Int J Med Sci 2021; 18(11):2276-2284. doi:10.7150/ijms.55510

Research Paper

Radiomics Signature: A potential biomarker for the prediction of survival in Advanced Hepatocellular Carcinoma

Lingli Li1,2*, Xuefeng Kan1,2*, Yongjun Zhao3, Bo Liang1,2, Tianhe Ye1,2, Lian Yang1,2✉, Chuansheng Zheng1,2✉

1. Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
2. Hubei Key Laboratory of Molecular Imaging, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
3. Wuhan Zhikai Technology, Wuhan 430074, China.
*These authors contributed equally to this work.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
Citation:
Li L, Kan X, Zhao Y, Liang B, Ye T, Yang L, Zheng C. Radiomics Signature: A potential biomarker for the prediction of survival in Advanced Hepatocellular Carcinoma. Int J Med Sci 2021; 18(11):2276-2284. doi:10.7150/ijms.55510. Available from https://www.medsci.org/v18p2276.htm

File import instruction

Abstract

Objectives: To develop and validate radiomics nomograms for the pretreatment predictions of overall survival (OS) and time to progression (TTP) in the patients with advanced hepatocellular carcinoma (HCC) treated with apatinib plus transarterial chemoembolization (TACE), and to assess the incremental value of the clinical-radiomics nomograms for estimating individual OS and TTP.

Methods: A total of 60 patients with advanced HCC (BCLC stage C) treated with apatinib plus TACE were divided into a training set (n=48) and a validation set (n=12). The predictors identified from the clinical variables and the radiomics signature constructed from the computed tomography images, such as ɑ-fetoprotein level (AFP), formfactor, the grey level co-occurrence matrix, the gray level size zone matrix, and the gray level run-length matrix, were used to build the clinical-radiomics nomograms and the radiomics nomograms for the prediction of OS and TTP.

Results: Apatinib plus TACE benefited the patients with advanced HCC, with a 579-day median OS and a 270-day median TTP. The nomograms were built with the radiomics signature and AFP, and achieved favorable prediction efficacy with acceptable calibration curves. Decision curve analyses demonstrated that the clinical-radiomics nomograms outperformed the radiomics nomograms for the predictions of OS and TTP.

Conclusions: Apatinib plus TACE may improve OS and prolonged TTP in the patients with advanced HCC. The clinical-radiomics nomograms, a noninvasive pretreatment prediction tool that incorporate radiomics signature and AFP, demonstrated good prediction accuracy for OS and TTP in these patients. These results indicate that the clinical-radiomics nomograms may provide novel insight for precise personalized medicine approaches in the patients with advanced HCC.

Keywords: radiomics, nomogram, hepatocellular carcinoma, survival