Magnetic resonance imaging-based radiomics signature for preoperative prediction of Ki67 expression in bladder cancer.

ABSTRACT:

Purpose

The Ki67 expression is associated with the advanced clinicopathological features and poor prognosis in bladder cancer (BCa). We aimed to develop and validate magnetic resonance imaging (MRI)-based radiomics signatures to preoperatively predict the Ki67 expression status in BCa.

Methods and materials

We retrospectively collected 179 BCa patients with Ki67 expression and preoperative MRI. Radiomics features were extracted from T2-weighted (T2WI) and dynamic contrast-enhancement (DCE) images. The synthetic minority over-sampling technique (SMOTE) was used to balance the minority group (low Ki67 expression group) in the training set. Minimum redundancy maximum relevance was used to identify the best features associated with Ki67 expression. Support vector machine and Lea

SUBMITTER: Zheng Z 

PROVIDER: S-EPMC8642943 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature