Differential characteristics of multislice spiral computed tomography between pancreatic solid pseudopapillary neoplasm and hypovascular pancreatic neuroendocrine tumor
10.3760/cma.j.cn311367-20211021-00569
- VernacularTitle:胰腺实性假乳头状肿瘤与乏血供胰腺神经内分泌瘤的多层螺旋计算机断层扫描鉴别特征
- Author:
Zhengteng LI
1
;
Peiyu ZHANG
;
Yuan JI
;
Mengsu ZENG
;
Mingliang WANG
Author Information
1. 复旦大学附属中山医院放射科，上海 200032
- Keywords:
Pancreas;
Solid pseudopaillary neoplasm;
Neuroendocrine tumors;
Tomography, X-ray computed
- From:
Chinese Journal of Digestion
2022;42(7):452-457
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the value of multislice spiral computed tomography (MSCT) features in the differential diagnosis of pancreatic solid pseudopapillary neoplasm (pSPN) and hypovascular pancreatic neuroendocrine tumor (hypo-PNET).Methods:From January 2016 to January 2021, at Zhongshan Hospital of Fudan University, the clinical information, pathological results and imaging data of 81 patients with pSPN and 40 patients with hypo-PNET confirmed by surgical pathology were retrospectively analyzed. The tumor location, shape, growth mode, relationship between the long axis of the lesion and pancreas, boundary, whether with calcification, floating cloud sign, ring enhancement, sausage-like enhancement, intratumoral vascular sign, pancreatic duct dilatation, distal pancreatic atrophy, intratumoral cystic change, cystic-solid ratio of tumor, the maximum diameter of the lesion, the plain and enhanced computed tomography (CT) values of the solid part of the tumor of pSPN patients and hypo-PNET patients were compared and analyzed. Chi-square test, independent sample t test and Mann-Whitney U test were used for statistical analysis. The variables with statistical significance in univariate analysis were included in the binary logistic regression model to screen the independent predictors of pSPN and hypo-PNET, and the receiver operating characteristic curve (ROC) was used to evaluate the diagnostic efficiency of MSCT characteristics in the differential diagnosis of pSPN and hypo-PNET. Results:Compared with hypo-PNET patients, most of pSPN patients were female (71.6%, 58/81 vs. 45.0%, 18/40), younger (36.0 years old (27.0 years old, 46.0 years old) vs. 56.5 years old (48.2 years old, 63.7 years old), the tumors were mostly round or elliptical (76.5%, 62/81 vs. 55.0%, 22/40), most with clear boundaries (70.4%, 57/81 vs. 40.0%, 16/40), with more intratumoral calcification (53.1%, 43/81 vs. 20.0%, 8/40), with more floating cloud sign (65.4%, 53/81 vs. 35.0%, 14/40), more without intratumoral vascular sign (77.8%, 63/81 vs. 32.5%, 13/40), more without pancreatic duct dilatation (79.0%, 64/81 vs. 55.0%, 22/40), more with mixed solid and cystic mass (38.3%, 31/81 vs. 22.5%, 9/40), with longer maximum diameter of tumor (4.0 cm (3.0 cm, 5.6 cm) vs. 3.3 cm (2.6 cm, 4.2 cm), with lower enhanced CT values in the arterial and venous phases ((54.7±13.1) HU vs. (68.2±15.0) HU and (65.9±16.0) HU vs. (79.2±14.2) HU), and the differences were all statistically significant ( χ2=8.11; Z=-6.24; χ2=5.85, 10.32, 12.02, 10.03, 23.50, 7.51, 7.72; Z=-2.53; t=-5.08 and -4.46, all P<0.05). The results of binary logistic regression model indicated that the independent predictive factors for the diagnosis of pSPN and hypo-PNET included age ( OR=0.874, 95% confidence interval (95% CI) 0.827 to 0.923, P<0.001), calcification ( OR=5.412, 95% CI 1.428 to 20.506, P=0.013), intratumoral vascular sign ( OR=0.212, 95% CI 0.055 to 0.817, P=0.024), CT value in the arterial phase ( OR=0.943, 95% CI 0.899 to 0.988, P=0.015). For the combination diagnostic model based on clinical features and MSCT characteristics, area under ROC was 0.944 (95% CI 0.905 to 0.990), sensitivity was 87.7% and specificity was 92.5% ( P<0.001). The results of ROC analysis of the independent predictive factors and combined diagnostic model showed that the areas under the curve (95% CI) of the age, calcification, intratumoral vascular sign, CT value in the arterial phase and the combined diagnostic model was 0.665 (0.565 to 0.765), 0.726 (0.627 to 0.826), 0.850 (0.775 to 0.924), 0.757 (0.660 to 0.853), and 0.944 (0.905 to 0.983), respectively, and the diagnostic efficacy of the combined diagnostic model was higher ( P<0.001). Conclusion:MSCT features such as intratumoral calcification, intratumoral vascular sign, tumor density in the arterial phase combined with age can be used in the differential diagnosis of pSPN and hypo-PNET.
