Dual-energy CT Research Articles

Visual assessment and quantitative analysis of dual-energy CT virtual non-calcium in imaging diagnosis of multiple myeloma.

To evaluate the reliability and diagnostic performance of dual-energy CT virtual non-calcium imaging in diagnosing bone marrow infiltration in multiple myeloma. Seventy-two patients with multiple myeloma and ten controls were recruited. Patients received dual-energy CT and MRI while controls underwent dual-energy CT only, covering the cervical, thoracic, and lumbar spine and the pelvis. Virtual non-calcium images were compared with magnetic resonance images for confirmation and pattern classification. Fleiss Kappa analysis assessed consistency between virtual non-calcium and MRI classifications. Inter-observer agreement for virtual non-calcium and CT attenuation values was evaluated using Bland-Altman analysis. Diagnostic performances across various sites were evaluated using analysis of variance and receiver operating characteristic curve analysis. Dual-energy CT achieved higher consistency in classifying bone marrow infiltration in multiple myeloma than did MRI (kappa = 0.944). In the overall analysis, the mean virtual non-calcium attenuation values in the bone marrow infiltration group (- 28.3 HU; 95% confidence interval (CI), - 32.1, - 24.6) were higher than those in the non-bone marrow infiltration (- 97.5 HU; 95% CI, - 104.7, - 90.3) and control (- 89.1 HU; 95% CI, - 95.1, - 83.1; F = 172.027, P < 0.001) groups. The optimal cutoff values for virtual non-calcium attenuation varied across the overall (- 42.2 HU), cervical spine (- 21.9 HU), thoracic spine (- 42.8 HU), lumbar spine (- 56.9 HU), and pelvis (- 66.3 HU). Dual-energy CT virtual non-calcium imaging and MRI exhibited good consistency in categorising bone marrow infiltration patterns in multiple myeloma. Different virtual non-calcium attenuation value cutoffs should be used to diagnose bone marrow infiltration in various body regions.

3D Printing Materials Mimicking Human Tissues after Uptake of Iodinated Contrast Agents for Anthropomorphic Radiology Phantoms.

(1) Background: 3D printable materials with accurately defined iodine content enable the development and production of radiological phantoms that simulate human tissues, including lesions after contrast administration in medical imaging with X-rays. These phantoms provide accurate, stable and reproducible models with defined iodine concentrations, and 3D printing allows maximum flexibility and minimal development and production time, allowing the simulation of anatomically correct anthropomorphic replication of lesions and the production of calibration and QA standards in a typical medical research facility. (2) Methods: Standard printing resins were doped with an iodine contrast agent and printed using a consumer 3D printer, both (resins and printer) available from major online marketplaces, to produce printed specimens with iodine contents ranging from 0 to 3.0% by weight, equivalent to 0 to 3.85% elemental iodine per volume, covering the typical levels found in patients. The printed samples were scanned in a micro-CT scanner to measure the properties of the materials in the range of the iodine concentrations used. (3) Results: Both mass density and attenuation show a linear dependence on iodine concentration (R2 = 1.00), allowing highly accurate, stable, and predictable results. (4) Conclusions: Standard 3D printing resins can be doped with liquids, avoiding the problem of sedimentation, resulting in perfectly homogeneous prints with accurate dopant content. Iodine contrast agents are perfectly suited to dope resins with appropriate iodine concentrations to radiologically mimic tissues after iodine uptake. In combination with computer-aided design, this can be used to produce printed objects with precisely defined iodine concentrations in the range of up to a few percent of elemental iodine, with high precision and anthropomorphic shapes. Applications include radiographic phantoms for detectability studies and calibration standards in projective X-ray imaging modalities, such as contrast-enhanced dual energy mammography (abbreviated CEDEM, CEDM, TICEM, or CESM depending on the equipment manufacturer), and 3-dimensional modalities like CT, including spectral and dual energy CT (DECT), and breast tomosynthesis.

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.

Fundamentals of Dual Energy CT and its emerging applications in Bladder Cancer

Fundamentals of Dual Energy CT and its emerging applications in Bladder Cancer

Dual-Energy CT of Intrahepatic Splenosis.

Dual-Energy CT of Intrahepatic Splenosis.

Dual-energy CT quantitative parameters to evaluate occult peritoneal metastasis in advanced gastric cancer preoperatively.

To explore whether dual-energy CT (DECT) quantitative parameters could provide analytic value for the diagnosis of patients with occult peritoneal metastasis (OPM) in advanced gastric cancer preoperatively. This retrospective study included 219 patients with advanced gastric cancer and DECT scans. The patient's clinical data and DECT related iodine concentration (IC) parameters and effective atomic number (Zeff) were collated and analyzed among noun-peritoneal metastasis (NPM), OPM and radiologically peritoneal metastasis (RPM) groups. The predictive performance of the DECT parameters was compared with that of the conventional CT features and clinical characteristics through evaluating area under curve of the precision-recall (AUC-PR), F1 score, balanced accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Borrmann IV type diagnosed on CT and serum tumor indicator CA125 index were statistically different between the NPM and OPM groups. DECT parameters included IC, normalized IC (NIC), and Zeff of PM group were lower than the NPM group. The DECT predictive nomogram combined three independent DECT parameters produced a better diagnostic performance than the conventional CT feature Borrmann IV type and serum CA125 index in AUC-PR with 0.884 vs 0.368 vs 0.189, but similar to the combined indicator which was based on the DECT parameters, the conventional CT feature, and serum CA125 index in AUC-PR with 0.884 vs 0.918. The lower quantitative NIC, IC ratio, and Zeff on DECT was associated with peritoneal metastasis in advanced gastric cancer and was promising to identify patients with OPM noninvasively.

Utility of dual-energy CT and advanced multiparametric MRI based imaging biomarkers of pancreatic fibrosis in grading the severity of chronic pancreatitis.

To non-invasively quantify pancreatic fibrosis and grade severity of chronic pancreatitis (CP) on dual-energy CT (DECT) and multiparametric MRI (mpMRI). We included 72 patients (mean age:30years; 59 men) with suspected or confirmed CP from December 2019 to December 2021 graded as equivocal(n = 20), mild(n = 18), and moderate-marked(n = 34) using composite imaging and endoscopic ultrasound criteria. Study patients underwent multiphasic DECT and mpMRI of the abdomen. Normalized iodine concentration(NIC) and fat fraction(FF) on 6-minute delayed DECT, and T1 relaxation time(T1Rt), extracellular volume fraction(ECVf), intravoxel incoherent motion-based perfusion fraction(PF), and magnetization transfer ratio(MTR) on mpMRI of pancreas were compared. 20 renal donors(for DECT) and 20 patients with renal mass(for mpMRI) served as controls. NIC of pancreas in controls and progressive grades of CP were 0.24 ± 0.05, 0.80 ± 0.18, 1.06 ± 0.23, 1.40 ± 0.36, FF were 9.28 ± 5.89, 14.19 ± 5.29, 17.31 ± 5.99, 29.32 ± 12.22, T1Rt were 590.11 ± 61.13, 801.93 ± 211.01, 1006.79 ± 352.18, 1388.01 ± 312.23ms, ECVf were 0.07 ± 0.03, 0.30 ± 0.12, 0.41 ± 0.12, 0.53 ± 0.13, PF were 0.38 ± 0.04, 0.28 ± 0.07, 0.25 ± 0.09, 0.21 ± 0.05 and MTR were 0.12 ± 0.03, 0.15 ± 0.06, 0.21 ± 0.07, 0.26 ± 0.06, respectively. There were significant differences for all quantitative parameters between controls and mild CP; for NIC, PF, and ECVf between controls and progressive CP grades (p < 0.05). Area under curve for NIC, FF, T1Rt, ECVf, PF, and MTR in differentiating controls and mild CP were 1.00, 0.86, 0.95, 1.00, 0.90 and 0.84 respectively and for NIC, FF, ECVf and PF in differentiating controls and equivocal CP were 1.00, 0.76, 0.95 and 0.92 respectively. DECT and mpMRI were useful in quantifying pancreatic fibrosis and grading the severity of CP. NIC was the most accurate marker.

Dual energy computed tomography in assessment of bone marrow edema in pathologies of the appendicular skeleton

BackgroundBone marrow edema cannot be detected on the conventional computed tomography scan. MRI has excellent diagnostic performance in detecting bone marrow edema but multiple difficulties in the emergency setting makes performing MRI logistically challenging. The aim of the study was to assess dual energy computed tomography accuracy for bone marrow edema in pathologies of the appendicular skeleton. This was based on color-coded maps and quantitative analysis of Hounsfield unit (HU) in subtraction images, compared with MRI. Materials and methodsProspective observational study was performed by including 60 patients who underwent Dual energy CT (DECT) and MRI. Statistical analysis was performed by calculating p-value and ROC curve analysis. The derived cut off value was used to identify bone marrow edema and diagnostic accuracy, sensitivity, specificity, negative predictive value and positive predictive value of DECT was calculated using MRI as gold standard. A further sub-analysis between the traumatic and non-traumatic groups was done. ResultsBone marrow edema on Color coded virtual non-calcium (VNCa) images and Mean HU of bone marrow edematous site was calculated. Attenuation difference between edematous bone marrow and rest of the bone were correlated with MRI, (p-value 0.0001). The sensitivity, specificity, negative predictive, positive predictive value, and diagnostic accuracy were 91.1, 93.3, 97.6, 77.8 and 91.67 % respectively. ConclusionOur results confirmed that Dual energy CT has high overall sensitivity, specificity and diagnostic accuracy in depicting bone marrow edema when compared to MRI, in various etiologies of the appendicular skeleton. This will lead to reduced missed cases by early detection of bone marrow edema secondary to fractures that are not identifiable in conventional CT. Marrow edema in DECT can be used as an indicator for disease activity and progression in conditions such as transient osteoporosis, tumour, arthritis, avascular necrosis and various other etiologies, generally missed in conventional radiography.

Image quality of virtual monochromatic and material density iodine images for evaluation of head and neck neoplasms using deep learning-based CT image reconstruction – A retrospective observational study

PurposeTo compare the quality of deep learning image reconstructed (DLIR) virtual monochromatic images (VMI) and material density (MD) iodine images from dual-energy computed tomography (DECT) for the evaluation of head and neck neoplasms with CT scans from a conventional single-energy protocol. MethodA total of 294 head and neck CT scans (98 VMIs operated at 60 keV, 102 MD iodine images, and 94 images from a 120 kVp single-energy CT (SECT) protocol) were retrospectively evaluated. VMIs and MD iodine images were generated using the Gemstone Spectral Imaging (GSI) mode using DLIR and metal artifact reduction (MAR) algorithms. SECT images were generated using adaptive statistical iterative reconstruction (ASIR-V). Images were scored by two independent readers on a 6-point Likert-type scale for overall image quality, vessel contrast, soft tissue contrast, noise texture, noise intensity, artifact reduction, and sharpness. ResultsSubjective overall image quality was rated as superior or excellent in 98 % of DLIR-based MD iodine images and VMIs, but only in 55 % of ASIR-V-based SECT images. For each individual quality criterion, image quality of VMIs and MD iodine images was rated as better than that of SECT images (p < 0.001 in each case). Noise texture and intensity were rated better in MD iodine images than in VMIs. ConclusionDECT using both DLIR and MAR for the generation of VMIs and MD iodine images resulted in higher subjective quality of oncologic head and neck images than ASIR-V-based SECT. Noise reduction and noise texture were best achieved with DLIR-based MD iodine images.

Quantitative pulmonary perfusion in acute pulmonary embolism and chronic thromboembolic pulmonary hypertension.

Current methods for quantifying perfusion from computed tomography pulmonary angiography (CTPA) often rely on semi-quantitative scoring systems and requires an experienced evaluator. Few studies report on absolute quantitative variables derived from the images, and the methods are varied with mixed results. Dual-energy CTPA (DE-CTPA) enables automatic quantification of lung and lobar perfusion with minimal user interaction by utilizing machine learning based software. We aimed to evaluate differences in DE-CTPA derived quantitative perfusion variables between patients with acute pulmonary embolism (PE) and chronic thromboembolic pulmonary hypertension (CTEPH). This retrospective, single-center, observational study included 162 adult patients diagnosed with PE (n = 81) or CTEPH (n = 81) and scanned using dual-energy CT between 2020 and 2023. Mann-Whitney U tests and permutational analysis of variance (PERMANOVA) were used for comparative analyses. We found whole lung perfusion blood volume to be lower (p < 0.001) in PE patients (median 3399 mL [2554, 4284]) than in CTEPH patients (median 4094 mL [3397, 4818]). The same was observed at single lung and lobar level. PERMANOVA encompassing all perfusion variables showed a difference between the two groups (F-statistic = 13.3, p = 0.002). Utilizing logistic regression, right and left lower lobe perfusion blood volume showed some ability to differentiate between PE and CTEPH with area under the receiver operation characteristics curve values of 0.71 (95% CI: 0.56; 0.84) and 0.72 (95% CI: 0.56; 0.86). Pulmonary perfusion is lower in patients with PE than patients with CTEPH, highlighted by differences in DECT-derived perfusion blood volume. Quantitative perfusion variables might be useful to differentiate between the two diseases.

109 - Evaluation of dose calculation in Direct Density algorithm reconstruction images using dual energy CT for Radiotherapy

109 - Evaluation of dose calculation in Direct Density algorithm reconstruction images using dual energy CT for Radiotherapy

Dual-Energy CT Bone Findings in Kidney Transplant Recipients with Uncontrolled Gout

Dual-Energy CT Bone Findings in Kidney Transplant Recipients with Uncontrolled Gout

Head and neck automatic multi-organ segmentation on Dual-Energy Computed Tomography

Background and purposeDeep-learning-based automatic segmentation is widely used in radiation oncology to delineate organs-at-risk. Dual-energy CT (DECT) allows the reconstruction of enhanced contrast images that could help with manual and auto-delineation. This paper presents a performance evaluation of a commercial auto-segmentation software on image series generated by a DECT. Material and methodsDifferent types of DECT images from seventy four head-and-neck (HN) patients were retrieved, including polyenergetic images at different voltages [80 kV reconstructed with a kernel corresponding to the commercial algorithm DirectDensity™ (PEI80-DD), 80 kV (PEI80), 120 kV-mixed (PEI120)] and a virtual-monoenergetic image at 40 keV (VMI40). Delineations used for treatment planning were considered as ground truth (GT) and were compared with the auto-segmentations performed on the 4 DECT images. A blinded qualitative evaluation of 3 structures (thyroid, left parotid, left nodes level II) was carried out. Performance metrics were calculated for thirteen HN structures to evaluate the auto-contours including dice similarity coefficient (DSC), 95th percentile Hausdorff distance (95HD) and mean surface distance (MSD). ResultsWe observed a high rate of low scores for PEI80-DD and VMI40 auto-segmentations on the thyroid and for GT and VMI40 contours on the nodes level II. All images received excellent scores for the parotid glands. The metrics comparison between GT and auto-segmented contours revealed that PEI80-DD had the highest DSC scores, significantly outperforming other reconstructed images for all organs (p < 0.05). ConclusionsThe results indicate that the auto-contouring system cannot generalize to images derived from DECT acquisition. It is therefore crucial to identify which organs benefit from these acquisitions to adapt the training datasets accordingly.

Diagnosis of newly developed multiple myeloma without bone disease detectable on conventional computed tomography (CT) scan by using dual-energy CT

ObjectiveTo evaluate the diagnostic utility of fat (hydroxyapatite) density [DFat (HAP)] on dual-energy computed tomography (DECT) for identifying clinical diagnosed multiple myeloma without bone disease (MNBD) that is not visible on conventional CT scans. Material and MethodsIn this age-gender-examination sites matched case control prospective study, Chest and/or abdominal images on Revolution CT of MNBDs and control subjects were consecutive enrolled in a 1:2 ratio from October 2022 to November 2023. Multiple myeloma was clinical diagnosed according to criteria of the International Myeloma Working Group. Regions of interest (ROIs) were drawn separately for all thoracolumbar vertebrae in the scanning range by two radiologists. Additionally, a radiologist specializing in musculoskeletal imaging supervised the process. DFat (HAP) was extracted from each ROI. The spine was divided into upper thoracic (UPT), middle and lower thoracic (MLT), thoracolumbar (TL), and middle and lower lumbar (MLL) vertebrae. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the diagnostic performance of DFat (HAP) in diagnosing multiple myeloma, and the sensitivity, specificity, and accuracy under the optimal cut-off were determined by Youden index (sensitivity + specificity −1). ResultsA total of 32 and MNBD patients and 64 control patients were included. The total number of ROIs outlined included MNBD group (n = 493) and control group (n = 986). For all vertebrae, DFat(HAP) got average performance in the diagnosis of MNBD (AUC = 0.733, p < 0.001) with a cut-off value of 958 (mg/cm3); the sensitivity, specificity, and accuracy were 58.8 %, 77.8 %, and 71.7 %, respectively. Regarding segment analysis, the diagnostic performance was good for all (AUC, 0.803–0.837; p < 0.001) but the UPT segment (AUC = 0.692, p = 0.002). The optimal diagnostic cut-off values for the MLT, TL, and MLL vertebrae were 955 mg/cm3, 947 mg/cm3, and 947 mg/cm3, respectively; the sensitivity, specificity, and accuracy were 80.0 %-87.5 %, 71.9 %-82.6 %, and 77.1 %-81.6 %, respectively. ConclusionDECT was effective for detecting MNBD, and better diagnostic results can be obtained by grouping different spine segments.

Benefits of Brain Dual-Energy CT Imaging in Detecting Intracranial Hemorrhage in Non-Contrast Brain CT Scans

Benefits of Brain Dual-Energy CT Imaging in Detecting Intracranial Hemorrhage in Non-Contrast Brain CT Scans

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 patientsaged 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.

Carotid artery assessment in dual-source photon-counting CT: impact of low-energy virtual monoenergetic imaging on image quality, vascular contrast and diagnostic assessability.

Preliminary dual-energy CT studies have shown that low-energy virtual monoenergetic (VMI) + reconstructions can provide superior image quality compared to standard 120kV CTA series. The purpose of this study is to evaluate the impact of low-energy VMI reconstructions on quantitative and qualitative image quality, vascular contrast, and diagnostic assessability of the carotid artery in patients undergoing photon-counting CTA examinations. A total of 122 patients (67 male) who had undergone dual-source photon-counting CTA scans of the carotid artery were retrospectively analyzed in this study. Standard 120kV CT images and low-keV VMI series from 40 to 100keV with an interval of 15keV were reconstructed. Quantitative analyses included the evaluation of vascular CT numbers, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). CT number measurements were performed in the common, external, and internal carotid arteries. Qualitative analyses were performed by three board-certified radiologists independently using five-point scales to evaluate image quality, vascular contrast, and diagnostic assessability of the carotid artery. Mean attenuation, CNR and SNR values were highest in 40keV VMI reconstructions (HU, 1362.32 ± 457.81; CNR, 33.19 ± 12.86; SNR, 34.37 ± 12.89) followed by 55-keV VMI reconstructions (HU, 736.94 ± 150.09; CNR, 24.49 ± 7.11; SNR, 26.25 ± 7.34); all three mean values at these keV levels were significantly higher compared with the remaining VMI series and standard 120kV CT series (HU, 154.43 ± 23.69; CNR, 16.34 ± 5.47; SNR, 24.44 ± 7.14) (p < 0.0001). The qualitative analysis showed the highest rating scores for 55keV VMI reconstructions followed by 40keV and 70keV VMI series with a significant difference compared to standard 120kV CT images series regarding image quality, vascular contrast, and diagnostic assessability of the carotid artery (all comparisons, p < 0.01). Low-keV VMI reconstructions at a level of 40-55keV significantly improve image quality, vascular contrast, and the diagnostic assessability of the carotid artery compared with standard CT series in photon-counting CTA.

Assessing muscle invasion in bladder cancer via virtual biopsy: a study on quantitative parameters and classical radiomics features from dual-energy CT imaging

ObjectiveTo evaluate the prediction value of Dual-energy CT (DECT)-based quantitative parameters and radiomics model in preoperatively predicting muscle invasion in bladder cancer (BCa).Materials and methodsA retrospective study was performed on 126 patients with BCa who underwent DECT urography (DECTU) in our hospital. Patients were randomly divided into training and test cohorts with a ratio of 7:3. Quantitative parameters derived from DECTU were identified through univariate and multivariate logistic regression analysis to construct a DECT model. Radiomics features were extracted from the 40, 70, 100 keV and iodine-based material-decomposition (IMD) images in the venous phase to construct radiomics models from individual and combined images using a support vector machine classifier, and the optimal performing model was chosen as the final radiomics model. Subsequently, a fusion model combining the DECT parameters and the radiomics model was established. The diagnostic performances of all three models were evaluated through receiver operating characteristic (ROC) curves and the clinical usefulness was estimated using decision curve analysis (DCA).ResultsThe normalized iodine concentration (NIC) in DECT was an independent factor in diagnosing muscle invasion of BCa. The optimal multi-image radiomics model had predictive performance with an area-under-the-curve (AUC) of 0.867 in the test cohort, better than the AUC = 0.704 with NIC. The fusion model showed an increased level of performance, although the difference in AUC (0.893) was not statistically significant. Additionally, it demonstrated superior performance in DCA. For lesions smaller than 3 cm, the fusion model showed a high predictive capability, achieving an AUC value of 0.911. There was a slight improvement in model performance, although the difference was not statistically significant. This improvement was observed when comparing the AUC values of the DECT and radiomics models, which were 0.726 and 0.884, respectively.ConclusionThe proposed fusion model combing NIC and the optimal multi-image radiomics model in DECT showed good diagnostic capability in predicting muscle invasiveness of BCa.

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.

Pulmonary embolism detection without intravenous contrast using electron density and Z-effective maps from dual-energy CT

Abstract Purpose This study aims to evaluate the feasibility of using electron density (ED) maps combined with Z-effective (Zeff) images obtained from unenhanced dual-layer dual-energy CT (dl-DECT) scans of the chest for the detection of pulmonary embolism (PE). Materials and methods A retrospective analysis was conducted on consecutive patients who underwent for contrast-enhanced chest CT (CECT) clinically suspected of PE or acute aortic syndrome. These scans were performed on a single dl-DECT scanner between October 2021 and November 2023. To distinguish emboli from circulating blood, color-coded maps were generated from the ED dataset superimposed on Zeff images, which were acquired from the unenhanced phase. Two radiologists with different levels of expertise independently assessed the presence of PE in the generated ED-Zeff maps, blinded to CECT results, which served as the reference standard. Diagnostic accuracy of ED-Zeff maps was assessed for each reader. Results The final study cohort comprised 150 patients, with 92 males (mean age: 68 ± 10 years, range: 47-93 years) and 58 females (mean age: 66 ± 15 years, range 38-89 years). ED-Zeff maps demonstrated high diagnostic performance, yielding accuracy, sensitivity, and specificity, respectively, of 86.67% (113/150, 95% CI, 80.16%-91.66%), 85% (17/20, 95% CI, 79.89%-92.19%), and 86.92% (113/130, 95% CI, 79.89%-92.19%). Ed-Zeff maps were able to identify PE in 85% of positive cases. Cohen’s kappa coefficient indicated excellent intra- and interobserver agreement (κ ≥ 0.9). Conclusion ED maps combined with Zeff images from unenhanced dl-DECT scans represent a feasible tool for detecting PE and may prove useful in evaluating patients with contraindications to iodinated contrast.