Abstract
Purpose To evaluate multiparametric analysis in differential diagnosis between pancreatic serous cystic neoplasms (SCNs) and mucinous cystic neoplasms (MCNs) as well as the differentiation of the benign and malignant MCNs with 18F-FDG (18-fluorodeoxyglucose) PET/CT (positron emission tomography). Methods Forty patients with total of 41 lesions (SCNs: 27/41; MCNs: 14/41), who were preoperatively examined with 18F-FDG PET/CT, were retrospectively analyzed. Multiple quantitative parameters using conventional and texture features were included. The combined model was established with complementary PET/MR parameters. The differential diagnostic efficacy of each independent parameter and the combined model were evaluated with receiver operating characteristic (ROC) analysis. Integrated discriminatory improvement (IDI) and net reclassification improvement (NRI) were used to evaluate improvement of diagnostic efficacy by using combination of multiple parameters. Results Among all independent parameters, the percentile 5th (0.88 ± 0.38 vs 0.47 ± 0.23, P < 0.001) showed the highest discriminative diagnostic value. The combination of multiple parameters can improve the differential diagnostic efficacy of SCNs and MCNs (sensitivity = 71.4%, specificity = 77.8%, and AUC = 0.788), and the addition of texture parameters to the conventional parameters allowed a significant reclassification with IDI = 0.236 (95% CI: 0.095–0.377) and categorical NRI = 0.434 (95% CI: 0.030–0.838). SURmax (tumor to normal pancreas ratio, T/P) and SURmax (tumor to aorta ratio, T/A) both showed the highest discriminative diagnostic value (sensitivity = 100.0%, specificity = 70.0%, AUC = 0.900, and Youden index = 0.700) in the differential diagnosis of benign and malignant MCNs, with the cutoff values of 0.84 and 0.90, respectively. ConclusionCombination of multiple parameters using 18F-FDG PET/CT could further improve differentiation between pancreatic SCNs and MCNs. SURmax (T/P) and SURmax (T/A) could improve differential diagnosis of benign and malignant MCNs.
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