Differential diagnosis of pancreatic cystic masses with the quantitative analysis of spectral CT imaging: Initial results
Authors
Abstract:
Background: To retrospectively evaluate whether quantitative information derived from spectral imaging can improve the differential diagnosis of pancreatic cystic masses including pancreatic solid pseudopapillary epithelial neoplasms (SPENs), mucin- producing cysts and pseudocysts. Materials and Methods: From June 2015 to October 2017, 56 patients (22 pseudocysts, 18 mucin-producing cysts and 16 SPENs) who underwent spectral CT imaging were included in the study. Conventional characteristics and quantitative parameters were compared among the three groups. The receiver-operating characteristic curve was used to evaluate the diagnostic performance of parameters which had statistical significance among the three groups. Two radiologists diagnosed the pancreatic cystic masses blinded in consensus, without and with the information of the statistical analysis. Results: The conventional characteristics including age, contour, nodule and septum were the independent factors correlated with category. The quantitative parameters including effective-Z, slope of energy spectral curve (slope), iodine (water) concentration and calcium (water) concentration demonstrated significantly lower values in pseudocysts group when compared with mucin-producing cysts and SPENs groups. Slope in portal venous phase, threshold of less than 0.50, was the best discriminator between pseudocysts group and mucin-producing cysts group, with a sensitivity of 95.5%, and a specificity of 88.9%. The best quantitative parameter for differentiate SPENs from mucin-producing cysts was the iodine (water) concentration in portal venous phase. With the knowledge of statistical analysis, the accuracy of the two radiologists increased from 78.5% to 90.9%. Conclusion: Multi-parametric analysis with the combination of quantitative parameters derived from CT spectral imaging could improve the diagnostic performance.
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Journal title
volume 19 issue 1
pages 155- 165
publication date 2021-01
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