Multi-parametric MRI-based radiomics nomogram for predicting lymphovascular space invasion in early-stage cervical adenocarcinoma.

ABSTRACT:

Purpose

To develop a magnetic resonance imaging (MRI)-based radiomics nomogram to predict lymphovascular space invasion (LVSI) status in patients with early-stage cervical adenocarcinoma (CAC).

Methods

Clinicopathological and MRI data from 310 patients with histopathologically confirmed early-stage CAC were retrospectively analyzed. Patients were divided into training (n = 186) and validation (n = 124) cohorts. Tumor volumes of interest (VOIs) were segmented on T2-weighted imaging (FS-T2WI) and aligned to diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) maps, and T1-weighted imaging (CE-T1WI) sequences. Radiomics features were extracted and screened using Pearson correlation and least absolute shrinkage and selection operator (LASSO) regression, and a r

SUBMITTER: Wang KY 

PROVIDER: S-EPMC12409719 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature