The DDD score outperforms the RENAL score in predicting high-grade renal cell carcinoma.

OBJECTIVES: To explore the relationship between Fuhrman grade of renal cell carcinoma (RCC) and the DDD score. METHODS: We reviewed the records of 527 nonmetastatic RCC patients. Demographic, clinical, and pathologic characteristics were reviewed. Binary logistic regression was used to explore the independent risk factors for high-grade RCC (HGRCC). RESULTS: Sex, BMI (Body Mass Index), RNS, and DDD score were significantly correlated with HGRCC. Based on these independent risk factors, we constructed two predictive models integrating the RNS and DDD scores with sex and BMI to predict tumor grade. The calibration curves of the predictive model showed good agreement between the observations and predictions. The concordance indexes (C-indexes) of the predictive models were 0.768 (95% CI, 0.713-0.824), and 0.809 (95% CI, 0.759-0.859). Receiver operating characteristic (ROC) curves were performed to compare the predictive power of the nomograms, and the prediction model including the DDD score had better prognostic ability (p = 0.01). CONCLUSIONS: This study found that RNS, DDD score, BMI, and sex were independent predictors of HGRCC. We developed effective nomograms integrating the above risk factors to predict HGRCC. Of note, the nomogram including the DDD score achieves better prediction ability for HGRCC.

Prediction of Fuhrman nuclear grade for clear cell renal carcinoma by a multi-information fusion model that incorporates CT-based features of tumor and serum tumor associated material.

PURPOSE: Prediction of Fuhrman nuclear grade is crucial for making informed herapeutic decisions in clear cell renal cell carcinoma (ccRCC). The current study aimed to develop a multi-information fusion model utilizing computed tomography (CT)-based features of tumors and preoperative biochemical parameters to predict the Fuhrman nuclear grade of ccRCC in a non-invasive manner. METHODS: 218 ccRCC patients confirmed by histopathology were retrospectively analyzed. Univariate and multivariate logistic regression analyses were performed to identify independent predictors and establish a model for predicting the Fuhrman grade in ccRCC. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration, the 10-fold cross-validation method, bootstrapping, the Hosmer-Lemeshow test, and decision curve analysis (DCA). RESULTS: R.E.N.A.L. Nephrometry Score (RNS) and serum tumor associated material (TAM) were identified as independent predictors for Fuhrman grade of ccRCC through multivariate logistic regression. The areas under the ROC curve (AUC) for the multi-information fusion model composed of the above two factors was 0.810, higher than that of the RNS (AUC 0.694) or TAM (AUC 0.764) alone. The calibration curve and Hosmer-Lemeshow test showed the integrated model had a good fitting degree. The 10-fold cross-validation method (AUC 0.806) and bootstrap test (AUC 0.811) showed the good stability of the model. DCA demonstrated that the model had superior clinical utility. CONCLUSION: A multi-information fusion model based on CT features of tumor and routine biochemical indicators, can predict the Fuhrman grade of ccRCC using a non-invasive approach. This model holds promise for assisting clinicians in devising personalized management strategies.

Characterization of renal artery variation in patients with clear cell renal cell carcinoma and the predictive value of accessory renal artery in pathological grading of renal cell carcinoma: a retrospective and observational study.

OBJECTIVE: To explore the characteristics of renal artery variation in patients with renal cell carcinoma and to evaluate the predicting value of accessory renal artery in the pathological grading of renal cell carcinoma. METHODS: The clinicopathological data of patients with clear cell renal cell carcinoma diagnosed in the Department of Urology of the First Hospital of Shanxi Medical University from September 2019 to March 2023 were retrospectively analyzed. All patients underwent visual three-dimensional model reconstruction from computed tomography images. All kidneys were divided into two groups: the affected kidney and the healthy kidney, and the incidence of renal artery variation in the two groups was analyzed. Then, according to the existence of accessory renal artery in the affected kidney, the patients were divided into two groups, and the relationship between accessory renal artery and clinicopathological features of patients with clear cell renal cell carcinoma was analyzed. Finally, univariate and multivariate logistic regression analyses were performed to determine the predictors of Fuhrman grading of clear cell renal cell carcinoma, and the predictive ability of the model was evaluated by the receiver operating characteristic curve. RESULTS: The incidence of renal artery variation and accessory renal artery in the affected kidney was significantly higher than them in the healthy kidney. The patients with accessory renal artery in the affected kidney had larger tumor maximum diameter, higher Fuhrman grade and more exophytic growth. The presence of accessory renal artery on the affected kidney and the maximum diameter of tumor are independent predictors of high-grade renal cell carcinoma. The receiver operating characteristic curve suggests that the model has a good predictive ability. CONCLUSION: The existence of accessory renal artery on the affected kidney may be related to the occurrence and development of clear cell renal cell carcinoma, and can better predict Fuhrman grade of clear cell renal cell carcinoma. The finding provides a reference for the future diagnostic evaluation of RCC, and provides a new direction for the study of the pathogenesis of RCC.

Using Peritumor and Intratumor Vascularity on Preoperative Imaging to Predict Fuhrman Grade Histology of Renal Tumors.

Objective: To investigate if peritumor and/or intratumor vasculature is associated with high-grade tumor histology for renal cell carcinoma. Methods: A retrospective review at a tertiary care facility was performed of patients who underwent radical nephrectomy or partial nephrectomy for a renal tumor between January 2015 and December 2020. Data of tumor characteristics were collected from final pathology reports. A single radiologist specializing in genitourinary imaging reviewed all preoperative cross-sectional imaging for peritumor vessels and intratumor vessels. Single and multivariable logistic regression was utilized to identify variables associated with high-grade tumor histology. Results: The average tumor size on final pathology report was 6.4 cm (range 3.0-17.0 cm). Ninety-two patients (56.1%) had either an enlarged peritumor vessel (n = 72), an intratumor vessel (n = 3), or both a peritumor vessel and an intratumor vessel (n = 17). Of the 92 patients with either a peritumor vessel or both a peritumor vessel and intratumor vessel, 60.9% of these patients had high Fuhrman grade histology on final pathology report (60.9% vs 39.1%, p < 0.001). Pathologic stage T1a tumors with an enlarged peritumor vessel on preoperative imaging were associated with high Fuhrman grade histology (58.3% vs 41.7%, p = 0.015). Across all stages, the presence of an enlarged peritumor vessel was significantly associated with high Fuhrman grade (odds ratio: 2.37, 95% confidence interval 1.17-4.9, p = 0.01). Conclusion: Findings suggest that vessels surrounding small renal tumors and large renal tumors is associated with high tumor grade (Fuhrman grade >3). Further research is needed to support the association of peritumor vessels with high tumor grade.

Metabolic Syndrome is an Independent Risk Factor for Fuhrman Grade and TNM Stage of Renal Clear Cell Carcinoma.

BACKGROUND: More and more evidences show that metabolic syndrome (MS) is closely related to clear cell renal cell carcinoma (ccRCC), but the impact of MS on Fuhrman grade and TNM stage of ccRCC is rarely reported. PURPOSE: To explore the relationship between MS and its components of Fuhrman grade and TNM stage in ccRCC. OBJECTIVE: The clinical data of 247 patients with ccRCC diagnosed in our hospital from January 2016 to November 2020 were retrospectively collected and analyzed. Based on diagnostic criteria of MS, the patients were divided into MS and non-MS group. Logistic regression analysis was used to analyze the independent risk factors of ccRCC. RESULTS: The incidence of MS was 32.79% (81/247). There was no significant difference in age, gender, smoking and drinking between MS group and non-MS group (P > 0.05). In MS group, BMI ≥25kg/m2, hypertension, diabetes, hyperlipidemia, tumor diameter, poorly differentiated renal cancer, high-stage renal cancer, triglyceride, fasting blood glucose, glycated hemoglobin, fasting insulin and homeostasis model assessment index were significantly higher than those in non-MS group (P < 0.001), while in high density lipoprotein cholesterol (p < 0.005), islet beta cell secretory index (P < 0.001), well-differentiated renal cell carcinoma (P= 0.009), and low-stage renal cell carcinoma (P = 0.019) were significantly lower than that of non-MS group. Logistic regression analysis showed that hypertension (P = 0.005), diabetes (P = 0.012), hyperlipidemia (P = 0.021) are independent risk factors for Fuhrman grade of ccRCC, while diabetes (P = 0.002), hyperlipidemia (P = 0.007) are independent risk factors for TNM staging of ccRCC. CONCLUSION: The patients with ccRCC and MS had higher Fuhrman grade and TNM stage. MS is an independent risk factor for Fuhrman grade and TNM stage of ccRCC.

The Growing Role for Semantic Segmentation in Urology.

As the quantity and quality of cross-sectional imaging data increase, it is important to be able to make efficient use of the information. Semantic segmentation is an emerging technology that promises to improve the speed, reproducibility, and accuracy of analysis of medical imaging, and to allow visualization methods that were previously impossible. Manual image segmentation often requires expert knowledge and is both time- and cost-prohibitive in many clinical situations. However, automated methods, especially those using deep learning, show promise in alleviating this burden to make segmentation a standard tool for clinical intervention in the future. It is therefore important for clinicians to have a functional understanding of what segmentation is and to be aware of its uses. Here we include a number of examples of ways in which semantic segmentation has been put into practice in urology. PATIENT SUMMARY: This mini-review highlights the growing role of segmentation methods for medical images in urology to inform clinical practice. Segmentation methods show promise in improving the reliability of diagnosis and aiding in visualization, which may become a tool for patient education.

18F-FDG texture analysis predicts the pathological Fuhrman nuclear grade of clear cell renal cell carcinoma.

PURPOSE: This article analyzes the image heterogeneity of clear cell renal cell carcinoma (ccRCC) based on positron emission tomography (PET) and positron emission tomography-computed tomography (PET/CT) texture parameters, and provides a new objective quantitative parameter for predicting pathological Fuhrman nuclear grading before surgery. METHODS: A retrospective analysis was performed on preoperative PET/CT images of 49 patients whose surgical pathology was ccRCC, 27 of whom were low grade (Fuhrman I/II) and 22 of whom were high grade (Fuhrman III/IV). Radiological parameters and standard uptake value (SUV) indicators on PET and computed tomography (CT) images were extracted by using the LIFEx software package. The discriminative ability of each texture parameter was evaluated through receiver operating curve (ROC). Binary logistic regression analysis was used to screen the texture parameters with distinguishing and diagnostic capabilities and whose area under curve (AUC) > 0.5. DeLong's test was used to compare the AUCs of PET texture parameter model and PET/CT texture parameter model with traditional maximum standardized uptake value (SUVmax) model and the ratio of tumor SUVmax to liver SUVmean (SUL)model. In addition, the models with the larger AUCs among the SUV models and texture models were prospectively internally verified. RESULTS: In the ROC curve analysis, the AUCs of SUVmax model, SUL model, PET texture parameter model, and PET/CT texture parameter model were 0.803, 0.819, 0.873, and 0.926, respectively. The prediction ability of PET texture parameter model or PET/CT texture parameter model was significantly better than SUVmax model (P = 0.017, P = 0.02), but it was not better than SUL model (P = 0.269, P = 0.053). In the prospective validation cohort, both the SUL model and the PET/CT texture parameter model had good predictive ability, and the AUCs of them were 0.727 and 0.792, respectively. CONCLUSION: PET and PET/CT texture parameter models can improve the prediction ability of ccRCC Fuhrman nuclear grade; SUL model may be the more accurate and easiest way to predict ccRCC Fuhrman nuclear grade.

[Expression of Hemeoxygenase-1 and clear cell renal cell carcinoma aggressiveness.] / Expresión de Hemo Oxigenasa-1 y agresividad del carcinoma renal de células claras.

OBJECTIVE: Hemoxigenase 1 (HO-1) is an enzyme that has anti-apoptotic and proliferative effects on tumor cells. However, there is little epidemiological and clinical evidence on the role of HO-1 in urologic tumors. OBJECTIVE: To determine if there is correlation between the expression of HO-1 and the histological characteristics, evolution, Disease Free Survival (DFS) and cancer mortality in Clear Cell Renal Cell Carcinoma (cRCC). MATERIALS AND METHODS: A retrospective study including 34 patients (9 women and 25 men) with cRCC from the "Servicio de Urología del Policlínico Neuquén" (Argentina) throughout 2003-2008. The expression of HO-1 by Immunohistochemistry (IHC) was determined. The statistical analysis was performed using the Student'sT test and Pearson correlation coefficient (p≤0.05). RESULTS: HO-1 was expressed in the epithelial cells of the tubules from normal kidney tissue and in the cytoplasmof cRCC tumor cells. There were no differences in the HO-1 expression related to the gender, age, tumorsize, stage of disease and 5 years DFS. High FuhrmancRCC had a greater expression of HO-1 compared with low Fuhrman cRCC (p≤0.05). The score of immunostaining for HO-1 was greater in those tumors located in the mesorrenal area, which coincidentally presented a more advanced stage of the disease. CONCLUSIONS: Over expression of HO-1 in tumors located in the interpolar zone and with high Furhman grade suggest that HO-1 could be a good adjunctive marker for the aggressiveness of the cRCC.

OBJETIVO: Hemoxigenasa 1 (HO-1) es una enzima que tiene efectos antiapoptóticos y proliferativos en células tumorales. Sin embargo, existe poca evidencia epidemiológica y clínica sobre el rol de la HO-1 en los tumores urológicos. Objetivo: determinar si existe correlación entre la expresión de HO-1 y las características histológicas, evolución, Sobrevida Libre de Enfermedad (SLE) y mortalidad por cáncer en Carcinomas Renales de Células Claras (cRCC). MATERIALES Y MÉTODOS: Se realizó un estudio retrospectivo en 34 pacientes (9 mujeres y 25 hombres) con cRCC del Servicio de Urología del Policlínico Neuquén, reclutados entre los años 2003 y 2008. Se determinó la expresión de HO-1 por Inmunohistoquímica (IHQ). El análisis estadístico se realizó mediante la prueba T de Student y Coeficiente de correlación de Pearson (p<0,05). RESULTADOS: HO-1 se expresó en el epitelio de los túbulos del tejido renal normal y en el citoplasma de las células tumorales de cRCC. No se observaron diferencias en la expresión de HO-1 según género, edad, tamaño tumoral, estadio de la enfermedad y SLE a los 5 años. Los tumores con Fuhrman alto presentaron una mayor expresión de HO-1 que los Furhman bajo (p≤0,05). El score de inmunotinción de HO-1 fue mayor en los tumores localizados en la zona interpolar, que coincidentemente presentaban un estadio más avanzado de la enfermedad. CONCLUSIONES: La sobreexpresión de HO-1 en tumores localizados en la zona interpolar y con grado de Furhman alto sugieren que HO-1 podría ser un buen marcador complementario de la agresividad del cRCC.

Decreased prolyl hydroxylase 3 mRNA expression in oncocytomas compared with clear cell renal cell carcinoma.

INTRODUCTION: Hypoxia inducible factors (HIF) and prolyl hydroxylase domain (PHD) enzymes play a central role in tumor progression in clear cell renal cell carcinoma (ccRCC). However, there are currently no data regarding the behavior of this pathway (HIF/PHD) in a large number of benign renal tumors, the oncocytomas. The aim of the present study was to compare the expression levels of these factors between ccRCC and oncocytoma tumors. MATERIAL AND METHODS: A total of 56 fresh frozen specimens from patients with ccRCC and 14 oncocytoma specimens were analyzed via reverse transcription-quantitative polymerase chain reaction in order to assess the expression levels of HIF-1α, HIF-2α, PHD1, PHD2, and PHD3. The analysis involved both fresh frozen tumor samples as well as adjacent normal kidney tissues. RESULTS: In ccRCC, HIF-1α and HIF-2α levels were upregulated in 65.5% and 71.4% of cases, respectively. PHD3 was downregulated only in 15.4% of the ccRCC cases, in contrast with oncocytoma cases, which exhibited low expression levels in the majority. The upregulation of PHD3 messenger RNA (mRNA) levels in ccRCC when compared with oncocytoma was statistically significant (P<0.001). No other comparisons (HIF-1α, HIF-2α, PHD1, and PHD2) were significantly different. HIF-2α and PHD3 mRNA expression levels were negatively correlated with Fuhrman Grade (P=0.029 and P=0.026, respectively) in ccRCC. CONCLUSION: To the best of our knowledge, this is the first time that the HIF/PHD pathway was compared between ccRCC and a common benign tumor, identifying the upregulation of PHD3 as the possible underlying factor guiding the difference in the behavior of ccRCC.

mRNA overexpression of prolyl hydroxylase PHD3 is inversely related to nuclear grade in renal cell carcinoma.

The aim of the present study was to evaluate the relative mRNA expression levels of genes involved in the hypoxia inducible factor (HIF) signalling pathway in renal cell carcinoma (RCC) and to analyse their associations with clinicopathological parameters and survival outcomes. Reverse transcription-quantitative PCR was used to quantify the mRNA expression levels of HIF-1α, HIF-2α, prolyl hydroxylase (PHD)1, PHD2 and PHD3 in formalin-fixed paraffin-embedded (FFPE) tumour tissue samples from 41 patients with RCC, including 33 cases of clear cell RCC (ccRCC). FFPE samples of corresponding adjacent normal kidney tissues were used as a comparison. mRNA expression levels were analysed in regard to clinical parameters, histological type, stage, nuclear grade, cancer specific survival and overall survival. Compared with adjacent normal kidney tissue, HIF-1α levels were lower in 16/33 ccRCC samples (48.48%), while HIF-2α, PHD1 and PHD2 levels did not exhibit a specific expression pattern. By contrast, the PHD3 mRNA level was higher in 29/33 (87.87%) of the tumour samples. HIF-1α was positively associated with HIF-2α, PHD1 and PHD2. HIF-2α levels were associated with PHD1, PHD2 and PHD3, while PHD3 was strongly associated with PHD2. PHD3 mRNA levels were inversely associated with nuclear grade (P=0.015). However, in univariate analysis, PHD3 was not associated with cancer-specific or overall survival rates. The present findings suggest an important involvement of PHD3 in ccRCC, since PHD3 mRNA expression was inversely associated with nuclear grade. However, PHD3 mRNA levels did not have an independent prognostic value. Further studies are required to investigate whether PHD3 could be used as either a therapeutic target or prognostic marker.

MRI Radiomics for the Prediction of Fuhrman Grade in Clear Cell Renal Cell Carcinoma: a Machine Learning Exploratory Study.

The Fuhrman nuclear grade is a recognized prognostic factor for patients with clear cell renal cell carcinoma (CCRCC) and its pre-treatment evaluation significantly affects decision-making in terms of management. In this study, we aimed to assess the feasibility of a combined approach of radiomics and machine learning based on MR images for a non-invasive prediction of Fuhrman grade, specifically differentiation of high- from low-grade tumor and grade assessment. Images acquired on a 3-Tesla scanner (T2-weighted and post-contrast) from 32 patients (20 with low-grade and 12 with high-grade tumor) were annotated to generate volumes of interest enclosing CCRCC lesions. After image resampling, normalization, and filtering, 2438 features were extracted. A two-step feature reduction process was used to between 1 and 7 features depending on the algorithm employed. A J48 decision tree alone and in combination with ensemble learning methods were used. In the differentiation between high- and low-grade tumors, all the ensemble methods achieved an accuracy greater than 90%. On the other end, the best results in terms of accuracy (84.4%) in the assessment of tumor grade were achieved by the random forest. These evidences support the hypothesis that a combined radiomic and machine learning approach based on MR images could represent a feasible tool for the prediction of Fuhrman grade in patients affected by CCRCC.

ACAT1 and Metabolism-Related Pathways Are Essential for the Progression of Clear Cell Renal Cell Carcinoma (ccRCC), as Determined by Co-expression Network Analysis.

Kidney cancer ranks as one of the top 10 causes of cancer death; this cancer is difficult to detect, difficult to treat, and poorly understood. The most common subtype of kidney cancer is clear cell renal cell carcinoma (ccRCC) and its progression is influenced by complex gene interactions. Few clinical studies have investigated the molecular markers associated with the progression of ccRCC. In this study, we collected microarray profiles of 72 ccRCCs and matched normal samples to identify differentially expressed genes (DEGs). Then a weighted gene co-expression network analysis (WGCNA) was conducted to identify co-expressed gene modules. By relating all co-expressed modules to clinical features, we found that the brown module and Fuhrman grade had the highest correlation (r = -0.8, p = 1e-09). Thus, the brown module was regarded as a clinically significant module and subsequently analyzed. Functional annotation showed that the brown module focused on metabolism-related biological processes and pathways, such as fatty acid oxidation and amino acid metabolism. We then performed a protein-protein interaction (PPI) network to identify the hub nodes in the brown module. It is worth noting that only one candidate, acetyl-CoA acetyltransferase (ACAT1), was considered to be the final target most relevant to the Fuhrman grade of ccRCC, by applying the intersection of hub genes in the co-expressed network and the PPI network. ACAT1 was subsequently validated using another two external microarray datasets and the TCGA dataset. Intriguingly, validation results indicated that ACAT1 was negatively correlated with four grades of ccRCC, which was also consistent with our results from qRT-PCR analysis and immunohistochemistry staining of clinical samples. Overexpression of ACAT1 inhibited the proliferation and migration of human ccRCC cells in vitro. In addition, the Kaplan-Meier survival curve showed that patients with a lower expression of ACAT1 showed a significantly lower overall survival rate and disease-free survival rate, indicating that ACAT1 could act as a prognostic and recurrence/progression biomarker of ccRCC. In summary, we found and confirmed that ACAT1 might help to identify the progression of ccRCC, which might have important clinical implications for enhancing risk stratification, therapeutic decision, and prognosis prediction in ccRCC patients.

Role of MR texture analysis in histological subtyping and grading of renal cell carcinoma: a preliminary study.

PURPOSE: The study evaluated the usefulness of magnetic resonance imaging (MRI) texture parameters in differentiating clear cell renal carcinoma (CC-RCC) from non-clear cell carcinoma (NC-RCC) and in the histological grading of CC-RCC. MATERIALS AND METHODS: After institutional ethical approval, this retrospective study analyzed 33 patients with 34 RCC masses (29 CC-RCC and five NC-RCC; 19 low-grade and 10 high-grade CC-RCC), who underwent MRI between January 2011 and December 2012 on a 1.5-T scanner (Avanto, Siemens, Erlangen, Germany). The MRI protocol included T2-weighted imaging (T2WI), diffusion-weighted imaging [DWI; at b 0, 500 and 1000 s/mm2 with apparent diffusion coefficient (ADC) maps] and T1-weighted pre and postcontrast [corticomedullary (CM) and nephrographic (NG) phase] acquisition. MR texture analysis (MRTA) was performed using the TexRAD research software (Feedback Medical Ltd., Cambridge, UK) by a single reader who placed free-hand polygonal region of interest (ROI) on the slice showing the maximum viable tumor. Filtration histogram-based texture analysis was used to generate six first-order statistical parameters [mean intensity, standard deviation (SD), mean of positive pixels (MPP), entropy, skewness and kurtosis] at five spatial scaling factors (SSF) as well as on the unfiltered image. Mann-Whitney test was used to compare the texture parameters of CC-RCC versus NC-RCC, and high-grade versus low-grade CC-RCC. P value < 0.05 was considered significant. A 3-step feature selection was used to obtain the best texture metrics for each MRI sequence and included the receiver-operating characteristic (ROC) curve analysis and Pearson's correlation test. RESULTS: The best performing texture parameters in differentiating CC-RCC from NC-RCC for each sequence included (area under the curve in parentheses): entropy at SSF 4 (0.807) on T2WI, SD at SSF 4 (0.814) on DWI b500, SD at SSF 6 (0.879) on DWI b1000, mean at SSF 0 (0.848) on ADC, skewness at SSF 2 (0.854) on T1WI and skewness at SSF 3 (0.908) on CM phase. In differentiating high from low-grade CC-RCC, the best parameters were: entropy at SSF 6 (0.823) on DWI b1000, mean at SSF 3 (0.889) on CM phase and MPP at SSF 5 (0.870) on NG phase. CONCLUSION: Several MR texture parameters showed excellent diagnostic performance (AUC > 0.8) in differentiating CC-RCC from NC-RCC, and high-grade from low-grade CC-RCC. MRTA could serve as a useful non-invasive tool for this purpose.

The Role of Hematological Parameters in Predicting Fuhrman Grade and Tumor Stage in Renal Cell Carcinoma Patients Undergoing Nephrectomy.

Background and objective: We investigated the ability of preoperative serum values of red blood cell distribution width (RDW), neutrophil lymphocyte ratio (NLR) and plateletcrit (PCT) to predict Fuhrman grades (FG) and tumor stages of renal cell carcinoma in patients who underwent radical nephrectomy. Materials and methods: Records of 283 patients that underwent radical or partial nephrectomy of renal masses at our clinic between January 2010 and April 2018, whose pathology results indicated renal cell carcinoma (RCC), and who had their FG and T1-4 N0M0 identified were retrospectively evaluated. The patients were divided into two groups based on their FG as low (I-II) and high (III-IV) and their T stages were similarly grouped as limited to kidney (pT1-pT2) and not limited to kidney (pT3-pT4). Results: Mean RDW, NLR, PCT cut-off values of the patients for FG and T stage were 15.65%, 3.54, 0.28% and 14.35%, 2.69, 0.28%, respectively. The RDW and NLR were determined to be statistically significant predictors of a pathologically high FG, whereas the PCT value was not a statistically significant predictor of high FG (p = 0.003, p = 0.006, p = 0.075, respectively). The relationship of RDW, NLR and PCT values with a limited to the kidney pathological T stage revealed statistically significant correlations for all three values. Conclusions: We determined that only RDW and NLR were markers predicting FG, while PCT had no prognostic value. On the other hand, all three of these values were associated with a limited to the kidney pathological T stage in patients who underwent nephrectomy due to renal masses and whose pathologies suggested RCC.

Is Cardiometabolic Index a Predictive Marker for Renal Cell Cancer Aggressiveness?

Studies show that metabolic syndrome is a factor for developing renal cell cancer (RCC) and tumour aggressiveness. In our study, we evaluated the association between renal cell cancer and cardiometabolic index (CMI) which meets the main components of the metabolic syndrome. We retrospectively reviewed the records of 310 consecutive patients with RCC who underwent radical nephrectomy at our institution. We evaluated the tumour size, histologic subtype, Fuhrman nuclear grade. CMI was calculated as the product of waist circumference (WC) to waist-to-height ratio (WHtR) and triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-c). CMI were statistically higher in patients with tumour size ≥ 7 cm than those < 7 cm (p<0.05). Mean CMI level was 2.34 ± 0.84 in patients with high tumour size; and 1.18 ± 0.74 in the other group. The patients with high tumour size had higher TG levels, higher WC and lower HDL-c levels. Similarly, CMI levels were statistically higher in patients with Fuhrman grade 3 and 4 than patients with Fuhrman grade 1 and 2 (p<0.001). The patients with high Fuhrman grade had higher TG levels, higher WC and lower HDL-c levels. The simplicity of WC and height measurement and TG and HDL assessment make CMI an easily applicable index for the evaluation of cardiovascular dysfunction. The components of CMI may have effect on tumour carcinogenesis in similar pathways. In this context, CMI which meets the main components of the metabolic syndrome, can be a useful index for the evaluation and calculation of renal cell cancer aggressiveness.

Synchronous bilateral renal cell carcinomas in "Asynchrony of metabolism".

Here, we present a case of bilateral synchronous renal cell carcinoma in a 52-year-old male patient, who underwent fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET-CT) scan followed by surgical removal of both tumors. On PET scan, left renal mass showed intense FDG uptake while uptake in the right renal mass was minimal. Histopathologically, both tumors were conventional clear cell carcinoma (Fuhrman Grade III). Only the FDG-avid tumor in the left kidney had lymphovascular invasion and necrosis, which are markers of aggressive form of any tumor. FDG PET-CT can act as strong and noninvasive prognostic parameter that could help to identify patients with aggressive disease before treatment.

CT texture analysis: a potential tool for predicting the Fuhrman grade of clear-cell renal carcinoma.

BACKGROUND: The purpose of this study was to analyze the image heterogeneity of clear-cell renal-cell carcinoma (ccRCC) by computer tomography texture analysis and to provide new objective quantitative imaging parameters for the pre-operative prediction of Fuhrman-grade ccRCC. METHODS: A retrospective analysis of 131 cases of ccRCCs was performed by manually depicting tumor areas. Then, histogram-based texture parameters were calculated. The texture-feature values between Fuhrman low- (Grade I-II) and high-grade (Grade III-IV) ccRCCs were compared by two independent sample t-tests (False Discovery Rate correction), and receiver operating characteristic curve (ROC) was used to evaluate the efficacy of using texture features to predict Fuhrman high- and low-grade ccRCCs. RESULTS: There were no statistical differences for any texture parameters without filtering (p > 0.05). There was a statistically significant difference between the entropy (fine) of the corticomedullary phase and the entropy (fine and coarse) of the nephrographic phase after Laplace of Gaussian filtering. The area under the ROC of the entropy was between 0.74 and 0.83. CONCLUSIONS: Computer tomography texture features can predict the Fuhrman grading of ccRCC pre-operatively, with entropy being the most important imaging marker for clinical application.

Value of CT signs in predicting Fuhrman grading of clear cell renal carcinoma / 实用放射学杂志

Objective To investigate the predictive value of CT signs in the pathological Fuhrman grading of clear cell renal carcinoma (ccRCC).Methods The clinicopathological features and CT findings of 72 patients with ccRCC which confirmed by operation and pathology were analyzed retrospectively.According to the WHO Fuhrman grading,all patients were divided into low-grade(Fuhrman gradeⅠorⅡ)or high-grade (Fuhrman gradeⅢorⅣ).ChiG square test and t-test were used to compare the clinical data and CT findings between the two groups,including morphological features (site,whether the renal medulla invasion,morphology,growth pattern,border,pseudo-envelope,lobulation sign,interface,perirenal fascia and the same lateral adrenal invasion,renal sinus and perirenal fat invasion,venous invasion,lymphadenopathy, maximum diameter),density (bleeding,necrosis ratio,calcification,fat)and enhancement characteristics (the degree of enhancement, strengthening method).And the pathological Fuhrman grading was the gold standard.The ROC was used to analyze the diagnostic efficacy of CT signs on Fuhrman grading.The Delong test was used to compare the AUC of different CT signs.Results There were significant differences in tumor maximum diameter,the renal medulla invasion,and lobulation sign between the Fuhrman low-grade and high-grade group(χ2/t＝－4.31 7,9.794,7.325,P＜0.05).There were no differences in gender,age,location sign,morphology,growth pattern, border,pseudo-envelope,interface,perirenal fascia and ipsilateral adrenal invasion,renal sinus and perirenal fat invasion,necrosis ratio,degree of enhancement,strengthening method between two groups (P＞0.05). The largest diameter of the tumor,the renal medulla invasion and the lobulation sign were useful for Fuhrman diagnosis.The AUC was 0.778,0.647 and 0.644,respectively.And there were significant differences between the maximum diameter and the renal medulla invasion or lobulation sign (P＜0.05).Conclusion The maximum diameter,medulla and lobular sign can predict the Fuhrman grading of ccRCC,and the maximum diameter prediction is the most accurate.

Clear cell renal cell carcinoma: CT-based radiomics features for the prediction of Fuhrman grade.

OBJECTIVES: To discriminate low grade (Fuhrman I/II) and high grade (Fuhrman III/IV) clear cell renal cell carcinoma (CCRCC) by using CT-based radiomic features. METHODS: 161 and 99 patients diagnosed with low and high grade CCRCCs from January 2011 to May 2018 were enrolled in this study. 1029 radiomic features were extracted from corticomedullary (CMP), and nephrographic phase (NP) CT images of all patients. We used interclass correlation coefficient (ICC) and the least absolute shrinkage and selection operator (LASSO) regression method to select features, then the selected features were constructed three classification models (CMP, NP and with their combination) to discriminate high and low grades CCRCC. These three models were built by logistic regression method using 5-fold cross validation strategy, evaluated with receiver operating characteristics curve (ROC) and compared using DeLong test. RESULTS: We found 11 and 24 CMP and NP features were independently significantly associated with the Fuhrman grades. The model of CMP, NP and Combined model using radiomic feature set showed diagnostic accuracy of 0.719 (AUC [area under the curve], 0.766; 95% CI [confidence interval]: 0.709-0.816; sensitivity, 0.602; specificity, 0.838), 0.738 (AUC, 0.818; 95% CI:0.765-0.838; sensitivity, 0.693; specificity, 0.838), 0.777(AUC, 0.822; 95% CI: 0.769-0.866; sensitivity, 0.677; specificity, 0.839). There were significant differences in AUC between CMP model and Combined model (P = 0.0208), meanwhile, the differences between CMP model and NP model, NP model and Combined model reached no significant (P = 0.0844, 0.7915). CONCLUSIONS: Radiomic features could be used as biomarker for the preoperative evaluation of the CCRCC Fuhrman grades.

World Health Organization (WHO)/International Society of Urological Pathology (ISUP) grading in fine-needle aspiration biopsies of renal masses.

BACKGROUND: Utilization of fine-needle aspiration (FNA) biopsy for the evaluation of renal masses has been increasing at our institution. At times diagnostic material on direct smears is superior to that in the cell block/core biopsy, therefore assigning an accurate nuclear grade in the cytopathology report would provide useful prognostic information. METHODS: Search of the pathology database identified renal FNAs performed during an 11-year period (2006-2017). Corresponding core biopsies and resections were identified. Cases with a diagnosis of primary renal neoplasia on FNA, core biopsy, and/or resection were included. Two pathologists reviewed all cases and assigned a World Health Organization (WHO)/International Society of Urological Pathology (ISUP) grade to each FNA, core biopsy, and resection case. RESULTS: A total of 162 kidney FNAs were identified. Primary renal neoplasia was diagnosed in 137 cases on core biopsy/resection. Among diagnostic FNAs of clear cell RCC and papillary RCC with core biopsy/resection specimens for re-review (n = 52), reviewers assigned a concordant WHO/ISUP grade to 83% (43/52) of cases. Among 9 cases with discrepant scores, all had a discrepancy of 1 grade and were undergraded on FNA. Using a two tier grading system (low vs. high grade), reviewers assigned a concordant grade to 88% (46/52) of cases. Among 6 cases with discrepant scores, all were classified as low grade (WHO/ISUP grade 2) on FNA versus high grade (WHO/ISUP grade 3) on resection. CONCLUSION: The WHO/ISUP grade assigned on FNA shows good concordance with subsequent resection/core specimens (83%), with all discrepant cases being undergraded by one grade.