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

Bosniak Classification of Cystic Renal Masses Version 2019: Proportion of Malignancy by Class and Subclass-Systematic Review and Meta-Analysis

BACKGROUND. Bosniak classification version 2019 (v2019) was a major revision to version 2005 (v2005) that defined cystic renal mass subclasses on the basis of wall or septa features. OBJECTIVE. The purpose of the study was to determine the proportion of malignancy within cystic renal masses stratified by Bosniak classification v2019 class and feature-based subclass. EVIDENCE ACQUISITION. MEDLINE and Embase databases were searched on July 24, 2023, for studies published in 2019 or later that reported cystic renal masses that underwent renal-mass CT or MRI, were assessed using Bosniak classification v2019, and had a reference standard (histopathology indicating benignancy or malignancy or ≥ 5 years of imaging follow-up indicating benignancy). Study authors were contacted to provide subclass-stratified data. Pooled proportions of malignancy stratified by v2019 class and subclass were determined using meta-analysis. EVIDENCE SYNTHESIS. The analysis included 12 studies reporting 966 patients with 975 cystic masses. No class I mass was malignant. Pooled proportions of malignancy by class were as follows: II, 9% (95% CI: 5-17%); IIF, 26% (95% CI: 13-46%); III, 80% (95% CI: 71-87%); and IV, 88% (95% CI: 83-91%). Pooled proportions of malignancy by subclass were as follows: IIF with many smooth, thin septa, 10% (95% CI: 2-33%); IIF with minimal wall or septal thickening, 47% (95% CI: 18-77%); IIF with heterogeneous T1 hyperintensity, 26% (95% CI: 8-57%); III with a thick, smooth wall or septa, 78% (95% CI: 60-90%); III with obtuse protrusion(s) 3 mm or less, 84% (95% CI: 77-90%); IV with acute protrusion(s) of any size, 88% (95% CI: 80-93%); and IV with obtuse protrusion(s) 4 mm or greater, 86% (95% CI: 77-91%). The proportion of malignancy was 41% for IIF masses with histopathology reference versus 2% for IIF masses with imaging follow-up reference. In four studies performing intraindividual comparisons of v2005 versus v2019, the proportions of malignancy were as follows: class IIF, 24% versus 42% (p = .13); III, 74% versus 77% (p = .72); and IV, 79% versus 84% (p = .22). CONCLUSION. Bosniak IIF masses had higher malignancy rates when histopathology rather than imaging follow-up was the reference standard, indicating verification bias. All Bosniak III and IV subclasses had high malignancy rates. CLINICAL IMPACT. The results improve understanding of imaging-based cystic renal-mass classification and may inform development of future renal-mass classification systems. TRIAL REGISTRATION. PROSPERO (International Prospective Register of Systematic Reviews) CRD42023472140.

Radiomics for differential diagnosis of Bosniak II-IV renal masses via CT imaging

RATIONALE AND OBJECTIVES

The management of complex renal cysts is guided by the Bosniak classification system, which may be inadequate for risk stratification of patients to determine the appropriate intervention. Radiomics models based on CT imaging may provide additional useful information.

MATERIALS AND METHODS

A total of 322 patients with Bosniak II-IV cysts were included in the study from January 2010 to December 2019. Contrast-enhanced CT scans were performed on all patients. ITK-snap was used for segmentation, and the PyRadiomics 3.0.1 package was used for feature extraction. The radiomics features were screened via the least absolute shrinkage and selection operator (LASSO) regression method. After feature selection, a logistic regression (LR) model, support vector machine (SVM) model and random forest (RF) model were constructed.

RESULTS

In the present study, 217 benign renal cysts (67.4%) and 105 cystic renal cell carcinomas (32.6%) were identified. According to the Bosniak classification, the sample included 179 (55.6%) Bosniak II cysts, 38 (11.8%) Bosniak IIF cysts, 44 (13.7%) Bosniak III cysts and 61 (18.9%) Bosniak IV cysts. A total of 1334 radiomics features were extracted from both unenhanced and cortical CT scans. After LASSO regression, all the models (LR, SVM and RF) showed satisfactory discrimination and reliability in both unenhanced and cortical CT scans (AUC > 0.950). In the Bosniak IIF-III subgroup analysis, the diagnostic accuracy of the LR model was very low for both the unenhanced and cortical scans. In contrast, the SVM model and RF model showed excellent and stable performance in classifying Bosniak IIF-III cysts. The AUCs of the models were all > 0.85, with a maximum of 0.941. The sensitivity, specificity, accuracy, and AUC of the RF model were 0.889, 0.913, 0.902, and 0.941, respectively.

CONCLUSION

Our data indicate that radiomics models can effectively distinguish between cystic renal cell carcinoma (cRCC) and complex renal cysts (Bosniak II-IV). Radiomics models may still have high diagnostic accuracy even for Bosniak IIF-III cysts that are clinically difficult to distinguish. However, external validation of these findings is still needed.

Bosniak Classification of Cystic Renal Masses: Looking Back, Looking Forward

RATIONALE AND OBJECTIVES

According to the 2019 update of the Bosniak classification, the main imaging features that need to be evaluated to achieve a correct characterization of renal cystic masses include the thickness of walls and septa, the number of septa, the appearance of walls and septa, the attenuation/intensity on non-contrast CT/MRI and the presence of unequivocally perceived or measurable enhancement of walls and septa. Despite the improvement deriving from a quantitative evaluation of imaging features, certain limitations seem to persist and some possible scenarios that can be encountered in clinical practice are still missing.

MATERIALS AND METHODS

A deep analysis of the 2019 update of the Bosniak classification was performed.

RESULTS

The most notable potential flaws concern: (1) the quantitative measurement of the walls and septa; (2) the fact that walls and septa > 2 mm are always referred to as "enhancing", not considering the alternative scenario; (3) the description of some class II masses partially overlaps with each other and with the definition of class I masses and (4) the morphological variations of cystic masses over time is not considered.

CONCLUSION

The present paper analyzes in detail the limitations of the 2019 Bosniak classification to improve this important tool and facilitate its use in daily radiological practice.

CT of the urinary tract revisited

Computed tomography (CT) of the abdomen is usually appropriate for the initial imaging of many urinary tract diseases, due to its wide availability, fast scanning and acquisition of thin slices and isotropic data, that allow the creation of multiplanar reformatted and three-dimensional reconstructed images of excellent anatomic details. Non-enhanced CT remains the standard imaging modality for assessing renal colic. The technique allows the detection of nearly all types of urinary calculi and the estimation of stone burden. CT is the primary diagnostic tool for the characterization of an indeterminate renal mass, including both cystic and solid tumors. It is also the modality of choice for staging a primary renal tumor. Urolithiasis and urinary tract malignancies represent the main urogenic causes of hematuria. CT urography (CTU) improves the visualization of both the upper and lower urinary tract and is recommended for the investigation of gross hematuria and microscopic hematuria, in patients with predisposing factors for urologic malignancies. CTU is highly accurate in the detection and staging of upper tract urothelial malignancies. CT represents the most commonly used technique for the detection and staging of bladder carcinoma and the diagnostic efficacy of CT staging improves with more advanced disease. Nevertheless, it has limited accuracy in differentiating non-muscle invasive bladder carcinoma from muscle-invasive bladder carcinoma. In this review, clinical indications and the optimal imaging technique for CT of the urinary tract is reviewed. The CT features of common urologic diseases, including ureterolithiasis, renal tumors and urothelial carcinomas are discussed.

Complications Risk Assessment and Imaging Findings of Thermal Ablation Treatment in Liver Cancers: What the Radiologist Should Expect

One of the major fields of application of ablation treatment is liver tumors. With respect to HCC, ablation treatments are considered as upfront treatments in patients with early-stage disease, while in colorectal liver metastases (CLM), they can be employed as an upfront treatment or in association with surgical resection. The main prognostic feature of ablation is the tumor size, since the goal of the treatment is the necrosis of all viable tumor tissue with an adequate tumor-free margin. Radiofrequency ablation (RFA) and microwave ablation (MWA) are the most employed ablation techniques. Ablation therapies in HCC and liver metastases have presented a challenge to radiologists, who need to assess response to determine complication-related treatment. Complications, defined as any unexpected variation from a procedural course, and adverse events, defined as any actual or potential injury related to the treatment, could occur either during the procedure or afterwards. To date, RFA and MWA have shown no statistically significant differences in mortality rates or major or minor complications. To reduce the rate of major complications, patient selection and risk assessment are essential. To determine the right cost-benefit ratio for the ablation method to be used, it is necessary to identify patients at high risk of infections, coagulation disorders and previous abdominal surgery interventions. Based on risk assessment, during the procedure as part of surveillance, the radiologists should pay attention to several complications, such as vascular, biliary, mechanical and infectious. Multiphase CT is an imaging tool chosen in emergency settings. The radiologist should report technical success, treatment efficacy, and complications. The complications should be assessed according to well-defined classification systems, and these complications should be categorized consistently according to severity and time of occurrence.