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

BACKGROUND: 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 (190 keV) virtual monochromatic imaging (VMI) from dual-energy CT (DECT) imaging enables earlier detection of ND from MCE. METHODS: Consecutive patients with severe stroke with National Institute of Health Stroke Scale (NIHSS) scores > 15 and DECT within 10 h 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 ≥ 5 mm 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. RESULTS: 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. CONCLUSIONS: 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.

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

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Dual-Energy Computed Tomography-Guided Assessment of Visceral Adiposity and Its Correlation With Lipid Function Test: A Retrospective Study.

Introduction Obesity, a prevalent global health concern, is associated with various chronic conditions, including cardiovascular diseases and metabolic syndrome. Visceral adiposity, the accumulation of fat around internal organs, has a more significant impact on metabolic health compared to subcutaneous fat. Accurate assessment of visceral fat is critical for predicting metabolic risks. Dual-Energy Computed Tomography (DECT) is emerging as an effective tool for quantifying visceral adiposity, allowing for enhanced tissue differentiation. This study aims to assess visceral adiposity using DECT and explore its correlation with lipid function tests, including cholesterol and triglyceride levels, in a cohort of patients. Materials and methods This retrospective observational study was conducted in the Department of Radiology at Saveetha Medical College and Hospital, Chennai. Data from 100 patients aged 25 to 75 years with a BMI of 25 kg/m² or higher, were analyzed. DECT scans were performed using a Siemens SOMATOM go.Top 128-slice CT scanner (Siemens, Munich) to quantify visceral fat, particularly mesenteric fat. Lipid function tests were conducted to measure total cholesterol, LDL cholesterol, HDL cholesterol, and triglycerides. Pearson's correlation coefficient was used to analyze the relationship between visceral fat volume and lipid profile components. Results The study found significant correlations between visceral adiposity and lipid profile components. Total Visceral Fat Area (VFA) volume positively correlated with total cholesterol (r = 0.65, p < 0.01), LDL cholesterol (r = 0.58, p < 0.01), and triglycerides (r = 0.52, p < 0.05). An inverse relationship was observed between VFA volume and HDL cholesterol (r = -0.48, p < 0.05). Regression analysis confirmed that VFA volume is an independent predictor of these lipid levels after adjusting for age, gender, and BMI. The study also reported the prevalence of hepatomegaly in 11 (36.6%) cases and fatty liver in nine (30%) cases in the study population, underscoring the metabolic implications of visceral fat accumulation. Conclusion This study highlights the significant role of visceral adiposity in influencing lipid metabolism and associated cardiovascular risks. DECT proved to be a precise and reliable tool for assessing visceral fat and its metabolic implications. The findings suggest that increased visceral fat is associated with adverse lipid profiles, contributing to a higher risk of metabolic disorders. These results emphasize the need for incorporating advanced imaging techniques like DECT in clinical practice for better risk stratification and personalized treatment strategies in patients with obesity and related metabolic conditions.

Combination of single-source dual-energy computed tomography (CT) parameters and extracellular volume fraction for predicting lymphovascular and perineural invasion in colorectal cancer.

Background: Lymphovascular invasion (LVI) and perineural invasion (PNI) are important histopathological variables that are directly related to the survival and recurrence of patients with colorectal cancer (CRC). Preoperative prediction of LVI and PNI status in CRC is helpful in selecting patients requiring appropriate adjuvant therapy and evaluating prognosis. This study aimed to investigate the value of combining single-source dual-energy computed tomography (ssDECT)-derived parameters with extracellular volume (ECV) fraction for preoperative evaluation of LVI and PNI in CRC. Methods: This retrospective study included patients with CRC who underwent contrast-enhanced ssDECT. All diagnoses were confirmed through histopathology, and the patients were classified into positive and negative groups based on the presence of LVI/PNI. Clinical data were collected. In the arterial (AP), venous (VP) and delayed phases (DP), the ssDECT-derived parameters were measured by two radiologists. The measurement consistency was evaluated using intraclass correlation coefficients. Differences between the two groups were analyzed using the t-test, Mann-Whitney U test, or Chi-square test. Binary logistic regression was employed to construct models incorporating multiple parameters. The diagnostic performance of various parameters or models was assessed by analyzing receiver operating characteristic curves. Results: In total, 118 patients with CRC were included in the study. Serum carcinoembryonic antigen levels, T and N stages, and histological grades differed between the two groups (all P<0.05). The ssDECT-derived parameters in the VP and DP of LVI/PNI-positive group were higher than those of -negative group (all P<0.05). The ECV fraction in the DP of LVI/PNI-positive group was higher than that of -negative group (P=0.001). Discriminating capability analysis demonstrated that the diagnostic efficacies of the DP parameters were superior to those of the VP parameters, and the normalized iodine concentration in the DP exhibited the best performance [area under the curve (AUC): 0.750; 95% confidence interval (CI): 0.648-0.852]. The combination of ECV DP with clinical and ssDECT-derived parameters demonstrated the highest discriminative capability (AUC: 0.857; 95% CI: 0.786-0.928). Conclusions: ssDECT-derived parameters and ECV fraction may serve as non-invasive tools for predicting the LVI/PNI status in CRC.

Diagnostic Value of Contrast-Enhanced Dual-Energy Computed Tomography in the Pancreatic Parenchymal and Delayed Phases for Pancreatic Cancer.

Background/Objectives: The usefulness of dual-energy computed tomography (DECT) for low absorption in the parenchymal phase and contrast effects in the delayed phase for pancreatic cancer is not clear. Therefore, the diagnostic capability of low-KeV images obtained using DECT for pancreatic cancer in the pancreatic parenchymal and delayed phases was evaluated quantitatively and qualitatively. Methods: Twenty-five patients with pancreatic cancer who underwent contrast-enhanced DECT were included. A total of 50 and 70 KeV CT images, classified as low-keV and conventional CT-equivalent images, were produced, respectively. The tumor-to-pancreas contrast (Hounsfield units [HU]) in the pancreatic parenchymal and delayed phases was calculated by subtracting the CT value of the pancreatic tumor from that of normal parenchyma. Results: The median tumor-to-pancreas contrast on 50 KeV CT in the pancreatic parenchymal phase (133 HU) was higher than that on conventional CT (68 HU) (p < 0.001). The median tumor-to-pancreas contrast in the delayed phase was -28 HU for 50 KeV CT and -9 HU for conventional CT (p = 0.545). For tumors < 20 mm, the tumor-to-pancreas contrast of 50 KeV CT (-39 HU) had a significantly clearer contrast effect than that of conventional CT (-16.5 HU), even in the delayed phase (p = 0.034). Conclusions: These 50 KeV CT images may clarify the low-absorption areas of pancreatic cancer in the pancreatic parenchymal phase. A good contrast effect was observed in small pancreatic cancers on 50 KeV delayed-phase images, suggesting that DECT is useful for the visualization of early pancreatic cancer with a small tumor diameter.

Characteristics of the imaging diagnosis of alveolar echinococcosis.

Alveolar echinococcosis (AE) primarily manifests in the liver and exhibits characteristics resembling those of slow-growing malignant tumours. Untreated Echinococcus multilocularis infection can be lethal. By infiltrating the vascular systems, biliary tracts, and the hilum of the liver, it might lead to various problems. Due to its ability to infiltrate neighbouring tissues or metastasize to distant organs, AE can often be mistaken for malignancies. We present a concise overview of the epidemiological and pathophysiological characteristics of AE, as well as the clinical manifestations of the disease. This article primarily examines the imaging characteristics of AE using various imaging techniques such as ultrasonography, computed tomography (CT), magnetic resonance imaging, diffusion-weighted imaging, and virtual non-enhanced dual-energy CT. We additionally examined the contribution of radiography in the diagnosis, treatment, and monitoring of the condition.

Dual-energy CT late arterial phase iodine maps for the diagnosis of acute non-occlusive mesenteric ischemia.

PURPOSE: To evaluate the diagnostic accuracy of dual-energy CT (DECT) iodine maps in comparison to conventional CT series for the assessment of non-occlusive mesenteric ischemia (NOMI). MATERIAL AND METHODS: We evaluated data from 142 patients (72 men; 50.7%) who underwent DECT between 2018 and 2022, with surgically confirmed diagnosis of NOMI. One board-certified radiologist performed region of interest (ROI) measurements in bowel segments on late arterial (LA) and portal venous (PV) phase DECT iodine maps as well as LA conventional series, in both ischemic and non-ischemic bowel loops, using surgical reports as reference standard, and in a control group of 97 patients. Intra- and inter-reader agreement with a second board-certified radiologist was also evaluated. Receiver operating characteristic (ROC) curve analysis was performed to calculate the optimal threshold for discriminating ischemic from non-ischemic bowel segments. Subjective image rating of LA and PV iodine maps was performed. RESULTS: DECT-based iodine concentration (IC) measurements showed significant differences in LA phase iodine maps between ischemic (median:0.72; IQR 0.52-0.91 mg/mL) and non-ischemic bowel loops (5.16; IQR 3.45-6.31 mg/ml) (P <.0001). IC quantification on LA phase revealed an AUC of 0.966 for the assessment of acute bowel ischemia, significantly higher compared to both IC quantification based on PV phase (0.951) and attenuation values evaluated on LA conventional CT series (0.828). Excellent intra-observer and strong inter-observer agreements were observed for the quantification of iodine concentration. Conversely, weak inter-observer agreement was noted for conventional HU assessments. The optimal LA phase-based IC threshold for assessing bowel ischemia was 1.34 mg/mL, yielding a sensitivity of 100% and specificity of 96.48%. CONCLUSION: Iodine maps based on LA phase significantly improve the diagnostic accuracy for the assessment of NOMI compared to conventional CT series and PV phase iodine maps.

Dual-energy computed tomography-based radiomics for differentiating patients with and without gout flares.

BACKGROUND: There is a current lack of data pertaining to the potential link between gout flares and dual-energy computed tomography radiomic features. This study aimed to construct and validate a comprehensive dual-energy computed tomography-based radiomics model for differentiating patients with and without gout flares. METHODS: The analysis included 200 patients, of whom 150 were confirmed to have experienced at least one flare in the past 12 months; the remaining 50 patients did not experience flares. The radiomic features of the tophi at the bilateral first metatarsophalangeal joints were extracted and analyzed. Optimal radiomic features were selected using the least absolute shrinkage and selection operator method, and logistic regression analysis was used to screen clinical characteristics and establish a clinical model. The optimal radiomic features were then combined with the identified independent clinical variables to develop a comprehensive model. The performances of the radiomic, clinical, and comprehensive models were evaluated using receiver operating characteristic curve analysis, calibration curves, and decision curve analysis. RESULTS: Four radiomic features distinguished patients with at least one flare from those without flares and were used to establish the radiomic model. Disease duration and hypertension were independent factors that differentiated flare occurrences. The radiomic, clinical, and comprehensive models showed favorable discrimination, with areas under the receiver operating characteristic curves of 0.76 (95% CI, 0.69-0.83), 0.72(95% CI, 0.63-0.80), and 0.79(95% CI, 0.73-0.86), respectively. The calibration curves (P > 0.05) showed that the differentiated values of the comprehensive model agreed well with the actual values. Decision curve analysis demonstrated that the comprehensive model achieved higher net clinical benefits than the use of either the radiomic or clinical model alone. CONCLUSION: The results of this study suggest that a radiomics model can distinguish patients with and without gout flares. Our proposed clinical radiomics nomogram can increase the efficacy of differentiating flare occurrence, which may facilitate the clinical decision-making process.

Dual-energy computed tomography for predicting histological grading and survival in patients with pancreatic ductal adenocarcinoma.

OBJECTIVES: We evaluated the value of dual-energy computed tomography (DECT) parameters derived from pancreatic ductal adenocarcinoma (PDAC) to discriminate between high- and low-grade tumors and predict overall survival (OS) in patients. METHODS: Data were retrospectively collected from 169 consecutive patients with pathologically confirmed PDAC who underwent third-generation dual-source DECT enhanced dual-phase scanning before surgery between January 2017 and March 2023. Patients with prior treatments, other malignancies, small tumors, or poor-quality scans were excluded. Two radiologists evaluated three clinical and seven radiological features and measured sixteen DECT-derived parameters. Univariate and multivariate analyses were applied to select independent predictors. A prediction model and a corresponding nomogram were developed, and the area under the curve (AUC), calibration, and clinical applicability were assessed. The correlations between factors and OS were evaluated using Kaplan-Meier survival and Cox regression analyses. RESULTS: One hundred sixty-nine patients were randomly divided into training (n = 118) and validation (n = 51) cohorts, among which 43 (36.4%) and 19 (37.3%) had high-grade PDAC confirmed by pathology, respectively. The vascular invasion, normalized iodine concentration in the venous phase, and effective atomic number in the venous phase were independent predictors for histological grading. A nomogram was constructed to predict the risk of high-grade tumors in PDAC, with AUCs of 0.887 and 0.844 in the training and validation cohorts, respectively. The nomogram exhibited good calibration and was more beneficial than a single parameter in both cohorts. Pathological- and nomoscore-predicted high-grade PDACs were associated with poor OS (all p < 0.05). CONCLUSIONS: The nomogram, which combines DECT parameters and radiological features, can predict the histological grade and OS in patients with PDAC before surgery. KEY POINTS: Question Preoperative determination of histological grade in PDAC is crucial for guiding treatment, yet current methods are invasive and limited. Findings A DECT-based nomogram combining vascular invasion, normalized iodine concentration, and effective atomic number accurately predicts histological grade and OS in PDAC patients. Clinical relevance The DECT-based nomogram is a reliable, non-invasive tool for predicting histological grade and OS in PDAC. It provides essential information to guide personalized treatment strategies, potentially improving patient management and outcomes.

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

BACKGROUND: 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. PURPOSE: To evaluate whether DLIR on low-keV VMIs of dual-energy CT scans improves the visualization of the AKA. MATERIAL AND METHODS: 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). RESULTS: 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. CONCLUSION: Visualization of the AKA was significantly better on low-keV VMIs subjected to DLIR than conventional HIR images.

Dual-energy computed tomography for predicting cervical lymph node metastasis in laryngeal squamous cell carcinoma.

Rationale and objectives: We constructed a dual-energy computed tomography (DECT)-based model to assess cervical lymph node metastasis (LNM) in patients with laryngeal squamous cell carcinoma (LSCC). Materials and methods: We retrospectively analysed 164 patients with LSCC who underwent preoperative DECT from May 2019 to May 2023. The patients were randomly divided into training (n = 115) and validation (n = 49) cohorts. Quantitative DECT parameters of the primary tumours and their clinical characteristics were collected. A logistic regression model was used to determine independent predictors of LNM, and a nomogram was constructed along with a corresponding online model. Model performance was assessed using the area under the curve (AUC) and the calibration curve, and the clinical value was evaluated using decision curve analysis (DCA). Results: In total, 64/164 (39.0 %) patients with LSCC had cervical LNM. Independent predictors of LNM included normalized iodine concentration in the arterial phase (odds ratio [OR]: 8.332, 95 % confidence interval [CI]: 2.813-24.678, P < 0.001), normalized effective atomic number in the arterial phase (OR: 5.518, 95 % CI: 1.095-27.818, P = 0.002), clinical T3-4 stage (OR: 5.684, 95 % CI: 1.701-18.989, P = 0.005), and poor histological grade (OR: 5.011, 95 % CI: 1.003-25.026, P = 0.049). These predictors were incorporated into the DECT-based nomogram and the corresponding online model, showing good calibration and favourable performance (training AUC: 0.910, validation AUC: 0.918). The DCA indicated a significant clinical benefit of the nomogram for estimating LNM. Conclusions: DECT parameters may be useful independent predictors of LNM in patients with LSCC, and a DECT-based nomogram may be helpful in clinical decision-making.

Standardization of Dual-Energy CT Iodine Uptake of the Abdomen and Pelvis: Defining Reference Values in a Big Data Cohort.

Background: To establish dual-energy-derived iodine density reference values in abdominopelvic organs in a large cohort of healthy subjects. Methods: 597 patients who underwent portal venous phase dual-energy CT scans of the abdomen were retrospectively enrolled. Iodine distribution maps were reconstructed, and regions of interest measurements were placed in abdominal and pelvic structures to obtain absolute iodine values. Subsequently, normalization of the abdominal aorta was conducted to obtain normalized iodine ratios. The values obtained were subsequently analyzed and differences were investigated in subgroups defined by sex, age and BMI. Results: Overall mean iodine uptake values and normalized iodine ratios ranged between 0.31 and 6.08 mg/mL and 0.06 and 1.20, respectively. Women exhibited higher absolute iodine concentration across all organs. With increasing age, normalized iodine ratios mostly tend to decrease, being most significant in the uterus, prostate, and kidneys (p < 0.015). BMI was the parameter less responsible for variations in iodine concentrations; normal weighted patients demonstrated higher values of both absolute and normalized iodine. Conclusions: Iodine concentration values and normalized iodine ratios of abdominal and pelvic organs reveal significant gender-, age-, and BMI-related differences, underscoring the necessity to integrate these variables into clinical practice.

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

Purpose: 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). Material and methods: 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. Results: 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. Conclusions: 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.

Differentiating Myelography Contrast from Intraventricular and Subarachnoid Hemorrhage Using Dual-Energy CT of the Head: A Case Report and a Review of Literature.

Single-energy computed tomography (SECT) head is a common diagnostic tool to evaluate for intracranial hemorrhage in emergency settings due to its widespread accessibility and non-invasive nature. However, SECT has densitometric evaluation limitations. For example, hyperdensities on SECT such as blood product and iodine contrast appear similarly. Dual-energy CT (DECT) is a relatively under-utilized imaging modality that has the capability to differentiate between multiple materials. This imaging technique can be extremely useful in identifying materials that are otherwise indistinguishable from standard SECT. The authors present a case of a patient with findings suspicious of intraventricular and subarachnoid hemorrhage on conventional SECT. The suspected hemorrhage was subsequently ruled out utilizing DECT, as iodinated contrast can be subtracted out, yielding an image that can differentiate iodine contrast from blood or other hyperdense material. The authors discuss the underlying physics, potential advantages, and limitations of the DECT.

Increased Multispectral CT Iodine Concentrations in Patients With Transient Neurological Deterioration Following Endovascular Neurointerventional Procedures: an Argument in Favor of the Elusive Contrast-Induced Encephalopathy?

BACKGROUND AND PURPOSE: So-called contrast-induced encephalopathy (CIE) is a rare but worrying condition occurring after cerebral angiography or neuroendovascular interventions using iodine contrast media. This study aimed to compare cerebral iodine concentrations in patients suspected of having CIE after endovascular procedures to those in matched controls. METHODS: This is a retrospective monocentric study of 25 suspected CIE patients in a tertiary care teaching hospital diagnosed from June 2017 to February 2024. Cerebral multispectral computed tomography (CT) iodine mean concentrations were measured and compared with 1:1 matched controls using the CT constructor's workstation in the whole brain and in specific regions of interest (ROIs) corresponding to a vascular territory downstream of the procedure. Concentration values were compared with paired samples t­test. RESULTS: During the study period, 1097 patients underwent aneurysm embolization and 137 arteriovenous malformation (AVM) embolization procedures. So-called CIE was suspected in 25 patients after aneurysm or AVM embolization (2%). Mean iodine concentrations in the procedure vascular territory ROIs were higher in suspected CIE cases (mean 543 ± 147 µg/cm3) compared to matched controls (mean 463 ± 141 µg/cm3; p = 0.01). Whole brain mean iodine concentrations were modestly higher in CIE patients compared to controls across all subgroups, without reaching statistical significance. CONCLUSIONS: CIE may be associated with modest increase in CT iodine concentration in the procedure vascular territory after neurointerventional procedures. The underlying pathophysiology of this condition remains uncertain and merits further investigation. KEY MESSAGES: Contrast-induced encephalopathy (CIE) is known as a rare neurologic condition following iodine contrast media use in neuroendovascular interventions, with unclear pathophysiology. WHAT THIS STUDY ADDS: This study provides evidence that suspected CIE is associated with higher cerebral iodine concentrations in affected vascular territories, a novel quantifiable change. Implications for research, practice, or policy: These findings suggest the potential for iodine concentration monitoring to refine CIE diagnosis and prevention strategies in clinical practice.

Correction for partial volume averaging in the quantification of radiopaque nanomaterial-embedded resorbable polymers.

Resorbable inferior vena cava (IVC) filters require embedded contrast for image-guided placement and integrity monitoring. We calculated correction factors to account for partial volume averaging of thin nanoparticle (NP)-embedded materials, accounting for object and slice thicknesses, background signal, and nanoparticle concentration. We used phantoms containing polycaprolactone disks embedded with bismuth (Bi) or ytterbium (Yb): 0.4- to 1.2-mm-thick disks of 20 mg ml-1NPs (thickness phantom), 0.4-mm-thick disks of 0-20 mg ml-1NPs in 2 mg ml-1iodine (concentration phantom), and 20 mg ml-1NPs in 0.4-mm-thick disks in 0-10 mg ml-1iodine (background phantom). Phantoms were scanned on a dual-source CT with 80, 90, 100, and 150 kVp with tin filtration and reconstructed at 1.0- to 1.5-mm slice thickness with a 0.1-mm interval. Following scanning, disks were processed for inductively coupled plasma optical emission spectrometry (ICP-OES) to determine NP concentration. Mean and maximum CT numbers (HU) of all disks were measured over a 0.5-cm2area for each kVp. HU was converted to concentration using previously measured calibrations. Concentration measurements were corrected for partial volume averaging by subtracting residual slice background and extrapolating disk thickness to both nominal and measured slice sensitivity profiles (SSP, mm). Slice thickness to agreement (STTA, mm) was calculated by replacing the CT-derived concentrations with ICP-OES measurements and solving for thickness. Slice thickness correction factors improved agreement with ICP-OES for all measured data. Yb corrections resulted in lower STTA than Bi corrections in the concentration phantom (1.01 versus 1.31 STTA/SSP, where 1.0 is perfect agreement), phantoms with varying thickness (1.30 versus 1.87 STTA/SSP), and similar ratio in phantoms with varying background iodine concentration (1.34 versus 1.35 STTA/SSP). All measured concentrations correlated strongly with ICP-OES and all corrections for partial volume averaging increased agreement with ICP-OES concentration, demonstrating potential for monitoring the integrity of thin IVC resorbable filters with CT.

Diagnostic Accuracy of Dual-Energy CT-Derived Metrics for the Prediction of Osteoporosis-Associated Fractures.

RATIONALE AND OBJECTIVES: This study aimed to compare the diagnostic value of dual-energy CT (DECT)-based volumetric material decomposition with that of Hounsfield units (HU)-based values and cortical thickness ratio for predicting the 2-year risk of osteoporosis-associated fractures. METHODS: The L1 vertebrae of 111 patients (55 men, 56 women; median age, 62 years) who underwent DECT between 01/2015 and 12/2018 were retrospectively analyzed. For phantomless bone mineral density (BMD) assessment, a specialized DECT postprocessing software employing material decomposition was utilized. The digital records of all patients were monitored for two years after the DECT scans to track the incidence of osteoporotic fractures. Diagnostic accuracy parameters were calculated for all metrics using receiver-operating characteristic (ROC) and precision-recall (PR) curves. Logistic regression models were used to determine associations of various predictive metrics with the occurrence of osteoporotic fractures. RESULTS: Patients who sustained one or more osteoporosis-associated fractures in a 2-year interval were significantly older (median age 74.5 years [IQR 57-83 years]) compared those without such fractures (median age 50.5 years [IQR 38.5-69.5 years]). According to logistic regression models, DECT-derived BMD was the sole predictive parameter significantly associated with osteoporotic fracture occurrence across all age groups. ROC and PR curve analyses confirmed the highest diagnostic accuracy for DECT-based BMD, with an area under the curve (AUC) of 0.95 [95% CI: 0.89-0.98] for the ROC curve and an AUC of 0.96 [95% CI: 0.85-0.99] for the PR curve. CONCLUSION: The diagnostic performance of DECT-based BMD in predicting the 2-year risk of osteoporotic fractures is greater than that of HU-based metrics and the cortical thickness ratio. DECT-based BMD values are highly valuable in identifying patients at risk for osteoporotic fractures.

Dual-energy computed tomography with new virtual monoenergetic image reconstruction enhances prostate lesion image quality and improves the diagnostic efficacy for prostate cancer.

BACKGROUND: Prostate cancer is one of the most common malignant tumors in middle-aged and elderly men and carries significant prognostic implications, and recent studies suggest that dual-energy computed tomography (DECT) utilizing new virtual monoenergetic images can enhance cancer detection rates. This study aimed to assess the impact of virtual monoenergetic images reconstructed from DECT arterial phase scans on the image quality of prostate lesions and their diagnostic performance for prostate cancer. METHODS: We conducted a retrospective analysis of 83 patients with prostate cancer or prostatic hyperplasia who underwent DECT scans at Meizhou People's Hospital between July 2019 and December 2023. The variables analyzed included age, tumor diameter and serum prostate-specific antigen (PSA) levels, among others. We also compared CT values, signal-to-noise ratio (SNR), subjective image quality ratings, and contrast-to-noise ratio (CNR) between virtual monoenergetic images (40-100 keV) and conventional linear blending images. Receiver operating characteristic (ROC) curve analyses were performed to evaluate the diagnostic efficacy of virtual monoenergetic images (40 keV and 50 keV) compared to conventional images. RESULTS: Virtual monoenergetic images at 40 keV showed significantly higher CT values (168.19 ± 57.14) compared to conventional linear blending images (66.66 ± 15.5) for prostate cancer (P < 0.001). The 50 keV images also demonstrated elevated CT values (121.73 ± 39.21) compared to conventional images (P < 0.001). CNR values for the 40 keV (3.81 ± 2.13) and 50 keV (2.95 ± 1.50) groups were significantly higher than the conventional blending group (P < 0.001). Subjective evaluations indicated markedly better image quality scores for 40 keV (median score of 5) and 50 keV (median score of 5) images compared to conventional images (P < 0.05). ROC curve analysis revealed superior diagnostic accuracy for 40 keV (AUC: 0.910) and 50 keV (AUC: 0.910) images based on CT values compared to conventional images (AUC: 0.849). CONCLUSIONS: Virtual monoenergetic images reconstructed at 40 keV and 50 keV from DECT arterial phase scans substantially enhance the image quality of prostate lesions and improve diagnostic efficacy for prostate cancer.

Radiomics model based on dual-energy CT can determine the source of thrombus in strokes with middle cerebral artery occlusion.

PURPOSE: To develop thrombus radiomics models based on dual-energy CT (DECT) for predicting etiologic cause of stroke. METHODS: We retrospectively enrolled patients with occlusion of the middle cerebral artery who underwent computed tomography (NCCT) and DECT angiography (DECTA). 70 keV virtual monoenergetic images (simulate conventional 120kVp CTA images) and iodine overlay maps (IOM) were reconstructed for analysis. Five logistic regression radiomics models for predicting cardioembolism (CE) were built based on the features extracted from NCCT, CTA and IOM images. From these, the best one was selected to integrate with clinical information for further construction of the combined model. The performance of the different models was evaluated and compared using ROC curve analysis, clinical decision curves (DCA), calibration curves and Delong test. RESULTS: Among all the radiomic models, model NCCT+IOM performed the best, with AUC = 0.95 significantly higher than model NCCT, model CTA, model IOM and model NCCT+CTA in the training set (AUC = 0.88, 0.78, 0.90,0.87, respectively, P < 0.05), and AUC = 0.92 in the testing set, significantly higher than model CTA (AUC = 0.71, P < 0.05). Smoking and NIHSS score were independent predictors of CE (P < 0.05). The combined model performed similarly to the model NCCT+IOM, with no statistically significant difference in AUC either in the training or test sets. (0.96 vs. 0.95; 0.94 vs. 0.92, both P > 0.05). CONCLUSION: Radiomics models constructed based on NCCT and IOM images can effectively determine the source of thrombus in stroke without relying on clinical information.

Differentiating between benign and malignant breast lesions using dual-energy CT-based model: development and validation.

OBJECTIVES: To develop and validate a dual-energy CT (DECT)-based model for noninvasively differentiating between benign and malignant breast lesions detected on DECT. MATERIALS AND METHODS: This study prospectively enrolled patients with suspected breast cancer who underwent dual-phase contrast-enhanced DECT from July 2022 to July 2023. Breast lesions were randomly divided into the training and test cohorts at a ratio of 7:3. Clinical characteristics, DECT-based morphological features, and DECT quantitative parameters were collected. Univariate analyses and multivariate logistic regression were performed to determine independent predictors of benign and malignant breast lesions. An individualized model was constructed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic ability of the model, whose calibration and clinical usefulness were assessed by calibration curve and decision curve analysis. RESULTS: This study included 200 patients (mean age, 49.9 ± 11.9 years; age range, 22-83 years) with 222 breast lesions. Age, lesion shape, and the effective atomic number (Zeff) in the venous phase were significant independent predictors of breast lesions (all p < 0.05). The discriminative power of the model incorporating these three factors was high, with AUCs of 0.844 (95%CI 0.764-0.925) and 0.791 (95% CI 0.647-0.935) in the training and test cohorts, respectively. The constructed model showed a preferable fitting (all p > 0.05 by the Hosmer-Lemeshow test) and provided enhanced net benefits than simple default strategies within a wide range of threshold probabilities in both cohorts. CONCLUSION: The DECT-based model showed a favorable diagnostic performance for noninvasive differentiation between benign and malignant breast lesions detected on DECT. CRITICAL RELEVANCE STATEMENT: The combination of clinical and morphological characteristics and DECT-derived parameter have the potential to identify benign and malignant breast lesions and it may be useful for incidental breast lesions on DECT to decide if further work-up is needed. KEY POINTS: It is important to characterize incidental breast lesions on DECT for patient management. DECT-based model can differentiate benign and malignant breast lesions with good performance. DECT-based model is a potential tool for distinguishing breast lesions detected on DECT.