Abstract
ObjectiveTo establish a diagnostic model by combining imaging features with enhanced CT texture analysis to differentiate pancreatic serous cystadenomas (SCNs) from pancreatic mucinous cystadenomas (MCNs).Materials and MethodsFifty-seven and 43 patients with pathology-confirmed SCNs and MCNs, respectively, from one center were analyzed and divided into a training cohort (n = 72) and an internal validation cohort (n = 28). An external validation cohort (n = 28) from another center was allocated. Demographic and radiological information were collected. The least absolute shrinkage and selection operator (LASSO) and recursive feature elimination linear support vector machine (RFE_LinearSVC) were implemented to select significant features. Multivariable logistic regression algorithms were conducted for model construction. Receiver operating characteristic (ROC) curves for the models were evaluated, and their prediction efficiency was quantified by the area under the curve (AUC), 95% confidence interval (95% CI), sensitivity and specificity.ResultsFollowing multivariable logistic regression analysis, the AUC was 0.932 and 0.887, the sensitivity was 87.5% and 90%, and the specificity was 82.4% and 84.6% with the training and validation cohorts, respectively, for the model combining radiological features and CT texture features. For the model based on radiological features alone, the AUC was 0.84 and 0.91, the sensitivity was 75% and 66.7%, and the specificity was 82.4% and 77% with the training and validation cohorts, respectively.ConclusionThis study showed that a logistic model combining radiological features and CT texture features is more effective in distinguishing SCNs from MCNs of the pancreas than a model based on radiological features alone.
Highlights
Pancreatic serous cystic neoplasms (SCNs) originate from cuboidal epithelial cells full of glycogen-rich components, and are the only benign tumors of the pancreas, accounting for 10-16% of pancreatic cystic neoplasms [1, 2]
As there is a chanceful spectrum of performances for Serous cystadenomas (SCNs) in radiology, up to 60% of SCN patients performed surgery with uncertain diagnosis [5]; atypical SCNs may misdiagnosed as mucinous cystic neoplasms (MCNs) or intraductal papillary mucinous neoplasms (IPMNs), which have the potential for malignancy, so misdiagnosis can lead to unnecessary surgery [6–8]
SCNs were more frequently observed among older women than MCNs
Summary
Pancreatic serous cystic neoplasms (SCNs) originate from cuboidal epithelial cells full of glycogen-rich components, and are the only benign tumors of the pancreas, accounting for 10-16% of pancreatic cystic neoplasms [1, 2]. As there is a chanceful spectrum of performances for SCNs in radiology, up to 60% of SCN patients performed surgery with uncertain diagnosis [5]; atypical SCNs may misdiagnosed as mucinous cystic neoplasms (MCNs) or intraductal papillary mucinous neoplasms (IPMNs), which have the potential for malignancy, so misdiagnosis can lead to unnecessary surgery [6–8]. There is no consensus regarding the management of SCNs in terms offollow-up and surgery [9, 10]. Initial tumor size and growth rate are always taken into consideration when determining whether surgery should be performed [11–13]. SCNs are very safe and develop an indolent nature after long-term follow-up, while MCNs should be treated with surgery once a diagnosis is made [14]
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