Prediction models for differentiating benign from malignant liver lesions based on multiparametric dual-energy non-contrast CT.

ABSTRACT:

Objectives

To create prediction models (PMs) for distinguishing between benign and malignant liver lesions using quantitative data from dual-energy CT (DECT) without contrast agents.

Materials and methods

This retrospective study included patients with liver lesions who underwent DECT, including non-contrast-enhanced scans. Benign lesions included hepatic hemangioma, whereas malignant lesions included hepatocellular carcinoma, metastatic liver cancer, and intrahepatic cholangiocellular carcinoma. Patients were divided into derivation and validation groups. In the derivation group, two radiologists calculated ten multiparametric data using univariate and multivariate logistic regression to generate PMs. In the validation group, two additional radiologists measured the paramet

SUBMITTER: Ota T 

PROVIDER: S-EPMC11836082 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature