Imaging features of intraductal papillary mucinous neoplasms of the pancreas in multi-detector row computed tomography

Ling Tan; Ya-E. Zhao; Deng-Bin Wang; Qing-Bing Wang; Jing Hu; Ke-Min Chen; Xia-Xing Deng; Karakose, Serdar
August 2009
World Journal of Gastroenterology;8/28/2009, Vol. 15 Issue 32, p4037
Academic Journal
AIM: To retrospectively evaluate the imaging features of pancreatic intraductal papillary mucinous neoplasms (IPMNs) in multi-detector row computed tomography (MDCT). METHODS: A total of 20 patients with pathologically-confirmed intraductal papillary mucinous neoplasms (IPMNs) were included in this study. Axial MDCT images combined with CT angiography (CTA) and multiplanar volume reformations (MPVR) or curved reformations (CR) were preoperatively acquired. Two radiologists (Tan L and Wang DB) reviewed all the images in consensus using an interactive picture archiving and communication system. The disputes in readings were resolved through consultation with a third experienced radiologist (Chen KM). Finally, the findings and diagnoses were compared with the pathologic results. RESULTS: The pathological study revealed 12 malignant IPMNs and eight benign IPMNs. The diameters of the cystic lesions and main pancreatic ducts (MPDs) were significantly larger in malignant IPMNs compared with those of the benign IPMNs ( P < 0.05). The combined- type IPMNs had a higher rate of malignancy than the other two types of IPMNs (P < 0.05). Tumors with mural nodules and thick septa had a significantly higher incidence of malignancy than tumors without these features (P < 0.05). Communication of side-branch IPMNs with the MPD was present in nine cases at pathologic examination. Seven of them were identified from CTA and MPVR or CR images. From comparison with the pathological diagnosis, the sensitivity, specificity, and accuracy of MDCT in characterizing the malignancy of IPMN of the pancreas were determined to be 100%, 87.5% and 95%, respectively. CONCLUSION: MDCT with CTA and MPVR or CR techniques can elucidate the imaging features of IPMNs and help predict the malignancy of these tumors.


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