Pathological implications of areas of lower enhancement on contrast-enhanced computed tomography in renal-cell carcinoma: additional information for selecting candidates for surveillance protocols

Villalobos-Gollás, Miguel; Aguilar-Davidov, Bernardo; Culebro-García, Carolina; Gómez-Alvarado, Martha Olivia; Rojas-García, Priscila; Ibarra-Fombona, Raúl; Uribe‐Uribe, Norma; Feria-Bernal, Guillermo; Castillejos-Molina, Ricardo; Sotomayor, Mariano; Gabilondo, Fernando; Rodríguez-Covarrubias, Francisco

doi:10.1007/s11255-012-0199-8

Cited by 13 publications

(3 citation statements)

References 22 publications

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Section: Discussionmentioning

confidence: 99%

“…Previous reports have shown that CCRCC is a highly angiogenic and vascularized tumor(31). In addition, the differences in enhancement patterns between low-and high-grade CCRCCs have been proved to correlate to the hemodynamics and microvessel density (MVD) of individual RCC lesions(32,33). Ficarra et al(34) validated that intratumoral necrosis as a prognostic factor is useful in the clinical management of CCRCC patients, which is recommended by the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) scoring system…”

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confidence: 99%

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A CT-Based Radiomics Nomogram Integrated With Clinic-Radiological Features for Preoperatively Predicting WHO/ISUP Grade of Clear Cell Renal Cell Carcinoma

Guo

et al. 2021

Front. Oncol.

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ObjectiveThis study aims to develop and validate a CT-based radiomics nomogram integrated with clinic-radiological factors for preoperatively differentiating high-grade from low-grade clear cell renal cell carcinomas (CCRCCs).Methods370 patients with complete clinical, pathological, and CT image data were enrolled in this retrospective study, and were randomly divided into training and testing sets with a 7:3 ratio. Radiomics features were extracted from nephrographic phase (NP) contrast-enhanced images, and then a radiomics model was constructed by the selected radiomics features using a multivariable logistic regression combined with the most suitable feature selection algorithm determined by the comparison among least absolute shrinkage and selection operator (LASSO), recursive feature elimination (RFE) and ReliefF. A clinical model was established using clinical and radiological features. A radiomics nomogram was constructed by integrating the radiomics signature and independent clinic-radiological features. Performance of these three models was assessed using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA).ResultsUsing multivariate logistic regression analysis, three clinic-radiological features including intratumoral necrosis (OR=3.00, 95% CI=1.30-6.90, p=0.049), intratumoral angiogenesis (OR=3.28, 95% CI=1.22-8.78, p=0.018), and perinephric metastasis (OR=2.90, 95% CI=1.03-8.17, p=0.044) were found to be independent predictors of WHO/ISUP grade in CCRCC. Incorporating the above clinic-radiological predictors and radiomics signature constructed by LASSO, a CT-based radiomics nomogram was developed, and presented better predictive performance than clinic-radiological model and radiomics signature model, with an AUC of 0.891 (95% CI=0.832-0.962) and 0.843 (95% CI=0.718-0.975) in the training and testing sets, respectively. DCA indicated that the nomogram has potential clinical usefulness.ConclusionThe CT-based radiomics nomogram is a promising tool to predict WHO/ISUP grade of CCRCC preoperatively and noninvasively.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

A CT-Based Radiomics Nomogram Integrated With Clinic-Radiological Features for Preoperatively Predicting WHO/ISUP Grade of Clear Cell Renal Cell Carcinoma

Guo

et al. 2021

Front. Oncol.

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“…We have previously evaluated the reliability of computed tomography (CT) to predict nuclear grade in renal cell carcinoma [8]. In the present study we aimed to identify and quantify AAT and its compartments, as measured by CT, and determine their influence on histopathologic characteristics and outcomes of renal cell carcinoma in patients treated with radical or partial nephrectomy at a single tertiary care referral center in Mexico.…”

Section: Introductionmentioning

confidence: 99%

Abdominal subcutaneous adipose tissue as a predictor of high-grade renal cell carcinoma

Covarrubias

2017

Rev Mex Urol

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BACKGROUND: information about the influence of abdominal adipose tissue on the prognosis and aggressiveness of renal cell carcinoma is scarce.OBJECTIVE: to identify and quantify the relationship between abdominal adipose tissue and histopathologic characteristics of renal cell carcinoma.MATERIALS AND METHODS: data on patients with renal cell carcinoma treated with partial or radical nephrectomy were retrospectively collected. Visceral adipose tissue and subcutaneous adipose tissue were measured on preoperative computerized tomography scans. Histopathologic (pathologic 2002 TNM classification, tumor size, nuclear grade, necrosis, and metastasis) and clinical (sex, age, body mass index) variables were assessed. Visceral adipose tissue and subcutaneous adipose tissue were adjusted by patient height (VAT-I and SAT-I). The association between adipose tissue measurements, patient characteristics, and histopathologic variables was assessed through a correlation, comparison, and regression analysis. A survival analysis was also carried out.RESULTS: one-hundred and five patients were included. No significant relationship between visceral adipose tissue and histopathologic characteristics was found. SAT-I was a significant variable inversely related to sex, but more importantly to nuclear grade, pN+, and necrosis. There was no influence of visceral adipose tissue or subcutaneous adipose tissue on survival.CONCLUSIONS: subcutaneous adipose tissue was related to the histopathologic characteristics of renal cell carcinoma. A larger amount of subcutaneous adipose tissue predicted a low nuclear grade and a lower frequency of pN+ and necrosis. Further study to clarify the interaction between adipose tissue and renal cell carcinoma biology is required.KEY WORDS: renal cell carcinoma, subcutaneous-abdominal adipose tissue, prognosis

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CT prediction of the Fuhrman grade of clear cell renal cell carcinoma (RCC): towards the development of computer-assisted diagnostic method

et al. 2015

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Pathological implications of areas of lower enhancement on contrast-enhanced computed tomography in renal-cell carcinoma: additional information for selecting candidates for surveillance protocols

Abstract: Lower enhancement of the entire tumor at the point where hypodense tumor areas are more predominant on tomography is associated with higher nuclear grade and more advanced stage.

Cited by 13 publications

References 22 publications

A CT-Based Radiomics Nomogram Integrated With Clinic-Radiological Features for Preoperatively Predicting WHO/ISUP Grade of Clear Cell Renal Cell Carcinoma

A CT-Based Radiomics Nomogram Integrated With Clinic-Radiological Features for Preoperatively Predicting WHO/ISUP Grade of Clear Cell Renal Cell Carcinoma

Abdominal subcutaneous adipose tissue as a predictor of high-grade renal cell carcinoma

CT prediction of the Fuhrman grade of clear cell renal cell carcinoma (RCC): towards the development of computer-assisted diagnostic method

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