Abstract
Background Clear cell renal cell carcinoma (ccRCC) is the most common renal malignant tumor. Preoperative imaging boasts advantages in diagnosing and choosing treatment methods for ccRCC. Purpose This study is aimed at building models based on R.E.N.A.L. nephrometry score (RNS) and CT texture analysis (CTTA) to estimate the Fuhrman grade of ccRCC and comparing the advantages and disadvantages of the two models. Materials and Methods 143 patients with pathologically confirmed ccRCC were enrolled. All patients were stratified into Fuhrman low-grade and high-grade groups with complete CT data and R.E.N.A.L. nephrometry scores. CTTA features were extracted from the ROI delineated at the largest tumor level, and RNS and CTTA features were included in the logistic regression model, respectively. Results RNS model constructed based on multivariate logistic regression analysis showed that 3 pts for R-scores, 2 pts for E-scores, and 3 pts for L-scores were significant indicators to predict high-grade ccRCC, the AUC of RNS model was 0.911, and the sensitivity and specificity were 71.11% and 83.67%, respectively. The CTTA-model confirmed energy, kurtosis, and entropy as independent predictive factors, and the AUC of CTTA model was 0.941, with an optimal sensitivity and specificity of 84.44% and 93.88%. Conclusions R.E.N.A.L. nephrometry score has a certain provocative effect on the Fuhrman pathological grading of ccRCC. As a potential emerging technology, CTTA is expected to replace R.E.N.A.L. nephrometry score in evaluating patients' Fuhrman classification, and this approach might become an available method for assisting clinicians in choosing appropriate operation.
Highlights
Renal cell carcinoma (RCC) is the most common renal malignant tumor, originating from the renal parenchymal urinary epithelial system and accounting for 80%–90% of primary renal malignant tumors
As compared with other subtypes of RCC, clear cell renal cell carcinoma is the most common subtype of RCC, which accounts for 70%-80% of RCC [1, 2]
Fuhrman classification scheme was widely used in the pathological grading of RCC and was one of the main factors suggesting affecting the prognosis of RCC
Summary
Renal cell carcinoma (RCC) is the most common renal malignant tumor, originating from the renal parenchymal urinary epithelial system and accounting for 80%–90% of primary renal malignant tumors. Fuhrman classification scheme was widely used in the pathological grading of RCC and was one of the main factors suggesting affecting the prognosis of RCC. This pathological grading system was originally proposed by Fuhrman et al [5], who mainly classified tumor cells into four grades based on the size of the nucleus and the morphology of the nucleoli. This study is aimed at building models based on R.E.N.A.L. nephrometry score (RNS) and CT texture analysis (CTTA) to estimate the Fuhrman grade of ccRCC and comparing the advantages and disadvantages of the two models. As a potential emerging technology, CTTA is expected to replace R.E.N.A.L. nephrometry score in evaluating patients’ Fuhrman classification, and this approach might become an available method for assisting clinicians in choosing appropriate operation
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