CT Radiomics Features in Differentiation of Focal-Type Autoimmune Pancreatitis from Pancreatic Ductal Adenocarcinoma: A Propensity Score Analysis
Jing Li, Fang Liu, Xu Fang, Kai Cao, Yinghao Meng, Hao Zhang, Jieyu Yu, Xiaochen Feng, Qi Li, Yanfang Liu, Li Wang, Hui Jiang, Chengwei Shao, Jianping Lu, Yun Bian
Acad Radiol . 2021 Jun 6;S1076-6332(21)00209-9. doi: 10.1016/j.acra.2021.04.014. Online ahead of print.
Purpose: To evaluate the diagnostic performance of the radiomics score (rad-score) for differentiating focal-type autoimmune pancreatitis (fAIP) from pancreatic ductal adenocarcinoma (PDAC).
Methods: This retrospective review included 42 consecutive patients with fAIP diagnosed according to the International Consensus Diagnostic Criteria between January 2011 and December 2018. Furthermore, 334 consecutive patients with PDAC confirmed by pathology were also reviewed during the same period. Patients with PDAC and fAIP were matched via propensity score matching (PSM). All patients underwent multidetector computed tomography (MDCT). For each patient, 1409 radiomics features of the portal phase were extracted and reduced using the least absolute shrinkage and selection operator (LASSO) logistic regression algorithm. The portal rad-score performance was assessed based on its discriminative ability.
Results: After PSM, we matched 55 patients with PDAC to 42 patients with fAIP, based on clinical and CT characteristics (e.g., patient age, sex, body mass index, location, size, enhanced mode). A rad-score for discriminating fAIP from PDAC, which contained four CT derived radiomic features, was developed (area under the curve = 0.97). The sensitivity, specificity, and accuracy of the radiomics model were 95.24%, 92.73% and 0.94, respectively.
Conclusion: The portal rad-score can accurately and noninvasively differentiate fAIP from PDAC.
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