Cystic renal masses

Differentiating mixed epithelial and stromal tumor family from predominantly cystic renal cell carcinoma using magnetic resonance imaging-based Bosniak classification system version 2019

PURPOSE

To differentiate mixed epithelial and stromal tumor family (MESTF) of the kidney from predominantly cystic renal cell carcinoma (RCC) using the magnetic resonance imaging (MRI)-based Bosniak classification system version 2019 (v2019).

MATERIALS AND METHODS

The study included 36 consecutive patients with MESTF and 77 with predominantly cystic RCC who underwent preoperative renal MRI. One radiologist evaluated and documented the clinical and MRI characteristics (age, sex, laterality, R.E.N.A.L. Nephrometry Score [RNS], surgical approach, the signal intensity on T2-weighted imaging, restricted diffusion and enhancement features in corticomedullary phase). Blinded to clinical and pathological information, another two radiologists independently evaluated Bosniak category of all masses. Interobserver agreement based on Bosniak classification system v2019 was measured by the weighted Cohen/Conger's Kappa coefficient. Furthermore, predominantly cystic RCCs and MESTFs were divided into low (categories I, II, and IIF) and high-class (categories III, and IV) tumors. The independent sample t test (Mann-Whitney U test) or Pearson Chi-square test (Fisher's exact probability test) was utilized to compare clinical and imaging characteristics between MESTFs and predominantly cystic RCCs. The performance of the Bosniak classification system v2019 in distinguishing MESTF from predominantly cystic RCC was investigated via receiver operating characteristic curve analysis.

RESULTS

MESTF and predominantly cystic RCC groups significantly differed in terms of age, lesion size, RNS, restricted diffusion, and obvious enhancement in corticomedullary phase, but not sex, laterality, surgical approach, and the signal intensity on T2WI. Interobserver agreement was substantially based on the Bosniak classification system v2019. There were 24 low-class tumors and 12 high-class tumors in the MESTF group. Meanwhile, 13 low-class tumors and 64 high-class tumors were observed in the predominantly cystic RCC group. The distribution of low- or high-class tumors significantly differed between the MESTF and predominantly cystic RCC groups. Bosniak classification system v2019 had excellent discrimination (cutoff value = category III), and an area under curve value was 0.81; accuracy, 80.5%; sensitivity, 87.0%; and specificity, 66.7%.

CONCLUSION

The MRI-based Bosniak classification system v2019 can effectively distinguish MESTF from predominantly cystic RCC if category III was used as a cutoff reference.

The efficacy of the new Bosniak classification v.2019 in benign lesions prediction within the higher Bosniak cysts classes

INTRODUCTION

Identification of benign lesions among higher classes of renal Bosniak cysts who are vulnerable to active surveillance instead of surgical approach is still questionable. We aimed in this study to delineate the efficacy of the new Bosniak v2019 classification in benign lesions identification among those cases with higher Bosniak classes in comparison with the final histopathology.

MATERIALS

In a retrospective review between 2010 and 2021 for patients diagnosed as higher classes Bosniak renal masses was done. Patients' demographics and radiological data i.e.,: age, gender, and final Bosniak v2019 categorization for class III: (1) Enhancing thick wall/septa >4 mm (III-WS) and (2) Enhancing irregular wall/septa or convex protrusion with obtuse margins <3 mm (III-OP) and for class IV as: (1) Enhancing nodule or convex protrusion with obtuse margins >4 mm (IV-OP) and (2) Enhancing nodule or convex protrusion with acute margins of any size (IV-AP).

RESULTS

A total of 137 patients were included. Bosniak III was identified in 56 patients. Malignancy was detected in 74.5% of resected masses. Among resected Bosniak III cyst, 46.4% were benign histopathologically. Male gender and Bosniak III-OP were independent risks for malignancy among the resected Bosniak III cysts. Conversely, in resected Bosniak IV renal cysts, only 9 of resected masses were benign. In univariate analysis, male gender, absence of multilocular cyst and endophytic masses were predictors for malignancy in resected Bosniak IV cyst. None of the previous predictors was significant in multivariate analysis.

CONCLUSION

The Bosniak subclassification v.2019 can define benign lesions. Bosniak III-OP was an independent risk for malignancy detection among the resected Bosniak III cysts.

Application of Contrast-enhanced Ultrasound and Bosniak Classification to the Diagnosis of Cystic Renal Masses

BACKGROUND

The Bosniak classification system based on contrast-enhanced computed tomography (CECT) is commonly used for the differential diagnosis of cystic renal masses. Contrastenhanced ultrasound (CEUS) is a relatively novel technique, which has gradually played an important role in the diagnosis of cystic renal cell carcinoma (CRCC) due to its safety and lowest price.

OBJECTIVE

The aim of the study is to investigate the application value of CEUS and Bosniak classification into the diagnosis of cystic renal masses.

METHODS

32 cystic masses from January 2018 to December 2019 were selected. The images of conventional ultrasound (US), CEUS and CECT from subjects confirmed by surgical pathology were retrospectively analyzed. The Bosniak classification system of cystic renal masses was implemented using CEUS and CECT, and the diagnostic ability was compared.

RESULTS

For the 32 cystic masses, postoperative pathology confirmed 11 cases of multilocular CRCC, 15 cases of clear cell carcinoma with hemorrhage, necrosis and cystic degeneration, 5 cases of renal cysts, and 1 case of renal tuberculosis. The Bosniak classification based on CEUS was higher than that based on CECT, and the difference was statistically significant (P = .024). The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of CEUS were comparable to CECT. There was no significant difference observed in the diagnosis of CRCC (P >.05).

CONCLUSION

CEUS combined with Bosniak classification greatly improves the diagnosis of CRCC. CEUS shows a comparable diagnostic ability to CECT. In daily clinical routine, patients who require multiple examinations and present contraindications for CECT can particularly benefit from CEUS.

Multiparametric Magnetic Resonance Imaging and Metabolic Characterization of Patient-Derived Xenograft Models of Clear Cell Renal Cell Carcinoma

Patient-derived xenografts (PDX) are high-fidelity cancer models typically credentialled by genomics, transcriptomics and proteomics. Characterization of metabolic reprogramming, a hallmark of cancer, is less frequent. Dysregulated metabolism is a key feature of clear cell renal cell carcinoma (ccRCC) and authentic preclinical models are needed to evaluate novel imaging and therapeutic approaches targeting metabolism. We characterized 5 PDX from high-grade or metastatic ccRCC by multiparametric magnetic resonance imaging (MRI) and steady state metabolic profiling and flux analysis. Similar to MRI of clinical ccRCC, T2-weighted images of orthotopic tumors of most PDX were homogeneous. The increased hyperintense (cystic) areas observed in one PDX mimicked the cystic phenotype typical of some RCC. The negligible hypointense (necrotic) areas of PDX grown under the highly vascularized renal capsule are beneficial for preclinical studies. Mean apparent diffusion coefficient (ADC) values were equivalent to those of ccRCC in human patients. Hyperpolarized (HP) [1-13C]pyruvate MRI of PDX showed high glycolytic activity typical of high-grade primary and metastatic ccRCC with considerable intra- and inter-tumoral variability, as has been observed in clinical HP MRI of ccRCC. Comparison of steady state metabolite concentrations and metabolic flux in [U-13C]glucose-labeled tumors highlighted the distinctive phenotypes of two PDX with elevated levels of numerous metabolites and increased fractional enrichment of lactate and/or glutamate, capturing the metabolic heterogeneity of glycolysis and the TCA cycle in clinical ccRCC. Culturing PDX cells and reimplanting to generate xenografts (XEN), or passaging PDX in vivo, altered some imaging and metabolic characteristics while transcription remained like that of the original PDX. These findings show that PDX are realistic models of ccRCC for imaging and metabolic studies but that the plasticity of metabolism must be considered when manipulating PDX for preclinical studies.

Robustness and performance of radiomic features in diagnosing cystic renal masses

PURPOSE

We study the inter-reader variability in manual delineation of cystic renal masses (CRMs) presented in computerized tomography (CT) images and its effect on the classification performance of a machine learning algorithm in distinguishing benign from potentially malignant CRMs. In addition, we assessed whether the inclusion of higher-order robust radiomic features improves the classification performance over the use of first-order features.

METHODS

230 CRMs were independently delineated by two radiologists. Through a combination of random fluctuations, dilation, and erosion operations over the original region of interests (ROIs), we generated four additional sets of synthetic ROIs to capture the inter-reader variability realistically, as confirmed by dice coefficient measurements and visual assessment. We then identified the robust features based on the intra-class coefficient (ICC > 0.85) across these datasets. We applied a tenfold stratified cross-validation (CV) to train and test the performance of the random forest model for the classification of CRMs into benign and potentially malignant.

RESULTS

The mean area under the curve (AUC), sensitivity, specificity, positive predictive value, and negative predictive value were 0.87, 0.82, 0.90, 0.85, and 0.93, respectively. With the usage of first-order features alone, the corresponding values were nearly identical.

CONCLUSION

AUC ranged for the robust and uncorrelated features from 0.83 ± 0.09 to 0.93 ± 0.04 and for the first-order features from 0.84 ± 0.09 to 0.91 ± 0.04. Our study indicates that the first-order features alone are sufficient for the classification of CRMs, and that inclusion of higher-order features does not necessarily improve performance.

Comparison of Magnetic Resonance Imaging and Contrast-Enhanced Ultrasound as Diagnostic Options for Unclear Cystic Renal Lesions: A Cost-Effectiveness Analysis

PURPOSE

 Correct differentiation between malignant and benign incidentally found cystic renal lesions has critical implications for patient management. In several studies contrast-enhanced ultrasound (CEUS) showed higher sensitivity with respect to the accurate characterization of these lesions compared to MRI, but the cost-effectiveness of CEUS has yet to be investigated. The aim of this study was to analyze the cost-effectiveness of CEUS as an alternative imaging method to MRI for the characterization of incidentally found cystic renal lesions.

MATERIALS AND METHODS

 A decision model including the diagnostic modalities MRI and CEUS was created based on Markov simulations estimating lifetime costs and quality-adjusted life years (QALYs). The recent literature was reviewed to obtain model input parameters. The deterministic sensitivity of diagnostic parameters and costs was determined and probabilistic sensitivity analysis using Monte-Carlo Modelling was applied. Willingness-to-pay (WTP) was assumed to be $ 100 000/QALY.

RESULTS

 In the base-case scenario, the total costs for CEUS were $9654.43, whereas the total costs for MRI were $9675.03. CEUS resulted in an expected effectiveness of 8.06 QALYs versus 8.06 QALYs for MRI. Therefore, from an economic point of view, CEUS was identified as an adequate diagnostic alternative to MRI. Sensitivity analysis showed that results may vary if CEUS costs increase or those of MRI decrease.

CONCLUSION

 Based on the results of the analysis, the use of CEUS was identified as a cost-effective diagnostic strategy for the characterization of incidentally found cystic renal lesions.

Renal Endometriosis Mimicking Cystic Renal Tumor: Case Report and Literature Review

Background: Endometriosis mainly affects female pelvic tissues and organs, and the presence of endometriosis in the kidney is extremely rare.

Case Presentation: We report a case of a 48-year-old woman who presented with intermittent hematuria. She was found to have a cystic mass on renal ultrasonography, and contrast-enhanced computed tomography (CT) showed slight enhancement of the cystic wall and septa. These findings were indicative of cystic renal tumor. The patient subsequently underwent partial right nephrectomy. Histopathology revealed endometriosis of the right renal parenchyma. The patient recovered well and had no evidence of a recurrent renal mass at the 3 months' follow up.

Conclusion: The possibility of renal endometriosis should be considered in a female patient with a cystic renal mass and clinical symptoms related to the menstrual cycle.

Bosniak Classification of Cystic Renal Masses Version 2019: Comparison to Version 2005 for Class Distribution, Diagnostic Performance, and Interreader Agreement Using CT and MRI

Background: The Bosniak classification system for cystic renal masses (CRMs) was updated in 2019, requiring further investigation. Objective: To compare version 2005 and version 2019 of the Bosniak classification system in terms of class distribution, diagnostic performance, inter-reader agreement, and inter-modality agreement between CT and MRI. Methods: This retrospective study included 100 patients (mean age, 52.4±11.6 years; 68 men, 32 women) with 104 CRMs (74 malignant) who underwent CT, MRI, and resection between 2010 and 2019. Two radiologists independently evaluated CRMs in separate sessions for each combination of version and modality and assigned a Bosniak class. Diagnostic performance was compared using McNemar tests. Inter-reader and inter-modality agreement were analyzed using weighted kappa coefficients. Results: Across readers and modalities, proportion of class IIF was higher for version 2019 than version 2005 (reader 1: 28.8%-30.8% vs 6.7%-12.5%; reader 2: 26.0%-28.8% vs 8.7%-19.2%), although 95% CIs overlapped for reader 2 on CT. Proportion of class III was lower for version 2019 than version 2005 (reader 1: 33.7%-35.6% vs 49%-51.9%; reader 2: 31.7%-40.4% vs 37.5%-52.9%), although 95% CIs overlapped for all comparisons. Version 2019 demonstrated lower sensitivity for malignancy than version 2005 across readers and modalities (all p<.05); for example, using CT, sensitivity was 75.7% for both readers with version 2019, versus 85.1%-87.8% with version 2005. However, version 2019 demonstrated higher specificity than version 2005, which was significant (all p<.05) for reader 1 For example, using CT, specificity was 73.3% (reader 1) and 70.0% (reader 2) with version 2019, versus 50.0% (reader 1) and 56.7% (reader 2) with version 2005. Diagnostic accuracy was not different between versions (version 2005: 76.9%-85.6%; version 2019: 74.0%-78.8%). Inter-reader and inter- modality agreement were substantial for version 2005 (κ=0.676-0.782; 0.711-0.723) and version 2019 (κ=0.756-0.804; 0.704-0.781). Conclusion: Version 2019, versus version 2005, results in shift in CRM assignment from class III to class IIF. Version 2019 results in lower sensitivity, higher specificity, and similar accuracy versus version 2005. Inter-reader and inter-modality agreement are similar between versions. Clinical impact: Version 2019 facilitates recommending imaging surveillance for more CRMs.

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

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

Imaging evaluation of hereditary renal tumors: a pictorial review

More than 10 hereditary renal tumor syndromes (HRTSs) and related germline mutations have been reported with HRTS-associated renal and extrarenal manifestations with benign and malignant tumors. Radiologists play an important role in detecting solitary or multiple renal masses with or without extrarenal findings on imaging and may raise the possibility of an inherited predisposition to renal cell carcinoma, providing direction for further screening, intervention and surveillance of the patients and their close family members before the development of potentially lethal renal and extrarenal tumors. Renal cell carcinomas (RCCs) associated with von Hippel-Lindau disease are typically slow growing while RCCs associated with HRTSs, such as hereditary leiomyomatosis and renal cell carcinoma syndrome, are highly aggressive. Therefore, radiologists need to be familiar with clinical and imaging findings of renal and extrarenal manifestations of HRTSs. This article reviews clinical and imaging findings for the evaluation of patients with well-established HRTSs from a radiologist's perspective to facilitate the clinical decision-making process for patient management.

Stratification of cystic renal masses into benign and potentially malignant: applying machine learning to the bosniak classification

PURPOSE

To create a CT texture-based machine learning algorithm that distinguishes benign from potentially malignant cystic renal masses as defined by the Bosniak Classification version 2019.

METHODS

In this IRB-approved, HIPAA-compliant study, 4,454 adult patients underwent renal mass protocol CT or CT urography from January 2011 to June 2018. Of these, 257 cystic renal masses were included in the final study cohort. Each mass was independently classified using Bosniak version 2019 by three radiologists, resulting in 185 benign (Bosniak I or II) and 72 potentially malignant (Bosniak IIF, III or IV) masses. Six texture features: mean, standard deviation, mean of positive pixels, entropy, skewness, kurtosis were extracted using commercial software TexRAD (Feedback PLC, Cambridge, UK). Random forest (RF), logistic regression (LR), and support vector machine (SVM) machine learning algorithms were implemented to classify cystic renal masses into the two groups and tested with tenfold cross validations.

RESULTS

Higher mean, standard deviation, mean of positive pixels, entropy, skewness were statistically associated with the potentially malignant group (P ≤ 0.0015 each). Sensitivity, specificity, positive predictive value, negative predictive value, and area under curve of RF model was 0.67, 0.91, 0.75, 0.88, 0.88; of LR model was 0.63, 0.93, 0.78, 0.86, 0.90, and of SVM model was 0.56, 0.91, 0.71, 0.84, 0.89, respectively.

CONCLUSION

Three CT texture-based machine learning algorithms demonstrated high discriminatory capability in distinguishing benign from potentially malignant cystic renal masses as defined by the Bosniak Classification version 2019. If validated, CT texture-based machine learning algorithms may help reduce interreader variability when applying the Bosniak classification.

Clinical use of contrast-enhanced ultrasound beyond the liver: a focus on renal, splenic, and pancreatic applications

Contrast-enhanced ultrasound (CEUS) is a relatively novel, but increasingly used, diagnostic imaging modality. In recent years, due to its safety, quickness, and repeatability, several studies have demonstrated the accuracy, specificity, and sensitivity of CEUS. The European Federation of Societies for Ultrasound in Medicine and Biology has recently updated the previous guidelines from 2012 for the use of CEUS in non-hepatic applications. This review deals with the clinical use and applications of CEUS for the evaluation of non-hepatic abdominal organs, focusing on renal, splenic, and pancreatic applications.

Imaging Manifestations of Acute and Chronic Renal Infection That Mimics Malignancy: How to Make the Diagnosis Using Computed Tomography and Magnetic Resonance Imaging

PURPOSE

To review the computed tomography and magnetic resonance imaging manifestations of acute and chronic renal infections that may mimic malignancy and to provide useful tips to establish an imaging diagnosis.

CONCLUSION

Acute and chronic bacterial pyelonephritis are usually readily diagnosed clinically and on imaging when the diagnosis is suspected based upon clinical presentation. When unsuspected, focal, extensive or mass-like, acute and chronic bacterial pyelonephritis may mimic infiltrative tumours such as urothelial cell carcinoma (UCC), lymphoma, and metastatic disease. Infection may be suspected when patients are young and otherwise healthy when there is marked associated perinephric changes and in the absence of metastatic adenopathy or disease elsewhere in the abdomen and pelvis. Renal abscesses, from bacterial or atypical microbial agents, can appear as complex cystic renal masses mimicking cystic renal cell carcinoma. Associated inflammatory changes in and around the kidney and local invasion favour infection. Emphysematous pyelonephritis can mimic necrotic or fistulizing tumour; however, infection is more likely and should always be considered first. Xanthogranulomatous pyelonephritis can mimic malignancy when focal or multifocal and in cases without associated renal calculi. Malacoplakia is an inflammatory process that may mimic malignancy and should be considered in patients with chronic infection. Bacillus Calmette-Guerin (BCG)-induced pyelonephritis is rare but can mimic renal malignancy and should be considered in patients presenting with a renal mass when being treated with BCG for urinary bladder UCC.

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

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

Comparison of contrast-enhanced ultrasound with MRI in the diagnosis of complex cystic renal masses: a meta-analysis

Background The differential diagnosis of cystic renal masses still faces great challenges. There has been no systematically assessment to compare the value of contrast-enhanced ultrasound (CEUS) with magnetic resonance imaging (MRI) in the diagnosis of cystic renal masses. Purpose To perform a meta-analysis to compare the diagnostic efficacy of CEUS with that of MRI for cystic renal masses. Material and Methods A systematic search was performed for literature evaluating the diagnostic performance of CEUS or MRI in cystic renal masses. Quality assessment of diagnostic studies 2 (QUADAS-2) was used to evaluate the quality of each study included. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and the areas under the summary receiver operating characteristic (AUCs-SROC) curve for CEUS and MRI were calculated, respectively. Results Seventeen studies with 1142 lesions were included. The pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio for CEUS /MRI were 0.95/0.92, 0.84/0.91, 5.62/6.74, and 0.09/0.13, respectively. The AUCs-SROC curves for the two methods were 95.66% and 94.65%. The subgroup analysis indicated that the scanning slice thickness may influence the diagnostic efficacy of MRI. Conclusion Both CEUS and MRI have good diagnostic performance for cystic renal masses and can provide the reference for clinicians. CEUS is more sensitive but less specific than MRI.

Urologic Diseases Germane to the Medical Renal Biopsy: Review of a Large Diagnostic Experience in the Context of the Renal Architecture and Its Environs

The kidney is one of the most complicated organs in development and is susceptible to more types of diseases than other organs. The disease spectrum includes developmental and cystic diseases, involvement by systemic diseases, iatrogenic complications, ascending infections and urinary tract obstruction, and neoplastic diseases. The diagnosis of kidney disease is unique involving 2 subspecialties, urologic pathology and renal pathology. Both renal and urologic pathologists employ the renal biopsy as a diagnostic modality. However, urologic pathologists commonly have a generous specimen in the form of a nephrectomy or partial nephrectomy while a renal pathologist requires ancillary modalities of immunofluorescence and electron microscopy. The 2 subspecialties differ in the disease spectrum they diagnose. This separation is not absolute as diseases of one subspecialty not infrequently appear in the diagnostic materials of the other. The presence of medical renal diseases in a nephrectomy specimen is well described and recommendations for reporting these findings have been formalized. However, urologic diseases appearing in a medical renal biopsy have received less attention. This review attempts to fill that gap by first reviewing the perirenal anatomy to illustrate why inadvertent biopsy of adjacent organs occurs and determine its incidence in renal biopsies followed by a discussion of gross anatomic features relevant to the microscopic domain of the medical renal biopsy. Unsuspected neoplasms and renal cysts and cystic kidney diseases will then be discussed as they create a diagnostic challenge for the renal pathologist who often has limited training and experience in these diseases.

Minimally Complex Renal Cysts: Outcomes and Ultrasound Evaluation Compared with Contrast-Enhanced Cross-Sectional Imaging Bosniak Classification

We correlated contrast-enhanced cross-sectional imaging and outcomes to assess the reproducibility of ultrasonographic criteria for renal minimally complex (MC) cysts. From 2003 to 2015, 143 cysts were described as complex or MC by ultrasound (US). After exclusions, 98 US studies were retrospectively evaluated and compared with computed tomography (CT)/magnetic resonance imaging (MRI). At sonography, 51 were MC cysts and 47 were complexes according to two independent observers. Inter-observer agreement for US was 0.704 and 0.745 for CT/MRI. Of 51 cysts classified as MC by US, 38 were Bosniak I/II and 6 were Bosniak IIF by CT/MRI. In 7, there were no cross-sectional images; however, they were stable for at least 2 y. Of 47 complex cysts, 9 were Bosniak II, 22 Bosniak IIF, 8 Bosniak III and 8 Bosniak IV. No Bosniak III/IV cysts by CT/MRI were classified as MC by US. Our results indicate that US offers reproducible criteria for MC cysts and may be used alone for these lesions.