Accuracy of on-bench biopsies in the evaluation of the histological subtype, grade, and necrosis of renal tumours

Characterization of renal masses with MRI-based radiomics: assessment of inter-package and inter-observer reproducibility in a prospective pilot study

OBJECTIVES

To evaluate radiomics features' reproducibility using inter-package/inter-observer measurement analysis in renal masses (RMs) based on MRI and to employ machine learning (ML) models for RM characterization.

METHODS

32 Patients (23M/9F; age 61.8 ± 10.6 years) with RMs (25 renal cell carcinomas (RCC)/7 benign masses; mean size, 3.43 ± 1.73 cm) undergoing resection were prospectively recruited. All patients underwent 1.5 T MRI with T2-weighted (T2-WI), diffusion-weighted (DWI)/apparent diffusion coefficient (ADC), and pre-/post-contrast-enhanced T1-weighted imaging (T1-WI). RMs were manually segmented using volume of interest (VOI) on T2-WI, DWI/ADC, and T1-WI pre-/post-contrast imaging (1-min, 3-min post-injection) by two independent observers using two radiomics software packages for inter-package and inter-observer assessments of shape/histogram/texture features common to both packages (104 features; n = 26 patients). Intra-class correlation coefficients (ICCs) were calculated to assess inter-observer and inter-package reproducibility of radiomics measurements [good (ICC ≥ 0.8)/moderate (ICC = 0.5-0.8)/poor (ICC < 0.5)]. ML models were employed using reproducible features (between observers and packages, ICC > 0.8) to distinguish RCC from benign RM.

RESULTS

Inter-package comparisons demonstrated that radiomics features from T1-WI-post-contrast had the highest proportion of good/moderate ICCs (54.8-58.6% for T1-WI-1 min), while most features extracted from T2-WI, T1-WI-pre-contrast, and ADC exhibited poor ICCs. Inter-observer comparisons found that radiomics measurements from T1-WI pre/post-contrast and T2-WI had the greatest proportion of features with good/moderate ICCs (95.3-99.1% T1-WI-post-contrast 1-min), while ADC measurements yielded mostly poor ICCs. ML models generated an AUC of 0.71 [95% confidence interval = 0.67-0.75] for diagnosis of RCC vs. benign RM.

CONCLUSION

Radiomics features extracted from T1-WI-post-contrast demonstrated greater inter-package and inter-observer reproducibility compared to ADC, with fair accuracy for distinguishing RCC from benign RM.

CLINICAL RELEVANCE

Knowledge of reproducibility of MRI radiomics features obtained on renal masses will aid in future study design and may enhance the diagnostic utility of radiomics models for renal mass characterization.

Multi-sequence MRI-based radiomics model to preoperatively predict the WHO/ISUP grade of clear Cell Renal Cell Carcinoma: a two-center study

OBJECTIVES

To develop radiomics models based on multi-sequence MRI from two centers for the preoperative prediction of the WHO/ISUP grade of Clear Cell Renal Cell Carcinoma (ccRCC).

METHODS

This retrospective study included 334 ccRCC patients from two centers. Significant clinical factors were identified through univariate and multivariate analyses. MRI sequences included Dynamic contrast-enhanced MRI, axial fat-suppressed T2-weighted imaging, diffusion-weighted imaging, and in-phase/out-of-phase images. Feature selection methods and logistic regression (LR) were used to construct clinical and radiomics models, and a combined model was developed using the Rad-score and significant clinical factors. Additionally, seven classifiers were used to construct the combined model and different folds LR was used to construct the combined model to evaluate its performance. Models were evaluated using receiver operating characteristic (ROC) curves, area under the curve (AUC), and decision curve analysis (DCA). The Delong test compared ROC performance, with p < 0.050 considered significant.

RESULTS

Multivariate analysis identified intra-tumoral vessels as an independent predictor of high-grade ccRCC. In the external validation set, the radiomics model (AUC = 0.834) outperformed the clinical model (AUC = 0.762), with the combined model achieving the highest AUC (0.855) and significantly outperforming the clinical model (p = 0.003). DCA showed that the combined model had a higher net benefit within the 0.04-0.54 risk threshold range than clinical model. Additionally, the combined model constructed using logistic regression has a higher priority compared to other classifiers. Additionally, 10-fold cross-validation with LR for the combined model showed consistent AUC values (0.849-0.856) across different folds.

CONCLUSION

The radiomics models based on multi-sequence MRI might be a noninvasive and effective tool, demonstrating good efficacy in preoperatively predicting the WHO/ISUP grade of ccRCC.

CT-based radiomics model using stability selection for predicting the World Health Organization/International Society of Urological Pathology grade of clear cell renal cell carcinoma

OBJECTIVES

This study aimed to develop a model to predict World Health Organization/International Society of Urological Pathology (WHO/ISUP) low-grade or high-grade clear cell renal cell carcinoma (ccRCC) using 3D multiphase enhanced CT radiomics features (RFs).

METHODS

CT data of 138 low-grade and 60 high-grade ccRCC cases were included. RFs were extracted from four CT phases: non-contrast phase (NCP), corticomedullary phase, nephrographic phase, and excretory phase (EP). Models were developed using various combinations of RFs and subjected to cross-validation.

RESULTS

There were 107 RFs extracted from each phase of the CT images. The NCP-EP model had the best overall predictive value (AUC = 0.78), but did not significantly differ from that of the NCP model (AUC = 0.76). By considering the predictive ability of the model, the level of radiation exposure, and model simplicity, the overall best model was the Conventional image and clinical features (CICFs)-NCP model (AUC = 0.77; sensitivity 0.75, specificity 0.69, positive predictive value 0.85, negative predictive value 0.54, accuracy 0.73). The second-best model was the NCP model (AUC = 0.76).

CONCLUSIONS

Combining clinical features with unenhanced CT images of the kidneys seems to be optimal for prediction of WHO/ISUP grade of ccRCC. This noninvasive method may assist in guiding more accurate treatment decisions for ccRCC.

ADVANCES IN KNOWLEDGE

This study innovatively employed stability selection for RFs, enhancing model reliability. The CICFs-NCP model's simplicity and efficacy mark a significant advancement, offering a practical tool for clinical decision-making in ccRCC management.

An exploratory study of CT radiomics using differential network feature selection for WHO/ISUP grading and progression-free survival prediction of clear cell renal cell carcinoma

Objectives

To explore the feasibility of predicting the World Health Organization/International Society of Urological Pathology (WHO/ISUP) grade and progression-free survival (PFS) of clear cell renal cell cancer (ccRCC) using the radiomics features (RFs) based on the differential network feature selection (FS) method using the maximum-entropy probability model (MEPM).

Methods

175 ccRCC patients were divided into a training set (125) and a test set (50). The non-contrast phase (NCP), cortico-medullary phase, nephrographic phase, excretory phase phases, and all-phase WHO/ISUP grade prediction models were constructed based on a new differential network FS method using the MEPM. The diagnostic performance of the best phase model was compared with the other state-of-the-art machine learning models and the clinical models. The RFs of the best phase model were used for survival analysis and visualized using risk scores and nomograms. The performance of the above models was tested in both cross-validated and independent validation and checked by the Hosmer-Lemeshow test.

Results

The NCP RFs model was the best phase model, with an AUC of 0.89 in the test set, and performed superior to other machine learning models and the clinical models (all p &lt;0.05). Kaplan-Meier survival analysis, univariate and multivariate cox regression results, and risk score analyses showed the NCP RFs could predict PFS well (almost all p &lt; 0.05). The nomogram model incorporated the best two RFs and showed good discrimination, a C-index of 0.71 and 0.69 in the training and test set, and good calibration.

Conclusion

The NCP CT-based RFs selected by differential network FS could predict the WHO/ISUP grade and PFS of RCC.

Percutaneous biopsy of small renal mass: can diagnostic accuracy be affected by hospital volume?

Introduction

High diagnostic performance and low morbidity for renal tumor biopsy (RTB) have been described in highly experienced centers. Here we present the five-year experience of our institute in performing RTB. The protocol used, the safety profile and the diagnostic accuracy obtained were analyzed.

Material and methods

The study is a retrospective single-institution clinical data review of 84 consecutive RTB of small renal masses. Post-biopsy complications were reported using the Clavien-Dindo system. To measure the concordance between biopsy and nephrectomy specimens regarding histological subtype and International Society of Urological Pathology/World Health Organization (ISUP/WHO) renal cell carcinoma grade, the kappa coefficient of Cohen was used.

Results

Median (IQR) follow-up time was 44 (29–58) months. In total, 94% of RTB procedures were free of complications; when complications did occur, 80% were grade I and 20% were grade II. No cases of tumor seeding were observed. Combining the first and repeated biopsies the overall diagnostic rate was 85.8%. Overall, 79.1% of diagnostic RTB were malignant. In 42 surgically treated patients, the concordance between the histological results of biopsies and surgical specimens was very good for histological subtypes (k = 0.87) and moderate for tumor grade (k = 0.51).

Conclusions

RTB resulted in a high safety profile. The overall diagnostic rate was 85% and an unnecessary intervention was avoided in 21% of patients. RTB showed a very good accuracy in determining the histological subtype of renal cancer while it was moderate for the tumor grade. These results are similar to those reported in larger series and support feasibility of this procedure in low-volume centers.

Diagnostic accuracy of core biopsies of renal masses: Experience in a real-life setting from a tertiary center

OBJECTIVE

To document and analyze diagnostic accuracy of renal core biopsy (RCB), its diagnostic correlation with resection specimens, and to question the need for immunohistochemistry (IHC) in the preoperative diagnosis of renal masses.

MATERIAL AND METHOD

RCBs performed at a reference center between 2007 and 2017 were included. Pathological, clinical, and radiological data were obtained from medical records.

RESULTS

Among 302 biopsies included in this study, 274 (90.7%) were diagnostic. Two hundred sixty-six were neoplastic and 179 were of primary renal origin. The most common secondary neoplasms were hematolymphoid (n = 35) and metastatic (n = 17). Sixty-nine tumors were classified as small renal masses (SRMs) (≤4 cm in diameter) and 53 of them were malignant. Nephrectomy was performed in 58 patients. Overall diagnostic accuracy between resections and RCBs was 88.7%. IHC was performed in 160 (53%) cases. In 15 of those, a definite diagnosis could not be rendered. Renal cell origin and subtype were determined by histomorphology alone in 81 and 75 cases, respectively. Sixty primary neoplasms of renal cell origin required IHC for diagnosis.

CONCLUSION

RCB is a safe and highly accurate method for the diagnosis of both primary and secondary renal neoplasms. IHC is mostly required for the diagnosis of secondary tumors. Histomorphology is still the primary diagnostic tool, highly dependent on the experience of the surgical pathologist.

Preoperative Predicting the WHO/ISUP Nuclear Grade of Clear Cell Renal Cell Carcinoma by Computed Tomography-Based Radiomics Features

Nuclear grade is important for treatment selection and prognosis in patients with clear cell renal cell carcinoma (ccRCC). This study aimed to determine the ability of preoperative four-phase multiphasic multidetector computed tomography (MDCT)-based radiomics features to predict the WHO/ISUP nuclear grade. In all 102 patients with histologically confirmed ccRCC, the training set (n = 62) and validation set (n = 40) were randomly assigned. In both datasets, patients were categorized according to the WHO/ISUP grading system into low-grade ccRCC (grades 1 and 2) and high-grade ccRCC (grades 3 and 4). The feature selection process consisted of three steps, including least absolute shrinkage and selection operator (LASSO) regression analysis, and the radiomics scores were developed using 48 radiomics features (10 in the unenhanced phase, 17 in the corticomedullary (CM) phase, 14 in the nephrographic (NP) phase, and 7 in the excretory phase). The radiomics score (Rad-Score) derived from the CM phase achieved the best predictive ability, with a sensitivity, specificity, and an area under the curve (AUC) of 90.91%, 95.00%, and 0.97 in the training set. In the validation set, the Rad-Score derived from the NP phase achieved the best predictive ability, with a sensitivity, specificity, and an AUC of 72.73%, 85.30%, and 0.84. We constructed a complex model, adding the radiomics score for each of the phases to the clinicoradiological characteristics, and found significantly better performance in the discrimination of the nuclear grades of ccRCCs in all MDCT phases. The highest AUC of 0.99 (95% CI, 0.92-1.00, p < 0.0001) was demonstrated for the CM phase. Our results showed that the MDCT radiomics features may play a role as potential imaging biomarkers to preoperatively predict the WHO/ISUP grade of ccRCCs.

CT-Based Radiomics Signature for Preoperative Prediction of Coagulative Necrosis in Clear Cell Renal Cell Carcinoma

OBJECTIVE

The presence of coagulative necrosis (CN) in clear cell renal cell carcinoma (ccRCC) indicates a poor prognosis, while the absence of CN indicates a good prognosis. The purpose of this study was to build and validate a radiomics signature based on preoperative CT imaging data to estimate CN status in ccRCC.

MATERIALS AND METHODS

Altogether, 105 patients with pathologically confirmed ccRCC were retrospectively enrolled in this study and then divided into training (n = 72) and validation (n = 33) sets. Thereafter, 385 radiomics features were extracted from the three-dimensional volumes of interest of each tumor, and 10 traditional features were assessed by two experienced radiologists using triple-phase CT-enhanced images. A multivariate logistic regression algorithm was used to build the radiomics score and traditional predictors in the training set, and their performance was assessed and then tested in the validation set. The radiomics signature to distinguish CN status was then developed by incorporating the radiomics score and the selected traditional predictors. The receiver operating characteristic (ROC) curve was plotted to evaluate the predictive performance.

RESULTS

The area under the ROC curve (AUC) of the radiomics score, which consisted of 7 radiomics features, was 0.855 in the training set and 0.885 in the validation set. The AUC of the traditional predictor, which consisted of 2 traditional features, was 0.843 in the training set and 0.858 in the validation set. The radiomics signature showed the best performance with an AUC of 0.942 in the training set, which was then confirmed with an AUC of 0.969 in the validation set.

CONCLUSION

The CT-based radiomics signature that incorporated radiomics and traditional features has the potential to be used as a non-invasive tool for preoperative prediction of CN in ccRCC.

Improving needle biopsy accuracy in small renal mass using tumor-specific DNA methylation markers

Purpose

The clinical management of small renal masses (SRMs) is challenging since the current methods for distinguishing between benign masses and malignant renal cell carcinomas (RCCs) are frequently inaccurate or inconclusive. In addition, renal cancer subtypes also have different treatments and outcomes. High false negative rates increase the risk of cancer progression and indeterminate diagnoses result in unnecessary and potentially morbid surgical procedures.

Experimental Design

We built a predictive classification model for kidney tumors using 697 DNA methylation profiles from six different subgroups: clear cell, papillary and chromophobe RCC, benign angiomylolipomas, oncocytomas, and normal kidney tissues. Furthermore, the DNA methylation-dependent classifier has been validated in 272 ex vivo needle biopsy samples from 100 renal masses (71% SRMs).

Results

In general, the results were highly reproducible (89%, n=70) in predicting identical malignant subtypes from biopsies. Overall, 98% of adjacent-normals (n=102) were correctly classified as normal, while 92% of tumors (n=71) were correctly classified malignant and 86% of benign (n=29) were correctly classified benign by this classification model.

Conclusions

Overall, this study provides molecular-based support for using routine needle biopsies to determine tumor classification of SRMs and support the clinical decision-making.

[WHO classification 2016 and first S3 guidelines on renal cell cancer: What is important for the practice?]

The first S3 guidelines on renal cell cancer cover the practical aspects of imaging, diagnostics and therapy as well as the clinical relevance of pathology reporting. This review summarizes the changes in renal tumor classification and the new recommendations for reporting renal cell tumors. The S3 guidelines recommend the 2016 World Health Organization (WHO) classification of renal cell tumors. Novel renal cell tumor entities and provisional or emerging renal cell tumor entities of the 2016 WHO classification of renal tumors are discussed. The S3 guidelines for renal cell cancer also recommend the use of the WHO/International Society of Urologic Pathology (ISUP) grading system for clear cell and for papillary renal cell carcinomas, which replaces the previously used Fuhrman grading system.

Introduction to small renal tumours and prognostic indicators

Over the past years, the widespread use of radiological imaging for evaluating abdominal symptoms unrelated to kidney cancer has been linked to a significant increase in the percentage of renal tumours incidentally detected at an asymptomatic stage. The definition of 'small' renal tumours has changed over the years. Presently, according to dimensional criteria, surgical indications and prognostic impact, small renal tumours are defined as masses ≤4 cm in size. Classical preoperative variables that influence the decision-making process in the management of T1a renal tumours can be classified as patient-related and tumour-related factors. Age is an independent predictor of cancer-specific survival (CSS), with older patients exhibiting significantly worse survival. An accurate classification of the anatomical and topographical characteristics of small renal masses based on available nephrometry systems is necessary for standard preoperative evaluation of patients eligible for partial nephrectomy (PN). Renal tumour biopsies (RTBs) can be indicated in patients eligible for active surveillance or ablative treatments, those with other primary tumours, those with prior renal lesions and/or those with multiple synchronous tumours, showing a median diagnostic rate of 92%. Small renal tumours typically have a good prognosis. Patient age, mode of presentation, nuclear grading, coagulative necrosis and histologic subtype can influence the prognosis of this subgroup of RCC.

The diagnostic accuracy of percutaneous renal needle core biopsy and its potential impact on the clinical management of renal cortical neoplasms

CONTEXT

While biopsies are now increasingly being performed for the diagnosis of renal cortical neoplasms, the influence of the rendered pathological diagnoses on the clinical management is only rarely documented.

OBJECTIVES

To report our experience with consecutively performed renal biopsies and the potential impact of the diagnosis on subsequent clinical management.

DESIGN

Material from needle biopsies performed consecutively at our institution between 2006 and 2011 was reviewed. The influence of the reported pathology results on the clinical management was determined from patient follow-up medical record review.

RESULTS

In total, 218 percutaneous biopsies for renal masses were performed during this period. Among them, 181 (83%) yielded neoplastic tissue, including 81 clear cell renal cell carcinomas, 29 low-grade oncocytic neoplasms, 7 papillary renal cell carcinomas, 5 clear cell papillary renal cell carcinomas, 5 angiomyolipomas, and 14 urothelial carcinomas. Fourteen additional cases (6%) contained lesional material from clinically known nonneoplastic processes, for a total diagnostic yield of 89%. Twenty-three (11%) were nonrepresentative of lesional tissue. In 10 of these, repeat biopsies or resections established the diagnosis of renal tumors. Biopsy diagnosis was confirmed in 29 of 30 cases (97%) on subsequent nephrectomy. Following the biopsy diagnosis, there were significant differences in the clinical management; overall, 79% of clear cell renal cell carcinomas received therapeutic interventions, and 17% were put on active surveillance. In contrast, 77% of the benign or low-grade lesions were put on active surveillance.

CONCLUSIONS

Accurate and specific diagnosis can be rendered on renal core biopsy in most renal tumors, and the biopsy diagnosis can have a definitive role in their clinical management.

Lessons learned from the comparative study between renal mass biopsy and the analysis of the surgical specimen

INTRODUCTION

The role of renal mass (RM) biopsy is currently under discussion. As a result of the progressive increase in the incidental diagnosis of RMs (which have a higher percentage of benignity and well-differentiated cancers), new approaches have emerged such as observation, especially with elderly patients or those with significant comorbidity. RM biopsy (RMB) should provide sufficient information for making this decision, but so far this has not been the case. We examine our prospective series of in-bench RMBs after surgery and compare them with the anatomy of the removed specimen.

MATERIAL AND METHODS

We obtained (prospectively, in-bench and with a 16-gauge needle) 4 biopsies of RMs operated on in our department from October 2008 to December 2009. These RMs were analyzed by 2 uropathologists and compared with the results of the specimen.

RESULTS

We analyzed 188 biopsies (47 RMs); 12.75% were "not valid". The ability of biopsy to diagnose malignancy or benignity was 100%, and the coincidence in the histological type was 95%. The success in determining the tumor grade was 100% when the cancer was low-grade and 62% when high-grade. None of the analyzed data (necrosis, size, etc.) influenced the results in a statistically significant manner.

CONCLUSION

RMB with a 16-G needle enables the differentiation between malignancy and benignity in 100% of cases, with a very similar diagnostic accuracy in the tumor type. Tumor grade is still the pending issue with renal mass biopsy.

Heterogeneity and renal mass biopsy: a review of its role and reliability

Increased abdominal imaging has led to an increase in the detection of the incidental small renal mass (SRM). With increasing recognition that the malignant potential of SRMs is heterogeneous, ranging from benign (15%-20%) to aggressive (20%), enthusiasm for more conservative management strategies in the elderly and infirmed, such as active surveillance (AS), have grown considerably. As the management of the SRM evolves to incorporate ablative techniques and AS for low risk disease, the role of renal mass biopsy (RMB) to help guide individualized therapy is evolving. Historically, the role of RMB was limited to the evaluation of suspected metastatic disease, renal abscess, or lymphoma. However, in the contemporary era, the role of biopsy has grown, most notably to identify patients who harbor benign lesions and for whom treatment, particularly the elderly or frail, may be avoided. When performing a RMB to guide initial clinical decision making for small, localized tumors, the most relevant questions are often relegated to proof of malignancy and documentation (if possible) of grade. However, significant intratumoral heterogeneity has been identified in clear cell renal cell carcinoma (ccRCC) that may lead to an underestimation of the genetic complexity of a tumor when single-biopsy procedures are used. Heterogeneous genomic landscapes and branched parallel evolution of ccRCCs with spatially separated subclones creates an illusion of clonal dominance when assessed by single biopsies and raises important questions regarding how tumors can be optimally sampled and whether future evolutionary tumor branches might be predictable and ultimately targetable. This work raises profound questions concerning the genetic landscape of cancer and how tumor heterogeneity may affect, and possibly confound, targeted diagnostic and therapeutic interventions. In this review, we discuss the current role of RMB, the implications of tumor heterogeneity on diagnostic accuracy, and highlight promising future directions.

Multiparametric magnetic resonance imaging for the differentiation of low and high grade clear cell renal carcinoma

PURPOSE

To retrospectively evaluate the ability of magnetic resonance (MR) imaging to differentiate low from high Fuhrman grade renal cell carcinoma (RCC).

MATERIALS AND METHODS

MR images from 80 consecutive pathologically proven RCC (57 clear cell, 16 papillary and 7 chromophobe) were evaluated. Double-echo chemical shift, dynamic contrast-enhanced T1- and T2-weighted images and apparent diffusion coefficient (ADC) maps were reviewed independently. Signal intensity index (SII), tumour-to-spleen SI ratio (TSR), ADC ratio, wash-in (WiI) and wash-out indices (WoI) between different phases were calculated and compared to pathological grade and size. The Fuhrman scoring system was used. Low grade (score ≤ 2) and high grade (score ≥ 3) tumours were compared using univariate and multivariate analyses.

RESULTS

No associations between grade and imaging factors were found for papillary and chromophobe RCCs. For clear cell RCCs, there was a significant association between the grade and parenchymal WiI (WiI2) (P = 0.02) or ADCr (P = 0.03). A significant association between tumour grade and size (P = 0.01), WiI2 (P = 0.02) and ADCr (P = 0.05) remained in multivariate analysis.

CONCLUSIONS

Multiparametric MRI can be used to accurately differentiate low Fuhrman grade clear cell RCC from high grade. High Fuhrman grade (≥ 3) RCCs were larger, had lower parenchymal wash-in indices and lower ADC ratios than low grade.

KEY POINTS

• Fuhrman grade of clear cell RCC can be differentiated with multiparametric MR imaging. • Fuhrman grade significantly differed for size, parenchymal wash-in index and ADC ratio. • No significant associations were found for papillary and chromophobe renal cell carcinoma.

BAP1 immunohistochemistry predicts outcomes in a multi-institutional cohort with clear cell renal cell carcinoma

PURPOSE

Mutations in the tumor suppressor gene BAP1 occur in approximately 15% of clear cell renal cell carcinoma cases. Sequencing efforts demonstrated worse outcomes in patients with BAP1 mutated clear cell renal cell carcinoma. We investigated the clinicopathological significance and oncologic outcomes of BAP1 loss using a previously validated immunohistochemical assay.

MATERIALS AND METHODS

Immunohistochemistry for BAP1 was performed on tissue microarray sections from 559 nonmetastatic clear cell renal cell carcinoma cases treated with nephrectomy at multiple institutions. The association of BAP1 expression with clinicopathological parameters was analyzed using the Wilcoxon rank sum and Cochran-Mantel-Haenszel tests. Survival was assessed by Cox regression analysis, which also identified independent predictors of time dependent outcomes.

RESULTS

At a median followup of 50 months (range 0 to 183) 86 of 483 patients (17.8%) experienced recurrence and 121 of 559 (21.6%) had died. BAP1 was negative in 82 of 559 tumors (14.7%). BAP1 loss was associated with adverse clinicopathological variables, including high Fuhrman grade (p <0.0001), advanced pT stage (p = 0.0021), sarcomatoid dedifferentiation (p = 0.0001) and necrosis (p <0.0001). Cox regression revealed that patients with BAP1 negative tumors had significantly worse disease-free survival (HR 2.9, 95% CI 1.8-4.7, p <0.0001) and overall survival (HR 2.0, 95% CI 1.3-3.1, p = 0.0010) than patients with BAP1 positive tumors.

CONCLUSIONS

Immunohistochemistry for BAP1 serves as a powerful marker to predict poor oncologic outcomes and adverse clinicopathological features in patients with nonmetastatic clear cell renal cell carcinoma. BAP1 assessment using immunohistochemistry on needle biopsy may benefit preoperative risk stratification and guide treatment planning in the future.

Multiphasic contrast-enhanced MRI: single-slice versus volumetric quantification of tumor enhancement for the assessment of renal clear-cell carcinoma fuhrman grade

PURPOSE

To assess the association between clear-cell carcinoma pathology grade at nephrectomy and magnetic resonance imaging (MRI) tumor enhancement.

MATERIALS AND METHODS

The Institutional Review Board approved this retrospective study and waived the informed consent requirement. In all, 32 patients underwent multiphase contrast-enhanced MRI prior to nephrectomy. MRI tumor enhancement was measured using two approaches: 1) the most enhancing portion of the tumor on a single slice and 2) volumetric analysis of enhancement in the entire tumor. Associations between pathological grade, tumor size, and enhancement were evaluated using the Kruskal-Wallis test and generalized logistic regression models.

RESULTS

No significant association between pathology grade and enhancement was found when measurements were made on a single slice. When measured in the entire tumor, significant associations were found between higher pathology grades and lower mean, median, top 10%, top 25%, and top 50% tumor enhancement (P < 0.001-0.002). On multivariate analysis the association between grade and enhancement remained significant (P = 0.041-0.043), but tumor size did not make an additional contribution beyond tumor enhancement alone in differentiating between tumor grades.

CONCLUSION

There is significant association between tumor grade and enhancement, but only when measured in the entire tumor and not on the most enhancing portion on a single slice.

Interpretation of needle biopsies of the kidney for investigation of renal masses

The development of new therapeutic options for renal tumors has lead to the need of a pretherapeutic diagnosis for an increasing proportion of patients presenting with a renal mass. This need is particularly important for a small, incidentally discovered renal mass (less than 4 cm) as it can be a benign lesion in a significant percentage of cases. Recent studies have shown that needle biopsy is an accurate and safe method allowing for a precise histopathological diagnosis of the mass in most cases. The aims of the biopsy are (1) to assess the benign or malignant nature of the lesion, (2) to assess the primary or secondary nature of the lesion, and (3), in case of a primary malignancy, to determine histological prognostic factors, such as the tumor type. This review, based on the most recent literature and our own experience, is intended to provide a practical approach to the diagnosis, relying on appropriate morphologic assessment and the use of immunohistochemistry.

Molecular characterization of kidney cancer: association of hyaluronic acid family with histological subtypes and metastasis

BACKGROUND

Molecular profiling of renal cell carcinomas (RCCs) may improve the distinction between oncocytoma and malignant RCC subtypes and aid in early detection of metastasis. The hyaluronic acid (HA) family includes HA synthases (HAS1, HAS2, HAS3), hyaluronidases (HYAL-1, HYAL-2, HYAL-3, HYAL-4, PH20, HYAL-P1), and HA receptors (CD44s, CD44v, RHAMM). HA family members promote tumor growth and metastasis. The authors evaluated the expression of HA family members in kidney specimens.

METHODS

By using quantitative polymerase chain reaction, mRNA levels of 12 HA family members were measured in tumor specimens obtained from 86 consecutive patients undergoing nephrectomy; 80 of them also provided normal specimens. Mean and median follow-up were 15.2 ± 8.8 and 13.8 months. RCC specimens included clear cell RCC: 65; papillary: 10; chromophobe: 5; oncocytoma: 6; metastasis positive: 17.

RESULTS

Median HAS1, CD44s, and RHAMM transcript levels were elevated 3- to 25-fold in clear cell RCC and papillary and chromophobe tumors when compared with normal tissues. HYAL-4, CD44s, and RHAMM levels were elevated 4- to 12-fold in clear cell RCC and papillary tumors when compared with oncocytomas; only HYAL-4 levels distinguished between chromophobe and oncocytoma (P = .009). CD44s and RHAMM levels were significantly higher in tumors <4 cm (510 ± 611 and 19.6 ± 20.8, respectively) when compared with oncocytoma (46.4 ± 20 and 3.8 ± 2.5; P ≤ .006). In univariate and multivariate analyses, CD44s (P < .0001), RHAMM (P < .0001), stage, tumor size, and/or renal vein involvement were significantly associated with metastasis. The combined CD44s + RHAMM marker had 82% sensitivity and 86% specificity to predict metastasis.

CONCLUSIONS

CD44s and RHAMM levels distinguish between oncocytoma and RCC subtypes regardless of tumor size and are potential predictors of RCC metastasis.