An MRI-based radiomics signature and clinical characteristics for survival prediction in early-stage cervical cancer.

ABSTRACT:

Objectives

To investigate the prognostic role of magnetic resonance imaging (MRI)-based radiomics signature and clinical characteristics for overall survival (OS) and disease-free survival (DFS) in the early-stage cervical cancer.

Methods

A total of 207 cervical cancer patients (training cohort: n = 144; validation cohort: n = 63) were enrolled. 792 radiomics features were extracted from T2W and diffusion-weighted imaging (DWI). 19 clinicopathological parameters were collected from the electronic medical record system. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to select significant features to construct prognostic model for OS and DFS. Kaplan-Meier (KM) analysis and log-rank test were applied to identify the associatio

SUBMITTER: Zheng RR 

PROVIDER: S-EPMC8722251 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature