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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.
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Evaluation of Texture Analysis for the Differential Diagnosis of Mass-Forming Pancreatitis From Pancreatic Ductal Adenocarcinoma on Contrast-Enhanced CT ImagesPurpose: 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.