Discussion
tumor, high-grade, kidney tumors, RCC, tumors
TUMOR, TUMORS, KIDNEY TUMORS, RCC
With the increased detection rate of small ccRCC, the frequent underestimation of the histological grade of tumors on puncture biopsy, and the widespread use of active surveillance for patients with small RCC in clinical practice, a reliable method is needed to differentiate the histological grade of small ccRCC. This study has high accuracy in constructing a nomogram for the WHO/ISUP nuclear grading of small ccRCC based on clinic-radiological characteristics and radiomics features, with AUC values of 0.940 (95%CI, 0.894–0.977) and 0.902 (95%CI, 0.811–0.976) in the training and testing sets, respectively.Previous studies have shown that the diagnostic of SRM is primarily based on imaging characteristics. Takahashi et al. [As a new form of artificial intelligence, radiomics is widely used in the diagnostic and differential diagnosis of SRMs [Our study has several limitations. Firstly, the sample size for this study is small, and there is a lack of external validation data. This is due to the fact that we only included ccRCC tumors with a diameter less than 4 cm, and more cases could be collected prospectively for future studies. Secondly, the tumor segmentation in this study was based on manual segmentation, which is both time-consuming and subjective. It would be beneficial to investigate an automated segmentation method for kidney tumors in the future. Lastly, this study only classified ccRCC as high-grade and low grades, which is not a highly accurate classification system. Future studies could develop a model with four categories.