Computed Tomography-Based Radiomics Signature for the Preoperative Differentiation of Pancreatic Adenosquamous Carcinoma From Pancreatic Ductal Adenocarcinoma
Author
Ren, ShuaiZhao, Rui
Cui, Wenjing
Qiu, Wenli
Guo, Kai
Cao, Yingying
Duan, Shaofeng
Wang, Zhongqiu
Chen, Rong
Date
2020-08-25Journal
Frontiers in OncologyPublisher
Frontiers Media S.A.Type
Article
Metadata
Show full item recordAbstract
Purpose: The purpose was to assess the predictive ability of computed tomography (CT)-based radiomics signature in differential diagnosis between pancreatic adenosquamous carcinoma (PASC) and pancreatic ductal adenocarcinoma (PDAC). Materials and Methods: Eighty-one patients (63.6 ± 8.8 years old) with PDAC and 31 patients (64.7 ± 11.1 years old) with PASC who underwent preoperative CE-CT were included. A total of 792 radiomics features were extracted from the late arterial phase (n = 396) and portal venous phase (n = 396) for each case. Significantly different features were selected using Mann–Whitney U test, univariate logistic regression analysis, and minimum redundancy and maximum relevance method. A radiomics signature was constructed using random forest method, the robustness and the reliability of which was validated using 10-times leave group out cross-validation (LGOCV) method. Results: Seven radiomics features from late arterial phase images and three from portal venous phase images were finally selected. The radiomics signature performed well in differential diagnosis between PASC and PDAC, with 94.5% accuracy, 98.3% sensitivity, 90.1% specificity, 91.9% positive predictive value (PPV), and 97.8% negative predictive value (NPV). Moreover, the radiomics signature was proved to be robust and reliable using the LGOCV method, with 76.4% accuracy, 91.1% sensitivity, 70.8% specificity, 56.7% PPV, and 96.2% NPV. Conclusion: CT-based radiomics signature may serve as a promising non-invasive method in differential diagnosis between PASC and PDAC.Sponsors
Traditional Chinese Medicine Bureau of Guangdong ProvinceKeyword
adenocarcinomaadenosquamous carcinoma
computed tomography
pancreas
pancreatic neoplasms
radiomics
Identifier to cite or link to this item
http://hdl.handle.net/10713/13715ae974a485f413a2113503eed53cd6c53
10.3389/fonc.2020.01618