Dual-energy CT Research Articles

The diagnostic performance of dual-energy CT imaging in cervical lymph node metastasis of papillary thyroid cancer: a meta-analysis

PurposeThis meta-analysis aimed to evaluate the diagnostic efficacy of dual-energy computed tomography (DECT) in detecting cervical lymph node metastasis among papillary thyroid cancer (PTC) patients.MethodsA comprehensive search across PubMed, Embase, and Web of Science databases was conducted to identify pertinent publications up to May 2024. This search focused on studies examining the diagnostic accuracy of DECT in detecting cervical lymph node metastases in PTC patients. We employed a bivariate random-effects model to calculate pooled sensitivity and specificity of DECT. The degree of heterogeneity in the studies was quantified using the I2 statistic. Furthermore, the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was utilized to evaluate the methodological quality of the included studies.ResultsThis meta-analysis encompassed 14 articles, collectively involving 1,615 patients. The pooled sensitivity, specificity, and AUC for DECT in detecting cervical lymph node metastases in PTC patients were 0.81 (95% CI: 0.76–0.85), 0.86 (95% CI: 0.80–0.91), and 0.89 (95% CI: 0.86–0.92), respectively. According to Fagan’s nomogram, for DECT, with a pre-test probability of 50%, the post-test probability was calculated as 85% for a positive result and 18% for a negative result. Deeks’ funnel plot asymmetry test showed no significant publication bias was observed for DECT (p = 0.28).ConclusionOur meta-analysis indicates that DECT demonstrates superior sensitivity and specificity in cervical lymph node metastasis among PTC patients. To corroborate these findings and evaluate their clinical applicability, further prospective studies are necessary.

Assessing Changes in Vascular Inflammation and Urate Deposition in the Vasculature of Gout Patients After Administration of Pegloticase Using Positron Emission Tomography and Dual-Energy Computed Tomography—A Pilot Study

We assessed changes in vascular inflammation and monosodium urate (MSU)-coded deposits after administration of Pegloticase in the vasculature of tophaceous gout patients using 18F-fluorodeoxyglucose (18F-FDG) Positron emission tomography/computed tomography (PET/CT) and dual-energy CT (DECT). Ten patients with tophaceous gout, intolerant or refractory to urate-lowering therapy (ULT), were treated with Pegloticase every two weeks for six months. 18F-FDG PET/CT and DECT were performed at baseline and after Pegloticase therapy to detect vessel wall inflammation (Standard uptake value, SUVmean, and SUVmax) and vascular MSU-coded deposition (MSU volume). Data were summarized using means and standard deviations. Baseline and follow-up values were compared for each variable using mixed-effect models. Significant decreases in SUVmean (p = 0.0003) and SUVmax (p = 0.009) were found with a trend towards a decrease in vessel wall MSU volume after treatment. There was a significant decrease in serum urate, correlating with reduction in SUVmean (R2 = 0.65), with a trend towards a decrease in CRP and blood pressure in all patients. Despite the small sample size, we were able to demonstrate a decrease in vessel wall inflammation and a trend towards a decrease in MSU volume by intensively lowering serum urate. These findings suggest that MSU-coded deposits and hyperuricemia may play a role in vascular wall inflammation. It remains to be seen whether this correlates with a decrease in adverse cardiovascular outcomes.

In situ isotropic 3D imaging of vasculature perfusion specimens using x-ray microscopic dual-energy CT.

Ex vivo x-ray angiography provides high-resolution, three-dimensional information on vascular phenotypes down to the level of capillaries. Sample preparation for ex vivo angiography starts with the removal of blood from the vascular system, followed by perfusion with an x-ray dense contrast agent mixed with a carrier such as gelatine or a polymer. Subsequently, the vascular micro-architecture of harvested organs is imaged in the intact fixed organ. In the present study, we present novel microscopic dual-energy CT (microDECT) imaging protocols that allow to visualise and analyse microvasculature in situ with reference to the morphology of hard and soft tissue. We show that the spectral contrast of µAngiofil and Micropaque barium sulphate in perfused specimens allows for the effective separation of vasculature from mineralised skeletal tissues. Furthermore, we demonstrate the counterstaining of perfused specimens using established x-ray dense contrast agents to depict blood vessels together with the morphology of soft tissue. Phosphotungstic acid (PTA) is used as a counterstain that shows excellent spectral contrast in both µAngiofil and Micropaque barium sulphate-perfused specimens. A novel Sorensen-buffered PTA protocol is introduced as a counterstain for µAngiofil specimens, as the polyurethane polymer is susceptible to artefacts when using conventional staining solutions. Finally, we demonstrate that counterstained samples can be automatically processed into three separate image channels (skeletal tissue, vasculature and stained soft tissue), which offers multiple new options for data analysis. The presented microDECT workflows are suited as tools to screen and quantify microvasculature and can be implemented in various correlative imaging pipelines to target regions of interest for downstream light microscopic investigation.

Spondylodiscitis of the thoraco-lumbar spine: diagnostic performance of dual-energy CT vs MRI.

Dual-energy computed tomography (DECT) could combine the high-resolution bone window images made available by multi-detector CT technology with its capability to identify bone marrow edema (BME) in the spine, for diagnosing spondylodiscitis. Our objective was to compare the diagnostic performance of contrast-enhanced MRI and non-contrast DECT to identify spondylodiscitis of the thoraco-lumbar spine. This prospective study included 77 consecutive participants (39 males; mean age of 61) who underwent DECT and MRI (within 7 days) between January 2020 and October 2023. DECT data were post-processed on a dedicated offline workstation (SyngoVia® VB20) by using a three-material decomposition algorithm. Four radiologists, blinded to clinical data, evaluated non-contrast DECT and contrast-enhanced MRI images. The diagnosis of spondylodiscitis was based on vertebral edema, disc edema, endplate erosions, and paraspinal involvement. Diagnostic accuracy values were calculated by using biopsy as a standard of reference. A multi-reader multi-case analysis was performed. Biopsy revealed a diagnosis of spondylodiscitis in 46 patients (60%). Thoracic and lumbar spondylodiscitis were diagnosed in 37/46 (80%) and 9/46 (20%) patients, respectively. DECT and MRI overall sensitivity, specificity, and AUC were 0.91, 0.89, and 0.90, and 0.94, 0.93, and 0.93, respectively. At lumbar and thoracic levels, the difference between AUC values between DECT and MRI was not significant (p = 0.15). For DECT and MRI, a very good inter-reader agreement was achieved (k = 0.90 and k = 0.97, respectively). Contrast-enhanced MRI represents the most accurate imaging tool for the diagnosis of spondylodiscitis. However, only a non-significant drop in diagnostic performance was achieved by evaluating non-contrast DECT images. Question To compare the diagnostic performance of contrast-enhanced MRI and non-contrast DECT for identifying spondylodiscitis of the thoraco-lumbar spine. Findings MRI was not significantly superior compared to DECT in diagnosing spondylodiscitis, whereas the inter-reader agreement was near perfect for both MRI and DECT. Clinical relevance DECT represents a fast and accurate imaging tool for the demonstration of BME, erosions, and peri-vertebral inflammation in thoraco-lumbar spondylodiscitis.

A simulation framework for preclinical proton irradiation workflow

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

Dual Energy Metal Artifact Reduction for Iodine-125 Seed Identification in Postimplant CT after Prostate Brachytherapy.

To assess the metal artifact reductions of dual-energy computed tomography (DECT) high-energy virtual monochromatic images (VMI) combined with the single energy metal artifact reduction (SEMER) (CANON MEDICAL SYSTEMS, Otawara, Japan) processing techniques for iodine (I)-125 seed identification in postimplant computed tomography (CT) after prostate brachytherapy. Dual-energy acquisition with fast tube voltage switching was performed on a prostate phantom with simulated seeds and six clinical cases treated with I-125 prostate brachytherapy. The images were retrospectively reconstructed at VMI energy levels of 65-200 keV and with and without SEMAR (SEMAR and non-SEMAR images). To estimate seed swelling, the caliber of iodine-125 seed was calculated as the full width at half maximum. The metal artifacts were evaluated using the artifact index (AI). The dose distributions were calculated and were compared among the high-energy VMI (SEMAR and non-SEMAR images) and low-energy VMI (SEMAR images). The blooming artifacts decreased at higher energy levels. In addition, the SEMAR process markedly reduced AI, which helped reduce overestimation of high dose ranges in the treatment planning dose map. The locations and number of iodine-125 seed were clearly identified in the dose distribution map of the treatment planning using 200keV VMI with SEMAR. The high-energy VMI of the dual energy CT in combination with SEMAR is appropriate for the postimplant planning process of I-125 prostate brachytherapy.

Associations of pulmonary microvascular blood volume with per cent emphysema and CT emphysema subtypes in the community: the MESA Lung study

BackgroundPulmonary microvasculature alterations are implicated in emphysema pathogenesis, but the association between pulmonary microvascular blood volume (PMBV) and emphysema has not been directly assessed at scale, and prior studies have...

Diagnostic Accuracy of CT for the Detection of Hepatic Steatosis: A Systematic Review and Meta-Analysis.

Background CT plays an important role in the opportunistic identification of hepatic steatosis. CT performance for steatosis detection has been inconsistent across various studies, and no clear guidelines on optimum thresholds have been established. Purpose To conduct a systematic review and meta-analysis to assess CT diagnostic accuracy in hepatic steatosis detection and to determine reliable cutoffs for the commonly mentioned measures in the literature. Materials and Methods A systematic search of the PubMed, Embase, and Scopus databases (English-language studies published from September 1977 to January 2024) was performed. Studies evaluating the diagnostic accuracy of noncontrast CT (NCCT), contrast-enhanced (CECT), and dual-energy CT (DECT) for hepatic steatosis detection were included. Reference standards included biopsy, MRI proton density fat fraction (PDFF), or NCCT. In several CECT and DECT studies, NCCT was used as the reference standard, necessitating subgroup analysis. Statistical analysis included a random-effects meta-analysis, assessment of heterogeneity with use of the I2 statistic, and meta-regression to explore potential sources of heterogeneity. When available, mean liver attenuation, liver-spleen attenuation difference, liver to spleen attenuation ratio, and the DECT-derived fat fraction for hepatic steatosis diagnosis were assessed. Results Forty-two studies (14 186 participants) were included. NCCT had a sensitivity and specificity of 72% and 88%, respectively, for steatosis (>5% fat at biopsy) detection and 82% and 94% for at least moderate steatosis (over 20%-33% fat at biopsy) detection. CECT had a sensitivity and specificity of 66% and 90% for steatosis detection and 68% and 93% for at least moderate steatosis detection. DECT had a sensitivity and specificity of 85% and 88% for steatosis detection. In the subgroup analysis, the sensitivity and specificity for detecting steatosis were 80% and 99% for CECT and 84% and 93% for DECT. There was heterogeneity among studies focusing on CECT and DECT. Liver attenuation less than 40-45 HU, liver-spleen attenuation difference less than -5 to 0 HU, and liver to spleen attenuation ratio less than 0.9-1 achieved high specificity for detection of at least moderate steatosis. Conclusion NCCT showed high performance for detection of at least moderate steatosis. © RSNA, 2024 Supplemental material is available for this article.

Impact of virtual monochromatic images of different low-energy levels in dual-energy CT on radiomics models for predicting muscle invasion in bladder cancer.

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

A quantitative model using multi-parameters in dual-energy CT to preoperatively predict serosal invasion in locally advanced gastric cancer

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

The diagnosis value of dual-energy computed tomography (DECT) multi-parameter imaging in lung adenocarcinoma and squamous cell carcinoma.

Lung cancer continues to pose a serious risk to human health. With a high mortality rate, non-small cell lung cancer (NSCLC) is the major type of lung cancer, making up to 85% of all cases of lung cancer. Lung adenocarcinoma (AC), and lung squamous cell carcinoma (SC) are the two primary types of NSCLC. Determining the pathological type of NSCLC is important in establishing the most effective treatment method. Dual-energy computed tomography (DECT) multi-parameter imaging is an imaging technology that provides accurate and reliable disease diagnosis, and its uses are utilized for the combined diagnostic efficacy of AC and SC. The purpose of this study was to investigate the diagnostic value of spectral parameters of DECT in efficacy to AC and SC, and their combined diagnostic efficacy was also analyzed. We conducted a retrospective analysis of clinical and imaging data for 36 patients diagnosed with SC and 35 patients with AC. These patients underwent preoperative DECT chest scans, encompassing both arterial and venous phases, at our hospital from December 2020 to April 2022. The tumor diameter, water concentration (WC), iodine concentration (IC), normalized iodine concentration (NIC), Z effective (Zeff), and slope of the curve (K) in lesions were evaluated during two scanning phases in the two separate pathological types of lung cancers. The differences in parameters between these two types of lung cancers were statistically analyzed. In addition, receiver operating characteristic (ROC) curves were performed for these parameters to distinguish between SC and AC. In a univariate analysis involving 71 lung cancer patients, the results from Zeff, IC, NIC, and K from the AC's arterial and venous phase images were more elevated than those from the SC (P < 0.05). In contrast, the WC results were lower than those from SC (P < 0.05). The area under the ROC curve (AUC) for multi-parameter joint prediction typing was 0.831, with a corresponding sensitivity of 63.9% and specificity of 94.3%. It is possible to distinguish between central SC and AC using the spectrum characteristics of DECT-enhanced scanning (Zeff, IC, NIC, K, WC, and tumor diameter). Diagnostic effectiveness can be greatly improved when multiple variables are included.

Dual-energy computed tomography: pediatric considerations.

Multidetector computed tomography (CT) has revolutionized medicine and is now a fundamental aspect of modern radiology. Hardware and software advancements have significantly improved CT accessibility, image quality, and acquisition times. While considerable attention has been directed towards the potential risks of ionizing radiation from CT scans in children, recent concerns regarding the possible short- and long-term risks related to magnetic resonance imaging (MRI) conducted under general anesthesia have generated fresh interest in novel pediatric CT applications and techniques that allow imaging of awake patients at low radiation doses. Among these novel techniques, dual-energy CT (DECT) stands out for its ability to provide enhanced diagnostic information, reduce radiation doses further, and facilitate faster scans, making it a highly promising tool in pediatric radiology. This manuscript explores the current role of DECT in pediatric imaging, emphasizing its technical foundations, hardware configurations, and various reconstruction techniques. We discuss advanced post-processing techniques, such as material decomposition algorithms and virtual monoenergetic imaging, highlighting their clinical advantages in improving diagnostic accuracy and patient outcomes. Furthermore, the paper reviews the clinical applications of DECT in evaluating pulmonary perfusion, cardiovascular assessments, and oncologic imaging in pediatric patients.

Differentiation of pathological subtypes and Ki-67 and TTF-1 expression by dual-energy CT (DECT) volumetric quantitative analysis in non-small cell lung cancer

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

Dual-energy CT angiography in detecting underlying causes of intracerebral hemorrhage: an observational cohort study.

CT angiography (CTA) is often used to detect underlying causes of acute intracerebral hemorrhage (ICH). Dual-energy CT (DECT) is able to distinguish materials with similar attenuation but different compositions, such as hemorrhage and contrast. We aimed to evaluate the diagnostic yield of DECT angiography (DECTA), compared to conventional CTA in detecting underlying ICH causes. All non-traumatic ICH patients who underwent DECTA (both arterial as well as delayed venous phase) at our center between January 2014 and February 2020 were analyzed. Conventional CTA acquisitions were reconstructed ('merged') from DECTA data. Structural ICH causes were assessed on both reconstructed conventional CTA and DECTA. The final diagnosis was based on all available diagnostic and clinical findings during one-year follow up. Of 206 included ICH patients, 30 (14.6%) had an underlying cause as final diagnosis. Conventional CTA showed a cause in 24 patients (11.7%), DECTA in 32 (15.5%). Both false positive and false negative findings occurred more frequently on conventional CTA. DECTA detected neoplastic ICH in all seven patients with a definite neoplastic ICH diagnosis, whereas conventional CTA only detected four of these cases. Both developmental venous anomalies (DVA) and cerebral venous sinus thrombosis (CVST) were more frequently seen on DECTA. Arteriovenous malformations and aneurysms were detected equally on both imaging modalities. Performing DECTA at clinical presentation of ICH may be of additional diagnostic value in the early detection of underlying causes, especially neoplasms, CVST and DVAs.

Computed Tomography and Magnetic Resonance Imaging in Liver Iron Overload: From Precise Quantification to Prognosis Assessment

Liver iron overload is associated with conditions such as hereditary hemochromatosis, thalassemia major, and chronic liver diseases. The liver-related outcomes, patient outcomes, and treatment recommendations of these patients differ depending on the cause and extent of iron overload. Accurate quantification of the liver iron concentration (LIC) is critical for effective patient management. This review focuses on the application of computed tomography (CT) and magnetic resonance imaging (MRI) for the precise quantification and prognostic assessment of liver iron overload. In recent years, the use of dual-energy CT and the emergence of MRI-based sequences (such as UTE, QSM, Dixon, and CSE technologies) have significantly increased the potential for noninvasive liver iron quantification. However, the establishment of internationally standardized imaging parameters, postprocessing procedures, and reporting protocols is urgently needed for better management of patients with liver iron overload.

Iodine-Based Dual-Energy Computed Tomography After Mechanical Thrombectomy Predicts Secondary Neurologic Decline from Cerebral Edema After Severe Stroke.

Patients with severe stroke are at high risk of secondary neurologic decline (ND) from the development of malignant cerebral edema (MCE). However, early infarcts are hard to diagnose on conventional head computed tomography (CT). We hypothesize that high-energy (190keV) virtual monochromatic imaging (VMI) from dual-energy CT (DECT) imaging enables earlier detection of ND from MCE. Consecutive patients with severe stroke with National Institute of Health Stroke Scale (NIHSS) scores > 15 and DECT within 10h of mechanical thrombectomy from May 2020 to March 2022 were included. We excluded patients with parenchymal hematoma type 2 transformation. Retrospective analysis of clinical and novel variables included the VMI Alberta Stroke Program Early CT Score (ASPECTS), total iodine content, and VMI infarct volume. The primary outcome was secondary ND, defined using a composite outcome variable of clinical worsening (increase in NIHSS score ≥ 4 or decrease in Glasgow Coma Scale score > 2) or malignant radiographical edema (midline shift ≥ 5mm at the level of the septum pellucidum). Fisher's exact test and Wilcoxon's test were used for univariate analysis. Logistic regression was used to develop prediction models for categorical outcomes. Eighty-four patients with severe stroke with a median age of 67.5 (interquartile range [IQR] 57-78) years and an NIHSS score of 22 (IQR 18-25) were included. Twenty-nine patients had ND. The VMI ASPECTS, total iodine content, and VMI infarct volume were associated with ND. The VMI ASPECTS, VMI infarct volume, and total iodine content were predictors of ND after adjusting for age, sex, initial NIHSS score, and tissue plasminogen activator administration, with areas under the receiver operating characteristic curve (AUROC) of 0.691 (95% confidence interval [CI] 0.572-0.810), 0.877 (95% CI 0.800-0.954), and 0.845 (95% CI 0.750-0.940). By including all three predictors, the model achieved an AUROC of 0.903 (95% CI 0.84-0.97) and was cross-validated by the leave one out method, with an AUROC of 0.827. The VMI ASPECTS and VMI infarct volume from DECT are superior to the conventional CT ASPECTS and are novel predictors for secondary ND due to MCE after severe stroke. Clinical trial registration ClinicalTrials.gov identifier: NCT04189471.

Unmet Needs in Spondyloarthritis: Imaging in Axial Spondyloarthritis.

Imaging biomarkers in axial spondyloarthritis (axSpA) are currently the most specific biomarkers for the diagnosis of this condition. Despite advances in imaging, from plain radiographs-which detect only damage-to magnetic resonance imaging (MRI)-which identifies disease activity and structural change-there are still many challenges that remain. Imaging in sacroiliitis is characterized by active and structural changes. Current classification criteria stress the importance of bone marrow edema (BME); however, BME can occur in various diseases, mechanical conditions, and healthy individuals. Thus, the identification of structural lesions such as erosion, subchondral fat, backfill, and ankylosis is important to distinguish from mimics on differential diagnosis. Various imaging modalities are available to examine structural lesions, but computed tomography (CT) is considered the current reference standard. Nonetheless, recent advances in MRI allow for direct bone imaging and the reconstruction of CT-like images that can provide similar information. Therefore, the ability of MRI to detect and measure structural lesions is strengthened. Here, we present an overview of the spectrum of current and cutting-edge techniques for SpA imaging in clinical practice; namely, we discuss the advantages, disadvantages, and usefulness of imaging in SpA through radiography, low-dose and dual-energy CT, and MRI. Cutting-edge MRI sequences including volumetric interpolated breath-hold examination, ultrashort echo time, zero echo time, and deep learning-based synthetic CT that creates CT-like images without ionizing radiation, are discussed. Imaging techniques allow for quantification of inflammatory and structural lesions, which is important in the assessment of treatment response and disease progression. Radiographic damage is poorly sensitive to change. Artificial intelligence has already revolutionized radiology practice, including protocolization, image quality, and image interpretation.

Dual-Energy CT as a Well-Established CT Modality to Reduce Contrast Media Amount: A Systematic Review from the Computed Tomography Subspecialty Section of the Italian Society of Radiology

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

Toward the Application of Dual-Energy Computed Tomography with Virtual Non-Hydroxyapatite Color-Coded Maps to Identify Traumatic Fractures in Daily Emergency Settings

To evaluate the advantages of dual-energy computed tomography (DECT) virtual non-hydroxyapatite color mapping (VNHAP) in combination with standard bone CT (BCT) in the identification of subtle or occult traumatic fractures referred to emergency and acceptance departments (DEAs). Forty patients (22 men; mean age 83 ± 23.7 y) with suspected traumatic fractures referred to our emergency department and examined with a fast kilovoltage-switching single-source spectral CT scan between January and October 2023 were retrospectively reviewed. The BCT and VNHAP images were blindly evaluated by two radiologists with &gt;10 years and &lt;2 years of experience in musculoskeletal imaging. Both techniques were evaluated in terms of sensitivity (SE), specificity (SP), positive and negative predictive values (PPVs and NPVs) and accuracy for fracture detection, as confirmed at a 3-month clinical–instrumental follow-up. Inter-observer agreement and examination times were also analyzed. Fractures were confirmed in 18/40 cases. The highest values of diagnostic performance for VNHAP images were obtained in terms of SP (90.9% and 95%) and PPV (87.5% and 92.8%) and for the less experienced operator. No statistically significant differences were observed between the diagnostic accuracy of the two readers in the evaluation of VNHAP images. Inter-observer agreement was moderate (κ = 0.536) for BCT and substantial (κ = 0.680) for VNHAP. Comparing the two operators, a significantly longer examination time for BCT and no significant difference for VNHAP were registered. Our preliminary experience may encourage the employment of VNHAP maps in combination with BCT images in emergency settings. Their use could be time-saving and valuable in terms of diagnostic performance, especially for less experienced operators.

Deep-learning reconstruction enhances image quality of Adamkiewicz Artery in low-keV dual-energy CT.

Low-keV virtual monoenergetic images (VMIs) of dual-energy computed tomography (CT) enhances iodine contrast for detecting small arteries like the Adamkiewicz artery (AKA), but image noise can be problematic. Deep-learning image reconstruction (DLIR) effectively reduces noise without sacrificing image quality. To evaluate whether DLIR on low-keV VMIs of dual-energy CT scans improves the visualization of the AKA. We enrolled 29 patients who underwent CT angiography before aortic repair. VMIs obtained at 70 and 40 keV were reconstructed using hybrid iterative reconstruction (HIR), and 40 keV VMIs were reconstructed using DLIR. The image noise of the spinal cord, the maximum CT values of the anterior spinal artery (ASA), and the contrast-to-noise ratio (CNR) of the ASA were compared. The overall image quality and the delineation of the AKA were evaluated on a 4-point score (1 = poor, 4 = excellent). The mean image noise of the spinal cord was significantly lower on 40-keV DLIR than on 40-keV HIR scans; they were significantly higher than on 70-keV HIR images. The CNR of the ASA was highest on the 40-keV DLIR images among the three reconstruction images. The mean image quality scores for 40-keV DLIR and 70-keV HIR scans were comparable, and higher than of 40-keV HIR images. The mean delineation scores for 40-keV HIR and 40-keV DLIR scans were significantly higher than for 70-keV HIR images. Visualization of the AKA was significantly better on low-keV VMIs subjected to DLIR than conventional HIR images.