Radiomics Analysis for Predicting Malignant Potential of Intraductal Papillary Mucinous Neoplasms of the Pancreas: Comparison of CT and MRI

Abstract

To compare the performance of CT and MRI radiomics for predicting the malignant potential of intraductal papillary mucinous neoplasms (IPMNs) of the pancreas, and to investigate their value compared to the revised 2017 international consensus Fukuoka guidelines. Sixty patients with surgically confirmed IPMNs (37 malignant and 23 benign) were included. Radiomics features were extracted from arterial and venous phase images of CT and T2-weighted images of MRI, respectively. Intraclass correlation coefficients for the radiomics features were calculated to assess the interobserver reproducibility. The least absolute shrinkage and selection operator algorithm was used for feature selection. Radiomics models were constructed based on selected features with logistic regression (LR) and support vector machine (SVM). A clinical and imaging model was constructed based on independent predictors of the revised 2017 Fukuoka guidelines determined in multivariate logistic regression with forward elimination. The reproducibility of MRI radiomics features was higher than that of CT radiomics features, regardless of arterial or venous phase features (all p < 0.001). MRI radiomics models achieved improved AUCs (0.879 with LR and 0.940 with SVM, respectively), than that of CT radiomics models (0.811 with LR and 0.864 with SVM, respectively). All radiomics models provided better predictive performance than the clinical and imaging model (AUC=0.764). The MRI radiomics models with higher reproducibility radiomics features performed better than CT radiomics models for predicting the malignant potential of IPMNs. The performance of radiomics models was superior to the clinical and imaging model based on Fukuoka guidelines.