Search

Objectives: To investigate different radiomics models based on single phase and the different phase combinations of radiomics features from 3D tri-phasic CT to distinguish RO from chRCC. Methods: A total of 96 patients (30 RO and 66 chRCC) were enrolled in this study. Radiomics features were extracted from unenhanced phase (UP), corticomedullary phase (CMP), and nephrographic phase (NP) CT images. Feature selection was based on the least absolute shrinkage and selection operator regression (LASSO) method. The selected features were used to develop different radiomics models using logistic regression (LR) analysis, including model 1 (UP), model 2(CMP), model 3(NP), model 4(UP+CMP), model 5(UP+NP), model 6(CMP+NP), and model 7(UP+CMP+NP). The radiomics model demonstrating the highest discrimination performance was utilized to construct the combined model (model 8) with clinical factors. A nomogram based on the model 8 was established. To evaluate the diagnostic performance of the different models, the receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used. Delong's test was utilized to assess the statistical significance of the AUC improvement across the models. Results: Among the seven radiomics models, model 7 exhibited the highest AUC of 0.84 (95% CI 0.69, 0.99), and model 7 demonstrated a significantly superior AUC compared to the other radiomics models (all P < 0.05). The AUC values of radiomics models based on two phases (model4, mode5, mode6) were greater than the models based on single phase (model1, mode2, mode3) (all P < 0.05). Model 3 illustrated the best performance of the three radiomics models based on single phase with an AUC of 0.76 (95% CI 0.57, 099). Model 6 illustrated the best performance of the three radiomics models based on two-phases combination with an AUC of 0.83 (0.66, 0.99). Model 8 achieved an AUC of 0.93 (95% CI 0.83, 1.00) which is higher than those all radiomics models. Conclusion: Radiomics models based on combination of radiomics features from UP, CMP, and NP can be a useful and promising technique to differentiate RO from chRCC. Moreover, the model combining clinical factors and radiomics features showed better classification performance to distinguish them. [ABSTRACT FROM AUTHOR]

Background: This study investigates the proteomic landscapes of chromophobe renal cell carcinoma (chRCC) and renal oncocytomas (RO), two subtypes of renal cell carcinoma that together account for approximately 10% of all renal tumors. Despite their histological similarities and shared origins, chRCC is a malignant tumor necessitating aggressive intervention, while RO, a benign growth, is often subject to overtreatment due to difficulties in accurate differentiation. Methods: We conducted a label-free quantitative proteomic analysis on solid biopsies of chRCC (n = 5), RO (n = 5), and normal adjacent tissue (NAT, n = 5). The quantitative analysis was carried out by comparing protein abundances between tumor and NAT specimens. Our analysis identified a total of 1610 proteins across all samples, with 1379 (85.7%) of these proteins quantified in at least seven out of ten LC‒MS/MS runs for one renal tissue type (chRCC, RO, or NAT). Results: Our findings revealed significant similarities in the dysregulation of key metabolic pathways, including carbohydrate, lipid, and amino acid metabolism, in both chRCC and RO. Compared to NAT, both chRCC and RO showed a marked downregulation in gluconeogenesis proteins, but a significant upregulation of proteins integral to the citrate cycle. Interestingly, we observed a distinct divergence in the oxidative phosphorylation pathway, with RO showing a significant increase in the number and degree of alterations in proteins, surpassing that observed in chRCC. Conclusions: This study underscores the value of integrating high-resolution mass spectrometry protein quantification to effectively characterize and differentiate the proteomic landscapes of solid tumor biopsies diagnosed as chRCC and RO. The insights gained from this research offer valuable information for enhancing our understanding of these conditions and may aid in the development of improved diagnostic and therapeutic strategies. [ABSTRACT FROM AUTHOR]

Renal oncocytoma (RO) accounts for 5% of renal cancers and generally behaves as a benign tumor with favorable long-term prognosis. It is difficult to confidently distinguish between benign RO and other renal malignancies, particularly chromophobe renal cell carcinoma (chRCC). Therefore, RO is often managed aggressively with surgery. We sought to identify molecular biomarkers to distinguish RO from chRCC and other malignant renal cancer mimics. In a 44-patient discovery cohort, we identified a significant differential abundance of nine genes in RO relative to chRCC. These genes were used to train a classifier to distinguish RO from chRCC in an independent 57-patient cohort. The trained classifier was then validated in five independent cohorts comprising 89 total patients. This nine-gene classifier trained on the basis of differential gene expression showed 93% sensitivity and 98% specificity for distinguishing RO from chRCC across the pooled validation cohorts, with a c-statistic of 0.978. This tool may be a useful adjunct to other diagnostic modalities to decrease the diagnostic and management uncertainty associated with small renal masses and to enable clinicians to recommend more confidently less aggressive management for some tumors. PATIENT SUMMARY: Renal oncocytoma is generally a benign form of kidney cancer that does not necessarily require surgical removal. However, it is difficult to distinguish renal oncocytoma from other more aggressive forms of kidney cancer, so it is treated most commonly with surgery. We built a classification tool based on the RNA levels of nine genes that may help avoid these surgeries by reliably distinguishing renal oncocytoma from other forms of kidney cancer.

Simple Summary: This study focuses on the integration of 99mTc Sestamibi SPECT/CT and radiomics analysis to characterize benign renal oncocytic neoplasia. Our research includes renal tumors with histopathological analysis (conducted by independent pathologists) serving as the ground truth. Radiomics data were extracted from contrast-enhanced CT images to build machine-learning models. The combined SPECT/radiomics model achieved higher accuracy (95%) than the radiomics-only model (75%) and visual evaluation of 99mTc Sestamibi SPECT/CT alone (90.8%). This approach promises the improvement of diagnostic accuracy in renal tumor characterization and the reduction in unnecessary surgery for benign tumors. The increasing evidence of oncocytic renal tumors positive in 99mTc Sestamibi Single Photon Emission Tomography/Computed Tomography (SPECT/CT) examination calls for the development of diagnostic tools to differentiate these tumors from more aggressive forms. This study combined radiomics analysis with the uptake of 99mTc Sestamibi on SPECT/CT to differentiate benign renal oncocytic neoplasms from renal cell carcinoma. A total of 57 renal tumors were prospectively collected. Histopathological analysis and radiomics data extraction were performed. XGBoost classifiers were trained using the radiomics features alone and combined with the results from the visual evaluation of 99mTc Sestamibi SPECT/CT examination. The combined SPECT/radiomics model achieved higher accuracy (95%) with an area under the curve (AUC) of 98.3% (95% CI 93.7–100%) than the radiomics-only model (71.67%) with an AUC of 75% (95% CI 49.7–100%) and visual evaluation of 99mTc Sestamibi SPECT/CT alone (90.8%) with an AUC of 90.8% (95%CI 82.5–99.1%). The positive predictive values of SPECT/radiomics, radiomics-only, and 99mTc Sestamibi SPECT/CT-only models were 100%, 85.71%, and 85%, respectively, whereas the negative predictive values were 85.71%, 55.56%, and 94.6%, respectively. Feature importance analysis revealed that 99mTc Sestamibi uptake was the most influential attribute in the combined model. This study highlights the potential of combining radiomics analysis with 99mTc Sestamibi SPECT/CT to improve the preoperative characterization of benign renal oncocytic neoplasms. The proposed SPECT/radiomics classifier outperformed the visual evaluation of 99mTc Sestamibii SPECT/CT and the radiomics-only model, demonstrating that the integration of 99mTc Sestamibi SPECT/CT and radiomics data provides improved diagnostic performance, with minimal false positive and false negative results. [ABSTRACT FROM AUTHOR]

Introduction “Other oncocytic renal tumors of the kidney” is a new category constituted by 2022 WHO classification and different in the point of morphology and immunohistochemistory from typical oncocytic/eosinophilic renal tumors including chromophobe renal cell carcinoma and oncocytoma. Case presentation The patient was an 84‐year‐old woman in whom a left renal tumor was incidentally discovered. She underwent left nephrectomy, and the pathological specimens showed a borderline eosinophilic renal tumor between chromophobe renal cell carcinoma and renal oncocytoma. After all recognized oncocytic tumors were excluded, we diagnosed the tumor as other oncocytic renal tumor of the kidney. Conclusion Other oncocytic renal tumor of the kidney is a provisional category. Therefore, further research and accumulation of similar cases are necessary.

Abstract Background To investigate the value of computed tomography (CT)-based radiomics model analysis in differentiating renal oncocytoma (RO) from renal cell carcinoma subtypes (chromophobe renal cell carcinoma, clear cell carcinoma) and predicting the expression of Cytokeratin 7 (CK7). Methods In this retrospective study, radiomics was applied for patients with RO, chRCC and ccRCC who underwent surgery between January 2013 and December 2019 comprised the training cohort, and the testing cohort was collected between January and October 2020. The corticomedullary (CMP) and nephrographic phases (NP) were manually segmented, and radiomics texture parameters were extracted. Support vector machine was generated from CMP and NP after feature selection. Shapley additive explanations were applied to interpret the radiomics features. A radiomics signature was built using the selected features from the two phases, and the radiomics nomogram was constructed by incorporating the radiomics features and clinical factors. Receiver operating characteristic curve was calculated to evaluate the above models in the two sets. Furthermore, Rad-score was used for correlation analysis with CK7. Results A total of 123 patients with RO, chRCC and ccRCC were analyzed in the training cohort and 57 patients in the testing cohort. Subsequently, 396 radiomics features were selected from each phase. The radiomics features combining two phases yielded the highest area under the curve values of 0.941 and 0.935 in the training and testing sets, respectively. The Pearson’s correlation coefficient was statistically significant between Rad-score and CK7. Conclusion We proposed a non-invasive and individualized CT-based radiomics nomogram to differentiation among RO, chRCC and ccRCC preoperatively and predict the immunohistochemical protein expression for accurate clinical diagnosis and treatment decision.

Background: Benign renal tumors, such as renal oncocytoma (RO), can be erroneously diagnosed as malignant renal cell carcinomas (RCC), because of their similar imaging features. Computer-aided systems leveraging radiomic features can be used to better discriminate benign renal tumors from the malignant ones. The purpose of this work was to build a machine learning model to distinguish RO from clear cell RCC (ccRCC). Method: We collected CT images of 77 patients, with 30 cases of RO (39%) and 47 cases of ccRCC (61%). Radiomic features were extracted both from the tumor volumes identified by the clinicians and from the tumor's zone of transition (ZOT). We used a genetic algorithm to perform feature selection, identifying the most descriptive set of features for the tumor classification. We built a decision tree classifier to distinguish between ROs and ccRCCs. We proposed two versions of the pipeline: in the first one, the feature selection was performed before the splitting of the data, while in the second one, the feature selection was performed after, i.e., on the training data only. We evaluated the efficiency of the two pipelines in cancer classification. Results: The ZOT features were found to be the most predictive by the genetic algorithm. The pipeline with the feature selection performed on the whole dataset obtained an average ROC AUC score of 0.87 ± 0.09. The second pipeline, in which the feature selection was performed on the training data only, obtained an average ROC AUC score of 0.62 ± 0.17. Conclusions: The obtained results confirm the efficiency of ZOT radiomic features in capturing the renal tumor characteristics. We showed that there is a significant difference in the performances of the two proposed pipelines, highlighting how some already published radiomic analyses could be too optimistic about the real generalization capabilities of the models. [ABSTRACT FROM AUTHOR]

Background: Correct tumor subtyping of primary renal tumors is essential for treatment decision in daily routine. Most of the tumors can be classified based on morphology alone. Nevertheless, some diagnoses are difficult, and further investigations are needed for correct tumor subtyping. Besides histochemical investigations, high-mass-resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can detect new diagnostic biomarkers and hence improve the diagnostic. Patients and Methods: Formalin-fixed paraffin embedded tissue specimens from clear cell renal cell carcinoma (ccRCC, n = 552), papillary renal cell carcinoma (pRCC, n = 122), chromophobe renal cell carcinoma (chRCC, n = 108), and renal oncocytoma (rO, n = 71) were analyzed by high-mass-resolution MALDI fourier-transform ion cyclotron resonance (FT-ICR) MSI. The SPACiAL pipeline was executed for automated co-registration of histological and molecular features. Pathway enrichment and pathway topology analysis were performed to determine significant differences between RCC subtypes. Results: We discriminated the four histological subtypes (ccRCC, pRCC, chRCC, and rO) and established the subtype-specific pathways and metabolic profiles. rO showed an enrichment of pentose phosphate, taurine and hypotaurine, glycerophospholipid, amino sugar and nucleotide sugar, fructose and mannose, glycine, serine, and threonine pathways. ChRCC is defined by enriched pathways including the amino sugar and nucleotide sugar, fructose and mannose, glycerophospholipid, taurine and hypotaurine, glycine, serine, and threonine pathways. Pyrimidine, amino sugar and nucleotide sugar, glycerophospholipids, and glutathione pathways are enriched in ccRCC. Furthermore, we detected enriched phosphatidylinositol and glycerophospholipid pathways in pRCC. Conclusion: In summary, we performed a classification system with a mean accuracy in tumor discrimination of 85.13%. Furthermore, we detected tumor-specific biomarkers for the four most common primary renal tumors by MALDI-MSI. This method is a useful tool in differential diagnosis and biomarker detection. [ABSTRACT FROM AUTHOR]

This is a case report about a patient which presents with two right renal tumors, one of them being an oncocytoma with typical histopathological features and renal vein extension. Recent studies show that despite renal vein thrombus being a histological sign of malignancy; when associated with renal oncocytoma, it should not alter the benign prognosis of oncocytoma, and a simple follow-up may be carried. Further explorations should be done when easily available, and when the histopathologic diagnosis of oncocytoma is uncertain, to rule out the differential diagnosis of a chromophobe renal cell carcinoma, oncocytic variant.

Renal oncocytoma is a benign renal neoplasm which has mostly been reported in adults. Occurrence in children is infrequent. To date, there are only six pediatric cases of renal oncocytoma reported previously. Herein, we report a 13-year-old girl presented with hematuria for a week. Abdominal computed tomography showed a well-defined heterogeneous solid mass with a stellate central scar in the left kidney. The patient underwent a nephron sparing surgery. Histopathological and immunohistochemical findings confirmed the diagnosis of renal oncocytoma. Though uncommon, renal oncocytoma should be considered as the differential diagnosis of renal tumor in children. In addition, intranuclear inclusions were firstly described in this pediatric patient with unclear significance, which need a large cohort to summarize and analyze.

Oncocytoma is a common benign kidney tumor. The size is often less than 5 cm. Oncocytomas may be misdiagnosed in clinic, radiology and histopathology for renal cell carcinoma. Different panels of immunohistochemistry (IHC) are suggested in the renal tumors with eosinophilic granular cytoplasm including oncocytoma, chromophobe and clear renal cell carcinoma. Here we report a large oncocytoma in a 64-year-old lady, that the mimickers ruled out by IHC.

Artificial intelligence (AI)-based techniques are increasingly being explored as an emerging ancillary technique for improving accuracy and reproducibility of histopathological diagnosis. Renal cell carcinoma (RCC) is a malignancy responsible for 2% of cancer deaths worldwide. Given that RCC is a heterogenous disease, accurate histopathological classification is essential to separate aggressive subtypes from indolent ones and benign mimickers. There are early promising results using AI for RCC classification to distinguish between 2 and 3 subtypes of RCC. However, it is not clear how an AI-based model designed for multiple subtypes of RCCs, and benign mimickers would perform which is a scenario closer to the real practice of pathology. A computational model was created using 252 whole slide images (WSI) (clear cell RCC: 56, papillary RCC: 81, chromophobe RCC: 51, clear cell papillary RCC: 39, and, metanephric adenoma: 6). 298,071 patches were used to develop the AI-based image classifier. 298,071 patches (350 × 350-pixel) were used to develop the AI-based image classifier. The model was applied to a secondary dataset and demonstrated that 47/55 (85%) WSIs were correctly classified. This computational model showed excellent results except to distinguish clear cell RCC from clear cell papillary RCC. Further validation using multi-institutional large datasets and prospective studies are needed to determine the potential to translation to clinical practice. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI)-based techniques are increasingly being explored as an emerging ancillary technique for improving accuracy and reproducibility of histopathological diagnosis. Renal cell carcinoma (RCC) is a malignancy responsible for 2% of cancer deaths worldwide. Given that RCC is a heterogenous disease, accurate histopathological classification is essential to separate aggressive subtypes from indolent ones and benign mimickers. There are early promising results using AI for RCC classification to distinguish between 2 and 3 subtypes of RCC. However, it is not clear how an AI-based model designed for multiple subtypes of RCCs, and benign mimickers would perform which is a scenario closer to the real practice of pathology. A computational model was created using 252 whole slide images (WSI) (clear cell RCC: 56, papillary RCC: 81, chromophobe RCC: 51, clear cell papillary RCC: 39, and, metanephric adenoma: 6). 298,071 patches were used to develop the AI-based image classifier. 298,071 patches (350 × 350-pixel) were used to develop the AI-based image classifier. The model was applied to a secondary dataset and demonstrated that 47/55 (85%) WSIs were correctly classified. This computational model showed excellent results except to distinguish clear cell RCC from clear cell papillary RCC. Further validation using multi-institutional large datasets and prospective studies are needed to determine the potential to translation to clinical practice.

Renal tumors with oncocytic or chromophobe-like morphology can be a common source of diagnostic difficulty. In some series, they constitute the largest group of unclassified renal cell carcinomas, a term used for neoplasms that do not fit the current classification of renal tumors. We describe the histological, immunohistochemical, and molecular findings of an eosinophilic renal neoplasm which presented with rib and liver metastases, and provide a review of the literature. The possibility of a renal oncocytoma with metastases was initially considered but excluded on the basis of several morphological and immunohistochemical features. Additionally, the tumor did not correspond with other traditional or newly emerging categories of renal neoplasms. It was therefore regarded as an unclassified oncocytic renal neoplasm which demonstrated evidence of malignant potential due to the presence of multiple metastases. [ABSTRACT FROM AUTHOR]

99mTc-Sestamibi Single Photon Emission Computed Tomography/Computed Tomography (SPECT/CT) contributes to the non-invasive differentiation of renal oncocytoma (RO) from renal cell carcinoma (RCC) by characterising renal tumours as Sestamibi positive or Sestamibi negative regarding their 99mTc-Sestamibi uptake compared to the non-tumoral renal parenchyma. To determine whether 99mTc- Sestamibi uptake in renal tumour and the non-tumoral renal parenchyma measured using Standard Uptake Value (SUV) SPECT, has a beneficial role in differentiating RO from RCC. Fifty-seven renal tumours from 52 patients were evaluated. In addition to visual evaluation of 99mTc-Sestamibi uptake, SUVmax measurements were performed in the renal tumour and the ipsilateral non-tumoral renal parenchyma. Analysis of the area under the receiver operating characteristic curve identified an optimal cut-off value for detecting RO, based on the relative ratio of 99mTc- Sestamibi uptake. Semiquantitative evaluation of 99mTc-Sestamibi uptake did not improve the performance of 99mTc- Sestamibi SPECT/CT in detecting RO. 99mTc- Sestamibi SPECT/CT identifies a group of mostly indolent Sestamibi-positive tumours with low malignant potential containing RO, Low-Grade Oncocytic Tumours, Hybrid Oncocytic Tumours, and a subset of chromophobe RCCs. The imaging limitations for accurate differentiation of Sestamibi-positive renal tumours mirror the recognised diagnostic complexities of the histopathologic evaluation of oncocytic neoplasia. Patients with Sestamibi-positive renal tumours could be better suited for biopsy and follow-up, according to the current active surveillance protocols. [ABSTRACT FROM AUTHOR]

Background: To investigate the value of computed tomography (CT)-based radiomics model analysis in differentiating renal oncocytoma (RO) from renal cell carcinoma subtypes (chromophobe renal cell carcinoma, clear cell carcinoma) and predicting the expression of Cytokeratin 7 (CK7).Methods: In this retrospective study, radiomics was applied for patients with RO, chRCC and ccRCC who underwent surgery between January 2013 and December 2019 comprised the training cohort, and the testing cohort was collected between January and October 2020. The corticomedullary (CMP) and nephrographic phases (NP) were manually segmented, and radiomics texture parameters were extracted. Support vector machine was generated from CMP and NP after feature selection. Shapley additive explanations were applied to interpret the radiomics features. A radiomics signature was built using the selected features from the two phases, and the radiomics nomogram was constructed by incorporating the radiomics features and clinical factors. Receiver operating characteristic curve was calculated to evaluate the above models in the two sets. Furthermore, Rad-score was used for correlation analysis with CK7.Results: A total of 123 patients with RO, chRCC and ccRCC were analyzed in the training cohort and 57 patients in the testing cohort. Subsequently, 396 radiomics features were selected from each phase. The radiomics features combining two phases yielded the highest area under the curve values of 0.941 and 0.935 in the training and testing sets, respectively. The Pearson's correlation coefficient was statistically significant between Rad-score and CK7.Conclusion: We proposed a non-invasive and individualized CT-based radiomics nomogram to differentiation among RO, chRCC and ccRCC preoperatively and predict the immunohistochemical protein expression for accurate clinical diagnosis and treatment decision. [ABSTRACT FROM AUTHOR]

Oncocytomas are referred to as benign kidney neoplasms. They primarily affect adults, with patients over 70 years old being the most affected. Renal oncocytomas (ROs) are frequently detected by excision, biopsy, or scan. Hematuria, flank pain, and a palpable mass are the traditional trio of symptoms. Oncocytomas appear as well-circumscribed, tan or mahogany-coloured masses with a central scar that is stellate. Histological features include well-circumscribed lesions, bland cytology, eosinophilic cytoplasm, regular nuclei with prominent central nucleoli, and nested architecture. ROs are rarely linked to an aggressive clinical course and have an excellent prognosis. There is proof that the disease can spread to the liver and bones. Some literature has also reported oncocytoma metastases to the lung and liver. This systematic review of the literature examines and evaluates the malignant potential of oncocytoma. The purpose of the study was to determine whether ROs can be diagnosed as a benign condition or if malignancy needs to be considered and investigated. Seventeen studies were analysed which had a total of 412 ROs. Four patients (one percent) died as a result of their illness. There was evidence of disease progression in every patient who passed away from their illness. Six patients (1.5%) experienced disease progression in total. Three hundred and seventeen patients (80%) underwent radical nephrectomy, while 81 patients (20%) underwent partial nephrectomy. Liver, bone, lung, lymphadenopathy, and local recurrence were among the metastasis sites. Perinephric fat invasion, renal sinus fat invasion, renal capsular invasion, and vascular invasion are characteristics of metastatic behavior that have been found. Despite this, the small number of patients who experienced disease progression and/or death as a result of ROs implies that aggressive malignant behavior is not always correlated with the presence of metastatic features or disease. Oncocytomas should be viewed as having a low potential for malignancy rather than as benign. Individuals who exhibit aggressive characteristics, such as vascular invasion and/or perinephric fat invasion, have an atypically good prognosis. Despite advancements in imaging and immunochemical techniques, it is indisputable that ROs, which were first classified as renal tumours in 1976, continue to pose a diagnostic challenge for multidisciplinary teams. There is considerable variation in practice across the globe due to difficulties in confirming ROs, especially when it comes to metastatic disease. There is even more variation in the management of follow-up care that follows. This will remain the MDT's current state until randomised controlled trials, long-term results, and a better comprehension of the behavior of this tumour are obtained., Competing Interests: Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Rajagopal et al.)

Here we report a case of renal oncocytoma in a 68 year-old male. The diagnosis was initially made on a needle biopsy 6 years prior to the partial nephrectomy. The case is unique that in addition to the gross and microscopic features commonly seen in renal oncocytomas, both lymphovascular invasion and prominent intracytoplasmic vacuole-like spaces are also present in this tumor. Although vascular invasion is increasingly recognized as compatible with renal oncocytoma, intracytoplasmic vacuoles are a rare and unusual finding that may lead to diagnostic difficulty. The diagnosis of renal oncocytoma was confirmed after immunohistochemistry was performed to argue against succinate dehydrogenase deficient renal cell carcinoma (RCC) and chromophobe RCC. This case highlights the importance for practicing pathologists to recognize the rare co-occurrence of lymphovascular invasion and large intracytoplasmic vacuole-like spaces in renal oncocytoma. Other differential diagnoses may include emerging renal tumor entities, such as the recently-proposed eosinophilic vacuolated tumor. [ABSTRACT FROM AUTHOR]

Renal oncocytoma is a benign tumor that arises from epithelial cells of the distal renal tubules. It is naturally presented with a small-sized mass, and giant oncocytoma is uncommon. Renal oncocytoma is frequently asymptomatic and challenging to distinguish preoperatively from renal cell carcinoma (RCC). We present a 40-yearold man who presented with intermittent abdominal pain in the last two years. Abdominal computed tomography (CT) scan showed a large, heterogenous left renal mass measured 15 x 16 x 19.5 cm and associated with central calcifications suspected of RCC. The patient underwent a left radical nephrectomy without complication. The histopathological study revealed typical oncocytoma features. There was no detected recurrence or distant metastasis on six months follow-up. In conclusion, it is challenging to distinguish renal oncocytoma from RCC via preoperative radiology images, especially when a giant mass is present. The only histopathology examination of the removed specimen can provide a definitive diagnosis. [ABSTRACT FROM AUTHOR]

Renal oncocytomas are rare benign epithelial tumors of the kidney. However, they are easily misdiagnosed as renal cancers, resulting in unnecessary radical nephrectomy. This review summarizes the use of ultrasound for the diagnosis of renal oncocytomas. On two-dimensional grayscale ultrasound, renal oncocytomas appear as solid, well-defined, round or oval, and relatively isoechoic or slightly hyperechoic masses. On color Doppler flow imaging, the "spoke-wheel" sign is evident. On power Doppler flow imaging, renal oncocytomas show mixed penetrating and peripheral patterns. Renal oncocytomas usually appear as highly enhanced on contrast-enhanced ultrasound images, and irregular nonenhanced areas in larger tumors. This review will help sonographers recognize renal oncocytomas. [ABSTRACT FROM AUTHOR]

Background: Renal oncocytoma (RO) and chromophobe renal cell carcinoma (chRCC) have a common cellular origin and different clinical management and prognosis. Purpose: To explore the utility of computed tomography (CT) in the differentiation of RO and chRCC. Material and Methods: Twenty-five patients with RO and 73 patients with chRCC presenting with the central scar were included retrospectively. Two experienced radiologists independently reviewed the CT imaging features, including location, tumor size, relative density ratio, segmental enhancement inversion (SEI), necrosis, and perirenal fascia thickening, among others. Interclass correlation coefficient (ICC, for continuous variables) or Kappa coefficient test (for categorical variables) was used to determine intra-observer and inter-observer bias between the two radiologists. Results: The inter- and intra-reader reproducibility of the other CT imaging parameters were nearly perfect (>0.81) except for the measurements of fat (0.662). RO differed from chRCC in the cortical or medullary side (P = 0.005), relative density ratio (P = 0.020), SEI (P < 0.001), and necrosis (P = 0.045). The logistic regression model showed that location (right kidney), hypo-density on non-enhanced CT, SEI, and perirenal fascia thickening were highly predictive of RO. The combined indicators from logistic regression model were used for ROC analysis. The area under the ROC curve was 0.923 (P < 0.001). The sensitivity and specificity of the four factors combined for diagnosing RO were 88% and 86.3%, respectively. The correlation coefficient between necrosis and tumor size in all tumors including both of RO and chRCC was 0.584, indicating a positive correlation (P < 0.001). Conclusion: The CT imaging features of location (right kidney), hypo-density on non-enhanced CT, SEI, and perirenal fascia thickening were valuable indicators in distinguishing RO from chRCC. [ABSTRACT FROM AUTHOR]

Oncocytoma is a common benign kidney tumor. The size is often less than 5 cm. Oncocytomas may be misdiagnosed in clinic, radiology and histopathology for renal cell carcinoma. Different panels of immunohistochemistry (IHC) are suggested in the renal tumors with eosinophilic granular cytoplasm including oncocytoma, chromophobe and clear renal cell carcinoma. Here we report a large oncocytoma in a 64-year-old lady, that the mimickers ruled out by IHC. [ABSTRACT FROM AUTHOR]

Objectives: To study the natural history of renal oncocytomas and address indications for intervention by determining how growth is associated with renal function over time, the reasons for surgery and ablation, and disease‐specific survival. Patients and Methods: The study was conducted in a retrospective cohort of consecutive patients with renal oncocytoma on active surveillance reviewed at the Specialist Centre for Kidney Cancer at the Royal Free London NHS Foundation Trust (2012 to 2019). Comparison between groups was performed using Mann–Whitney U‐tests and chi‐squared tests. A mixed‐effects model with a random intercept for patient was used to study the longitudinal association between tumour size and estimated glomerular filtration rate (eGFR). Results: Longitudinal data from 98 patients with 101 lesions were analysed. Most patients were men (68.3%) and the median (interquartile range [IQR]) age was 69 (13) years. The median (IQR) follow‐up was 29 (26) months. Most lesions were small renal masses, and 24% measured over 4 cm. Over half (64.4%) grew at a median (IQR) rate of 2 (4) mm per year. No association was observed between tumour size and eGFR over time (P = 0.871). Nine lesions (8.9%) were subsequently treated. Two deaths were reported, neither were related to the diagnosis of renal oncocytoma. Conclusion: Natural history data from the largest active surveillance cohort of renal oncocytomas to date show that renal function does not seem to be negatively impacted by growing oncocytomas, and confirms clinical outcomes are excellent after a median follow‐up of over 2 years. Active surveillance should be considered the 'gold standard' management of renal oncocytomas up to 7cm. [ABSTRACT FROM AUTHOR]

Purpose: Renal oncocytoma (RO) is the most commonly resected benign renal tumor because of misdiagnosis as renal cell carcinoma. This misdiagnosis is generally owing to overlapping imaging features. This study describes the building of a radiomics nomogram based on clinical data and radiomics signature for the preoperative differentiation of RO from clear cell renal cell carcinoma (ccRCC) on tri-phasic contrast-enhanced CT. Methods: A total of 122 patients (85 in training set and 37 in external validation set) with ROs (n = 46) or ccRCCs (n = 76) were enrolled. Patient characteristics and tri-phasic contrast-enhanced CT imaging features were evaluated to build a clinical factors model. A radiomics signature was constructed by extracting radiomics features from tri-phasic contrast-enhanced CT images and a radiomics score (Rad-score) was calculated. A radiomics nomogram was then built by incorporating the Rad-score and significant clinical factors according to a multivariate logistic regression analysis. The diagnostic performance of the above three models was evaluated in training and validation sets. Results: Central stellate area and perirenal fascia thickening were selected to build the clinical factors model. Eleven radiomics features were combined to construct the radiomics signature. The AUCs of the radiomics nomogram, which was based on the selected clinical factors and Rad-score, were 0.960 and 0.898 in the training and validation sets, respectively. The decision curves of the radiomics nomogram and radiomics signature in the validation set indicated an overall net benefit over the clinical factors model. Conclusion: Our radiomics nomogram can effectively predict the preoperative diagnosis of ROs and may therefore be of assistance in sparing unnecessary surgery and tailoring precise therapy. The ROC curves of the clinical model, the radiomics signature and the radiomics nomogram for the validation set. RO = Renal oncocytoma; ccRCC = Clear cell renal cell carcinoma. [ABSTRACT FROM AUTHOR]

Objective: Renal oncocytoma (RO) and chromophobe renal cell carcinoma (ChRCC) originate from the same cell origin, that is, the intercalated cells of the collecting duct.[1] In most cases, there are clear morphologic differences between RO and ChRCC; however, in some instances, overlapping features may be encountered and the differentiation between the two entities becomes difficult.[2] Several immunohistochemical markers with different expression patterns in ChRCC and RO have been described to rule out this dilemma. Materials and Methods: About 47 primary renal neoplasms that had been diagnosed as RO or ChRCC were submitted for immunohistochemical staining of amylase α-1A (AMY1A), MOC 31, and CD 82. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy have been analyzed. Results: AMY1A positivity was observed in all RO cases in our work with 91.7% sensitivity and 100% specificity in the diagnosis of RO. The PPV of its expression was (100%) and NPV (97.2%) with a diagnostic accuracy of 97.9%. A significant high expression of MOC 31 was observed in ChRCC compared to its expression in RO with a statistical significance (P < 0.001). In addition, we obtained 82.9% sensitivity and 91.7% specificity of MOC 31 expression in the diagnosis of ChRCC. The positive predictive value (PPV) was (96.7%), negative predictive value (NPV) (64.7%) with diagnostic accuracy (85.1%). In our studied cases, we detected positive immunoexpression of CD 82 in 10 cases (83.3%) of ChRCC. However, it was lost in all RO cases (100%). CD 82 sensitivity and specificity in differentiating ChRCC from RO were 100% and 83.3%, respectively. Conclusion: We propose MOC 31 and CD 82 as negative immunostains for RO, as these markers are commonly expressed in ChRCC. In conjunction with AMY1A strong immunopositivity in RO cases, we provide a triple panel of biomarkers (AMY1A, MOC 31, and CD 82) for the distinction between RO and ChRCC.

Renal oncocytomas are asymptomatic, benign tumors often encountered incidentally on various imaging modalities. Renal oncocytomas comprise 5–7% of primary renal neoplasms and are derived from cells of the distal renal tubule. We present a case report of renal oncocytoma in a 22-year-old male having right-sided flank pain and symptomatic gross hematuria with a giant urinary bladder clot retention. The tumor was excised, and the patient underwent laparoscopic partial nephrectomy. Typical features of renal oncocytoma were observed upon histopathological examination of the resected specimen. The patient was catheterized, and bladder irrigation with clot retraction was performed.

Purpose: To evaluate the ability of inferior vena cava-lesion-attenuation-difference (ILAD) and lesion-cortex-attenuation-ratio (LCAR) to differentiate renal oncocytomas (RO) from chromophobe renal cell carcinomas (chRCC). Methods: Retrospective study with analysis of 84 cases of chRCC and 30 cases of RO confirmed by surgical pathology. ILAD was calculated by measuring the difference in Hounsfield units (HU) between the inferior vena cava and the lesion of interest on the same image slice on preoperative CT scan. Calculating LCAR using the CT attenuation ratio of lesion to renal cortex at the same image slice. Receiver operating characteristic (ROC) curves were plotted to analyze the diagnostic values of ILAD and LCAR for disease activity. Results: There were no statistically significant differences in demographic and lesion characteristics between patients with chRCC and RO (p > 0.05). ILAD has significant statistical differences in the identification of RO and chRCC in the arterial (p = 0.031), venous (p = 0.047), and delayed phase (p = 0.002). And LCAR showed a statistically significant difference between two lesions during the arterial (p = 0.043), venous (p = 0.026), and delayed phase (p = 0.008). When all significant variables were used in combination to build a predicting model (Mix), the AUC was 0.871 (95% CI 0.759–0.984) with 67.9% sensitivity and 100% specificity. Conclusion: ILAD and LCAR at the arterial phase, venous phase and delayed phase were shown to be useful CT attenuation parameter in discriminating RO from chRCC when histologic evaluation on biopsy is indeterminate. [ABSTRACT FROM AUTHOR]

FOXI1 is a forkhead family transcription factor that plays a key role in differentiation and functional maintenance for the renal intercalated cell (IC). The diagnostic utility of FOXI1 is rarely studied thus far. Comparative analyses of FOXI1 mRNA expression in normal kidney tissue and different renal neoplasms including chromophobe renal cell carcinoma (chRCC), renal oncocytoma (RO), and other renal cell carcinomas were conducted using transcriptomic data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus, and single-cell RNA-seq datasets, in combination with integrative analyses using mutant data, karyotype data, and digital slides for cases with anomalous FOXI1 expression in TCGA. Formalin-fixed, paraffin-embedded whole-tissue slides of varied primary renal neoplasms (n = 367) were subjected to FOXI1 staining for validating FOXI1 transcription levels. We confirmed that FOXI1 was significantly upregulated at mRNA levels in ICs, chRCCs, and ROs compared with other renal tubule cell and renal cell carcinoma subtypes. Furthermore, most of the cases with FOXI1 expression outliers were misclassified in the TCGA kidney cancer project. An underlying novel entity with frequent mutations involved in the mTOR pathway was also found. FOXI1 immunoreactivity was consistently noted in ICs of the distal nephron. FOXI1 staining was positive in 85 of 93 chRCCs and 13 of 18 ROs, respectively. FOXI1 staining was not seen in renal neoplasms (n = 254) derived from non-ICs. In conclusion, FOXI1 expression in normal kidney tissue is restricted to ICs. This cell type–specific expression is retained during neoplastic transformation from ICs to chRCCs or ROs. FOXI1 is thereby a potential biomarker of IC-related tumors. [ABSTRACT FROM AUTHOR]

The histologic features of renal oncocytoma (RO) are similar to those for the more aggressive chromophobe renal cell carcinoma (ChRCC). To assess immunohistochemical markers of the two, the sensitivity and specificity of cytokeratin 7 (CK7) and C-kit, as well as hepatocyte nuclear factor-1β (HNF-1β), were analyzed. Typical cases of ChRCC and RO at Severance Hospital between July 2014 and July 2018 were selected retrospectively. Among 44 cases, 17 were unanimously compatible with ChRCC, 16 were RO, and 11 cases were indeterminate. Samples from all selected cases were used for immunostaining with antibodies against CK7, C-kit, HNF-1β, and CD10. Immunostaining demonstrated complete loss of HNF-1β expression in 11 out of 17 (64.7%) ChRCC cases and a partial, but significant loss in > 50% of tumor cells in the remaining 6 cases (35.3%). In contrast, HNF-1β expression was preserved in tumor cells of RO cases. Fourteen of 17 ChRCC cases (82.4%) were diffusely positive for CK7, whereas cases of RO were focal positive or negative. C-kit staining did not show a significant difference between ChRCC and RO. Two of five ChRCC cases showing diffuse immunoreactivity for CD10 had poor prognoses of local invasion, distant metastasis, or death. Loss of HNF-1β expression is a useful marker with which to diagnose ChRCC, especially in cases with confusing histologic findings or equivocal CK7 staining. Additionally, CD10 staining in high-grade ChRCC aids in diagnosis and prediction of the clinical prognosis. [ABSTRACT FROM AUTHOR]

Background ChRCC is a rare form of kidney cancer and presents with a poor prognosis in the metastatic setting, with limited response to immune checkpoint inhibitors (ICI) and targeted therapy. While previous studies suggested that ChRCC originates from intercalated cells of the kidney, its exact cellular origin has not been clearly defined. We therefore investigated the cellular origin of ChRCC and renal oncocytic neoplasms at single-cell resolution. Methods ChRCC, renal oncocytoma (RO) and low-grade oncocytic tumor (LOT) samples with matched normal kidney specimens were analyzed using single-cell RNA sequencing (scRNA-seq). Epithelial cells from normal samples were clustered and annotated into the distinct known cellular types found in the adult healthy human kidney. A logistic regression model (Young M.D. et al., Science, 2018) was trained on the normal epithelial clusters, using a comprehensive set of 74 marker genes (features). Subsequently, the model was tested on tumor clusters from ChRCC, RO and LOT to investigate their cellular origin through the identification of the highest predicted probabilities of similarity between normal epithelial cellular types and tumor cells. Differential gene expression and pathway analyses between ChRCC and its cell of origin were then conducted to investigate mechanisms of oncogenesis. Results Following quality-control, 46,817 cells from 5 tumors (ChRCC: n=3, RO: n=1 and LOT: n=1) and 4 normal samples were isolated for scRNA-seq analysis. Among normal samples, 784 epithelial cells were clustered and annotated into the following cellular entities: proximal tubule (PT), loop of Henle – distal tubule (LOH-DT), principal cells (PC), α-intercalated cells (ICA) and β-intercalated cells (ICB). Across all ChRCC and oncocytic tumors, 7,573 tumor cells were identified, among which 7,425 corresponded to ChRCC. For ChRCC, RO, and LOT neoplasms, the highest predicted probability of similarity was consistently identified with ICA cells (ranging from 0.60 to 0.80). This finding was validated using an external and previously published (Zhang Y. et al., Proc Natl Acad Sci USA, 2021) scRNA-seq dataset from a patient with ChRCC (n=2,853 cells). Additionally, evaluation of previously defined ChRCC-specific markers (i.e. FOXI1, RHCG, KIT, CLCNKA, and CLCNKB) in scRNA-seq data of normal kidney epithelial cells consistently showed the highest expression in ICA cells. Differential gene expression between ChRCC and ICA cells revealed a significant downregulation of MHC class I genes (i.e. HLA-A , HLA-B, and HLA-C) and HSP70 (family A) genes (i.e. HSPA1A, HSPA1B, HSPA6, and HSPA8) in ChRCC. Differential pathway analysis between ChRCC and ICA cells showed a significant enrichment of the ferroptosis, glutathione metabolism, mTOR signaling and IL-15 pathways in ChRCC. Conclusions Renal oncocytic tumors, including ChRCC, appear to originate from the α-intercalated cells of the normal human kidney. As compared to α-intercalated cells, ChRCC downregulates MHC class I genes, which may be associated with its poor response to immunotherapy. Further, the selective downregulation of HSP70 genes may in part explain ChRCC's increased sensitivity to ferroptosis. CDMRP DOD Funding: yes [ABSTRACT FROM AUTHOR]

Purpose: We investigate the use of ratio of lesion to cortex (L/C) attenuation and aorta–lesion attenuation difference (ALAD) on multiphase contrast-enhanced CT to help distinguish oncocytoma from clear cell RCC in small renal masses (diameter < 4 cm). Methods: We retrospectively identified 76 patients that undergo CT before surgery for a suspicious small renal mass between January 2014 and December 2018 with pathological diagnosis of 21 oncocytomas (ROs), 25 clear cell RCCs, 7 chromophobe RCCs, 7 papillary RCCs, 7 multilocular cystic RCCs, 7 angiomyolipomas and 2 leiomyomas. CT attenuation values were obtained for the tumor, the normal renal cortex and the aorta, placing a circular region of interest (ROI) in the same slice by two radiologists, independently. Results: In the corticomedullary phase, ROs showed isodense enhancement to the renal cortex (ratio L/C 0.92 ± 0.12), while clear cell RCCs appeared hypodense to the renal cortex (ratio L/C 0.69 ± 0.20; p < 0.01) with an accuracy of 80% for diagnosing RO. In nephrographic phase, the ratio L/C attenuation was lower than the corticomedullary phase in ROs (0.78 ± 0.11) showing an early washout pattern, while the ratio L/C was similar to the corticomedullary phase in clear cell RCCs (0.69 ± 0.13; p = 0.025, with an accuracy of 65% for diagnosing RO). The ratio L/C attenuation showed considerable overlap between ROs and clear cell RCCs in the excretory phase (p = 0.27). Mean ALAD values in the nephrographic phase were 21.95 ± 16.24 for ROs and 36.96 ± 30.53 for clear cell RCCs (p = 0.049). Conclusion: The ratio L/C attenuation in corticomedullary phase may be useful to differentiate RO from clear cell RCC. [ABSTRACT FROM AUTHOR]

Abstract Background Renal oncocytoma is the most common benign renal tumor, and papillary renal cell carcinoma is the second most common histologic subtype of renal cell carcinoma. Renal tumors containing different components such as papillary renal cell carcinoma and oncocytoma are extremely rare. Case presentation A renal mass was incidentally detected in a 52-year-old Korean woman, and a computed tomographic scan showed a 32-mm multicystic mass with some calcifications in the lower pole of the right kidney. She underwent laparoscopic partial nephrectomy without any perioperative complications. We found a papillary renal cell carcinoma and an oncocytoma in a tumor mass. Conclusions The possibility of a mixed malignant tumor should be considered while treating benign tumors such as oncocytoma.

Objectives. Differentiating renal oncocytoma (RO) from chromophobe renal cell carcinoma (ChRCC) can occasionally be challenging. We evaluated the expression of RB1 and ERBB4 in RO and ChRCC, and compared the immunohistochemistry (IHC) results to RB1 and ERBB4 gene abnormalities detected by fluorescence in situ hybridization (FISH). Materials and Methods. Fifty-three kidney resections (ChRCC, n=28; RO, n=25) were stained for RB1 and ERBB4 IHC and FISH was performed to evaluate gene copy number analysis. Results. A loss of RB1 staining was identified in 64% (18/28) of ChRCCs, which was not found in any ROs (0/25; P <.001). FISH analysis revealed 36% (10/28) of ChRCCs contained a RB1 hemizygous deletion with a concordance of 56% (10/18) between the IHC and FISH findings. No RB1 gene copy number variations were detected in any of the ROs (0/25; P <.001) and retained expression of RB1 by IHC. ERBB4 showed cytoplasmic/membranous staining in all ROs and ChRCCs. However, 75% (21/28) of ChRCCs also contained nuclear positivity for ERBB4, which was uncommonly seen in ROs (3/25, 12%; P <.001). A hemizygous ERBB4 gene deletion was detected in 46% of ChRCCs (13/28), but none of the ROs (0/25; 0%). Loss of labeling by RB1 or nuclear staining for ERBB4 IHC identified 25 of 28 (89%) of ChRCCs. Conclusion. In summary, the loss of RB1 expression is a highly specific diagnostic biomarker in distinguishing ChRCC from RO. Nuclear ERBB4 expression also appears to be a sensitive diagnostic biomarker for ChRCC, albeit the mechanism is unknown. [ABSTRACT FROM AUTHOR]

Purpose: The aim of the present retrospective single-center study is to evaluate the diagnostic performance of contrast-enhanced ultrasound (CEUS) in the evaluation of renal oncocytoma. Method: Thirteen patients with histopathologically confirmed renal oncocytoma and 26 patients with histopathologically confirmed renal cell carcinoma were included in this retrospective single-center study on whom CEUS was performed between 2005 and 2015. The applied contrast agent was a second-generation blood pool agent. CEUS examinations were performed and interpreted by a single radiologist with more than 15 years of experience (EFSUMB Level 3). Results: CEUS examinations were successfully performed in all included patients without any adverse effects. Renal oncocytomas showed varying echogenicity (46% hypoechoic, 23% hyperechoic, 8% iso-/hyperechoic, 8% isoechoic). In two cases renal oncocytoma only demarcated upon i.v. application of contrast medium. In bilateral oncocytosis, lesions presented as hyperechoic. Only 23% of renal oncocytomas showed slight vascularization using Color Doppler. No oncocytoma-specific pattern of microperfusion could be elucidated: 85% of the oncocytomas presented hyperenhancing, of whom 50% also showed delayed venous wash-out; 8% of renal oncocytomas showed venous wash-out without early arterial hyperenhancement. Conclusions: Within the frame of the present study and in line with the recent state of knowledge, no specific sonomorphological feature – including CEUS – could be detected allowing for adequate discrimination between oncocytoma and renal cell carcinoma. [ABSTRACT FROM AUTHOR]

Renal Oncocytomas are rare benign renal masses. They can be easily mistaken for Renal Cell Cancers and patients usually undergo a radical nephrectomy. We present a case of a female patient who was admitted with a large mass originating from the right kidney. The results from the CT (stellate scar) and the angiography (spoke-wheel pattern) were consistent with Renal Oncocytoma, but still a radical nephrectomy was performed. This decision was made due to the inability of the current diagnostic procedures to safely differentiate Renal Oncocytomas from Renal Cell Cancers. [ABSTRACT FROM AUTHOR]

Renal oncocytoma is a benign epithelial neoplasm typically composed of large cells with granular eosinophilic cytoplasm. Although rare, histologically worrisome features such as vascular and perinephric fat invasion have been reported. Of the 159 renal oncocytomas resected at our institution, 20 (12.6%) had vascular and/or perinephric fat invasion. Microscopically, 10 oncocytomas had perinephric fat invasion, 7 had vascular invasion and 3 had both vascular and perinephric fat invasion. Grossly, perinephric fat invasion was visible in three cases and tumour was identified within the branches of the renal vein in two cases. Tumours occurred in 14 men and 6 women (M:F = 2.3:1). The mean age at diagnosis was 64.5 years (range, 33-88 years). A total of 11 cases had radical nephrectomies while 9 cases had partial nephrectomies. There was no evidence of disease recurrence, metastasis or death due to tumour after a mean follow up of 25.6 months (range, 2-103 months). The presence of vascular and perinephric fat invasion in renal oncocytoma though worrisome, does not alter the benign course of the tumour. [ABSTRACT FROM AUTHOR]

Background: The present study aims to evaluate the diagnostic performance of contrast-enhanced ultrasound (CEUS) for discriminating between benign and malignant solid renal masses. Methods: 18 patients with histopathologically confirmed benign solid renal masses (11 oncocytomas, seven angiomyolipomas) as well as 96 patients with confirmed renal cell carcinoma (RCC) who underwent CEUS followed by radical or partial nephrectomy were included in this single-center study. CEUS examinations were performed by an experienced radiologist (EFSUMB Level 3) and included the application of a second-generation contrast agent. Results: Renal angiomyolipomas, oncocytomas, and renal cell carcinomas showed varying sonomorphological characteristics in CEUS. Angiomyolipomas showed heterogeneous echogenicity (57% hypo-, 43% hyperechoic), while all lesions showed rapid contrast-enhancement with two lesions also showing venous wash-out (29%). Notably, 9/11 oncocytomas could be detected in conventional ultrasound (64% hypo-, 9% hyper-, 9% isoechoic) and 2/11 only demarcated upon intravenous application of contrast agent (18%). All oncocytomas showed hyperenhancement in CEUS, venous wash-out was registered in 7/11 lesions (64%). Conclusions: In line with the current state of knowledge, no specific sonomorphological characteristics allowing for accurate distinction between benign and malignant solid renal masses in CEUS could be detected in our study.

Renal oncocytosis is a rare condition in which the kidney develops numerous oncocytomas. We present a case of a 12-year-old female who presented with right-sided flank pain of one-year duration. Imaging revealed several masses in the right kidney. Tissue biopsy confirmed multiple benign oncocytomas. Due to the presence of multiple oncocytomas throughout the kidney, a radical nephrectomy was performed. Given the rarity of this condition, as well as its known association with von Hippel-Lindau disease and Birt-Hogg-Dube syndrome, genetic investigations were pursued but failed to identify any abnormalities. This patient remains well and disease free six years after surgery. A review of the literature of this rare condition was performed.