Radiomics analysis of dual-layer spectral-detector CT-derived iodine maps for predicting tumor deposits in colorectal cancer.

OBJECTIVE: To investigate the value of radiomics analysis of dual-layer spectral-detector computed tomography (DLSCT)-derived iodine maps for predicting tumor deposits (TDs) preoperatively in patients with colorectal cancer (CRC). MATERIALS AND METHODS: A total of 264 pathologically confirmed CRC patients (TDs + (n = 80); TDs - (n = 184)) who underwent preoperative DLSCT from two hospitals were retrospectively enrolled, and divided into training (n = 124), testing (n = 54), and external validation cohort (n = 86). Conventional CT features and iodine concentration (IC) were analyzed and measured. Radiomics features were derived from venous phase iodine maps from DLSCT. The least absolute shrinkage and selection operator (LASSO) was performed for feature selection. Finally, a support vector machine (SVM) algorithm was employed to develop clinical, radiomics, and combined models based on the most valuable clinical parameters and radiomics features. Area under receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis were used to evaluate the model's efficacy. RESULTS: The combined model incorporating the valuable clinical parameters and radiomics features demonstrated excellent performance in predicting TDs in CRC (AUCs of 0.926, 0.881, and 0.887 in the training, testing, and external validation cohorts, respectively), which outperformed the clinical model in the training cohort and external validation cohorts (AUC: 0.839 and 0.695; p: 0.003 and 0.014) and the radiomics model in two cohorts (AUC: 0.922 and 0.792; p: 0.014 and 0.035). CONCLUSION: Radiomics analysis of DLSCT-derived iodine maps showed excellent predictive efficiency for preoperatively diagnosing TDs in CRC, and could guide clinicians in making individualized treatment strategies. CLINICAL RELEVANCE STATEMENT: The radiomics model based on DLSCT iodine maps has the potential to aid in the accurate preoperative prediction of TDs in CRC patients, offering valuable guidance for clinical decision-making. KEY POINTS: Accurately predicting TDs in CRC patients preoperatively based on conventional CT features poses a challenge. The Radiomics model based on DLSCT iodine maps outperformed conventional CT in predicting TDs. The model combing DLSCT iodine maps radiomics features and conventional CT features performed excellently in predicting TDs.

Contrast thresholds for detection of various iodine concentrations in subtraction CT and dual-energy CT systems.

OBJECTIVE: To estimate the minimum iodine concentrations detectable in simulated vessels of various diameters for both subtraction computed tomography (CT) and dual-energy CT systems. METHODS: Fillable tubes (diameters: 1, 3, and 5 mm) were filled with a variety of iodine concentrations (range: 0-20 mg/ml), placed in the center of 28-mm cylindrical rods and surrounded with water. Rods with and without fillable tubes were placed in a 20-cm cylindrical solid-water phantom to simulate administration of iodine in blood vessels. The phantom was scanned with clinical subtraction CT (SCT) and dual-energy CT (DECT) head protocols to assess the detection of minimum iodine concentrations in both systems. The SCT and DECT images were evaluated quantitatively with a MATLAB script to extract regions of interest (ROIs) of each simulated vessel. ROI measurements were used to calculate the limit of detectability (LOD) and signal-to-noise ratio of Rose criteria for the assessment of the contrast thresholds. RESULTS: Both SNRRose and LOD methods agreed and determined the minimum detectable iodine concentration to be 0.4 mg/ml in the 5-mm diameter vessel for SCT. However, the minimum detectable concentration in the 5-mm vessel with DECT was 1 mg/ml. The 3-mm vessel had a minimum detectable concentration of 0.8 mg/ml for SCT and 2 mg/ml for DECT. Lastly, the minimum detectable iodine concentration for the 1-mm vessel was 10 mg/ml for SCT and 10 mg/ml for DECT. CONCLUSION: In this phantom study, SCT showed the capability to detect lower iodine concentrations compared to DECT. Contrast thresholds varied for vessels of different diameters and the smaller vessels required a higher iodine concentration for detection. Based on this knowledge, radiologists can modify their protocols to increase contrast enhancement.

Efficiency of dual-energy computed tomography enterography in the diagnosis of Crohn's disease.

BACKGROUND: This retrospective study aimed to investigate the usefulness of the optimized kiloelectron volt (keV) for virtual monoenergetic imaging (VMI) combined with iodine map in dual-energy computed tomography enterography (DECTE) in the diagnosis of Crohn's disease (CD). METHODS: Seventy-two patients (mean age: 41.89 ± 17.28 years) with negative computed tomography enterography (CTE) were enrolled for investigating the optimized VMI keV in DECTE by comparing subjective and objective parameters of VMIs that were reconstructed from 40 to 90 keV. Moreover, 68 patients (38.27 ± 15.10 years; 35 normal and 33 CD) were included for evaluating the diagnostic efficacy of DECTE iodine map at the optimized VMI energy level and routine CTE for CD and active CD. Statistical analysis for all data was conducted. RESULTS: Objective and subjective imaging evaluations showed the best results at 60 keV for VMIs. The CT values of the normal group, active subgroup, and CD group during the small intestinal phase at routine 120 kVp or 60 keV VMI had significant differences. The diagnostic efficacy of an iodine map was the best when NIC = 4% or fat value = 45.8% for CD, whereas NIC < 0.35 or the fat value < 0.38 for active CD. The combined routine CTE and optimized VMI improved the diagnostic efficacy (P < 0.001). CONCLUSIONS: VMI at 60 keV provided the best imaging quality on DECTE. NIC and fat value provided important basis for active CD evaluation. Routine CTE combined with VMI at 60 keV improved the diagnostic efficiency for CD.

Quantitative contrast enhanced dual energy CT to predict avascular necrosis: a feasibility study of proximal humerus fractures.

BACKGROUND: Avascular necrosis is a delayed complication of proximal humerus fractures that increases the likelihood of poor clinical outcomes. CT scans are routinely performed to guide proximal humerus fracture management. We hypothesized iodine concentration on post-contrast dual energy CT scans identifies subjects who develop avascular necrosis and ischemia due to compromised blood flow. MATERIALS AND METHODS: 55 patients with proximal humerus fractures enrolled between 2014 and 2017 underwent clinical, radiographic and contrast enhanced dual energy CT assessment. Iodine densities of the humeral head and the glenoid (control) were measured on CT. Subjects managed with open reduction internal fixation or conservatively (non-surgical) were followed for up to two years for radiographic evidence of avascular necrosis. Arthroplasty subjects underwent histopathologic evaluation for ischemia of the resected humeral head. RESULTS: 17 of 55 subjects (30.9%) were treated conservatively, 21 (38.2%) underwent open reduction internal fixation and 17 of 55 (30.9%) underwent arthroplasty. Of the 38 subjects treated conservatively or with ORIF, 20 (52.6%) completed 12 months of follow up and 14 (36.8%) 24 months of follow up. At 12 months follow up, two of 20 subjects (10%) and at 24 months 3 of 14 subjects (21.4%) developed avascular necrosis. At 12 months, the mean humerus/glenoid iodine ratio was 1.05 (standard deviation 0.24) in subjects with AVN compared to 0.91 (0.24) in those who did not. At 24 months, subjects with avascular necrosis had a mean humerus/glenoid iodine concentration ratio of 1.06 (0.17) compared to 0.924 (0.21) in those who did not. Of 17 arthroplasty subjects, 2 had severe ischemia and an iodine ratio of 1.08 (0.30); 5 had focal ischemia and a ratio of 1.00 (0.36); and 8 no ischemia and a ratio of 0.83 (0.08). CONCLUSIONS: Quantifying iodine using dual energy CT in subjects with proximal humerus fractures is technically feasible. Preliminary data suggest higher humeral head iodine concentration may increase risk of avascular necrosis; however, future studies must enroll and follow enough subjects managed with open reduction internal fixation or conservatively for two or more years to provide statistically significant results. Trial Registrations NCT02170545 registered June 23, 2014, ClinicalTrials.gov.

Myocardial iodine concentration measurement using dual-energy computed tomography for the diagnosis of cardiac amyloidosis: a pilot study.

OBJECTIVE: To measure myocardium iodine concentration (MIC) in patients with cardiac amyloidosis (CA) using dual-energy computed tomography (DECT). METHODS: Twenty-two patients with CA, 13 with non-amyloid hypertrophic cardiomyopathies (CH) and 10 control patients were explored with pre-contrast, arterial and 5-minute DECT acquisition (Iomeprol; 1.5 mL/kg). Inter-ventricular septum (IVS) thickness, blood pool iodine concentration (BPIC), MIC (mg/mL), iodine ratio and extra-cellular volume (ECV) were calculated. RESULTS: IVS thickness was significantly (p < 0.001) higher in CA (17 ± 4 mm) and CH (15 ± 3 mm) patients than in control patients (10 ± 1 mm). CA patients exhibited significantly (p < 0.001) higher 5-minute MIC [2.6 (2.3-3.1) mg/mL], 5-minute iodine ratio (0.88 ± 0.12) and ECV (0.56 ± 0.07) than CH [1.7 (1.4-2.2) mg/mL, 0.57 ± 0.07 and 0.36 ± 0.05, respectively] and control patients [1.9 (1.7-2.4) mg/mL, 0.58 ± 0.07 and 0.35 ± 0.04, respectively). CH and control patients exhibited similar values (p = 0.9). The area under the curve of 5-minute iodine ratio for the differential diagnosis of CA from CH patients was 0.99 (0.73-1.0; p = 0.001). With a threshold of 0.65, the sensitivity and specificity of 5-minute iodine ratio were 100% and 92%, respectively. CONCLUSION: Five-minute MIC and iodine ratio were increased in CA patients and exhibited best diagnosis performance to diagnose CA in comparison to other parameters. KEY POINT: • Dual-energy computed tomography can be used to detect cardiac amyloidosis • Five-minute myocardial iodine concentration and iodine ratio increase in cardiac amyloidosis • Among iodine parameters, 5-minute iodine ratio has the best diagnosis performance.

Imaging the renal lesion with dual-energy multidetector CT and multi-energy applications in clinical practice: what can it truly do for you?

OBJECTIVE: Many fortuitously detected renal lesions are incompletely characterised at traditional MDCT imaging, thus posing daily challenges to radiologists and referring physicians. There is burgeoning evidence that dual-energy MDCT and multi-energy applications provide an added value over traditional MDCT imaging in renal lesion characterisation and throughput. This special report gives a vendor-neutral outlook on technical essentials, recommended protocols, high-yield clinical opportunities and reviews radiation dose aspects of dual-energy MDCT imaging and multi-energy applications in renal lesions. In addition to a guide on interpretative traps and emerging problems, we provide an update on new, potential imaging horizons. CONCLUSION: Dual-energy MDCT and multi-energy applications can facilitate the imaging interpretation and throughput of renal lesions. Conjointly with capitalisation on the benefits, familiarity with dual- and multi-energy data sets as well as continuous scrutiny of interpretative traps can be the keys to the successful implementation and enhanced clinical acceptance of this powerful technique in the imaging community. Continuous advances in hardware and computer interfaces are expected to pave the way for the further expansion of the application spectrum. KEY POINTS: • Optimal protocols must be adopted for leveraging dual-energy benefits in renal imaging. • Virtual monochromatic imaging can overcome renal cyst pseudoenhancement. • Iodine maps help to interpret renal lesions incompletely characterised at traditional MDCT. • Interpretative traps need to be weighed-up in dual-energy renal lesions imaging. • Technical advances are expanding the dual-energy applications spectrum for renal lesions imaging.

Dual-Energy MDCT for Imaging the Renal Mass.

OBJECTIVE: The purpose of this article is to provide the reader with a comprehensive overview of dual-energy MDCT applications for imaging renal masses. CONCLUSION: Dual-energy MDCT has the potential to substantially improve the ability of radiologists to diagnose renal masses compared with conventional MDCT, potentially streamlining patients' clinical management.

CT-based synthetic iodine map generation using conditional denoising diffusion probabilistic model.

BACKGROUND: Iodine maps, derived from image-processing of contrast-enhanced dual-energy computed tomography (DECT) scans, highlight the differences in tissue iodine intake. It finds multiple applications in radiology, including vascular imaging, pulmonary evaluation, kidney assessment, and cancer diagnosis. In radiation oncology, it can contribute to designing more accurate and personalized treatment plans. However, DECT scanners are not commonly available in radiation therapy centers. Additionally, the use of iodine contrast agents is not suitable for all patients, especially those allergic to iodine agents, posing further limitations to the accessibility of this technology. PURPOSE: The purpose of this work is to generate synthetic iodine map images from non-contrast single-energy CT (SECT) images using conditional denoising diffusion probabilistic model (DDPM). METHODS: One-hundered twenty-six head-and-neck patients' images were retrospectively investigated in this work. Each patient underwent non-contrast SECT and contrast DECT scans. Ground truth iodine maps were generated from contrast DECT scans using commercial software syngo.via installed in the clinic. A conditional DDPM was implemented in this work to synthesize iodine maps. Three-fold cross-validation was conducted, with each iteration selecting the data from 42 patients as the test dataset and the remainder as the training dataset. Pixel-to-pixel generative adversarial network (GAN) and CycleGAN served as reference methods for evaluating the proposed DDPM method. RESULTS: The accuracy of the proposed DDPM was evaluated using three quantitative metrics: mean absolute error (MAE) (1.039 ± 0.345 mg/mL), structural similarity index measure (SSIM) (0.89 ± 0.10) and peak signal-to-noise ratio (PSNR) (25.4 ± 3.5 db) respectively. Compared to the reference methods, the proposed technique showcased superior performance across the evaluated metrics, further validated by the paired two-tailed t-tests. CONCLUSION: The proposed conditional DDPM framework has demonstrated the feasibility of generating synthetic iodine map images from non-contrast SECT images. This method presents a potential clinical application, which is providing accurate iodine contrast map in instances where only non-contrast SECT is accessible.

What to Expect (and What Not) from Dual-Energy CT Imaging Now and in the Future?

Dual-energy CT (DECT) imaging has broadened the potential of CT imaging by offering multiple postprocessing datasets with a single acquisition at more than one energy level. DECT shows profound capabilities to improve diagnosis based on its superior material differentiation and its quantitative value. However, the potential of dual-energy imaging remains relatively untapped, possibly due to its intricate workflow and the intrinsic technical limitations of DECT. Knowing the clinical advantages of dual-energy imaging and recognizing its limitations and pitfalls is necessary for an appropriate clinical use. The aims of this paper are to review the physical and technical bases of DECT acquisition and analysis, to discuss the advantages and limitations of DECT in different clinical scenarios, to review the technical constraints in material labeling and quantification, and to evaluate the cutting-edge applications of DECT imaging, including artificial intelligence, qualitative and quantitative imaging biomarkers, and DECT-derived radiomics and radiogenomics.

Dual-Energy CT in Oncologic Imaging.

Dual-energy CT (DECT) is an innovative technology that is increasingly widespread in clinical practice. DECT allows for tissue characterization beyond that of conventional CT as imaging is performed using different energy spectra that can help differentiate tissues based on their specific attenuation properties at different X-ray energies. The most employed post-processing applications of DECT include virtual monoenergetic images (VMIs), iodine density maps, virtual non-contrast images (VNC), and virtual non-calcium (VNCa) for bone marrow edema (BME) detection. The diverse array of images obtained through DECT acquisitions offers numerous benefits, including enhanced lesion detection and characterization, precise determination of material composition, decreased iodine dose, and reduced artifacts. These versatile applications play an increasingly significant role in tumor assessment and oncologic imaging, encompassing the diagnosis of primary tumors, local and metastatic staging, post-therapy evaluation, and complication management. This article provides a comprehensive review of the principal applications and post-processing techniques of DECT, with a specific focus on its utility in managing oncologic patients.

Estimation of renal function using iodine maps in dual-energy spectral computed tomography urography: a feasibility and accuracy study.

PURPOSE: To explore the feasibility of measuring glomerular filtration rate (GFR) using iodine maps in dual-energy spectral computed tomography urography (DEsCTU) and correlate them with the estimated GFR (eGFR) based on the equation of creatinine-cystatin C. MATERIALS AND METHODS: One hundred and twenty-eight patients referred for DEsCTU were retrospectively enrolled. The DEsCTU protocol included non-contrast, nephrographic, and excretory phase imaging. The CT-derived GFR was calculated using the above 3-phase iodine maps (CT-GFRiodine) and 120 kVp-like images (CT-GFR120kvp) separately. CT-GFRiodine and CT-GFR120kvp were compared with eGFR using paired t-test, correlation analysis, and Bland-Altman plots. The receiver operating characteristic curves were used to test the renal function diagnostic performance with CT-GFR120kvp and CT-GFRiodine. RESULTS: The difference between eGFR (89.91 ± 18.45 ml·min-1·1.73 m-2) as reference standard and CT-GFRiodine (90.06 ± 20.89 ml·min-1·1.73 m-2) was not statistically significant, showing excellent correlation (r = 0.88, P < 0.001) and agreement (± 19.75 ml·min-1·1.73 m-2, P = 0.866). The correlation between eGFR and CT-GFR120kvp (66.13 ± 19.18 ml·min-1·1.73 m-2) was poor (r = 0.36, P < 0.001), and the agreement was poor (± 40.65 ml·min-1·1.73 m-2, P < 0.001). There were 62 patients with normal renal function and 66 patients with decreased renal function based on eGFR. The CT-GFRiodine had the largest area under the curve (AUC) for distinguishing between normal and decreased renal function (AUC = 0.951). CONCLUSION: The GFR can be calculated accurately using iodine maps in DEsCTU. DEsCTU could be a non-invasive and reliable one-stop-shop imaging technique for evaluating both the urinary tract morphology and renal function.

Whole-lesion iodine map histogram analysis versus single-slice spectral CT parameters for determining novel International Association for the Study of Lung Cancer grade of invasive non-mucinous pulmonary adenocarcinomas.

PURPOSE: The purpose of this study was to evaluate and compare the performances of whole-lesion iodine map histogram analysis to those of single-slice spectral computed tomography (CT) parameters in discriminating between low-to-moderate grade invasive non-mucinous pulmonary adenocarcinoma (INMA) and high-grade INMA according to the novel International Association for the Study of Lung Cancer grading system of INMA. MATERIALS AND METHODS: Sixty-one patients with INMA (34 with low-to-moderate grade [i.e., grade I and grade II] and 27 with high grade [i.e., grade III]) were evaluated with spectral CT. There were 28 men and 33 women, with a mean age of 56.4 ± 10.5 (standard deviation) years (range: 29-78 years). The whole-lesion iodine map histogram parameters (mean, standard deviation, variance, skewness, kurtosis, entropy, and 1st, 10th, 25th, 50th, 75th, 90th, and 99th percentile) were measured for each INMA. In other sessions, by placing regions of interest at representative levels of the tumor and normalizing them, spectral CT parameters (iodine concentration and normalized iodine concentration) were obtained. Discriminating capabilities of spectral CT and histogram parameters were assessed and compared using area under the ROC curve (AUC) and logistic regression models. RESULTS: The 1st, 10th, and 25th percentiles of the iodine map histogram analysis, and iodine concentration and normalized iodine concentration of single-slice spectral CT parameters were significantly different between high-grade and low-to-moderate grade INMAs (P < 0.001 to P = 0.002). The 1st percentile of histogram parameters (AUC, 0.84; 95% confidence interval [CI]: 0.73-0.92) and iodine concentration (AUC, 0.78; 95% CI: 0.66-0.88) from single-slice spectral CT parameters had the best performance for discriminating between high-grade and low-to-moderate grade INMAs. At ROC curve analysis no significant differences in AUC were found between histogram parameters (AUC = 0.86; 95% CI: 0.74-0.93) and spectral CT parameters (AUC = 0.81; 95% CI: 0.74-0.93) (P = 0.60). CONCLUSION: Both whole-lesion iodine map histogram analysis and single-slice spectral CT parameters help discriminate between low-to-moderate grade and high-grade INMAs according to the novel International Association for the Study of Lung Cancer grading system, with no differences in diagnostic performances.

Preoperative prediction of Lauren classification in gastric cancer: a radiomics model based on dual-energy CT iodine map.

OBJECTIVE: To investigate the value of a radiomics model based on dual-energy computed tomography (DECT) venous-phase iodine map (IM) and 120 kVp equivalent mixed images (MIX) in predicting the Lauren classification of gastric cancer. METHODS: A retrospective analysis of 240 patients undergoing preoperative DECT and postoperative pathologically confirmed gastric cancer was done. Training sets (n = 168) and testing sets (n = 72) were randomly assigned with a ratio of 7:3. Patients are divided into intestinal and non-intestinal groups. Traditional features were analyzed by two radiologists, using logistic regression to determine independent predictors for building clinical models. Using the Radiomics software, radiomics features were extracted from the IM and MIX images. ICC and Boruta algorithm were used for dimensionality reduction, and a random forest algorithm was applied to construct the radiomics model. ROC and DCA were used to evaluate the model performance. RESULTS: Gender and maximum tumor thickness were independent predictors of Lauren classification and were used to build a clinical model. Separately establish IM-radiomics (R-IM), mixed radiomics (R-MIX), and combined IM + MIX image radiomics (R-COMB) models. In the training set, each radiomics model performed better than the clinical model, and the R-COMB model showed the best prediction performance (AUC: 0.855). In the testing set also, the R-COMB model had better prediction performance than the clinical model (AUC: 0.802). CONCLUSION: The R-COMB radiomics model based on DECT-IM and 120 kVp equivalent MIX images can effectively be used for preoperative noninvasive prediction of the Lauren classification of gastric cancer. CRITICAL RELEVANCE STATEMENT: The radiomics model based on dual-energy CT can be used for Lauren classification prediction of preoperative gastric cancer and help clinicians formulate individualized treatment plans and assess prognosis.

Dual-energy Computed Tomography Iodine Map for Breast Cancer: Comparison With Dynamic Contrast-enhanced Magnetic Resonance Imaging.

BACKGROUND/AIM: The characteristics of different breast cancers imaged using dual-energy computed tomography (DECT) are unknown. Furthermore, the differences between DECT and magnetic resonance imaging (MRI) in the ability to assess tumor extent have not been clarified. Therefore, this study aimed to evaluate the effectiveness of DECT iodine maps compared to contrast-enhanced MRI in patients with operable breast cancer. PATIENTS AND METHODS: Clinicopathological data from 858 patients with breast cancer who underwent resection after DECT (100/140 kv) and MRI during 2012-2021 were collected. Tumoral iodine concentration (IC; max/Δ) was analyzed from iodine maps. Factors associated with the ability of iodine maps and MRI to predict tumor extent were analyzed with reference to resected specimens' pathological diagnosis. RESULTS: IC parameters varied according to the tumors' histological types and were correlated with the estrogen receptor, histological grade, and Ki-67 labeling index. In 86.2% of patients with invasive carcinoma with intraductal extension, images and resected specimen mapping were matched. Iodine maps were less accurate than MRI in identifying tumor borders in 9.8% and more accurate in 2.1% of patients. The discrepancies in assessing tumor borders between imaging modalities were associated with the tumor's IC parameters and mammary gland status. CONCLUSION: Differences in assessment between DECT and MRI in operable breast cancer are associated with IC parameters and background parenchymal enhancement. Therefore, evaluating tumor extent using DECT considering these characteristics appears to be a feasible approach.

Quantitative dual-energy CT techniques in the abdomen.

Advances in dual-energy CT (DECT) technology and spectral techniques are catalyzing the widespread implementation of this technology across multiple radiology subspecialties. The inclusion of energy- and material-specific datasets has ushered overall improvements in CT image contrast and noise as well as artifacts reduction, leading to considerable progress in radiologists' ability to detect and characterize pathologies in the abdomen. The scope of this article is to provide an overview of various quantitative clinical DECT applications in the abdomen and pelvis. Several of the reviewed applications have not reached mainstream clinical use and are considered investigational. Nonetheless awareness of such applications is critical to having a fully comprehensive knowledge base to DECT and fostering future clinical implementation.

Diagnosis of Serosal Invasion in Gastric Adenocarcinoma by Dual-Energy CT Radiomics: Focusing on Localized Gastric Wall and Peritumoral Radiomics Features.

Objectives: To build a radiomics model and combined model based on dual-energy CT (DECT) for diagnosing serosal invasion in gastric adenocarcinoma. Materials and methods: 231 gastric adenocarcinoma patients were enrolled and randomly divided into a training (n = 132), testing (n = 58), and independent validation (n = 41) cohort. Radiomics features were extracted from the rectangular ROI of the 120-kV equivalent mixed images and iodine map (IM) images in the venous phase of DECT, which was manually delineated perpendicularly to the gastric wall in the deepest location of tumor infiltration, including the peritumoral adipose tissue within 5 mm outside the serosa. The random forest algorithm was used for radiomics model construction. Traditional features were collected by two radiologists. Univariate and multivariate logistic regression was used to construct the clinical model and combined model. The diagnostic efficacy of the models was evaluated using ROC curve analysis and compared using the Delong's test. The calibration curves were used to evaluate the calibration performance of the combined model. Results: Both the radiomics model and combined model showed high efficacy in diagnosing serosal invasion in the training, testing and independent validation cohort, with AUC of 0.90, 0.90, and 0.85 for radiomics model; 0.93, 0.93, and 0.89 for combined model. The combined model outperformed the clinical model (AUC: 0.76, 0.76 and 0.81). Conclusion: The radiomics model and combined model constructed based on tumoral and peritumoral radiomics features derived from DECT showed high diagnostic efficacy for serosal invasion in gastric adenocarcinoma.

Dual-Energy Computed Tomography for Evaluation of Breast Cancer Follow-Ups: Comparison of Virtual Monoenergetic Images and Iodine-Map.

Differentiating tumor tissue from dense breast tissue can be difficult. Dual-energy CT (DECT) could be suitable for making diagnoses at breast cancer follow-ups. This study investigated the contrast in DECT images and iodine maps for patients with breast cancer being followed-up. Chest CT images captured in 2019 were collected. Five cases of metastatic breast cancer in the lungs were analyzed; the contrast-to-noise ratio (for breast tissue and muscle: CNRb and CNRm, respectively), tumor-to-breast mammary gland ratio (T/B), and tumor-to-muscle ratio (T/M) were calculated. For 84 cases of no metastasis, monochromatic spectral and iodine maps were obtained to compare differences under various breast densities using the K-means algorithm. The optimal T/B, T/M, and CNRb (related to mammary glands) were achieved for the 40-keV image. Conversely, CNRm (related to lungs) was better for higher energy. The optimal balance was achieved at 80 keV. T/B, T/M, and CNR were excellent for iodine maps, particularly for density > 25%. In conclusion, energy of 80 keV is the parameter most suitable for observing the breast and lungs simultaneously by using monochromatic spectral images. Adding iodine mapping can be appropriate when a patient's breast density is greater than 25%.

Dual-energy CT: Technical considerations and clinical applications.

Although dual-energy CT was initially described by Hounsfield in 1973, it remains underused in clinical practice. It is therefore important to emphasize the clinical benefits and limitations of this technique. Iodine mapping makes it possible to quantify the uptake of iodine, which is very important in characterizing tumors, lung perfusion, pulmonary nodules, and the tumor response to new treatments. Dual-energy CT also makes it possible to obtain virtual single-energy images and virtual images without iodinated contrast or without calcium, as well as to separate materials such as uric acid or fat and to elaborate hepatic iron overload maps. In this article, we review some of the clinical benefits and technical limitations to improve understanding of dual-energy CT and expand its use in clinical practice.

Added value of iodine-specific imaging and virtual non-contrast imaging for gastrointestinal assessment using dual-energy computed tomography.

Dual-energy computed tomography (DECT) has become increasingly available and can be readily incorporated into clinical practice. Although DECT can provide a wide variety of spectral imaging reconstructions, most clinically valuable information is available from a limited number of standard image reconstructions including virtual non-contrast and iodine overlay. The combination of these standard reconstructions can be used for specific diagnostic tasks that provide added value over traditional CT protocols. In this pictorial essay, the added value of these standard reconstructed images will be demonstrated by case examples for diseases specifically related to the gastrointestinal system.