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Computed Tomography-Based Radiomics Signature for the Preoperative Differentiation of Pancreatic Adenosquamous Carcinoma From Pancreatic Ductal AdenocarcinomaPurpose: 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.
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Contrast-enhanced endoscopic ultrasound for differentially diagnosing autoimmune pancreatitis and pancreatic cancerBackground/Aims: Differentially diagnosing focal-type autoimmune pancreatitis (f-AIP) and pancreatic cancer (PC) is challenging. Contrast-enhanced harmonic endoscopic ultrasound (CEH-EUS) may provide information for differentiating pancreatic masses. In this study, we evaluated the usefulness of CEH-EUS in differentiating f-AIP from PC. Methods: Data were collected prospectively and analyzed on patients who underwent CEH-EUS between May 2014 and May 2015. Eighty consecutive patients were diagnosed with f-AIP or PC. PC and f-AIP were compared for enhancement intensity, contrast agent distribution, and internal vasculature. Results: The study group comprised 53 PC patients and 27 f-AIP patients (17 with type-1 AIP [15 definite and two probable], two with probable type-2 AIP, and eight with AIP, not otherwise specified). Hyper- to iso-enhancement in the arterial phase (f-AIP, 89% vs PC, 13%; p<0.05), homogeneous contrast agent distribution (f-AIP, 81% vs PC, 17%; p<0.05), and absent irregular internal vessels (f-AIP, 85% vs PC, 30%; p<0.05) were observed more frequently in the f-AIP group. The combination of CEH-EUS and enhancement intensity, absent irregular internal vessels improved the specificity (94%) in differentiating f-AIP from PC. Conclusions: CEH-EUS may be a useful noninvasive modality for differentially diagnosing f-AIP and PC. Combined CEH-EUS findings could improve the specificity of CEH-EUS in differentiating f-AIP from PC. Copyright 2018 Editorial Office of Gut and Liver. All rights reserved.
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Differentiation of chronic mass-forming pancreatitis from pancreatic ductal adenocarcinoma using contrast-enhanced computed tomographyPurpose: Both chronic mass-forming pancreatitis (CMFP) and pancreatic ductal adenocarcinoma (PDAC) are focal pancreatic lesions and share very similar clinical symptoms and imaging performance. There is great clinical value in preoperative differentiation of those two lesions. The purpose of this study was to investigate the value of computed tomography (CT) features in discriminating CMFP from PDAC. Patients and methods: Forty-seven patients with pathologically confirmed PDAC and 21 patients with CMFP were included in this study. Demographic and CT features, including tumor location, size, margin, pancreatic or bile duct dilatation, vascular invasion, cystic necrosis, pancreatic atrophy, calcification, and tumor contrast enhancement, were retrospectively analyzed and compared. Multivariate logistic regression analyses were adopted to identify relevant CT imaging features to discriminate CMFP from PDAC. Results: There were significant differences between CMFP and PDAC with respect to main pancreatic duct dilatation, vascular invasion, cystic necrosis, pancreatic atrophy, calcification, and tumor contrast enhancement. Delayed contrast enhancement (>70.5 Hounsfield units) showed high sensitivity and specificity of 84.2% and 84.7%. The areas under the curve (AUCs) of the predicting models based on qualitative and quantitative variables were 0.770 (95% CI: 0.660–0.880) and 0.943 (95% CI: 0.888–0.999), respectively. When all significant variables were used in combination to build a predicting model, the AUC was 0.969 (95% CI: 0.930–1.000) with 84.2% sensitivity and 94.7% specificity. Conclusion: Main pancreatic duct dilatation, vascular invasion, cystic necrosis, pancreatic atrophy, calcification, tumor size, and tumor contrast enhancement were shown to be useful CT imaging features in discriminating CMFP from PDAC. Copyright 2019 Ren et al.