Dual-energy CT: minimal essentials for radiologists

Dual-Contrast Agent with Nanoparticle and Molecular Components in Photon-Counting Computed Tomography: Assessing Articular Cartilage Health

PURPOSE

Photon-counting detectors (PCDs) are cutting-edge technology that enable spectral computed tomography (CT) imaging with a single scan. Spectral imaging is particularly effective in contrast-enhanced CT (CECT) imaging, especially when multiple contrast agents are utilized, as materials are distinguishable based on their unique X-ray absorption. One application of CECT is joint imaging, where it assesses the structure and composition of articular cartilage soft tissue. This evaluates articular cartilage and reveals compositional changes associated with early-stage osteoarthritis (OA) using a photon-counting detector CT (PCD-CT) technique combined with a dual-contrast agent method.

METHODS

A dual-contrast agent combination was used, consisting of proteoglycan-binding cationic tantalum oxide nanoparticles, developed in our lab, and a commercial non-ionic iodinated iodixanol agent. Ex vivo equine stifle joint cartilage samples (N = 30) were immersed in the contrast agent bath for 96 hours and imaged at multiple timepoints for analysis of proteoglycan, collagen, and water contents as well as collagen orientation, histological scoring, and biomechanical parameters.

RESULTS

By analyzing contrast agent concentrations, the technique provided a simultaneous assessment of the solid constituents and function of cartilage. Contrast agent diffusion depended on contrast agent composition and was significantly different between healthy and early-stage OA groups within 12 hours.

CONCLUSION

The present study shows the promising utility of the dual-contrast PCD-CT technique for articular cartilage assessment and early-stage OA detection.

Spectral CT for non-invasive evaluation of bladder cancer grade

OBJECTIVE

To investigate the potential role of dual-energy spectral computer tomography (CT) quantitative parameters in the definition of bladder cancer (BCa) pathological grading.

METHODS

This retrospective study evaluated the use of spectral CT imaging features for BCa. From 2021 to 2023, 63 patients with histologically-confirmed BCa diagnosis were examined at our Institution. The patients were pathologically divided, following international guidelines, into two groups: low-grade (n = 24) and high-grade urothelial carcinoma group (n = 39). The iodine concentrations (IC), the normalized iodine concentrations (NIC), and the slope of the spectrum curve (SLOPE) were calculated along with the measure of each lesion CT value on the monochromatic image from 40 to 120 keV. The diagnostic performance was assessed by Receiver operator characteristic curve (ROC) analysis.

RESULTS

The high-grade group showed significantly higher mean values of IC, SLOPE, and HU in 40 KeV monoenergetic images (VMI40 HU). AUC values for NIC, SLOPE, IC, and VMI40 HU were 0,677, 0,745, 0,745, and 0,755 respectively. In multivariate logistic regression models with backward stepwise, including all quantitative parameters, only VMI40 HU remained statistically significant to correlate with high-grade tumors.

CONCLUSION

Preliminary data shows that quantitative parameters of dual-energy spectral CT can be helpful to characterize low-grade and high-grade urothelial bladder tumors. The prediction of high-grade BCa with non-invasive methods (e.g. dlCT) can aid in early detection of muscle-invasive and worse prognostic tumors that need more aggressive and timely treatments, personalizing the management on the risk of recurrence.

Influence of object size on beam hardening in dual energy images: A study using different dual-energy CT systems

INTRODUCTION

Dual-energy CT (DECT) enables material decomposition and artifact reduction. However, beam hardening effects, which vary by DECT system and object size, can impact measurement accuracy. This study investigates the influence of beam hardening across various DECT systems and object sizes.

METHODS

A polyethylene Mercury phantom with five diameters (16, 21, 26, 31, and 36 cm) was scanned using three DECT systems: fast kilovolt-switching CT (FKSCT), dual-source CT (DSCT), and dual-layer CT (DLCT). Measurements included CT numbers and standard deviations (SD) of virtual monochromatic images (VMI) at 70 keV for iodine inserts, iodine concentrations, and artifact indices (AI) to assess beam hardening artifacts.

RESULTS

CT numbers and iodine concentrations decreased with increasing phantom size for FKSCT and DLCT, with DLCT showing a larger decrease. DSCT exhibited relatively stable CT numbers and iodine concentrations across all sizes. Noise levels (SD) increased significantly with phantom size for DSCT and DLCT, while FKSCT showed a smaller increase. Beam hardening artifacts, as assessed by AI, were the lowest for FKSCT, while DSCT and DLCT exhibited greater artifacts compared to FKSCT, particularly at larger phantom sizes.

CONCLUSION

The effect of beam hardening varies among DECT systems. FKSCT demonstrated the most stable performance across object sizes, while DSCT and DLCT were more sensitive to object size, affecting measurement accuracy and stability. These findings emphasize the importance of understanding system-specific characteristics to ensure optimal DECT use.

IMPLICATIONS FOR PRACTICE

In clinical practice, when using DECT to measure CT numbers and iodine concentration, it is important to understand that the size of the object may be affected by beam hardening, depending on the DECT system.

Single-Energy, Dual-Energy, and Photon-Counting Computed Tomography of the Liver: Current Development and Clinical Utility for the Assessment of Focal Liver Lesions

ABSTRACT

Advancements in computed tomography (CT) technology, particularly the emergence of dual-energy CT (DE-CT) and photon-counting detector CT (PCD-CT), can improve detection, characterization, and treatment monitoring of focal liver lesions. DE-CT, through its ability to differentiate tissues with similar densities and produce diverse datasets, has enhanced lesion visibility and diagnostic precision. PCD-CT further advances imaging with superior spatial resolution and material decomposition capabilities, offering potential for complex diagnostic scenarios. This review aimed to highlight the role of CT in hepatic imaging and its application to focal liver lesions.DE-CT improves lesion detectability using low-energy virtual monochromatic images, which enhance iodine contrast and reduce radiation and contrast agent doses. It also facilitates treatment response evaluation after locoregional therapies for hepatocellular carcinoma by quantifying biomarkers, such as the extracellular volume fraction. This review underscores the transformative impact of DE-CT and PCD-CT on liver imaging, emphasizing their complementary roles alongside magnetic resonance imaging. These innovations have paved the way for more precise diagnostics, improved treatment planning, and enhanced patient outcomes in the management of liver diseases.

The role of dual-energy computed tomography (DECT) in emergency radiology: a visual guide to advanced diagnostics

Dual-energy computed tomography (DECT) has become an essential tool in emergency radiology, significantly enhancing diagnostic capabilities for a variety of acute conditions. By utilising two distinct X-ray energy spectra, DECT differentiates materials based on their attenuation properties, providing detailed insights into tissue composition and pathology. In emergency settings, DECT is used in thoracic imaging for the detection of pulmonary embolism, in abdominal imaging to enhance the diagnosis and characterisation of conditions such as pancreatitis, appendicitis, gastrointestinal bleeding, and bowel ischaemia and in the genitourinary system for identifying kidney stones, pyelonephritis, and urinary bleeding. In neuroimaging, DECT enables image optimisation through virtual monochromatic images and the reduction of metal artifacts. It helps in the differential diagnosis of haemorrhage versus tumour-related haemorrhage, haemorrhage versus contrast extravasation, and in the dating of vertebral collapse. DECT offers several advantages, including enhanced visualisation, the potential to reduce radiation exposure and contrast medium, and improved diagnostic accuracy across a wide range of conditions. However, its routine clinical adoption is still evolving due to challenges such as limited availability, cost, and the need for specialised training. This pictorial essay aims to encourage the broader integration of DECT into emergency imaging protocols by showcasing its clinical applications and benefits.

Contrast Volume Reduction in Oncologic Body Imaging Using Dual-Energy CT: A Comparison with Single-Energy CT

Background/Objectives: To evaluate the feasibility of reducing contrast volume in oncologic body imaging using dual-energy CT (DECT) by (1) identifying the optimal virtual monochromatic imaging (VMI) reconstruction using DECT and (2) comparing DECT performed with reduced iodinated contrast media (ICM) volume to single-energy CT (SECT) performed with standard ICM volume. Methods: In this retrospective study, we quantitatively and qualitatively compared the image quality of 35 thoracoabdominopelvic DECT across 9 different virtual monoenergetic image (VMI) levels (from 40 to 80 keV) using a reduced volume of ICM (0.3 gI/kg of body weight) to determine the optimal keV reconstruction level. Out of these 35 patients, 20 had previously performed SECT with standard ICM volume (0.3 gI/kg of body weight + 9 gI), enabling protocol comparison. The qualitative analysis included overall image quality, noise, and contrast enhancement by two radiologists. Quantitative analysis included contrast enhancement measurements, contrast-to-noise ratio, and signal-to-noise ratio of the liver parenchyma and the portal vein. ANOVA was used to identify the optimal VMI level reconstruction, while t-tests and paired t-tests were used to compare both protocols. Results: VMI60 keV provided the highest overall image quality score. DECT with reduced ICM volume demonstrated higher contrast enhancement and lower noise than SECT with standard ICM volume (p < 0.001). No statistical difference was found in the overall image quality between the two protocols (p = 0.290). Conclusions: VMI60 keV with reduced contrast volume provides higher contrast and lower noise than SECT at a standard contrast volume. DECT using a reduced ICM volume is the technique of choice for oncologic body CT.

Advancements in Computed Tomography Angiography for Pulmonary Embolism Assessment

Pulmonary embolism (PE) is a critical condition stemming from venous thromboembolism, with potentially fatal outcomes. Computed tomography pulmonary angiography (CTPA) serves as the gold standard for diagnosing PE, offering unparalleled diagnostic accuracy, accessibility, and speed. Recent innovations, such as spectral CT systems and artificial intelligence (AI)-driven algorithms, have enhanced the diagnostic and prognostic capabilities of CTPA, enabling precise anatomical and functional assessments. This review highlights these technological advancements and their clinical implications.

Dual-phase computed tomography imaging for lung function assessment in patients with early-stage non-small cell lung cancer

Background

Early-stage non-small cell lung cancer (NSCLC) requires accurate preoperative lung function assessment, but traditional tests have limitations in evaluating regional lung function. This study aimed to evaluate the efficacy of dual-phase computed tomography (CT) imaging for preoperative lung function assessment in patients with early-stage NSCLC.

Methods

Sixty patients (28 men and 32 women; mean age 55.47±10.30 years) with early-stage NSCLC were prospectively included in this study. The data utilized in this study were retrospectively analyzed from prospectively collected clinical data. Each patient underwent dual-phase (inspiratory and respiratory) CT using dual-energy computed tomography (DECT) before surgery. The DECT parameters, including volume, iodine content, and iodine concentration (iodine content per unit volume) for each lung and lobe in both phases, were collected by a dual-energy workstation and the eXamine software. Semi-automatic lobe segmentation was achieved through the DE Lung Isolation function in the eXamine. Pulmonary function tests (PFTs) before surgery were conducted as the reference standard to assess the accuracy of DECT in lung function evaluation. The correlation between DECT parameters and PFT metrics was analyzed using Spearman correlation.

Results

DECT can achieve stable and reliable semi-automatic lung lobe segmentation. The median iodine concentration in each lobe showed that the left lung had slightly lower values than the right, with the left upper lobe having lower concentrations than the left lower lobe. In the right lung, the middle lobe had the lowest concentration, while the lower lobe had the highest. The Spearman correlation analysis indicated that multiple parameters from DECT correlated with lung function indices measured by PFT (P<0.05). Dual-phase functional CT imaging can accurately measure lung function.

Conclusions

Dual-phase CT imaging provides a comprehensive and precise preoperative lung function evaluation of patients who underwent operations for early-stage NSCLC.

Exploring bias in spectral CT material decomposition: a simulation-based approach

Introduction -

Computed tomography (CT) imaging has seen significant advancements with the introduction of spectral CT, which improves material differentiation by acquiring images at multiple energy levels. Photon-counting CT (PCCT) is an emerging technique to implement spectral CT with photon counting detectors that may discriminate detected photon energies to different energy bins. Material differentiation is achieved by decomposing the acquired data into two-material models such as brain/bone or brain/iodine. However, such decomposition is susceptible to bias due to inaccurate physical modeling. In this study, we aim to study the relationship between the material decomposition bias and the energy thresholds used in PCCT, under ideal, noiseless models.

Methods -

A projection-based material decomposition model was used to directly decompose projection data. Bias simulation was performed using a Shepp-Logan phantom with brain/bone and brain/iodine as basis materials. X-ray spectra were generated using a fixed 10 keV threshold and a varying threshold sampled from 20 to 90 keV, with extra sampling points around iodine's k-edge. Virtual monoenergetic images (VMIs) at 60 keV and 140 keV were analyzed to evaluate bias for each material and material pair.

Results -

Lower energy thresholds (<40 keV) introduced a larger bias in material decomposition, with peaks observed between 30 and 40 keV, particularly around the k-edge of iodine. The bias generally decreased with increasing thresholds above 50 keV, especially for non-basis materials. This trend was consistent across brain/bone and brain/iodine bases and for both 60 and 140 keV VMIs.

Conclusion -

Energy thresholds significantly affect the accuracy of projection-based material decomposition in PCCT. Greater differences between thresholds lead to reduced decomposition bias. Future research should incorporate non-ideal detector responses and noise, as well as explore image-domain decomposition and real phantom studies with possible translation to improve patient care.

Stereotactic arrhythmia radioablation for ventricular tachycardia: a review of clinical trials and emerging roles of imaging

Ventricular tachycardia (VT) is a severe arrhythmia commonly treated with implantable cardioverter defibrillators, antiarrhythmic drugs and catheter ablation (CA). Although CA is effective in reducing recurrent VT, its impact on survival remains uncertain, especially in patients with extensive scarring. Stereotactic arrhythmia radioablation (STAR) has emerged as a novel treatment for VT in patients unresponsive to CA, leveraging techniques from stereotactic body radiation therapy used in cancer treatments. Recent clinical trials and case series have demonstrated the short-term efficacy and safety of STAR, although long-term outcomes remain unclear. Imaging techniques, such as electroanatomical mapping, contrast-enhanced magnetic resonance imaging and nuclear imaging, play a crucial role in treatment planning by identifying VT substrates and guiding target delineation. However, challenges persist owing to the complex anatomy and variability in target volume definitions. Advances in imaging and artificial intelligence are expected to improve the precision and efficacy of STAR. The exact mechanisms underlying the antiarrhythmic effects of STAR, including potential fibrosis and improvement in cardiac conduction, are still being explored. Despite its potential, STAR should be cautiously applied in prospective clinical trials, with a focus on optimizing dose delivery and understanding long-term outcomes. Collaborative efforts are necessary to standardize treatment strategies and enhance the quality of life for patients with refractory VT.

The Impact of Weighting Factors on Dual-Energy Computed Tomography Image Quality in Non-Contrast Head Examinations: Phantom and Patient Study

Background: This study aims to evaluate the impact of various weighting factors (WFs) on the quality of weighted average (WA) dual-energy computed tomography (DECT) non-contrast brain images and to determine the optimal WF value. Because they simulate standard CT images, 0.4-WA reconstructions are routinely used. Methods: In the initial phase of the research, quantitative and qualitative analyses of WA DECT images of an anthropomorphic head phantom, utilizing WFs ranging from 0 to 1 in 0.1 increments, were conducted. Based on the phantom study findings, WFs of 0.4, 0.6, and 0.8 were chosen for patient analyses, which were identically carried out on 85 patients who underwent non-contrast head DECT. Three radiologists performed subjective phantom and patient analyses. Results: Quantitative phantom image analysis revealed the best gray-to-white matter contrast-to-noise ratio (CNR) at the highest WFs and minimal noise artifacts at the lowest WF values. However, the WA reconstructions were deemed non-diagnostic by all three readers. Two readers found 0.6-WA patient reconstructions significantly superior to 0.4-WA images (p < 0.001), while reader 1 found them to be equally good (p = 0.871). All readers agreed that 0.8-WA images exhibited the lowest image quality. Conclusions: In conclusion, 0.6-WA reconstructions demonstrated superior image quality over 0.4-WA and are recommended for routine non-contrast brain DECT.

Dual-energy CT in head and neck applications

Dual-energy CT (DECT), also known as spectral CT, has advanced diagnostic capabilities in head and neck pathologies beyond those of conventional single-energy CT (SECT). By having images at two distinct energy levels, DECT generates virtual monoenergetic images (VMIs), iodine maps, and quantitative features such as iodine concentration (IC) and spectral Hounsfield unit attenuation curves (SHUAC), which leads to enhancing tissue characterization, reducing artifacts, and differentiating head and neck pathologies. This review highlights DECT's applications in evaluating head and neck squamous cell carcinoma (SCC), thyroid cartilage invasion, cervical lymph node metastasis, radiation therapy planning, post-treatment assessment, and role in other head and neck conditions, such as infection and sialolithiasis. Additionally, it explores emerging applications of DECT in radiomics and artificial intelligence. The review also discusses about integrating DECT into clinical practice requires overcoming workflow challenges and ensuring radiologist proficiency with its diverse image reconstructions. As DECT technology evolves, its integration promises to further enhance the efficacy of managing head and neck pathologies.

Additional value of dynamic iodine concentration derived from dual-energy CT in larynx preservation decision following neoadjuvant chemotherapy

AIM

To develop a larynx preservation (LP) score model to predict laryngectomy-free survival (LFS) in advanced laryngeal squamous-cell carcinoma (LSCC) with morphological response to neoadjuvant chemotherapy (NAC).

MATERIALS AND METHODS

In this retrospective study, patients with advanced LSCC were included. All patients were classified into NAC response and non-response groups according RECIST. Arterial and venous phases of standardized iodine concentrations of dual-energy CT were measured in the response group, and the rate of iodine concentration change (ΔNIC%) was calculated by (NICpost-NICpre)/NICpre ×100%. Clinical outcomes between the two groups were analyzed using chi-square test. Univariable and multivariable cox regression analyses were performed to evaluate the independent predictors of LFS in the response group. A risk score was developed based on the hazard ratios from the multivariable analysis.

RESULTS

A total of 146 patients were included. 86 patients achieved a response. T stage, N status, and ΔNAIC% were independent predictors of LFS for LSCC patients with NAC morphological response (all, p<0.001). Based on these factors, the established LP risk score model demonstrated an AUC of 0.877 for the 1-year LFS rate and 0.950 for the 2-year LFS rate. Patients with a score ≥6 had a worse LFS (p<0.001) and OS (p=0.001).

CONCLUSION

A prediction risk score incorporating T stage, N status, and ΔNAIC% shows good predictive effectiveness for LFS in advanced LSCC with morphological response to NAC. It can prevent high-risk patients in the NAC response group from undergoing salvage laryngectomy and improve patient prognosis.

Next-Gen Poly(ε-Caprolactone) Scaffolds: Non-Destructive In Vivo Monitoring and Accelerated Biodegradation

Poly(ɛ-caprolactone) (PCL) is a biocompatible, biodegradable, and highly mechanically resilient FDA-approved material (for specific biomedical applications, e.g. as drug delivery devices, in sutures, or as an adhesion barrier), rendering it a promising candidate to serve bone tissue engineering. However, in vivo monitoring of PCL-based implants, as well as biodegradable implants in general, and their degradation profiles pose a significant challenge, hindering further development in the tissue engineering field and subsequent clinical adoption. To address this, photo-cross-linkable mechanically resilient PCL networks are developed and functionalized with a radiopaque monomer, 5-acrylamido-2,4,6-triiodoisophthalic acid (AATIPA), to enable non-destructive in vivo monitoring of PCL-based implants. The covalent incorporation of AATIPA into the crosslinked PCL networks does not significantly affect their crosslinking kinetics, mechanical properties, or thermal properties, but it increases their hydrolysis rate and radiopacity. Complex and porous 3D designs of radiopaque PCL networks can be effectively monitored in vivo. This work paves the way toward non-invasive monitoring of in vivo degradation profiles and early detection of potential implant malfunctions.

Non-contrast spectral CT vs chemical-shift MRI in discriminating lipid-poor adrenal lesions

OBJECTIVES

To compare the diagnostic performance of conventional non-contrast CT, dual-energy spectral CT, and chemical-shift MRI (CS-MRI) in discriminating lipid-poor adenomas (> 10-HU on non-contrast CT) from non-adenomas.

METHODS

A total of 110 patients (69 men; 41 women; mean age 66.5 ± 13.4 years) with 80 lipid-poor adenomas and 30 non-adenomas who underwent non-contrast dual-layer spectral CT and CS-MRI were retrospectively identified. For each lesion, non-contrast attenuation on conventional 120-kVp images, ΔHU-index ([attenuation difference between virtual monoenergetic 140-keV and 40-keV images]/conventional attenuation × 100), and signal intensity index (SI-index) were quantified. Each parameter was compared between adenomas and non-adenomas using the Mann-Whitney U-test. The area under the receiver operating characteristic curve (AUC) and sensitivity to achieve > 95% specificity for adenoma diagnosis were determined.

RESULTS

Conventional non-contrast attenuation was lower in adenomas than in non-adenomas (22.4 ± 8.6 HU vs 32.8 ± 48.5 HU), whereas ΔHU-index (148.0 ± 103.2 vs 19.4 ± 25.8) and SI-index (41.6 ± 19.6 vs 4.2 ± 10.2) were higher in adenomas (all, p < 0.001). ΔHU-index showed superior performance to conventional non-contrast attenuation (AUC: 0.919 [95% CI: 0.852-0.963] vs 0.791 [95% CI: 0.703-0.863]; sensitivity: 75.0% [60/80] vs 27.5% [22/80], both p < 0.001), and near equivalent to SI-index (AUC: 0.952 [95% CI: 0.894-0.984], sensitivity 85.0% [68/80], both p > 0.05). Both the ΔHU-index and SI-index provided a sensitivity of 96.0% (48/50) for hypoattenuating adenomas (≤ 25 HU). For hyperattenuating (> 25 HU) adenomas, SI-index showed higher sensitivity than ΔHU-index (66.7% [20/30] vs 40.0% [12/30], p = 0.022).

CONCLUSIONS

Non-contrast spectral CT and CS-MRI outperformed conventional non-contrast CT in distinguishing lipid-poor adenomas from non-adenomas. While CS-MRI demonstrated superior sensitivity for adenomas measuring > 25 HU, non-contrast spectral CT provided high discriminative values for adenomas measuring ≤ 25 HU.

CLINICAL RELEVANCE STATEMENT

Spectral attenuation analysis improves the diagnostic performance of non-contrast CT in discriminating lipid-poor adrenal adenomas, potentially serving as an alternative to CS-MRI and obviating the necessity for additional diagnostic workup in indeterminate adrenal incidentalomas, particularly for lesions measuring ≤ 25 HU.

KEY POINTS

Incidental adrenal lesion detection has increased as abdominal CT use has become more frequent. Non-contrast spectral CT and CS-MRI differentiated lipid-poor adenomas from non-adenomas better than conventional non-contrast CT. For lesions measuring ≤ 25 HU, spectral CT may obviate the need for additional evaluation.

Multi-DECT Image-based Intratumoral and Peritumoral Radiomics for Preoperative Prediction of Muscle Invasion in Bladder Cancer

OBJECTIVES

To assess the predictive value of intratumoral and peritumoral radiomics based on Dual-energy CT urography (DECTU) multi-images for preoperatively predicting the muscle invasion status of bladder cancer (BCa).

MATERIAL AND METHODS

This retrospective analysis involved 202 BCa patients who underwent DECTU. DECTU-derived quantitative parameters were identified as risk factors through stepwise regression analysis to construct a DECT model. The radiomic features from the intratumoral and 3 mm outward peritumoral regions were extracted from the 120 kVp-like, 40 keV, 100 keV, and iodine-based material-decomposition (IMD) images in the venous-phase and were screened using Mann-Whitney U test, Spearman correlation analysis, and LASSO. Radiomics models were developed using the Multilayer Perceptron for the intratumoral, peritumoral and intra- and peritumoral (IntraPeri) regions. Subsequently, a nomogram was created by integrating the multi-image IntraPeri radiomics and DECT model. Model performance was evaluated using area-under-the-curve (AUC), accuracy, sensitivity, and specificity.

RESULTS

Normalized iodine concentration (NIC) was identified as an independent predictor for the DECT model. The IntraPeri model demonstrated superior performance compared to the intratumoral and peritumoral models both in 40 keV (0.830 vs. 0.766 vs. 0.763) and IMD images (0.881 vs. 0.840 vs. 0.821) in the test cohort. In the test cohort, the nomogram exhibited the best predictability (AUC=0.886, accuracy=0.836, sensitivity=0.737, and specificity=0.881), outperformed the DECT model (AUC=0.763, accuracy=0.754, sensitivity=0.632, and specificity=0.810) in predicting muscle invasion status of BCa with a statistically significant difference (p < 0.05).

CONCLUSION

The nomogram, incorporating IntraPeri radiomics and NIC, serves as a valuable and non-invasive tool for preoperatively assessing the muscle invasion status of BCa.

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

PURPOSE

To 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.

METHOD

A 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.

RESULTS

Subjective 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.

CONCLUSION

DECT 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.

Non-unique water and contrast agent solutions in dual-energy CT

The goal of this work is to study occurrences of non-unique solutions in dual-energy CT (DECT) for objects containing water and a contrast agent. Previous studies of the Jacobian of nonlinear systems identified that a vanishing Jacobian determinant indicates the existence of multiple solutions to the system. Vanishing Jacobian determinants are identified for DECT setups by simulating intensity data for practical thickness ranges of water and contrast agent. Once existence is identified, non-unique solutions are found by simulating scan data and finding intensity contours with that intersect multiple times. With this process non-unique solutions are found for DECT setups scanning iodine and gadolinium, including setups using tube potentials in practical ranges. Non-unique solutions demonstrate a large range of differences and can result in significant discrepancies between recovered and true material mapping.

Spectral imaging and analysis of monophasic CT angiography to assess infarct core and penumbra in acute stroke

Acute stroke imaging includes native CT, CT-angiography (CTA), and CT-perfusion (CTP). CTP assesses the irreversibly damaged infarct core (IC), and the potentially salvageable penumbra (PEN) and distinguishes these from areas of healthy parenchyma (HA). However, it requires additional contrast agent and radiation. Spectral-CT (SCT) enables spectral imaging like e.g., iodine-density imaging, and we evaluated its potential in estimating IC and PEN using monophasic CTA data only. We analysed 28 patients with mediainfarction. CTP-analysis derived areas of IC, PEN and HA on infarction side, as well as their healthy hemisphere's counterparts were transferred to CTA as Region of interest (ROI). Spectral measurements included Hounsfield-Units in monoenergetic maps (MonoE) at 40 keV, 70 keV, and 120 keV, plus iodine-density (ID) and electron-density (ED) values, totalling 2970 values. Unilateral absolute values and ratios to the healthy counterparts were evaluated. Visual infarct delineation on each map was also rated. In all spectral maps, the infarct areas could be distinguished from the healthy counterpart by absolute values (p < 0.05). IC, PEN and HA could be distinguished from each other by absolute values (p < 0.05) (except for ED), and by the ratio-value formed to the contralateral side (p < 0.05). Detection of IC and PEN were best possible in ID (IC (AUC = 0.9999, p < 0.0001); PEN (AUC = 0.9745, p < 0.0001)) and MonoE40 (IC (AUC = 0.9963, p < 0.0001); PEN (AUC = 0.9622, p < 0.0001)). Differentiation of IC and PEN was also best in ID (AUC = 0.93, p < 0.0001) and MonoE40 (AUC = 0.80, p < 0.0001). Similarly, visual delineation was best too in ID and MonoE40. Accordingly, IC and PEN can be detected and differentiated in monophasic CTA by using SCT-derived spectral maps like ID or MonoE40.

Head and Neck Squamous Cell Carcinoma: Insights from Dual-Energy Computed Tomography (DECT)

Head and neck cancer represents the seventh most common neoplasm worldwide, with squamous cell carcinoma being the most represented histologic variant. The rising incidence of the neoplastic pathology of this district, coupled with the drastic changes in its epidemiology over the past decades, have posed significant challenges to physicians worldwide in terms of diagnosis, prognosis, and treatment. In order to meet these challenges, a considerable amount of effort has been spent by the authors of the recent literature to explore new technologies and their possible employment for the better diagnostic and prognostic definition of head and neck squamous cell carcinoma (HNSCC). Among these technologies, a growing interest has been gathering around the possible applications of dual-energy computed tomography (DECT) in head and neck pathology. Dual-energy computed tomography (DECT) utilizes two distinct X-ray energy spectra to obtain two datasets in a single scan, allowing for material differentiation based on unique attenuation profiles. DECT offers key benefits such as enhanced contrast resolution, reduced beam-hardening artifacts, and precise iodine quantification through monochromatic reconstructions. It also creates material decomposition images, like iodine maps, aiding in tumor characterization and therapy assessment. This paper aims to summarize recent findings on the use of DECT in HNSCC, providing a comprehensive overview to aid further research and exploration in the field.

Discrimination of thrombus types in ischemic stroke using Dual-Energy CT

OBJECTIVE

This study explores the clinical utility of dual-energy computed tomography (DECT) in discriminating thrombus types in ischemic stroke.

METHODS

Patients with acute ischemic stroke who underwent brain DECT non-contrast scanning and brain CT perfusion (CTP) before thrombectomy were included, and the thrombus composition was analyzed by postoperative pathology. DECT data was conducted to reconstruct polychromatic images and effective atomic number images. Computed tomography (CT) values, effective atomic numbers, and spectral curve slopes of the thrombus were measured and calculated. Thrombus attenuation increase was obtained from CTP data. Parameters were compared between red blood cell (RBC)-dominant thrombi and fibrin/platelet (F/P)-dominant thrombi. Thresholds, sensitivity, specificity, and area under the curve (AUC) were analyzed to distinguish these thrombi. The associations between DECT parameters and proportion of RBCs were analyzed by Spearman's correlation.

RESULTS

Pathological analysis of 42 enrolled patients revealed 24 cases of RBC-dominant thrombi and 18 cases of F/P-dominant thrombi. Effective atomic numbers, spectral curve slopes, and polychromatic images CT values were significantly higher in the RBC-dominant thrombi group compared with the F/P-dominant thrombi group. Although the average thrombus attenuation increase was greater in the F/P-dominant thrombi group, this difference was not statistically significant. Among the DECT parameters, polychromatic images CT values had the greatest AUC at 0.924 (0.848-0.999) for discriminating RBC-dominant and F/P-dominant thrombi, with a threshold of 59 HU, sensitivity of 79.2 %, and specificity of 94.4 %. The combined diagnostic AUC reached 0.938 (0.863-1.012), with 87.5 % sensitivity and 94.4 % specificity. DECT polychromatic images CT values, effective atomic numbers, and spectral curve slopes were significantly correlated with proportion of RBCs (r = 0.673, 0.574, and 0.571, all p < 0.01).

CONCLUSION

DECT non-contrast scan parameters are associated with thrombus composition, which could be effective in distinguishing between RBC-dominant and F/P-dominant thrombi.

Dual-Energy Computed Tomography Virtual Noncalcium Imaging of Intracranial Arteries in Acute Ischemic Stroke: Differentiation Between Acute Thrombus and Calcification

OBJECTIVE

Hyperdense artery sign (HAS) on noncontrast brain computed tomography (CT) indicates an acute thrombus within the cerebral artery. It is a valuable imaging biomarker for diagnosing large-vessel occlusion; however, its identification may be challenging with the presence of vascular calcification. Dual-energy CT virtual noncalcium (VNCa) imaging using a 3-material decomposition algorithm is helpful for differentiating between calcification and hemorrhage. This study aimed to clarify the potential of VNCa imaging for differentiating HAS from vascular calcification.

METHODS

Patients with acute ischemic stroke and large-vessel occlusion identified on MR angiography, who also underwent noncontrast dual-energy CT, were included. The 80 kV/Sn 140 kV mixed images, with a weighting factor of 0.4, were considered 120 kVp-equivalent images. Postprocessing using a 3-material decomposition algorithm to differentiate between calcium (Ca), cerebrospinal fluid, and hemorrhage was performed via a commercially available 3-dimensional workstation. A mixed image, VNCa image, color-coded Ca image, and color-coded Ca image with VNCa image overlay (color-coded Ca-overlay image) were obtained, and axial reconstruction with a 1-mm slice thickness was performed for each image type. Two experienced neuroradiologists conducted imaging evaluations in consensus.

RESULTS

Thirty-four patients (mean age, 76.0 years; 21 male and 13 female patients) were included. The mixed and VNCa images revealed an HAS (indicating an acute clot) corresponding to the large-vessel occlusion site in 30 patients. Among them, the VNCa and color-coded Ca-overlay images enabled clear differentiation between the acute thrombus and adjacent vessel wall calcification in 5 patients. Among the other 4 patients, the VNCa, Ca-overlay, and Ca images identified calcified cerebral emboli in the M1 segment in 1 patient. For the other 3 patients, no high attenuation corresponding to magnetic resonance angiography findings was observed in any of the mixed, VNCa, Ca-overlay, or Ca images.

CONCLUSIONS

VNCa and color-coded Ca-overlay images obtained via dual-energy brain CT enabled differentiation of acute thrombus from vessel wall calcification and calcified cerebral emboli in patients with acute ischemic stroke.

Multi-energy CT and iodinated contrast

Spectral CT acquires images with the emission or detection of two separate energy spectra. This enables material decomposition due to the photoelectric effect (prevalent in low-energy photons) and Compton scattering (prevalent in high-energy photons). Iodine and other materials with high atomic numbers appear more hyperdense on low-energy monoenergetic images because of the direct relation between the photoelectric effect and the Z value. Given the way iodine behaves on spectral maps, radiologists can optimise the use of contrast media in these CTs, thus allowing lower doses of radiation and lower volumes of contrast media while achieving the same CT values and even enabling lower contrast flow rates, which is especially helpful in patients with poor vascular access. Moreover, in suboptimal diagnostic cases caused by poor contrast opacification, the resolution can be improved, thus avoiding the need to repeat the study.

Chances and challenges of photon-counting CT in musculoskeletal imaging

In musculoskeletal imaging, CT is used in a wide range of indications, either alone or in a synergistic approach with MRI. While MRI is the preferred modality for the assessment of soft tissues and bone marrow, CT excels in the imaging of high-contrast structures, such as mineralized tissue. Additionally, the introduction of dual-energy CT in clinical practice two decades ago opened the door for spectral imaging applications. Recently, the advent of photon-counting detectors (PCDs) has further advanced the potential of CT, at least in theory. Compared to conventional energy-integrating detectors (EIDs), PCDs provide superior spatial resolution, reduced noise, and intrinsic spectral imaging capabilities. This review briefly describes the technical advantages of PCDs. For each technical feature, the corresponding applications in musculoskeletal imaging will be discussed, including high-spatial resolution imaging for the assessment of bone and crystal deposits, low-dose applications such as whole-body CT, as well as spectral imaging applications including the characterization of crystal deposits and imaging of metal hardware. Finally, we will highlight the potential of PCD-CT in emerging applications, underscoring the need for further preclinical and clinical validation to unleash its full clinical potential.

Comparison of Conventional and Virtual Non-contrast Abdominal Images Using the Third-Generation Dual-Source Dual-Energy Computed Tomography

PURPOSE

To determine the efficacy and safety of virtual unenhanced imaging by comparing the attenuation values of virtual and true unenhanced images acquired using third-generation dual-source dual-energy computed tomography (dsDECT).

METHODS

Single-energy non-contrast and dual-energy arterial and venous phase images of 97 patients who underwent triphasic abdominal computed tomography (CT) were included in this retrospective study. Virtual unenhanced images were generated for the arterial (a) and venous (v) phases using two dsDECT algorithms. The attenuation values were measured on the true and virtual unenhanced images of the liver, spleen, kidney, gallbladder, paraspinal muscle, aorta, subcutaneous fat, retroperitoneal fat, and renal cysts.

RESULTS

A statistically significant difference was observed between the attenuation values ​​of true and virtual unenhanced images for all tissues (p < 0.001-0.025), except the venous phase virtual unenhanced images of the kidney, renal cysts, and gallbladder (p = 0.061-0.325). The proportion of cases with differences of ≥ 10 Hounsfield unit (HU) in the attenuation values between the virtual and true unenhanced images ranged from 3% to 8% for renal parenchyma, renal cysts, and gallbladder using this algorithm; however, this proportion was up to 90% for adipose tissue. No significant correlation was observed between the body mass index and attenuation differences between the true and virtual unenhanced images, except for those of the aorta and paraspinal muscle.

CONCLUSION

Virtual unenhanced images acquired using third-generation dsDECT cannot replace true unenhanced images in clinical practice owing to the difference between the attenuation values and variability of attenuation between true and virtual unenhanced images.

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.

Photon-Counting Computed Tomography for Microstructural Imaging of Bone and Joints

PURPOSE OF REVIEW

Recently, photon-counting computed tomography (PCCT) has been introduced in clinical research and diagnostics. This review describes the technological advances and provides an overview of recent applications with a focus on imaging of bone.

RECENT FINDINGS

PCCT is a full-body scanner with short scanning times that provides better spatial and spectral resolution than conventional energy-integrating-detector CT (EID-CT), along with an up to 50% reduced radiation dose. It can be used to quantify bone mineral density, to perform bone microstructural analyses and to assess cartilage quality with adequate precision and accuracy. Using a virtual monoenergetic image reconstruction, metal artefacts can be greatly reduced when imaging bone-implant interfaces. Current PCCT systems do not allow spectral imaging in ultra-high-resolution (UHR) mode. Given its improved resolution, reduced noise and spectral imaging capabilities PCCT has diagnostic capacities in both qualitative and quantitative imaging that outperform those of conventional CT. Clinical use in monitoring bone health has already been demonstrated. The full potential of PCCT systems will be unlocked when UHR spectral imaging becomes available.

Comparison of preoperative diagnostic performance between dual-energy CT, conventional CT, and MRI in endometrial cancer

Purpose

To compare the diagnostic performance of virtual monoenergetic imaging (VMI), computed tomography (CT), and magnetic resonance imaging (MRI) in patients with endometrial cancer (EC).

Material and methods

This retrospective study analysed 45 EC patients (mean age: 62 years, range: 44-84 years) undergoing contrast-enhanced CT with dual-energy CT (DECT) and MRI between September 2021 and October 2022. Dual-energy CT generated conventional CT (C-CT) and 40 keV VMI. Quantitative analysis compared contrast-to-noise ratio (CNR) of tumour to myometrium between C-CT and VMI. Qualitative assessment by 5 radiologists compared C-CT, VMI, and MRI for myometrial invasion (MI), cervical invasion, and lymph node metastasis. Sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) were calculated and compared for each diagnostic parameter.

Results

Virtual monoenergetic imaging showed significantly higher CNR than C-CT (p < 0.001) and a higher sensitivity for MI than C-CT (p = 0.027) and MRI (p = 0.011) but lower specificity than MRI (p = 0.018). C-CT had a higher sensitivity and AUC for cervical invasion than MRI (p = 0.018 and 0.004, respectively).

Conclusions

The study found no significant superiority of MRI over CT across all diagnostic parameters. VMI demonstrated heightened sensitivity for MI, and C-CT showed greater sensitivity and AUC for cervical invasion than MRI. This suggests that combining VMI with C-CT holds promise as a comprehensive preoperative staging tool for EC when MRI cannot be performed.

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.

Influencing factors and improvement methods of coronary artery plaque evaluation in CT

Accurate evaluation of the nature and composition of coronary plaque involves clinical follow-up and prognosis. Coronary CT angiography is the most commonly non-invasive method for plaque evaluation, however, the qualitative and quantitative evaluation of plaque based on CT value is inaccurate, due to the influence of luminal attenuation, tube voltage, parameter setting and the subjectivity.

Utility of Dual-Energy Computed Tomography in Clinical Conundra

Advancing medical technology revolutionizes our ability to diagnose various disease processes. Conventional Single-Energy Computed Tomography (SECT) has multiple inherent limitations for providing definite diagnoses in certain clinical contexts. Dual-Energy Computed Tomography (DECT) has been in use since 2006 and has constantly evolved providing various applications to assist radiologists in reaching certain diagnoses SECT is rather unable to identify. DECT may also complement the role of SECT by supporting radiologists to confidently make diagnoses in certain clinically challenging scenarios. In this review article, we briefly describe the principles of X-ray attenuation. We detail principles for DECT and describe multiple systems associated with this technology. We describe various DECT techniques and algorithms including virtual monoenergetic imaging (VMI), virtual non-contrast (VNC) imaging, Iodine quantification techniques including Iodine overlay map (IOM), and two- and three-material decomposition algorithms that can be utilized to demonstrate a multitude of pathologies. Lastly, we provide our readers commentary on examples pertaining to the practical implementation of DECT's diverse techniques in the Gastrointestinal, Genitourinary, Biliary, Musculoskeletal, and Neuroradiology systems.

A Comprehensive Study on the Diagnostic Value of Multi-Slice Computed Tomography for Peripancreatic Infection in Elderly With Severe Acute Pancreatitis

BACKGROUND

This study investigated the diagnostic efficacy of multi-slice spiral computed tomography (MSCT) perfusion imaging in evaluating peripancreatic infection in elderly patients with severe acute pancreatitis (SAP).

METHODS

A retrospective analysis was conducted on the clinical data of 110 elderly SAP patients treated at our hospital from March 2018 to August 2019. The study correlated MSCT perfusion imaging characteristics with peripancreatic infection in elderly SAP patients. Additionally, receiver operating characteristic (ROC) curves were constructed to assess the diagnostic performance of MSCT perfusion imaging parameters in evaluating peripancreatic infection in elderly SAP patients.

RESULTS

The results indicated that among all 110 elderly SAP patients, the incidence rate of peripancreatic infection was 20.91%, with a mortality rate of 0.91%. MSCT perfusion imaging revealed that after peripancreatic infection in elderly SAP patients, there was a decrease in pancreatic density, local enlargement of the pancreas, blurring of the pancreatic margins, and associated ascites. Compression/narrowing/occlusion of the splenic vein was observed in 22 patients, compression/narrowing/occlusion of the superior mesenteric vein in 17 patients, thickening/thrombosis of the portal vein in 19 patients, and collateral circulation in 21 patients. Compared to elderly SAP patients without peripancreatic infection, those with the infection showed prolonged peak times, reduced peak heights, and decreased blood flow. ROC analysis indicated that the combination of the three parameters (peak time, peak height, and blood flow) had higher specificity and area under the curve (AUC) than single parameters, with no significant difference in sensitivity between the combination and single parameters.

CONCLUSIONS

In conclusion, combining the three key MSCT perfusion imaging parameters (peak time, peak height, and blood flow) can significantly enhance the predictive efficacy for the risk of peripancreatic infection in elderly SAP patients.

Material decomposition with a prototype photon-counting detector CT system: expanding a stoichiometric dual-energy CT method via energy bin optimization and K-edge imaging

Objective.Computed tomography (CT) has advanced since its inception, with breakthroughs such as dual-energy CT (DECT), which extracts additional information by acquiring two sets of data at different energies. As high-flux photon-counting detectors (PCDs) become available, PCD-CT is also becoming a reality. PCD-CT can acquire multi-energy data sets in a single scan by spectrally binning the incident x-ray beam. With this, K-edge imaging becomes possible, allowing high atomic number (high-Z) contrast materials to be distinguished and quantified. In this study, we demonstrated that DECT methods can be converted to PCD-CT systems by extending the method of Bourqueet al(2014). We optimized the energy bins of the PCD for this purpose and expanded the capabilities by employing K-edge subtraction imaging to separate a high-atomic number contrast material.Approach.The method decomposes materials into their effective atomic number (Zeff) and electron density relative to water (ρe). The model was calibrated and evaluated using tissue-equivalent materials from the RMI Gammex electron density phantom with knownρevalues and elemental compositions. TheoreticalZeffvalues were found for the appropriate energy ranges using the elemental composition of the materials.Zeffvaried slightly with energy but was considered a systematic error. Anex vivobovine tissue sample was decomposed to evaluate the model further and was injected with gold chloride to demonstrate the separation of a K-edge contrast agent.Main results.The mean root mean squared percent errors on the extractedZeffandρefor PCD-CT were 0.76% and 0.72%, respectively and 1.77% and 1.98% for DECT. The tissue types in theex vivobovine tissue sample were also correctly identified after decomposition. Additionally, gold chloride was separated from theex vivotissue sample with K-edge imaging.Significance.PCD-CT offers the ability to employ DECT material decomposition methods, along with providing additional capabilities such as K-edge imaging.

Differentiation of Hamartomas and Malignant Lung Tumors in Single-Phased Dual-Energy Computed Tomography

This study investigated the efficacy of single-phase dual-energy CT (DECT) in differentiating pulmonary hamartomas from malignant lung lesions using virtual non-contrast (VNC), iodine, and fat quantification. Forty-six patients with 47 pulmonary lesions (mean age: 65.2 ± 12.1 years; hamartomas-to-malignant lesions = 22:25; male: 67%) underwent portal venous DECT using histology, PET-CT and follow-up CTs as a reference. Quantitative parameters such as VNC, fat fraction, iodine density and CT mixed values were statistically analyzed. Significant differences were found in fat fractions (hamartomas: 48.9%; malignancies: 22.9%; p ≤ 0.0001) and VNC HU values (hamartomas: -20.5 HU; malignancies: 17.8 HU; p ≤ 0.0001), with hamartomas having higher fat content and lower VNC HU values than malignancies. CT mixed values also differed significantly (p ≤ 0.0001), but iodine density showed no significant differences. ROC analysis favored the fat fraction (AUC = 96.4%; sensitivity: 100%) over the VNC, CT mixed value and iodine density for differentiation. The study concludes that the DECT-based fat fraction is superior to the single-energy CT in differentiating between incidental pulmonary hamartomas and malignant lesions, while post-contrast iodine density is ineffective for differentiation.

Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review

The accurate and timely assessment of lymph node involvement is paramount in the management of patients with malignant tumors, owing to its direct correlation with cancer staging, therapeutic strategy formulation, and prognostication. Dual-energy computed tomography (DECT), as a burgeoning imaging modality, has shown promising results in the diagnosis and prediction of preoperative metastatic lymph nodes in recent years. This article aims to explore the application of DECT in identifying metastatic lymph nodes (LNs) across various cancer types, including but not limited to thyroid carcinoma (focusing on papillary thyroid carcinoma), lung cancer, and colorectal cancer. Through this narrative review, we aim to elucidate the clinical relevance and utility of DECT in the detection and predictive assessment of lymph node metastasis in malignant tumors, thereby contributing to the broader academic discourse in oncologic radiology and diagnostic precision.

The role of iodinated contrast media in computed tomography structured Reporting and Data Systems (RADS): a narrative review

Background and Objective

In recent years, there has been a large-scale dissemination of guidelines in radiology in the form of Reporting & Data Systems (RADS). The use of iodinated contrast media (ICM) has a fundamental role in enhancing the diagnostic capabilities of computed tomography (CT) but poses certain risks. The scope of the present review is to summarize the current role of ICM only in clinical reporting guidelines for CT that have adopted the "RADS" approach, focusing on three specific questions per each RADS: (I) what is the scope of the scoring system; (II) how is ICM used in the scoring system; (III) what is the impact of ICM enhancement on the scoring.

Methods

We analyzed the original articles for each of the latest versions of RADS that can be used in CT [PubMed articles between January, 2005 and March, 2023 in English and American College of Radiology (ACR) official website].

Key Content and Findings

We found 14 RADS suitable for use in CT out of 28 RADS described in the literature. Four RADS were validated by the ACR: Colonography-RADS (C-RADS), Liver Imaging-RADS (LI-RADS), Lung CT Screening-RADS (Lung-RADS), and Neck Imaging-RADS (NI-RADS). One RADS was validated by the ACR in collaboration with other cardiovascular scientific societies: Coronary Artery Disease-RADS 2.0 (CAD-RADS). Nine RADS were proposed by other scientific groups: Bone Tumor Imaging-RADS (BTI-RADS), Bone‑RADS, Coronary Artery Calcium Data & Reporting System (CAC-DRS), Coronavirus Disease 2019 Imaging-RADS (COVID-RADS), COVID-19-RADS (CO-RADS), Interstitial Lung Fibrosis Imaging-RADS (ILF-RADS), Lung-RADS (LU-RADS), Node-RADS, and Viral Pneumonia Imaging-RADS (VP-RADS).

Conclusions

This overview suggests that ICM is not strictly necessary for the study of bones and calcifications (CAC-DRS, BTI-RADS, Bone-RADS), lung parenchyma (Lung-RADS, LU-RADS, COVID-RADS, CO-RADS, VP-RADS and ILF-RADS), and in CT colonography (C-RADS). On the other hand, ICM plays a key role in CT angiography (CAD-RADS), in the study of liver parenchyma (LI-RADS), and in the evaluation of soft tissues and lymph nodes (NI-RADS, Node-RADS). Future studies are needed in order to evaluate the impact of the new iodinated and non-iodinate contrast media, artificial intelligence tools and dual energy CT in the assignment of RADS scores.

The value of dual-energy computed tomography (DECT) in the diagnosis of urinary calculi: a systematic review and meta-analysis of retrospective studies

Objective

Dual-energy computed tomography (DECT) imaging technology opens a new idea and method for analyzing stone composition, which can obtain several quantitative parameters reflecting tissue-related information and energy images different from traditional images. However, the application of DECT in diagnosing urinary calculi remains unknown. This study aims to evaluate the value of DECT in diagnosing urinary calculi by meta-analysis.

Methods

PubMed, EMBASE, Web of Science, and the Cochrane Library were searched to articles published from the establishment of the databases to April 18, 2023. We reviewed the articles on the diagnosis of urinary calculi detected by DECT, established standards, screened the articles, and extracted data. Two researchers carried out data extraction and the Cohen's unweighted kappa was estimated for inter-investigator reliability. The quality of the literature was evaluated by the diagnostic test accuracy quality evaluation tool (QUADAS-2). The heterogeneity and threshold effects were analyzed by Meta-Disc 1.4 software, and the combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic ratio were calculated. The combined receiver-operating characteristic (ROC) curve was drawn, and the value of DECT in the diagnosis of urinary calculi was evaluated by the area under the curve (AUC). The meta-analysis was registered at PROSPERO (CRD42023418204).

Results

One thousand and twenty-seven stones were detected in 1,223 samples from 10 diagnostic tests. The analyzed kappa alternated between 0.78-0.85 for the document's retrieval and detection procedure. The sensitivity of DECT in the diagnosis of urinary calculi was 0.94 (95% CI [0.92-0.96]). The positive likelihood ratio (PLR) of DECT in the diagnosis of urinary stones was 0.91 (95% CI [0.88-0.94]), and the negative likelihood ratio (NLR) was 0.08 (95% CI [0.05-0.11]). The specificity of DECT for detecting urinary calculi was 0.91 (95% CI [0.88-0.94]). The area under the curve of the summary receiver operator characteristic (SROC) was 0.9875. The sensitivity of dual-energy CT in the diagnosis of urinary calculi diameter <3 mm was 0.94 (95% CI [0.91-0.96]). The PLR of DECT in the diagnosis of urinary stones diameter <3 mm was 10.79 (95% CI [5.25 to 22.17]), and the NLR was 0.08 (95% CI [0.05-0.13]). The specificity of DECT for detecting urinary calculi <3 mm was 0.91 (95% CI [0.87-0.94]). The SROC was 0.9772.

Conclusion

The DECT has noble application value in detecting urinary calculi.

Effect of iodine concentration reduction by comparison of virtual monoenergetic image quality with dual-energy computed tomography

This study aimed to evaluate the image quality of virtual monoenergetic images (VMIs) with tube voltage modulation in pediatric abdominal computed tomography (CT) examination and to determine the effect of decreasing contrast agent concentration. Using a 1-year old pediatric phantom, five contrast agent concentration diluent tubes of 100%, 80%, 60%, 40%, and 20% of the same concentration as the average Hounsfield unit (HU) in the descending aorta were inserted, and the mixed image and VMIs (40, 60, and 80 keV) acquired using dual-energy CT were compared with single-energy CT (SECT) images. For quantitative evaluation, the HU and coefficient of variation (COV) of each image were compared and analyzed. The analysis revealed that the HU of the 40 keV VMIs, acquired with a tube voltage of 70 kV and 100% contrast agent concentration, was 61% higher than that of the SECT image. The results showed that SECT had the lowest COV among all contrast agent concentration and tube voltage combinations, while the 40 keV image acquired at 70 kV had the second-lowest COV value. The HU of the 40 keV image acquired at 70 kV at a contrast agent concentration of 100% was 9% higher than that of SECT at 80% concentration. This study confirms that 40 keV VMIs are more useful than SECT images for vascular diagnosis with contrast in pediatric abdominal CT examinations and that a 20% reduction in contrast agent concentration can reduce the risk of contrast agent concentration-induced nephrotoxicity in pediatric patients by increasing the subjective acceptability of image quality for diagnosis.

Comparison of radiomics models and dual-energy material decomposition to decipher abdominal lymphoma in contrast-enhanced CT

PURPOSE

The radiologists' workload is increasing, and computational imaging techniques may have the potential to identify visually unequivocal lesions, so that the radiologist can focus on equivocal and critical cases. The purpose of this study was to assess radiomics versus dual-energy CT (DECT) material decomposition to objectively distinguish visually unequivocal abdominal lymphoma and benign lymph nodes.

METHODS

Retrospectively, 72 patients [m, 47; age, 63.5 (27-87) years] with nodal lymphoma (n = 27) or benign abdominal lymph nodes (n = 45) who had contrast-enhanced abdominal DECT between 06/2015 and 07/2019 were included. Three lymph nodes per patient were manually segmented to extract radiomics features and DECT material decomposition values. We used intra-class correlation analysis, Pearson correlation and LASSO to stratify a robust and non-redundant feature subset. Independent train and test data were applied on a pool of four machine learning models. Performance and permutation-based feature importance was assessed to increase the interpretability and allow for comparison of the models. Top performing models were compared by the DeLong test.

RESULTS

About 38% (19/50) and 36% (8/22) of the train and test set patients had abdominal lymphoma. Clearer entity clusters were seen in t-SNE plots using a combination of DECT and radiomics features compared to DECT features only. Top model performances of AUC = 0.763 (CI = 0.435-0.923) were achieved for the DECT cohort and AUC = 1.000 (CI = 1.000-1.000) for the radiomics feature cohort to stratify visually unequivocal lymphomatous lymph nodes. The performance of the radiomics model was significantly (p = 0.011, DeLong) superior to the DECT model.

CONCLUSIONS

Radiomics may have the potential to objectively stratify visually unequivocal nodal lymphoma versus benign lymph nodes. Radiomics seems superior to spectral DECT material decomposition in this use case. Therefore, artificial intelligence methodologies may not be restricted to centers with DECT equipment.

Virtual monochromatic images of dual-energy CT as an alternative to single-energy CT: performance comparison using a detectability index for different acquisition techniques

OBJECTIVES

To investigate the performance of virtual monochromatic (VM) images with the same dose and iodine contrast as those for single-energy (SE) images using five dual-energy (DE) scanners with DE techniques: two generations of fast kV switching (FKS), two generations of dual source (DS), and one split filter (SF).

METHODS

A water-bath phantom with a diameter of 300 mm, which contains one rod-shaped phantom made of a material equivalent to soft-tissue and two rod-shaped phantoms made of diluted iodine (2 and 12 mg/mL), was scanned using both SE (120, 100, and 80 kV) and DE techniques with the same CT dose index in each scanner. The VM energy at which the CT number of the iodine rod is closest to that of each SE tube voltage was determined as the equivalent energy (Eeq). A detectability index (d') was calculated from the noise power spectrum, the task transfer functions, and a task function corresponding to each rod. The percentage of the d' value of the VM image to that of the corresponding SE image was calculated for performance comparison.

RESULTS

The average percentages of d' of FKS1, FKS2, DS1, DS2, and SF were 84.6%, 96.2%, 94.3%, 107%, and 104% for 120 kV-Eeq; 75.9%, 91.2%, 88.2%, 99.2%, and 82.6% for 100 kV-Eeq; 71.6%, 88.9%, 82.6%, 85.2%, and 62.3% for 80 kV-Eeq, respectively.

CONCLUSION

The performance of VM images was on the whole inferior to that of SE images especially at low equivalent energy levels, depending on the DE techniques and their generations.

KEY POINTS

• This study evaluated the performance of VM images with the same dose and iodine contrast as those for SE images using five DE scanners. • The performance of VM images varied with the DE techniques and their generations and was mostly inferior at low equivalent energy levels. • The results highlight the importance of distribution of available dose over the two energy levels and spectral separation for the performance improvement of VM images.

Virtual monoenergetic dual-layer dual-energy CT images in colorectal cancer: CT diagnosis could be improved?

PURPOSE

To compare conventional CT images and virtual monoenergetic images (VMI) at dual-layer dual-energy CT (dlDECT) in patients with colorectal cancer (CRC) through quantitative analysis and to investigate the added value of VMI.

MATERIAL AND METHODS

Sixty-six consecutive patients with histologically documented CRC and available VMI reconstructions were retrospectively investigated. Subsequently, forty-two patients, without any colonic disease at colonoscopy, were selected as control group. Conventional CT images and VMI reconstructions at energy levels ranging from 40 (VMI40) to 100 keV (VMI100) in 10 keV increments, were obtained from the late arterial phase. First, signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were obtained to select the best VMI reconstruction. Finally, the diagnostic accuracy of conventional CT and VMI40 in late arterial phase was evaluated.

RESULTS

On quantitative analysis, SNR and CNR were higher for VMI40 (19.5 ± 7.7 and 11.8 ± 6.2, respectively) with statistically significant differences compared to conventional CT (P < 0.05) and all the other VMI reconstructions (P < 0.05), except for VMI50 (P > 0.05). The addition of VMI40 to conventional CT images significantly improved the area under the curve (AUC) for the diagnosis of CRC, increasing it from 0.875 to 0.943 for reader 1 (P < 0.05) and from 0.916 to 0.954 for reader 2 (P < 0.05). The improvement was greater in the less experienced radiologist (0.068) compared to the more experienced one (0.037).

CONCLUSION

VMI40 has showed the highest quantitative image parameters. Furthermore, the use of VMI40 can lead to a significant improvement in the diagnostic performance for detecting CRC.

Virtual Non-Contrast Spectral CT in Renal Masses: Is It Time to Discard Conventional Unenhanced Phase?

Dual-layer Dual-Energy CT (dl-DECT) allows one to create virtual non-contrast (VNC) reconstructions from contrast-enhanced CT scans, with a consequent decrease of the radiation dose. This study aims to assess the reliability of VNC for the diagnostic evaluation of renal masses in comparison with true non-contrast (TNC) images. The study cohort included 100 renal masses in 40 patients who underwent dl-DECT between June and December 2021. Attenuation values and standard deviations were assessed through the drawing of regions of interest on TNC and VNC images reconstructed from corticomedullary and nephrographic phases. A Wilcoxon signed-rank test was performed in order to assess equivalence of data and Spearman's Rho correlation coefficient to evaluate correlations between each parameter. The diagnostic accuracy of VNC was estimated through the performance of receiver operating characteristic (ROC) curve analysis. Differences between attenuation values were, respectively, 74%, 18%, 5% and 3% (TNC-VNCcort), and 74%, 15%, 9% and 2% (TNC-VNCneph). The Wilcoxon signed-rank test demonstrated the equivalence of attenuation values between the TNC and VNC images. The diagnostic performance of VNC images in the depiction of kidney simple cysts remains high compared to TNC (VNCcort-AUC: 0.896; VNCneph-AUC: 0.901, TNC-AUC: 0.903). In conclusion, quantitative analysis of attenuation values showed a strong agreement between VNC and TNC images in the evaluation of renal masses.

Advances for Pulmonary Functional Imaging: Dual-Energy Computed Tomography for Pulmonary Functional Imaging

Dual-energy computed tomography (DECT) can improve the differentiation of material by using two different X-ray energy spectra, and may provide new imaging techniques to diagnostic radiology to overcome the limitations of conventional CT in characterizing tissue. Some techniques have used dual-energy imaging, which mainly includes dual-sourced, rapid kVp switching, dual-layer detectors, and split-filter imaging. In iodine images, images of the lung's perfused blood volume (PBV) based on DECT have been applied in patients with pulmonary embolism to obtain both images of the PE occluding the pulmonary artery and the consequent perfusion defects in the lung's parenchyma. PBV images of the lung also have the potential to indicate the severity of PE, including chronic thromboembolic pulmonary hypertension. Virtual monochromatic imaging can improve the accuracy of diagnosing pulmonary vascular diseases by optimizing kiloelectronvolt settings for various purposes. Iodine images also could provide a new approach in the area of thoracic oncology, for example, for the characterization of pulmonary nodules and mediastinal lymph nodes. DECT-based lung ventilation imaging is also available with noble gases with high atomic numbers, such as xenon, which is similar to iodine. A ventilation map of the lung can be used to image various pulmonary diseases such as chronic obstructive pulmonary disease.

[Accuracy of Virtual Non-contrast Image Reconstruction Using Material Decomposition for Fast kV-switching Dual-energy CT]

PURPOSE

Dual-energy computed tomography (DECT) system can generate virtual non-contrast (VNC) images. Although several reconstruction algorithms are defined, there are not many researches using deep learning image reconstruction (DLIR) algorithm. In this study, we evaluated the accuracy of the VNC image reconstruction under various conditions using DLIR algorithm.

METHODS

At first, each iodine insert with variable concentrations (2.0, 5.0, 10.0, 15.0 mg/ml) or diameters (2.0, 5.0, 10.0, 28.5 mm), or mixed insert including blood-mimicking material with iodine (iodine concentrations: 2.0, 4.0 mg/ml) was put in the center of the multi-energy CT phantom (Gammex, USA). This phantom was placed in the isocenter of DECT, and it scanned and reconstructed the VNC images. In addition, the VNC images were reconstructed with various display field of view (DFOV) sizes (240, 350 mm) or reconstruction algorithms (filtered back projection, advanced statistical iterative reconstruction, deep learning image reconstruction) for each iodine diameter. Attenuation values of these images (CT_VNC) were measured and assessed by placing a circular region of interest (ROI) on each insert.

RESULTS

CT_VNC form iodine inserts increased with iodine concentration became lower, whereas CT_VNC form blood plus iodine inserts were stable regardless of low iodine concentration. As iodine diameter became smaller, CT_VNC increased remarkably. CT_VNC remained steady even though reconstruction parameters were varied.

CONCLUSION

In our study, the VNC image reconstruction using DLIR algorithm was affected by various conditions such as iodine concentration and size. In particular, its accuracy was reduced by the size of target.

Diagnosis of an Acute Anterior Wall Infarction in Dual-Energy CT

Due to its high morbidity and mortality, myocardial infarction is the leading cause of death worldwide. Against this background, rapid diagnosis is of immense importance. Especially in case of an atypical course, the correct diagnosis may be delayed and thus lead to increased mortality rates. In this report, we present a complex case of acute coronary syndrome. A triple-rule-out CT examination was performed in dual-energy CT (DECT) mode. While pulmonary artery embolism and aortic dissection could be ruled out with conventional CT series, the presence of anterior wall infarction was only detectable on DECT reconstructions. Subsequently, adequate and rapid therapy was then initiated leading to survival of the patient.

Pros and Cons of Dual-Energy CT Systems: "One Does Not Fit All"

Dual-energy computed tomography (DECT) uses different energy spectrum x-ray beams for differentiating materials with similar attenuation at a certain energy. Compared with single-energy CT, it provides images with better diagnostic performance and a potential reduction of contrast agent and radiation doses. There are different commercially available DECT technologies, with machines that may display two x-ray sources and two detectors, a single source capable of fast switching between two energy levels, a specialized detector capable of acquiring high- and low-energy data sets, and a filter splitting the beam into high- and low-energy beams at the output. Sequential acquisition at different tube voltages is an alternative approach. This narrative review describes the DECT technique using a Q&A format and visual representations. Physical concepts, parameters influencing image quality, postprocessing methods, applicability in daily routine workflow, and radiation considerations are discussed. Differences between scanners are described, regarding design, image quality variabilities, and their advantages and limitations. Additionally, current clinical applications are listed, and future perspectives for spectral CT imaging are addressed. Acknowledging the strengths and weaknesses of different DECT scanners is important, as these could be adapted to each patient, clinical scenario, and financial capability. This technology is undoubtedly valuable and will certainly keep improving.

An introduction to photon-counting detector CT (PCD CT) for radiologists

The basic performance of photon-counting detector computed tomography (PCD CT) is superior to conventional CT (energy-integrating detector CT: EID CT) because its spatial- and contrast resolution of soft tissues is higher, and artifacts are reduced. Because the X-ray photon energy separation is better with PCD CT than conventional EID-based dual-energy CT, it has the potential to improve virtual monochromatic- and virtual non-contrast images, material decomposition including quantification of the iodine distribution, and K-edge imaging. Therefore, its clinical applicability may be increased. Although the image quality of PCD CT scans is superior to that of EID CT currently, further improvement may be possible. The introduction of iterative image reconstruction and reconstruction with deep convolutional neural networks will be useful.

Dual-energy computed tomography of the abdomen: A reliable trouble-shooter

Dual-energy computed tomography (CT) systems have undergone significant evolution and advancements in technology since they came into clinical practice in 2006. The basic principle of dual-energy is comparing the attenuation of different materials when exposed to high and low energy levels. In this article, we provide a brief overview of the basics of dual-energy CT systems, a pictorial review of commonly encountered abdominal conditions, and its role as a trouble-shooter in various diagnostic difficulties.

Imaging biomarkers to stratify lymph node metastases in abdominal CT - Is radiomics superior to dual-energy material decomposition?

PURPOSE

To assess the potential of radiomic features in comparison to dual-energy CT (DECT) material decomposition to objectively stratify abdominal lymph node metastases.

MATERIALS AND METHODS

In this retrospective study, we included 81 patients (m, 57; median age, 65 (interquartile range, 58.7-73.3) years) with either lymph node metastases (n = 36) or benign lymph nodes (n = 45) who underwent contrast-enhanced abdominal DECT between 06/2015-07/2019. All malignant lymph nodes were classified as unequivocal according to RECIST criteria and confirmed by histopathology, PET-CT or follow-up imaging. Three investigators segmented lymph nodes to extract DECT and radiomics features. Intra-class correlation analysis was applied to stratify a robust feature subset with further feature reduction by Pearson correlation analysis and LASSO. Independent training and testing datasets were applied on four different machine learning models. We calculated the performance metrics and permutation-based feature importance values to increase interpretability of the models. DeLong test was used to compare the top performing models.

RESULTS

Distance matrices and t-SNE plots revealed clearer clusters using a combination of DECT and radiomic features compared to DECT features only. Feature reduction by LASSO excluded all DECT features of the combined feature cohort. The top performing radiomic features model (AUC = 1.000; F1 = 1.000; precision = 1.000; Random Forest) was significantly superior to the top performing DECT features model (AUC = 0.942; F1 = 0.762; precision = 0.800; Stochastic Gradient Boosting) (DeLong < 0.001).

CONCLUSION

Imaging biomarkers have the potential to stratify unequivocal lymph node metastases. Radiomics models were superior to DECT material decomposition and may serve as a support tool to facilitate stratification of abdominal lymph node metastases.

Dual-energy CT based material decomposition to differentiate intrahepatic cholangiocarcinoma from hepatocellular carcinoma

PURPOSE

To assess the potential of material decomposition in dual-energy CT (DECT) to differentiate intrahepatic cholangiocarcinoma (iCCA) from hepatocellular carcinoma (HCC).

METHOD

In this retrospective study, we included 94 patients (26 female (27.7 %), median age 64.5 (interquartile range 55.5-74.5) years) with either iCCA or HCC who underwent abdominal contrast-enhanced DECT in arterial phase. To test for differences between iCCA (n = 47) and HCC (n = 47), we evaluated mean attenuation and DECT material density values including iodine density (ID), normalized iodine uptake (NIU), fat fraction, and lesion-to-liver parenchyma ratio. Histopathology served as reference standard for all lesions. We used univariate logistic regression models for the outcome iCCA versus HCC. ROC curve analysis was applied to assess discriminative ability of the model. Model accuracy was evaluated by calculating the Brier score. Youden index was applied to establish thresholds to differentiate between iCCA and HCC.

RESULTS

Comparison of quantitative image parameters revealed significant differences between iCCA and HCC for ID (1.6 ± 0.5 mg/ml vs 2.8 ± 0.8 mg/ml, p < 0.001), NIU (14.5 ± 4.8 vs 24.8 ± 10.3, p < 0.001), attenuation (41.9 ± 10.1 HU vs 47.9 ± 8.9 HU, p = 0.003), and fat fraction (12.0 ± 7.8 % vs 9.0 ± 6.4 %, p = 0.045). ROC curve analysis revealed highest ability to differentiate iCCA from HCC for ID (AUC = 0.93, 95 % CI 0.89-0.98). For ID, an optimal threshold of 2.33 mg/dl was determined to discriminate between iCCA and HCC (sensitivity 89.4 %, specificity 76.6 %).

CONCLUSIONS

DECT-based iodine quantification can serve as a tool for the differentiation of iCCA and HCC in contrast-enhanced CT. ID yielded the highest diagnostic performance and may assist in clinical routine CT diagnostics.