CT Features in Differentiating Chromophobe Cell Renal Carcinoma from Renal Oncocytoma and CK7 Expression Evaluation: A Radiomics Analysis

Abstract Background: To investigate the value of computed tomography (CT)-based radiomics model analysis in differentiating chromophobe cell renal carcinoma (chRCC) from renal oncocytoma (RO) and predicting the expression of Cytokeratin 7 (CK7).Methods: In this retrospective study, radiomics was applied for patients with chRCC and RO who underwent surgery between January 2013 and December 2019 comprised the training cohort, and the validation cohort was collected between January and October 2020. The corticomedullary (CMP) and nephrographic phases (NP) were manually segmented, and radiomics texture parameters were extracted. Support vector machine was generated from CMP and NP after feature selection. Shapley additive explanations were applied to interpret the radiomics features. A radiomics signature was built using the selected features from the two phases, and the radiomics nomogram was constructed by incorporating the radiomics features and clinical factors. Receiver operating characteristic curve was calculated to evaluate the above models in the two sets. Furthermore, Rad-score was used for correlation analysis with CK7.Results: A total of 80 patients with chRCC and RO were analyzed in the training cohort and 36 patients with chRCC and RO in the validation cohort. Subsequently, 396 radiomics features were selected from each phase. The radiomics features combining two phases yielded the highest area under the curve values of 0.951 and 0.890 in the training and validation sets, respectively. The Pearson’s correlation coefficient was statistically significant between Rad-score and CK7.Conclusion: We proposed a non-invasive and individualized CT-based radiomics nomogram to differentiation between chRCC and RO preoperatively and predict the immunohistochemical protein expression for accurate clinical diagnosis and treatment decision.