Prediction early recurrence of hepatocellular carcinoma eligible for curative ablation using a Radiomics nomogram.

ABSTRACT:

Background

Predicting early recurrence (ER) after radical therapy for HCC patients is critical for the decision of subsequent follow-up and treatment. Radiomic features derived from the medical imaging show great potential to predict prognosis. Here we aim to develop and validate a radiomics nomogram that could predict ER after curative ablation.

Methods

Total 184 HCC patients treated from August 2007 to August 2014 were included in the study and were divided into the training (n = 129) and validation(n = 55) cohorts randomly. The endpoint was recurrence free survival (RFS). A set of 647 radiomics features were extracted from the 3 phases contrast enhanced computed tomography (CECT) images. The minimum redundancy maximum relevance algorithm (MRMRA) was used for feature selec

SUBMITTER: Yuan C 

PROVIDER: S-EPMC6485136 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature