Value of the application of computed tomography-based radiomics for preoperative prediction of unfavorable pathology in initial bladder cancer.

ABSTRACT:

Objectives

To construct and validate unfavorable pathology (UFP) prediction models for patients with the first diagnosis of bladder cancer (initial BLCA) and to compare the comprehensive predictive performance of these models.

Materials and methods

A total of 105 patients with initial BLCA were included and randomly enrolled into the training and testing cohorts in a 7:3 ratio. The clinical model was constructed using independent UFP-risk factors determined by multivariate logistic regression (LR) analysis in the training cohort. Radiomics features were extracted from manually segmented regions of interest in computed tomography (CT) images. The optimal CT-based radiomics features to predict UFP were determined by the optimal feature filter and the least absolute shrinkage a

SUBMITTER: Xiong S 

PROVIDER: S-EPMC10469743 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature