Spectral CT radiomics features of the tumor and perigastric adipose tissue can predict lymph node metastasis in gastric cancer.

ABSTRACT:

Objectives

To develop a nomogram based on the radiomics features of tumour and perigastric adipose tissue adjacent to the tumor in dual-layer spectral detector computed tomography (DLCT) for lymph node metastasis (LNM) prediction in gastric cancer (GC).

Methods

A retrospective analysis was conducted on 175 patients with gastric adenocarcinoma. They were divided into training cohort (n = 125) and validation cohort (n = 50). The radiomics features from the tumour and perigastric fat based on DLCT spectral images were extracted to construct radiomics models for LNM prediction using Lasso-GLM method. Preoperative clinicopathological features, DLCT routine parameters, and the optimal radiomics models were analyzed to establish the clinical-DLCT model, clinical-DLCT-radiomics mode

SUBMITTER: Zhang Z 

PROVIDER: S-EPMC12267316 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature