Multimodality Imaging Features of Papillary Renal Cell Carcinoma

Objectives: To describe the US, CEUS, CT, and MRI features of papillary renal cell carcinoma (PRCC) and to underline the imaging characteristics that are helpful in the differential diagnosis. Methods: Patients with histologically proven papillary renal cell carcinoma who underwent at least two imaging examinations (US, CEUS, CT, and MRI) were included in the study. Tumor size, homogeneity, morphology, perilesional stranding, contrast enhancement locoregional extension were assessed. A comparison and the characteristics of the imaging features for each imaging modality were analyzed. Results: A total of 27 patients with an histologically confirmed diagnosis of PRCC were included in the study. US was highly accurate in distinguishing solid masses from cystic masses, supporting the differential diagnosis of PRCC, as well as in patients with a poor representation of the solid component. CEUS significantly increased diagnostic accuracy in delineating the solid intralesional component. Furthermore, when using CEUS, in the arterial phase, PRCC exhibited hypo-enhancement, and in the late phase it showed an inhomogeneous and delayed wash-out compared with the surrounding renal parenchyma. At MRI, PRCC showed a marked restiction of DWI and was hypointense in the T2-weighted compared to the renal parenchyma. Conclusions: In our study, the characteristic hypodensity and hypoenhancement of PRCC make CT the weakest method of their recognition, while US/CEUS and MRI are necessary to reach a definitive diagnosis. Knowledge of the appearance of PRCC can support an early diagnosis and prompt management, and radiologists should be aware that PRCC, when detected using CT, may resemble spurious non-septate renal cyst.

Basic Statistics for Radiologists: Part 1-Basic Data Interpretation and Inferential Statistics

A systematic approach to statistical analysis is essential for accurate data interpretation and informed decision-making in the rapidly evolving field of radiology. This review provides a comprehensive overview of the fundamental statistical concepts for radiologists and clinicians. The first part of this series introduces foundational elements such as data types, distributions, descriptive and inferential statistics, hypothesis testing, and sampling methods. These are crucial for understanding the underlying structure of research data. The second part of this series delves deeper into advanced topics, including correlation and causality, regression analysis, survival curves, and the analysis of diagnostic tests using contingency tables and receiver operator characteristic (ROC) curves. These tools are vital for evaluating the efficacy of imaging techniques and drawing valid conclusions from clinical studies. As radiology continues to push the boundaries of technology and therapeutic interventions, mastering these statistical principles will empower radiologists to critically assess literature, conduct rigorous research, and contribute to evidence-based practices. Despite the pivotal role of statistics in radiology, formal training in these methodologies is still limited to a certain extent. This primer aims to bridge that gap, providing radiologists with the necessary tools to enhance diagnostic accuracy, optimize patient outcomes, and advance the field through robust research.

Imaging modalities for characterising T1 renal tumours: A systematic review and meta-analysis of diagnostic accuracy

Objectives

International guidelines recommend resection of suspected localised renal cell carcinoma (RCC), with surgical series showing benign pathology in 30%. Non-invasive diagnostic tests to differentiate benign from malignant tumours are an unmet need. Our objective was to determine diagnostic accuracy of imaging modalities for detecting cancer in T1 renal tumours.

Methods

A systematic review was performed for reports of diagnostic accuracy of any imaging test compared to a reference standard of histopathology for T1 renal masses, from inception until January 2023. Twenty-seven publications (including 2277 tumours in 2044 participants) were included in the systematic review, and nine in the meta-analysis.

Results

Forest plots of sensitivity and specificity were produced for CT (seven records, 1118 participants), contrast-enhanced ultrasound (seven records, 197 participants), [99mTc]Tc-sestamibi SPECT/CT (five records, 263 participants), MRI (three records, 220 participants), [18F]FDG PET (four records, 43 participants), [68Ga]Ga-PSMA-11 PET (one record, 27 participants) and [111In]In-girentuximab SPECT/CT (one record, eight participants). Meta-analysis returned summary estimates of sensitivity and specificity for [99mTc]Tc-sestamibi SPECT/CT of 88.6% (95% CI 82.7%-92.6%) and 77.0% (95% CI 63.0%-86.9%) and for [18F]FDG PET 53.5% (95% CI 1.6%-98.8%) and 62.5% (95% CI 14.0%-94.5%), respectively. A comparison hierarchical summary receiver operating characteristic (HSROC) model did not converge. Meta-analysis was not performed for other imaging due to different thresholds for test positivity.

Conclusion

The optimal imaging strategy for T1 renal masses is not clear. [99mTc]Tc-sestamibi SPECT/CT is an emerging tool, but further studies are required to inform its role in clinical practice. The field would benefit from standardisation of diagnostic thresholds for CT, MRI and contrast-enhanced ultrasound to facilitate future meta-analyses.

Deep Learning Assessment of Small Renal Masses at Contrast-enhanced Multiphase CT

Background Accurate characterization of suspicious small renal masses is crucial for optimized management. Deep learning (DL) algorithms may assist with this effort. Purpose To develop and validate a DL algorithm for identifying benign small renal masses at contrast-enhanced multiphase CT. Materials and Methods Surgically resected renal masses measuring 3 cm or less in diameter at contrast-enhanced CT were included. The DL algorithm was developed by using retrospective data from one hospital between 2009 and 2021, with patients randomly allocated in a training and internal test set ratio of 8:2. Between 2013 and 2021, external testing was performed on data from five independent hospitals. A prospective test set was obtained between 2021 and 2022 from one hospital. Algorithm performance was evaluated by using the area under the receiver operating characteristic curve (AUC) and compared with the results of seven clinicians using the DeLong test. Results A total of 1703 patients (mean age, 56 years ± 12 [SD]; 619 female) with a single renal mass per patient were evaluated. The retrospective data set included 1063 lesions (874 in training set, 189 internal test set); the multicenter external test set included 537 lesions (12.3%, 66 benign) with 89 subcentimeter (≤1 cm) lesions (16.6%); and the prospective test set included 103 lesions (13.6%, 14 benign) with 20 (19.4%) subcentimeter lesions. The DL algorithm performance was comparable with that of urological radiologists: for the external test set, AUC was 0.80 (95% CI: 0.75, 0.85) versus 0.84 (95% CI: 0.78, 0.88) (P = .61); for the prospective test set, AUC was 0.87 (95% CI: 0.79, 0.93) versus 0.92 (95% CI: 0.86, 0.96) (P = .70). For subcentimeter lesions in the external test set, the algorithm and urological radiologists had similar AUC of 0.74 (95% CI: 0.63, 0.83) and 0.81 (95% CI: 0.68, 0.92) (P = .78), respectively. Conclusion The multiphase CT-based DL algorithm showed comparable performance with that of radiologists for identifying benign small renal masses, including lesions of 1 cm or less. Published under a CC BY 4.0 license. Supplemental material is available for this article.

Risk-stratified screening for the early detection of kidney cancer

Earlier detection and screening for kidney cancer has been identified as a key research priority, however the low prevalence of the disease in unselected populations limits the cost-effectiveness of screening. Risk-stratified screening for kidney cancer may improve early detection by targeting high-risk individuals whilst limiting harms in low-risk individuals, potentially increasing the cost-effectiveness of screening. A number of models have been identified which estimate kidney cancer risk based on both phenotypic and genetic data, and while several of the former have been shown to identify individuals at high-risk of developing kidney cancer with reasonable accuracy, current evidence does not support including a genetic component. Combined screening for lung cancer and kidney cancer has been proposed, as the two malignancies share some common risk factors. A modelling study estimated that using lung cancer risk models (currently used for risk-stratified lung cancer screening) could capture 25% of patients with kidney cancer, which is only slightly lower than using the best performing kidney cancer-specific risk models based on phenotypic data (27%-33%). Additionally, risk-stratified screening for kidney cancer has been shown to be acceptable to the public. The following review summarises existing evidence regarding risk-stratified screening for kidney cancer, highlighting the risks and benefits, as well as exploring the management of potential harms and further research needs.

Comparison of aggressiveness in central versus peripheral T1a clear-cell renal cell carcinoma

PURPOSE

This study aimed to estimate the difference between peripheral and central small renal lesions in terms of their oncologic potential.

METHODS

Cross-sectional retrospective analysis of patients with small renal masses (T1a) who underwent surgical treatment between January 2008 and July 2019 at the affiliated hospital. Only patients with ccRCC pathology were included. Cases were divided into 2 groups depending on tumor location (central or peripheral) based on the R.E.N.A.L and local nephrometry scoring. Presence of nodal involvement, distant metastases, ISUP grade and endophytic growth were defined as aggressiveness predictors. Statistical analyses was performed using a standard statistical software (IBM SPPS Statistics Ver. 22), with P < 0.05 considered statistically significant. Associations between tumor location and Fuhrman grade, exo-/endophytic growth, TNM classification, and type of operation were tested using the Pearson χ² test and 1-way ANOVA test.

RESULTS

Patients with centrally located tumors had a higher incidence of clinical and pathological lymph node involvement (P = 0.02, χ2 = 5.1). Patients in both groups had an equal number of distant metastases at the time of diagnosis (P = 0.3, χ2 = 0.8). The operation time was significantly longer in patients with central lesions, which obviously showed higher tumor complexity in this group (P < 0.005). Pathological evaluation revealed differences between ISUP grades in both groups (P < 0.005, χ2 = 29.9). Central masses were characterized by higher aggressiveness, indicating a worse prognosis. Furthermore, the cases in the first group were more often endophytic (P = 0.03, χ2 = 0.9). Nevertheless, this did not affect the surgical strategy in most cases with a tendency toward partial nephrectomy. Eventually, organ-sparing treatment was preferable in both groups (P = 0.13, χ2 = 2.29).

CONCLUSION

Centrally located kidney cancer has showed in present study a higher incidence of high ISUP grade, regional nodal involvement and endophytic growth type. Endophytic growth type was associated with worse ISUP grading. Distribution of ISUP grade was not age depended, thus showing no difference by this criterion, when comparing different age groups. Higher ISUP grade was strongly associated with presence of distant metastases in T1a kidney tumors. Further analysis is needed to investigate aggressiveness of centrally located T1a RCC, as it may influence current conservative management options.

Automatic segmentation framework of X-Ray tomography data for multi-phase rock using Swin Transformer approach

A thorough understanding of the impact of the 3D meso-structure on damage and failure patterns is essential for revealing the failure conditions of composite rock materials such as coal, concrete, marble, and others. This paper presents a 3D XCT dataset of coal rock with 1372 slices (each slice contains 1720 × 1771 pixels in x × y direction). The 3D XCT datasets were obtained by MicroXMT-400 using the 225/320kv Nikon Metris custom bay. The raw datasets were processed by an automatic semantic segmentation method based on the Swin Transformer (Swin-T) architecture, which aims to overcome the issue of large errors and low efficiency for traditional methods. The hybrid loss function proposed can also effectively mitigate the influence of large volume features in the training process by incorporating modulation terms into the cross entropy loss, thereby enhancing the accuracy of segmentation for small volume features. This dataset will be available to the related researchers for further finite element analysis or microstructural statistical analysis, involving complex physical and mechanical behaviors at different scales.

Small Renal Masses: Developing a Robust Radiomic Signature

(1) Background and (2) Methods: In this retrospective, observational, monocentric study, we selected a cohort of eighty-five patients (age range 38-87 years old, 51 men), enrolled between January 2014 and December 2020, with a newly diagnosed renal mass smaller than 4 cm (SRM) that later underwent nephrectomy surgery (partial or total) or tumorectomy with an associated histopatological study of the lesion. The radiomic features (RFs) of eighty-five SRMs were extracted from abdominal CTs bought in the portal venous phase using three different CT scanners. Lesions were manually segmented by an abdominal radiologist. Image analysis was performed with the Pyradiomic library of 3D-Slicer. A total of 108 RFs were included for each volume. A machine learning model based on radiomic features was developed to distinguish between benign and malignant small renal masses. The pipeline included redundant RFs elimination, RFs standardization, dataset balancing, exclusion of non-reproducible RFs, feature selection (FS), model training, model tuning and validation of unseen data. (3) Results: The study population was composed of fifty-one RCCs and thirty-four benign lesions (twenty-five oncocytomas, seven lipid-poor angiomyolipomas and two renal leiomyomas). The final radiomic signature included 10 RFs. The average performance of the model on unseen data was 0.79 ± 0.12 for ROC-AUC, 0.73 ± 0.12 for accuracy, 0.78 ± 0.19 for sensitivity and 0.63 ± 0.15 for specificity. (4) Conclusions: Using a robust pipeline, we found that the developed RFs signature is capable of distinguishing RCCs from benign renal tumors.

Implications of IL-21 in solid tumor therapy

Cancer, the most deadly disease, is known as a recent dilemma worldwide. Presently different treatments are used for curing cancers, especially solid cancers. Because of the immune-enhancing functions of cytokine, IL-21 as a cytokine may have new possibilities to manipulate the immune system in disease conditions, as it stimulates NK and CTL functions and drives IgG antibody production. Indeed, IL-21 has been revealed to elicit antitumor-immune responses in several tumor models. Combining IL-21 with other agents, which target tumor cells, immune-regulatory circuits, or other immune-enhancing molecules enhances this activity. The exciting breakthrough in the results obtained in pre-clinical situations has led to the early outset of present developing clinical trials in cancer patients. In the paper, we have reviewed the function of IL-21 in solid tumor immunotherapy.

Distinguishing lipid-poor angiomyolipoma from renal carcinoma using tumor shape

OBJECTIVES

To validate the "overflowing beer sign" (OBS) for distinguishing between lipid-poor angiomyolipoma (AML) and renal cell carcinoma, and to determine whether it improves the detection of lipid-poor AML when added to the angular interface sign, a previously-validated morphologic feature associated with AML.

METHODS

Retrospective nested case-control study of all 134 AMLs in an institutional renal mass database matched 1:2 with 268 malignant renal masses from the same database. Cross-sectional imaging from each mass was reviewed and the presence of each sign was identified. A random selection of 60 masses (30 AML and 30 benign) was used to measure interobserver agreement.

RESULTS

Both signs were strongly associated with AML in the total population (OBS: OR 17.4 95% CI 8.0-42.5, p < 0.001; angular interface: OR 12.6, 95% CI 5.9-29.7, p < 0.001) and the population of patients excluding those with visible macroscopic fat (OBS: OR 11.2, 95% CI 4.8-28.7, p < 0.001; angular interface: 8.5, 95% CI 3.7-21.1, p < 0.001). In the lipid-poor population, the specificity of both signs was excellent (OBS: 95.6%, 95% CI 91.9%-98%; angular interface: 95.1%, 95% CI 91.3%-97.6%). Sensitivity was low for both signs (OBS: 31.4%, 95% CI 24.0-45.4%; angular interface: 30.5%, 95% CI 20.8%-41.6%). Both signs showed high levels of inter-rater agreement (OBS 90.0% 95% CI 80.5 - 95.9; angular interface 88.6, 95% CI 78.7-94.9) Testing for AML using the presence of either sign in this population improved sensitivity (39.0%, 95% CI 28.4%-50.4%, p = 0.023) without significantly reducing specificity (94.2%, 95% CI 90%-97%, p = 0.2) relative to the angular interface sign alone.

CONCLUSIONS

Recognition of the OBS increases the sensitivity of detection of lipid-poor AML without significantly reducing specificity.

Novel Retroperitoneal Neovascularity Scoring System in Renal Cell Carcinoma Tumor Staging

Purpose: Renal cell carcinoma (RCC) is the most common type of kidney cancer worldwide. Although radiologists assess enhancement patterns of renal tumors to predict tumor pathology report, to our knowledge, no formal scoring system has been created and validated to assess the level of neovascularity in RCC, despite its critical role in cancer metastases. In this study, we characterized and analyzed the level of angiogenesis in tumor-burdened kidneys and their benign counterparts. We then created and validated a scoring scale for neovascularity that can help predict tumor staging for RCC. Methods: After Institutional Review Board approval, the charts of patients who had undergone operation for RCC between January 13, 2014 and February 4, 2020 were retrospectively reviewed for inclusion in this study. Inclusion criteria were a diagnosis of RCC, simple/radical nephrectomy, preoperative contrast-enhanced CT scans, and complete pathology reports. Neovascularity was scored on a scale of 0-4 where 0 = no neovascularity detected, 1 = a single vessel <3 mm wide, 2 = a single vessel ≥3 mm wide, 3 = multiple vessels <3 mm wide, and 4 = multiple vessels ≥3 mm wide. Results: A total of 227 patients were included in this study. Most of the tumor pathology reports were clear cell carcinoma, regardless of tumor staging. The average neovascularity score was 1.07 for pT1x tumors, 2.83 for pT2x tumors, and 3.04 for pT3x tumors. There was a significant difference in neovascularity score between pT1x and pT2x tumors (p = 0.0046), pT1x and pT3x tumors (p < 0.0001), and benign kidneys and kidneys with RCC (p < 0.0001). Conclusion: Our novel vascular scoring system for RCC demonstrates significant correlation with RCC pathological tumor staging. This scoring system may be utilized as part of a comprehensive radiological assessment of renal tumors, potentially improving tumor characterization and clinical decision making.

Targeted Renal Biopsy: Predictors on Imaging

Objectives The renal nephrometry score uses imaging characteristics such as lesion diameter, location, and proximity to hilar vessels to categorize renal masses by complexity for preoperative planning. These characteristics may also be used to determine the best approach to targeted renal biopsy. This study was conducted to investigate the impact of renal lesion characteristics as measured by the renal nephrometry score on the choice of modality used for performing a targeted renal lesion biopsy and increasing the chance of yielding a diagnostic biopsy.

Materials and Methods All targeted computed tomography (CT)/ultrasound-guided renal biopsies performed by our radiology department from January 2017 to February 2020 were reviewed. Radiological characteristics and pathological outcomes were recorded with data on lesion size/ side, location in craniocaudal/anterior–posterior planes, endophytic/exophytic/mixed nature, and skin-lesion distance.

Statistical Analysis Chi-squared tests, multivariate analysis, and t-tests were used in this study.

Results Of the 145 consecutive patients included in the study, 86.2% (125/145) biopsies were diagnostic. About 54.5% (79/145) biopsies were ultrasound-guided, while 45.5% (66/145) were CT-guided. About 62.1% (90/145) biopsies revealed renal cell carcinoma. The highest rate of diagnostic biopsy was in the exophytic, laterally positioned mass either entirely below lower polar or above upper polar line. Ultrasound was preferred for lesions under 4cm and 4 to 7cm (p = 0.06). CT was used for anterior lesions and ultrasound for posterior and lateral lesions (p < 0.001). Of the 20 nondiagnostic biopsies, 7/20 had a repeat biopsy, 7/20 underwent surveillance, 5/20 underwent partial or total nephrectomy, and 1/20 underwent a pathological lymph node biopsy.

Conclusions Our study highlights some factors radiologists should consider when predicting whether CT or ultrasound guidance is more appropriate and the probability of achieving a diagnostic biopsy based on lesion characteristics. At our institution, both modalities achieved high accuracy, although we favored ultrasound in lateral, posterior, and small lesions. These factors should be weighed against local experience and preference.

Diagnosis and Treatment of Small Renal Masses: Where Do We Stand?

PURPOSE OF REVIEW

To present an overview of the current evidence-based studies covering diagnostic and management of SRM.

RECENT FINDINGS

Renal cell carcinoma (RCC) represents 3% of the cancers. Nowadays, partial nephrectomy (PN) represents gold standard treatment. New nephron-sparing approaches such as active surveillance and ablative therapies have been increasingly used as an alternative to surgical intervention. Due to novel comprehension of RCC and widespread use of imaging techniques, diagnosis at early stage in elderly patients has increased. Treatment decision-making should be based on patient and tumour characteristics. With expanding treatment options, the management of SRMs has become a debate and should be adjusted to patient and tumour characteristics. In a shared decision manner, both active surveillance with possible delayed intervention and focal therapy should be discussed with the patient as an alternative to partial nephrectomy.

Kidney Tumor Semantic Segmentation Using Deep Learning: A Survey of State-of-the-Art

Cure rates for kidney cancer vary according to stage and grade; hence, accurate diagnostic procedures for early detection and diagnosis are crucial. Some difficulties with manual segmentation have necessitated the use of deep learning models to assist clinicians in effectively recognizing and segmenting tumors. Deep learning (DL), particularly convolutional neural networks, has produced outstanding success in classifying and segmenting images. Simultaneously, researchers in the field of medical image segmentation employ DL approaches to solve problems such as tumor segmentation, cell segmentation, and organ segmentation. Segmentation of tumors semantically is critical in radiation and therapeutic practice. This article discusses current advances in kidney tumor segmentation systems based on DL. We discuss the various types of medical images and segmentation techniques and the assessment criteria for segmentation outcomes in kidney tumor segmentation, highlighting their building blocks and various strategies.

CT imaging findings of renal epithelioid lipid-poor angiomyolipoma

OBJECTIVES

To identify specific imaging and clinicopathological features of a rare potentially malignant epithelioid variant of renal lipid-poor angiomyolipoma (E-lpAML).

METHODS

A total of 20 patients with E-lpAML and 43 patients with other lpAML were retrospectively included. Multiphase computed tomography (CT) imaging features and clinicopathological findings were recorded. Independent predictors for E-lpAML were identified using multivariate logistic regression and were used to construct a diagnostic score for differentiation of E-lpAML from other lpAML.

RESULTS

The E-lpAML group consisted of 6 men and 14 women (age median ± SD: 39.45 ± 15.70, range: 16.0-68.0 years). E-lpAML tended to appear as hyperdense mass lesions located at the renal sinus (n = 8, 40%) or at the renal cortex (n = 12, 60%), with a "fast-in and slow-out" enhancement pattern (n = 20, 100%), cystic degeneration (n = 18, 90%), "eyeball" sign (n = 11, 55%), and tumor neo-vasculature (n = 15, 75%) on CT. Multivariate logistic regression analysis showed that the independent predictors for diagnosing E-lpAML were cystic degeneration on CT imaging and CT value of the tumor in corticomedullary phase of enhancement. A predictive model was built with the two predictors, achieving an area under the curve (AUC) of 93.5% (95% confidence interval (95%CI): 84.3-98.2%) with a sensitivity of 95.0% (95%CI: 75.1-99.9%) and a specificity of 83.72% (95%CI: 69.3-93.2%).

CONCLUSION

We identified specific CT imaging features and predictors that could contribute to the correct diagnosis of E-lpAML. Our findings should be helpful for clinical management of E-lpAML which could potentially be malignant and may require nephron-sparing surgery while other lpAML tumors which are benign require no intervention.

KEY POINTS

• It is important to differentiate renal epithelioid lipid-poor angiomyolipoma (E-lpAML) from other lpAML because of differences in clinical management. • E-lpAML tumors tend to be large hyperdense tumors in the renal sinus with cystic degeneration and "fast-in and slow-out" pattern of enhancement. • Our CT imaging-based predictive model was robust in its performance for predicting E-lpAML from other lpAML tumors.

Differentiating the clinical and computed tomography imaging features of mixed epithelial and stromal tumors of the kidney to establish a treatment plan

Objective

To differentiate the clinical features and computed tomography imaging features in the two types of mixed epithelial and stromal tumor of the kidney (MESTK) and to establish a treatment plan for the MESTK types.

Methods

Seventeen patients who underwent multidetector computed tomography (MDCT) before surgery and had a pathological diagnosis of MESTK were enrolled. Their clinical information (R.E.N.A.L. nephrometry score (R.E.N.A.L.‐NS), radical nephrectomy (RN), partial nephrectomy (PN), etc.) were collected. The radiological features included renal sinus fat invagination (SFI), maximal diameter (MD), capsule and septa of the tumor, etc., were also analyzed. They were divided into two types according to the MD_solid/MD_tumor ratio (solid type with >60%; cystic type with ≤60%). An independent‐sample t‐test and Fisher exact test were used to assess the differences between the two groups.

Results

MESTKs demonstrated a variable multi‐septate cystic and solid components with a delayed enhancement. There were nine patients for solid type and eight patients for cystic type. Compared with solid type, the lesions in cystic type have larger MD (81.00 ± 37.91 vs. 41.22 ± 24.19, p = 0.020), higher R.E.N.A.L.‐NS (10.03 ± 0.50 vs. 8.95 ± 1.26, p < 0.001), higher RN (75.00% vs. 22.22%, p = 0.015), larger SFI (87.5% vs. 33.3%, p = 0.05), more septa (100% vs. 0%, p < 0.001), and more capsule (100% vs. 11.1%, p < 0.001).

Conclusion

Cystic type MESTK has more hazardous features (such as larger MD, higher R.E.N.A.L.‐NS, more RN, greater SFI, multiple septa) compared with solid type, suggesting that RN is more suitable for cystic type and PN for solid type.

Renal Segmentation Using an Improved U-Net3D Model

Hundreds of thousands of people worldwide are diagnosed with kidney cancer each year, and this disease is more common in developed societies. Approximately 30% of patients with kidney cancer are recognized at the metastatic stage. Segmentation is an important process in the computer-aided treatment planning of kidney diseases. For this reason, more importance should be given to studies focused on segmentation as accurate segmentation is of high importance in the medical sense. This paper focuses on an improved version of the existing U-Net3D models. The aim is to assist physicians struggling with kidney segmentation. The improved U-Net3D model showed better performance than U-Net, U-Net+ResNet, and U-Net++ models, with 97.89% accurate segmentation.

CT-based multi-phase Radiomic models for differentiating clear cell renal cell carcinoma

Background

The aim of the study is to compare the diagnostic value of models that based on a set of CT texture and non-texture features for differentiating clear cell renal cell carcinomas(ccRCCs) from non-clear cell renal cell carcinomas(non-ccRCCs).

Methods

A total of 197 pathologically proven renal tumors were divided into ccRCC(n = 143) and non-ccRCC (n = 54) groups. The 43 non-texture features and 296 texture features that extracted from the 3D volume tumor tissue were assessed for each tumor at both Non-contrast Phase, NCP; Corticomedullary Phase, CMP; Nephrographic Phase, NP and Excretory Phase, EP. Texture-score were calculated by the Least Absolute Shrinkage and Selection Operator (LASSO) to screen the most valuable texture features. Model 1 contains the three most distinctive non-texture features with p < 0.001, Model 2 contains texture scores, and Model 3 contains the above two types of features.

Results

The three models shown good discrimination of the ccRCC from non-ccRCC in NCP, CMP, NP, and EP. The area under receiver operating characteristic curve (AUC)values of the Model 1, Model 2, and Model 3 in differentiating the two groups were 0.748–0.823, 0.776–0.887 and 0.864–0.900, respectively. The difference in AUC between every two of the three Models was statistically significant (p < 0.001).

Conclusions

The predictive efficacy of ccRCC was significantly improved by combining non-texture features and texture features to construct a combined diagnostic model, which could provide a reliable basis for clinical treatment options.

'Hybrid' oncocytoma: collecting duct (Bellini) carcinoma-the peril from this extremely rare intratumoural coexistence

We presented an extremely rare entity of 'hybrid' oncocytoma and collecting duct (Bellini) carcinoma. The intratumoural coexistence of benign and malignant cells may lead to false diagnosis and suboptimal treatment of an aggressive tumour. Diagnosis may be challenging if only based on imaging modalities. Even the established value of targeted renal biopsy may be questioned in such scarce cases. Consequently, active surveillance for small renal tumours shall not considered a widely safe management.

Congenital Anomalies of the Upper Urinary Tract: A Comprehensive Review

The upper urinary tract is the most common human system affected by congenital anomalies. Congenital anomalies of the kidneys and ureters comprise a wide spectrum of disorders ranging from simple variants with no clinical significance to complex anomalies that may lead to severe complications and end-stage renal disease. They may be classified as anomalies of renal form, which are subclassified as structural anomalies (eg, persistent fetal lobulation, hypertrophied column of Bertin, and dromedary hump) and fusion anomalies (eg, horseshoe kidney and pancake kidney); anomalies of renal position (eg, renal malrotation, simple renal ectopia, and crossed renal ectopia) and renal number (eg, renal agenesis and supernumerary kidney); and abnormalities in development of the urinary collecting system (eg, pyelocaliceal diverticulum, megacalycosis, ureteropelvic junction obstruction, duplex collecting system, megaureter, ectopic ureter, and ureterocele). US is usually the first imaging modality used because of its low cost, wide availability, and absence of ionizing radiation. Intravenous urography and voiding cystourethrography are also useful, mainly for characterization of the collecting system and vesicoureteral reflux. However, intravenous urography has been replaced by CT urography and MR urography. These imaging methods not only allow direct visualization of the collecting system but also demonstrate the function of the kidneys, the vascular anatomy, adjacent structures, and complications. Comprehension of congenital anomalies of the upper urinary tract is crucial for an accurate diagnosis and correct management. The authors discuss the spectrum of these anomalies, with emphasis on embryologic development, imaging findings, clinical manifestations, and complications. Online supplemental material is available for this article. ^©RSNA, 2021.

Diagnostic accuracy of urinary aquaporin-1 as a biomarker for renal cell carcinoma

Introduction:

Optimal patient selection plays a vital role in management of renal tumors with the introduction of nephron-sparing approaches and active surveillance. A reliable and accurate diagnostic biomarker will be a useful adjunct to decision-making. We studied the diagnostic accuracy of urinary aquaporin-1 (uAQP-1), an upcoming urinary biomarker, for renal cell carcinoma.

Materials and Methods:

In this prospective biomarker study, urine samples were obtained preoperatively from 36 patients with an imaged renal mass suggestive of RCC and 24 healthy age-matched controls, chosen from among voluntary kidney donors. uAQP-1 concentrations were estimated with a sensitive and specific enzyme-linked immunosorbent assay (ELISA) and normalized by estimation of urinary creatinine. The Mann–Whitney U-test was used to compare differences between any two groups. A receiver operator characteristic (ROC) curve was plotted to analyze the diagnostic accuracy of uAQP-1 for RCC.

Results:

The median uAQP-1 concentration among the cases and controls was 8.78 ng/mg creatinine (interquartile range [IQR]: 5.56–12.67) and 9.52 ng/mg creatinine (IQR: 5.55–12.45), respectively. There was no significant difference in uAQP-1 concentrations between the two groups. ROC analysis showed that, for a cutoff value of 8 ng/mg creatinine, the sensitivity and specificity of uAQP-1 as a diagnostic test were 47.2% and 66.7%, respectively, and area under the curve was 0.52 (95% confidence interval: 0.42–0.62).

Conclusions:

uAQP-1 concentrations did not discriminate between healthy individuals and patients with RCC. The results of this study suggest that uAQP-1 may not be a suitable diagnostic biomarker for RCC in the study population.

The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge

There is a large body of literature linking anatomic and geometric characteristics of kidney tumors to perioperative and oncologic outcomes. Semantic segmentation of these tumors and their host kidneys is a promising tool for quantitatively characterizing these lesions, but its adoption is limited due to the manual effort required to produce high-quality 3D segmentations of these structures. Recently, methods based on deep learning have shown excellent results in automatic 3D segmentation, but they require large datasets for training, and there remains little consensus on which methods perform best. The 2019 Kidney and Kidney Tumor Segmentation challenge (KiTS19) was a competition held in conjunction with the 2019 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) which sought to address these issues and stimulate progress on this automatic segmentation problem. A training set of 210 cross sectional CT images with kidney tumors was publicly released with corresponding semantic segmentation masks. 106 teams from five continents used this data to develop automated systems to predict the true segmentation masks on a test set of 90 CT images for which the corresponding ground truth segmentations were kept private. These predictions were scored and ranked according to their average Sørensen-Dice coefficient between the kidney and tumor across all 90 cases. The winning team achieved a Dice of 0.974 for kidney and 0.851 for tumor, approaching the inter-annotator performance on kidney (0.983) but falling short on tumor (0.923). This challenge has now entered an "open leaderboard" phase where it serves as a challenging benchmark in 3D semantic segmentation.

The role of renal mass biopsy in the management of small renal masses – patterns of use and surgeon opinion

Aims:

Renal mass biopsy (RMB) is advocated to improve management of small renal masses, however there is concern about its clinical utility. This study aimed to elicit opinions about the role of RMB in small renal mass management from surgeons managing renal cell carcinomas (RCC), and examine the frequency of pre-treatment biopsy in those with RCC.

Methods:

All surgeons in two Australian states (Queensland: n = 59 and Victoria: n = 108) who performed nephrectomies for RCC in 2012/2013 were sent questionnaires to ascertain views about RMB. Response rates were 54% for Queensland surgeons and 38% for Victorian surgeons. We used medical records data from RCC patients to determine RMB frequency.

Results:

Most Queensland (81%) and Victorian (59%) surgeons indicated they rarely requested RMB; however 34% of Victorians reported often requesting RMB, compared with no Queensland surgeons. This was consistent with medical records data: 17.6% of Victorian patients with T1a tumours received RMB versus 6.7% of Queensland patients ( p < 0.001). Surgeons’ principal concerns regarding RMB related to sampling reliability (90%) and/or histopathological interpretation (76%).

Conclusions:

Most surgeons report infrequent use of RMB for small renal masses, however we observed practice variation. The principal reasons for infrequent use were concerns about sampling reliability and histopathological interpretation, which may be valid in regions with less access to interventional radiologists and uropathologists. Further evidence is required to define patient groups for whom biopsy results will alter management.

Level of evidence:

Not applicable for this multicentre audit.

Differentiation of Small (≤ 4 cm) Renal Masses on Multiphase Contrast-Enhanced CT by Deep Learning

OBJECTIVE. This study evaluated the utility of a deep learning method for determining whether a small (≤ 4 cm) solid renal mass was benign or malignant on multiphase contrast-enhanced CT. MATERIALS AND METHODS. This retrospective study included 1807 image sets from 168 pathologically diagnosed small (≤ 4 cm) solid renal masses with four CT phases (unenhanced, corticomedullary, nephrogenic, and excretory) in 159 patients between 2012 and 2016. Masses were classified as malignant (n = 136) or benign (n = 32). The dataset was randomly divided into five subsets: four were used for augmentation and supervised training (48,832 images), and one was used for testing (281 images). The Inception-v3 architecture convolutional neural network (CNN) model was used. The AUC for malignancy and accuracy at optimal cutoff values of output data were evaluated in six different CNN models. Multivariate logistic regression analysis was also performed. RESULTS. Malignant and benign lesions showed no significant difference of size. The AUC value of corticomedullary phase was higher than that of other phases (corticomedullary vs excretory, p = 0.022). The highest accuracy (88%) was achieved in corticomedullary phase images. Multivariate analysis revealed that the CNN model of corticomedullary phase was a significant predictor for malignancy compared with other CNN models, age, sex, and lesion size. CONCLUSION. A deep learning method with a CNN allowed acceptable differentiation of small (≤ 4 cm) solid renal masses in dynamic CT images, especially in the corticomedullary image model.

Role of Interface Sign and Diffusion-Weighted Magnetic Resonance Imaging in Differential Diagnosis of Exophytic Renal Masses

PURPOSE

We aimed to investigate the role of interfaces of exophytic solid and cystic renal masses on magnetic resonance imaging (MRI) and the added value of diffusion-weighted imaging in differentiating benign from malignant lesions.

METHODS

The Institutional Review Board approved this retrospective study, and informed consent was waived. A total of 265 patients (109 [41%] women and 156 [59%] men) with a mean age of 57 ± 12 (standard deviation) years were enrolled in this study. Preoperative MRI (n = 238) examinations of patients with solid or cystic renal masses and MRI (n = 27) examinations of patients with Bosniak IIF cysts without progression were reviewed. Solid/cystic pattern, interface types and apparent diffusion coefficient (ADC) values were recorded by 2 radiologists. The diagnostic performance of combining normalized ADC values with interface sign were evaluated.

RESULTS

Among 265 renal lesions (109 cystic and 156 solid), all malignant lesions (n = 192) had a round interface. No malignant lesions showed an angular interface. For prediction of benignity in cystic lesions, sensitivity (82.86% vs 56.16%), negative predictive value (92.50% vs 85.71%), and accuracy (94.50% vs 87.92%) ratios of angular interface were higher compared to all (solid plus cystic) lesions. The best normalized ADC cutoff values for predicting malignancy in lesions with round interface were as follows: for all (solid plus cystic), ≤ 0.75 (AUROC = 0.804); solid, ≤ 0.6 (AUROC = 0.819); and cystic, ≤ 0.8 (AUROC = 0.936).

CONCLUSIONS

Angular interface can be a predictor of benignity for especially cystic renal masses. The evaluation of interface type with normalized ADC value can be an important clue in differential diagnosis especially in patients avoiding contrast.

Renal solitary fibrous tumor/hemangiopericytoma: computed tomography findings and clinicopathologic features

PURPOSE

To retrospectively characterize the clinical, pathological, and computed tomography (CT) findings of renal solitary fibrous tumor/hemangiopericytoma (rSFT/HPC).

METHODS

Twelve patients with rSFT/HPCs were enrolled. The CT findings and clinicopathological features were retrospectively reviewed.

RESULTS

This study included six male and six female patients (median age: 47; age range: 20-82 years). Eight benign (grade I) and four malignant (grade III) rSFT/HPCs were identified. Of the 12 lesions, 10 were in the renal sinus near the renal pelvis, while two replaced the whole kidney. Five lesions were well-defined, five were partially ill-defined, and two were ill-defined. Mild (5/12) and intermediate (1/12) hydronephrosis was observed. On the unenhanced CT images, ten tumors showed slightly higher density when compared to the normal renal parenchyma, and two masses were isodense to hypodense. After intravenous contrast medium injection, three enhancement patterns were observed, including "prolonged enhancement" (PE) (6/12), "gradual enhancement" (4/12), and "early washout" (2/12). A central fibrous scar was found in five patients. Compared to the grade I lesions, the grade III rSFT/HPC lesions tended to be larger (maximal diameter > 10 cm) and more heterogeneous with a higher incidence of the PE pattern.

CONCLUSIONS

We have shown that rSFT/HPCs usually arise from the renal sinus, and present as lobulated, slightly hyperdense, gradually enhancing soft tissue masses. CT findings, including large size, heterogeneity, and the PE pattern, may assist in the pre-operative identification of malignant grade III rSFT/HPCs.

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.

Differentiation of Predominantly Solid Enhancing Lipid-Poor Renal Cell Masses by Use of Contrast-Enhanced CT: Evaluating the Role of Texture in Tumor Subtyping

OBJECTIVE

The purpose of this study was to assess the accuracy of a panel of texture features extracted from clinical CT in differentiating benign from malignant solid enhancing lipid-poor renal masses.

MATERIALS AND METHODS

In a retrospective case-control study of 174 patients with predominantly solid nonmacroscopic fat-containing enhancing renal masses, 129 cases of malignant renal cell carcinoma were found, including clear cell, papillary, and chromophobe subtypes. Benign renal masses-oncocytoma and lipid-poor angiomyolipoma-were found in 45 patients. Whole-lesion ROIs were manually segmented and coregistered from the standard-of-care multiphase contrast-enhanced CT (CECT) scans of these patients. Pathologic diagnosis of all tumors was obtained after surgical resection. CECT images of the renal masses were used as inputs to a CECT texture analysis panel comprising 31 texture metrics derived with six texture methods. Stepwise logistic regression analysis was used to select the best predictor among all candidate predictors from each of the texture methods, and their performance was quantified by AUC.

RESULTS

Among the texture predictors aiding renal mass subtyping were entropy, entropy of fast-Fourier transform magnitude, mean, uniformity, information measure of correlation 2, and sum of averages. These metrics had AUC values ranging from good (0.80) to excellent (0.98) across the various subtype comparisons. The overall CECT-based tumor texture model had an AUC of 0.87 (p < 0.05) for differentiating benign from malignant renal masses.

CONCLUSION

The CT texture statistical model studied was accurate for differentiating benign from malignant solid enhancing lipid-poor renal masses.

Imaging Protocols for Active Surveillance in Renal Cell Carcinoma

PURPOSE OF REVIEW

To review the growth kinetics of small renal masses and available imaging modalities for mass characterization and surveillance, highlight current organizational recommendations for the active surveillance of small renal masses, and discuss the most recently reported oncological outcomes of patients as they relate to various surveillance imaging protocols and progression to delayed intervention.

RECENT FINDINGS

Overall, organizational guideline recommendations are broad and lack specifics regarding timing and modality for follow-up imaging of small renal masses. Additionally, despite general consensus in the literature about certain criteria to trigger delayed intervention, there exist no formal guidelines. Active surveillance of small renal masses is an acceptable management strategy for patients with prohibitive surgical risk; however, standardized imaging protocols for surveillance are lacking, as are randomized, prospective trials to evaluate the ideal follow-up protocol.

The Probability of Aggressive Versus Indolent Histology Based on Renal Tumor Size: Implications for Surveillance and Treatment

BACKGROUND

While the probability of malignant versus benign histology based on renal tumor size has been described, this alone does not sufficiently inform decision-making in the modern era since indolent malignant tumors can be managed with active surveillance.

OBJECTIVE

To characterize the probability of aggressive versus indolent histology based on radiographic tumor size.

DESIGN, SETTING, AND PARTICIPANTS

We evaluated patients who underwent radical or partial nephrectomy at Mayo Clinic for a pT1-2, pNx/0, M0 solid renal tumor between 1990 and 2010. Pathology was reviewed by one genitourinary pathologist. High-grade clear-cell renal cell carcinoma (RCC), high-grade papillary RCC, collecting duct RCC, translocation-associated RCC, hereditary leiomyomatosis RCC, unclassified RCC, and malignant non-RCC tumors were all considered aggressive, as well as any tumors demonstrating coagulative necrosis (except low-grade papillary RCC) or sarcomatoid differentiation. The remaining benign and malignant tumors were considered indolent.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Cancer-specific survival (CSS) was estimated using the Kaplan-Meier method. Logistic regression models were used to estimate the probability of malignant and aggressive histology based on tumor size. Sex-stratified analyses were also performed.

RESULTS AND LIMITATIONS

Of the 2650 patients included, there were 1860 patients with indolent tumors (300 benign; 1560 malignant) and 790 with aggressive tumors. The 10-yr CSS was 96% for indolent malignant tumors and 81% for aggressive malignant tumors. The predicted percentages of any malignant histology as well as aggressive histology increased with tumor size. Specifically, 2cm, 3cm, and 4cm tumors have an estimated 84%, 87%, and 88% likelihood of malignancy, respectively, and an 18%, 24%, and 29% likelihood of aggressive histology, respectively. For any given tumor size, men had a greater chance of aggressive histology than women. Potential limitations of this observational surgical cohort include selection bias.

CONCLUSIONS

We present tumor size-based estimates of the probability of aggressive histology for renal masses. This information should be useful for initial patient counseling and management.

PATIENT SUMMARY

Active surveillance is an option for kidney masses, even if they are malignant. Beyond knowing whether the mass is benign or cancer, it is important to know whether or not it is an aggressive tumor. This study presents tumor size-specific and sex-specific estimates of the probability of cancer overall and aggressive cancer among patients with a kidney mass in order to aid with initial decision-making.

Two in One: Epithelioid angiomyolipoma within a classic kidney angiomyolipoma - a case report

Background

Epithelioid angiomyolipoma is defined as potentially malignant mesenchymal neoplasm, characterized by proliferating epithelioid cells, whereas classic angiomyolipoma, composed of fat, smooth muscle cells and dysmorphic vessels, is defined as a potentially benign. The usual or classic angiomyolipoma is often found incidentally on imaging studies, relatively easily identified due to the presence of fat, in contrast to the epithelioid angiomyolipoma that can pose diagnostic challenges.

Case presentation

We report a 51-year-old female patient in which an ultrasonography examination showed a solid mass close to the right renal pelvis with hypoechoic and hyperechoic areas. A differential diagnosis of atypical sinus lipomatosis, lipoma and a transitional cell carcinoma was postulated whereas in a subsequent computed tomography a classic angiomyolipoma was postulated. A re-examination by contrast enhanced ultrasound revealed a striking perfusion difference of the hypoechoic and hyperechoic areas. The hypoechoic area showed homogenous and prolonged enhancement whereas the hypoechoic area displayed a marked slower contrast material flooding and a relatively rapid wash out. The histological analysis from the biopsy of the hyperechoic area showed a classic angiomyolipoma, whereas the sample of the hypoechoic central portion revealed an epithelioid angiomyolipoma. A nephrectomy was performed because of the malignant potential of the epithelioid variant of the angiomyolipoma.

Conclusions

A solid kidney mass with two sharply defined parts, one-part compatible with a classical angiomyolipoma and the other being suspected of carcinoma, is rare, but also illustrative and instructive. The combination of different imaging modalities in the work up of a solid renal mass facilitated to discriminate benign from malignant areas.

Are growth patterns on MRI in small (< 4 cm) solid renal masses useful for predicting benign histology?

PURPOSE

To evaluate previously described growth patterns in < 4 cm solid renal masses.

MATERIALS AND METHODS

With IRB approval, 63 renal cell carcinomas (RCC; clear cell n = 22, papillary n = 28, chromophobe n = 13) and 36 benign masses [minimal-fat (mf) angiomyolipoma (AML) n = 13, oncocytoma n = 23) from a single institution were independently evaluated by two blinded radiologists (R1/R2) using T2-weighted MRI for (1) the angular interface sign (AIS), (2) bubble-over sign (BOS), (3) percentage (%) exophytic growth and (4) long-to-short axis ratio. Comparisons were performed using ANOVA, chi-square and multi-variate regression.

RESULTS

AIS was present in 11.1% (7/63) -9.5% (6/63) R1/R2 RCC compared to 13.9% (5/36) -19.4% (7/36) R1/R2 benign masses (p = 0.68 and 0.16). BOS was present in 11.1% (7/63) -3.2% (2/63) R1/R2 RCC compared to 16.7% (6/36) -8.3% (3/36) R1/R2 benign masses (p = 0.432 and 0.261). Agreement was moderate (K = 0.50 and 0.55). mf-AML [66 ± 32% (range 0-100%)] and oncocytoma [53 ± 26% (0-90%)] had larger % exophytic growth compared to RCC [32 ± 23% (0-80%)] (p < 0.001). No RCC had 90-100% exophytic growth, present in 38.5% (5/13) mf-AMLs and 17.4% (4/23) oncocytomas. The long-to-short axis did not differ between groups (p = 0.053).

CONCLUSIONS

Benign masses show greater % exophytic growth whereas other growth patterns are not useful. Future studies evaluating % exophytic growth using multi-variate MR analysis in renal masses are required.

KEY POINTS

• Greater exophytic growth is associated with benignity among solid renal masses. • Only minimal fat AMLs and oncocytomas had 90-100% exophytic growth. • The angular interface sign was not useful to differentiate benign masses from RCC. • The bubble-over sign was not useful to differentiate benign masses from RCC. • Subjective analysis of growth patterns had fair-to-moderate agreement.

Modern Pathologic Diagnosis of Renal Oncocytoma

Oncocytoma is a well-defined benign renal tumor, with classic gross and histologic features, including a tan or mahogany-colored mass with central scar, microscopic nested architecture, bland cytology, and round, regular nuclei with prominent central nucleoli. As a result of variations in this classic appearance, difficulty in standardizing diagnostic criteria, and entities that mimic oncocytoma, such as eosinophilic variant chromophobe renal cell carcinoma and succinate dehydrogenase-deficient renal cell carcinoma, pathologic diagnosis remains a challenge. This review addresses the current state of pathologic diagnosis of oncocytoma, with emphasis on modern diagnostic markers, areas of controversy, and emerging techniques for less invasive diagnosis, including renal mass biopsy and advanced imaging.

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.

Persistent hematuria caused by renal cell carcinoma after aortic valve replacement and warfarin therapy

Hematuria is a common finding in renal cell carcinoma, and persistent hematuria, even in those receiving anticoagulation, warrants workup. We present a case of a patient with persistent hematuria who was found to have a renal mass that was not evident on renal ultrasound and computed tomography of the abdomen and pelvis but was seen on magnetic resonance imaging.

Persistent fetal lobulation of kidney mimicking renal tumour

Renal pseudotumour is a term coined to describe conditions of renal anatomic variants that simulate focal renal pathology like a tumour on ultrasonography. These include persistent fetal lobulation, hypertrophy of Bertin columns and dromedary humps. We report a case of a 30-year-old nulliparous woman who was managed in gynaecology clinic for menorrhagia and was subsequently referred to us for management of recurrent urinary tract infections. The clinical examination was normal and on ultrasound scan, she was found to have multiple enlarged heterogeneous solid masses in both kidneys with significantly increased vascularity, suspicious for neoplastic lesions. She subsequently underwent a CT urogram and her case was discussed in uro-radiology meeting where a diagnosis of persistent fetal lobulation was made excluding other diagnoses. She was managed conservatively. We also present grey scale and Doppler ultrasound and CT urogram findings of this condition along with the literature review.

Voxel-based whole-lesion enhancement parameters: a study of its clinical value in differentiating clear cell renal cell carcinoma from renal oncocytoma

PURPOSE

The purpose of this study was to compare whole-lesion (WL) enhancement parameters to single region of interest (ROI)-based enhancement in discriminating clear cell renal cell carcinoma (ccRCC) from renal oncocytoma.

MATERIALS AND METHODS

In this IRB-approved retrospective study, the surgical database was queried to derive a cohort of 94 postnephrectomy patients with ccRCC or oncocytoma (68 ccRCC, 26 oncocytoma), who underwent preoperative multiphase contrast-enhanced computed tomography (CECT) between June 2009 and August 2013. CT acquisitions were transferred to a three-dimensional workstation, and WL ROIs were manually segmented. WL enhancement and histogram distribution parameters skewness, kurtosis, standard deviation (SD), and interquartile range (IQR) were calculated. WL enhancement parameters were compared to single ROI-based enhancement using receiver operating characteristic (ROC) analysis.

RESULTS

Oncocytoma had significantly higher WL enhancement than ccRCC in nephrographic (mean, p = 0.02; median, p = 0.03) and excretory phases (mean, p = 0.03; median p < 0.01). ccRCC had significantly higher kurtosis than oncocytoma in corticomedullary (p = 0.03) and excretory phases (p < 0.01), and significantly higher SD and IQR than oncocytoma in all postcontrast phases: corticomedullary (SD, p = 0.02; IQR, p < 0.01), nephrographic (SD, p = 0.01; IQR, p = 0.03), and excretory (SD, p < 0.01; IQR, p < 0.01). When compared to single ROI-based enhancement, WL enhancement alone did not demonstrate a statistical advantage in discriminating between ccRCC and oncocytoma (area under ROC curve of 0.78 and 0.72 respectively), but when combined with histogram distribution parameters (area under ROC curve of 0.86), it did demonstrate a slight improvement.

CONCLUSION

Our study suggests that voxel-based WL enhancement parameters provide only a slight improvement over single ROI-based enhancement techniques in differentiating between ccRCC and renal oncocytoma.

Contrast-Enhanced Ultrasonography with Quantitative Analysis allows Differentiation of Renal Tumor Histotypes

Totally 85 patients with 93 renal lesions who underwent contrast-enhanced ultrasound (CEUS) were retrospectively studied with quantitative analysis to evaluate its value in the differential diagnosis of renal tumor histotypes. CEUS characteristics were analysed including the enhancement patterns, peak intensity, homogeneity of enhancement, and pseudocapsule. Quantitative parameters of peak intensity (P) and time to peak (TP) were measured with QontraXt software, and the index “relative enhancement percentage” ΔP% and “difference in TP between tumor and cortex” ΔTP were used to quantify the CEUS features of renal tumors. There are significant difference in CEUS features between the 46 clear cell renal cell carcinoma (CCRCC) and other types of renal tumors, including 17 low malignant lesions, 11 urothelial carcinoma of the renal pelvis, and 19 renal angiomyolipoma. The differences lie in the peak intensity, the homogeneity, the time of wash-in, peak, clearance and presence of pseudocapsule. The ΔTP and ΔP% of the CCRCC is significantly different from other tumors. With “fast to peak + high peak intensity” as the main criterion, assisted with “heterogeneous enhancement” and “fast wash-in” as the secondary criteria, the diagnostic accuracy of CCRCC is 91.4%, demonstrating quantitative CEUS imaging is highly valuable in differentiating CCRCC from other tumors.

Comparison of Percutaneous Renal Mass Biopsy and R.E.N.A.L. Nephrometry Score Nomograms for Determining Benign Vs Malignant Disease and Low-risk Vs High-risk Renal Tumors

OBJECTIVE

To compare the accuracies of renal mass biopsy (RMB) and R.E.N.A.L. nephrometry score (RNS) nomograms for predicting benign vs malignant disease, and low- vs high-risk renal tumors.

MATERIALS AND METHODS

We included 281 renal masses in 277 patients who had complete RNS, preoperative RMB, and final pathology from renal surgery for clinically localized renal tumors. RMB and final pathology were determined to be benign or malignant, and malignancies were classified as low-risk (Fuhrman grade I/II) or high-risk (Fuhrman grade III/IV) (benign included in low-risk group). Previously published RNS nomograms were used to determine probabilities of any cancer and high-risk cancer. The gamma statistic was used to assess strength of association between RMB or RNS with final pathology.

RESULTS

Of the 281 masses, 13 (5%) and 268 (95%) were confirmed benign and malignant, respectively, and 155 (55%) and 126 (45%) were confirmed low-risk and high-risk, respectively, on final pathology. The areas under the curve of the RNS nomograms for benign vs malignant disease and for low-risk vs high-risk renal tumors were 0.56 and 0.64, respectively. Concordances for predicting benign vs malignant disease were 99% for RMB (P < .01, gamma 0.99) and 29% for RNS nomogram (P = .16, gamma 0.38). Concordances for predicting low-risk vs high-risk renal tumors were 67% for RMB (P < .01, gamma 0.97) and 61% for RNS nomogram (P < .01, gamma 0.47), respectively.

CONCLUSION

Although RNS nomograms are useful for discriminating between benign vs malignant renal masses, and low-risk vs high-risk renal tumors, they are outperformed by RMB.

Percutaneous Needle Based Optical Coherence Tomography for the Differentiation of Renal Masses: a Pilot Cohort

PURPOSE

We determine the ability of percutaneous needle based optical coherence tomography to differentiate renal masses by using the attenuation coefficient (μOCT, mm(-1)) as a quantitative measure.

MATERIALS AND METHODS

Percutaneous needle based optical coherence tomography of the kidney was performed in patients presenting with a solid renal mass. A pathology specimen was acquired in the form of biopsies and/or a resection specimen. Optical coherence tomography results of 40 patients were correlated to pathology results of the resected specimens in order to derive μOCT values corresponding with oncocytoma and renal cell carcinoma, and with the 3 main subgroups of renal cell carcinoma. The sensitivity and specificity of optical coherence tomography in differentiating between oncocytoma and renal cell carcinoma were assessed through ROC analysis.

RESULTS

The median μOCT of oncocytoma (3.38 mm(-1)) was significantly lower (p=0.043) than the median μOCT of renal cell carcinoma (4.37 mm(-1)). ROC analysis showed a μOCT cutoff value of greater than 3.8 mm(-1) to yield a sensitivity, specificity, positive predictive value and negative predictive value of 86%, 75%, 97% and 37%, respectively, to differentiate between oncocytoma and renal cell carcinoma. The area under the ROC curve was 0.81. Median μOCT was significantly lower for oncocytoma vs clear cell renal cell carcinoma (3.38 vs 4.36 mm(-1), p=0.049) and for oncocytoma vs papillary renal cell carcinoma (3.38 vs 4.79 mm(-1), p=0.027).

CONCLUSIONS

We demonstrated that the μOCT is significantly higher in renal cell carcinoma vs oncocytoma, with ROC analysis showing promising results for their differentiation. This demonstrates the potential of percutaneous needle based optical coherence tomography to help in the differentiation of renal masses, thus warranting ongoing research.