Dual-energy Scan Research Articles

Non-electrocardiography-gated dual-energy cardiac CT angiography for assessment of left atrial appendage thrombus

ObjectiveTo explore the diagnosis value of a low dose, dual-energy cardiac computed tomography angiography (CTA) with non-electrocardiography-gated (non-ECG-gated) in detecting left atrial appendage (IAA) thrombus. MethodsConsecutive patients with atrial fibrillation who underwent cardiac CTA protocol (dual-energy scan for arterial phase and conventional scan for delayed phase) were prospectively enrolled. LAA lesions were proved by clinical comprehensive diagnosis, the final study included 18 cases with LAA thrombus and 48 cases with circulatory stasis. Quantitative parameters derived from dual-energy images were measured for the LAA lesions, including the conventional CT attenuation value (CT value), iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number values (Zeff) and energy spectrum curve slope (Slope). The differences between LAA thrombus group and circulatory stasis group were compared by independent sample t-test or Wilcoxon rank sum test regarding to the normality test. The diagnosis performance of the dual-energy parameters was assessed using receiver operating characteristic (ROC) curve analysis and area under curve (AUC). ResultsAll the dual-energy parameters were demonstrated significantly difference between LAA thrombus and circulatory stasis group (P＜0.05), and showed better diagnostic performance than the conventional CT value. ROC analysis revealed IC was the most predictive parameter with AUC equal to 0.836. The radiation dose in the arterial phase was (2.64 ​± ​0.66) mSv. ConclusionDual-energy CTA scanning shows convincing diagnostic performance in detecting left atrial appendage thrombus with lower radiation dose, and may help reduce the need for delayed phase scan.

Diet and Lifestyle Intervention-Induced Pattern of Weight Loss Related to Reduction in Low-Attenuation Coronary Plaque Burden.

Despite extensive research on body weight and cardiovascular risk, the mechanistic relationship between weight loss and coronary plaque modification has not been adequately addressed. This study aimed to determine the association between body composition dynamics and low-attenuation coronary plaque (LAP) burden. Eighty-nine participants (40% women, 60 ± 7.7 years) of the Dietary Intervention to Stop Coronary Atherosclerosis in Computed Tomography (DISCO-CT) study with non-obstructive atherosclerosis with nonobstructive atherosclerosis confirmed in computed tomography angiography (CCTA), a randomized (1:1), prospective, single-center study were included into the analysis. Patients were randomly assigned to either experimental arm (intensive diet and lifestyle intervention atop optimal medical therapy, n = 45) or control arm (optimal medical therapy alone, n = 44) over 66.8 ± 13.7 weeks. Changes (∆) in body mass (BM) and body composition parameters, including total body fat (TBF), skeletal muscle mass (SMM), and fat-to-muscle ratio (FMR), measured with bioimpedance analyzer were compared with CCTA-measured ∆LAP. Coronary plaque analysis was performed using the 2 × 192 dual-energy scanner (Somatom Force, Siemens, Germany), while quantitative coronary plaque measurements were performed using a semi-automated plaque analysis software system (QAngioCT v3.1.3.13, Medis Medical Imaging Systems, Leiden, The Netherlands). Significant intergroup differences were found for ∆BM (-3.6 ± 4.9 kg in the experimental vs. -1.4 ± 2.9 kg in the control group, p = 0.015), ∆TBF (-3.4 ± 4.8% in the experimental vs. 1.1 ± 5.5% in the control arm, p < 0.001), ∆SMM (1.9 ± 2.8% in the experimental vs. -0.7 ± 3.2% in the control arm, p < 0.001), and FMR [-12.9 (-21.2; -4.3)% in the experimental vs. 3.1 (-5.3; 10.7)% in the control arm, p < 0.001]. ∆LAP did not differ significantly between the study arms; however, in the whole study population, ∆LAP was positively correlated with ∆BM, ∆TBF, and ∆FMR (r = 0.45, p < 0.001; r = 0.300, p = 0.004; r = 0.233, p = 0.028, respectively), and negatively with ∆SMM (r = -0.285, p = 0.007). Multivariate linear regression analysis revealed the association of ∆LAP with ∆BM, ∆TBF, and ∆FMR. The study intervention resulted in BM reduction characterized by fat loss, skeletal muscle gain, and increased FMR. This weight loss pattern may lead to a reduction in high-risk coronary plaque. Compared to a simple weight control, tracking body composition changes over time can provide valuable information on adverse coronary plaque modification.

Assessing the diagnostic accuracy of artificial intelligence in post-endovascular aneurysm repair endoleak detection using dual-energy computed tomography angiography.

The aim of this study was to evaluate the diagnostic accuracy of an artificial intelligence (AI) tool in detecting endoleaks in patients undergoing endovascular aneurysm repair (EVAR) using dual-energy computed tomography angiography (CTA). The study involved 95 patients who underwent EVAR and subsequent CTA follow-up. Dualenergy scans were performed, and images were reconstructed as linearly blended (LB) and 40 keV virtual monoenergetic (VMI) images. The AI tool PRAEVAorta®2 was used to assess arterial phase images for endoleaks. Two experienced readers independently evaluated the same images, and their consensus served as the reference standard. Key metrics, including accuracy, precision, recall, F1 score, and area under the receiver operating characteristic (ROC) curve (AUC), were calculated. The final analysis included 94 patients. The AI tool demonstrated an accuracy of 78.7%, precision of 67.6%, recall of 10 71.9%, F1 score of 69.7%, and an AUC of 0.77 using LB images. However, the tool failed to process 40 keV VMI images correctly, limiting further analysis of these datasets. The AI tool showed moderate diagnostic accuracy in detecting endoleaks using LB images but failed to achieve the reliability needed for clinical use due to the significant number of misdiagnoses.

The Application of Dual-layer Spectral Detector CT in Abdominal Vascular Imaging.

As a convenient and non-invasive diagnostic method, computed tomography (CT) has been developing continuously, and dual-energy CT imaging is one of its current research hotspots. Dualenergy CT, using two different X-ray energies for imaging, can generate spectral image sets such as virtual monoenergetic images, virtual non-contrast images, iodine density images, uric acid images, calcium inhibition images, and effective atomic number images. These images could help to increase the contrast of vascular, improve the detection rate of lesions, reduce artifacts, reduce the dose of radiation, and characterize materials. Dual-layer spectral detector CT, a detector-based dual-energy scanning device, has an X-ray tube and a dual-layer X-ray detector that can simultaneously separate lowenergy and high-energy photons from a multi-energy X-ray beam, which means excellent time registration. This paper aims to introduce the applications of dual-layer spectral detector CT in abdominal angiography, including optimizing image quality, reducing the dose of contrast agent and radiation, providing richer diagnostic information, organ perfusion, and thrombus identification.

Accuracy of iodine quantification in dual energy CT: A phantom study across 3 different CT systems

IntroductionNo study has rigorously compared the performances of iodine quantification on recent CT systems employing different emission-based technologies, depending on the manufacturers and models. MethodsA specific bespoke phantom was used for this study, with 12 known concentrations of iodinated contrast agent: 0.4, 0.5, 1.0, 2.0, 3.0, 4.0, 5.0, 10.0, 15.0, 20.0, 30.0 and 50.0 mg/mL. Three different dual-energy scanners were tested: one system using dual-source acquisition (CT#1) and two systems using Fast kilovolt-peak switching technology ± artificial intelligence (AI) reconstruction methods (CT#2 and #3) from two different manufacturers. For each system, helical scans were performed following recommended clinical protocols. Four acquisitions were performed per iodine concentration (mg/mL), and measurements were made on iodine-maps using ROIs. Mean measured values were compared to the known concentrations, and the absolute quantification error (AQE) and the relative percentage error (RPE) were used to compare the performances of each CT. ResultsThe accuracy of the obtained measurements varied depending on the studied model but not on the acquisition mode (dual-source vs kVp switch ± AI). The quantification was more precise at high concentrations. RPE values were below 10 % with CT#2 (kVp switch) and below 25 % with CT#1 (dual-source), but were significantly higher with CT#3 (kVp switch + AI), exceeding 50 % at low concentrations (<3 mg/mL). ConclusionsWith the help of a phantom, we identified variability in the results accuracy depending on the CT model, with sometimes significant deviation. Considering the performances of the different DECT technologies in iodine mapping, dual-source (CT#1) and kVp switch (CT#2) technologies appear more accurate than kVp switch technology combined with deep-learning-based reconstruction (CT#3) especially at low concentrations (<3 mg/mL). Implications for practiceAs the primary and daily user of medical imaging devices, the radiographer role is to be attentive to the performance of imaging systems, particularly when performing quantitative acquisitions like iodine-quantification. In CT quantitative imaging (iodine map), it's essential for radiographers to consider their CT systems as measuring tools, and to be aware of their accuracies and limits.

Application of dual-energy CT with prospective ECG-gating in cardiac CT angiography for children: Radiation and contrast agent dose

ObjectiveThis research aimed to investigate the feasibility of utilizing dual-energy CT virtual monoenergetic images (VMI11VMI:virtual monoenergetic images.) with prospective electrocardiogram (ECG22ECG:electrocardiogram.) gating for reducing radiation and contrast agent doses in pediatric patients with congenital heart disease (CHD33CHD:congenital heart disease.). MethodsThere were 100 pediatric patients with CHD included in this study. Group A (n = 50) underwent dual-energy scanning with prospective ECG-gating, and group B (n = 50) underwent conventional scanning with retrospective ECG-gating. Comparative analysis of CT values of lumen, objective image quality assessment, subjective image quality evaluations, and diagnostic efficacy were performed. ResultsCT values, image noise, signal-to-noise ratio (SNR44SNR:signal-to-noise ratio.), and contrast-to-noise ratio (CNR55CNR:contrast-to-noise ratio.) were significantly affected by the VMI energy level, and they all increased with decreasing energy levels (P > 0.05). Combining subjective evaluation, the 45 keV VMI was considered the optimum image in group A. The 45 keV VMI exhibited higher CT values of lumen compared to conventional scanning images (P < 0.003 ∼ 0.836), but meanwhile, the image noise was also higher in the 45 keV VMI (P = 0.004). Differences between the two groups in SNR, CNR, and diagnostic accuracy were not statistically significant. Compared to group B, the 45 keV VMI showed fewer contrast-induced artifacts (P < 0.001) and higher image quality score (P = 0.037). Group A had a 64 % reduction in radiation dose and a 40 % decrease in iodine dose compared to group B. ConclusionThe combination of dual-energy CT with prospective ECG-gating reduces radiation and iodine doses in pediatric patients with CHD. The 45 keV VMI can provide clinically acceptable image quality while declining contrast agent artifacts.

An Efficient Transformer Model for Synthesizing Dual Energy CT from Single Energy Scanner

Dual-energy CT can be used to optimize radiation treatment. Recently, deep learning has been demonstrated to synthesize high-energy CT images from low-energy ones for dose reduction and lower CT system burden. As the state-of-the-art deep learning architecture, the computation burden of Transformer increases quadratically with the feature size, making the model training resource-demanding or even infeasible. Here, we introduce an efficient transformer for the balance between CT image synthesis quality and computational burden. The model is a U-shape deep neural network with encoders and decoders built by Transformer blocks. The model input is low-energy 100kVp CT image and the output is high-energy 140kVp one. Each block has a Self Channel Correlation Unit (SCCU) and a Self Spatial Attention Unit (SSAU). Local shortcuts are applied for both units. Under-sampling operation achieved by pixel shuffling is used to obtain multi-scale feature maps, and the transformer block is applied on each feature scale. Symmetric skip connection sending features from shallow layers to deep layers, thus an additional 1 × 1 convolution is used for feature fusion in each decoder. In a SCCU, the feature is first mapped to one Query, one Key, and one Value. Then the Query and the Key tensors perform matrix multiplication to compute cross covariance of feature channels. The channel correlation score can be obtained by normalization of the covariance, and it is used to weight the Value tensor. As a result, the model complexity only increases linearly with the feature size. Besides the channel weighting, we enhance spatial information using SSAU, where the feature is mapped to two tensors. One tensor after activation is used to point-wisely calibrate another tensor. Additional Transformer blocks are cascaded to the last decoder for feature refinement. Because of the structure similarity of low- and high-energy CT images, a global shortcut is used to ease model training. Clinical iodine contrast-enhanced dual energy CT image datasets of 19 patients are used in this study. The dual-energy scanning is performed by a SOMATOM Definition Flash DECT scanner. We split the datasets into training dataset of 15 patients, validation dataset of 1 patient, and testing dataset of 3 patients. The image size is 512 × 512 with pixel size 0.5 × 0.5 mm2. The U-Net model with 1.95M parameters and 44.87G FLOPS achieved the averaged PSNR value of 44.55 dB (s.t.d. 1.34) and averaged RMSE value of 0.0060 (s.t.d. 0.001). In comparison, our efficient Transformer with 1.408M parameters and 31.375G FLOPS achieved the averaged PSNR value of 44.78 dB (s.t.d. 1.37) and RMSE value of 0.0059 (s.t.d. 0.001), demonstrating our model has better performance with small model size and less computation. The efficient Transformer model allows high-resolution CT image synthesis with small model scale and computation burden from low-energy CT image.

Raw data consistent deep learning-based field of view extension for dual-source dual-energy CT.

Due to technical constraints, dual-source dual-energy CT scans may lack spectral information in the periphery of thepatient. Here, we propose a deep learning-based iterative reconstruction to recover the missing spectral information outside the field of measurement (FOM) of the second source-detectorpair. In today's Siemens dual-source CT systems, one source-detector pair (referred to as A) typically has a FOM of about 50cm, while the FOM of the other pair (referred to as B) is limited by technical constraints to a diameter of about 35cm. As a result, dual-energy applications are currently only available within the small FOM, limiting their use for larger patients. To derive a reconstruction at B's energy for the entire patient cross-section, we propose a deep learning-based iterative reconstruction. Starting with A's reconstruction as initial estimate, it employs a neural network in each iteration to refine the current estimate according to a raw data fidelity measure. Here, the corresponding mapping is trained using simulated chest, abdomen, and pelvis scans based on a data set containing 70 full body CT scans. Finally, the proposed approach is tested on simulated and measured dual-source dual-energy scans and compared against existing referenceapproaches. For all test cases, the proposed approach was able to provide artifact-free CT reconstructions of B for the entire patient cross-section. Considering simulated data, the remaining error of the reconstructions is between 10 and 17HU on average, which is about half as low as the reference approaches. A similar performance with an average error of 8HU could be achieved for real phantommeasurements. The proposed approach is able to recover missing dual-energy information for patients exceeding the small 35cm FOM of dual-source CT systems. Therefore, it potentially allows to extend dual-energy applications to the entire-patient crosssection.

Quantitative performance of photon-counting CT at low dose: Virtual monochromatic imaging and iodine quantification.

Quantitative imaging techniques, such as virtual monochromatic imaging (VMI) and iodine quantification (IQ), have proven valuable diagnostic methods in several specific clinical tasks such as tumor and tissue differentiation. Recently, a new generation of computed tomography (CT) scanners equipped with photon-counting detectors (PCD) has reached clinical status. This work aimed to investigate the performance of a new photon-counting CT (PC-CT) in low-dose quantitative imaging tasks, comparing it to an earlier generation CT scanner with an energy-integrating detector dual-energy CT (DE-CT). The accuracy and precision of the quantification across size, dose, material types (including low and high iodine concentrations), displacement from iso-center, and solvent (tissue background) composition wereexplored. Quantitative analysis was performed on two clinical scanners, Siemens SOMATOM Force and NAEOTOM Alpha using a multi-energy phantom with plastic inserts mimicking different iodine concentrations and tissue types. The tube configurations in the dual-energy scanner were 80/150Sn kVp and 100/150Sn kVp, while for PC-CT both tube voltages were set to either 120 or 140 kVp with photon-counting energy thresholds set at 20/65 or 20/70 keV. The statistical significance of patient-related parameters in quantitative measurements was examined using ANOVA and pairwise comparison with the posthoc Tukey honest significance test. Scanner bias was assessed in both quantitative tasks for relevant patient-specificparameters. The accuracy of IQ and VMI in the PC-CT was comparable between standard and low radiation doses (p < 0.01). The patient size and tissue type significantly affect the accuracy of both quantitative imaging tasks in both scanners. The PC-CT scanner outperforms the DE-CT scanner in the IQ task in all cases. Iodine quantification bias in the PC-CT (-0.9 ± 0.15 mg/mL) at low doses in our study was comparable to that of DE-CT (range -2.6 to 1.5 mg/mL, published elsewhere) at a 1.7× higher dose, but the dose reduction severely biased DE-CT (4.72 ± 0.22 mg/mL). The accuracy in Hounsfield units (HU) estimation was comparable for 70 and 100 keV virtual imaging between scanners, but PC-CT was significantly underestimating virtual 40 keV HU values of dense materials in the phantom representing the extremely obesepopulation. The statistical analysis of our measurements reveals better IQ at lower radiation doses using new PC-CT. Although VMI performance was mostly comparable between the scanners, the DE-CT scanner quantitatively outperformed PC-CT when estimating HU values in the specific case of very large phantoms and dense materials, benefiting from increased X-ray tubepotentials.

High-resolution computed tomography angiography of the orbit using a photon-counting computed tomography scanner.

Recent introduction of photon counting detector (PCD) computed tomography (CT) scanners into clinical practice further improve CT angiography (CTA) depiction of orbital arterial vasculature compared to conventional energy integrating detector (EID) CT scanners. PCD-CTA of the orbit can provide a detailed arterial roadmap of the orbit which can de diagnostic on its own or serve as a helpful planning adjunct for both diagnostic and therapeutic catheter-based angiography of the orbit. For this review, EID and PCD-CT imaging was obtained in 28 volunteers. The volume CT dose index was closely matched. A dual-energy scanning protocol was used on EID-CT. An ultra-high-resolution (UHR) scan mode was used on PCD-CT. Images were reconstructed at 0.6 mm slice thickness using a closely matched medium-sharp standard resolution (SR) kernel. High-resolution (HR) images with the sharpest quantitative kernel were also reconstructed on PCD-CT at the thinnest slice thickness of 0.2 mm. A denoising algorithm was applied to the HR image series. The imaging description of the orbital vascular anatomy presented in this work was derived from these patients' PCD-CTA images in combination with review of the literature. We found that orbital arterial anatomy is much better depicted with PCD-CTA, and this work can serve primarily as an imaging atlas of the normal orbital vascular anatomy. With recent advances in technology, arterial anatomy of the orbit is much better depicted with PCD-CTA as opposed to EID-CTA. Current orbital PCD-CTA technology approaches the necessary resolution threshold for reliable evaluation of central retinal artery occlusion.

Myocardial Characterisation Using Delayed Dual-Energy Cardiac Computed Tomography

Myocardial characterisation is conventionally assessed using cardiac MRI (cMRI). Delayed dual-energy cardiac computed tomography (CTD) may provide useful myocardial characterisation in patients with acute myocardial infarction. This prospective case series described experience and feasibility of this technique in contemporary, real-world practice. Patients admitted to Auckland City Hospital, New Zealand, with acute myocardial infarction and found to have left ventricular thrombus were invited to participate. Three CT acquisitions timed at peak contrast enhancement arterial-phase (CTA), 60–70 seconds delay venous-phase (CTV), and 5 minutes delay dual-energy scan (CTDE) were performed. Using virtual monochromic energy, the myocardium was assessed between 40 keV and 80 keV at 10-keV increments. The CTDE findings were correlated with cMRI. The study was supported by the Greenlane Cardiovascular Fund. Between April 2019 and October 2021, nine patients were recruited and underwent CT assessment of the myocardium. Transmural infarction was found in six (67%) patients and microvascular obstruction (MVO) in four (44%) patients on CTD. All patients found to have transmural infarct (n=4) and MVO (n=2) on CTD correlated with the cMRI findings. Absence of transmural infarction (n=1) and MVO (n=3) was confirmed on cMRI. The Figure shows findings on CTD and cMRI consistent with microvascular obstruction. Myocardial assessment appears possible, with good correlation demonstrated when compared with cMRI, in the detection of transmural myocardial enhancement and presence of MVO following acute myocardial infarction.

Decomposition of musculoskeletal structures from radiographs using an improved CycleGAN framework

This paper presents methods of decomposition of musculoskeletal structures from radiographs into multiple individual muscle and bone structures. While existing solutions require dual-energy scan for the training dataset and are mainly applied to structures with high-intensity contrast, such as bones, we focused on multiple superimposed muscles with subtle contrast in addition to bones. The decomposition problem is formulated as an image translation problem between (1) a real X-ray image and (2) multiple digitally reconstructed radiographs, each of which contains a single muscle or bone structure, and solved using unpaired training based on the CycleGAN framework. The training dataset was created via automatic computed tomography (CT) segmentation of muscle/bone regions and virtually projecting them with geometric parameters similar to the real X-ray images. Two additional features were incorporated into the CycleGAN framework to achieve a high-resolution and accurate decomposition: hierarchical learning and reconstruction loss with the gradient correlation similarity metric. Furthermore, we introduced a new diagnostic metric for muscle asymmetry directly measured from a plain X-ray image to validate the proposed method. Our simulation and real-image experiments using real X-ray and CT images of 475 patients with hip diseases suggested that each additional feature significantly enhanced the decomposition accuracy. The experiments also evaluated the accuracy of muscle volume ratio measurement, which suggested a potential application to muscle asymmetry assessment from an X-ray image for diagnostic and therapeutic assistance. The improved CycleGAN framework can be applied for investigating the decomposition of musculoskeletal structures from single radiographs.

Prediction of low DEXA T-scores by routine computed tomography body scans at different kilovoltage peaks.

Previous studies have demonstrated positive correlations between computed tomography (CT) attenuation of lumbar spine vertebrae and their bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DEXA). However, these studies were performed using a standard 120 kilovoltage peak (kVp) setting. As radiation attenuation in mineralised tissues varies by the tube voltage applied, we determined the diagnostic accuracy of CT attenuation at identifying individuals with low BMD at different kVp settings. Single centre retrospective study of adults who had CT and DEXA scans within 6 months of each other. CT scans were performed at either 100 kVp, 120 kVp or dual energy (80 kVp/140 kVp). Attenuation was measured in axial cross-sections of L1-4 vertebrae and correlated with the results of DEXA. Receiver operated characteristic (ROC) curves were generated to determine diagnostic cut-off thresholds. Analysis included 268 subjects (169 females; mean age: 70, range: 20-94 years). CT attenuation values at L1 or mean L1-4 correlated positively with DEXA-derived T-scores. At L1, the optimal Hounsfield units (HU) thresholds for predicting DEXA T-scores of -2.5 or less at 100 kVp, 120 kVp and dual-energy scans were <170, <128 and <164, with corresponding AUCs of 0.925, 0.814 and 0.743 respectively. For mean L1-4, the HU thresholds were <173, <134 and <151, with corresponding AUCs of 0.933, 0.824 and 0.707 respectively. CT attenuation thresholds differ depending on the tube voltage used. We provide voltage-specific, probability-optimised thresholds for the identification of persons likely to have low BMD on DEXA scanning.

Report on the AAPM deep-learning spectral CT Grand Challenge.

This Special Report summarizes the 2022 AAPM Grand Challenge on Deep-Learning spectral Computed Tomography (DL-spectral CT) imagereconstruction. The purpose of the challenge is to develop the most accurate image reconstruction algorithm possible for solving the inverse problem associated with a fast kilovolt switching dual-energy CT scan using a three tissue-map decomposition. Participants could choose to use a deep-learning (DL), iterative, or a hybridapproach. The challenge is based on a 2D breast CT simulation, where the simulated breast phantom consists of three tissue maps: adipose, fibroglandular, and calcification distributions. The phantom specification is stochastic so that multiple realizations can be generated for DL approaches. A dual-energy scan is simulated where the x-ray source potential of successive views alternates between 50 and 80 kilovolts (kV). A total of 512 views are generated, yielding 256 views for each source voltage. We generate 50 and 80 kV images by use of filtered back-projection (FBP) on negative logarithm processed transmission data. For participants who develop a DL approach, 1000 cases are available. Each case consists of the three 512 × 512 tissue maps, 50 and 80-kV transmission data sets and their corresponding FBP images. The goal of the DL network would then be to predict the material maps from either the transmission data, FBP images, or a combination of the two. For participants developing a physics-based approach, all of the required modeling parameters are made available: geometry, spectra, and tissue attenuation curves. The provided information also allows for hybrid approaches where physics is exploited as well as information about the scanned object derived from the 1000 training cases. Final testing is performed by computation of root-mean-square error (RMSE) for predictions on the tissue maps from 100 newcases. Test phase submission were received from 18 research groups. Of the 18 submissions, 17 were results obtained with algorithms that involved DL. Only the second place finishing team developed a physics-based image reconstruction algorithm. Both the winning and second place teams had highly accurate results where the RMSE was nearly zero to single floating point precision. Results from the top 10 also achieved a high degree of accuracy; and as a result, this special report outlines the methodology developed by each of thesegroups. The DL-spectral CT challenge successfully established a forum for developing image reconstruction algorithms that address an important inverse problem relevant forspectral CT.

Virtual monochromatic images of dual-energy CT as an alternative to single-energy CT: performance comparison using a detectability index for different acquisition techniques.

To investigate the performance of virtual monochromatic (VM) images with the same dose and iodine contrast as those for single-energy (SE) images using five dual-energy (DE) scanners with DE techniques: two generations of fast kV switching (FKS), two generations of dual source (DS), and one split filter (SF). A water-bath phantom with a diameter of 300mm, which contains one rod-shaped phantom made of a material equivalent to soft-tissue and two rod-shaped phantoms made of diluted iodine (2 and 12mg/mL), was scanned using both SE (120, 100, and 80kV) and DE techniques with the same CT dose index in each scanner. The VM energy at which the CT number of the iodine rod is closest to that of each SE tube voltage was determined as the equivalent energy (Eeq). A detectability index (d') was calculated from the noise power spectrum, the task transfer functions, and a task function corresponding to each rod. The percentage of the d' value of the VM image to that of the corresponding SE image was calculated for performance comparison. The average percentages of d' of FKS1, FKS2, DS1, DS2, and SF were 84.6%, 96.2%, 94.3%, 107%, and 104% for 120kV-Eeq; 75.9%, 91.2%, 88.2%, 99.2%, and 82.6% for 100kV-Eeq; 71.6%, 88.9%, 82.6%, 85.2%, and 62.3% for 80kV-Eeq, respectively. The performance of VM images was on the whole inferior to that of SE images especially at low equivalent energy levels, depending on the DE techniques and their generations. • This study evaluated the performance of VM images with the same dose and iodine contrast as those for SE images using five DE scanners. • The performance of VM images varied with the DE techniques and their generations and was mostly inferior at low equivalent energy levels. • The results highlight the importance of distribution of available dose over the two energy levels and spectral separation for the performance improvement of VM images.

Energy dispersive x-ray CT using a fixed gantry design for material classification in aviation security x-ray screening

This work presents opportunities and challenges in energy dispersive CT systems for aviation security applications. Current security x-ray scanners use dual-energy systems for threat identification. Dual-energy scanners cannot clearly separate all materials, which results in high false-alarm rates and cause delays for travellers. The development of both new energy dispersive photon counting detectors and associated analysis algorithms allows for improved threat detection by employing energy dispersive scanner systems. The implementation in aviation of such systems as security x-ray scanners also poses several challenges, which are discussed in the paper.

Influence of Scan Parameters of Single and Dual-Energy CT Protocols in Combination with Metal Artifact Suppression Algorithms for THA: An ex Vivo Study.

Metal artifacts caused by hip arthroplasty stems limit the diagnostic value of computed tomography (CT) in the evaluation of periprosthetic fractures or implant loosening. The aim of this ex vivo study was to evaluate the influence of different scan parameters and metal artifact algorithms on image quality in the presence of hip stems. Nine femoral stems, 6 uncemented and 3 cemented, that had been implanted in subjects during their lifetimes were exarticulated and investigated after death and anatomical body donation. Twelve CT protocols consisting of single-energy (SE) and single-source consecutive dual-energy (DE) scans with and without an iterative metal artifact reduction algorithm (iMAR; Siemens Healthineers) and/or monoenergetic reconstructions were compared. Streak and blooming artifacts as well as subjective image quality were evaluated for each protocol. Metal artifact reduction with iMAR significantly reduced the streak artifacts in all investigated protocols (p = 0.001 to 0.01). The best subjective image quality was observed for the SE protocol with a tin filter and iMAR. The least streak artifacts were observed for monoenergetic reconstructions of 110, 160, and 190 keV with iMAR (standard deviation of the Hounsfield units: 151.1, 143.7, 144.4) as well as the SE protocol with a tin filter and iMAR (163.5). The smallest virtual growth was seen for the SE with a tin filter and without iMAR (4.40 mm) and the monoenergetic reconstruction of 190 keV without iMAR (4.67 mm). This study strongly suggests that metal artifact reduction algorithms (e.g., iMAR) should be used in clinical practice for imaging of the bone-implant interface of prostheses with either an uncemented or cemented femoral stem. Among the iMAR protocols, the SE protocol with 140 kV and a tin filter produced the best subjective image quality. Furthermore, this protocol and DE monoenergetic reconstructions of 160 and 190 keV with iMAR achieved the lowest levels of streak and blooming artifacts. Diagnostic Level III . See Instructions for Authors for a complete description of levels of evidence.

The application study of dual-energy CT nonlinear blending technique in pulmonary angiography*

Abstract Objective This study aimed to explore the feasibility of enhancing image quality in computed tomography (CT) pulmonary angiography (CTPA) and reducing radiation dose using the nonlinear blending (NLB) technique of dual-energy CT. Methods A total of 61 patients scheduled for CTPA were enrolled, and 30 patients underwent dual-energy scanning. Nonlinear blending images (NLB group) and three groups of linear blending images (LB group, 80 kV group, and 140 kV group) were reconstructed after scanning; 31 patients underwent single-energy scanning (120 kV group). The CT values and standard deviations of the pulmonary trunk, left and right pulmonary arteries, and ipsilateral back muscle at the bifurcation level of the left and right pulmonary arteries were measured. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the five groups were calculated. The subjective image quality of the five groups was assessed. The radiation doses of the dual- and single-energy groups were recorded and calculated. Results The CNR and SNR values of blood vessels in the NLB group were significantly higher than those in the LB, 140 kV, and 80 kV groups (CNR of pulmonary artery trunk: t = 3.50, 4.06, 7.17, all P &lt; 0.05; SNR of pulmonary trunk: t = 3.76, 4.71, 6.92, all P &lt; 0.05). There were no statistical differences in the CNR and SNR values between the NLB group and 120 kV group (P &gt; 0.05). The effective radiation dose of the dualenergy group was lower than that of the single-energy group (t = -4.52, P &lt; 0.05). The subjective scores of images in the NLB group were the highest (4.28 ± 0.74). Conclusion The NLB technique of dual-energy CT can improve the image quality of CTPA and reduce the radiation dose, providing more reliable imaging data for the clinical diagnosis of pulmonary embolism.

Value of dual-source CT dual-energy parameters combined with serum detection of VEGF and CEA in the diagnosis of early lung cancer

ABSTRACT To discuss the value of dual-source CT dual-energy parameters combined with serum detection of vascular endothelial growth factor (VEGF) and carcinoembryonic antigen (CEA) in the diagnosis of early lung cancer (LC). In total, 100 patients with lung lesions in our hospital from January 2020 to January 2022 were selected for retrospective study, and were divided into the lung cancer group (group A) and benign lung disease group (group B) according to the final results of pathological diagnosis, using dual-source CT dual-energy scanning combined with serum detection of VEGF and CEA to analyze the diagnostic values of single detection and combined detection. Among the 100 patients with lung lesions, there were 58 patients with LC and 42 patients with benign lung diseases after pathological examination, with no statistical difference in normalized iodine concentration (NIC) and the increased value of iodine at arterial phase between the two groups (P > 0.05). The NIC value of group A was higher than group B at venous phase (P < 0.05). The serum levels of VEGF and CEA in group A were higher than group B (P < 0.05). The area under the curve, specificity, sensitivity, Youden index and 95% CI of combined diagnosis were higher than single detection of NIC, VEGF and CEA at venous phase. The combined application of dual-source CT dual-energy parameters and serum detection of VEGF and CEA has higher diagnostic value in patients with early LC, which can provide effective reference for clinical diagnosis and treatment, with higher application value in clinic.

Advanced virtual monoenergetic imaging algorithm for lower extremity computed tomography angiography: effects on image quality, artifacts, and peripheral arterial disease evaluation

To investigate the image quality of lower extremity computed tomography angiography (LE-CTA) using a reconstruction algorithm for monoenergetic images (MEIs) to evaluate peripheral arterial disease (PAD) at different kiloelectron volt (keV) levels. A total of 146 consecutive patients who underwent LE-CTA on a dual-energy scanner to obtain MEIs at 40, 50, 60, 70, and 80 keV were included. The overall image quality, segmental image quality of the arteries and PAD segments, venous contamination, and metal artifacts from prostheses, which may compromise quality, were analyzed. The mean overall image quality of each MEI was 2.9 ± 0.7, 3.6 ± 0.6, 3.9 ± 0.3, 4.0 ± 0.2, and 4.0 ± 0.2 from 40 to 80 keV, respectively. The segmental image quality gradually increased from 40 to 70-80 keV until reaching its highest value. Among 295 PAD segments in 68 patients, 40 (13.6%) were scored at 1-2 at 40 keV and 13 (4.4%) were scored at 2 at 50 keV, indicating unsatisfactory image quality due to the indistinguishability between high-contrast areas and arterial calcifications. The segments exhibiting metal artifacts and venous contamination were reduced at 70-80 keV (2.6 ± 1.2, 2.7 ± 0.5) compared with at 40 keV (2.4 ± 1.1, 2.5 ± 0.7). The LE-CTA method using a reconstruction algorithm for MEIs at 70-80 keV can enhance the image quality for PAD evaluation and improve mitigate venous contamination and metal artifacts.