Construction of a postoperative liver metastasis prediction model for colorectal cancer based on spectral CT imaging, CEA, and CA19-9.

ABSTRACT:

Background

Most existing models for predicting liver metastasis primarily rely on single clinical indicators or traditional imaging features, which, while useful, offer limited accuracy and reliability. In recent years, spectral computed tomography (CT) has emerged as a dual-energy imaging technology that provides detailed quantitative analyses of the blood supply characteristics and metabolic activity of tumors. The integration of serum biomarkers such as carcinoembryonic antigen (CEA) and cancer antigen 19-9 (CA19-9) with spectral CT features holds great potential for significantly enhancing the accuracy of liver metastasis predictions. This study aims to develops a novel nomogram prediction model based on spectral CT, CEA, and CA19-9 to predict the risk of liver metastasis after

SUBMITTER: Yang Q 

PROVIDER: S-EPMC11985183 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature