Published online Mar 21, 2020. doi: 10.3748/wjg.v26.i11.1208
Peer-review started: October 12, 2019
First decision: January 13, 2020
Revised: February 18, 2020
Accepted: February 21, 2020
Article in press: February 21, 2020
Published online: March 21, 2020
Postoperative liver failure is the most serious complication for patients with hepatocellular carcinoma (HCC) after major hepatectomy. There are many methods for predicting postoperative liver failure after hepatectomy but not sufficiently accurate enough. This paper provides a radiomics model based on gadoxetic acid-enhanced magnetic resonance imaging (MRI), serve as a reliable predictive tool to reduce postoperative liver failure and mortality in cirrhotic patients with HCC after major hepatectomy.
In order to determine a new method to predict the postoperative liver failure after major hepatectomy and our radiomics model showed a favorable performance. However, the results obtained in this study need to be further verified in the population, and validation cohort need to be allocated.
The objective of this study is to determine the performance for predicting liver failure of a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging. The finding provides important information for medical decision making when surgery is required for a patient with HCC.
The significant clinical variables were chosen and the radiomics signature was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced MRI in 101 patients with HCC from Sun Yat-Sen Memorial Hospital. The integrated radiomics-based model was presented as a radiomics nomogram. The performances for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve and decision curve analysis.
This study found that five radiomic features from hepatobiliary phase images were selected, and a radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure. The performance of radiomics model need to be further validated.
The liver failure is very severe after liver resection. In this study, a radiomics signature based on preoperative gadoxetic acid–enhanced MRI was developed, which showed favorable performance in predicting liver failure in cirrhotic patients with HCC after major liver resection.
This study confirmed the performance for predicting of our radiomics model. On this basis, future studies will further expand the sample size, and add the validation cohort.