MRI Feature-Based Nomogram Model for Discrimination Between Non-Hypervascular Pancreatic Neuroendocrine Tumors and Pancreatic Ductal Adenocarcinomas - Xu, Jiake; Yang, Jie; Feng, Ye; Zhang, Jie; Zhang, Yuqiao; Chang, Sha; Jin, Jingqiang; Du, Xia (Frontiers in Oncology, 2022)
To investigate whether magnetic resonance imaging (MRI) features could differentiate non-hypervascular pancreatic neuroendocrine tumors (PNETs) from pancreatic ductal adenocarcinomas (PDACs). In this study,131 patients with surgically and pathologically proved non-hypervascular PNETs (n = 44) or PDACs (n = 87) were enrolled. Two radiologists independently analyzed MRI imaging findings and clinical features. Relevant features in differentiating non-hypervascular PNETs from PDACs was identified via univariate and multivariate logistic regression models. The MRI features-based nomogram was constructed based on multivariable logistic analysis and the reliability of the constructed nomogram was further validated. The results showed that the tumor margin (P = 0.012; OR, 6.622; 95% CI 1.510, 29.028), MPD dilation (P = 0. 047, OR, 4.309; 95% CI: 1.019, 18.227) and signal on portal phase (P < 0.001, OR, 53.486; 95% CI: 10.690, 267.618) were independent discriminative MRI features between non-hypervascular PNETs and PDACs. The discriminative performance of the developed nomogram was optimized compared with single imaging features. The calibration curve, C-index and DCA validated the superior practicality and usefulness of the MRI-based nomogram. In conclusion, the radiologically discriminative model integrating various MRI features could be preoperatively and easily utilized to differentiate non-hypervascular PNETs from PDACs.