MRI Radiomics Combined with Clinicopathological Factors for Predicting 3-Year Overall Survival of Hepatocellular Carcinoma After Hepatectomy

Abstract

Background: A limited number of studies have examined the use of radiomics to predict 3-year overall survival (OS) after hepatectomy in patients with hepatocellular carcinoma (HCC). This study develops 3-year OS prediction models for HCC patients after liver resection using MRI radiomics and clinicopathological factors.
Materials and Methods: A retrospective analysis of 141 patients who underwent surgical resection of HCC was performed. Patients were randomized into two set: the training set (n=98) and the validation set (n=43) including the survival groups (n=111) and non-survival groups (n=30) based on 3-year survival after hepatectomy. Furthermore, x² or Fisher’s exact test, univariate and multivariate logistic regression analyses were conducted to determine independent clinicopathological risk factors associated with 3-year OS. 1688 quantitative imaging features were extracted from preoperative T2-weighted imaging (T2WI) and contrast-enhanced magnetic resonance imaging (CE-MRI) of arterial phase (AP), portal venous phases (PVP)and delay period (DP). The features were selected using the variance threshold method, the select K best method and the least absolute shrinkage and selection operator (LASSO) algorithm. By using Bernoulli Naive Bayes (BernoulliNB) and Multinomial Naive Bayes (MultinomialNB) classifiers, we constructed models based on the independent clinicopathological factors and Rad-scores. To determine the best model, receiver operating characteristics (ROC) and Delong’s test were used. Moreover, calibration curves were used to determine the calibration ability of the model, while decision curve analysis (DCA) was implemented to evaluate its clinical benefit.
Results: The fusion model showed excellent prediction precision with AUC of 0.910 and 0.846 in training and validation set and revealed significant diagnostic accuracy and value in the calibration curve and DCA analysis.
Conclusion: Nomograms based on MRI radiomics and clinicopathological factors have significant predictive value for 3-year OS after hepatectomy and can be used for risk classification.