Dual-energy CT Imaging Research Articles

A New Outlook on the Ability to Accumulate an Iodine Contrast Agent in Solid Lung Tumors Based on Virtual Monochromatic Images in Dual Energy Computed Tomography (DECT): Analysis in Two Phases of Contrast Enhancement.

For some time, dual energy computed tomography (DECT) has been an established method used in a vast array of clinical applications, including lung nodule assessment. The aim of this study was to analyze (using monochromatic DECT images) how the X-ray absorption of solitary pulmonary nodules (SPNs) depends on the iodine contrast agent and when X-ray absorption is no longer dependent on the accumulated contrast agent. Sixty-six patients with diagnosed solid lung tumors underwent DECT scans in the late arterial phase (AP) and venous phase (VP) between January 2017 and June 2018. Statistically significant correlations (p ≤ 0.001) of the iodine contrast concentration were found in the energy range of 40–90 keV in the AP phase and in the range of 40–80 keV in the VP phase. The strongest correlation was found between the concentrations of the contrast agent and the scanning energy of 40 keV. At the higher scanning energy, no significant correlations were found. We concluded that it is most useful to evaluate lung lesions in DECT virtual monochromatic images (VMIs) in the energy range of 40–80 keV. We recommend assessing SPNs in only one phase of contrast enhancement to reduce the absorbed radiation dose.

DECT in Detection of Vertebral Fracture-associated Bone Marrow Edema: A Systematic Review and Meta-Analysis with Emphasis on Technical and Imaging Interpretation Parameters.

Background Dual-energy CT (DECT) shows promising performance in detecting bone marrow edema (BME) associated with vertebral body fractures. However, the optimal technical and image interpretation parameters are not well described. Purpose To conduct a systematic review and meta-analysis to determine the diagnostic performance of DECT in detecting BME associated with vertebral fractures (VFs), using different technical and image interpretation parameters, compared with MRI as the reference standard. Materials and Methods A systematic literature search was performed on July 9, 2020, to identify studies evaluating DECT performance for in vivo detection of vertebral BME. A random-effects model was used to derive estimates of the diagnostic accuracy parameters of DECT. The impact of relevant covariates in technical, image interpretation, and study design parameters on the diagnostic performance of DECT was investigated using subgroup analyses. Results Seventeen studies (with 742 of 2468 vertebrae with BME at MRI) met inclusion criteria. Pooled estimates of sensitivity, specificity, and area under the curve of DECT for vertebral body BME were 89% (95% CI: 84%, 92%), 96% (95% CI: 92%, 98%), and 96% (95% CI: 94%, 97%), respectively. Single-source consecutive scanning showed poor specificity (78%) compared with the dual-source technique (98%, P < .001). Specificity was higher using bone and soft-tissue kernels (98%) compared with using only soft-tissue kernels (90%, P = .001). Qualitative assessment had a better specificity (97%) versus quantitative assessment (90%) of DECT images (P = .01). Experienced readers showed considerably higher specificity (96%) compared with trainees (79%, P = .01). DECT sensitivity improved using a higher difference between low- and high-energy spectra (90% vs 83%, P = .04). Conclusion Given its high specificity, the detection of vertebral bone marrow edema with dual-energy CT (DECT) associated with vertebral fracture may obviate confirmatory MRI in an emergency setting. Technical parameters, such as the dual-source technique, both bone and soft-tissue kernels, and qualitative assessment by experienced readers, can ensure the high specificity of DECT. © RSNA, 2021 Online supplemental material is available for this article.

Detection of bone marrow edema in osteonecrosis of the femoral head using virtual noncalcium dual-energy computed tomography

PurposeTo determine the diagnostic performance of virtual noncalcium (VNCa) dual-energy computed tomography (DECT) in the detection of bone marrow edema (BME) in participants with osteonecrosis of the femoral head (ONFH). MethodsIn this prospective study, 24 consecutive participants (15 men, 9 women; mean age, 44 years, range, 21–72 years) diagnosed with ONFH who underwent DECT and magnetic resonance imaging (MRI) between September 2019 and January 2020 were involved. Two independent readers visually evaluated color-coded VNCa images using a binary classification (0 = normal bone marrow, 1 = BME). MRI served as the reference standard for the presence of BME. Interobserver agreement for the visual evaluation of VNCa DECT images was calculated with κ statistics. We determined computed tomography (CT) numbers on VNCa images and weighted-average CT sets using region-of-interest-based quantitative analysis. The t-test was used to compare the differences of CT values between BME areas and normal bone marrow areas. Receiver operating characteristic (ROC) curve was used to select an optimal CT values of VNCa images for detecting BME. A p value of <0.05 was considered as statistically significant. ResultsThe sensitivity, specificity, and accuracy of Reader 1 and Reader 2, respectively, in the identification of BME at DECT were 95 % and 89 % (18 and 17 of 19), 96 % and 96 % (25 and 25 of 26), and 93 % (43 and 42 of 45). Interobserver agreement was excellent (κ = 0.86). The VNCa CT numbers of the BME area and the normal bone marrow area were −28.6 (−17.9–−39.4) HU and −97.9 (−91.3–−104.4) HU, respectively, with statistical significance (t = −10.6, p < 0.001). The weighted-average CT numbers of the BME area and the normal bone marrow area were 152.4(122.2–182.7) HU and 121.1(103.6–183.6) HU, respectively, with no statistical significance (t = −2.0, p > 0.05). The area under the receiver operating characteristic curve was 0.99 in differentiation of the BME from normal bone marrow. A cut-off value of −57.2 HU yielded overall sensitivity, specificity, and accuracy, respectively, of 95 % (18 of 19), 100 % (26 of 26), and 98 % (44 of 45) detection of BME in participants with ONFH. ConclusionVisual and quantitative analyses of VNCa images shows excellent diagnostic performance for assessing BME in participants with ONFH.

Skeletal muscle fat quantification by dual-energy computed tomography in comparison with 3T MR imaging

ObjectivesTo quantify the proportion of fat within the skeletal muscle as a measure of muscle quality using dual-energy CT (DECT) and to validate this methodology with MRI.MethodsTwenty-one patients with abdominal contrast-enhanced DECT scans (100 kV/Sn 150 kV) underwent abdominal 3-T MRI. The fat fraction (DECT-FF), determined by material decomposition, and HU values on virtual non-contrast-enhanced (VNC) DECT images were measured in 126 regions of interest (≥ 6 cm2) within the posterior paraspinal muscle. For validation, the MR-based fat fraction (MR-FF) was assessed by chemical shift relaxometry. Patients were categorized into groups of high or low skeletal muscle mean radiation attenuation (SMRA) and classified as either sarcopenic or non-sarcopenic, according to the skeletal muscle index (SMI) and cut-off values from non-contrast-enhanced single-energy CT. Spearman’s and intraclass correlation, Bland-Altman analysis, and mixed linear models were employed.ResultsThe correlation was excellent between DECT-FF and MR-FF (r = 0.91), DECT VNC HU and MR-FF (r = - 0.90), and DECT-FF and DECT VNC HU (r = − 0.98). Intraclass correlation between DECT-FF and MR-FF was good (r = 0.83 [95% CI 0.71–0.90]), with a mean difference of - 0.15% (SD 3.32 [95% CI 6.35 to − 6.66]). Categorization using the SMRA yielded an eightfold difference in DECT VNC HU values between both groups (5 HU [95% CI 23–11], 42 HU [95% CI 33–56], p = 0.05). No significant relationship between DECT-FF and SMI-based classifications was observed.ConclusionsFat quantification within the skeletal muscle using DECT is both feasible and reliable. DECT muscle analysis offers a new approach to determine muscle quality, which is important for the diagnosis and therapeutic monitoring of sarcopenia, as a comorbidity associated with poor clinical outcome.Key Points• Dual-energy CT (DECT) material decomposition and virtual non-contrast-enhanced DECT HU values assess muscle fat reliably.• Virtual non-contrast-enhanced dual-energy CT HU values allow to differentiate between high and low native skeletal muscle mean radiation attenuation in contrast-enhanced DECT scans.• Measuring muscle fat by dual-energy computed tomography is a new approach for the determination of muscle quality, an important parameter for the diagnostic confirmation of sarcopenia as a comorbidity associated with poor clinical outcome.

A quantitative assessment of dual energy computed tomography-based material decomposition for imaging bone marrow edema associated with acute knee injury.

This study developed methods to quantify and improve the accuracy of dual-energy CT (DECT)-based bone marrow edema imaging using a clinical CT system. Objectives were: (a) to quantitatively compare DECT with gold-standard, fluid-sensitive MRI for imaging of edema-like marrow signal intensity (EMSI) and (b) to identify image analysis parameters that improve delineation of EMSI associated with acute knee injury on DECT images. DECT images from ten participants with acute knee injury were decomposed into estimated fractions of bone, healthy marrow, and edema based on energy-dependent differences in tissue attenuation. Fluid-sensitive MR images were registered to DECT for quantitative, voxel-by-voxel comparison between the two modalities. An optimization scheme was developed to find attenuation coefficients for healthy marrow and edema that improved EMSI delineation, compared to MRI. DECT method accuracy was evaluated by measuring dice coefficients, mutual information, and normalized cross correlation between the DECT result and registered MRI. When applying the optimized three-material decomposition method, dice coefficients for EMSI identified through DECT vs MRI were 0.32 at the tibia and 0.13 at the femur. Optimization of attenuation coefficients improved dice coefficient, mutual information, and cross-correlation between DECT and gold-standard MRI by 48%-107% compared to three-material decomposition using non-optimized parameters, and improved mutual information and cross-correlation by 39%-58% compared to the manufacturer-provided two-material decomposition. This study quantitatively evaluated the performance of DECT in imaging knee injury-associated EMSI and identified a method to optimize DECT-based visualization of complex tissues (marrow and edema) whose attenuation parameters cannot be easily characterized. Further studies are needed to improve DECT-based EMSI imaging at the femur.

Observation of targeted gold nanoparticles in nasopharyngeal tumour nude mice model through dual-energy computed tomography.

This study was performed to specify the efficiency of imaging nanoparticle concentration as contrast media in dual‐energy computed tomography (DECT). Gold nanoparticles (AuNPs) and gold nanoparticles‐conjugated folic acid through cysteamine (FA‐Cya‐AuNPs) were both considered as contrast agents. Characterization of NPs was performed using Dynamic Light Scattering (DLS) and zeta potential. The hemocompatibility of NPs was confirmed by different blood parameters such as white blood cell, red cell distribution width, hemoglobin, lymphocytes counts and haemolysis assay. DECT algorithm was confirmed using calibration phantom at different concentrations of NPs and tube potentials (80 and 140 kVp). Then, DECT was used to quantify the concentration of both AuNPs and FA‐Cys‐AuNPs in human nasopharyngeal cancer cells. Mice were injected with non‐targeted AuNPs and targeted AuNps at a concentration of 3 × 103 μg/ml. Then, they were scanned with different tube potentials. The concentration of nanoparticles in the various organs of nude mice was measured through DECT imaging and inductively coupled plasma mass spectrometry (ICP‐MS) analysis. The results of DECT images were compared with ICP‐MS analysis and indicated that they were approximately similar. In sum, FA‐Cys‐AuNPs can be a proper candidate for targeted contrast media in DECT molecular scanning of human nasopharyngeal tumours.

Prediction of ipsilateral lateral cervical lymph node metastasis in papillary thyroid carcinoma: a combined dual-energy CT and thyroid function indicators study

BackgroundPredicting the possibility of ipsilateral lateral cervical lymph node metastasis (ipsi-LLNM) was crucial to the operation plan for patients with papillary thyroid carcinoma (PTC). This study aimed to investigate the independent risk factors for ipsi-LLNM in PTC patients by combining dual-energy computed tomography (DECT) with thyroid function indicators.MethodsWe retrospectively enrolled 406 patients with a pathological diagnosis of PTC from Jan 2016 to Dec 2019. Ensure the DECT images were clear and the thyroid function indicators were complete. Univariate and multivariate logistic analyses explored the independent risk factors for ipsi-LLNM. To evaluate the cutoff value of each risk factor by using receiver operating characteristic (ROC) curves.ResultsA total of 406 patients with PTC were analyzed, including 128 with ipsi-LLNM and 278 without ipsi-LLNM. There were statistical differences of parameters between the two groups (P < .0001), including serum Tg, Anti-Tg, Anti-TPO, the volume of the primary lesion, calcification, extrathyroidal extension (ETE), and iodine concentration (IC) in the arterial and the venous phases. Independent risk factors for ipsi-LLNM included serum Tg, Anti-Tg, ETE, and IC in the arterial and the venous phases (P < .05). The combined application of the above independent risk factors can predict the possibility of ipsi-LLNM, with an AUC of 0.834. Ipsi-LLNM was more likely to occur when the following conditions were met: with ETE, Tg > 100.01 ng/mL, Anti-Tg > 89.43 IU/mL, IC in arterial phase > 3.4 mg/mL and IC in venous phase > 3.1 mg/mL.ConclusionsThe combined application of DECT quantitative parameters and thyroid function indicators can help clinicians accurately predict ipsi-LLNM before surgery, thereby assisting the individualized formulation of surgical procedures.

Dual-Energy Computed Tomography Virtual Noncalcium Imaging for the Detection of Acute Bone Marrow Edema in Vertebrae: Qualitative and Quantitative Analysis

Purpose: To evaluate the feasibility of dual-energy computed tomography (DECT) virtual noncalcium (VNCa) images for detecting vertebral bone marrow edema (BME), both in qualitative and quantitative analyses. Materials and Methods: Nineteen cases with acute spinal trauma were enrolled. DECT and MR Imaging were performed over an interval of 0–3 days within 3 weeks of injury. Both gray-scale and color-coded VNCa images were evaluated in an independent and blind manner using a three-scale grading system (2 = distinct BME, 1 = suspicious BME, and 0 = no edema) by two radiologists. CT value of bone marrow were measured for each region and subjected to receiver operating characteristic (ROC) curve analysis for diagnosis of BME on VNCa images from DECT. Subsequently, as a standard of reference, MR imaging was evaluated by a third radiologist for the presence of traumatic BME. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the detection of BME using VNCa images were evaluated. Kappa analysis and one-way ANOVA were performed to evaluate the consistency and variance of VNCa images in the BME. Results: For two observers, the sensitivity of VNCa images for detecting BME (grade 2) were 97.8% and 96.7%, with the specificity 76% and 72%, the PPV 93.8% and 92.7%, the NPV 90.5% and 85.7%, respectively. And the sensitivity for detecting BME (grade 1–2) were 94.3% and 94.3%, with the specificity 96.7% and 93.3%, the PPV 98.8% and 97.6%, the NPV 85.3% and 84.8%, respectively. The consistency test between the two observers showed that Kappa value was 0.650 (P &lt; 0.001). The VNCa images had higher CT value in the positive regions than in the negative regions (P &lt; 0.05). Statistically significant differences in the CT value were identified in different regions with the three-scale grading system (thoracic levels: F = 136.690, P &lt; 0.001; lumbar levels: F = 92.689, P &lt; 0.001). Conclusions: Acute traumatic BME in the vertebrae can be detected on VNCa images in both qualitative and quantitative analyses. DECT VNCa images are expected to serve as an additional method for the evaluation of BME.

Abstract P327: Utilizing Iodine Contrast Extravasation Post Reperfusion and Dual Energy Ct Imaging to Predict Risk of Hemorrhagic Conversion in Acute Stroke Patients

Introduction: Hyperintense acute reperfusion marker (HARM) has been identified on post-contrast magnetic resonance imaging (MRI) to be a marker of hemorrhagic conversion (HC) post reperfusion therapy in acute stroke patients. We have previously described a case where MRI HARM was mimicked on post contrast computed topography (CT) imaging in an acute stroke patient post reperfusion. Dual-Energy (DECT) allows for differentiation between acute blood and iodine contrast extravasation (ICE), and thus can have utility when ICE is present. Here we sought to validate whether post-intervention ICE/CT hyperdensity reperfusion maker (CT HARM), and contrast subtracted on DECT is associated with HC in acute stroke patients. Method: Data was obtained from our Institutional Review Board approved stroke admission database from January 2017 to November 2019, including ischemic stroke patients that received thrombolysis or thrombectomy, had evaluable images within 24 hours of admission, and received a DECT. Ischemic volumes of the stroke was measured on diffusion-weighted image (DWI). ICE was measured on CT head and DECT using the freehand 3D region of interest tool on the Visage Imaging PACS System. Susceptibility weighted MRI sequences were used to grade HC. Data analysis was conducted with regression modeling. Results: A total of 82 patients were included, 49% women, median age 73 (interquartile range (IQR), 61- 77), admission NIHSS 12 (IQR, 7 - 21), 24 hour change in NIHSS 4 (IQR, 0 -13), glucose 125 (IQR, 106 -158), creatinine 1.0 (IQR, 0.8 - 1.2), infarct volume 50.6 ± 7.1 mL, 48% treated with thrombectomy, 7% with PH-1 or PH-2 identified on MRI, and 56% with MCA infarcts. ICE volume was 2.6 ± 1.0 mL and DECT volume was 2.2 ± 1.1mL. ICE increased the likelihood of MRI confirmed PH-1 or PH-2 hemorrhagic conversion (odds ratio (OR) 14.34, 95% confidence interval (CI) 5.74 - 22.94) and decreased likelihood of increase in NIHSS at 24 hours (OR 0.20, 95% CI 0.01 to 0.40). There were no other significant associations with ICE or DECT volumes. Conclusion: Our results are supportive of our proposed association between CT HARM and risk of HC. More studies are needed to study whether quantitative of DECT can be predictive of stroke outcomes post reperfusion therapy.

Recognizing and Minimizing Artifacts at Dual-Energy CT.

Dual-energy CT (DECT) is an exciting innovation in CT technology with profound capabilities to improve diagnosis and add value to patient care. Significant advances in this technology over the past decade have improved our ability to successfully adopt DECT into the clinical routine. To enable effective use of DECT, one must be aware of the pitfalls and artifacts related to this technology. Understanding the underlying technical basis of artifacts and the strategies to mitigate them requires optimization of scan protocols and parameters. The ability of radiologists and technologists to anticipate their occurrence and provide recommendations for proper selection of patients, intravenous and oral contrast media, and scan acquisition parameters is key to obtaining good-quality DECT images. In addition, choosing appropriate reconstruction algorithms such as image kernel, postprocessing parameters, and appropriate display settings is critical for preventing quantitative and qualitative interpretive errors. Therefore, knowledge of the appearances of these artifacts is essential to prevent errors and allows maximization of the potential of DECT. In this review article, the authors aim to provide a comprehensive and practical overview of possible artifacts that may be encountered at DECT across all currently available commercial clinical platforms. They also provide a pictorial overview of the diagnostic pitfalls and outline strategies for mitigating or preventing the occurrence of artifacts, when possible. The broadening scope of DECT applications necessitates up-to-date familiarity with these technologies to realize their full diagnostic potential.

Estimating dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network.

Dual-energy computed tomography (DECT) is of great significance for clinical practice due to its huge potential to provide material-specific information. However, DECT scanners are usually more expensive than standard single-energy CT (SECT) scanners and thus are less accessible to undeveloped regions. In this paper, we show that the energy-domain correlation and anatomical consistency between standard DECT images can be harnessed by a deep learning model to provide high-performance DECT imaging from fully-sampled low-energy data together with single-view high-energy data. We demonstrate the feasibility of the approach with two independent cohorts (the first cohort including contrast-enhanced DECT scans of 5753 image slices from 22 patients and the second cohort including spectral CT scans without contrast injection of 2463 image slices from other 22 patients) and show its superior performance on DECT applications. The deep-learning-based approach could be useful to further significantly reduce the radiation dose of current premium DECT scanners and has the potential to simplify the hardware of DECT imaging systems and to enable DECT imaging using standard SECT scanners.

Neural MLAA for PET-enabled Dual-Energy CT Imaging.

The PET-enabled dual-energy CT method allows dual-energy CT imaging on PET/CT scanners without the need for a second x-ray CT scan. A 511 keV γ-ray attenuation image can be reconstructed from time-of-flight PET emission data using the maximum-likelihood attenuation and activity (MLAA) algorithm. However, the attenuation image reconstructed by standard MLAA is commonly noisy. To suppress noise, we propose a neural-network approach for MLAA reconstruction. The PET attenuation image is described as a function of kernelized neural networks with the flexibility of incorporating the available x-ray CT image as anatomical prior. By applying optimization transfer, the complex optimization problem of the proposed neural MLAA reconstruction is solved by a modularized iterative algorithm with each iteration decomposed into three steps: PET activity image update, attenuation image update, and neural-network learning using a weighed mean squared-error loss. The optimization algorithm is guaranteed to monotonically increase the data likelihood. The results from computer simulations demonstrated the neural MLAA algorithm can achieve a significant improvement on the γ-ray CT image quality as compared to other algorithms.

Comparison of different CT metal artifact reduction strategies for standard titanium and carbon\u2010fiber reinforced polymer implants in sheep cadavers

BackgroundCT artifacts induced by orthopedic implants can limit image quality and diagnostic yield. As a number of different strategies to reduce artifact extent exist, the aim of this study was to systematically compare ex vivo the impact of different CT metal artifact reduction (MAR) strategies on spine implants made of either standard titanium or carbon-fiber-reinforced-polyetheretherketone (CFR-PEEK).MethodsSpine surgeons fluoroscopically-guided prepared six sheep spine cadavers with pedicle screws and rods of either titanium or CFR-PEEK. Samples were subjected to single- and dual-energy (DE) CT-imaging. Different tube voltages (80, DE mixed, 120 and tin-filtered 150 kVp) at comparable radiation dose and iterative reconstruction versus monoenergetic extrapolation (ME) techniques were compared. Also, the influence of image reconstruction kernels (soft vs. bone tissue) was investigated. Qualitative (Likert scores) and quantitative parameters (attenuation changes induced by implant artifact, implant diameter and image noise) were evaluated by two independent radiologists. Artifact degree of different MAR-strategies and implant materials were compared by multiple ANOVA analysis.ResultsCFR-PEEK implants induced markedly less artifacts than standard titanium implants (p < .001). This effect was substantially larger than any other tested MAR technique. Reconstruction algorithms had small impact in CFR-PEEK implants and differed significantly in MAR efficiency (p < .001) with best MAR performance for DECT ME 130 keV (bone kernel). Significant differences in image noise between reconstruction kernels were seen (p < .001) with minor impact on artifact degree.ConclusionsCFR-PEEK spine implants induce significantly less artifacts than standard titanium compositions with higher MAR efficiency than any alternate scanning or image reconstruction strategy. DECT ME 130 keV image reconstructions showed least metal artifacts. Reconstruction kernels primarily modulate image noise with minor impact on artifact degree.

The Calcium Versus Hemorrhage Trial: Developing Diagnostic Criteria for Chronic Intracranial Susceptibility Lesions Using Single-Energy Computed Tomography, Dual-Energy Computed Tomography, and Quantitative Susceptibility Mapping.

Chronic susceptibility lesions in the brain can be either hemorrhagic (potentially dangerous) or calcific (usually not dangerous) but are difficult to discriminate on routine imaging. We proposed to develop quantitative diagnostic criteria for single-energy computed tomography (SECT), dual-energy computed tomography (DECT), and quantitative susceptibility mapping (QSM) to distinguish hemorrhage from calcium. Patients with positive susceptibility lesions on routine T2*-weighted magnetic resonance of the brain were recruited into this prospective imaging clinical trial, under institutional review board approval and with informed consent. The SECT, DECT, and QSM images were obtained, the lesions were identified, and the regions of interest were defined, with the mean values recorded. Criteria for quantitative interpretation were developed on the first 50 patients, and then applied to the next 45 patients. Contingency tables, scatter plots, and McNemar test were applied to compare classifiers. There were 95 evaluable patients, divided into a training set of 50 patients (328 lesions) and a validation set of 45 patients (281 lesions). We found the following classifiers to best differentiate hemorrhagic from calcific lesions: less than 68 Hounsfield units for SECT, calcium level of less than 15 mg/mL (material decomposition value) for DECT, and greater than 38 ppb for QSM. There was general mutual agreement among the proposed criteria. The proposed criteria outperformed the current published criteria. We provide the updated criteria for the classification of chronic positive susceptibility brain lesions as hemorrhagic versus calcific for each major clinically available imaging modality. These proposed criteria have greater internal consistency than the current criteria and should likely replace it as gold standard.

Metal artefact reduction of different alloys with dual energy computed tomography (DECT)

To evaluate the influence of dual-energy CT (DECT) and Virtual monochromatic spectral (VMS) imaging on: (1) the artefact size of geometrically identical orthopaedic implants consisting of three different compositions and (2) the image quality of the surrounding bone, three similar phantoms—each featuring one femoral stem composed of either titanium, chrome-cobalt or stainless steel surrounded by five calcium pellets (200 mg hydroxyapatite/calcium carbonate) to simulate bony tissue and one reference pellet located away from the femoral stem—were built. DECT with two sequential scans (80 kVp and 140 kVp; scan-to-scan technique) was performed, and VMS images were calculated between 40 and 190 keV. The artefact sizes were measured volumetrically by semiautomatic selection of regions of interest (ROIs), considering the VMS energies and the polychromatic spectres. Moreover, density and image noise within the pellets were measured. All three phantoms exhibit artefact size reduction as energy increases from 40 to 190 keV. Titanium exhibited a stronger reduction than chrome-cobalt and stainless steel. The artefacts were dependent on the diameter of the stem. Image quality increases with higher energies on VMS with a better depiction of surrounding structures. Monoenergetic energies 70 keV and 140 keV demonstrate superior image quality to those produced by spectral energies 80 kVp and 140 kVp.

Hemorrhagic cholecystitis: ultrasound and CT imaging findings—a retrospective case review series

Gallbladder pathology is diverse, and imaging tests are essential tools for its diagnosis. Acute cholecystitis has multiple manifestations or complications, one of which is hemorrhagic cholecystitis (HC). In the current literature, this pathology has been described only in the spectrum of acute cholecystitis complications, case reports, or series with a maximum of 2 to 3 cases. After a retrospective review, we present 11 cases of hemorrhagic cholecystitis and discuss its various causes, clinical presentations, and findings on ultrasound (US) and computed tomography (CT), considering dual-energy CT and magnetic resonance imaging (MRI). A retrospective review of 6 years (2012-2018) of hemorrhagic cholecystitis cases diagnosed at our hospital was performed. A search engine of medical terms was used and the database of radiological cases in the emergency department of the hospital. After a careful review by two emergency and one abdominal radiologists, 11 patients were identified as hemorrhagic cholecystitis cases according to their clinical, radiological, and surgical records and confirmed with pathology reports. Both lithiasis and anticoagulation/antiplatelet therapy were the most common etiologies found (9 patients, 82%). The clinical presentation may be misleading, simulating a usual cholecystitis episode with abdominal pain, nausea, and vomiting, or manifesting with signs of bile duct obstruction, hematemesis, or anemia that may compromise the patient hemodynamically and become fatal. US is useful, but CT is the most complete test for evaluating hemorrhagic cholecystitis and was performed in all the patients. The common findings were inflammatory changes in all patients (100%), hemobilia in 10 patients (91%), hemoperitoneum in 6 patients (55%), intestinal bleeding in 3 patients (27%), and occasionally perihepatic hematomas or signs of active bleeding. Although a rare entity, hemorrhagic cholecystitis may be present, and management can be delayed if the appropriate imaging modality is not used for diagnosis.

Virtual Unenhanced Dual-Energy CT Images Obtained with a Multimaterial Decomposition Algorithm: Diagnostic Value for Renal Mass and Urinary Stone Evaluation.

Background Virtual unenhanced (VUE) images obtained by using a dual-energy CT (DECT) multimaterial decomposition algorithm hold promise for diagnostic use in the abdomen in lieu of true unenhanced (TUE) images. Purpose To assess VUE images obtained from a DECT multimaterial decomposition algorithm in patients undergoing renal mass and urinary stone evaluation. Materials and Methods In this retrospective Health Insurance Portability and Accountability Act-compliant study, DECT was performed in patients undergoing evaluation for renal mass or urinary stone. VUE images were compared quantitatively to TUE images and qualitatively assessed by four independent radiologists. Differences in attenuation between VUE and TUE images were summarized by using 95% limits of agreement. Diagnostic performance in urinary stone detection was summarized by using area under the receiver operating characteristic curve, sensitivity, and specificity. Results A total of 221 patients (mean age ± standard deviation, 61 years ± 14; 129 men) with 273 renal masses were evaluated. Differences in renal mass attenuation between VUE and TUE images were within 3 HU for both enhancing masses (95% limits of agreement, -3.1 HU to 2.7 HU) and nonenhancing cysts (95% limits of agreement, -2.9 HU to 2.5 HU). Renal mass classification as enhancing mass versus nonenhancing cyst did not change (reclassification rate of enhancing masses, 0% [0 of 78]; 95% CI: 0, 5; reclassification rate of nonenhancing cysts, 0% [0 of 193]; 95% CI: 0, 2) with use of VUE in lieu of TUE images. Among 166 urinary stones evaluated, diagnostic performance of VUE images for stone detection was lower compared with that of TUE images (area under the receiver operating characteristic curve, 0.79 [95% CI: 0.73, 0.84] vs 0.93 [95% CI: 0.91, 0.95]; P < .001) due to reduced sensitivity of VUE for detection of stones 3 mm in diameter or less compared with those greater than 3 mm (sensitivity, 23% [25 of 108; 95% CI: 12, 40] vs 88% [126 of 144; 95% CI: 77, 94]; P < .001). Conclusion Compared with true unenhanced images, virtual unenhanced (VUE) images were unlikely to change renal mass classification as enhancing mass versus nonenhancing cyst. Diagnostic performance of VUE images remained suboptimal for urinary stone detection due to subtraction of stones 3 mm or less in diameter. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Sosna in this issue.

Reducing motion artifact in sequential-scan dual-energy CT imaging by incorporating deformable registration within joint statistical image reconstruction

Dual-energy computed tomography (DECT) has been widely used to reconstruct basis components. In previous studies, ou DECT algorithm has shown high accuracy in stopping power ratio (SPR) estimation of fixed objects for proton radiotherapy planning. However, patient movement between sequential data acquisitions may lead to severe motion artifacts in the component images. In order to reduce or eliminate the motion artifacts in clinical applications, we combine a deformable registration method with an accurate joint statistical iterative reconstruction algorithm, dual-energy alternating minimization (DEAM). Image registration is a process of geometrically aligning two or more images. We implement a multi-modality symmetric deformable registration method based on Advanced Normalization Tools (ANTs) to automatically align the scans we acquire for the same patient. The precalculated registration mapping and its inverse are then embedded into each iteration of the DEAM algorithm. The performance of warped DEAM is quantitatively assessed. Theoretically, the performance of warped DEAM on moved patients should be comparable to the performance of the original DEAM algorithm on fixed objects. The warped DEAM algorithm reduces motion artifacts while preserving the accuracy of the iterative joint statistical CT reconstruction algorithm, which enables us to reconstruct accurate results from sequentially scanned dual-energy patient data.

Generation of Brain Dual-Energy CT from Single-Energy CT Using Deep Learning.

Deep learning (DL) has shown great potential in conversions between various imaging modalities. Similarly, DL can be applied to synthesize a high-kV computed tomography (CT) image from its corresponding low-kV CT image. This indicates the feasibility of obtaining dual-energy CT (DECT) images without purchasing a DECT scanner. In this study, we investigated whether a low-to-high kV mapping was better than a high-to-low kV mapping. We used a U-Net model to perform conversions between different kV CT images. Moreover, we proposed a double U-Net model to improve the quality of original single-energy CT images. Ninety-eight patients who underwent brain DECT scans were used to train, validate, and test the proposed DL-based model. The results showed that the low-to-high kV conversion was better than the high-to-low kV conversion. In addition, the DL-based DECT images had better signal-to-noise ratios (SNRs) than the true (original) DECT images, but at the expense of a slight loss in spatial resolution. The mean CT number differences between the true and DL-based DECT images were within [Formula: see text]1 HU. No statistically significant difference in CT number measurements was found between the true and DL-based DECT images (p>0.05). The DL-based DECT images with improved SNR could produce low-noise virtual monoenergetic images. Our preliminary results indicate that DL has the potential to generate brain DECT images using single-energy brain CT images.

Dual-energy computed tomography for the detection of sacroiliac joints bone marrow oedema in patients with axial spondyloarthritis.

To investigate the diagnostic performance of dual-energy computed tomography (DECT) in detection bone marrow oedema (BME) in patients with sacroiliitis associated with axial spondyloarthritis (axial SpA). Patients with axial SpA according to the ASAS criteria underwent DECT and 1.5-T magnetic resonance imaging (MRI). DECT was post-processed for generating virtual non-calcium (VNCa) images. The presence of abnormal bone marrow attenuation was scored on DECT VNCa images and MRI using a four-point classification system: 0-1 = absent or non-significant oedema, 2 = oedema present in a third of the articular surface, 3 = oedema present in 2/3 of the articular surface, 4 = diffuse oedema throughout the articular surface. Diagnostic accuracy values for BME were calculated for DECT images (quantitative assessment) by using receiver operating characteristic (ROC) curves analysis, applying MRI as gold standard. Eighty sacroiliac joints from 40 axial SpA patients were included for study analysis, and 36 sacroiliac joints (45%) were classified as having BME at MRI and compared to DECT. Sensitivity, specificity, and positive likelihood ratio (LR+) in the identification of BME at DECT were 90.0%, 92.8%, and 12.6 respectively. Negative LR was 0.11, positive predictive value 93.1%, and negative predictive value 89.7%. The area under the curve (AUC) was 0.953 in the differentiation of the presence of BME. A cut-off value of -1.6 HU (Youden's index = 0.828) yielded a sensitivity of 90.0% and specificity of 92.8%, with an LR+ of 12.6, in the detection of BME in the sacroiliac joints. DECT VNCa images had good diagnostic performance in the evaluation of the extent of BME in patients with sacroiliitis associated with axial SpA.