Combining clinical characteristics with CT radiomics to predict Ki67 expression level of small renal mass based on artificial intelligence algorithms.

Background: Most small renal masses (SRMs) grow slowly and have good prognosis, but a portion of SRMs can also demonstrate aggressive characteristics, which can be explored by the proliferation-related marker Ki67.

Methods: A total of 241 patients collected from the two centers were included in the study, of which 145 patients from the First Affiliated Hospital of Guangzhou Medical University were divided into training and validation cohort, while 96 patients from Sun Yat-sen Memorial Hospital were served as test cohort. To ensure the class balance of the outcome measures, the training cohort was oversampled, resulting in an increase of 77 cases in the minority class.