Prediction of 3-year recurrence rate of hepatocellular carcinoma after resection based on contrast-enhanced CT: a single-centre study.

ABSTRACT:

Objective

We present a new artificial intelligence-powered method to predict 3-year hepatocellular carcinoma (HCC) recurrence by analysing the radiomic profile of contrast-enhanced CT (CECT) images that was validated in patient cohorts.

Methods

This retrospective cohort study of 224 HCC patients with follow-up for at least 3 years was performed at a single centre from 2012 to 2019. Two groups of radiomic signatures were extracted from the arterial and portal venous phases of pre-operative CECT. Then, the radiological model (RM), deep learning-based radiomics model (DLRM), and clinical & deep learning-based radiomics model (CDLRM) were established and validated in the area under curve (AUC), calibration curve, and clinical decision curve.

Results

Comparison of the clin

SUBMITTER: Lv C 

PROVIDER: S-EPMC10161905 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature