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dc.contributor.authorRen, S.
dc.contributor.authorZhang, J.
dc.contributor.authorChen, R.
dc.date.accessioned2019-12-04T15:55:05Z
dc.date.available2019-12-04T15:55:05Z
dc.date.issued2019
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85075370331&doi=10.3389%2ffonc.2019.01171&partnerID=40&md5=334b25657a87ec1d2a5748c27a9af572
dc.identifier.urihttp://hdl.handle.net/10713/11469
dc.description.abstractPurpose: To investigate the potential of computed tomography (CT) imaging features and texture analysis to differentiate between mass-forming pancreatitis (MFP) and pancreatic ductal adenocarcinoma (PDAC). Materials and Methods: Thirty patients with pathologically proved MFP and 79 patients with PDAC were included in this study. Clinical data and CT imaging features of the two lesions were evaluated. Texture features were extracted from arterial and portal phase CT images using commercially available software (AnalysisKit). Multivariate logistic regression analyses were used to identify relevant CT imaging and texture parameters to discriminate MFP from PDAC. Receiver operating characteristic curves were performed to determine the diagnostic performance of predictions. Results: MFP showed a larger size compared to PDAC (p = 0.009). Cystic degeneration, pancreatic ductal dilatation, vascular invasion, and pancreatic sinistral portal hypertension were more frequent and duct penetrating sign was less frequent in PDAC compared to MFP. Arterial CT attenuation, arterial, and portal enhancement ratios of MFP were higher than PDAC (p < 0.05). In multivariate analysis, arterial CT attenuation and pancreatic duct penetrating sign were independent predictors. Texture features in arterial phase including SurfaceArea, Percentile40, InverseDifferenceMoment_angle90_offset4, LongRunEmphasis_angle45_offset4, and uniformity were independent predictors. Texture features in portal phase including LongRunEmphasis_angle135_offset7, VoxelValueSum, LongRunEmphasis_angle135_offset4, and GLCMEntropy_angle45_offset1 were independent predictors. Areas under the curve of imaging feature-based, texture feature-based in arterial and portal phases, and the combined models were 0.84, 0.96, 0.93, and 0.98, respectively. Conclusions: CT texture analysis demonstrates great potential to differentiate MFP from PDAC. Copyright 2019 The Authors.en_US
dc.description.sponsorshipThis study was funded by Jiangsu Provincial Key Research and Development Program (BE2017772), Administration of Traditional Chinese Medicine of Jiangsu Province (ZD201907), and the National Natural Science Foundation of China (81771899).en_US
dc.description.urihttps://doi.org/10.3389/fonc.2019.01171en_US
dc.language.isoen_USen_US
dc.publisherFrontiers Media S.A.en_US
dc.relation.ispartofFrontiers in Oncology
dc.subjectchronic pancreatitisen_US
dc.subjectcomputed tomographyen_US
dc.subjectmachine learningen_US
dc.subjectpancreatic ductal adenocarcinomaen_US
dc.subjecttexture analysisen_US
dc.titleEvaluation of Texture Analysis for the Differential Diagnosis of Mass-Forming Pancreatitis From Pancreatic Ductal Adenocarcinoma on Contrast-Enhanced CT Imagesen_US
dc.typeArticleen_US
dc.identifier.doi10.3389/fonc.2019.01171


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