Intrarenal epidermoid cyst mimicking a cystic renal cell carcinoma: A case report and review of literature.

Key Clinical Message: This case highlights the diagnostic pitfalls that can occur when evaluating complex cystic renal masses. Distinguishing epidermoid cysts from renal cell carcinoma is difficult but imperative to guide conservative management when appropriate, avoiding unnecessary nephrectomy. Abstract: Renal epidermoid cysts are extremely rare, with only 12 cases reported in the literature. Their radiographic features often resemble cystic renal cell carcinoma, frequently prompting unnecessary nephrectomy. A 64-year-old man with a history of nephrolithiasis presented with left flank pain and hematuria. Imaging revealed a complex cystic renal mass suspicious for renal cell carcinoma. Following left radical nephrectomy, histopathology examination revealed a benign epidermoid cyst. Renal presentation of epidermoid cyst poses unique diagnostic and therapeutic challenges. Possible pathogenesis includes ectopic epidermal implantation during embryogenesis or squamous metaplasia following chronic irritation or deficiency. Radiographic distinction from concerning entities like renal cell carcinoma is difficult but imperative to avoid extensive surgery. This case highlights the diagnostic pitfalls and management considerations for renal epidermoid cysts. Additional study of clinical and imaging factors that distinguish epidermoid cysts from renal cell carcinoma can guide conservative management when appropriate, avoiding unnecessary nephrectomy for benign disease.

Cystic renal mass screening: machine-learning-based radiomics on unenhanced computed tomography

PURPOSE: The present study compares the diagnostic performance of unenhanced computed tomography (CT) radiomics-based machine learning (ML) classifiers and a radiologist in cystic renal masses (CRMs). METHODS: Patients with pathologically diagnosed CRMs from two hospitals were enrolled in the study. Unenhanced CT radiomic features were extracted for ML modeling in the training set (Guangzhou; 162 CRMs, 85 malignant). Total tumor segmentation was performed by two radiologists. Features with intraclass correlation coefficients of >0.75 were screened using univariate analysis, least absolute shrinkage and selection operator, and bidirectional elimination to construct random forest (RF), decision tree (DT), and k-nearest neighbor (KNN) models. External validation was performed in the Zhuhai set (45 CRMs, 30 malignant). All images were assessed by a radiologist. The ML models were evaluated using calibration curves, decision curves, and receiver operating characteristic (ROC) curves. RESULTS: Of the 207 patients (102 women; 59.1 ± 11.5 years), 92 (41 women; 58.0 ± 13.7 years) had benign CRMs, and 115 (61 women; 59.8 ± 11.4 years) had malignant CRMs. The accuracy, sensitivity, and specificity of the radiologist's diagnoses were 85.5%, 84.2%, and 91.1%, respectively [area under the (ROC) curve (AUC), 0.87]. The ML classifiers showed similar sensitivity (94.2%-100%), specificity (94.7%-100%), and accuracy (94.3%-100%) in the training set. In the validation set, KNN showed better sensitivity, accuracy, and AUC than DT and RF but weaker specificity. Calibration and decision curves showed excellent and good results in the training and validation set, respectively. CONCLUSION: Unenhanced CT radiomics-based ML classifiers, especially KNN, may aid in screening CRMs.

Role of Contrast-Enhanced Ultrasound in Evaluation of Cystic Renal Mass.

OBJECTIVES: Contrast-enhanced ultrasound (CEUS) allows excellent delineation of perfusion in septa and nodules without exposure to ionizing radiation or nephrotoxic contrast media. The aim of our study was to evaluate the role of CEUS for the assessment of cystic renal masses and compare its diagnostic performance with that of CECT. METHODS: Exactly 40 patients diagnosed to have cystic renal masses on CECT scan were prospectively evaluated with CEUS and were assigned a Bosniak class. Based on results of final histopathology and clinical follow-up, internal validity of both CEUS and CECT was evaluated, including agreement between these two modalities. RESULTS: Out of the 40 patients (mean size 3.1 ± 2.5 cm), 23 patients had benign lesions and 17 patients had malignant lesions. For CEUS, the sensitivity and negative predictive value was 100%, the specificity and positive predictive value was 73.9%. For CECT, the sensitivity and negative predictive value were 88.2 and 83.3%, respectively, whereas the specificity and positive predictive value was 87 and 90.9%, respectively. Both imaging modalities had similar accuracy with fair to good agreement with the final diagnosis (Κ = 0.71 and 0.75 for CEUS and CECT, respectively). Concordance between CEUS and CECT was seen in 29 patients (72.5%) with fair agreement between the two modalities (K = 0.66). CONCLUSION: CEUS has comparable accuracy with CECT and could be used as screening modality to rule out the presence of complex cystic renal masses without exposure of nephrotoxic contrast media and ionizing radiation.

Clinical Evaluation of Cystic Renal Masses With Bosniak Classification by Contrast-Enhanced Ultrasound and Contrast-Enhanced Computer Tomography.

OBJECTIVES: The study aims to compare retrospectively three clinically applied methods for the diagnostic performance of cystic renal masses (CRMs) by contrast-enhanced ultrasound (CEUS) and contrast-enhanced computer tomography (CECT) with Bosniak classification system. METHODS: A total of 52 cases of Bosniak II-IV CRMs in 49 consecutive patients were diagnosed from January 2013 to July 2022 and their data were analyzed. All patients had been subjected to CEUS and CECT simultaneously. Pathological diagnoses and masses stability were used as standard references to determine whether lesions were malignant or benign. Then 49 CRMs only with pathologic results were classified into group 1 and 2. RESULTS: A total of 52 CRMs in 49 enrolled patients were classified into 8 category II, 16 category IIF, 15 category III, and 13 category IV by CEUS (EFSUMB 2020), 10 category II, 13 category IIF, 16 category III, and 13 category IV by CEUS (V2019), while 15 category II, 9 category IIF, 13 category III, and 15 category IV by CECT (V2019). Pathological results and masses stability longer than 5 years follow-up performed substantially for CEUS (EFSUMB 2020), CEUS (V2019), and CECT (V2019) (kappa values were 0.696, 0.735, and 0.696, respectively). Among 49 pathologic approving CRMs, wall/septation thickness ≥4 mm, wall/septation thickness, presence of enhancing nodule and the diameter were found to be statistically significant for malignancy. Twenty-two malignant masses were correctly diagnosed by CEUS (V2019), while 21 malignant masses were both correctly diagnosed by CEUS (EFSUMB 2020) and CECT (V2019), and 1 mass was misdiagnosed. CONCLUSIONS: Bosniak classification of EFSUMB 2020 version might be as accurate as version 2019 CEUS and version 2019 CECT in diagnosing CRMs, and CEUS is found to have an excellent safety profile in dealing with clinical works.

Risk of malignancy in T1-hyperintense Bosniak version 2019 class II and IIF cystic renal masses.

BACKGROUND: Bosniak classification version 2019 includes cystic masses in class II and IIF based partly on their hyperintense appearance at T1-weighted MRI. The prevalence of malignancy in non-enhancing heterogeneously T1-hyperintense masses is unknown, nor whether the pattern of T1 hyperintensity affects malignancy likelihood. PURPOSE: To determine the malignancy proportion among six patterns of T1 hyperintensity within non-enhancing cystic renal masses. METHODS: This retrospective, single-institution study included 72 Bosniak class II and IIF, non-enhancing, T1-hyperintense cystic renal masses. Diagnosis was confirmed by histopathology or by follow-up imaging demonstrating 5-year size and morphologic stability, decreased in size by ≥ 30%, resolution, or Bosniak down-classification. Six patterns of T1 hyperintensity were pre-defined: homogeneous (pattern A), fluid-fluid level (pattern B), peripherally markedly T1-hyperintense (pattern C), containing a T1-hyperintense non-enhancing nodule (pattern D), peripherally T1-hypointense (pattern E), and heterogeneously T1-hyperintense without a distinct pattern (pattern F). Three readers independently assigned each mass to a pattern. Individual and mean malignancy proportion were determined. Mann-Whitney test and Fischer's exact test compared the likelihood of malignancy between patterns. Inter-reader agreement was analyzed with Gwet's agreement coefficient (AC). RESULTS: Among 72 masses, the mean number of masses assigned was 11 (15%) to pattern A, 21 (29%) to pattern B, 6 (8%) to pattern C, 7 (10%) to pattern D, 5 (7%) to pattern E, and 22 (31%) to pattern F. Five of 72 masses (7%) were malignant; none was assigned pattern A, B, or D. Mean malignancy proportion was 5% (0/9, 1/6, and 0/4) for pattern C, 13% (0/4, 1/3, and 1/7) for pattern E, and 18% (5/20, 3/21, and 4/25) for pattern F. Malignant masses were more likely assigned to pattern E or F (p = 0.003-0.039). Inter-reader agreement was substantial (Gwet's AC: 0.68). CONCLUSION: Bosniak version 2019 class IIF masses that are non-enhancing and heterogeneously T1-hyperintense with a fluid-fluid level are likely benign. Those that are non-enhancing and heterogeneously T1-hyperintense without a distinct pattern have a malignancy proportion up to 25% (5/20).

Outcomes of Bosniak Classification Version 2019 Class IIF Cystic Renal Masses at Imaging Surveillance.

BACKGROUND. Bosniak classification system version 2019 (v2019) recommends that class IIF masses undergo follow-up imaging at 6 months, 12 months, and then annually for 5 years. The frequency and timing of upgrade on follow-up imaging are incompletely understood. OBJECTIVE. The purpose of this article is to describe the temporal evolution of Bosniak v2019 class IIF cystic renal masses, with attention to outcomes at 6-month follow-up, the time to class upgrade, and malignant histologic diagnoses. METHODS. This retrospective study included 219 patients (91 women, 128 men; median age, 72 years) with 246 localized class IIF masses from January 2005 to June 2022. Patients underwent both a baseline and at least one follow-up renal-mass protocol contrast-enhanced CT or MRI examination. Two radiologists evaluated masses at all follow-up time points to categorize masses as downgraded (class I or II), stable (localized class IIF), or upgraded (class III or IV, solid, or category T3a, N1, or M1 or higher disease); a third radiologist resolved discrepancies. Incidence rate of upgrade was determined. Histopathologic outcomes were assessed for resected masses. RESULTS. Median follow-up was 28.4 months (IQR, 13.7-59.4 months). At 6-month follow-up, five (2%) masses were downgraded, 241 (98%) were stable, and none were upgraded. On the basis of final follow-up, 14 (6%) masses were downgraded, 223 (91%) were stable, and nine (4%) were upgraded. All upgrade events entailed a class increase to III (n = 7) or IV (n = 2); no mass became solid or developed T3, N1, or M1 disease. Among the nine upgraded masses, median time to upgrade was 53.5 months (IQR, 23.2-63.7 months). Incidence rate of upgrade was 3.006 per 100,000 person-days (95% CI, 1.466-5.516). Ten masses were resected; histopathology was benign in six and malignant in four. Of the four malignant masses, one was upgraded to class III after 15 months of preoperative follow-up imaging, and three remained class IIF on preoperative follow-up imaging. No resected malignant mass developed postoperative recurrence. CONCLUSION. Bosniak v2019 class IIF masses are unlikely to represent aggressive malignancy; only 4% were upgraded over time and never on initial 6-month follow-up. CLINICAL IMPACT. The currently recommended initial 6-month follow-up imaging examination for class IIF masses is of questionable clinical utility.

Bosniak classification of cystic renal masses, version 2019: Is it helpful to incorporate the diffusion weighted imaging characteristic of lesions into the guideline?

Objective: To improve understanding of diffusion weighted imaging (DWI) characteristic of MRI and clinical variables, further optimize the Bosniak classification for diagnosis of cystic renal masses (CRMs). Methods: This study retrospectively analyzed 130 CRMs in 125 patients with CT or MRI, including 87 patients with DWI (b = 600, 1000 s/mm2). Clinical variables and histopathological results were recorded. Two radiologists in consensus analyzed images of each lesion for the size, thickness of wall, number of septum, enhancement of wall/septum, wall nodule, signal intensity on DWI, calcification, and cyst content. Clinical variables, CT and MRI image characteristics were compared with pathology or follow-up results to evaluate the diagnostic performance for CRMs. Results: Of the 130 lesions in 125 patients, histological analysis reported that 36 were malignant, 38 were benign, and no change was found in 56 followed-up lesions (mean follow-up of 24 months). The incidences of cystic wall thickened, more septa, measurable enhancement of wall/septum, nodule(s) on CT/MRI, and high signal intensity on DWI were significantly higher in malignant than in benign CRMs (CT: p = 0.005, p < 0.001, p < 0.001, p < 0.001, p < 0.001; MRI: p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001). Combination of MRI including DWI features with CT findings showed the highest area under ROC curve (0.973) in distinguishing benign and malignant CRMs. Conclusions: Incorporating DWI characteristic of CRMs into Bosniak classification helps to improve diagnostic efficiency.

Nyquist sampling theorem and Bosniak classification, version 2019: effect of thin axial sections on categorization and agreement.

OBJECTIVE: To determine if CT axial images reconstructed at current standard of care (SOC; 2.5-3 mm) or thin (≤ 1 mm) sections affect categorization and inter-rater agreement of cystic renal masses assessed with Bosniak classification, version 2019. METHODS: In this retrospective single-center study, 3 abdominal radiologists reviewed 131 consecutive cystic renal masses from 100 patients performed with CT renal mass protocol from 2015 to 2021. Images were reviewed in two sessions: first with SOC and then the addition of thin sections. Individual and overall categorizations are reported, latter of which is based on majority opinion with 3-way discrepancies resolved by a fourth reader. Major categorization changes were defined as differences between classes I-II, IIF, or III-IV. RESULTS: Thin sections led to a statistically significant major category change with class II for all readers individually (p = 0.004-0.041; McNemar test), upgrading 10-17% of class II masses, most commonly to class IIF followed by III. Modal reason for upgrades was due to identification of additional septa followed by larger measurement of enhancing features. Masses categorized as class I, III, or IV on SOC sections were unaffected, as were identification of protrusions. Inter-rater agreements using weighted Cohen's kappa were 0.679 for SOC and 0.691 for thin sections (both substantial). CONCLUSION: Thin axial sections upgraded up to one in six class II masses to IIF or III through identification of additional septa or larger feature. Other classes, including III-IV, were unaffected. Inter-rater agreements were substantial regardless of section thickness. KEY POINTS: • Thin axial sections (≤ 1 mm) compared to standard of care sections (2.5-3 mm) led to identification of additional septa but did not affect identification of protrusions. • Thin axial sections (≤ 1 mm) compared to standard of care sections (2.5-3 mm) can upgrade a small proportion of cystic renal masses from class II to IIF or III when applying Bosniak classification, version 2019. • Inter-rater agreements were substantial regardless of section thickness.

Growth Kinetics and Progression Rate of Bosniak Classification Version 2019 Class III and IV Cystic Renal Masses on Imaging Surveillance.

BACKGROUND. Active surveillance is increasingly used as first-line management for localized renal masses. Triggers for intervention primarily reflect growth kinetics, which have been poorly investigated for cystic masses defined by the Bosniak classification version 2019 (v2019). OBJECTIVE. The purpose of this study was to determine growth kinetics and incidence rates of progression of class III and IV cystic renal masses, as defined by the Bosniak classification v2019. METHODS. This retrospective study included 105 patients (68 men, 37 women; median age, 67 years) with 112 Bosniak v2019 class III or IV cystic renal masses on baseline renal mass protocol CT or MRI examinations performed from January 2005 to September 2021. Mass dimensions were measured. Progression was defined as any of the following: linear growth rate (LGR) of 5 mm/y or greater (representing the clinical guideline threshold for intervention), volume doubling time less than 1 year, T category increase, or N1 or M1 disease. Class III and IV masses were compared. Time to progression was estimated using Kaplan-Meier curve analysis. RESULTS. At baseline, 58 masses were class III and 54 were class IV. Median follow-up was 403 days. Median LGR for class III masses was 0.0 mm/y (interquartile range [IQR], -1.3 to 1.8 mm/y) and for class IV masses was 2.3 mm/y (IQR, 0.0-5.7 mm/y) (p < .001). LGR was at least 5 mm/y in four (7%) class III masses and 15 (28%) class IV masses (p = .005). Two patients, both with class IV masses, developed distant metastases. Incidence rate of progression for class III masses was 11.0 (95% CI, 4.5-22.8) and for class IV masses 73.6 (95% CI, 47.8-108.7) per 100,000 person-days of follow-up. Median time to progression was undefined for class III masses given the small number of progression events and 710 days for class IV masses. Hazard ratio of progression for class IV relative to class III masses was 5.1 (95% CI, 2.5-10.8; p < .001). CONCLUSION. During active surveillance of cystic masses evaluated using the Bosniak classification v2019, class IV masses grew faster and were more likely to progress than class III masses. CLINICAL IMPACT. In comparison with current active surveillance guidelines that treat class III and IV masses similarly, future iterations may incorporate relatively more intensive surveillance for class IV masses.

Clinical utility of the Bosniak classification version 2019: Diagnostic value of adding magnetic resonance imaging to computed tomography examination.

PURPOSE: To assess the impact of the updated Bosniak classification (BC2019) for cystic renal masses (CRMs) on interobserver agreement between radiologists and urologists and the diagnostic value of adding MRI to CT examination (combined CT/MRI). METHOD: This study included 103 CRMs from 83 consecutive patients assessed using contrast-enhanced CT and MRI between 2010 and 2016. Nine readers in three groups (three radiologists, three radiology residents, and three urologists) reviewed CT alone and the combined CT/MRI using BC2019. Bosniak category was determined by consensus in each group for diagnosing malignancy, with a cut-off category of ≧III. Interobserver agreement was assessed using Fleiss' kappa values. The effect of CT or combined CT/MRI on the diagnosis of malignancy was assessed using McNemar's test. RESULTS: Interobserver agreement of BC2019 for CT alone was substantial for radiologists and residents, moderate for urologists (0.77, 0.63, and 0.58, respectively). Interobserver agreement of BC2019 for combined CT/MRI was substantial for all three groups (radiologists: 0.78; residents: 0.65; and urologists: 0.61). Among residents, the sensitivity/specificity/accuracy rates of combined CT/MRI vs. CT alone were 82.1/74.7/76.7% vs. 75.0/66.7/68.9%, and specificity and accuracy were significantly higher for combined CT/MRI than that for CT alone (p = 0.03 and 0.008, respectively). Similarly, sensitivity/specificity/accuracy values were significantly higher for combined CT/MRI among urologists (78.6/73.3/74.8% vs. 64.3/64.0/64.1%, p = 0.04/0.04/0.008). However, sensitivity/specificity/accuracy did not significantly differ between the two among radiologists (89.3/74.7/78.6% vs. 85.7/73.3/76.7%, p = 0.32/0.56/0.32). CONCLUSIONS: Combined CT/MRI is useful for diagnosing malignancy in patients with CRMs using BC2019, especially for non-expert readers.

Test-retest reliability analysis of MRI criteria in the 2019 Bosniak classification of cystic renal masses / 中华放射学杂志

Objective:To evaluate the test-retest reliability of MRI criteria in the 2019 Bosniak classification of cystic renal masses (CRMs) and to analyze the impact of lesions′ property, size and readers′ experience on the test-retest reliability.Methods:From January 2009 to June 2019, 207 patients with 207 CRMs were included in this retrospective study. All of them underwent renal MRI and surgical-pathologic examination. According to Bosniak classification, version 2019, all CRMs were independently classified twice by eight radiologists with different levels of experience. All radiologists were blinded to the pathology of the lesions. By using intraclass correlation coefficient (ICC), test-retest reliability was evaluated for all CRMs and for subgroups with different pathological properties (benign and malignant) and different sizes (≤40 mm and>40 mm). The test-retest reliability of 4 senior readers (≥10 years of experience) and 4 junior readers (<10 years of experience) were evaluated respectively. The comparison of ICC was performed using Z test. Results:The 207 CRMs included 111 benign lesions (83 benign cysts, 28 benign tumors) and 96 malignant tumors. There were 87 lesions with maximum diameter ≤40 mm and 120 with maximum diameter>40 mm. The test-retest reliability (ICC) of each reader for all lesions was 0.776-0.888, the overall ICC was 0.848 (95%CI 0.821-0.872). The ICCs of senior and junior readers were 0.853 (95%CI 0.824-0.880) and 0.843 (95%CI 0.811-0.871) respectively, without significant difference between the two groups ( Z=0.85, P=0.374). The ICC of all readers was 0.827 for benign lesions and 0.654 for malignant lesions, showing significant difference ( Z=2.80, P=0.005). The ICC was 0.770 for lesions ≤40 mm and 0.876 for lesions>40 mm, which was significantly different ( Z=-2.36, P=0.018). For CRM subgroups with different pathological properties and different sizes, there was no significant difference in test-retest reliability between senior and junior readers (all P>0.05). Conclusion:The test-retest reliability of MRI criteria in the 2019 Bosniak classification of CRMs is excellent and unaffected by readers′ experience. The reliabilities are not consistent among CRMs of different pathological properties and different sizes, but all reached the level of good and above.

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.

Bosniak Classification of Cystic Renal Masses Version 2019: Comparison With 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. The purpose of this study was to compare versions 2005 and 2019 of the Bosniak classification system in terms of class distribution, diagnostic performance, interreader agreement, and intermodality 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. Interreader and intermodality agreement were analyzed using weighted kappa coefficients. RESULTS. Across readers and modalities, the proportion of class IIF CRMs 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. The proportion of class III CRMs was lower for version 2019 than version 2005 (reader 1: 33.7-35.6% vs 49.0-51.9%; reader 2: 31.7-40.4% vs 37.5-52.9%), although 95% CIs overlapped for all comparisons. Version 2019 showed 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 showed 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%). Interreader and intermodality agreement were substantial for version 2005 (κ = 0.676-0.782 and 0.711-0.723, respectively) and version 2019 (κ = 0.756-0.804 and 0.704-0.781, respectively). CONCLUSION. Use of version 2019 versus version 2005 of the Bosniak classification system results in a shift in CRM assignment from class III to class IIF. Version 2019 results in lower sensitivity, higher specificity, and similar accuracy versus version 2005. Interreader and intermodality agreement are similar between versions. CLINICAL IMPACT. Version 2019 facilitates recommending imaging surveillance for more CRMs.

The Incidental Renal Mass- Update on Characterization and Management.

Renal masses are commonly encountered on cross-sectional imaging examinations performed for nonrenal indications. Although most can be dismissed as benign cysts, a subset will be either indeterminate or suspicious; in many cases, imaging cannot be used to reliably differentiate between benign and malignant masses. On-going research in defining characteristics of common renal masses on advanced imaging shows promise in offering solutions to this issue. A recent update of the Bosniak classification (used to categorize cystic renal masses) was proposed with the goals of decreasing imaging follow-up in likely benign cystic masses, and therefore avoiding unnecessary surgical resection of such masses.

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.

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.

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.

Long-Term Functional and Oncologic Outcomes of Robot-Assisted Partial Nephrectomy for Cystic Renal Tumors: A Single-Center Retrospective Study.

Objectives: To evaluate the outcomes of robot-assisted partial nephrectomy (RAPN) in cystic renal tumors. Materials and Methods: We retrospectively analyzed patients who underwent RAPN for either cystic (n = 46) or solid (n = 271) renal tumors at Fujita Health University between 2010 and 2019. Cystic renal tumors were diagnosed using cross-sectional imaging. Perioperative, oncologic, and functional outcomes were assessed. Results: The median follow-up periods were 38, 41, and 37 months in the total, cystic, and solid groups, respectively. Most patient characteristics were similar among both groups, while the median age of the cystic group was significantly lower than that of the solid group (p = 0.02). Most perioperative variables and complications were comparable between the two groups. There was no significant difference between the groups in perioperative renal function. The estimated glomerular filtration rate preservation rates were 93.1% and 89.2% in the cystic and solid groups, respectively (p = 0.17). The cystic group showed a higher benign histology rate (19.6% vs 7%) and lower Fuhrman grade than the solid group (24.3% vs 15.1% in grade 1, and 73% vs 81.3% in grade 2), although there was no statistically significant difference between the two groups. In the solid group, 10 patients (3.7%) experienced recurrence, and 2 patients (0.7%) died of renal-cell carcinoma, while none of the patients with cystic tumors experienced recurrence. There was no statistically significant difference between the cystic and solid tumors with respect to 5-year recurrence-free survival (p = 0.18), cancer-specific survival (p = 0.55), and overall survival (p = 0.35). Conclusions: RAPN for cystic renal tumors appears to be safe and feasible with perioperative, long-term functional and oncologic outcomes comparable with those in solid tumors. RAPN can be a safe and effective surgical option for cystic renal tumors.

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.