MRI evaluation of complex renal cysts using the Bosniak classification: a comparison to CT

Multiparametric MRI-Based Machine Learning Models for the Characterization of Cystic Renal Masses Compared to the Bosniak Classification, Version 2019: A Multicenter Study

RATIONALE AND OBJECTIVE

Accurate differentiation between benign and malignant cystic renal masses (CRMs) is challenging in clinical practice. This study aimed to develop MRI-based machine learning models for differentiating between benign and malignant CRMs and compare the best-performing model with the Bosniak classification, version 2019 (BC, version 2019).

METHODS

Between 2009 and 2021, consecutive surgery-proven CRM patients with renal MRI were enrolled in this multicenter study. Models were constructed to differentiate between benign and malignant CRMs using logistic regression (LR), random forest (RF), and support vector machine (SVM) algorithms, respectively. Meanwhile, two radiologists classified CRMs into I-IV categories according to the BC, version 2019 in consensus in the test set. A subgroup analysis was conducted to investigate the performance of the best-performing model in complicated CRMs (II-IV lesions in the test set). The performances of models and BC, version 2019 were evaluated using the area under the receiver operating characteristic curve (AUC). Performance was statistically compared between the best-performing model and the BC, version 2019.

RESULTS

278 and 48 patients were assigned to the training and test sets, respectively. In the test set, the AUC and accuracy of the LR model, the RF model, the SVM model, and the BC, version 2019 were 0.884 and 75.0%, 0.907 and 83.3%, 0.814 and 72.9%, and 0.893 and 81.2%, respectively. Neither the AUC nor the accuracy of the RF model that performed best were significantly different from the BC, version 2019 (P = 0.780, P = 0.065). The RF model achieved an AUC and accuracy of 0.880 and 81.0% in complicated CRMs.

CONCLUSIONS

The MRI-based RF model can accurately differentiate between benign and malignant CRMs with comparable performance to the BC, version 2019, and has good performance in complicated CRMs, which may facilitate treatment decision-making and is less affected by interobserver disagreements.

Cystic Renal Masses: Old and New Paradigms

Cystic renal masses describe a spectrum of lesions with benign and/or malignant features. Cystic renal masses are most often identified incidentally with the Bosniak classification system stratifying their malignant potential. Solid enhancing components most often represent clear cell renal cell carcinoma yet display an indolent natural history relative to pure solid renal masses. This has led to an increased adoption of active surveillance as a management strategy in those who are poor surgical candidates. This article provides a contemporary overview of historical and emerging clinical paradigms in the diagnosis and management of this distinct clinical entity.

Role of multiparametric MRI in characterization of complicated cystic renal masses

Background

Bosniak classification improves sensitivity and specificity for malignancy among cystic renal masses characterized with MRI. The quantitative parameters derived from diffusion-weighted imaging, and contrast enhancement, can be used in distinguishing between benign and malignant cystic renal masses.

Methods

This prospective observational study included 58 patients (39 male and 19 female) with complicated cystic renal mass initially diagnosed by US or CT. All patients underwent multiparametric MRI study (Pre- and Post-Gd-enhanced T1WI, T2WI and DWI) by using 3 Tesla MRI scanner. Each cystic renal lesion was assigned a category based on Bosniak classification. Demographic data were recorded. ADC ratio, dynamic enhancement parameters in both corticomedullary and nephrographic phases as well as absolute washout were calculated and compared using ROC curve analysis.

Results

The sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of the multiparametric MRI in categorization of cystic renal masses according to Bosniak classification version 2019 were 90.32%, 100%, 100%, 90% and 94.83%, respectively, which was higher compared to biparametric MRI and conventional MRI.

Conclusions

Multiparametric MRI can be utilized to confidently evaluate cystic renal masses, overcoming the traditional limitations of overlapping morphological imaging features. Quantitative parameters derived from multiparametric MRI allow better evaluation of complex cystic renal tumors to distinguish between benign and malignant complex cystic renal lesions.

Bosniak classification version 2019: a prospective comparison of CT and MRI

OBJECTIVE

To assess the diagnostic accuracy and agreement of CT and MRI in terms of the Bosniak classification version 2019 (BCv2019).

MATERIALS AND METHODS

A prospective multi-institutional study enrolled 63 patients with 67 complicated cystic renal masses (CRMs) discovered during ultrasound examination. All patients underwent CT and MRI scans and histopathology. Three radiologists independently assessed CRMs using BCv2019 and assigned Bosniak class to each CRM using CT and MRI. The final analysis included 60 histopathologically confirmed CRMs (41 were malignant and 19 were benign).

RESULTS

Discordance between CT and MRI findings was noticed in 50% (30/60) CRMs when data were analyzed in terms of the Bosniak classes. Of these, 16 (53.3%) were malignant. Based on consensus reviewing, there was no difference in the sensitivity, specificity, and accuracy of the BCv2019 with MRI and BCv2019 with CT (87.8%; 95% CI = 73.8-95.9% versus 75.6%; 95% CI = 59.7-87.6%; p = 0.09, 84.2%; 95% CI = 60.4-96.6% versus 78.9%; 95% CI = 54.4-93.9%; p = 0.5, and 86.7%; 95% CI = 64.0-86.6% versus 76.7%; 95% CI = 75.4-94.1%; p = 0.1, respectively). The number and thickness of septa and the presence of enhanced nodules accounted for the majority of variations in Bosniak classes between CT and MRI. The inter-reader agreement (IRA) was substantial for determining the Bosniak class in CT and MRI (k = 0.66; 95% CI = 0.54-0.76, k = 0.62; 95% CI = 0.50-0.73, respectively). The inter-modality agreement of the BCv219 between CT and MRI was moderate (κ = 0.58).

CONCLUSION

In terms of BCv2019, CT and MRI are comparable in the classification of CRMs with no significant difference in diagnostic accuracy and reliability.

KEY POINTS

• There is no significant difference in the sensitivity, specificity, and accuracy of the BCv2019 with MRI and BCv2019 with CT. • The number of septa and their thickness and the presence of enhanced nodules accounted for the majority of variations in Bosniak classes between CT and MRI. • The inter-reader agreement was substantial for determining the Bosniak class in CT and MRI and the inter-modality agreement of the BCv219 between CT and MRI was moderate.

Deep learning and radiomic feature-based blending ensemble classifier for malignancy risk prediction in cystic renal lesions

BACKGROUND

The rising prevalence of cystic renal lesions (CRLs) detected by computed tomography necessitates better identification of the malignant cystic renal neoplasms since a significant majority of CRLs are benign renal cysts. Using arterial phase CT scans combined with pathology diagnosis results, a fusion feature-based blending ensemble machine learning model was created to identify malignant renal neoplasms from cystic renal lesions (CRLs). Histopathology results were adopted as diagnosis standard. Pretrained 3D-ResNet50 network was selected for non-handcrafted features extraction and pyradiomics toolbox was selected for handcrafted features extraction. Tenfold cross validated least absolute shrinkage and selection operator regression methods were selected to identify the most discriminative candidate features in the development cohort. Feature's reproducibility was evaluated by intra-class correlation coefficients and inter-class correlation coefficients. Pearson correlation coefficients for normal distribution and Spearman's rank correlation coefficients for non-normal distribution were utilized to remove redundant features. After that, a blending ensemble machine learning model were developed in training cohort. Area under the receiver operator characteristic curve (AUC), accuracy score (ACC), and decision curve analysis (DCA) were employed to evaluate the performance of the final model in testing cohort.

RESULTS

The fusion feature-based machine learning algorithm demonstrated excellent diagnostic performance in external validation dataset (AUC = 0.934, ACC = 0.905). Net benefits presented by DCA are higher than Bosniak-2019 version classification for stratifying patients with CRL to the appropriate surgery procedure.

CONCLUSIONS

Fusion feature-based classifier accurately distinguished malignant and benign CRLs which outperformed the Bosniak-2019 version classification and illustrated improved clinical decision-making utility.

Multiparametric magnetic resonance imaging for characterizing renal tumors: A validation study of the algorithm presented by Cornelis et al

Objectives

In the last decade, the incidence of renal cell carcinoma (RCC) has been rising, with the greatest increase observed for solid tumors. Magnetic resonance imaging (MRI) protocols and algorithms have recently been available for classifying RCC subtypes and benign subtypes. The objective of this study was to prospectively validate the MRI algorithm presented by Cornelis et al. for RCC classification.

Material and Methods

Over a 7-month period, 38 patients with 44 renal tumors were prospectively included in the study and received an MRI examination in addition to the conventional investigation program. The MRI sequences were: T2-weighted, dual chemical shift MRI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced T1-weighted in wash-in and wash-out phases. The images were evaluated according to the algorithm by two experienced, blinded radiologists, and the histopathological diagnosis served as the gold standard.

Results

Of 44 tumors in 38 patients, only 8 tumors (18.2%) received the same MRI diagnosis according to the algorithm as the histopathological diagnosis. MRI diagnosed 16 angiomyolipoma, 14 clear cell RCC (ccRCC), 12 chromophobe RCC (chRCC), and two papillary RCC (pRCC), while histopathological examination diagnosed 24 ccRCC, four pRCC, one chRCC, and one mixed tumor of both pRCC and chRCC. Malignant tumors were statistically significantly larger than the benign (3.16 ± 1.34 cm vs. 2.00 ± 1.04 cm, P = 0.006).

Conclusion

This prospective study could not reproduce Cornelis et al.'s results and does not support differentiating renal masses using multiparametric MRI without percutaneous biopsy in the future. The MRI algorithm showed few promising results to categorize renal tumors, indicating histopathology for clinical decisions and follow-up regimes of renal masses are still required.

Stratification of malignant renal neoplasms from cystic renal lesions using deep learning and radiomics features based on a stacking ensemble CT machine learning algorithm

Using nephrographic phase CT images combined with pathology diagnosis, we aim to develop and validate a fusion feature-based stacking ensemble machine learning model to distinguish malignant renal neoplasms from cystic renal lesions (CRLs). This retrospective research includes 166 individuals with CRLs for model training and 47 individuals with CRLs in another institution for model testing. Histopathology results are adopted as diagnosis criterion. Nephrographic phase CT scans are selected to build the fusion feature-based machine learning algorithms. The pretrained 3D-ResNet50 CNN model and radiomics methods are selected to extract deep features and radiomics features, respectively. Fivefold cross-validated least absolute shrinkage and selection operator (LASSO) regression methods are adopted to identify the most discriminative candidate features in the development cohort. Intraclass correlation coefficients and interclass correlation coefficients are employed to evaluate feature’s reproducibility. Pearson correlation coefficients for normal distribution features and Spearman’s rank correlation coefficients for non-normal distribution features are used to eliminate redundant features. After that, stacking ensemble machine learning models are developed in the training cohort. The area under the receiver operator characteristic curve (ROC), calibration curve, and decision curve analysis (DCA) are adopted in the testing cohort to evaluate the performance of each model. The stacking ensemble machine learning algorithm reached excellent diagnostic performance in the testing dataset. The calibration plot shows good stability when using the stacking ensemble model. Net benefits presented by DCA are higher than the Bosniak 2019 version classification when employing any machine learning algorithm. The fusion feature-based machine learning algorithm accurately distinguishes malignant renal neoplasms from CRLs, which outperformed the Bosniak 2019 version classification, and proves to be more applicable for clinical decision-making.

Diagnostic performance of the Bosniak classification, version 2019 for cystic renal masses: A systematic review and meta-analysis

Purpose

To systematically assess the diagnostic performance of the Bosniak classification, version 2019 for risk stratification of cystic renal masses.

Methods

We conducted an electronic literature search on Web of Science, MEDLINE (Ovid and PubMed), Cochrane Library, EMBASE, and Google Scholar to identify relevant articles between June 1, 2019 and March 31, 2022 that used the Bosniak classification, version 2019 for risk stratification of cystic renal masses. Summary estimates of sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR−), and diagnostic odds ratio (DOR) were pooled with the bivariate model and hierarchical summary receiver operating characteristic (HSROC) model. The quality of the included studies was assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

Results

A total of eight studies comprising 720 patients were included. The pooled sensitivity and specificity were 0.85 (95% CI 0.79–0.90) and 0.68 (95% CI 0.58–0.76), respectively, for the class III/IV threshold, with a calculated area under the HSROC curve of 0.84 (95% CI 0.81–0.87). The pooled LR+, LR−, and DOR were 2.62 (95% CI 2.0–3.44), 0.22 (95% CI 0.16–0.32), and 11.7 (95% CI 6.8–20.0), respectively. The Higgins I² statistics demonstrated substantial heterogeneity across studies, with an I² of 57.8% for sensitivity and an I² of 74.6% for specificity. In subgroup analyses, the pooled sensitivity and specificity for CT were 0.86 and 0.71, respectively, and those for MRI were 0.87 and 0.67, respectively. In five studies providing a head-to-head comparison between the two versions of the Bosniak classification, the 2019 version demonstrated significantly higher specificity (0.62 vs. 0.41, p < 0.001); however, it came at the cost of a significant decrease in sensitivity (0.88 vs. 0.94, p = 0.001).

Conclusions

The Bosniak classification, version 2019 demonstrated moderate sensitivity and specificity, and there was no difference in diagnostic accuracy between CT and MRI. Compared to version 2005, the Bosniak classification, version 2019 has the potential to significantly reduce overtreatment, but at the cost of a substantial decline in sensitivity.

Ultrasound, CT, and MR Imaging for Evaluation of Cystic Renal Masses

Cystic renal masses are often encountered during abdominal imaging. Although most of them are benign simple cysts, some cystic masses have malignant characteristics. The Bosniak classification system provides a useful way to classify cystic masses. The Bosniak classification is based on the results of a well-established computed tomography protocol. Over the past 30 years, the classification system has been refined and improved. This paper reviews the literature on this topic and compares the advantages and disadvantages of different screening and classification methods. Patients will benefit from multimodal diagnosis for lesions that are difficult to classify after a single examination.

A Comprehensive Commentary on the Multilocular Cystic Renal Neoplasm of Low Malignant Potential: A Urologist’s Perspective

Multilocular cystic renal neoplasm of low malignant potential (MCRNLMP) is a cystic renal tumor with indolent clinical behavior. In most of cases, it is an incidental finding during the examination of other health issues. The true incidence rate is estimated to be between 1.5% and 4% of all RCCs. These lesions are classified according to the Bosniak classification as Bosniak category III. There is a wide spectrum of diagnostic tools that can be utilized in the identification of this tumor, such as computed tomography (CT), magnetic resonance (MRI) or contrast-enhanced ultrasonography (CEUS). Management choices of these lesions range from conservative approaches, such as clinical follow-up, to surgery. Minimally invasive techniques (i.e., robotic surgery and laparoscopy) are preferred, with an emphasis on nephron sparing surgery, if clinically feasible.

Active Surveillance of Renal Masses: The Role of Radiology

Active surveillance of renal masses, which includes serial imaging with the possibility of delayed treatment, has emerged as a viable alternative to immediate therapeutic intervention in selected patients. Active surveillance is supported by evidence that many benign masses are resected unnecessarily, and treatment of small cancers has not substantially reduced cancer-specific mortality. These data are a call to radiologists to improve the diagnosis of benign renal masses and differentiate cancers that are biologically aggressive (prompting treatment) from those that are indolent (allowing treatment deferral). Current evidence suggests that active surveillance results in comparable cancer-specific survival with a low risk of developing metastasis. Radiology is central in this. Imaging is used at the outset to estimate the probability of malignancy and degree of aggressiveness in malignant masses and to follow up masses for growth and morphologic change. Percutaneous biopsy is used to provide a more definitive histologic diagnosis and to guide treatment decisions, including whether active surveillance is appropriate. Emerging applications that may improve imaging assessment of renal masses include standardized assessment of cystic and solid masses and radiomic analysis. This article reviews the current and future role of radiology in the care of patients with renal masses undergoing active surveillance.

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.

Prospective Comparison of Contrast-Enhanced Ultrasound and Magnetic Resonance Imaging to Computer Tomography for the Evaluation of Complex Cystic Renal Lesions

OBJECTIVE

To prospectively evaluate the diagnostic accuracy of contrast enhanced ultrasound (CEUS) and MRI compared to computed tomography (CT) as the current gold standard for the characterization of cystic renal lesions using the Bosniak classification.

METHODS

Between July 2014 and October 2017 we prospectively enrolled patients with cystic renal lesions. Based on the Bosniak classification of complex renal lesions (≥BII-F) we evaluated the accuracy of observed agreement by Cohen's Kappa coefficient and calculated sensitivity, specificity, positive and negative predictive values (PPV/NPV) between the three imaging modalities CT, MRI and CEUS.

RESULTS

We evaluated 65 cystic renal lesions in 48 patients (median age 63 years, range 36-91 years; 18 females, 30 males). According to CT 29 (47%) of the cystic renal lesions were classified as complex. The agreement between CEUS and CT in the classification of complex cystic lesions was fair (agreement 50.8%, Kappa 0.31), and was excellent between MRI and CT (agreement 93.9%, Kappa 0.88). Compared to CT, CEUS and MRI had a sensitivity of 100% and 96.6%, a specificity of 33.3% and 91.7%, a PPV of 54.7% and 90.3%, and a NPV of 100% and 97.1% with an accuracy of 63.1% and 93.8% respectively.

CONCLUSION

CEUS has an excellent sensitivity and NPV and represents a promising non-invasive screening tool for renal cystic lesions. The classification of complex renal cysts based on MRI and CT scans correlated closely.

EFSUMB 2020 Proposal for a Contrast-Enhanced Ultrasound-Adapted Bosniak Cyst Categorization - Position Statement

The well-established Bosniak renal cyst classification is based on contrast-enhanced computed tomography determining the malignant potential of cystic renal lesions. Ultrasound has not been incorporated into this pathway. However, the development of ultrasound contrast agents coupled with the superior resolution of ultrasound makes it possible to redefine the imaging of cystic renal lesions. In this position statement, an EFSUMB Expert Task Force reviews, analyzes, and describes the accumulated knowledge and limitations and presents the current position on the use of ultrasound contrast agents in the evaluation of cystic renal lesions.

Bosniak Classification of Cystic Renal Masses Version 2019: Comparison of Categorization Using CT and MRI

BACKGROUND. Bosniak classification version 2019 proposed refinements for cystic renal mass characterization and now formally incorporates MRI, which may improve concordance with CT. OBJECTIVE. The purpose of this study is to compare concordance of CT and MRI in evaluation of cystic renal masses using Bosniak classification version 2019. METHODS. Three abdominal radiologists retrospectively reviewed 68 consecutive cystic renal masses from 45 patients assessed with both CT and MRI renal mass protocols within a year between 2005 and 2019. CT and MRI were reviewed independently and in separate sessions, using both the original and 2019 versions of Bosniak classification systems. RESULTS. Using Bosniak classification version 2019, cystic renal masses were classified into 12 category I, 19 category II, 13 category IIF, four category III, and 20 category IV by CT and eight category I, 15 category II, 23 category IIF, nine category III, and 13 category IV by MRI. Among individual features, MRI showed more septa (p < 0.001, p = 0.046, p = 0.005; McNemar test) for all three radiologists, although both CT and MRI showed a similar number of protrusions (p = 0.823, p = 1.0, p = 0.302) and maximal septa and wall thickness (p = 1.0, p = 1.0, p = 0.145). Of the discordant cases with version 2019, MRI led to a higher categorization in 12 masses. The reason for upgrade was most commonly because of protrusions identified only on MRI (n = 4), an increased number of septa (n = 3), and a new category: heterogeneously T1-weighted hyperintensity (n = 3). Neither modality was more likely to lead to a categorization change for either version 2019 (p = 0.502; McNemar test) or the original (p = 0.823) Bosniak classification system. Overall interrater agreement was substantial for both CT (κ = 0.745) and MRI (κ = 0.655) using version 2019 and was slightly higher than that of the original system for CT (κ = 0.707) and MRI (κ = 0.623). CONCLUSION. CT and MRI were concordant in the majority of cases using Bosniak classification version 2019, and category changes by modality were not statistically significant. Interrater agreements were substantial for both CT and MRI. CLINICAL IMPACT. Bosniak classification version 2019 as applied to cystic renal masses has substantial interrater agreement and does not lead to systematic category upgrades with either CT or MRI.

Contrast-enhanced ultrasound (CEUS) of cystic renal lesions in comparison to CT and MRI in a multicenter setting

PURPOSE

Contrast-enhanced-ultrasound (CEUS) has been frequently used in assessment of cystic renal lesions.

OBJECTIVE

The aim of this study was to investigate the Bosniak classification in CEUS compared to CT and MRI in a multi-center setting.

METHODS

Bosniak classification in CEUS examinations of cystic renal lesions were compared to imaging findings in computed-tomography (ceCT) and magnetic-resonance-imaging (ceMRI). Imaging results were correlated to histopathological reports. All examinations were performed by experts (EFSUMB level 3) using up-to-date CEUS examination-protocols.

RESULTS

Overall, 173 cystic renal lesions were compared to subgroups CT (n = 87) and MRI (n = 86). Using Bosniak-classification 64/87 renal cysts (73.6%) were rated equal compared to CT with upgrade of four lesions (4.6%) and downgrade of 19 lesions (21.8%) by CT (Intra-class-correlation [ICC] coefficient of 0.824 [p < 0.001]). CEUS compared to MRI, presenting different scoring especially in classes Bosniak IIF (n = 16/31) and Bosniak III (n = 16/28) with an ICC coefficient of 0.651 (p < 0.001).

CONCLUSION

CEUS can visualize even finest septal and small nodular wall enhancement, which may result in an upgrade of cystic lesions into a higher Bosniak class compared to CT or MRI. Thus, a modification of the Bosniak classification on CEUS may reduce unnecessary biopsies and surgery.

Update on MRI of Cystic Renal Masses Including Bosniak Version 2019

Incidental cystic renal masses are common, usually benign, and almost always indolent. Since 1986, the Bosniak classification has been used to express the risk of malignancy in a cystic renal mass detected at imaging. Historically, magnetic resonance imaging (MRI) was not included in that classification. The proposed Bosniak v.2019 update has formally incorporated MRI, included definitions of imaging terms designed to improve interobserver agreement and specificity for malignancy, and incorporated a variety of masses that were incompletely defined or not included in the original classification. For example, at unenhanced MRI, homogeneous masses markedly hyperintense at T₂ -weighted imaging (similar to cerebrospinal fluid) and homogeneous masses markedly hyperintense at fat suppressed T₁ -weighted imaging (approximately ≥2.5 times more intense than adjacent renal parenchyma) are classified as Bosniak II and may be safely ignored, even when they have not been imaged with a complete renal mass MRI protocol. MRI has specific advantages and is recommended to evaluate masses that at computed tomography (CT) 1) have abundant thick or nodular calcifications; 2) are homogeneous, hyperattenuating, ≥3 cm, and nonenhancing; or 3) are heterogeneous and nonenhancing. Although MRI is generally excellent for characterizing cystic renal masses, there are unique weaknesses of MRI that bear consideration. These details and others related to MRI of cystic renal masses are described in this review, with an emphasis on Bosniak v.2019. A website (https://bosniak-calculator.herokuapp.com/) and mobile phone apps named "Bosniak Calculator" have been developed for ease of assignment of Bosniak classes. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.

MRI-based Bosniak Classification of Cystic Renal Masses, Version 2019: Interobserver Agreement, Impact of Readers' Experience, and Diagnostic Performance

Background The 2019 Bosniak classification (version 2019) of cystic renal masses (CRMs) provides a systematic update to the currently used 2005 Bosniak classification (version 2005). Further validation is required before widespread application. Purpose To evaluate the interobserver agreement of MRI criteria, the impact of readers' experience, and the diagnostic performance between version 2019 and version 2005. Materials and Methods From January 2009 to December 2018, consecutive patients with CRM who had undergone renal MRI and surgical-pathologic examination were included in this retrospective study. On the basis of version 2019 and version 2005, all CRMs were independently classified by eight radiologists with different levels of experience. By using multirater κ statistics, interobserver agreement was evaluated with comparisons between classifications and between senior and junior radiologists. Diagnostic performance between classifications by dichotomizing classes I-IV into lower (I-IIF) and higher (III-IV) classes was compared by using the McNemar test. P < .05 was considered to indicate a statistically significant difference. Results A total of 207 patients (mean age ± standard deviation, 49 years ± 12; 139 male and 68 female patients) with CRMs were included. Overall, interobserver agreement was higher with version 2019 than version 2005 (weighted κ = 0.64 vs 0.50, respectively; P < .001). Interobserver agreement between senior and junior radiologists did not differ between version 2019 (weighted κ = 0.65 vs 0.64, respectively; P = .71) and version 2005 (weighted κ = 0.54 vs 0.46; P < .001). Diagnostic specificity for malignancy was higher with version 2019 than with version 2005 (83% [92 of 111] vs 68% [75 of 111], respectively; P < .001), without any difference in sensitivity (89% [85 of 96] vs 84% [81 of 96]; P = .34). Conclusion In the updated Bosniak classification, interobserver agreement improved and was unaffected by observers' experience. The diagnostic performance with version 2019 was superior to that with version 2005, with higher specificity. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Choyke in this issue.

Bosniak classification of cystic renal masses version 2019 does not increase the interobserver agreement or the proportion of masses categorized into lower Bosniak classes for non-subspecialized readers on CT or MR

PURPOSE

In a condition so prevalent as renal cysts, classifications should display satisfactory reproducibility not only among subspecialized readers. We aimed to compare the interobserver agreement of the Bosniak classification version 2019 (BC19) and current Bosniak classification (CBC) for non-subspecialized readers on CT and MRI and to verify whether BC19 leads to a downgrade of renal cystic masses when compared to CBC.

METHODS

We evaluated 50 renal cystic masses in 47 patients on MR and CT (25 per method). Eighteen readers (nine third-year radiology residents and nine abdominal imaging fellows) assessed the images using BC19 and CBC with an eight-week interval. Kappa statistic was used to assess agreement. An average score of Bosniak categories across all raters evaluated if there was downgrading of lesions on BC19.

RESULTS

The highest values of Kappa were found for fellows on CBC-MR (κ = 0.51), and the lowest values were found for residents on CBC-MR and fellows on BC19-MR (both κ = 0.36). On CBC, interobserver agreement was moderate for MR and CT (κ = 0.42 and 0.43, respectively), whereas on BC19, it was fair (κ = 0.38 and 0.40, respectively). The best agreements were in categories I (κ = 0.49-0.69) and IV (κ = 0.45-0.51). The poorest agreements occurred at IIF (κ = 0.18 on BC19-CT). There was a moderate median increase from CBC to BC19 in terms of Bosniak categories for both methods (MR [Z=-2.058, p = 0.040] and CT [Z=-2.509, p = 0.012]).

CONCLUSION

BC19, when compared to CBC, did not improve interobserver agreement nor diminished the proportion of masses categorized into lower Bosniak classes among non-subspecialized readers.

Contrast-Enhanced Ultrasound (CEUS) for Follow-Up of Bosniak 2F Complex Renal Cystic Lesions-A 12-Year Retrospective Study in a Specialized European Center

Bosniak 2F renal cystic lesions feature morphologic characteristics between Bosniak I and III categories, the majority of which remain benign. However, a minor part of Bosniak 2F lesions may progress to malignancy. The purpose of this study was to assess Bosniak 2F cystic lesions during follow-up examinations by CEUS. One-hundred-and-twelve out of 364 patients with Bosniak 2F lesions underwent follow-up CEUS examinations between February 2008 and February 2020. Twelve out of 364 patients underwent renal surgery without follow-up CEUS. The progression rate of Bosniak 2F renal lesions detected by CEUS accounted for 7.1% (8/112 patients) after a mean of 12.9 months. The first follow-up CEUS revealed 75% of progressions (6/8), the remaining 25% (2/8) of progressions were detected during second follow-up CEUS. Underlying clear-cell renal cell carcinoma was histopathologically validated in 5/8 progressive complex cystic renal lesions. Stable sonomorphologic features were observed in 92.1% (104/112 patients). CEUS depicts a promising diagnostic imaging modality in the diagnostic work-up and follow-up of complex renal cystic lesions at higher spatial and temporal resolutions than CT or MRI. Its excellent safety profile, its easy and repeatable accessibility, and low financial costs render CEUS an attractive and powerful alternative imaging tool for monitoring complex renal cystic lesions.

[Kidney Cysts and Cystic Nephropathies in Children - A Consensus Guideline by 10 German Medical Societies]

This consensus-based guideline was developed by all relevant German pediatric medical societies. Ultrasound is the standard imaging modality for pre- and postnatal kidney cysts and should also exclude extrarenal manifestations in the abdomen and internal genital organs. MRI has selected indications. Suspicion of a cystic kidney disease should prompt consultation of a pediatric nephrologist. Prenatal management must be tailored to very different degrees of disease severity. After renal oligohydramnios, we recommend delivery in a perinatal center. Neonates should not be denied renal replacement therapy solely because of their age. Children with unilateral multicystic dysplastic kidney do not require routine further imaging or nephrectomy, but long-term nephrology follow-up (as do children with uni- or bilateral kidney hypo-/dysplasia with cysts). ARPKD (autosomal recessive polycystic kidney disease), nephronophthisis, Bardet-Biedl syndrome and HNF1B mutations cause relevant extrarenal disease and genetic testing is advisable. Children with tuberous sclerosis complex, tumor predisposition (e. g. von Hippel Lindau syndrome) or high risk of acquired kidney cysts should have regular ultrasounds. Even asymptomatic children of parents with ADPKD (autosomal dominant PKD) should be monitored for hypertension and proteinuria. Presymptomatic diagnostic ultrasound or genetic examination for ADPKD in minors should only be done after thorough counselling. Simple cysts are very rare in children and ADPKD in a parent should be excluded. Complex renal cysts require further investigation.

Bosniak Classification Version 2019 of Cystic Renal Masses Assessed With MRI

OBJECTIVE. The purpose of this study was to determine how use of Bosniak classification version 2019 affects categorization and overall accuracy of MRI evaluation of cystic renal masses with tissue pathologic analysis as the reference standard. MATERIALS AND METHODS. MR images of 50 consecutively registered patients with tissue pathologic results from 2005 to 2019 were retrospectively reviewed by two abdominal radiologists. Each radiologist independently assigned a category based on the original and Bosniak classification version 2019 systems. Interreader agreements (kappa statistic) for both were calculated, and consensus reading was performed. Tissue pathologic analysis was used as the reference standard to determine whether a lesion was benign or renal cell carcinoma. RESULTS. Fifty-nine cystic renal masses were characterized as 38 renal cell carcinomas and 21 benign lesions on the basis of the results of tissue pathologic analysis. By consensus, according to the original Bosniak criteria, the renal masses were classified into three category I, five category II, four category IIF, 25 category III, and 22 category IV lesions. By consensus, according to the version 2019 criteria, the renal masses were classified into three category I, two category II, 12 category IIF, 18 category III, and 24 category IV lesions. Overall sensitivity and specificity for identifying renal cell carcinoma were 95% and 81%, respectively, with the original classification system and 100% and 86%, respectively, with version 2019. Weighted interreader agreement was moderate for both the original system (κ = 0.57) and version 2019 (κ = 0.55). CONCLUSION. Use of Bosniak classification version 2019 system improves sensitivity and specificity for malignancy among cystic renal masses characterized with MRI. Most lesions that changed categories were reclassified as Bosniak category IIF.

The effectiveness of multiparametric magnetic resonance imaging in bladder cancer (Vesical Imaging-Reporting and Data System): A systematic review

Objective

To evaluate the role of the Vesical Imaging-Reporting and Data System (VI-RADS) score in the diagnostic pathway of bladder cancer.

Methods

A systemic search of the contemporary literature was performed in December 2019 using the Medical Literature Analysis and Retrieval System Online (MEDLINE), the Excerpta Medica dataBASE (EMBASE), and Web of Science databases focussing on all available articles on VI-RADS.

Results

Overall, six of 15 articles were included. All the available articles evaluated the ability of radiologists to use the VI-RADS score for discriminating non-muscle-invasive bladder cancer (NMIBC) from muscle-invasive bladder cancer (MIBC). Considering a cut-off VI-RADS score of >2, the sensitivity, specificity, positive (PPV) and negative predictive value (NPV) were 78-91.9%, 85-91%.1, 69-78%, and 88-97.1%, respectively. Considering a VI-RADS score cut-off of >3, the sensitivity, specificity, PPV and NPV were 77-94.6%, 43.9-96.5%, 51.6-86%, and 63.7-93%, respectively. Good interobserver agreement was demonstrated in the evaluated studies with a κ score of 0.73-0.89. Only one study evaluated the utility of VI-RADS in determining the presence of MIBC in patients treated with transurethral resection of the bladder diagnosed with high-grade T1 before the second transurethral resection using a VI-RADS score cut-off of >2; the sensitivity, specificity, PPV and NPV were 85%, 93.6%, 74.5%, and 96.6%, respectively.

Conclusion

The VI-RADS score, using multiparametric magnetic resonance imaging, showed excellent results in discriminating MIBC from NMIBC. Preliminary results have been reported for its use in patients with high-grade T1 bladder cancer. These results need to be validated in high-quality real-world settings.

Abbreviations

DCE: dynamic contrast enhancement; DWI: diffusion-weighted imaging; (N)MIBC: (non-)muscle-invasive bladder cancer; mpMRI: multiparametric MRI; TURBT: transurethral resection of bladder tumour; (N)(P)PV: (negative) (positive) predictive value; SC: structural category; T2W: T2-weighted; VI-RADS: vesical imaging-reporting and data system.

Imaging protocols for renal multiparametric MRI and MR urography: results of a consensus conference from the French Society of Genitourinary Imaging

OBJECTIVES

To develop technical guidelines for magnetic resonance imaging aimed at characterising renal masses (multiparametric magnetic resonance imaging, mpMRI) and at imaging the bladder and upper urinary tract (magnetic resonance urography, MRU).

METHODS

The French Society of Genitourinary Imaging organised a Delphi consensus conference with a two-round Delphi survey followed by a face-to-face meeting. Two separate questionnaires were issued for renal mpMRI and for MRU. Consensus was strictly defined using a priori criteria.

RESULTS

Forty-two expert uroradiologists completed both survey rounds with no attrition between the rounds. Fifty-six of 84 (67%) statements of the mpMRI questionnaire and 44/71 (62%) statements of the MRU questionnaire reached final consensus. For mpMRI, there was consensus that no injection of furosemide was needed and that the imaging protocol should include T2-weighted imaging, dual chemical shift imaging, diffusion-weighted imaging (use of multiple b-values; maximal b-value, 1000 s/mm²) and fat-saturated single-bolus multiphase (unenhanced, corticomedullary, nephrographic) contrast-enhanced imaging; late imaging (more than 10 min after injection) was judged optional. For MRU, the patients should void their bladder before the examination. The protocol must include T2-weighted imaging, anatomical fast T1/T2-weighted imaging, diffusion-weighted imaging (use of multiple b-values; maximal b-value, 1000 s/mm²) and fat-saturated single-bolus multiphase (unenhanced, corticomedullary, nephrographic, excretory) contrast-enhanced imaging. An intravenous injection of furosemide is mandatory before the injection of contrast medium. Heavily T2-weighted cholangiopancreatography-like imaging was judged optional.

CONCLUSION

This expert-based consensus conference provides recommendations to standardise magnetic resonance imaging of kidneys, ureter and bladder.

KEY POINTS

• Multiparametric magnetic resonance imaging (mpMRI) aims at characterising renal masses; magnetic resonance urography (MRU) aims at imaging the urinary bladder and the collecting systems. • For mpMRI, no injection of furosemide is needed. • For MRU, an intravenous injection of furosemide is mandatory before the injection of contrast medium; heavily T2-weighted cholangiopancreatography-like imaging is optional.

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.

Progression rate in Bosniak category IIF complex renal cysts

Objective

To evaluate progression rate of Bosniak category IIF complex renal cysts and the malignancy rate among surgically resected cysts.

Materials and Methods

We performed a database search for complex renal cysts classified as Bosniak category IIF on computed tomography or magnetic resonance imaging between January 2008 and April 2016. Follow-up examinations (computed tomography or magnetic resonance imaging) were used in order to evaluate progression (Bosniak category reclassification) and stability, the latter being defined as remaining stable for a minimum of six months. Pathology reports were used as the reference to assess the malignancy rate of surgically resected cysts.

Results

A total of 152 cysts in 143 patients were included in the final analysis. Seven cysts (4.6%) were reclassified on follow-up studies, and mean time to progression was 20 months (range, 1 month to 4 years). Three cysts were surgically resected. All three were diagnosed as low-grade malignant renal cell carcinomas (RCCs): one clear cell RCC and two papillary RCCs. The remaining 145 cysts remained unchanged after a mean follow-up period of 28 months (range, 6 to 118 months).

Conclusion

The progression rate in Bosniak category IIF cysts was low. Even lesions that were upgraded on follow-up remained stable, indicating an indolent behavior. Our data support the idea of conservative management of Bosniak IIF renal cyst.

Active Surveillance Versus Nephron-Sparing Surgery for a Bosniak IIF or III Renal Cyst: A Cost-Effectiveness Analysis

OBJECTIVE

The objective of our study was to evaluate the cost-effectiveness of active surveillance (AS) versus nephron-sparing surgery (NSS) in patients with a Bosniak IIF or III renal cyst.

MATERIALS AND METHODS

Markov models were developed to estimate life expectancy and lifetime costs for 60-year-old patients with a Bosniak IIF or III renal cyst (the reference cases) managed by AS versus NSS. The models incorporated the malignancy rates, reclassification rates during follow-up, treatment effectiveness, complications and costs, and short- and long-term outcomes. An incremental cost-effectiveness analysis was performed to identify management preference under an assumed $75,000 per quality-adjusted life-year (QALY) societal willingness-to-pay threshold, using data from studies in the literature and the 2015 Medicare Physician Fee Schedule. The effects of key parameters were addressed in a multiway sensitivity analysis.

RESULTS

The prevalence of malignancy for Bosniak IIF and III renal cysts was 26% (25/96) and 52% (542/1046). Under base case assumptions for Bosniak IIF cysts, the incremental cost-effectiveness ratio of NSS relative to AS was $731,309 per QALY for women, exceeding the assumed societal willingness-to-pay threshold, and AS outperformed NSS for both life expectancy and cost for men. For Bosniak III cysts, AS yielded greater life expectancy (24.8 and 19.4 more days) and lower lifetime costs (cost difference of $12,128 and $11,901) than NSS for men and women, indicating dominance of AS over NSS. Superiority of AS held true in sensitivity analyses for men 46 years old or older and women 57 years old or older even when all parameters were set to favor NSS.

CONCLUSION

AS is more cost-effective than NSS for patients with a Bosniak IIF or III renal cyst.

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.

Magnetic resonance imaging as an adjunct diagnostic tool in computed tomography defined Bosniak IIF-III renal cysts: a multicenter study

INTRODUCTION

CT imaging is the standard examination for renal cystic lesions and defines the Bosniak category, which dictates further management. Given that Bosniak II/IIF/III renal cystic lesions can potentially harbor renal cell carcinoma (RCC), additional diagnostic modalities may be required in management decision making.

AIM

To determine the value of additional magnetic resonance imaging in CT-defined Bosniak IIF-III renal cystic lesions.

MATERIALS AND METHODS

This a multicenter retrospective study of 46 consecutive patients, diagnosed with cystic renal lesions between 2009 and 2016. The inclusion criteria were: (1) cystic renal lesion classified as Bosniak IIF-III on CT, (2) a subsequent MRI examination, and (3) documented outcome via surgery for cystic renal mass or follow-up.

RESULTS

46 patients (35 males, 11 females) were included. The mean size of the cystic lesion was 3.92 cm (0.7-10 cm). According to the CT findings, Bosniak IIF and III were found in 12 (26.1%) and 34 (73.9%) cases. Reclassification of Bosniak category was done after MRI examination in 31 cases (67.4%). An upgrade rate of 58.7% (27 cases) to a higher category was made, while the downgrade rate to a lower category was achieved in 4 cases (8.7%). As a result, significant therapeutic management change was made in 12/31 patients (38.7%), of whom 8 underwent subsequent surgery.

CONCLUSION

MRI study may reduce the use of Bosniak IIF category (in comparison with CT), which has a direct impact on therapeutic management (surgery vs. surveillance) in a significant proportion of patients.

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.