients were scanned by DECT. Unenhanced and enhanced (3 min delay) images were obtained. 3D texture analysis was performed for each nodule to obtain 7 features (max, min, median, mean, standard deviation, skewness, and kurtosis) from iodine density mapping and extracellular volume (ECV). A pathologist evaluated a tumor proportion score (TPS, %) using PD-L1 immunostaining: PD-L1 high (TPS ≥ 50%) and low or negative expression (TPS < 50%). Associations between PD-L1 expression and each 8 parameter were evaluated using logistic regression analysis. The multivariate logistic regression analysis revealed that skewness and ECV were independent indicators associated with high PD-L1 expression (skewness: odds ratio [OR]  7.1 [95% CI 1.1, 45.6], p = 0.039; ECV: OR 6.6 [95% CI 1.1, 38.4], p = 0.037). In the receiver-operating characteristic analysis, the area under the curve of the combination of skewness and ECV was 0.83 (95% CI 0.67, 0.93) with sensitivity of 64% and specificity of 96%. Skewness from 3D iodine density histogram and ECV on dual energy CT were significant factors for predicting PD-L1 expression., (© 2024. The Author(s).)

Objective. The study aimed to generate synthetic contrast-enhanced Dual-energy CT (CE-DECT) images from non-contrast single-energy CT (SECT) scans, addressing the limitations posed by the scarcity of DECT scanners and the health risks associated with iodinated contrast agents, particularly for high-risk patients. Approach. A conditional denoising diffusion probabilistic model (C-DDPM) was utilized to create synthetic images. Imaging data were collected from 130 head-and-neck (HN) cancer patients who had undergone both non-contrast SECT and CE-DECT scans. Main Results. The performance of the C-DDPM was evaluated using Mean Absolute Error (MAE), Structural Similarity Index (SSIM), and Peak Signal-to-Noise Ratio (PSNR). The results showed MAE values of 27.37±3.35 Hounsfield Units (HU) for high-energy CT (H-CT) and 24.57±3.35HU for low-energy CT (L-CT), SSIM values of 0.74±0.22 for H-CT and 0.78±0.22 for L-CT, and PSNR values of 18.51±4.55 decibels (dB) for H-CT and 18.91±4.55 dB for L-CT. Significance. The study demonstrates the efficacy of the deep learning model in producing high-quality synthetic CE-DECT images, which significantly benefits radiation therapy planning. This approach provides a valuable alternative imaging solution for facilities lacking DECT scanners and for patients who are unsuitable for iodine contrast imaging, thereby enhancing the reach and effectiveness of advanced imaging in cancer treatment planning., (Creative Commons Attribution license.)

Background : The aim was to assess the diagnostic accuracy of DECT in diagnosing Achilles tendon tears, using MRI as the reference for diagnosis. Methods : This feasibility study conducted prospectively at a single center included consecutive patients suffering from ankle pain who underwent DECT and MRI between April 2023 and October 2023. A total of three radiologists, blinded to the patient's clinical data, assessed the images. Achille Tendon injuries were diagnosed in case of thickened and inflamed tendons or in case of a partial or complete tear. Diagnostic accuracy values of DECT were calculated using a multi-reader approach. Inter-observer agreement was calculated using k statistics. Results : The final study population included 22 patients (mean age 48.5 years). At MRI, Achille's tendon lesion was present in 12 cases (54.5%) with 2 cases of complete rupture, 8 cases of partial tear (5 with tendon retraction), and 2 cases of tendon thickening. The mean thickness of injured tendons was 10 mm. At DECT, R1 was allowed to correctly classify 20/22 cases (90.9%), R2 19/22 cases (86.4%), and R3 18/22 cases (81.8%). At DECT, the mean thickness of the positively scored tendon was 10 mm for R1, 10.2 mm for R2, and 9.8 mm for R3. A very good agreement was achieved with regard to the evaluation of tears (k = 0.94), thickness (k = 0.96), and inflammatory changes (k = 0.82). Overall agreement was very good (k = 0.88). Conclusions : DECT showed a good diagnostic performance in identifying Achille's tendon tears, with respect to MRI.

The article addresses the diagnostic value of the combined use of computed tomography (CT) perfusion and dual-energy CT (DECT) in patients with neuroendocrine tumors. It emphasizes the heterogeneity and complexity of these neoplasms, primarily affecting the gastrointestinal tract, bronchopulmonary system, and pancreas. While conventional CT is widely employed in their diagnosis, the combination of CT perfusion and dual-energy CT offers greater precision, particularly in detecting synchronous tumors and characterizing their vascularization. A clinical case of a patient with chronic abdominal symptoms, whose diagnosis was facilitated using both combined techniques, is presented. The discussion explores how CT perfusion assesses tumor vascularization and how dual-energy CT improves soft tissue differentiation, resulting in increased diagnostic accuracy. It is highlighted that this approach not only enhances detection rates but also positively impacts clinical management and healthcare costs. Therefore, the importance of considering these advanced tools in the diagnosis of neuroendocrine tumors to improve diagnostic precision and efficiency in patient care is underscored., (© 2024 The Authors. Published by Elsevier Inc. on behalf of University of Washington.)

Objective  This article evaluates the ability of low-energy (40 keV) virtual monoenergetic images (VMIs) in the local diagnosis of cervical cancer compared with that of conventional computed tomography (C-CT) and magnetic resonance imaging (MRI), using clinicopathologic staging as a reference. Methods  This prospective study included 33 patients with pathologically confirmed cervical cancer who underwent dual-energy CT and MRI between 2021 and 2022. The contrast-to-noise ratio (CNR) of the tumor-to-myometrium was compared between C-CT and VMI. Additionally, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) for each local diagnostic parameter were compared between C-CT, VMI, and MRI. Interradiologist agreement was also assessed. Results  The mean CNR was significantly higher on VMI ( p  = 0.002). No significant difference in AUC was found between C-CT and VMI for all local diagnostic parameters, and the specificity of VMI was often significantly less than that of MRI. For parametrial invasion, mean sensitivity, specificity, and AUC for C-CT, VMI, and MRI were 0.81, 0.99, 0.93; 0.64, 0.35, 0.79; and 0.73, 0.67, 0.86, respectively, and MRI had significantly higher specificity and AUC than that of VMI ( p  = 0.013 and 0.008, respectively). Interradiologist agreement was higher for VMI than C-CT and for MRI than VMI. Conclusion  The CNR of VMI was significantly higher than C-CT and interradiologist agreement was better than with C-CT; however, the overall diagnostic performance of VMI did not significantly differ from C-CT and was inferior to MRI. VMI was characterized by low specificity, which should be understood and used for reading., Competing Interests: Conflict of Interest None declared., (Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ).)

Rationale and Objectives: To explore the value of splenic hemodynamic parameters from low-dose one-stop dual-energy and perfusion CT (LD-DE&PCT) in non-invasively predicting high-risk esophageal varices (HREV) in cirrhotic patients., Methods: We retrospectively analyzed cirrhotic patients diagnosed with esophageal varices (EV) through clinical, laboratory, imaging, and endoscopic examinations from September 2021 to December 2023 in our hospital. All patients underwent LD-DE&PCT to acquire splenic iodine concentration and perfusion parameters. Radiation dose was recorded. Patients were classified into non-HREV and HREV groups based on endoscopy. Univariate and multivariate logistic regression analysis were performed, and the prediction model for HREV was constructed. P < 0.05 was considered statistically significant., Results: Univariate analysis revealed that significant differences were found in portal iodine concentration (PIC), blood flow (BF), permeability surface (PS), spleen volume (V-S), total iodine concentration (TIC), and total blood volume of the spleen (BV-S) between groups. TIC demonstrated the highest predictive value with an area under the curve (AUC) value of 0.87. Multivariate analysis showed that PIC, PS, and BV-S were independent risk factors for HREV. The logistic regression model for predicting HREV had an AUC of 0.93. The total radiation dose was 20.66 ± 4.07 mSv., Conclusion: Splenic hemodynamic parameters obtained from LD-DE&PCT can non-invasively and accurately assess the hemodynamic status of the spleen in cirrhotic patients with EV and predict the occurrence of HREV. Despite the retrospective study design and limited sample size of this study, these findings deserve further validation through prospective studies with larger cohorts., 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 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Purpose: To determine the feasibility of meniscal imaging using virtual monochromatic images obtained through dualenergy computed tomography (DECT) technique, and to determine which keV levels optimise contrast resolution., Material and Methods: All DECT exams were performed on a Discovery CT750 HD system from GE Healthcare. Virtual monochromatic images were reconstructed at 40 keV, 73 keV, 106 keV, and 139 keV. Contrast resolution of the medial and lateral menisci using a 5-point Likert scale at each keV level was determined through a consensus agreement by 2 fellowship-trained musculoskeletal radiologists. Friedman's and Wilcoxon signed rank tests were used to compare visualisation scores across different keV levels., Results: Seventeen knee exams from 10 patients met criteria for inclusion in the study. All patients included in the study cohort were male. The median age of patients was 46 years (interquartile range, 35-53 years). Virtual monochromatic images at 40 keV demonstrated highest contrast resolution of the menisci, with a statistically significant difference between contrast resolution scores at 40 keV and 76 keV, Friedman test: p < 0.0001., Conclusions: Meniscal imaging is feasible using DECT virtual monochromatic images at low keV levels. Improved contrast resolution at these specified KeV values could pave the way for further research in this field to determine its role in the future as an alternative option for assessment of the menisci in patients with contraindications to MRI or in the setting of a periarticular ferromagnetic foreign body obscuring the field of view., (© Pol J Radiol 2024.)

Purpose: The purpose of this study was to evaluate the incremental diagnostic value of virtual non-contrast (VNC) images derived from unenhanced dual-energy computed tomography (CT) for the diagnosis of choledocholithiasis by comparison with conventional unenhanced CT., Materials and Methods: Eighty-nine patients with gallbladder stones who had undergone both abdominal unenhanced dual-energy CT and magnetic resonance cholangiopancreatography (MRCP) were retrospectively included. There were 53 men and 36 women, with a mean age of 54 ± 13 (standard deviation) years (age range: 41-67 years). VNC and conventional CT images were generated. Two independent radiologists evaluated the presence of choledocholithiasis in three reading sessions (session 1, conventional unenhanced CT images; session 2, VNC images; session 3, conventional unenhanced CT plus VNC images). The reading time to identify choledocholithiasis was recorded. Inter-reader agreement was measured by using the Cohen kappa (κ) test. Incremental diagnostic value of VNC imaging when combined with conventional unenhanced CT was assessed based on discrimination (area under the curve [AUC]) and clinical utility (decision curve analysis). The diagnostic performance of dual-energy CT and that of MRCP were compared using DeLong test., Results: Using the standard of reference, 39 patients (39/89; 44%) had choledocholithiasis. The diagnosis of choledocholithiasis was improved using VNC images in combination with conventional unenhanced CT (AUC, 0.877; 95% confidence interval [CI]: 0.808, 0.947) by comparison with conventional unenhanced CT alone (AUC, 0.789; 95% CI: 0.718, 0.877) (P = 0.033) and achieved almost perfect inter-reader agreement (κ = 0.88; 95% CI: 0.72, 1.00) for the diagnosis of choledocholithiasis, without lengthening the median reading time (16.2 s for the combination of conventional CT and VNC images vs. 14.7 s for conventional CT alone; P= 0.325). Based on decision curve analysis, adding VNC imaging to conventional unenhanced CT resulted in a higher net benefit among most of decision thresholds. No differences in diagnostic performance were found between the combination of conventional unenhanced CT and VNC imaging (AUC, 0.877; 95% CI: 0.808, 0.947) and MRCP (AUC, 0.913; 95% CI: 0.852, 0.974) (P= 0.458)., Conclusions: VNC images derived from dual-energy unenhanced CT have incremental diagnostic value for the diagnosis of choledocholithiasis. Unenhanced CT in a dual-energy mode may be a useful tool for the diagnosis of choledocholithiasis., Competing Interests: Declaration of competing interest The authors have no relevant financial or non-financial interests to disclose in relation with this article., (Copyright © 2024 The Author(s). Published by Elsevier Masson SAS.. All rights reserved.)

Dual-energy CT stands out as a robust and innovative imaging modality, which has shown impressive advancements and increasing applications in musculoskeletal imaging. It allows to obtain detailed images with novel insights that were once the exclusive prerogative of magnetic resonance imaging. Attenuation data obtained by using different energy spectra enable to provide unique information about tissue characterization in addition to the well-established strengths of CT in the evaluation of bony structures. To understand clearly the potential of this imaging modality, radiologists must be aware of the technical complexity of this imaging tool, the different ways to acquire images and the several algorithms that can be applied in daily clinical practice and for research. Concerning musculoskeletal imaging, dual-energy CT has gained more and more space for evaluating crystal arthropathy, bone marrow edema, and soft tissue structures, including tendons and ligaments. This article aims to analyze and discuss the role of dual-energy CT in musculoskeletal imaging, exploring technical aspects, applications and clinical implications and possible perspectives of this technique., (© 2024. The Author(s).)

Dual-energy CT (DECT) with scans over limited-angular ranges (LARs) may allow reductions in scan time and radiation dose and avoidance of possible collision between the moving parts of a scanner and the imaged object. The beam-hardening (BH) and LAR effects are two sources of image artifacts in DECT with LAR data. In this work, we investigate a two-step method to correct for both BH and LAR artifacts in order to yield accurate image reconstruction in DECT with LAR data. From low- and high-kVp LAR data in DECT, we first use a data-domain decomposition (DDD) algorithm to obtain LAR basis data with the non-linear BH effect corrected for. We then develop and tailor a directional-total-variation (DTV) algorithm to reconstruct from the LAR basis data obtained basis images with the LAR effect compensated for. Finally, using the basis images reconstructed, we create virtual monochromatic images (VMIs), and estimate physical quantities such as iodine concentrations and effective atomic numbers within the object imaged. We conduct numerical studies using two digital phantoms of different complexity levels and types of structures. LAR data of low- and high-kVp are generated from the phantoms over both single-arc (SA) and two-orthogonal-arc (TOA) LARs ranging from 14∘ to 180∘. Visual inspection and quantitative assessment of VMIs obtained reveal that the two-step method proposed can yield VMIs in which both BH and LAR artifacts are reduced, and estimation accuracy of physical quantities is improved. In addition, concerning SA and TOA scans with the same total LAR, the latter is shown to yield more accurate images and physical quantity estimations than the former. We investigate a two-step method that combines the DDD and DTV algorithms to correct for both BH and LAR artifacts in image reconstruction, yielding accurate VMIs and estimations of physical quantities, from low- and high-kVp LAR data in DECT. The results and knowledge acquired in the work on accurate image reconstruction in LAR DECT may give rise to further understanding and insights into the practical design of LAR scan configurations and reconstruction procedures for DECT applications.

Background : The electrodes of implantable cardiac devices (ICDs) may cause significant problems in cardiac computed tomography (CT) because they are a source of artifacts that obscure surrounding structures and possible pathology. There are a few million patients currently with ICDs, and some of these patients will require cardiac imaging due to coronary artery disease or problems with ICDs. Modern CT scanners can reduce some of the metal artifacts because of MAR software, but in some vendors, it does not work with ECG gating. Introduced in 2008, dual-energy CT scanners can generate virtual monoenergetic images (VMIs), which are much less susceptible to metal artifacts than standard CT images. Objective : This study aimed to evaluate if dual-energy CT can reduce metal artifacts caused by ICD leads by using VMIs. The second objective was to determine how the angle between the electrode and the plane of imaging affects the severity of the artifacts in three planes of imaging. Methods : A 3D-printed model was constructed to obtain a 0-90-degree field at 5-degree intervals between the electrode and each of the planes: axial, coronal, and sagittal. This electrode was scanned in dual-energy and single-energy protocols. VMIs with an energy of 40-140 keV with 10 keV intervals were reconstructed. The length of the two most extended artifacts originating from the tip of the electrode and 2 cm above it-at the point where the thick metallic defibrillating portion of the electrode begins-was measured. Results : For the sagittal plane, these observations were similar for both points of the ICDs that were used as the reference location. VMIs with an energy over 80 keV produce images with fewer artifacts than similar images obtained in the single-energy scanning mode. Conclusions : Virtual monoenergetic imaging techniques may reduce streak artifacts arising from ICD electrodes and improve the quality of the image. Increasing the angle of the electrode as well as the imaging plane can reduce artifacts. The angle between the electrode and the beam of X-rays can be increased by tilting the gantry of the scanner or lifting the upper body of the patient.

Background: Treatment efficacy may differ among patients with nasopharyngeal carcinoma (NPC) at similar tumor-node-metastasis stages. Moreover, end-of-treatment tumor regression is a reliable indicator of treatment sensitivity. This study aimed to investigate whether quantitative dual-energy computed tomography (DECT) parameters could predict sensitivity to neck-lymph node radiotherapy in patients with NPC., Methods: Overall, 388 lymph nodes were collected from 98 patients with NPC who underwent pretreatment DECT. The patients were divided into complete response (CR) and partial response (PR) groups. Clinical characteristics and quantitative DECT parameters were compared between the groups, and the optimal predictive ability of each parameter was determined using receiver operating characteristic (ROC) analysis. A nomogram prediction model was constructed and validated using univariate and binary logistic regression., Results: DECT parameters were higher in the CR group than in the PR group. The iodine concentration (IC), normalized IC, Mix-0.6, spectral Hounsfield unit curve slope, effective atomic number, and virtual monoenergetic images were significantly different between the groups. The area under the ROC curve of the DECT parameters was 0.73-0.77. Based on the binary logistic regression, a column chart was constructed using 10 predictive factors, including age, sex, N stage, maximum lymph node diameter, arterial phase NIC, venous phase NIC, λHU and spectral Hounsfield units at 70 keV. The area under the ROC curve value of the constructed model was 0.813, with a sensitivity and specificity of 85.6% and 81.3%, respectively., Conclusion: Quantitative DECT parameters could effectively predict the sensitivity of NPC to radiotherapy. Therefore, DECT parameters and NPC clinical features can be combined to construct a nomogram with high predictive power and used as a clinical analytical tool., (© 2024. The Author(s).)

Dual-energy CT (DECT) imaging has broadened the potential of CT imaging by offering multiple postprocessing datasets with a single acquisition at more than one energy level. DECT shows profound capabilities to improve diagnosis based on its superior material differentiation and its quantitative value. However, the potential of dual-energy imaging remains relatively untapped, possibly due to its intricate workflow and the intrinsic technical limitations of DECT. Knowing the clinical advantages of dual-energy imaging and recognizing its limitations and pitfalls is necessary for an appropriate clinical use. The aims of this paper are to review the physical and technical bases of DECT acquisition and analysis, to discuss the advantages and limitations of DECT in different clinical scenarios, to review the technical constraints in material labeling and quantification, and to evaluate the cutting-edge applications of DECT imaging, including artificial intelligence, qualitative and quantitative imaging biomarkers, and DECT-derived radiomics and radiogenomics.