CT-based liver peritumoural radiomics features predict hepatic metastases sources as gastrointestinal or non-gastrointestinal. Academic Article uri icon

Overview

abstract

  • OBJECTIVES: To investigate the feasibility of radiomics models for predicting the source of hepatic metastases from gastrointestinal (GI) vs non-gastrointestinal (non-GI) primary tumours on contrast-enhanced CT (CECT). METHODS: Three hundred and forty-seven patients with liver metastases (180 from GI and 167 from non-GI) and abdominal CECT including arterial, portal venous, and delayed phases were divided into training (221) and validation (96) sets at a ratio of 7:3 and an independent testing set (30). Radiomics features were extracted from volumes of interest (VOIs) including tumoural (Vtc) and peritumoural (Vpt) regions on CECT. Optimal radiomics features were used in logistic regression models using receiver operating curve (ROC) analysis to evaluate the diagnostic efficiency. RESULTS: The best single-phase model was a venous phase peritumoural VOI with 11 features. Area under the curve (AUC), sensitivity, and specificity were 0.817, 0.740, and 0.761, respectively in the validation set. While the best arterial phase tumoural VOI gave an AUC of 0.677 in the validation set. For the combined models, peritumoural VOI in arterial and venous phases (15 features) achieved the best prediction performance with an AUC of 0.926 in the validation set and 0.884 in the testing set. CONCLUSION: Liver peritumoural radiomics features extracted from CECT were able to identify the source of hepatic metastases as GI vs non-GI. ADVANCES IN KNOWLEDGE: Peritumoural radiomics features showed a correlation with source of liver metastases. The radiomics features from liver peritumoural arterial and venous phases CT were promising in differentiating the source of hepatic metastases from GI vs non-GI primary tumours.

publication date

  • March 1, 2025

Research

keywords

  • Gastrointestinal Neoplasms
  • Liver Neoplasms
  • Tomography, X-Ray Computed

Identity

Scopus Document Identifier

  • 85218791517

Digital Object Identifier (DOI)

  • 10.1093/bjr/tqae248

PubMed ID

  • 39719063

Additional Document Info

volume

  • 98

issue

  • 1167