Renal Cyst Pseudoenhancement: Influence of Multidetector CT Reconstruction Algorithm and Scanner Type in Phantom Model

Detection and characterization of urinary stones using material-specific images derived from contrast-enhanced dual-energy CT urography

OBJECTIVE

To determine the accuracy of material-specific images derived from contrast-enhanced dual-energy CT urography (DECTU) in detecting and measuring urinary stones in comparison with that of unenhanced images and its utility in calcified stone differentiation.

METHODS

105 patients with 202 urinary stones (121 had confirmed composition by infrared spectroscopy) underwent triphasic (unenhanced, portal venous (VP) and excretory phase (EP)) DECTU. Material-specific images were derived in VP and EP with calcium-water, calcium-iodine and CaOxalate_Dihydrate (COD)-Hydroxyapatite (HAP) as basis material pairs. Stone number and size were recorded on unenhanced images and VP and EP material-specific images, where stone densities were also measured. Material densities of calcified stones (pure calcium oxalate [pCaO, n = 34], mixed calcium oxalate [mCaO, n = 14], mixed carbonate phosphate [mCaP, n = 70]) were compared and thresholds for differentiating these stones were determined using receiver operating characteristic analysis.

RESULTS

All 202 urinary stones were detected on the unenhanced, calcium (water) and calcium (iodine) images in VP. While the detection rate was significantly decreased to 58 and 64% using calcium (water) and calcium (iodine) images in EP, respectively (all p < 0.001). Stone sizes measured on calcium (iodine) images in VP was similar to that of unenhanced images (10.6 vs 10.7 mm, p > 0.05). Significant differences in material densities were found among pCaO, mCaO and mCaP on COD(HAP) images with AUC of 0.72-0.74 for differentiating these stones.

CONCLUSION

Material-specific images in VP derived from DECTU allow reliably detecting and measuring urinary tract stones in comparison with unenhanced images and can identify calcified stones with moderate diagnostic performance to provide potential 33% dose reduction.

ADVANCES IN KNOWLEDGE

Material-specific images, especially the calcium (iodine) images in VP allow for reliable detection of urinary stones.Stone size measurement should be performed on the calcium (iodine) images in VP.Material density measurements on COD-HAP (VP) material decomposition images can be used to differentiate among pure calcium oxalate, mixed calcium oxalate and mixed carbonate phosphate stones with AUC of 0.72-0.74.

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.

Pseudoenhancement in Cystic Renal Lesions - Impact of Virtual Monoenergetic Images of Photon-Counting Detector CT on Lesion Classification

RATIONALE AND OBJECTIVES

To investigate the impact of virtual monoenergetic images (VMI) from photon-counting detector CT (PCD-CT) on the enhancement and classification of renal cysts.

MATERIALS AND METHODS

Adults with renal cysts (≥7 mm) who received a triphasic examination on a clinical PCD-CT (120 kVp; IQ level 68) between July 2021 and March 2022 were retrospectively identified. Only non-enhancing cysts (enhancement<10 HU between unenhanced and venous phase at 70 keV) were included. VMI from 40 to 190 keV with increments of 10 keV were reconstructed from the venous phase. Enhancement was measured to classify each lesion as non-enhancing (<10 HU), equivocally enhancing (10-19 HU), and definitely enhancing (≥20 HU). Classification changes as a function of VMI were assessed. Pearson correlation coefficient, the Kruskal-Wallis and the Chi-square test were used.

RESULTS

A total of 86 patients (mean age, 74 ± 9 years; 74 male) with 160 non-enhancing renal cysts (17.6 ± 10 mm) were included. CT attenuation of the cysts increased from higher to lower VMI levels with a mean attenuation of 4 ± 11 HU at 190 keV to 36 ± 17 HU at 40 keV. Mean attenuation of the renal parenchyma was 43 ± 4 HU at 190 keV and 414 ± 71 HU at 40 keV. No cyst exhibited enhancement from 70 keV to 190 keV. At 40, 50, and 60 keV, 35% (56/160), 29% (47/160) and 9% (15/160) of cysts showed equivocal and 46% (74/160), 10% (16/160), and 0% (0/160) definite enhancement, respectively. There was no significant influence of size (P=.13), cyst location (P=.9) and BMI (P=.19) on enhancement classification.

CONCLUSION

VMI has a relevant impact on enhancement and classification of renal cysts with misclassification in a large number of cases at energy levels below 70 keV.

Imaging Recommendations for Diagnosis, Staging, and Management of Renal Tumors

Renal cell carcinomas accounts for 2% of all the cancers globally. Most of the renal tumors are detected incidentally. Ultrasound remains the main screening modality to evaluate the renal masses. A multi -phase contrast enhanced computer tomography is must for characterizing the renal lesions. Imaging plays an important role in staging, treatment planning and follow up of renal cancers. In this review , we discuss the imaging guidelines for the management of renal tumors.

Machine-learning classifiers based on non-enhanced computed tomography radiomics to differentiate anterior mediastinal cysts from thymomas and low-risk from high-risk thymomas: A multi-center study

Background

This study aimed to investigate the diagnostic value of machine-learning (ML) models with multiple classifiers based on non-enhanced CT Radiomics features for differentiating anterior mediastinal cysts (AMCs) from thymomas, and high-risk from low risk thymomas.

Methods

In total, 201 patients with AMCs and thymomas from three centers were included and divided into two groups: AMCs vs. thymomas, and high-risk vs low-risk thymomas. A radiomics model (RM) was built with 73 radiomics features that were extracted from the three-dimensional images of each patient. A combined model (CM) was built with clinical features and subjective CT finding features combined with radiomics features. For the RM and CM in each group, five selection methods were adopted to select suitable features for the classifier, and seven ML classifiers were employed to build discriminative models. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of each combination.

Results

Several classifiers combined with suitable selection methods demonstrated good diagnostic performance with areas under the curves (AUCs) of 0.876 and 0.922 for the RM and CM in group 1 and 0.747 and 0.783 for the RM and CM in group 2, respectively. The combination of support vector machine (SVM) as the feature-selection method and Gradient Boosting Decision Tree (GBDT) as the classification algorithm represented the best comprehensive discriminative ability in both group. Comparatively, assessments by radiologists achieved a middle AUCs of 0.656 and 0.626 in the two groups, which were lower than the AUCs of the RM and CM. Most CMs exhibited higher AUC value compared to RMs in both groups, among them only a few CMs demonstrated better performance with significant difference in group 1.

Conclusion

Our ML models demonstrated good performance for differentiation of AMCs from thymomas and low-risk from high-risk thymomas. ML based on non-enhanced CT radiomics may serve as a novel preoperative tool.

Added Value of Magnetic Resonance Over Computed Tomography in Distinguishing Nonneoplastic Complex Thymic Cysts From Malignant Cystic Thymic Neoplasms

PURPOSE

The aim of the study was to evaluate cystic thymic masses by using computed tomography (CT) and magnetic resonance (MR) scoring systems to differentiate nonneoplastic thymic cysts from cystic thymic neoplasms.

METHODS

This retrospective multisite study included adult patients who underwent CT and MR imaging of the chest between 2007 and 2020 with any of the following impressions on cross-sectional imaging studies: "thymic mass with cystic component," "unilocular or multilocular cystic thymic lesion," "complex thymic cyst," "thymic cyst with hemorrhage." Two blinded radiologists reviewed and recorded specific imaging features as well as overall impressions on both CT and MR using a Likert scale scoring system. Data were analyzed, and diagnostic accuracy of CT and MR was compared using areas under the receiver operating characteristic curves (AUC).

RESULTS

Fifty-six patients were included, of which 45 (80%) had benign masses. Total of 21 patients (38%) had indeterminate scores on CT of which 3 (14%) were malignant, while only 6 (11%) had indeterminate scores on MR and 1 was malignant. Magnetic resonance scoring system (AUC, 0.95) performed better than CT scoring system (AUC, 0.86) in distinguishing benign versus malignant lesions (P = 0.06). Lack of enhancement within the mass was completely predictive of benign etiology (P < 0.001). Wall thickness of an enhancing cyst was predictive of malignancy, with AUC 0.93.

CONCLUSIONS

Magnetic resonance yielded higher specificity allowing a larger number of lesions to be confidently assigned a benign diagnosis. This could help in averting unnecessary follow-up, biopsies, or surgery. The authors recommend follow-up imaging with MR for prevascular masses, even those appearing "solid" on CT.

Effect of Ultra-High Resolution CT on Pseudoenhancement in Renal Cysts: A Phantom Experiment and Clinical Study

Background: Ultra-high resolution CT (U-HRCT) allows acquisition using a small detector element size, in turn allowing very high spatial resolutions. The high resolution may reduce partial-volume averaging and thereby renal cyst pseudoenhancement. Objective: To assess the impact of U-HRCT on renal cyst pseudoenhancement. Methods: A phantom was constructed that contained 7-, 15-, and 25-mm simulated cysts within compartments simulating unenhanced and nephrographic-phase renal parenchyma. The phantom underwent two U-HRCT acquisitions using 0.25- and 0.5-mm detector elements, with reconstruction at varying matrices and slice thicknesses. A retrospective study was performed of 36 patients (24 men, 12 women; mean age, 75.7±9.4 years) with 118 renal cysts who underwent renal-mass protocol CT using U-HRCT and the 0.25-mm detector element, with reconstruction at varying matrices and slice thicknesses; detector element size could not be retrospectively adjusted. ROIs were placed to measure cysts' attenuation increase from unenhanced to nephrographic phases (to reflect pseudoenhancement), and SD of unenhanced-phase attenuation (to reflect image noise). Results: In the phantom, attenuation increase was lower for the 0.25 mm than 0.5 mm detector element for the 15-mm cyst (4.6±2.7 HU vs 6.8±2.9 HU, p=.03) and 25-mm cyst (2.3±1.4 HU vs 3.8±1.2 HU, p=.02), but not the 7-mm cyst (p=.72). Attenuation increase was not different between 512×512 and 1024×1024 matrices for any cyst size in the phantom or patients (p>.05). Attenuation increase was not associated with slice thickness for any cyst size in the phantom or for ≥5-to-<10 mm and ≥10 mm cysts in patients (p>.05). For cysts <5 mm in patients, attenuation increase showed decreases with thinner slices (3 mm: 23.7±22.5, 2 mm: 20.2±22.7 HU, 0.5 mm: 11.6±17.5 HU, 0.25 mm: 12.6±19.7 HU; p<.001). Smaller detector element size, increased matrix size, and thinner slices all increased image noise for cysts of all sizes in the phantom and patients (p<.05). Conclusion: U-HRCT may reduce renal cyst pseudoenhancement through a smaller detector element size and, for <5 mm cysts, very thin slices; however, these adjustments result in increased noise. Clinical Impact: Although requiring further clinical evaluation, U-HRCT may facilitate characterization of small cystic renal lesions, thereby reducing equivocal interpretations and follow-up recommendations.

Role of quantitative energy spectrum CT parameters in differentiating thymic epithelial tumours and thymic cysts

AIM

To explore the utility of multiple energy spectrum computed tomography (CT) parameters in distinguishing thymic epithelial tumours (TETs) from thymic cysts among lesions <5 cm in diameter.

MATERIALS AND METHODS

Data pertaining to 56 patients with TETs and thymic cysts <5 cm in diameter were assessed retrospectively. All patients underwent surgical resection and the diagnosis was confirmed histopathologically. Thirty-five patients with TETs (average age, 51.97 years) and 21 patients with thymic cysts (average age, 50.54 years) were included. The region of interest for the lesion on the energy spectrum CT was delineated on the post-processing workstation, and multiple parameters of the energy spectrum CT were obtained. The diagnostic efficacies of the parameters were analysed using receiver operating characteristic (ROC) curves.

RESULTS

To distinguish small TETs from thymic cysts, a single-energy CT value of 60 keV showed good differential diagnostic performance in the arterial phase (cut-off value = 68.42 HU; area under the curve [AUC] = 0.978), a single-energy CT value of 70 keV showed good differential diagnostic performance in the venous phase (cut-off value = 59.77 HU; AUC = 0.956). In the arterial and venous phases, effective atomic numbers of 8.065 and 8.175, respectively, were used as cut-off values to distinguish small TETs from thymic cysts (AUC = 0.972 and AUC = 0.961, respectively). Iodine concentrations of 10.99 and 11.05 were used as cut-off values to distinguish small TETs from thymic cysts (AUC = 0.956 and AUC = 0.924, respectively).

CONCLUSION

According to the present study, energy spectrum CT parameters may have clinical value in the differential diagnosis of TETs and thymic cysts.

The role of imaging in the management of renal masses

The wide availability of cross-sectional imaging is responsible for the increased detection of small, usually asymptomatic renal masses. More than 50 % of renal cell carcinomas (RCCs) represent incidental findings on noninvasive imaging. Multimodality imaging, including conventional US, contrast-enhanced US (CEUS), CT and multiparametric MRI (mpMRI) is pivotal in diagnosing and characterizing a renal mass, but also provides information regarding its prognosis, therapeutic management, and follow-up. In this review, imaging data for renal masses that urologists need for accurate treatment planning will be discussed. The role of US, CEUS, CT and mpMRI in the detection and characterization of renal masses, RCC staging and follow-up of surgically treated or untreated localized RCC will be presented. The role of percutaneous image-guided ablation in the management of RCC will be also reviewed.

MB-FSGAN: Joint segmentation and quantification of kidney tumor on CT by the multi-branch feature sharing generative adversarial network

The segmentation of the kidney tumor and the quantification of its tumor indices (i.e., the center point coordinates, diameter, circumference, and cross-sectional area of the tumor) are important steps in tumor therapy. These quantifies the tumor morphometrical details to monitor disease progression and accurately compare decisions regarding the kidney tumor treatment. However, manual segmentation and quantification is a challenging and time-consuming process in practice and exhibit a high degree of variability within and between operators. In this paper, MB-FSGAN (multi-branch feature sharing generative adversarial network) is proposed for simultaneous segmentation and quantification of kidney tumor on CT. MB-FSGAN consists of multi-scale feature extractor (MSFE), locator of the area of interest (LROI), and feature sharing generative adversarial network (FSGAN). MSFE makes strong semantic information on different scale feature maps, which is particularly effective in detecting small tumor targets. The LROI extracts the region of interest of the tumor, greatly reducing the time complexity of the network. FSGAN correctly segments and quantifies kidney tumors through joint learning and adversarial learning, which effectively exploited the commonalities and differences between the two related tasks. Experiments are performed on CT of 113 kidney tumor patients. For segmentation, MB-FSGAN achieves a pixel accuracy of 95.7%. For the quantification of five tumor indices, the R² coefficient of tumor circumference is 0.9465. The results show that the network has reliable performance and shows its effectiveness and potential as a clinical tool.

Quantitative Thoracic Magnetic Resonance Criteria for the Differentiation of Cysts from Solid Masses in the Anterior Mediastinum

Objective

To evaluate quantitative magnetic resonance imaging (MRI) parameters for differentiation of cysts from and solid masses in the anterior mediastinum.

Materials and Methods

The development dataset included 18 patients from two institutions with pathologically-proven cysts (n = 6) and solid masses (n = 12) in the anterior mediastinum. We measured the maximum diameter, normalized T1 and T2 signal intensity (nT1 and nT2), normalized apparent diffusion coefficient (nADC), and relative enhancement ratio (RER) of each lesion. RERs were obtained by non-rigid registration and subtraction of precontrast and postcontrast T1-weighted images. Differentiation criteria between cysts and solid masses were identified based on receiver operating characteristics analysis. For validation, two separate datasets were utilized: 15 patients with 8 cysts and 7 solid masses from another institution (validation dataset 1); and 11 patients with clinically diagnosed cysts stable for more than two years (validation dataset 2). Sensitivity and specificity were calculated from the validation datasets.

Results

nT2, nADC, and RER significantly differed between cysts and solid masses (p = 0.032, 0.013, and < 0.001, respectively). The following criteria differentiated cysts from solid masses: RER < 26.1%; nADC > 0.63; nT2 > 0.39. In validation dataset 1, the sensitivity of the RER, nADC, and nT2 criteria was 87.5%, 100%, and 75.0%, and the specificity was 100%, 40.0%, and 57.4%, respectively. In validation dataset 2, the sensitivity of the RER, nADC, and nT2 criteria was 90.9%, 90.9%, and 72.7%, respectively.

Conclusion

Quantitative MRI criteria using nT2, nADC, and particularly RER can assist differentiation of cysts from solid masses in the anterior mediastinum.

Distinguishing between Thymic Epithelial Tumors and Benign Cysts via Computed Tomography

Objective

To investigate whether computed tomography (CT) and fluorine-18-labeled fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) may be applied to distinguish thymic epithelial tumors (TETs) from benign cysts in the anterior mediastinum.

Materials and Methods

We included 262 consecutive patients with pathologically proven TETs and benign cysts 5 cm or smaller who underwent preoperative CT scans. In addition to conventional morphological and ancillary CT findings, the relationship between the lesion and the adjacent mediastinal pleura was evaluated qualitatively and quantitatively. Mean lesion attenuation was measured on CT images. The maximum standardized uptake value (SUVmax) was obtained with FDG-PET scans in 40 patients. CT predictors for TETs were identified with multivariate logistic regression analysis. For validation, we assessed the diagnostic accuracy and inter-observer agreement between four radiologists in a size-matched set of 24 cysts and 24 TETs using a receiver operating characteristic curve before and after being informed of the study findings.

Results

The multivariate analysis showed that post-contrast attenuation of 60 Hounsfield unit or higher (odds ratio [OR], 12.734; 95% confidence interval [CI], 2.506–64.705; p = 0.002) and the presence of protrusion from the mediastinal pleura (OR, 9.855; 95% CI, 1.749–55.535; p = 0.009) were the strongest CT predictors for TETs. SUVmax was significantly higher in TETs than in cysts (5.3 ± 2.4 vs. 1.1 ± 0.3; p < 0.001). After being informed of the study findings, the readers' area under the curve improved from 0.872–0.955 to 0.949–0.999 (p = 0.066–0.149). Inter-observer kappa values for protrusion were 0.630–0.941.

Conclusion

Post-contrast CT attenuation, protrusion from the mediastinal pleura, and SUVmax were useful imaging features for distinguishing TETs from cysts in the anterior mediastinum.

Bosniak Classification of Cystic Renal Masses, Version 2019: An Update Proposal and Needs Assessment

Cystic renal cell carcinoma (RCC) is almost certainly overdiagnosed and overtreated. Efforts to diagnose and treat RCC at a curable stage result in many benign neoplasms and indolent cancers being resected without clear benefit. This is especially true for cystic masses, which compared with solid masses are more likely to be benign and, when malignant, less aggressive. For more than 30 years, the Bosniak classification has been used to stratify the risk of malignancy in cystic renal masses. Although it is widely used and still effective, the classification does not formally incorporate masses identified at MRI or US or masses that are incompletely characterized but are highly likely to be benign, and it is affected by interreader variability and variable reported malignancy rates. The Bosniak classification system cannot fully differentiate aggressive from indolent cancers and results in many benign masses being resected. This proposed update to the Bosniak classification addresses some of these shortcomings. The primary modifications incorporate MRI, establish definitions for previously vague imaging terms, and enable a greater proportion of masses to enter lower-risk classes. Although the update will require validation, it aims to expand the number of cystic masses to which the Bosniak classification can be applied while improving its precision and accuracy for the likelihood of cancer in each class.

Imaging for the diagnosis and response assessment of renal tumours

PURPOSE

Imaging plays a key role throughout the renal cell carcinoma (RCC) patient pathway, from diagnosis and staging of the disease, to the assessment of response to therapy. This review aims to summarise current knowledge with regard to imaging in the RCC patient pathway, highlighting recent advances and challenges.

METHODS

A literature review was performed using Medline. Particular focus was paid to RCC imaging in the diagnosis, staging and response assessment following therapy.

RESULTS

Characterisation of small renal masses (SRM) remains a diagnostic conundrum. Contrast-enhanced ultrasound (CEUS) has been increasingly applied in this field, as have emerging technologies such as multiparametric MRI, radiomics and molecular imaging with 99mtechnetium-sestamibi single photon emission computed tomography/CT. CT remains the first-line modality for staging of locoregional and suspected metastatic disease. Although the staging accuracy of CT is good, limitations in determining nodal status persist. Response assessment following ablative therapies remains challenging, as reduction in tumour size may not occur. The pattern of enhancement on CT may be a more reliable indicator of treatment success. CEUS may also have a role in monitoring response following ablation. Response assessments following anti-angiogenic and immunotherapies in advanced RCC is an evolving field, with a number of alternative response criteria being proposed. Tumour response patterns may vary between different immunotherapy agents and tumour types; thus, future response criteria modifications may be inevitable.

CONCLUSION

The diagnosis and characterisation of SRM and response assessment following targeted therapy for advanced RCC are key challenges which warrant further research.

Imaging of Solid Renal Masses

The increase in serendipitous detection of solid renal masses on imaging has not resulted in a reduction in mortality from renal cell carcinoma. Consequently, efforts for improved lesion characterization have been pursued and incorporated into management algorithms for distinguishing clinically significant tumors from those with favorable histology or benign conditions. Although diagnostic imaging strategies have evolved for optimized lesion detection, distinction between benign tumors and both indolent and aggressive malignant neoplasms remain an important diagnostic challenge. Recent advances in cross-sectional imaging have expanded the role of these tests in the noninvasive characterization of solid renal tumors.

Energy-Specific Optimization of Attenuation Thresholds for Low-Energy Virtual Monoenergetic Images in Renal Lesion Evaluation

OBJECTIVE

The purpose of this study was to determine in vitro and in vivo the optimal threshold for renal lesion vascularity at low-energy (40-60 keV) virtual monoenergetic imaging.

MATERIALS AND METHODS

A rod simulating unenhanced renal parenchymal attenuation (35 HU) was fitted with a syringe containing water. Three iodinated solutions (0.38, 0.57, and 0.76 mg I/mL) were inserted into another rod that simulated enhanced renal parenchyma (180 HU). Rods were inserted into cylindric phantoms of three different body sizes and scanned with single- and dual-energy MDCT. In addition, 102 patients (32 men, 70 women; mean age, 66.8 ± 12.9 [SD] years) with 112 renal lesions (67 nonvascular, 45 vascular) measuring 1.1-8.9 cm underwent single-energy unenhanced and contrast-enhanced dual-energy CT. Optimal threshold attenuation values that differentiated vascular from nonvascular lesions at 40-60 keV were determined.

RESULTS

Mean optimal threshold values were 30.2 ± 3.6 (standard error), 20.9 ± 1.3, and 16.1 ± 1.0 HU in the phantom, and 35.9 ± 3.6, 25.4 ± 1.8, and 17.8 ± 1.8 HU in the patients at 40, 50, and 60 keV. Sensitivity and specificity for the thresholds did not change significantly between low-energy and 70-keV virtual monoenergetic imaging (sensitivity, 87-98%; specificity, 90-91%). The AUC from 40 to 70 keV was 0.96 (95% CI, 0.93-0.99) to 0.98 (95% CI, 0.95-1.00).

CONCLUSION

Low-energy virtual monoenergetic imaging at energy-specific optimized attenuation thresholds can be used for reliable characterization of renal lesions.

Expanding the Definition of a Benign Renal Cyst on Contrast-enhanced CT: Can Incidental Homogeneous Renal Masses Measuring 21-39 HU be Safely Ignored?

RATIONALE AND OBJECTIVE

We aimed to determine the frequency and clinical significance of homogeneous renal masses measuring 21-39 Hounsfield units on contrast-enhanced computed tomography (CT).

METHODS

Subjects 40-69 years old undergoing portal-venous-phase contrast-enhanced abdominal CT from January 1, 2006 to December 31, 2010 with slice thickness ≤5 mm and no prior CT or magnetic resonance imaging were identified (n = 1387) for this institutional review board-approved retrospective cohort study. Images were manually reviewed by three radiologists in consensus to identify all circumscribed homogeneous renal masses (maximum of three per subject) ≥10 mm with a measured attenuation of 21-39 Hounsfield units. Exclusion criteria were known renal cancer or imaging performed for a renal indication. The primary outcome was retrospective characterization as a clinically significant mass, defined as a solid mass, a Bosniak IIF/III/IV mass, or extirpative therapy or metastatic renal cancer within 5 years' follow-up.

RESULTS

Eligible masses (n = 74) were found in 5% (63/1387) of subjects. Of those with a reference standard (n = 42), none (0% [95% CI: 0.0%-8.4%]) were determined to be clinically significant.

CONCLUSION

Incidental renal masses on contrast-enhanced CT that are homogeneous and display an attenuation of 21-39 Hounsfield units are uncommon in patients 40-69 years of age, unlikely to be clinically significant, and may not need further imaging evaluation. If these results can be replicated in an independent and larger population, the practical definition of a benign cyst on imaging may be able to be expanded.

Evaluation of the CT Parameters to Suppress Renal Cysts Pseudoenhancement Effect: Influence of the Virtual Monochromatic Spectral Images, the Model-based Iterative Reconstruction Algorithm and the Aperture Size in Phantom Model

PURPOSE

The purpose of this study was to evaluate the effect of the virtual monochromatic spectral images (VMSI) and the model-based iterative reconstruction (MBIR) images, to evaluate the influence of the aperture size (40- and 20-mm beam) on renal pseudoenhancement (PE) compared with the filtered back projection (FBP) images.

METHODS

The renal compartment-CT phantom was filled with iodinated contrast material diluted to the attenuation of 180 Hounsfield units (HU) at 120 kV. The water-filled spherical structures, which simulate cyst, were inserted into the renal compartment. Those diameters were 7, 15 and 25 mm. These were scanned by conventional mode (helical scan, 120 kV-FBP) and dual energy mode. 70 keV-VMSI were reconstructed from the dual energy mode, and MBIR images were reconstructed from conventional mode at 40- and 20-mm aperture. Additionally, the phantom was scanned using non-helical mode with 20-mm aperture, and FBP images were reconstructed. The CT value of the PE for cyst areas was measured for these images.

RESULTS

The CT values of the cysts were 20.0-14.3 HU on the FBP images, 12.8-12.7 HU on the 70 keV-VMSI (PE-inhibition ratio was 36.0-11.2%) and 16.2-14.0 HU on the MBIR images (19.0-2.1%), respectively, at 40-mm aperture. The PE-inhibition ratio scanned by 20-mm aperture was improved by 28.0% with FBP, 32.8% with 70 keV-VMSI and 29.6% with MBIR compared with 40-mm aperture. One of the FBP images with non-helical mode was 11.6 HU.

CONCLUSIONS

The best CT technique to minimize PE was the combination of 70 keV-VMSI and 20-mm aperture.

Superiorized algorithm for reconstruction of CT images from sparse-view and limited-angle polyenergetic data

Recent work in CT image reconstruction has seen increasing interest in the use of total variation (TV) and related penalties to regularize problems involving reconstruction from undersampled or incomplete data. Superiorization is a recently proposed heuristic which provides an automatic procedure to 'superiorize' an iterative image reconstruction algorithm with respect to a chosen objective function, such as TV. Under certain conditions, the superiorized algorithm is guaranteed to find a solution that is as satisfactory as any found by the original algorithm with respect to satisfying the constraints of the problem; this solution is also expected to be superior with respect to the chosen objective. Most work on superiorization has used reconstruction algorithms which assume a linear measurement model, which in the case of CT corresponds to data generated from a monoenergetic x-ray beam. Many CT systems generate x-rays from a polyenergetic spectrum, however, in which the measured data represent an integral of object attenuation over all energies in the spectrum. This inconsistency with the linear model produces the well-known beam hardening artifacts, which impair analysis of CT images. In this work we superiorize an iterative algorithm for reconstruction from polyenergetic data, using both TV and an anisotropic TV (ATV) penalty. We apply the superiorized algorithm in numerical phantom experiments modeling both sparse-view and limited-angle scenarios. In our experiments, the superiorized algorithm successfully finds solutions which are as constraints-compatible as those found by the original algorithm, with significantly reduced TV and ATV values. The superiorized algorithm thus produces images with greatly reduced sparse-view and limited angle artifacts, which are also largely free of the beam hardening artifacts that would be present if a superiorized version of a monoenergetic algorithm were used.

Threshold for Enhancement in Treated Hepatocellular Carcinoma on MDCT: Effect on Necrosis Quantification

OBJECTIVE

The objective of our study was to determine whether the conventionally used enhancement threshold of 10 HU for assessing tumor viability in treated hepatocellular carcinoma (HCC) lesions is valid.

MATERIALS AND METHODS

To distinguish pseudoenhancement from enhancement in a tumor, we used an in vivo model: The attenuation of 54 hepatic cysts during the unenhanced and portal venous phases of MDCT, similar to what may be observed in HCC with central necrosis, was used to determine the threshold for pseudoenhancement. To validate this model, we compared the attenuation value of liver parenchyma in this cohort with that of 22 HCCs during the late arterial phase of enhancement. We tested the effect of this pseudoenhancement on quantifying necrosis in HCC compared with the conventionally used threshold of 10 HU.

RESULTS

Values of enhancing HCC tissue on arterial phase MDCT (mean, 121.3 HU) were comparable with normal liver parenchyma on venous phase MDCT (117.3 HU) (p = 0.27). The threshold of 17.1 HU was the best threshold for the detection of pseudoenhancement in cysts (99% accuracy, 100% sensitivity, and 98% specificity). When this threshold was used instead of the conventional threshold of 10 HU, the mean necrosis proportion of treated HCC increased from 34.0% to 42.6% and the mean viable tumor proportion decreased from 66.0% to 57.4%. The quantification of viable HCC tissue based on 10 HU and the quantification of viable HCC tissue based on 17.1 HU were found to be significantly different (p < 0.0001).

CONCLUSION

The threshold of 17.1 HU may be the appropriate cutoff for nonenhancement in a necrotic HCC. Use of this threshold may potentially affect how response to therapy is quantified and categorized.

Cystic renal masses

PURPOSE

The purpose of the study is to provide an update on the imaging evaluation of cystic renal masses, to review benign and malignant etiologies of cystic renal masses, and to review current controversies and future directions in the management of these lesions.

CONCLUSIONS

Cystic renal masses are relatively common in daily practice. The Bosniak classification is a time-proven method for the imaging classification and management of these lesions. Knowledge of the pathognomonic features of certain benign Bosniak 2F/3 lesions is important to avoid surgery on these lesions (e.g., localized cystic disease, renal abscess). For traditionally surgical Bosniak lesions (Classes 3 and 4), there are evolving data that risk stratification based on patient demographics, imaging size, and appearance may allow for expanded management options including tailored surveillance or ablation, along with the traditional surgical approach.

Renal Masses With Equivocal Enhancement at CT: Characterization With Contrast-Enhanced Ultrasound

OBJECTIVE

The purpose of this article is to retrospectively investigate in two radiology centers the role of contrast-enhanced ultrasound in the characterization of renal masses with equivocal enhancement at CT (i.e., with a density increase of 10-20 HU between unenhanced and contrast-enhanced scans) not characterized with conventional ultrasound modes.

MATERIALS AND METHODS

Forty-seven renal lesions (range, 0.8-7.7 cm; average, 2.6 cm) with equivocal enhancement at CT underwent contrast-enhanced ultrasound using sulfur hexafluoride-filled microbubbles. Examinations were digitally recorded for retrospective blinded evaluation by two radiologists with 20 and 10 years' experience in urologic imaging. Histologic results were available for 30 of 47 (64%) lesions (25 primary malignant tumors, two metastases, and three primary benign lesions). Two lesions increased in size and complexity during the follow-up and were considered malignant. One Bosniak category III and 14 category IIF cysts were stable after a follow-up of at least 3 years and were considered benign. ROC curve analysis was used to assess the capability of contrast-enhanced ultrasound to differentiate benign from malignant lesions.

RESULTS

Twelve likely complex cystic lesions at gray-scale ultrasound were cystic also on contrast-enhanced ultrasound and reference procedures. Eleven of 34 lesions that appeared solid at gray-scale ultrasound were cystic on contrast-enhanced ultrasound and reference procedures. One lesion considered likely solid by one radiologist and possibly cystic by the other was a solid tumor at contrast-enhanced ultrasound and histologic analysis. The diagnostic performance of contrast-enhanced ultrasound to characterize the lesions as benign or malignant was high for both readers (AUC, 0.958 and 0.966, respectively).

CONCLUSION

Contrast-enhanced ultrasound is effective for characterizing renal lesions presenting with equivocal enhancement at CT.

Renal cyst pseudoenhancement: intraindividual comparison between virtual monochromatic spectral images and conventional polychromatic 120-kVp images obtained during the same CT examination and comparisons among images reconstructed using filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction

The purpose of this study was to compare renal cyst pseudoenhancement between virtual monochromatic spectral (VMS) and conventional polychromatic 120-kVp images obtained during the same abdominal computed tomography (CT) examination and among images reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and model-based iterative reconstruction (MBIR). Our institutional review board approved this prospective study; each participant provided written informed consent. Thirty-one patients (19 men, 12 women; age range, 59-85 years; mean age, 73.2 ± 5.5 years) with renal cysts underwent unenhanced 120-kVp CT followed by sequential fast kVp-switching dual-energy (80/140 kVp) and 120-kVp abdominal enhanced CT in the nephrographic phase over a 10-cm scan length with a random acquisition order and 4.5-second intervals. Fifty-one renal cysts (maximal diameter, 18.0 ± 14.7 mm [range, 4-61 mm]) were identified. The CT attenuation values of the cysts as well as of the kidneys were measured on the unenhanced images, enhanced VMS images (at 70 keV) reconstructed using FBP and ASIR from dual-energy data, and enhanced 120-kVp images reconstructed using FBP, ASIR, and MBIR. The results were analyzed using the mixed-effects model and paired t test with Bonferroni correction. The attenuation increases (pseudoenhancement) of the renal cysts on the VMS images reconstructed using FBP/ASIR (least square mean, 5.0/6.0 Hounsfield units [HU]; 95% confidence interval, 2.6-7.4/3.6-8.4 HU) were significantly lower than those on the conventional 120-kVp images reconstructed using FBP/ASIR/MBIR (least square mean, 12.1/12.8/11.8 HU; 95% confidence interval, 9.8-14.5/10.4-15.1/9.4-14.2 HU) (all P < .001); on the other hand, the CT attenuation values of the kidneys on the VMS images were comparable to those on the 120-kVp images. Regardless of the reconstruction algorithm, 70-keV VMS images showed a lower degree of pseudoenhancement of renal cysts than 120-kVp images, while maintaining kidney contrast enhancement comparable to that on 120-kVp images.

Solid renal masses: what the numbers tell us

OBJECTIVE

Solid renal masses are most often incidentally detected at imaging as small (≤ 4 cm) localized lesions. These lesions comprise a wide spectrum of benign and malignant histologic subtypes, but are largely treated with surgical resection given the limited ability of imaging to differentiate among them with consistency and high accuracy. Numerous studies have thus examined the ability of CT and MRI techniques to separate benign lesions from malignancies and to predict renal cancer histologic grade and subtype. This article synthesizes the evidence regarding renal mass characterization at CT and MRI, provides diagnostic algorithms for evidence-based practice, and highlights areas of further research needed to drive imaging-based management of renal masses.

CONCLUSION

Despite extensive study of morphologic and quantitative criteria at conventional imaging, no CT or MRI techniques can reliably distinguish solid benign tumors, such as oncocytoma and lipid-poor angiomyolipoma, from malignant renal tumors. Larger studies are required to validate recently developed techniques, such as diffusion-weighted imaging. Evidence-based practice includes MRI to assess renal lesions in situations where CT is limited and to help guide management in patients who are considered borderline surgical candidates.

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

OBJECTIVE

The objective of our study was to assess the accuracy of iodine-related attenuation and iodine quantification as imaging biomarkers of iodine uptake in renal lesions on a single-phase nephrographic image with dual-energy MDCT.

MATERIALS AND METHODS

Fifty-nine patients (41 men, 18 women; age range, 28-84 years) with 80 renal lesions underwent contrast-enhanced dual-energy CT during the nephrographic phase of enhancement. Renal lesions were characterized as enhancing or nonenhancing on color-coded iodine overlay maps using iodine-related attenuation (in Hounsfield units) and iodine quantification (in milligrams per milliliter). For iodine-related attenuation the iodine uptake thresholds of 15 and 20 HU were tested; a threshold of 0.5 mg/mL was used for iodine quantification. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of iodine-related attenuation and iodine quantification were calculated from chi-square tests of contingency with histopathology or imaging follow-up as the reference standard. The 95% CIs were calculated from binomial expression. Differences in sensitivity and specificity were assessed by means of McNemar analysis.

RESULTS

A significant difference in sensitivity and specificity was found between iodine-related attenuation with the thresholds of 15 HU (sensitivity, 91.4%; specificity, 93.3%; PPV, 91.4%; NPV, 93.3%) and 20 HU (sensitivity, 77.1%; specificity, 100%; PPV, 100%; NPV, 84.9%) (p = 0.008) and between iodine quantification (sensitivity, 100%; specificity, 97.7%; PPV, 97.2%; NPV, 100%) and iodine-related attenuation with a threshold of 20 HU (p = 0.004). No significant difference in sensitivity and specificity was found between iodine quantification and iodine-related attenuation with a threshold of 15 HU.

CONCLUSION

Contrast-enhanced dual-energy MDCT with iodine-related attenuation and iodine quantification allows accurate evaluation of iodine uptake in renal lesions on a single-phase nephrographic image.

Impact of dual-energy multi-detector row CT with virtual monochromatic imaging on renal cyst pseudoenhancement: in vitro and in vivo study

PURPOSE

To investigate whether dual-energy multi-detector row computed tomography (CT) with virtual monochromatic imaging can overcome renal cyst pseudoenhancement in a phantom experiment and a clinical study.

MATERIALS AND METHODS

This retrospective single-center HIPAA-compliant study was approved by the institutional review board, with waiver of informed consent. Four renal compartments inserted into torso phantoms were filled with saline to simulate the unenhanced state and with iodinated solutions to simulate the three levels of renal parenchyma enhancement (140, 180, and 240 HU). Saline-filled spheres simulating renal cysts (15 and 18 mm in diameter) were serially suspended in the renal compartments and imaged with dual-energy and single-energy multi-detector row CT at four different energy levels (80, 100, 120, and 140 kVp). In addition, 28 patients (mean age, 66 years ± 10; mean body mass index, 31.3 kg/m(2) ± 6.2) with 34 intrarenal cysts were included. Virtual monochromatic images were reconstructed in 10-keV increments at energy levels ranging from 40 to 140 keV. Phantom and clinical data were analyzed by using multivariate regression analysis.

RESULTS

In the phantom experiment, all polychromatic image data sets showed pseudoenhancement (postcontrast attenuation increase >10 HU) in all investigated conditions, with a significant effect on cyst size (P <.001), location (P <.001), and renal background attenuation level (P <.001). Virtual monochromatic images at energy levels ranging from 80 to 140 keV did not show pseudoenhancement, with the minimum attenuation increase (mean, 6.1 HU ± 1.6; range, 1.6-7.7 HU) on 80-keV images. In patients, pseudoenhancement never occurred on virtual monochromatic images at energy levels ranging from 90 to 140 keV. Patient body size had a significant effect (P = .007) on selection of the optimal monochromatic energy level.

CONCLUSION

Dual-energy multi-detector row CT with reconstruction of virtual monochromatic images at an optimal energy level can overcome renal cyst pseudoenhancement.

In vivo predictors of renal cyst pseudoenhancement at 120 kVp

OBJECTIVE

The purpose of this article is to assess the effects of various CT, patient, and renal cyst characteristics on the occurrence of pseudoenhancement in in vivo renal mass CT examinations using subtraction MRI as the reference standard.

MATERIALS AND METHODS

Adult patients imaged with 120-kVp standard kernel biphasic renal mass protocol CT and dynamic contrast-enhanced MRI of the abdomen from January 1, 2005, through May 4, 2012, were identified. Those with nonenhancing Bosniak categories I and II cysts on MRI were selected (n = 33 patients; 110 cysts). By treating measured cyst enhancement (nephrographic CT attenuation minus unenhanced CT attenuation) as either a continuous or categoric outcome variable, a variety of CT, patient-level, and renal cyst characteristics were assessed using mixed effect multivariate models.

RESULTS

On univariate assessment, cysts that exhibited pseudoenhancement (> 10 HU) were significantly more endophytic (p = 0.02), significantly smaller (p = 0.0004), and adjacent to significantly higher attenuation renal parenchyma in the nephrographic phase (p = 0.02). On multivariate assessment, cyst diameter (p < 0.0001) and background nephrographic phase parenchymal attenuation (p = 0.003) were the strongest in vivo predictors of pseudoenhancement. The odds of pseudoenhancement occurring increased by 2.14 (95% CI, 1.41-3.23) for every 5-mm decrease in renal cyst diameter and increased by 2.45 (95% CI, 1.41-4.26) for every 25-HU increase in enhanced renal parenchymal attenuation. Endophytic growth was not significant in the multivariate analyses (p = 0.07).

CONCLUSION

Renal cyst size and enhanced renal parenchymal attenuation are better in vivo predictors of pseudoenhancement than is endophytic growth pattern.

Impact of size of region-of-interest on differentiation of renal cell carcinoma and renal cysts on multi-phase CT: preliminary findings

INTRODUCTION

To assess impact of size of regions-of-interest (ROI) on differentiation of RCC and renal cysts using multi-phase CT, with focus on differentiating papillary RCC (pRCC) and cysts given known hypovascularity of pRCC.

METHODS

99 renal lesions (23 pRCC, 47 clear-cell RCC, 7 chromophobe RCC, 22 cysts) underwent multi-phase CT. Subjective presence of visual enhancement was recorded for each lesion. Whole-lesion (WL) ROIs, and small (≤ 5 mm(2)), medium (average size of small and large ROIs), and large (half of lesion diameter) peripherally located partial-lesion (PL) ROIs, were placed on non-contrast and nephrographic phases. Impact of ROI size in separating cysts from all RCC and from pRCC based on increased attenuation between phases was assessed using ROC analysis.

RESULTS

Visual enhancement was perceived in 96% of ccRCC, 61% of pRCC, and 9% of cysts. AUCs for separating all RCC and cysts for WL-ROI and small, medium, and large PL-ROIs were 91%, 96%, 91% and 93%, and among lesions without visible enhancement were 60%, 79%, 67% and 67%. AUCs for separating pRCC and cysts for WL-ROI and small, medium, and large PL-ROIs were 78%, 92%, 82% and 84%, and among lesions without visible enhancement were 64%, 88%, 69% and 69%.

CONCLUSION

Small PL-ROIs had higher accuracy than WL-ROI or other PL-ROIs in separating RCC from cysts, with greater impact in differentiating pRCC from cysts and differentiating lesions without visible enhancement. Thus, when evaluating renal lesions using multi-phase CT, we suggest placing small peripheral ROIs for highest accuracy in distinguishing renal malignancy and benign cysts.

Percutaneous radiofrequency ablation of renal cell carcinomas in patients with von Hippel Lindau disease: indications, techniques, complications, and outcomes

Renal cell carcinoma (RCC) in patients with von Hippel Lindau (VHL) disease tends to be multifocal, bilateral, and recur or develop new tumors after removal. These characteristics make treating hereditary RCCs difficult for urologists or radiologists compared to treating a sporadic RCC. Radiofrequency ablation (RFA) is a minimally-invasive treatment for small hereditary RCCs associated with a low complication rate and a minimal decrease in renal function. No RFA guidelines have been established about what to treat and when and how to ablate RCCs in patients with VHL disease. Besides, reports on complications and treatment outcomes in this patient group are rare. The purpose of this review is to discuss the indications, techniques, complications, and outcomes of RFA in treating RCC in patients with VHL disease.

Usefulness of the virtual monochromatic image in dual-energy spectral CT for decreasing renal cyst pseudoenhancement: a phantom study

OBJECTIVE

The purpose of this study was to determine the effect that dual-energy spectral CT has on renal cyst pseudoenhancement with a renal cyst phantom.

MATERIALS AND METHODS

Two renal compartments within a CT phantom were filled with 40- and 240-HU solutions of diluted contrast material, mimicking the nonenhanced phase and nephrographic phase of MDCT, respectively. A saline-filled tapering cylindric cyst model was used, simulating cysts of varying diameters (range, 0.7-3.0 cm) suspended in the renal compartments. The phantom was scanned using dual-energy CT (DECT) (80 and 140 kVp) and conventional, single-energy CT (120 kVp) with the same 64-MDCT scanner. Attenuation increase was measured for a cyst model within 40- and 240-HU dilutions. We compared the attenuation increase obtained on virtual monochromatic images from DECT with conventional, single-energy MDCT images using a paired Student t test.

RESULTS

Pseudoenhancement occurred in the conventional single-energy CT acquisitions, with water attenuation increase of 42.44 ± 4.03 HU measured at 120 kVp. In virtual monochromatic images of DECT, we observed less pseudoenhancement with water attenuation increase of 21.51 ± 6.18 HU at 70 keV. Both acquisitions yielded a p value less than 0.0001.

CONCLUSION

We achieved less pseudoenhancement of renal cysts with virtual monochromatic images of DECT compared with conventional single-energy CT. This method may be useful when an accurate differentiation between small renal cysts and solid masses is critical.

Dual-source dual-energy CT evaluation of complex cystic renal masses

OBJECTIVE

The purpose of this study was to assess the value of dual-source dual-energy CT in the evaluation of complex cystic renal masses.

SUBJECTS AND METHODS

Seventy patients underwent contrast-enhanced dual-energy CT that included true unenhanced images acquired in single-energy mode, corticomedullary phase images acquired in dual-energy mode, and nephrographic phase images acquired in single-energy mode. Virtual unenhanced, blended weighted-average, and color-coded iodine overlay images were reconstructed. The acceptance level and image quality of virtual and true unenhanced images were evaluated. Contrast enhancement on both true unenhanced or blended weighted-average images and color-coded iodine overlay images was evaluated with both calculation in regions of interest and use of confidence level scales. Radiation dose parameters were estimated.

RESULTS

Virtual unenhanced images of 70 lesions (97.2%) and true unenhanced images of 72 lesions (100%) were judged acceptable (p = 0.5). The mean quality score of virtual unenhanced images was 2.0 ± 0.7 and of true unenhanced images was 1.5 ± 0.5 (p < 0.001). Mean contrast enhancement measured on true unenhanced and blended weighted-average images was 45.9 ± 15.9 HU (range, 21-78 HU) and on color-coded iodine overlay images was 47.3 ± 16.8 HU (range, 22-75 HU) with no significant differences. Enhancement was excluded on color-coded iodine overlay images with a significantly (p < 0.03) higher level of confidence than it was on true unenhanced and blended weighted-average images. The mean dose reduction with use of a combined dual- and single-energy dual-phase CT protocol was 29.1% ± 11.9% (p < 0.001).

CONCLUSION

Dual-source dual-energy CT is a reliable imaging technique in the evaluation of complex cystic renal masses. True unenhanced images can be replaced by virtual unenhanced images with considerable radiation dose reduction. The color-coded iodine overlay technique is a useful tool for both excluding and identifying endocystic enhancement.

[The potential of dual-energy virtual monochromatic imaging in reducing renal cyst pseudoenhancement: a phantom study]

Renal cyst pseudoenhancement, an artifactual increase of computed tomography (CT) attenuation for cysts with increased iodine concentrations in the renal parenchyma, complicates the classification of cysts and may thus lead to the mischaracterization of a benign non-enhancing lesion as an enhancing mass. The purpose of this study was to use a phantom model to assess the ability of dual-energy virtual monochromatic imaging to reduce renal pseudoenhancement. A water-filled cylindrical cyst model suspended in varying concentrations of iodine solution, to simulate varying levels of parenchymal enhancement, was scanned with a dual-energy CT scanner using the following three scanning protocols with different combinations of tube voltage: 80 and 140 kV; 80 and 140 kV with tin filter; and 100 and 140 kV with tin filter. Virtual monochromatic images were then synthesized for each dual-energy scan. Single-energy scan with a tube voltage of 120 kV was also performed to obtain polychromatic images as controls. Mean attenuation values (in Hounsfield units) of cyst proxies were measured on both polychromatic and virtual monochromatic images. Pseudoenhancement was considered to be present when the cyst attenuation level increased by more than 10 HU as the background iodine concentration increased from 0.0% to 0.4%, 1.5%, or 2.5%. Our results revealed that pseudoenhancement was not observed on any of the monochromatic images, but appeared on polychromatic images at a background iodine concentration of 2.5%. We thus conclude that dual-energy virtual monochromatic images have a potential to reduce renal pseudoenhancement.

Plaque imaging with CT coronary angiography: Effect of intra-vascular attenuation on plaque type classification

AIM: To assess the attenuation of non-calcified atherosclerotic coronary artery plaques with computed tomography coronary angiography (CTCA).

METHODS: Four hundred consecutive patients underwent CTCA (Group 1: 200 patients, Sensation 64 Cardiac, Siemens; Group 2: 200 patients, VCT GE Healthcare, with either Iomeprol 400 or Iodixanol 320, respectively) for suspected coronary artery disease (CAD). CTCA was performed using standard protocols. Image quality (score 0-3), plaque (within the accessible non-calcified component of each non-calcified/mixed plaque) and coronary lumen attenuation were measured. Data were compared on a per-segment/per-plaque basis. Plaques were classified as fibrous vs lipid rich based on different attenuation thresholds. A P < 0.05 was considered significant.

RESULTS: In 468 atherosclerotic plaques in Group 1 and 644 in Group 2, average image quality was 2.96 ± 0.19 in Group 1 and 2.93 ± 0.25 in Group 2 (P≥ 0.05). Coronary lumen attenuation was 367 ± 85 Hounsfield units (HU) in Group 1 and 327 ± 73 HU in Group 2 (P < 0.05); non-calcified plaque attenuation was 48 ± 23 HU in Group 1 and 39 ± 21 HU in Group 2 (P < 0.05). Overall signal to noise ratio was 15.6 ± 4.7 in Group 1 and 21.2 ± 7.7 in Group 2 (P < 0.01).

CONCLUSION: Higher intra-vascular attenuation modifies significantly the attenuation of non-calcified coronary plaques. This results in a more difficult characterization between lipid rich vs fibrous type.