Abstract
BACKGROUND AND AIM: Intraductal papillary mucinous neoplasms (IPMNs) have a wide pathologic spectrum and it is difficult to differentiate malignant from benign tumors. The aim of this study was to identify predictors of malignancy using contrast-enhanced endoscopic ultrasound (CE-EUS). SUBJECTS AND METHODS: In our institute, main duct type and mixed type IPMNs, branch duct type IPMNs with mural nodules, and IPMNs with coexistent invasive ductal cancer were indications for surgery. Eighty-seven IPMNs (14 main duct, 25 mixed, and 48 branch duct type) were resected and CE-EUS findings were compared with pathologic findings. Twelve clinicopathological variables and CE-EUS morphologic findings were assessed. Mural nodules defined as blood flow supplied protrusions were classified into 4 types: type I: low papillary nodule, type II: polypoid nodule, type III: papillary nodule, and type IV: invasive nodule. RESULTS: Forty-two, 26, 16, and 3 were pathologically diagnosed as adenoma, noninvasive carcinoma, invasive IPMNs, and coexistent invasive ductal cancer, respectively. Multivariable logistic regression analysis showed that types III/IV mural nodule (odds ratio =10.8; 95% confidential intervals =2.75-56.1) and symptomatic IPMNs (odds ratio =4.31; 95% confidential intervals =1.37-14.7) were significant for malignancy. For mural nodule diameter, invasive IPMNs were significantly larger, but types III and IV mural nodules were more frequently associated with malignancy, particularly invasive cancer, at 88.9% and 91.7%, respectively. The diagnosis of IPMNs with types III or IV mural nodule as malignant resulted in a sensitivity of 60%, specificity of 92.9%, and accuracy of 75.9%. CONCLUSIONS: In conclusion, new morphologic criteria were useful to identify the malignant potentials of IPMNs.
| Original language | English |
|---|---|
| Pages (from-to) | 628-634 |
| Number of pages | 7 |
| Journal | Annals of Surgery |
| Volume | 249 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 04-2009 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Surgery
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