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| Correlation Analysis of Imaging Manifestations and Pathological Features of Pancreatoblastoma in Children |
| PENG Yaozong, YIN Yiwei, LI Chunwang, et al |
| Hunan Children's Hospital,Changsha Hunan 410007 |
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Abstract 【Objective】 To explore the correlation between imaging manifestations and pathological features of pancreatoblastoma in children, and to improve the diagnostic accuracy of this disease.【Methods】 The clinical data of 9 children pathologically confirmed as pancreatoblastoma after surgery were retrospectively analyzed. The CT and MRI imaging data of the children were detailedly analyzed and compared with the pathological results. 【Results】 The tumors occurred in the pancreatic head region in 3 cases, in the pancreatic body region in 5 cases, and in both the pancreatic body and tail regions in 1 case. CT showed mixed-density masses with lobulated shapes; necrosis and calcification were observed in all 9 cases. The masses showed heterogeneous mild enhancement in the arterial phase of enhanced scan, and progressive enhancement in 6 cases. On MRI, the masses presented low signal or intermediate signal intensity on T1WI and isointense or hyperintense signal intensity on T2WI, with heterogeneous enhancement after contrast administration; main pancreatic duct dilatation was found in 1 case. Tumors with clear boundaries on imaging usually had relatively complete fibrous capsules on histopathological sections, while those with blurred boundaries often indicated that tumor cells infiltrated into the surrounding tissues with incomplete or absent capsules. The enhancement pattern of tumors on imaging was closely related to the vascular distribution of tumors on histopathological sections. 【Conclusion】 Pancreatoblastoma has certain characteristic manifestations on different imaging examinations and is closely correlated with pathological changes. Imaging examinations play an important role in the diagnosis, differential diagnosis and preoperative evaluation of pancreatoblastoma in children. Combining with pathological features can further improve the accuracy and reliability of diagnosis, providing a strong basis for formulating clinical treatment plans.
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Received: 03 March 2025
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2025, Vol. 42 
