Can We Predict the Grade of Clear Cell Renal Cell Carcinoma from Houns-Field Unit of Renal Lesion on Computerized Tomography Scan, a Retrospective Cross-Sectional Study

Introduction

Renal cell carcinoma (RCC) is a type of urological malignancy that affects approximately 2% of the global population. Imaging modalities, especially computed tomography (CT) scanning, play a critical role in diagnosing RCC. In this study, we investigated whether there is a relationship between tumour grade of clear cell RCC and HU values of renal lesions on CT scan performed before operation.

Materials and Methods

We conducted a retrospective analysis of 123 patients who underwent radical or partial (open or laparoscopic) nephrectomy for clear cell RCC between January 2017 and January 2021. Post-operation histopathological grades were recorded according to World Health Organization (WHO)/International Society of Urological Pathology (ISUP) 2016 grading system and divided into low grade (includes grade 1 and 2) and high grade (grade 3 and 4), and their links to age, sex, smoking habits, tumour size, and HUs of renal lesions were evaluated.

Results

The mean age of the patients studied was 63.02 years old. About 56.9% of the patients were low grade (grade 1 or grade 2), while 43.1% were high grade (grade 3 or 4). The mean tumour size was 6.31 cm. There were no significant differences in tumour grade according to age, sex, or smoking habits. We found a significant relation between tumour grade and HU in the pre-contrast and nephrogenic phases, with p values of 0.001 and 0.037, respectively. On the other hand, there was no significant relation linking the tumour grade to the difference in HU between these phases, where there was a p value of 0.641.

Conclusion

HU in the pre-contrast and nephrogenic phases in addition to tumour size on CT scan have a significant relation to clear cell RCC grade.

Utility of multiparametric renal CT for differentiation of low-grade from high-grade cT1a clear cell renal cell carcinoma

OBJECTIVE

To determine if CT can differentiate low-grade from high-grade clear cell renal cell carcinoma (ccRCC) in cT1a solid ccRCC.

METHODS AND MATERIALS

This retrospective cross-sectional study evaluated 78 < 4 cm solid (>25% enhancing) ccRCC in 78 patients with renal CT within 12 months of surgery between January 2016 and December 2019. Two radiologists (R1/R2), blinded to pathology, independently recorded mass:size, calcification, attenuation and heterogeneity (5-point Likert scale) and recorded a 5-point ccRCC CT Score. Multivariate logistic regression (LR) was performed.

RESULTS

There were 64.1% (50/78) low-grade (5/50 Grade 1 and 45/50 Grade 2) and 35.9% (28/78) high-grade (27/28 Grade 3 and 1/28 Grade 4) tumors.Unenhanced CT attenuation was higher (35.9±10.3 R1 and 34.9±10.7 R2 high-grade vs 29.7±10.2 R1 and 29.5±9.8 R2 low-grade, p=0.01-0.02), absolute corticomedullary phase attenuation ratio (CMphase-ratio; 0.67±0.16 R1 and 0.66±0.16 R2 vs 0.93±0.83 R1 and 0.80±0.33 R2, p=0.04-0.05) and 3-tiered stratification of CMphase-ratio (p=0.02) lower in high-grade tumors.A two-variable LR-model including unenhanced CT attenuation and CM.phase-ratio achieved area under the receiver operator characteristic curve of: 73% (95% confidence intervals 59-86%) and 72% (59-84%) for R1 and R2.ccRCC CT score differed by ccRCC grade (p<0.01 R1, R2) with high-grade tumors occurring most commonly in moderately enhancing ccRCC score 4 (46.4% [13/28] R1 and 54% [15/28]).

CONCLUSION

Among cT1a ccRCC, high-grade tumors have higher unenhanced CT attenuation and are less avidly enhancing.

ADVANCES IN KNOWLEDGE

High-grade ccRCC have higher attenuation (possibly due to less microscopic fat) and lower corticomedullary phase enhancement compared to low-grade tumors. This may result in categorization of high-grade tumors in lower ccRCC diagnostic algorithm categories.

Radiological Features of T1a Renal Cell Carcinoma on Axial Unenhanced Computed Tomography

CT has become a commonly used diagnostic procedure in clinical practice, particularly in emergency healthcare delivery. Accordingly, the increase in CT usage has increased the likelihood of incidental detections (ID) of renal cell carcinomas (RCCs). This article discusses key points and limitations associated with the diagnosis and characterization of T1a RCC (≤4 cm in diameter) and shows how to improvise on the differentiation of T1a RCC with unenhanced CT (UE-CT). We retrospectively reviewed UE-CT findings of cases associated with the histopathologic diagnosis of T1a RCC and examined the discrimination capacity and radiological characteristics with regard to small RCCs (SRCCs). Detection and characterization of T1a RCC based on UE-CT are not easy in many cases due to limitations in CT findings, but there are notable radiological features to facilitate detection and differentiation. The growth pattern is important for the detection of SRCCs. Internal characteristic features (average attenuation, heterogeneity) are useful for the characterization of the RCC. In addition, CT image visualization techniques may help improve the detectability of RCCs on UE-CT. Radiological features are important in detecting SRCCs and facilitating further examination. In this study, we discuss some cases of T1a RCCs and evaluate the radiological characteristics of the tumors seen on UE-CT.

The Role of CT Imaging in Characterization of Small Renal Masses

Small renal masses (SRM) are increasingly detected incidentally during imaging. They vary widely in histology and aggressiveness, and include benign renal tumors and renal cell carcinomas that can be either indolent or aggressive. Imaging plays a key role in the characterization of these small renal masses. While a confident diagnosis can be made in many cases, some renal masses are indeterminate at imaging and can present as diagnostic dilemmas for both the radiologists and the referring clinicians. This review focuses on CT characterization of small renal masses, perhaps helping us understand small renal masses. The following aspects were considered for the review: (a) assessing the presence of fat, (b) assessing the enhancement, (c) differentiating renal tumor subtype, and (d) identifying valuable CT signs.

Development of a Multiparametric Renal CT Algorithm for Diagnosis of Clear Cell Renal Cell Carcinoma Among Small (≤ 4 cm) Solid Renal Masses

BACKGROUND. The MRI clear cell likelihood score predicts the likelihood that a renal mass is clear cell renal cell carcinoma (ccRCC). A CT-based algorithm has not yet been established. OBJECTIVE. The purpose of our study was to develop and evaluate a CT-based algorithm for diagnosing ccRCC among small (≤ 4 cm) solid renal masses. METHODS. This retrospective study included 148 patients (73 men, 75 women; mean age, 58 ± 12 [SD] years) with 148 small (≤ 4 cm) solid (> 25% enhancing tissue) renal masses that underwent renal mass CT (unenhanced, corticomedullary, and nephrographic phases) before resection between January 2016 and December 2019. Two radiologists independently evaluated CT examinations and recorded calcification, mass attenuation in all phases, mass-to-cortex corticomedullary attenuation ratio, and heterogeneity score (score on a 5-point Likert scale, assessed in corticomedullary phase). Features associated with ccRCC were identified by multivariable logistic regression analysis and then used to create a five-tiered CT score for diagnosing ccRCC. RESULTS. The masses comprised 53% (78/148) ccRCC and 47% (70/148) other histologic diagnoses. The mass-to-cortex corticomedullary attenuation ratio was higher for ccRCC than for other diagnoses (reader 1: 0.84 ± 0.68 vs 0.68 ± 0.65, p = .02; reader 2: 0.75 ± 0.29 vs 0.59 ± 0.25, p = .02). The heterogeneity score was higher for ccRCC than other diagnoses (reader 1: 4.0 ± 1.1 vs 1.5 ± 1.6, p < .001; reader 2: 4.4 ± 0.9 vs 3.3 ± 1.5, p < .001). Other features showed no difference. A five-tiered diagnostic algorithm including the mass-to-cortex corticomedullary attenuation ratio and heterogeneity score had interobserver agreement of 0.71 (weighted κ) and achieved an AUC for diagnosing ccRCC of 0.75 (95% CI, 0.68-0.82) for reader 1 and 0.72 (95% CI, 0.66-0.82) for reader 2. A CT score of 4 or greater achieved sensitivity, specificity, and PPV of 71% (95% CI, 59-80%), 79% (95% CI, 67-87%), and 79% (95% CI, 67-87%) for reader 1 and 42% (95% CI, 31-54%), 81% (95% CI, 70-90%), and 72% (95% CI, 56-84%) for reader 2. A CT score of 2 or less had NPV of 85% (95% CI, 69-95%) for reader 1 and 88% (95% CI, 69-97%) for reader 2. CONCLUSION. A five-tiered renal CT algorithm, including the mass-to-cortex corticomedullary attenuation ratio and heterogeneity score, had substantial interobserver agreement, moderate AUC and PPV, and high NPV for diagnosing ccRCC. CLINICAL IMPACT. The CT algorithm, if validated, may represent a useful clinical tool for diagnosing ccRCC.

Evaluation of class II cystic renal masses proposed in Bosniak classification version 2019: a systematic review of supporting evidence

PURPOSE

The Bosniak classification of cystic renal masses version 2019 (v.2019) includes an expanded number of types of masses in class II; such masses are considered benign in clinical practice. Data supporting these additions have not been well-documented. We aim to determine the proportion of malignant or probably malignant renal masses among the types added to Bosniak v.2019 class II.

METHODS

Multiple databases were searched for studies evaluating the proportion of malignant or probably malignant renal masses among new Bosniak v.2019 class II types, four for CT and two for MRI. Risk of bias and applicability was assessed using the QUADAS-2 tool.

RESULTS

Ten studies (2068 renal masses) met inclusion criteria. Among the four added class II types at CT, the proportion of malignancy among (1) 'homogeneous hyperattenuating (≥ 70 HU) masses at unenhanced CT' was 0% (0/32) in three studies; (2) 'homogeneous masses - 9 to 20 HU at unenhanced CT' was 0% (0/1454) in two studies, and (3) 'homogeneous masses 21 to 30 HU at portal-venous phase CT' was 0% (0/454) in four studies. Masses that are homogeneous, have low attenuation, and are too small to characterize on CT had no supportive evidence. Among the two added class II types at MRI, the proportion of malignancy among (1) 'homogeneous masses markedly hyperintense at unenhanced T2-weighted MR imaging (similar to CSF) was 0% (0/72) in one study, and (2) 'homogeneous masses markedly hyperintense at T1-weighted MR imaging (~ 2.5 × renal parenchyma signal intensity)' was 0% (0/32) and 5% (2/37) in two studies. Nine studies were at risk of bias within at least one QUADAS-2 domain.

CONCLUSION

The addition of six types of cystic renal masses to Class II in the Bosniak v.2019 proposal may be justified but based on limited evidence, with no evidence for 'homogeneous low attenuation masses that are too small to characterize' on CT, and thus considering them benign is in part based on expert opinion. Protocol Registration: PROSERO CRD42020196408.

Bosniak classification of cystic renal masses, version 2019: interpretation pitfalls and recommendations to avoid misclassification

The purpose of this review is to describe the potential sources of variability or discrepancy in interpretation of cystic renal masses under the Bosniak v2019 classification system. Strategies to avoid these pitfalls and clinical examples of diagnostic approaches are also presented. Potential pitfalls in the application of Bosniak v2019 are divided into three categories: interpretative, technical, and mass related. An organized, comprehensive review of possible discrepancies in interpreting Bosniak v2019 cystic masses is presented with pictorial examples of difficult clinical cases and proposed solutions. The scheme provided can guide readers to consistent, precise application of the classification system. Radiologists should be aware of the possible sources of misinterpretation of cystic renal masses when applying Bosniak v2019. Knowing which features and types of cystic masses are prone to interpretive errors, in addition to the inherent trade-offs between the CT and MR techniques used to characterize them, can help radiologists avoid these pitfalls.

Bosniak Classification of Cystic Renal Masses, Version 2019: A Pictorial Guide to Clinical Use

Cystic renal masses are commonly encountered in clinical practice. In 2019, the Bosniak classification of cystic renal masses, originally developed for CT, underwent a major revision to incorporate MRI and is referred to as the Bosniak Classification, version 2019. The proposed changes attempt to (a) define renal masses (ie, cystic tumors with less than 25% enhancing tissue) to which the classification should be applied; (b) emphasize specificity for diagnosis of cystic renal cancers, thereby decreasing the number of benign and indolent cystic masses that are unnecessarily treated or imaged further; (c) improve interobserver agreement by defining imaging features, terms, and classes of cystic renal masses; (d) reduce variation in reported malignancy rates for each of the Bosniak classes; (e) incorporate MRI and to some extent US; and (f) be applicable to all cystic renal masses encountered in clinical practice, including those that had been considered indeterminate with the original classification. The authors instruct how, using CT, MRI, and to some extent US, the revised classification can be applied, with representative clinical examples and images. Practical tips, pitfalls to avoid, and decision tree rules are included to help radiologists and other physicians apply the Bosniak Classification, version 2019 and better manage cystic renal masses. An online resource and mobile application are also available for clinical assistance. An invited commentary by Siegel and Cohan is available online. ^©RSNA, 2021.

Utility of T2-weighted MRI to Differentiate Adrenal Metastases from Lipid-Poor Adrenal Adenomas

Purpose

To evaluate T2-weighted MRI features to differentiate adrenal metastases from lipid-poor adenomas.

Materials and Methods

With institutional review board approval, this study retrospectively compared 40 consecutive patients (mean age, 66 years ± 10 [standard deviation]) with metastases to 23 patients (mean age, 60 years ± 15) with lipid-poor adenomas at 1.5- and 3-T MRI between June 2016 and March 2019. A blinded radiologist measured T2-weighted signal intensity (SI) ratio (SI_nodule/SI_{psoas muscle}), T2-weighted histogram features, and chemical shift SI index. Two blinded radiologists (radiologist 1 and radiologist 2) assessed T2-weighted SI and T2-weighted heterogeneity using five-point Likert scales.

Results

Subjectively, T2-weighted SI (P < .001 for radiologist 1 and radiologist 2) and T2-weighted heterogeneity (P < .001, for radiologist 1 and radiologist 2) were higher in metastases compared with adenomas when assessed by both radiologists. Agreement between the radiologists was substantial for T2-weighted SI (Cohen κ = 0.67) and T2-weighted heterogeneity (κ = 0.62). Metastases had higher T2-weighted SI ratio than adenomas (3.6 ± 1.7 [95% confidence interval {CI}: 0.2, 8.2] vs 2.2 ± 1.0 [95% CI: 0.6, 4.3], P < .001) and higher T2-weighted entropy (6.6 ± 0.6 [95% CI: 4.9, 7.5] vs 5.0 ± 0.8 [95% CI: 3.5, 6.6], P < .001). At multivariate analysis, T2-weighted entropy was the best differentiating feature (P < .001). Chemical shift SI index did not differ between metastases and adenomas (P = .748). Area under the receiver operating characteristic curve (AUC) for T2-weighted SI ratio and T2-weighted entropy were 0.76 (95% CI: 0.64, 0.88) and 0.94 (95% CI: 0.88, 0.99). The logistic regression model combining T2-weighted SI ratio with T2-weighted entropy yielded AUC of 0.95 (95% CI: 0.91, 0.99) and did not differ compared with T2-weighted entropy alone (P = .268). There was no difference in logistic regression model accuracy comparing the data by either field strength, 1.5- or 3-T MRI (P > .05).

Conclusion

Logistic regression models combining T2-weighted SI and T2-weighted heterogeneity can differentiate metastases from lipid-poor adenomas. Validation of these preliminary results is required.Keywords: Adrenal, MR-Imaging, UrinarySupplemental material is available for this article.© RSNA, 2020.

Mimics and Pitfalls in Renal Imaging

There are several potential pitfalls that radiologists face when interpreting images of the kidneys. Some result from image acquisition and can arise from the imaging equipment or imaging technique, whereas others are patient related. Another category of pitfalls relates to image interpretation. Some difficulties stem from methods to detect enhancement after contrast administration, whereas others are benign entities that can mimic a renal tumor. Finally, interpretation and diagnosis of fat-containing renal masses may be tricky due to the complexities discerning the pattern of fat within a mass and how that translates to an accurate diagnosis.

Radiomics and Artificial Intelligence for Renal Mass Characterization

Radiomics allows for high throughput extraction of quantitative data from images. This is an area of active research as groups try to capture and quantify imaging parameters and convert these into descriptive phenotypes of organs or tumors. Texture analysis is one radiomics tool that extracts information about heterogeneity within a given region of interest. This is used with or without associated machine learning classifiers or a deep learning approach is applied to similar types of data. These tools have shown utility in characterizing renal masses, renal cell carcinoma, and assessing response to targeted therapeutic agents in metastatic renal cell carcinoma.

Computed Tomography Imaging Characteristics of Histologically Confirmed Papillary Renal Cell Carcinoma-Implications for Ancillary Imaging

Low-attenuation renal lesions on non-contrast computed tomography (CT) are often considered to be benign cysts without need for further imaging. However, the papillary subtype of renal cell carcinoma (RCC) may have similar radiographic characteristics. A single-center retrospective review was therefore performed to identify extirpated papillary RCC (pRCC) specimens with correlation made to preoperative tumor imaging characteristics. A total of 108 pRCC specimens were identified of which 84 (27 type I, 17 type 2, 40 unspecified) had CT imaging available for review. Non-contrast CT was available for 73 tumors with 16 (22%) demonstrating Hounsfield units (HU) measurements fewer than 20 at baseline without differences between papillary subtypes. Mean attenuation following contrast administration was similar between papillary subtypes (45 HU for type 1 pRCC and 49 HU for type 2). This study highlights that pathologically proven pRCC is a heterogeneous entity in terms of density on preoperative CT imaging. A non-contrast CT scan with HU fewer than 20 may not be an adequate evaluation for incidental renal masses, as over 1 in 5 pRCCs demonstrate lower attenuation than this cutoff. Further study is needed to identify the appropriate role of ancillary imaging in the workup of seemingly benign-appearing renal lesions.

Combined Qualitative and Quantitative Assessment of Low-Attenuation Renal Lesions Improves Identification of Renal Malignancy on Noncontrast Computed Tomography

OBJECTIVE

The objective of this study was to assess renal lesions measuring less than 20 Hounsfield units (HU) on noncontrast computed tomography (NCT).

METHODS

Twenty-one (18.1%) of 116 consecutive pathologically proven renal cell carcinomas measured less than 20 HU on NCT and were compared with 40 confirmed benign cysts also measuring less than 20 HU. All lesions were assessed qualitatively (heterogeneous or homogenous) by 3 blinded readers and quantitatively with commercially available textural analysis software. Finally, a combined assessment was performed.

RESULTS

Qualitative assessment performed well (sensitivity, 76%-90%; specificity, 70%-88%). Quantitative assessment revealed mean positive pixels as having the highest performance (area under the curve, 0.912; sensitivity, 90%; specificity, 80% at a cutoff value of 21). The combined assessment, using the mean positive pixel cutoff, improved the sensitivity (reader 1, 100%; reader 2, 95%; and reader 3, 95%).

CONCLUSION

Qualitative and quantitative assessments have relatively good performance, but the combination can nearly eliminate renal cell carcinomas being missed on NCT.

T1a renal cell carcinoma on unenhanced CT: analysis of detectability and imaging features

Background

Increasing use of unenhanced computed tomography (CT) has been associated with the increasing incidental detection of renal cell carcinoma (RCC) at an earlier stage.

Purpose

To evaluate the characteristics in detecting and differentiating T1a RCCs on unenhanced CT.

Material and Methods

We retrospectively reviewed 68 patients with 68 T1a RCCs and 39 benign regions. Two radiologists interpreted the images on unenhanced axial CT and performed a blinded and independent review of T1a RCCs. The readers evaluated the presence of RCC and differentiated the detected lesions.

Results

The consensus of two readers detected 53 (78%) RCCs. Of the 53 detected RCCs, 42 (62%) RCCs were correctly diagnosed and 11 (16%) masses were misdiagnosed as benign. Of the 39 benign regions, 29 (74%) cysts were diagnosed correctly, but 10 (26%) cysts were misdiagnosed as malignant. The following values of the radiologists were obtained by consensus: sensitivity = 61.8% (42/68); specificity = 74.4% (29/39); positive predictive value = 80.8% (42/52); negative predictive value = 55.0% (29/55); accuracy = 66.4% (71/107). The receiver operating characteristic curve of consensus was 0.754. Inter-observer correlation was κ = 0.849. There was a significant difference in tumor size (P = 0.019) and the contour type of tumor (P = 0.0207) between correctly diagnosed RCCs and not correctly diagnosed RCCs.

Conclusion

Our findings showed that tumor size and contour type could affect the detection and differentiation of T1a RCC on unenhanced CT. To detect and differentiate T1a RCC on unenhanced CT is difficult. However, the findings from this study may help detection of RCCs on unenhanced CT.

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.

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.

Contemporary update on imaging of cystic renal masses with histopathological correlation and emphasis on patient management

This article presents an updated review of cystic renal mass imaging. Most cystic renal masses encountered incidentally are benign and can be diagnosed confidently on imaging and require no follow-up. Hyperattenuating masses discovered at unenhanced or single-phase enhanced computed tomography (CT) measuring between 20-70 HU are indeterminate and can be further investigated first by using ultrasound and, then with multi-phase CT or magnetic resonance imaging (MRI); as the majority represent haemorrhagic/proteinaceous cysts (HPCs). Dual-energy CT may improve differentiation between HPCs and masses by suppressing unwanted pseudo-enhancement observed with conventional CT. HPCs can be diagnosed confidently when measuring >70 HU at unenhanced CT or showing markedly increased signal on T1-weighted imaging. Although the Bosniak criteria remains the reference standard for diagnosis and classification of cystic renal masses, histopathological classification and current management has evolved: multilocular cystic renal cell carcinoma (RCC) has been reclassified as a cystic renal neoplasm of low malignant potential, few Bosniak 2F cystic masses progress radiologically during follow-up; RCC with predominantly cystic components are less aggressive than solid RCC; and Bosniak III cystic masses behave non-aggressively. These advances have led to an increase in non-radical management or surveillance of cystic renal masses including Bosniak 3 lesions. Tubulocystic RCC is a newly described entity with distinct imaging characteristics, resembling a pancreatic serous microcystadenoma. Other benign cystic masses including: mixed epithelial stromal tumours (MEST) are now considered in the spectrum of cystic nephroma and angiomyolipoma (AML) with epithelial cysts (AMLEC) resemble a fat-poor AML with cystic components.

Differentiating solid, non-macroscopic fat containing, enhancing renal masses using fast Fourier transform analysis of multiphase CT

OBJECTIVE

To test the feasibility of two-dimensional fast Fourier transforms (FFT)-based imaging metrics in differentiating solid, non-macroscopic fat containing, enhancing renal masses using contrast-enhanced CT images. We quantify image-based intratumoral textural variations (indicator of tumor heterogeneity) using frequency-based (FFT) imaging metrics.

METHODS

In this Institutional Review Board approved, Health Insurance Portability and Accountability Act -compliant, retrospective case-control study, we evaluated 156 patients with predominantly solid, non-macroscopic fat containing, enhancing renal masses identified between June 2009 and June 2016. 110 cases (70%) were malignant RCC, including clear cell, papillary and chromophobe subtypes and, 46 cases (30%) were benign renal masses: oncocytoma and lipid-poor angiomyolipoma. Whole lesions were manually segmented using Synapse 3D (Fujifilm, CT) and co-registered from the multiphase CT acquisitions for each tumor. Pathological diagnosis of all tumors was obtained following surgical resection. Matlab function, FFT2 was used to perform the image to frequency transformation.

RESULTS

A Wilcoxon rank sum test showed that FFT-based metrics were significantly (p < 0.005) different between 1. benign vs malignant renal masses, 2. oncocytoma vs clear cell renal cell carcinoma and 3. oncocytoma vs lipid-poor angiomyolipoma. Receiver operator characteristics analysis revealed reasonable discrimination (area under the curve >0.7, p < 0.05) within these three groups of comparisons.

CONCLUSION

In combination with other metrics, FFT-metrics may improve patient management and potentially help differentiate other renal tumors. Advances in knowledge: We report for the first time that FFT-based metrics can differentiate between some solid, non-macroscopic fat containing, enhancing renal masses using their contrast-enhanced CT data.

Characterization of small (<4cm) solid renal masses by computed tomography and magnetic resonance imaging: Current evidence and further development

Diagnosis of renal cell carcinomas (RCC) subtypes on computed tomography (CT) and magnetic resonance imaging (MRI) is clinically important. There is increased evidence that confident imaging diagnosis is now possible while standardization of the protocols is still required. Fat-poor angiomyolipoma show homogeneously increased unenhanced attenuation, homogeneously low signal on T2-weighted MRI and apparent diffusion coefficient (ADC) map, may contain microscopic fat and are classically avidly enhancing. Papillary RCC are also typically hyperattenuating and of low signal on T2-weighted MRI and ADC map; however, their gradual progressive enhancement after intravenous administration of contrast material is a differentiating feature. Clear cell RCC are avidly enhancing and may show intracellular lipid; however, these tumors are heterogeneous and are of characteristically increased signal on T2-weighted MRI. Oncocytomas and chromophobe tumors (collectively oncocytic neoplasms) show intermediate imaging findings on CT and MRI and are the most difficult subtype to characterize accurately; however, both show intermediately increased signal on T2-weighted with more gradual enhancement compared to clear cell RCC. Chromophobe tumors tend to be more homogeneous compared to oncocytomas, which can be heterogeneous, but other described features (e.g. scar, segmental enhancement inversion) overlap considerably between tumors. Tumor grade is another important consideration in small solid renal masses with emerging studies on both CT and MRI suggesting that high grade tumors may be separated from lower grade disease based upon imaging features.

Diagnostic Accuracy of Unenhanced CT Analysis to Differentiate Low-Grade From High-Grade Chromophobe Renal Cell Carcinoma

OBJECTIVE

The objective of our study was to evaluate tumor attenuation and texture on unenhanced CT for potential differentiation of low-grade from high-grade chromophobe renal cell carcinoma (RCC).

MATERIALS AND METHODS

A retrospective study of 37 consecutive patients with chromophobe RCC (high-grade, n = 13; low-grade, n = 24) who underwent preoperative unenhanced CT between 2011 and 2016 was performed. Two radiologists (readers 1 and 2) blinded to the histologic grade of the tumor and outcome of the patients subjectively evaluated tumor homogeneity (3-point scale: completely homogeneous, mildly heterogeneous, or mostly heterogeneous). A third radiologist, also blinded to tumor grade and patient outcome, measured attenuation and contoured tumors for quantitative texture analysis. Comparisons were performed between high-grade and low-grade tumors using the chi-square test for subjective variables and sex, independent t tests for patient age and tumor attenuation, and Mann-Whitney U tests for texture analysis. Logistic regression models and ROC curves were computed.

RESULTS

There were no differences in age or sex between the groups (p = 0.652 and 0.076). High-grade tumors were larger (mean ± SD, 62.6 ± 34.9 mm [range, 17.0-141.0 mm] vs 39.0 ± 17.9 mm [16.0-72.3 mm]; p = 0.009) and had higher attenuation (mean ± SD, 45.5 ± 8.2 HU [range, 29.0-55.0 HU] vs 35.3 ± 8.5 HU [14.0-51.0 HU]; p = 0.001) than low-grade tumors. CT size and attenuation achieved good accuracy to diagnose high-grade chromophobe RCC: The AUC ± standard error was 0.85 ± 0.08 (p < 0.0001) with a sensitivity of 69.0% and a specificity of 100%. Subjectively, high-grade tumors were more heterogeneous (mildly or markedly heterogeneous: 69.2% [9/13] for reader 1 and 76.9% [10/13] for reader 2; reader 1, p = 0.024; reader 2, p = 0.001) with moderate agreement (κ = 0.57). Combined texture features diagnosed high-grade tumors with a maximal AUC of 0.84 ± 0.06 (p < 0.0001).

CONCLUSION

Tumor attenuation and heterogeneity assessed on unenhanced CT are associated with high-grade chromophobe RCC and correlate well with the histopathologic chromophobe tumor grading system.

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.

Renal cell carcinoma attenuation values on unenhanced CT: importance of multiple, small region-of-interest measurements

OBJECTIVE

Since it has been suggested that benign renal cysts can be diagnosed at unenhanced CT on the basis of homogeneity and attenuations of 20 HU or less, we determined the prevalence of renal cell carcinomas (RCCs) with these characteristics using two different methods of measuring attenuation.

MATERIALS AND METHODS

After IRB approval, two radiologists obtained unenhanced attenuation values of 104 RCCs (mean size 5.6 cm) using a single, large region of interest (ROI), two-thirds the size of the mass. They were then determined if the masses appeared heterogeneous. Of RCCs measuring 20 HU or less, those which appeared homogeneous were re-measured with multiple (6 or more), small (0.6 cm² or smaller) ROIs dispersed throughout the lesion. Masses with attenuations 20 HU or less were compared to those with masses with HU greater than 20 for any differences in demographic data.

RESULTS

Of 104 RCCS, 24 RCC had HU less than 20 using a large ROI. Of these, 21 appeared heterogeneous and 3 appeared homogeneous. Using multiple small ROIs, these three RCCs revealed maximum attenuation values above 20 HU (Range: 26-32 HU). A greater portion of RCCs measuring 20 HU or less using a large ROI were clear cell sub-type. There were no other differences.

CONCLUSIONS

Renal cell carcinoma can measure 20 HU or less at unenhanced CT when a single large ROI is used. While most appear heterogeneous, some may appear homogeneous, but will likely reveal attenuations greater than 20 HU when multiple, small ROIs are used. This knowledge may prevent some RCCs from being misdiagnosed as cysts on unenhanced CT.

CT imaging of solid renal masses: pitfalls and solutions

Computed tomography (CT) remains the first-line imaging test for the characterisation of renal masses; however, CT has inherent limitations, which if unrecognised, may result in errors. The purpose of this manuscript is to present 10 pitfalls in the CT evaluation of solid renal masses. Thin section non-contrast enhanced CT (NECT) is required to confirm the presence of macroscopic fat and diagnosis of angiomyolipoma (AML). Renal cell carcinoma (RCC) can mimic renal cysts at NECT when measuring <20 HU, but are usually heterogeneous with irregular margins. Haemorrhagic cysts (HC) may simulate solid lesions at NECT; however, a homogeneous lesion measuring >70 HU is essentially diagnostic of HC. Homogeneous lesions measuring 20-70 HU at NECT or >20 HU at contrast-enhanced (CE) CT, are indeterminate, requiring further evaluation. Dual-energy CT (DECT) can accurately characterise these lesions at baseline through virtual NECT, iodine overlay images, or quantitative iodine concentration analysis without recalling the patient. A minority of hypo-enhancing renal masses (most commonly papillary RCC) show indeterminate or absent enhancement at multiphase CT. Follow-up, CE ultrasound or magnetic resonance imaging (MRI) is required to further characterise these lesions. Small (<3 cm) endophytic cysts commonly show pseudo-enhancement, which may simulate RCC; this can be overcome with DECT or MRI. In small (<4 cm) solid renal masses, 20% of lesions are benign, chiefly AML without visible fat or oncocytoma. Low-dose techniques may simulate lesion heterogeneity due to increased image noise, which can be ameliorated through the appropriate use of iterative reconstruction algorithms.

Qualitative and Quantitative Imaging Evaluation of Renal Cell Carcinoma Subtypes with Grating-based X-ray Phase-contrast CT

Current clinical imaging methods face limitations in the detection and correct characterization of different subtypes of renal cell carcinoma (RCC), while these are important for therapy and prognosis. The present study evaluates the potential of grating-based X-ray phase-contrast computed tomography (gbPC-CT) for visualization and characterization of human RCC subtypes. The imaging results for 23 ex vivo formalin-fixed human kidney specimens obtained with phase-contrast CT were compared to the results of the absorption-based CT (gbCT), clinical CT and a 3T MRI and validated using histology. Regions of interest were placed on each specimen for quantitative evaluation. Qualitative and quantitative gbPC-CT imaging could significantly discriminate between normal kidney cortex (54 ± 4 HUp) and clear cell (42 ± 10), papillary (43 ± 6) and chromophobe RCCs (39 ± 7), p < 0.05 respectively. The sensitivity for detection of tumor areas was 100%, 50% and 40% for gbPC-CT, gbCT and clinical CT, respectively. RCC architecture like fibrous strands, pseudocapsules, necrosis or hyalinization was depicted clearly in gbPC-CT and was not equally well visualized in gbCT, clinical CT and MRI. The results show that gbPC-CT enables improved discrimination of normal kidney parenchyma and tumorous tissues as well as different soft-tissue components of RCCs without the use of contrast media.