Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Pancreatology. 2024 Nov;24(7):1152-1159. doi: 10.1016/j.pan.2024.09.014. Epub 2024 Sep 14.
To investigate whether computed tomography features can differentiate pancreatoblastoma (PB) from solid pseudopapillary tumor (SPN) in children.
Clinical and imaging data of 18 cases of PB and 61 cases of SPN confirmed by surgery or biopsy were retrospectively analyzed. All enrolled patients underwent 3 phases (non-contrast, arterial, and portal venous phases) of CT scanning. Qualitative CT analysis (location, margin, solid/cystic component proportion, calcification, hemorrhage, peritumoral vascularity, bile duct dilatation, pancreatic duct dilatation, pancreatic atrophy, vascular invasion, peripancreatic invasion, and distant metastases) and quantitative analysis (maximum tumor diameter, interface between tumor and parenchyma [delta], arterial enhancement ratio [AER], and portal enhancement ratio [PER]) were performed. The general CT morphologic features, age and tumor markers were compared also compared between the groups. Univariate analysis and the F test were conducted to identify features of PB. Then logistic Regression classifier was trained using the top five features with the highest F-value. Moreover, we used 5-fold cross-validation techniques for the validation of our model.
PB exhibited a significantly higher frequency of location in the body/tail, larger tumor size, poorly defined margins, calcification, peritumoral vascularity, pancreatic atrophy, and less hemorrhage. In addition, PB had higher AER, PER and lower delta relative to SPN (p < 0.05). PB presented a younger age and higher levels of AFP. Results of the F test indicated that AFP, AER, Age, calcification and pancreatic atrophy were the top five features included in the model that could differentiate pediatric PB from SPN. The combined model of CT and clinical features performed well in differentiating PB from SPN, with an AUC of 0.981 in the training cohort and 0.953 in the validation cohort.
AFP, AER, age, calcification and pancreatic atrophy are robust CT and clinical features for differentiating pediatric PB from SPN. A combination of qualitative and quantitative CT features may provide good diagnostic accuracy in differentiating PB from SPN in children.
本研究旨在探讨 CT 特征能否区分儿童胰腺母细胞瘤（PB）和实性假乳头状肿瘤（SPN）。
回顾性分析了 18 例 PB 和 61 例经手术或活检证实的 SPN 患儿的临床和影像学资料。所有患者均行 CT 三期扫描（平扫、动脉期和门静脉期）。定性 CT 分析（位置、边缘、实性/囊性成分比例、钙化、出血、肿瘤周围血管、胆管扩张、胰管扩张、胰腺萎缩、血管侵犯、胰周侵犯和远处转移）和定量分析（最大肿瘤直径、肿瘤与实质界面[Δ]、动脉增强比[AER]和门静脉增强比[PER]）。比较两组间一般 CT 形态特征、年龄和肿瘤标志物。采用单因素分析和 F 检验对 PB 特征进行分析，然后使用 F 值最高的前 5 个特征训练逻辑回归分类器。此外，我们还使用 5 折交叉验证技术对模型进行验证。
PB 位于体尾部、肿瘤较大、边缘不清、钙化、肿瘤周围血管、胰腺萎缩和出血较少的比例明显更高。此外，PB 的 AER、PER 较高，Δ值较低（p<0.05）。PB 发病年龄较小，AFP 水平较高。F 检验结果表明，AFP、AER、年龄、钙化和胰腺萎缩是纳入模型中可区分儿童 PB 和 SPN 的前 5 个特征。CT 和临床特征联合模型在区分 PB 和 SPN 方面表现良好，在训练队列中的 AUC 为 0.981，在验证队列中的 AUC 为 0.953。
AFP、AER、年龄、钙化和胰腺萎缩是区分儿童 PB 和 SPN 的可靠 CT 和临床特征。定性和定量 CT 特征的联合应用可能为儿童 PB 和 SPN 的鉴别诊断提供较高的准确性。
