MRI-based radiomics model for preoperative prediction of 5-year survival in patients with hepatocellular carcinoma

Xiao-Hang Wang,Zhi Wang,Zhao-Hai Wang,Chong-Ming Zhan,Wei-Hu Wang,Liu-Hua Long,Xiang-Gao Zhu,Yong Cui,Angela Y Jia,Hong-Zhi Wang

doi:10.1038/s41416-019-0706-0

Abstract

BackgroundRecurrence is the major cause of mortality in patients with resected HCC. However, without a standard approach to evaluate prognosis, it is difficult to select candidates for additional therapy.MethodsA total of 201 patients with HCC who were followed up for at least 5 years after curative hepatectomy were enrolled in this retrospective, multicentre study. A total of 3144 radiomics features were extracted from preoperative MRI. The random forest method was used for radiomics signature building, and five-fold cross-validation was applied. A radiomics model incorporating the radiomics signature and clinical risk factors was developed.ResultsPatients were divided into survivor (n = 97) and non-survivor (n = 104) groups based on the 5-year survival after surgery. The 30 most survival-related radiomics features were selected for the radiomics signature. Preoperative AFP and AST were integrated into the model as independent clinical risk factors. The model demonstrated good calibration and satisfactory discrimination, with a mean AUC of 0.9804 and 0.7578 in the training and validation sets, respectively.ConclusionsThis radiomics model is a valid method to predict 5-year survival in patients with HCC and may be used to identify patients for clinical trials of perioperative therapies and for additional surveillance.

Highlights

Recurrence is the major cause of mortality in patients with resected Hepatocellular carcinoma (HCC)
Clinical characteristics A total of 201 patients with HCC were analysed in this study
The model integrates the magnetic resonance imaging (MRI) radiomics signature with preoperative AFP and AST, all of which can be obtained, to offer prognostic information on long-term survival, which is a key concern for patients

Summary

Introduction

Recurrence is the major cause of mortality in patients with resected HCC. without a standard approach to evaluate prognosis, it is difficult to select candidates for additional therapy. CONCLUSIONS: This radiomics model is a valid method to predict 5-year survival in patients with HCC and may be used to identify patients for clinical trials of perioperative therapies and for additional surveillance. Hepatectomy is the primary curative treatment for patients with early-stage HCC with well-preserved liver function.[3] tumour recurrence remains the major cause of death after surgery, with the postoperative 5-year recurrence rate approaching 70%.4. Some retrospective and prospective studies have suggested that adjuvant transarterial chemoembolisation could delay recurrence and improve survival in high-risk patients with HCC.[6,7] Retrospective studies from our own group indicated that postoperative intensity-modulated radiotherapy may be a favourable option in patients with HCC with narrow-margin resection or microscopic vascular invasion.[8,9] Prognosis classification is essential for individualised treatment; no generally accepted approach for risk stratification in HCC is currently available

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