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

Scientific Status Quo of Small Renal Lesions: Diagnostic Assessment and Radiomics

Background: Small renal masses (SRMs) are defined as contrast-enhanced renal lesions less than or equal to 4 cm in maximal diameter, which can be compatible with stage T1a renal cell carcinomas (RCCs). Currently, 50-61% of all renal tumors are found incidentally. Methods: The characteristics of the lesion influence the choice of the type of management, which include several methods SRM of management, including nephrectomy, partial nephrectomy, ablation, observation, and also stereotactic body radiotherapy. Typical imaging methods available for differentiating benign from malignant renal lesions include ultrasound (US), contrast-enhanced ultrasound (CEUS), computed tomography (CT), and magnetic resonance imaging (MRI). Results: Although ultrasound is the first imaging technique used to detect small renal lesions, it has several limitations. CT is the main and most widely used imaging technique for SRM characterization. The main advantages of MRI compared to CT are the better contrast resolution and tissue characterization, the use of functional imaging sequences, the possibility of performing the examination in patients allergic to iodine-containing contrast medium, and the absence of exposure to ionizing radiation. For a correct evaluation during imaging follow-up, it is necessary to use a reliable method for the assessment of renal lesions, represented by the Bosniak classification system. This classification was initially developed based on contrast-enhanced CT imaging findings, and the 2019 revision proposed the inclusion of MRI features; however, the latest classification has not yet received widespread validation. Conclusions: The use of radiomics in the evaluation of renal masses is an emerging and increasingly central field with several applications such as characterizing renal masses, distinguishing RCC subtypes, monitoring response to targeted therapeutic agents, and prognosis in a metastatic context.

Dual-Energy Computed Tomography Applications in the Genitourinary Tract

By virtue of material differentiation capabilities afforded through dedicated postprocessing algorithms, dual-energy CT (DECT) has been shown to provide benefit in the evaluation of various diseases. In this article, we review the diagnostic use of DECT in the assessment of genitourinary diseases, with emphasis on its role in renal stone characterization, incidental renal and adrenal lesion characterization, retroperitoneal trauma, reduction of radiation, and contrast dose and cost-effectiveness potential. We also discuss future perspectives of the DECT scanning mode, including the use of novel contrast injection strategies and photon-counting detector computed tomography.

Incidental Indeterminate Renal Lesions: Distinguishing Non-Enhancing from Potential Enhancing Renal Lesions Using Iodine Quantification on Portal Venous Dual-Layer Spectral CT

The purpose of our study is to determine a threshold for iodine quantification to distinguish definitely non-enhancing benign renal lesions from potential enhancing masses on portal venous dual-layer spectral computed tomography (CT) to reduce the need for additional multiphase CT. In this single-center retrospective study, patients (≥18 years) scanned between April 2021 and January 2023 following the local renal CT protocol were included. Exclusion criteria were patients without renal lesions, lesions smaller than 10 mm, only fat-containing lesions, abscesses or infarction, follow-up after radiofrequent ablation, wrong scan protocol, or artefacts. Scans were performed on a dual layer detector-based spectral CT (CT 7500, Philips Healthcare, Best, The Netherlands). Iodine concentration (mgI/mL) in renal lesions was determined using spectral data. Analyses were performed for all lesions and for lesions of >30 HU on portal venous CT. Enhancement on multiphase CT (≥20 ΔHU from true unenhanced (TUE) to portal venous phase (PVP) CT) was used as reference standard. To determine thresholds for iodine concentration receiver operating characteristic (ROC) curves, area under the curve (AUC) and 95% confidence intervals were calculated. To obtain thresholds for definite (non-)enhancement, 100% sensitivity with maximum specificity and 100% specificity with maximum sensitivity were noted. Data were measured using one reader. To assess interobserver agreement, a second reader performed measurements on the PVP CT scans. A total of 103 patients (62 years ± 14, 68 men) were included. We measured 328 renal lesions, 56 enhancing lesions (17%) in 38 patients and 272 non-enhancing lesions (83%) in 86 patients. The threshold for non-enhancing lesions was 0.76 mgI/mL or lower (100% sensitivity, 76% specificity). The threshold for a definite enhancing mass was 1.69 mgI/mL or higher (100% specificity, 78% sensitivity). A total of 77% of indeterminate lesions (>30 HU on PVP CT) in our study could be definitely characterized. Renal lesions can be definitively classified as non-enhancing or enhancing on PVP spectral CT using thresholds of 0.76 mgI/mL or 1.69 mgI/mL, respectively, eliminating the need for multiphase imaging.

Can radiomic analysis of a single-phase dual-energy CT improve the diagnostic accuracy of differentiating enhancing from non-enhancing small renal lesions?

BACKGROUND

The value of dual-energy computed tomography (DECT)-based radiomics in renal lesions is unknown.

PURPOSE

To develop DECT-based radiomic models and assess their incremental values in comparison to conventional measurements for differentiating enhancing from non-enhancing small renal lesions.

MATERIAL AND METHODS

A total of 349 patients with 519 small renal lesions (390 non-enhancing, 129 enhancing) who underwent contrast-enhanced nephrographic phase DECT examinations between June 2013 and January 2020 on multiple DECT platforms were retrospectively recruited. Cohort A included all lesions, while cohort B included Bosniak II-IV and solid enhancing renal lesions. Radiomic models were built with features selected by the least absolute shrinkage and selection operator regression (LASSO). ROC analyses were performed to compare the diagnostic accuracy among conventional and radiomic models for predicting enhancing renal lesions.

RESULTS

The individual iodine concentration (IC), normalized IC, mean attenuation on 75-keV images, radiomic model of iodine images, 75-keV images and a combined model integrating all the above-mentioned features all demonstrated high AUCs for predicting renal lesion enhancement in cohort A (AUCs = 0.934-0.979) as well as in the test dataset (AUCs = 0.892-0.962) of cohort B (P values with Bonferroni correction >0.003). The AUC (0.864) of mean attenuation on 75-keV images was significantly lower than those of other models (all P values ≤0.001) except the radiomic model of 75-keV images (P = 0.038) in the training dataset of cohort B.

CONCLUSION

No incremental value was found by adding radiomic and machine learning analyses to iodine images for differentiating enhancing from non-enhancing renal lesions.

Renal Lesion Characterization by Dual-Layer Dual-Energy CT: Comparison of Virtual and True Unenhanced Images

Background: Prior studies have provided mixed results for the ability to replace true unenhanced (TUE) images with virtual unenhanced (VUE) images when characterizing renal lesions by dual-energy CT. Detector-based dual-layer dual-energy (dlDECT) systems may optimize performance of VUE images for this purpose. Objective: To compare dual-phase dlDECT examinations evaluated using VUE and TUE images in differentiating cystic and solid renal masses. Methods: This retrospective study included 110 patients (mean age, 64.3±11.8 years; 46 women, 64 men) who underwent renal-mass protocol dlDECT between July 2018 and February 2022. TUE, VUE, and nephrographic-phase image sets were reconstructed. Lesions were diagnosed as solid masses by histopathology or MRI. Lesions were diagnosed as cysts by composite criteria reflecting findings from MRI, ultrasound, and the TUE and nephrographic-phase images of the dlDECT examinations. One radiologist measured lesions' attenuation on all dlDECT image sets. Lesion characterization was compared between use of VUE and TUE images, including when considering enhancement ≥20 HU to indicate presence of a solid mass. Results: The analysis included 219 lesions [33 solid masses; 186 cysts (132 simple, 20 septated, 34 hyperattenuating]. TUE and VUE attenuation were significantly different for solid masses (33.4 ± 7.1 HU vs 35.4 ± 8.6 HU, p=.002), simple cysts (10.8±5.6 vs 7.1±8.1 HU, p<.001), and hyperattenuating cysts (56.3±21.0 HU vs 47.6±16.3 HU, p<.001), but not septated cysts (13.6±8.1 HU vs 14.0±6.8 HU, p=.79). Frequency of enhancement ≥20 HU when using TUE and VUE images was 90.9% and 90.9% in solid masses, 0.0% and 9.1% in simple cysts, 15.0% and 10.0% in septated cysts, and 11.8% and 38.2% in hyperattenuating cysts. All solid lesions were concordant in terms of enhancement ≥20 HU when using TUE and VUE images. Twelve simple cysts and nine hyperattenuating cysts showed enhancement ≥20 HU when using VUE but not TUE images. Conclusion: Use of VUE images reliably detected enhancement in solid masses. However, VUE images underestimated attenuation of simple and hyperattenuating cysts, leading to false-positive findings of enhancement by such lesions. Clinical impact: The findings do not support replacement of TUE acquisitions with VUE images when characterizing renal lesions by dlDECT.

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.

Dual-Energy CT Images: Pearls and Pitfalls

Dual-energy CT (DECT) is a tremendous innovation in CT technology that allows creation of numerous imaging datasets by enabling discrete acquisitions at more than one energy level. The wide range of images generated from a single DECT acquisition provides several benefits such as improved lesion detection and characterization, superior determination of material composition, reduction in the dose of iodine, and more robust quantification. Technological advances and the proliferation of various processing methods have led to the availability of diverse vendor-based DECT approaches, each with a different acquisition and image reconstruction process. The images generated from various DECT scanners differ from those from conventional single-energy CT because of differences in their acquisition techniques, material decomposition methods, image reconstruction algorithms, and postprocessing methods. DECT images such as virtual monochromatic images, material density images, and virtual unenhanced images have different imaging appearances, texture features, and quantitative capabilities. This heterogeneity creates challenges in their routine interpretation and has certain associated pitfalls. Some artifacts such as residual iodine on virtual unenhanced images and an appearance of pseudopneumatosis in a gas-distended bowel loop on material-density iodine images are specific to DECT, while others such as pseudoenhancement seen on virtual monochromatic images are also observed at single-energy CT. Recognizing the potential pitfalls associated with DECT is necessary for appropriate and accurate interpretation of the results of this increasingly important imaging tool. Online supplemental material is available for this article. ©RSNA, 2021.

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.

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.

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.

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.