Accuracy of contrast-enhanced dual-energy MDCT for the assessment of iodine uptake in renal lesions

Iodine Density Threshold to Distinguish Between Enhancing and Nonenhancing Renal Lesions With Dual-Layer Dual-Energy CT

PURPOSE

This study aimed to determine the optimal threshold iodine density to distinguish enhancing and nonenhancing renal masses with dual-layer dual-energy CT (dlDECT).

METHODS

In this retrospective, HIPAA-compliant, institutional review board-approved study, 383 consecutive renal mass dlDECT studies from September 5, 2018, through December 15, 2022, were reviewed for enhancing solid renal masses with ≥∆20 HU. Studies with simple cysts in the same interval served as controls. Lesion ROI HU measurements on unenhanced and nephrographic phases and ROI iodine density measurements of each lesion and the abdominal aorta for normalization were recorded. The mean lesion HU values and absolute and normalized iodine densities were compared with enhancing and nonenhancing renal lesions using a two-sample t test. The diagnostic accuracy of iodine thresholds was assessed by calculating sensitivity and specificity, with receiver operating characteristic curve and AUC analysis.

RESULTS

There were 38 enhancing and 39 nonenhancing renal lesions. The mean (standard deviation [SD]) ∆HU was 73.5 (38.7) and 3.9 (5.1) HU for enhancing and nonenhancing lesions, respectively. The mean absolute iodine density was significantly different for enhancing and nonenhancing lesions (3.2 [1.7] mg/mL and 0.20 [0.22] mg/mL, respectively; P < 0.0001). Normalized mean iodine density was significantly different for enhancing and nonenhancing lesions (0.62 [0.33] mg/mL and 0.04 [0.04] mg/mL, respectively; P < 0.0001). The optimal absolute iodine density threshold of 0.70 mg/mL (AUC, 0.999) and normalized iodine density threshold of 0.11 mg/mL (AUC, 0.999) were 100% sensitive and 97.4% specific for discriminating enhancing and nonenhancing renal lesions.

CONCLUSIONS

This study provides absolute and normalized iodine density thresholds to distinguish enhancing and nonenhancing renal lesions with high sensitivity and specificity using dlDECT.

Iodine quantification of renal lesions: Preliminary results using spectral-based material extraction on photon-counting CT

Objectives

To assess the range of quantitative iodine values in renal cysts (RC) (with a few renal neoplasms [RNs] as a comparison) to develop an expected range of values for RC that can be used in future studies for their differentiation.

Material and Methods

Consecutive patients (n = 140) with renal lesions who had undergone abdominal examination on a clinical photon-counting computed tomography (PCCT) were retrospectively included. Automated iodine quantification maps were reconstructed, and region of interest (ROI) measurements of iodine concentration (IC) (mg/cm3) were performed on whole renal lesions. In addition, for heterogeneous lesions, a secondary ROI was placed on the area most suspicious for malignancy. The discriminatory values of minimum, maximum, mean, and standard deviation for IC were compared using simple logistic regression and receiver operating characteristic curves (area under the curve [AUC]).

Results

A total of 259 renal lesions (243 RC and 16 RN) were analyzed. There were significant differences between RC and RN for all IC measures with the best-performing metrics being mean and maximum IC of the entire lesion ROI (AUC 0.912 and 0.917, respectively) but also mean and minimum IC of the most suspicious area in heterogeneous lesions (AUC 0.983 and 0.992, respectively). Most RC fell within a range of low measured iodine values although a few had higher values.

Conclusion

Automated iodine quantification maps reconstructed from clinical PCCT have a high diagnostic ability to differentiate RCs and neoplasms. The data from this pilot study can be used to help establish quantitative values for clinical differentiation of renal lesions.

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.

Constrained one-step material decomposition reconstruction of head CT data from a silicon photon-counting prototype

BACKGROUND

Spectral CT material decomposition provides quantitative information but is challenged by the instability of the inversion into basis materials. We have previously proposed the constrained One-Step Spectral CT Image Reconstruction (cOSSCIR) algorithm to stabilize the material decomposition inversion by directly estimating basis material images from spectral CT data. cOSSCIR was previously investigated on phantom data.

PURPOSE

This study investigates the performance of cOSSCIR using head CT datasets acquired on a clinical photon-counting CT (PCCT) prototype. This is the first investigation of cOSSCIR for large-scale, anatomically complex, clinical PCCT data. The cOSSCIR decomposition is preceded by a spectrum estimation and nonlinear counts correction calibration step to address nonideal detector effects.

METHODS

Head CT data were acquired on an early prototype clinical PCCT system using an edge-on silicon detector with eight energy bins. Calibration data of a step wedge phantom were also acquired and used to train a spectral model to account for the source spectrum and detector spectral response, and also to train a nonlinear counts correction model to account for pulse pileup effects. The cOSSCIR algorithm optimized the bone and adipose basis images directly from the photon counts data, while placing a grouped total variation (TV) constraint on the basis images. For comparison, basis images were also reconstructed by a two-step projection-domain approach of Maximum Likelihood Estimation (MLE) for decomposing basis sinograms, followed by filtered backprojection (MLE + FBP) or a TV minimization algorithm (MLE + TVmin ) to reconstruct basis images. We hypothesize that the cOSSCIR approach will provide a more stable inversion into basis images compared to two-step approaches. To investigate this hypothesis, the noise standard deviation in bone and soft-tissue regions of interest (ROIs) in the reconstructed images were compared between cOSSCIR and the two-step methods for a range of regularization constraint settings.

RESULTS

cOSSCIR reduced the noise standard deviation in the basis images by a factor of two to six compared to that of MLE + TVmin , when both algorithms were constrained to produce images with the same TV. The cOSSCIR images demonstrated qualitatively improved spatial resolution and depiction of fine anatomical detail. The MLE + TVmin algorithm resulted in lower noise standard deviation than cOSSCIR for the virtual monoenergetic images (VMIs) at higher energy levels and constraint settings, while the cOSSCIR VMIs resulted in lower noise standard deviation at lower energy levels and overall higher qualitative spatial resolution. There were no statistically significant differences in the mean values within the bone region of images reconstructed by the studied algorithms. There were statistically significant differences in the mean values within the soft-tissue region of the reconstructed images, with cOSSCIR producing mean values closer to the expected values.

CONCLUSIONS

The cOSSCIR algorithm, combined with our previously proposed spectral model estimation and nonlinear counts correction method, successfully estimated bone and adipose basis images from high resolution, large-scale patient data from a clinical PCCT prototype. The cOSSCIR basis images were able to depict fine anatomical details with a factor of two to six reduction in noise standard deviation compared to that of the MLE + TVmin two-step approach.

Quantitative performance of photon-counting CT at low dose: Virtual monochromatic imaging and iodine quantification

BACKGROUND

Quantitative imaging techniques, such as virtual monochromatic imaging (VMI) and iodine quantification (IQ), have proven valuable diagnostic methods in several specific clinical tasks such as tumor and tissue differentiation. Recently, a new generation of computed tomography (CT) scanners equipped with photon-counting detectors (PCD) has reached clinical status.

PURPOSE

This work aimed to investigate the performance of a new photon-counting CT (PC-CT) in low-dose quantitative imaging tasks, comparing it to an earlier generation CT scanner with an energy-integrating detector dual-energy CT (DE-CT). The accuracy and precision of the quantification across size, dose, material types (including low and high iodine concentrations), displacement from iso-center, and solvent (tissue background) composition were explored.

METHODS

Quantitative analysis was performed on two clinical scanners, Siemens SOMATOM Force and NAEOTOM Alpha using a multi-energy phantom with plastic inserts mimicking different iodine concentrations and tissue types. The tube configurations in the dual-energy scanner were 80/150Sn kVp and 100/150Sn kVp, while for PC-CT both tube voltages were set to either 120 or 140 kVp with photon-counting energy thresholds set at 20/65 or 20/70 keV. The statistical significance of patient-related parameters in quantitative measurements was examined using ANOVA and pairwise comparison with the posthoc Tukey honest significance test. Scanner bias was assessed in both quantitative tasks for relevant patient-specific parameters.

RESULTS

The accuracy of IQ and VMI in the PC-CT was comparable between standard and low radiation doses (p < 0.01). The patient size and tissue type significantly affect the accuracy of both quantitative imaging tasks in both scanners. The PC-CT scanner outperforms the DE-CT scanner in the IQ task in all cases. Iodine quantification bias in the PC-CT (-0.9 ± 0.15 mg/mL) at low doses in our study was comparable to that of DE-CT (range -2.6 to 1.5 mg/mL, published elsewhere) at a 1.7× higher dose, but the dose reduction severely biased DE-CT (4.72 ± 0.22 mg/mL). The accuracy in Hounsfield units (HU) estimation was comparable for 70 and 100 keV virtual imaging between scanners, but PC-CT was significantly underestimating virtual 40 keV HU values of dense materials in the phantom representing the extremely obese population.

CONCLUSIONS

The statistical analysis of our measurements reveals better IQ at lower radiation doses using new PC-CT. Although VMI performance was mostly comparable between the scanners, the DE-CT scanner quantitatively outperformed PC-CT when estimating HU values in the specific case of very large phantoms and dense materials, benefiting from increased X-ray tube potentials.

Facilitated encapsulation of a nonionic contrast agent for X-ray computed tomography into lipid vesicles by the multiple emulsification-solvent evaporation method

We studied the encapsulation of iohexol (Ihex), a nonionic contrast agent used for X-ray computational tomography, into lipid vesicles using the multiple emulsification-solvent evaporation method to formulate a nanosized contrast agent. This lipid vesicle preparation method consists of three steps: (1) primary emulsification for producing water-in-oil (W/O) emulsions containing fine water droplets that will be converted to the internal water phase of the lipid vesicles, (2) secondary emulsification for formulating multiple water-in-oil-in-water (W/O/W) emulsions encapsulating the fine water droplets containing Ihex, and (3) solvent evaporation to remove the oil phase solvent (n-hexane) and to form lipid bilayers surrounding the fine inner droplets, resulting in the formation of lipid vesicles encapsulating Ihex. As the diameter and Ihex concentration of the primary W/O emulsion droplets decreased, a higher Ihex encapsulation yield was obtained for the final lipid vesicles. The entrapment yield of Ihex in the final lipid vesicles varied significantly with the emulsifier (Pluronic® F-68) concentration in the external water phase of W/O/W emulsion, and the highest yield (65%) was obtained when the emulsifier concentration was 0.1 wt%. We also investigated the powderization of lipid vesicles encapsulating Ihex via lyophilization. The powderized vesicles were dispersed in water after rehydration and maintained their controlled diameters. The entrapment yield of Ihex in powderized lipid vesicles was maintained for over 1 month at 25 ˚C, while significant leakage of Ihex was observed in the lipid vesicles suspended in the aqueous phase.

Renal lesion characterization: clinical utility of single-phase dual-energy CT compared to MRI and dual-phase single-energy CT

OBJECTIVES

To assess the impact of dual-energy CT (DECT) utilization in practice by measuring the readers' confidence, the need for additional image requests, and diagnostic performance in renal lesion assessment, compared to single-energy CT (SECT) using contrast-enhanced MRI to establish the reference standard.

MATERIALS AND METHODS

Sixty-nine patients (M/F = 47/22) who underwent a dual-phase renal SECT (n = 34) or DECT (n = 35) and had a contrast-enhanced MRI within 180 days were retrospectively collected. Three radiologists assessed images on different sessions (SECT, DECT, and MRI) for (1) likely diagnosis (enhancing/non-enhancing); (2) diagnostic confidence (5-point Likert scale); (3) need for additional imaging test (yes/no); and (4) need for follow-up imaging (yes/no). Diagnostic accuracy was compared using AUC; p value < 0.05 was considered significant.

RESULTS

One hundred fifty-six lesions consisting of 18% enhancing (n = 28/156, mean size: 30.37 mm, range: 9.9-94 mm) and 82% non-enhancing (n = 128/156, mean size: 23.91 mm, range: 5.0-94.2 mm) were included. The confidence level was significantly lower for SECT than their MRI (4.50 vs. 4.80, p value < 0.05) but not significantly different for DECT and the corresponding MRI (4.78 vs. 4.78, p > 0.05). There were significantly more requests for additional imaging in the SECT session than the corresponding MRI (20% vs. 4%), which was not significantly different between DECT and their MRI counterpart session (5.7% vs. 4.9%). Inter-reader agreement was almost perfect for DECT and MRI (kappa: 0.8-1) and substantial in SECT sessions (kappa: 0.6-0.8) with comparable diagnostic accuracy between SECT, DECT, and MRI (p value > 0.05).

CONCLUSION

Single-phase DECT allows confident and reproducible characterization of renal masses with fewer recommendation for additional and follow-up imaging tests than dual-phase SECT and a performance similar to MRI.

KEY POINTS

• DECT utilization leads to similar additional image requests to MRI (5.7% vs. 4.9%, p value > 0.05), whereas single-energy CT utilization leads to significantly higher image requests (20% vs. 4%, p value < 0.05). • DECT and MRI utilization bring highly reproducible results with almost perfect inter-reader agreement (kappa: 0.8-1), better than the inter-reader agreement in SECT utilization (kappa: 0.6-0.8). • Readers' confidence was not significantly altered between DECT and their MRI readout session (p value > 0.05). In contrast, confidence in the diagnosis was significantly lower in the SECT session than their MRI readout (p value < 0.05).

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 SNR_Rose 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.

Virtual monochromatic spectral attenuation curve analysis for evaluation of incidentally detected small renal lesions using rapid kilovoltage-switching dual-energy computed tomography

PURPOSE

To determine whether the spectral attenuation curve on a rapid kilovoltage-switching dual-energy computed tomography (DECT) scan can distinguish enhancing from nonenhancing incidental small (1-4 cm) renal lesions compared with conventional single-energy attenuation changes.

METHODS

This retrospective study enrolled 46 patients with 78 renal lesions (24 enhancing; 54 nonenhancing) who underwent DECT with DE mode performed during the portovenous or nephrographic phase. Final diagnosis of enhancing and nonenhancing masses was confirmed by pathology or imaging following the established criteria. Virtual monochromatic images (VMI) were reconstructed, and the slopes between the VMI dataset at 40-70 keV (Slope HU_40-70), 40-100 keV (Slope HU_40-100), and 40-140 keV (Slope HU_40-140) were measured. Visual assessment of the curve pattern was recorded. Diagnostic accuracies were calculated with a cross-validated Mann-Whitney U test, and correlations of quantitative spectral parameters and intraclass correlation coefficient (ICC) were calculated using Spearman's rho correlation.

RESULTS

All quantitative and qualitative spectral analysis parameters significantly differentiated the enhancing and nonenhancing lesions (P < 0.001). The optimal slope thresholds calculated by cross-validation for Slope HU_40-70, Slope HU_40-100, and Slope HU_40-140 were 3.0, 1.8 and 1.2, respectively for reader 1 and 3.0, 1.9 and 1.15, respectively for reader 2. Using a slope threshold at all datasets yielded a high diagnostic accuracy of 96 for reader 1 and 95 for reader 2. Using a ∆HU threshold of 20 HU yielded an accuracy of 100. Visual analysis of the curve pattern also yielded high accuracy of 94.

CONCLUSIONS

The spectral attenuation curve on rapid kilovoltage-switching DECT gives excellent diagnostic accuracy differentiating between incidental enhancing and nonenhancing renal lesions. This benefit of DECT will be most helpful when the true unenhanced phase is not performed.

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.

Tumorous tissue characterization using integrated 18F-FDG PET/dual-energy CT in lung cancer: Combining iodine enhancement and glycolytic activity

Positron emission tomography/computed tomography (PET/CT) with 18F-fluorodeoxyglucose (18F-FDG) has become the method of choice for tumor staging in lung cancer patients with improved diagnostic accuracy for the evaluation of lymph node involvement and distant metastasis. Due to its spectral capabilities, dual-energy CT (DECT) employs a material decomposition algorithm enabling precise quantification of iodine concentrations in distinct tissues. This technique enhances the characterization of tumor blood supply and has demonstrated promising results for the assessment of therapy response in patients with lung cancer. Several studies have demonstrated that DECT provides additional value to the PET-based evaluation of glycolytic activity, especially for the evaluation of therapy response and follow-up of patients with lung cancer. The combination of PET and DECT in a single scanner system enables the simultaneous assessment of glycolytic activity and iodine enhancement, offering further insight to the characterization of tumorous tissues. Recently a new approach of a novel integrated PET/DECT was investigated in a pilot study on patients with non-small cell lung cancer (NSCLC). The study showed a moderate correlation between PET-based standard uptake values (SUV) and DECT-based iodine densities in the evaluation of lung tumorous tissue but with limited assessment of lymph nodes. The following review on tumorous tissue characterization using PET and DECT imaging describes the strengths and limitations of this novel technique.

A Method for Reducing Variability Across Dual-Energy CT Manufacturers in Quantification of Low Iodine Content Levels

Background: Clinical use of the dual-energy CT (DECT) iodine quantification technique is hindered by between-platform (i.e., across different manufacturers) variability in iodine concentration (IC), particularly at low iodine levels. Objective: To develop in an anthropomorphic phantom a method for reducing between-platform variability in quantification of low iodine content levels using DECT and to evaluate the method's performance in patients undergoing serial clinical DECT examinations on different platforms. Methods: An anthropomorphic phantom in three body sizes, incorporating varied lesion types and scanning conditions, was imaged with three distinct DECT implementations from different manufacturers at varying radiation exposures. A cross-platform iodine quantification model for correcting between-platform variability at low iodine content was developed using the phantom data. The model was tested in a retrospective series of 30 patients (20 men, 10 women; median age, 62 years) who each underwent three serial contrast-enhanced DECT examinations of the abdomen and pelvis (90 scans total) for routine oncology surveillance, using the same three DECT platforms as in the phantom. Estimated accuracy of phantom IC values was summarized using rootmean-squared error (RMSE) relative to known IC. Between-platform variability in patients was summarized using root-mean-square-deviation (RMSD). RMSE and RMSD were compared between platform-based IC (ICPB) and cross-platform IC (ICCP). ICPB was normalized to aorta and portal vein. Results: In the phantom study, mean RMSE of ICPB across platforms and other experimental conditions was 0.65 ± 0.18 mgI/mL compared with 0.40 ± 0.075 mgI/mL for ICCP (38% decrease in mean RMSE; P<.05). Intra-patient between-platform variability across serial DECT examinations was lower for ICPB than ICCP (RMSD: 97% vs 88%; P<.001). Between-platform variability was not reduced by normalization of ICPB to aorta (RMSD: 97% vs 101%; P=.12) or portal vein (RMSD: 97% vs 97%; P=.81). Conclusion: The developed cross-platform method significantly decreased between-platform variability occurring at low iodine content with platform-based DECT iodine quantification. Clinical Impact: With further validation, the cross-platform method, which has been implemented as a webbased app, may expand clinical use of DECT iodine quantification, yielding meaningful IC values that reflect tissue biologic viability or treatment response in patients who undergo serial examinations on different platforms.

Spectral CT of the abdomen: Where are we now?

Spectral CT adds a new dimension to radiological evaluation, beyond assessment of anatomical abnormalities. Spectral data allows for detection of specific materials, improves image quality while at the same time reducing radiation doses and contrast media doses, and decreases the need for follow up evaluation of indeterminate lesions. We review the different acquisition techniques of spectral images, mainly dual-source, rapid kV switching and dual-layer detector, and discuss the main spectral results available. We also discuss the use of spectral imaging in abdominal pathologies, emphasizing the strengths and pitfalls of the technique and its main applications in general and in specific organs.

Design and implementation of a practical quality control program for dual-energy CT

A novel routine dual‐energy computed tomography (DECT) quality control (QC) program was developed to address the current deficiency of routine QC for this technology. The dual‐energy quality control (DEQC) program features (1) a practical phantom with clinically relevant materials and concentrations, (2) a clinically relevant acquisition, reconstruction, and postprocessing protocol, and (3) a fully automated analysis software to extract quantitative data for database storage and trend analysis. The phantom, designed for easy set up for standalone or adjacent imaging next to the ACR phantom, was made in collaboration with an industry partner and informed by clinical needs to have four iodine inserts (0.5, 1, 2, and 5 mg/ml) and one calcium insert (100 mg/ml) equally spaced in a cylindrical water‐equivalent background. The imaging protocol was based on a clinical DECT abdominal protocol capable of producing material specific concentration maps, virtual unenhanced images, and virtual monochromatic images. The QC automated analysis software uses open‐source technologies which integrates well with our current automated CT QC database. The QC program was tested on a GE 750 HD scanner and two Siemens SOMATOM FLASH scanners over a 3‐month period. The automated algorithm correctly identified the appropriate region of interest (ROI) locations and stores measured values in a database for monitoring and trend analysis. Slight variations in protocol settings were noted based on manufacturer. Overall, the project proved to provide a convenient and dependable clinical tool for routine oversight of DE CT imaging within the clinic.

Solid renal masses in adults

With the ever increasing trend of using cross-section imaging in today's era, incidental detection of small solid renal masses has dramatically multiplied. Coincidentally, the number of asymptomatic benign lesions being detected has also increased. The role of radiologists is not only to identify these lesions, but also go a one step further and accurately characterize various renal masses. Earlier detection of small renal cell carcinomas means identifying at the initial stage which has an impact on prognosis, patient management and healthcare costs. In this review article we share our experience with the typical and atypical solid renal masses encountered in adults in routine daily practice.

Diagnostic performance of single-phase dual-energy CT to differentiate vascular and nonvascular incidental renal lesions on portal venous phase: comparison with CT

OBJECTIVES

To determine whether single-phase dual-energy CT (DECT) differentiates vascular and nonvascular renal lesions in the portal venous phase (PVP). Optimal iodine threshold was determined and compared to Hounsfield unit (HU) measurements.

METHODS

We retrospectively included 250 patients (266 renal lesions) who underwent a clinically indicated PVP abdominopelvic CT on a rapid-kilovoltage-switching single-source DECT (rsDECT) or a dual-source DECT (dsDECT) scanner. Iodine concentration and HU measurements were calculated by four experienced readers. Diagnostic accuracy was determined using biopsy results and follow-up imaging as reference standard. Area under the curve (AUC) was calculated for each DECT scanner to differentiate vascular from nonvascular lesions and vascular lesions from hemorrhagic/proteinaceous cysts. Univariable and multivariable logistic regression analyses evaluated the association between variables and the presence of vascular lesions.

RESULTS

A normalized iodine concentration threshold of 0.25 mg/mL yielded high accuracy in differentiating vascular and nonvascular lesions (AUC 0.93, p < 0.001), with comparable performance to HU measurements (AUC 0.93). Both iodine concentration and HU measurements were independently associated with vascular lesions when adjusted for age, gender, body mass index, and lesion size (AUC 0.95 and 0.95, respectively). When combined, diagnostic performance was higher (AUC 0.96). Both absolute and normalized iodine concentrations performed better than HU measurements (AUC 0.92 vs. AUC 0.87) in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.

CONCLUSION

A single-phase (PVP) DECT scan yields high accuracy to differentiate vascular from nonvascular renal lesions. Iodine concentration showed a slightly higher performance than HU measurements in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.

KEY POINTS

• A single-phase dual-energy CT scan in the portal venous phase differentiates vascular from nonvascular renal lesions with high accuracy (AUC 0.93). • When combined, iodine concentration and HU measurements showed the highest diagnostic performance (AUC 0.96) to differentiate vascular from nonvascular renal lesions. • Compared to HU measurements, iodine concentration showed a slightly higher performance in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.

Dual-Energy CT-Based Iodine Quantification in Liver Tumors - Impact of Scan-, Patient-, and Position-Related Factors

RATIONALE AND OBJECTIVES

To quantify the contribution of lesion location and patient positioning, dual-energy approach, patient size, and radiation dose to the error of dual-energy CT-based iodine quantification (DECT-IQ) in liver tumors.

MATERIALS AND METHODS

A phantom with four liver lesions (diameter 15 mm; iodine concentration 0-5 mgI/mL) and two sizes was used. One lesion emulated a subdiaphragmatic lesion. Both sizes were imaged in dual-energy mode on (1) a dual-source DECT (DS-DE) at 100/Sn150 kV and (2) a single-source split-filter DECT (SF-DE) at AuSn120 kV at two radiation doses (8 and 12 mGy). Scans were performed at seven different vertical table positions (from -6 to + 6 cm from the gantry isocenter). Iodine concentration was repeatedly measured and absolute errors (error_abs) were calculated. Errors were compared using robust repeated-measures ANOVAs with post-hoc comparisons. A linear mixed effect model was used to determine the factors influencing the error of DECT-IQ.

RESULTS

The linear mixed effect models showed that errors were significantly influenced by DECT approach, phantom size, and lesion location (all p < 0.001). The impact of lesion location on the error was stronger in SF-DE compared to DS-DE. Radiation dose did not significantly influence error (p = 0.22). When averaged across all setups, error_abs was significantly higher for SF-DE (2.08 ± 1.92 mgI/mL) compared to DS-DE (0.37 ± 0.29 mgI/mL) (all p < 0.001). Artefacts were found in the subdiaphragmatic lesion for SF-DE with significantly increased error_abs compared to DS-DE (p < 0.001). Error_abs was significantly higher in the large compared to the medium phantom for DS-DE (0.30 ± 0.23 mgI/mL vs. 0.43 ± 0.33 mgI/mL) and SF-DE (1.68 ± 1.99 vs. 2.36 ± 1.81 mgI/mL) (p < 0.001).

CONCLUSION

The dual-energy approach, patient size, and lesion location modified by patient position significantly impacted DECT-IQ in simulated liver tumors.

Investigating new CT contrast agents: a phantom study exploring quantification and differentiation methods for high-Z elements using dual-energy CT

OBJECTIVES

To develop a dual-energy CT method for differentiating and quantifying high-Z contrast elements and to evaluate the limitations based on element concentration and atomic number by using an anthropomorphic phantom study.

METHODS

Mass spectrometry standards for iodine, barium, gadolinium, ytterbium, tantalum, gold, and bismuth were diluted from 10.0 to 0.3 mg/mL, placed inside 7-mL vials, and scanned with dual-energy CT using an abdominal phantom and cylindrical water-filled insert. This procedure was repeated with all seven high-Z elements at six isoattenuating values from 250 to 8 HU. Quantification accuracy was measured using a linear regression model and residual error analysis with 90% limits of agreement. The limit of detection for each element was evaluated using the limit of blank of water. Pairwise differentiation of isoattenuating vials was evaluated using AUC values and the difference in fit angles between the two elements.

RESULTS

Each high-Z element had a unique concentration vector in a two-dimensional plot of Compton scattering versus photoelectric effect attenuations. Mean quantification values were within ± 0.1 mg/mL of the true values for each element with no proportional bias. Limits of detection ranged from 0.35 to 0.56 mg/mL. Pairwise differentiations were proportional to the isoattenuating HU and the angle between the linear fits with mean AUC values increasing from 0.61 to 0.98 at 8 to 250 HU, respectively.

CONCLUSION

Dual-energy CT can differentiate and quantify isoattenuating high-Z elements. The high-attenuation characteristics and unique concentration vectors of ytterbium, tantalum, gold, and bismuth are well suited for new dual-energy CT contrast agents especially when simultaneously imaged with iodine, barium, or gadolinium.

KEY POINTS

• Dual-energy CT can accurately quantify high-Z contrast elements and readily differentiate iodine, barium, and gadolinium from ytterbium, tantalum, gold, and bismuth. • The differentiation and quantification capabilities for high-Z contrast elements are largely unaffected by phantom size and transaxial location within the phantom. • Potential benefits of new CT contrast agents based on these high-Z elements include alternatives for patients with iodine sensitivity, high conspicuity at both 120 and 140 kVp, simultaneous imaging of two contrast agents, and reduced injection volume.

Comparative Study on Iron Content Detection by Energy Spectral CT and MRI in MDS Patients

Objective: The purpose of this study was to identify the difference between dual energy spectral computed tomography (DECT) and magnetic resonance imaging (MRI) used to detect liver/cardiac iron content in Myelodysplastic syndrome (MDS) patients with differently adjusted serum ferritin (ASF) levels. Method: Liver and cardiac iron content were detected by DECT and MRI. Patients were divided into different subgroups according to the level of ASF. The receiver operating characteristic curve (ROC) analysis was applied in each subgroup. The correlation between iron content detected by DECT/MRI and ASF was analyzed in each subgroup. Result: ROC curves showed that liver virtual iron content (LVIC) Az was significantly less than liver iron concentration (LIC) Az in the subgroup with ASF < 1,000 ng/ml. There was no significant difference between LVIC Az and LIC Az in the subgroup with 1,000 ≤ ASF < 2,500 ng/ml and 2,500 ≤ ASF < 5,000 ng/ml. LVIC Az was significantly higher than LIC Az in the subgroup with ASF <5,000 and 5,000 ≤ ASF ng/ml. In patients undergoing DECT and MRI examination on the same day, ASF was significantly correlated with LVIC, whereas no significant correlation was observed between ASF and LIC. After removing the data of ASF > 5,000 mg/L in LIC, LIC became correlated with ASF. There was no significant difference between the subgroup with 2,500 ≤ ASF < 5,000 ng/ml and 5,000 ng/ml ≤ ASF in LIC expression. Furthermore, both LIC and liver VIC had significant correlations with ASF in patients with ASF < 2,500 ng/ml, while LVIC was still correlated with ASF, LIC was not correlated with ASF in patients with 2,500 ng/ml ≤ ASF. Moreover, neither cardiac VIC nor myocardial iron content (MIC) were correlated with ASF in these subgroups. Conclusion: MRI and DECT were complementary to each other in liver iron detection. In MDS patients with high iron content, such as ASF ≥ 5,000 ng/ml, DECT was more reliable than the MRI in the assessment of iron content. But in patients with low iron content, such as ASF < 1,000 ng/ml, MRI is more reliable than DECT. Therefore, for the sake of more accurately evaluating the iron content, the appropriate detection method can be selected according to ASF.

Intraindividual Consistency of Iodine Concentration in Dual-Energy Computed Tomography of the Chest and Abdomen

OBJECTIVES

Dual-energy computed tomography (DECT)-derived quantification of iodine concentration (IC) is increasingly used in oncologic imaging to characterize lesions and evaluate treatment response. However, only limited data are available on intraindividual consistency of IC and its variation. This study investigates the longitudinal reproducibility of IC in organs, vessels, and lymph nodes in a large cohort of healthy patients who underwent repetitive DECT imaging.

MATERIALS AND METHODS

A total of 159 patients, who underwent a total of 469 repetitive (range, 2-4), clinically indicated portal-venous phase DECT examinations of the chest and abdomen, were retrospectively included. At time of imaging, macroscopic tumor burden was excluded by follow-up imaging (≥3 months). Iodine concentration was measured region of interest-based (N = 43) in parenchymatous organs, vessels, lymph nodes, and connective tissue. Normalization of IC to the aorta and to the trigger delay as obtained from bolus tracking was performed. For statistical analysis, intraclass correlation coefficient and modified variation coefficient (MVC) were used to assess intraindividual agreement of IC and its variation between different time points, respectively. Furthermore, t tests and analysis of variance with Tukey-Kramer post hoc test were used.

RESULTS

The mean intraclass correlation coefficient over all regions of interest was good to excellent (0.642-0.936), irrespective of application of normalization or the normalization technique. Overall, MVC ranged from 1.8% to 25.4%, with significantly lower MVC in data normalized to the aorta (5.8% [1.8%-15.8%]) in comparison with the MVC of not normalized data and data normalized to the trigger delay (P < 0.01 and P = 0.04, respectively).

CONCLUSIONS

Our study confirms intraindividual, longitudinal variation of DECT-derived IC, which varies among vessels, lymph nodes, organs, and connective tissue, following different perfusion characteristics; normalizing to the aorta seems to improve reproducibility when using a constant contrast media injection protocol.

Adequacy of Unenhanced MRI for Surveillance of Small (Clinical T1a) Solid Renal Masses

OBJECTIVE. The purpose of this study was to determine if contrast enhancement is necessary for MRI surveillance of clinical T1a (cT1a) solid renal masses. MATERIALS AND METHODS. With institutional review board approval, 36 patients who underwent two or more contrast-enhanced (CE) MRI examinations (median, four examinations; range, two to 10 examinations) for surveillance of 39 cT1a solid renal masses between 2009 and 2019 (median time between scans, 2 years; range, 1-7 years) were evaluated. Two radiologists independently measured renal mass size and assessed tumor stage in two sessions for baseline and follow-up examinations using T1-weighted nephrographic phase CE-MRI and unenhanced single-shot T2-weighted MRI in mixed order with a 4-week washout period. Comparisons were performed using the Wilcoxon sign-rank test and Pearson correlation. Bland-Altman and intraclass correlation determined interobserver agreement. RESULTS. Mean size ± SD of renal masses on CE-MRI and T2-weighted MRI were 18 ± 5 mm (range, 9-37 mm) and 18 ± 5 mm (range, 9-37 mm) for radiologist 1 and 19 ± 7 mm (range, 10-39 mm) and 19 ± 6 mm (range, 10-39 mm) for radiologist 2 with near perfect correlation (for radiologist 1, β = 0.9897; for radiologist 2, β = 0.9317; p < .001). Interob-server agreement for measurements comparing radiologist 1 and radiologist 2 on CEMRI and T2-weighted MRI and intraobserver agreement for measurements on CE-MRI and T2-weighted MRI were excellent. Mean growth rate of renal masses measured on CE-MRI and T2-weighted MRI were 2 ± 2 mm (range, -5 to 8 mm) and 2 ± 3 mm (range, -3 to 8 mm) for radiologist 1 and 3 ± 5 mm (range, -1 to 18 mm) and 3 ± 6 mm (range, -1 to 24 mm) for radiologist 2 with high correlation (for radiologist 1, β = 0.8313 [p < .001]; for radiologist 2, β = 0.848 [p = .002]). At baseline, all tumors were subjectively cT1a on CE-MRI and T2-weighted MRI (p > .99, intraclass correlation coefficient [ICC] = 1). During follow-up, one mass progressed to T3 on CE-MRI and T2-weighted MRI for radiologist 1 and radiologist 2 (p > .99, ICC = 1). CONCLUSION. In this study, size measurements on unenhanced T2-weighted MRI had near perfect correlation to measurements using CE-MRI in cT1a solid renal masses undergoing surveillance, with high agreement between and within observers. Clinical staging did not differ comparing T2-weighted MRI and CE-MRI, with near perfect agreement. Contrast enhancement is not necessary for follow-up size measurements in cT1a solid renal masses with MRI.

A Universal Protocol for Abdominal CT Examinations Performed on a Photon-Counting Detector CT System: A Feasibility Study

OBJECTIVE

The aims of this study were to investigate the feasibility of using a universal abdominal acquisition protocol on a photon-counting detector computed tomography (PCD-CT) system and to compare its performance to that of single-energy (SE) and dual-energy (DE) CT using energy-integrating detectors (EIDs).

METHODS

Iodine inserts of various concentrations and sizes were embedded into different sizes of adult abdominal phantoms. Phantoms were scanned on a research PCD-CT and a clinical EID-CT with SE and DE modes. Virtual monoenergetic images (VMIs) were generated from PCD-CT and DE mode of EID-CT. For each image type and phantom size, contrast-to-noise ratio (CNR) was measured for each iodine insert and the area under the receiver operating characteristic curve (AUC) for iodine detectability was calculated using a channelized Hotelling observer. The optimal energy (in kiloelectrovolt) of VMIs was determined separately as the one with highest CNR and the one with the highest AUC. The PCD-CT VMIs at the optimal energy were then compared with DE VMIs and SE images in terms of CNR and AUC.

RESULTS

Virtual monoenergetic image at 50 keV had both the highest CNR and highest AUC for PCD-CT and DECT. For 1.0 mg I/mL iodine and 35 cm phantom, the CNRs of 50 keV VMIs from PCD-CT (2.01 ± 0.67) and DE (1.96 ± 0.52) were significantly higher (P < 0.001, Wilcoxon signed-rank test) than SE images (1.11 ± 0.35). The AUC of PCD-CT (0.98 ± 0.01) was comparable to SE (0.98 ± 0.01), and both were slightly lower than DE (0.99 ± 0.01, P < 0.01, Wilcoxon signed-rank test). A similar trend was observed for other phantom sizes and iodine concentrations.

CONCLUSIONS

Virtual monoenergetic images at a fixed energy from a universal acquisition protocol on PCD-CT demonstrated higher iodine CNR and comparable iodine detectability than SECT images, and similar performance compared with DE VMIs.

Use of dual-energy CT for renal mass assessment

Although dual-energy CT (DECT) may prove useful in a variety of abdominal imaging tasks, renal mass evaluation represents the area where this technology can be most impactful in abdominal imaging compared to routinely performed contrast-enhanced-only single-energy CT exams. DECT post-processing techniques, such as creation of virtual unenhanced and iodine density images, can help in the characterization of incidentally discovered renal masses that would otherwise remain indeterminate based on post-contrast imaging only. The purpose of this article is to review the use of DECT for renal mass assessment, including its benefits and existing limitations. KEY POINTS: • If DECT is selected as the scanning mode for most common abdominal protocols, many incidentally found renal masses can be fully triaged within the same exam. • Virtual unenhanced and iodine density DECT images can provide additional information when renal masses are discovered in the post-contrast-only setting. • For renal mass evaluation, virtual unenhanced and iodine density DECT images should be interpreted side-by-side to troubleshoot pitfalls that can potentially lead to erroneous interpretation.

ACR Appropriateness Criteria® Indeterminate Renal Mass

Renal masses are increasingly detected in asymptomatic individuals as incidental findings. CT and MRI with intravenous contrast and a dedicated multiphase protocol are the mainstays of evaluation for indeterminate renal masses. A single-phase postcontrast dual-energy CT can be useful when a dedicated multiphase renal protocol CT is not available. Contrast-enhanced ultrasound with microbubble agents is a useful alternative for characterizing renal masses, especially for patients in whom iodinated CT contrast or gadolinium-based MRI contrast is contraindicated. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Normalized Dual-Energy Iodine Ratio Best Differentiates Renal Cell Carcinoma Subtypes Among Quantitative Imaging Biomarkers From Perfusion CT and Dual-Energy CT

OBJECTIVE. The objective of our study was to assess and compare the diagnostic accuracy of perfusion CT (PCT) and dual-energy CT (DECT) in differentiating clear cell renal cell carcinoma (ccRCC) from non-ccRCC. MATERIALS AND METHODS. This retrospective study included 51 patients with 52 renal cell carcinomas (RCCs) (36 ccRCCs and 16 non-ccRCCs) who underwent both PCT and DECT before surgery or biopsy between January 2014 and December 2018. Three independent readers measured blood flow, blood volume (BV), and permeability using PCT and iodine concentration (IC) and iodine ratio using DECT. Interreader agreement was calculated using the intraclass correlation coefficient (ICC). Multivariable logistic regression analysis was performed to assess PCT and DECT models. Size-specific dose estimates of the two methods were compared. RESULTS. BV (ICC, 0.93) and iodine ratio (ICC, 0.85) were the most reproducible parameters. Both PCT and DECT were significant models (p < 0.05, all readers) for differentiating ccRCC from non-ccRCC. There was no significant difference in diagnostic accuracy between PCT and DECT (p > 0.05). BV and iodine ratio were independent predictors of nonccRCC (p < 0.05). However, the mean size-specific dose estimate was 16 times lower with DECT than with PCT (p < 0.001). The AUC of iodine ratio was 0.95, and sensitivity, specificity, and accuracy with an iodine ratio cutoff of 63.72% was 0.90, 0.86, and 0.87, respectively. CONCLUSION. PCT and DECT had comparable and high diagnostic accuracy in differentiating RCC subtypes; however, because of the significantly lower radiation dose of DECT, iodine ratio may be used as the best independent predictor.

Protocol Optimization for Renal Mass Detection and Characterization

Renal masses increasingly are found incidentally, largely due to the frequent use of medical imaging. Computed tomography (CT) and MR imaging are mainstays for renal mass characterization, presurgical planning of renal tumors, and surveillance after surgery or systemic therapy for advanced renal cell carcinomas. CT protocols should be tailored to different clinical indications, balancing diagnostic accuracy and radiation exposure. MR imaging protocols should take advantage of the improved soft tissue contrast for renal tumor diagnosis and staging. Optimized imaging protocols enable analysis of imaging features that help narrow the differential diagnoses and guide management in patients with renal masses.

Discrimination of papillary renal cell carcinoma from benign proteinaceous cyst based on iodine and water content on rapid kV-switching dual-energy CT

PURPOSE

We aimed to evaluate whether rapid kV-switching dual energy CT (rsDECT) can discriminate between papillary renal cell carcinoma (RCC) and benign proteinaceous cysts (BPCs) based on iodine and water content.

METHODS

Twenty-four patients with histopathologically proven papillary RCC and 38 patients with 41 BPCs were retrospectively included. Patients with BPCs were eligible for inclusion when the cysts were stable in size and appearance for at least 2 years or proved to be a cyst on ultrasound or MRI. All patients underwent delayed phase (70-90 s) rsDECT. Iodine and water content of each lesion was measured on the workstation.

RESULTS

Of papillary RCC patients, 4 (16%) were female and 20 (84%) were male. Mean tumor size was 39±20 mm. Mean iodine and water content was 2.08±0.7 mg/mL and 1021±14 mg/mL, respectively. Of BPC patients, 9 were female and 29 were male. Mean cyst size was 20±7 mm. Mean iodine and water content was 0.82±0.4 mg/mL and 1012±14 mg/mL, respectively. There were significant differences between iodine and water contents of papillary RCCs and BPCs (P < 0.001). The best cutoff of iodine content for differentiating papillary RCC from BPC was 1.21 mg/mL (area under the curve [AUC]=0.97, P < 0.001, sensitivity 96%, specificity 88%, positive predictive value [PPV] 82%, negative predictive value [NPV] 97%, accuracy 91%,); the best cutoff of water content was 1015.5 mg/mL (AUC=0.68, P = 0.016, sensitivity 83%, specificity 56%, PPV 52%, NPV 85%, accuracy 66%).

CONCLUSION

An iodine content threshold of 1.21 mg/mL accurately differentiates papillary RCC from BPCs on a single postcontrast rsDECT. Despite having a high sensitivity, water content has inferior diagnostic accuracy.

Multi-energy computed tomography and material quantification: Current barriers and opportunities for advancement

Computed tomography (CT) technology has rapidly evolved since its introduction in the 1970s. It is a highly important diagnostic tool for clinicians as demonstrated by the significant increase in utilization over several decades. However, much of the effort to develop and advance CT applications has been focused on improving visual sensitivity and reducing radiation dose. In comparison to these areas, improvements in quantitative CT have lagged behind. While this could be a consequence of the technological limitations of conventional CT, advanced dual-energy CT (DECT) and photon-counting detector CT (PCD-CT) offer new opportunities for quantitation. Routine use of DECT is becoming more widely available and PCD-CT is rapidly developing. This review covers efforts to address an unmet need for improved quantitative imaging to better characterize disease, identify biomarkers, and evaluate therapeutic response, with an emphasis on multi-energy CT applications. The review will primarily discuss applications that have utilized quantitative metrics using both conventional and DECT, such as bone mineral density measurement, evaluation of renal lesions, and diagnosis of fatty liver disease. Other topics that will be discussed include efforts to improve quantitative CT volumetry and radiomics. Finally, we will address the use of quantitative CT to enhance image-guided techniques for surgery, radiotherapy and interventions and provide unique opportunities for development of new contrast agents.

Quantitative enhancement thresholds and machine learning algorithms for the evaluation of renal lesions using single-phase split-filter dual-energy CT

PURPOSE

To establish thresholds for contrast enhancement-based attenuation (CM) and iodine concentration (IOD) for the quantitative evaluation of enhancement in renal lesions on single-phase split-filter dual-energy CT (tbDECT) and combine measurements in a machine learning algorithm to potentially improve performance.

MATERIAL

126 patients with incidental renal cysts (both hypo- and hyperdense cysts) or high suspicion for renal cell carcinoma (312 total lesions) undergoing abdominal, portal venous phase tbDECT were initially included in this retrospective study. Gold standard was pathological confirmation or follow-up imaging (MRI or multiphasic CT). CM, IOD, and ROI size were recorded. Thresholds for CM and IOD were identified using Youden-Index of the empirical ROC curves. Decision tree (DTC) and random forest classifier (RFC) were trained. Sensitivities, specificities, and AUCs were compared using McNemar and DeLong test.

RESULTS

The final study cohort comprised 40 enhancing and 113 non-enhancing renal lesions. Optimal thresholds for quantitative iodine measurements and contrast enhancement-based attenuation were 1.0 ± 0.0 mg/ml and 23.6 ± 0.3 HU, respectively. Single DECT parameters (IOD, CM) showed similar overall performance with an AUC of 0.894 and 0.858 (p = 0.541) (sensitivity 90 and 80%, specificity 88 and 92%, respectively). While overall performance for the DTC (AUC 0.944) was higher than RFC (AUC 0.886), this difference (p = 0.409) and comparison to CM (p = 0.243) and IOD (p = 0.353) was not statistically significant.

CONCLUSIONS

Enhancement in incidental renal lesions on single-phase tbDECT can be classified with up to 87.5% sensitivity and 94.6% specificity. Algorithms combining DECT parameters did not increase overall performance.

Quantitative attenuation accuracy of virtual non-enhanced imaging compared to that of true non-enhanced imaging on dual-source dual-energy CT

PURPOSE

To evaluate the quantitative attenuation and reliability of virtual non-contrast (VNC) images of the abdomen acquired from multiphasic scans with a dual-energy computed tomography (DECT) system and compare it with that of true non-enhanced images (TNC) on second- (Flash) and third- (Force) generation DECT scanners.

METHODS

This retrospective study was approved by the institutional review board and included 123 patients with pancreatic cancer who had undergone routine clinical multiphasic DECT examinations at our institution using Flash and Force scanners between March and August 2017. VNC images of the abdomen were reconstructed from late arterial phase images. For every patient, regions-of-interest were defined in the aorta, fluid-containing structures (gallbladder, pleural effusion, and renal cysts > 10 mm), paravertebral muscles, subcutaneous fat, spleen, pancreas, renal cortex, and liver (eight locations) on TNC and VNC images. The mean attenuation of VNC was compared with TNC by organ for each CT scanner using an equivalence test and the Bland-Altman plot. The mean attenuations for TNC or VNC were compared between the Force and Flash CT scanners using a two-sample t test.

RESULTS

The VNC attenuation of organs on the Force scanner was lower than was that on the Flash, and the mean attenuation difference in different organs on the Force was closer to 0. The estimated means of TNC and VNC were equivalent for an equivalence margin of 10 on the Force scanner.

CONCLUSION

VNC images in DECT are a promising alternative to TNC images. In clinical scenarios in which non-enhanced CT images are required but are not available for accurate diagnosis, VNC images can potentially serve as an alternative to TNC images without the radiation exposure risks.

Current management of small renal masses

One of the consequences of the growing use of diagnostic imaging techniques is the notable growth in the detection of small renal masses presumably corresponding to localized tumors that are potentially curable with surgical treatment. When faced with the finding of a small renal mass, radiologists must determine whether it is benign or malignant, and if it is malignant, what subtype it belong to, and whether it should be managed with surgical treatment, with ablative techniques, or with watchful waiting with active surveillance. Small renal masses are now a clinical entity that require management different from the approaches used for classical renal cell carcinomas. In this scenario, radiologists are key because they are involved in all aspects of the management of these tumors, including in their diagnosis, treatment, and follow-up.

Characterization of clear cell renal cell carcinoma and other renal tumors: evaluation of dual-energy CT using material-specific iodine and fat imaging

OBJECTIVE

This study aimed to assess material-specific iodine and fat images for diagnosis of clear cell renal cell carcinoma (cc-RCC) compared to papillary RCC (p-RCC) and other renal masses.

MATERIALS AND METHODS

With IRB approval, we identified histologically confirmed solid renal masses that underwent rapid-kVp-switch DECT between 2016 and 2018: 25 cc-RCC (7 low grade versus 18 high grade), 11 p-RCC, and 6 other tumors (2 clear cell papillary RCC, 2 chromophobe RCC, 1 oncocytoma, 1 renal angiomyomatous tumor). A blinded radiologist measured iodine and fat concentration on material-specific iodine-water and fat-water basis pair images. Comparisons were performed between groups using univariate analysis and diagnostic accuracy calculated by ROC.

RESULTS

Iodine concentration was higher in cc-RCC (6.14 ± 1.79 mg/mL) compared to p-RCC (1.40 ± 0.54 mg/mL, p < 0.001), but not compared to other tumors (5.0 ± 2.2 mg/mL, p = 0.370). Intratumoral fat was seen in 36.0% (9/25) cc-RCC (309.6 ± 234.3 mg/mL [71.1-762.3 ng/mL]), 9.1% (1/11) papillary RCC (97.11 mg/mL), and no other tumors (p = 0.036). Iodine concentration ≥ 3.99 mg/mL achieved AUC and sensitivity/specificity of 0.88 (CI 0.76-1.00) and 92.31%/82.40% to diagnose cc-RCC. To diagnose p-RCC, iodine concentration ≤ 2.5 mg/mL achieved AUC and sensitivity/specificity of 0.99 (0.98-1.00) and 100%/100%. The presence of intratumoral fat had AUC 0.64 (CI 0.53-0.75) and sensitivity/specificity of 34.6%/93.8% to diagnose cc-RCC. A logistic regression model combining iodine concentration and presence of fat increased AUC to 0.91 (CI 0.81-1.0) with sensitivity/specificity of 80.8%/93.8% to diagnose cc-RCC.

CONCLUSION

Iodine concentration values are highly accurate to differentiate clear cell RCC from papillary RCC; however, they overlap with other tumors. Fat-specific images may improve differentiation of clear cell RCC from other avidly enhancing tumors.

KEY POINTS

• Clear cell renal cell carcinoma (RCC) has significantly higher iodine concentration than papillary RCC, but there is an overlap in values comparing clear cell RCC to other renal tumors. • Iodine concentration ≤ 2.5 mg/mL is highly accurate to differentiate papillary RCC from clear cell RCC and other renal tumors. • The presence of microscopic fat on material-specific fat images was specific for clear cell RCC, helping to differentiate clear cell RCC from other avidly enhancing renal tumors.

Iodine quantification and detectability thresholds among major dual-energy CT platforms

OBJECTIVES

To estimate the minimum detectable iodine concentration on multiple dual-energy CT (DECT) platforms.

METHODS AND MATERIALS

A phantom containing iodine concentrations ranging from 0 to 10 mg ml^-1 was scanned with five dual-energy platforms (two rapid kilo volt switching (r-kVs), one dual source (DS), one sequential acquisition and one split-filter). Serial dilutions of 300 mg ml^-1 iodinated contrast material were used to generate concentrations below 2 mg ml^-1. Iodine density and virtual monoenergetic images were reviewed by three radiologists to determine the minimum visually detectable iodine concentration. Contrast-to-noise ratios (CNRs) were calculated.

RESULTS

1 mg mL^-1 (~0.8 mg mL^-1 corrected) was the minimum visually detectable concentration among the platforms and could be seen by all readers on the third-generation r-kVs and DS platforms.

CONCLUSIONS

At low concentrations, CNR for monoenergetic images was highest on the DS platform and lowest in the sequential acquisition and split-filter platforms.

ADVANCES IN KNOWLEDGE

The results of this study corroborate previous in vivo estimates of iodine detection limits at DECT and provide a comparison for the performance of different DECT platforms at low iodine concentrations in vitro.

Clinical and Payer-Based Analysis of Value of Dual-Energy Computed Tomography for Workup of Incidental Abdominal Findings

OBJECTIVE

To perform a clinical and payer-based analysis of the value of dual-energy computed tomography (DECT) for workup of incidental abdominal findings.

METHODS

This was a single-center, retrospectively designed, Health Insurance Portability and Accountability Act-compliant study approved by our institutional review board. Sixty-nine examinations in 69 patients (45 men, 24 women; mean age, 57.7 years) who underwent single-phase postcontrast abdominal DECT studies between January 1, 2011, and December 31, 2017, were included. Two radiologists, blinded to study objective and design, reviewed all cases and identified incidental abdominal findings needing further imaging. All incidental findings were reviewed by 2 other investigators, who determined whether an imaging-based diagnosis could be made using DECT virtual noncontrast images and iodine maps. Additional studies and associated payer-reimbursement amounts avoided by use of DECT were estimated. All imaging costs were estimated based on the US Centers for Medicare & Medicaid Services reimbursement amounts.

RESULTS

Thirty-four incidental findings (renal mass, n = 20; adrenal nodule, n = 8; pancreatic cystic lesions, n = 3; others, n = 3) were identified in 19 (27.5%) of 69 patients. Dual-energy computed tomography characterized 27 incidental findings in 15 patients and accounted for cost savings of 15 additional imaging examinations (abdominal magnetic resonance imaging, n = 11; abdominal computed tomography, n = 4). Based on Centers for Medicare & Medicaid Services reimbursement amounts, we estimated that, by abolishing the need for additional imaging use, DECT saved US $84.95 per patient.

CONCLUSIONS

Dual-energy computed tomography can provide an imaging-based diagnosis of incidental abdominal findings, otherwise incompletely characterized on routine abdominal computed tomography, in approximately 21% of patients. In select patients, the monetary savings from abolishing additional imaging may reduce payer costs associated with use of DECT.

Diagnostic Accuracy of Attenuation Difference and Iodine Concentration Thresholds at Rapid-Kilovoltage-Switching Dual-Energy CT for Detection of Enhancement in Renal Masses

OBJECTIVE. The objective of our study was to evaluate iodine concentration and attenuation change in Hounsfield unit (ΔHU) thresholds to diagnose enhancement in renal masses at rapid-kilovoltage-switching dual-energy CT (DECT). MATERIALS AND METHODS. We evaluated 30 consecutive histologically confirmed solid renal masses (including nine papillary renal cell carcinomas [RCCs]) and 27 benign cysts (17 simple and 10 hemorrhagic or proteinaceous cysts) with DECT December 2016 and May 2018. A blinded radiologist measured iodine concentration (in milligrams per milliliter) and ΔHU (attenuation on enhanced CT - attenuation on unenhanced CT) using 70-keV corticomedullary (CM) phase virtual monochromatic and 120-kVp nephrographic (NG) phase images. The accuracies of previously described enhancement thresholds were compared by ROC curve analysis. RESULTS. An iodine concentration of ≥ 2.0 mg/mL and an iodine concentration of ≥ 1.2 mg/mL achieved sensitivity, specificity, and the area under the ROC curve (AUC) of 73.3%, 100.0%, and 0.87 and 86.7%, 100.0%, and 0.93, respectively. On 70-keV CM phase images, ΔHU ≥ 20 HU and ΔHU ≥ 15 HU yielded sensitivity, specificity, and AUC of 80.0%, 100.0%, and 0.90 and 90.0%, 100.0%, and 0.95, respectively. The numbers of incorrectly classified papillary RCCs were as follows: iodine concentration of ≥ 2.0 mg/mL, 77.8% (7/9; range, 0.7-1.6 mg/mL); iodine concentration of ≥ 1.2 mg/mL, 44.4% (4/9; range, 0.7-0.9 mg/mL); ΔHU ≥ 20 HU on 70-keV CM phase images, 66.7% (6/9; range, 4-17 HU); and ΔHU ≥ 15 HU on 70-keV DECT images, 33.3% (3/9; 4-12 HU). No cyst pseudoenhancement occurred on DECT. For 120-kVp NG phase DECT, ΔHU ≥ 20 HU and ΔHU ≥ 15 HU yielded sensitivity, specificity, and AUC of 93.3%, 96.3%, and 0.95 and 100.0%, 88.9%, and 0.94, respectively. With ΔHU ≥ 20 HU, 22.2% (2/9) (range, 15-18 HU) of papillary RCCs were misclassified and there was one pseudoenhancing cyst. With ΔHU ≥ 15 HU, no papillary RCCs were misclassified but 11.1% (3/27) of cysts showed pseudoenhancement. Only an iodine concentration of ≥ 2.0 mg/mL showed significantly lower accuracy than other measures (p = 0.031-0.045). CONCLUSION. DECT applied in the CM phase performed best using an iodine concentration of ≥ 1.2 mg/mL or a 70-keV ΔHU ≥ 15 HU; these parameters improved sensitivity for the detection of enhancement in renal masses without instances of cyst pseudoenhancement.

Systematic Review and Meta-Analysis Investigating the Diagnostic Yield of Dual-Energy CT for Renal Mass Assessment

OBJECTIVE. The objective of our study was to perform a systematic review and meta-analysis to evaluate the diagnostic accuracy of dual-energy CT (DECT) for renal mass evaluation. MATERIALS AND METHODS. In March 2018, we searched MEDLINE, Cochrane Database of Systematic Reviews, Embase, and Web of Science databases. Analytic methods were based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Pooled estimates for sensitivity, specificity, and diagnostic odds ratios were calculated for DECT-based virtual monochromatic imaging (VMI) and iodine quantification techniques as well as for conventional attenuation measurements from renal mass CT protocols. I² was used to evaluate heterogeneity. The methodologic quality of the included studies and potential bias were assessed using items from the Quality Assessment Tool for Diagnostic Accuracy Studies 2 (QUADAS-2). RESULTS. Of the 1043 articles initially identified, 13 were selected for inclusion (969 patients, 1193 renal masses). Cumulative data of sensitivity, specificity, and summary diagnostic odds ratio for VMI were 87% (95% CI, 80-92%; I², 92.0%), 93% (95% CI, 90-96%; I², 18.0%), and 183.4 (95% CI, 30.7-1093.4; I², 61.6%), respectively. Cumulative data of sensitivity, specificity, and summary diagnostic odds ratio for iodine quantification were 99% (95% CI, 97-100%; I², 17.6%), 91% (95% CI, 89-94%; I², 84.2%), and 511.5 (95% CI, 217-1201; I², 0%). No significant differences in AUCs were found when comparing iodine quantification to conventional attenuation measurements (p = 0.79). CONCLUSION. DECT yields high accuracy for renal mass evaluation. Determination of iodine content with the iodine quantification technique shows diagnostic accuracy similar to conventional attenuation measurements from renal mass CT protocols. The iodine quantification technique may be used to characterize incidental renal masses when a dedicated renal mass protocol is not available.

Usefulness of rapid kV-switching dual energy CT in renal tumor characterization

PURPOSE

To investigate whether iodine content can discriminate between benign or malignant renal tumors, malign tumor subtypes, low-grade and high-grade tumors on rapid kv-switching dual-energy CT (rsDECT).

METHODS

This prospective study enrolled 95 patients with renal tumors who underwent rsDECT for tumor characterization between 2016 and 2018. Attenuation on true and virtual unenhanced images, absolute enhancement and enhancement ratio and iodine content of each lesion on nephrographic phase iodine density images were measured. Histopathological diagnosis was obtained following either surgery or core biopsy.

RESULTS

Eighty-five tumors were renal cell carcinoma (RCC) (56 clear cell, 20 papillary, 9 chromophobe) and 10 were benign (6 angiomyolipoma,4 oncocytoma). 46 tumors were low-grade and 23 high-grade. There was significant difference between iodine content of clear cell and non-clear cell (papillary + chromophobe) RCC (p < 0.001). However, no significant iodine content differences were found between papillary and chromophobe RCC, benign and malignant tumors, low-grade and high-grade tumors. The best cut-off iodine content for differentiating clear cell from non-clear cell RCC was 3.2 mg/ml and clear cell from papillary RCC was 2.9 mg/ml with a high sensitivity and specificity. Also, significant difference was found between attenuation values of true and virtual unenhanced images (p = 0.007). Mean iodine content, absolute enhancement and enhancement ratio were highly correlated.

CONCLUSION

rsDECT contributes to renal tumor characterization by showing higher iodine content in clear cell RCCs compared with non-clear cell RCCs.

Comparison of Iodine Quantification and Conventional Attenuation Measurements for Differentiating Small, Truly Enhancing Renal Masses From High-Attenuation Nonenhancing Renal Lesions With Dual-Energy CT

OBJECTIVE. The purpose of this study is to determine whether iodine quantification techniques from contrast-enhanced dual-energy CT (DECT) data allow equal differentiation of small enhancing renal masses from high-attenuation (> 20 HU of unenhanced attenuation) nonenhancing lesions, compared with conventional attenuation measurements. MATERIALS AND METHODS. A total of 220 nonconsecutive patients (mean [± SD] age, 66 ± 13 years; 130 men and 90 women) with 265 high-attenuation renal lesions (mean attenuation, 54 ± 33 HU; 91 enhancing lesions) were included. Each patient underwent single-energy unenhanced CT followed by DECT during the nephrographic phase using one of four different high-end DECT platforms (first- and second-generation rapid-kilovoltage-switching DECT platforms and second- and third-generation dual-source DECT platforms). Iodine quantification measurements and conventional attenuation change measurements were calculated for each lesion. Diagnostic accuracy was determined by pathologic analysis, confirmation with another imaging modality, or greater than 24 months of imaging follow-up as the reference standard. RESULTS. The diagnostic accuracy for differentiating enhancing from nonenhancing renal lesions was significantly higher for conventional attenuation change measurements, compared with iodine quantification measurements (AUC values, 0.973 vs 0.875; p < 0.0001). The diagnostic performance of iodine quantification measurements improved only marginally with the utilization of DECT platform-specific optimized iodine quantification thresholds, yielding AUC values of 0.907 and 0.893 for the rapid-kilovoltage-switching DECT and dual-source DECT platforms, respectively. Unenhanced lesion attenuation (p = 0.0010) and intraparenchymal location (p = 0.0249) significantly influenced the diagnostic accuracy of the iodine quantification techniques. CONCLUSION. Iodine quantification from DECT data yields inferior diagnostic accuracy when compared with conventional attenuation change measurements for differentiating small, truly enhancing renal masses and high-attenuation renal lesions.

High-Pitch Wide-Coverage Fast-Kilovoltage-Switching Dual-Energy CT: Impact of Pitch on Noise, Spatial Resolution, and Iodine Quantification in a Phantom Study

OBJECTIVE

The purpose of this study was to assess the impact of high pitch values on image noise, spatial resolution, and iodine quantification in single-source wide-coverage fast-kilovoltage-switching dual-energy CT (DECT).

MATERIALS AND METHODS

Two phantom experiments were conducted. First, image noise and spatial resolution in the x-, y-, and z-directions were assessed. Second, the accuracy of iodine quantification was investigated with multiple-size phantoms with pure iodine and blood-iodine inserts. Both phantoms were scanned repeatedly with a third-generation fast-kilovoltage-switching DECT scanner with a collimation width of 80 mm at four different pitch values (0.5, 0.99, 1.375, 1.53) and three different gantry rotation times (0.6, 0.8, 1.0 second). Image noise, spatial resolution, and absolute error of iodine concentration (E) were measured. A linear mixed effects model was used to determine the effect of pitch, rotation time, and size on the error of iodine concentration.

RESULTS

Image noise and xy spatial resolution were comparable among the four pitch values. Spatial resolution in the z-direction was inferior and had higher variance at a low pitch of 0.5 compared with pitches of 0.99, 1.375, and 1.53. Error of iodine concentration was significantly affected by pitch and rotation time (p < 0.001). E decreased with increasing pitch and decreasing rotation time. In detail, mean E was 0.91 ± 0.47 mg I/mL for a pitch of 0.5, 0.52 ± 0.29 mg I/mL for 0.99, 0.44 ± 0.25 mg I/mL for 1.375, and 0.40 ± 0.25 mg I/mL for 1.53.

CONCLUSION

High-pitch wide-coverage fast-kilovoltage-switching DECT can be performed without impairing image quality or iodine quantification, and the results are superior to those of imaging at a low pitch of 0.5.

The Role of Dual-Energy Computed Tomography in Assessment of Abdominal Oncology and Beyond

The added value and strength of dual energy computed tomography for the evaluation of oncologic patients revolve around the use of lower energy reconstructed images and iodine material density images. Lower keV simulated monoenergetic images optimize soft tissue tumor to nontumoral attenuation differences and increase contrast to noise ratios to improve lesion detection. Iodine material density images or maps are helpful from a qualitative standpoint for image interpretation because they result in improved detection and characterization of tumors and lymph node involvement, and from a quantitative assessment by enabling interrogation of specific properties of tissues to predict and assess therapeutic response.