Acinar cell cystadenocarcinoma of the pancreas: Report of rare case and review of the literature
Department of Pathology, Humanitas Clinical Institute, University of Milan School of Medicine, Rozzano, Milan, Itlay. Human Pathlogy
(Impact Factor: 2.77).
01/2005; 35(12):1568-71. DOI: 10.1016/j.humpath.2004.08.004
Most exocrine pancreatic tumors are of ductal origin, whereas acinar cell adenocarcinomas are unusual (1% to 2% of all exocrine pancreatic neoplasms). We recently found a cystic adenocarcinoma of the pancreatic body whose cells had the characteristics of acinar cells, which we term acinar cell cystadenocarcinoma. Macroscopically, this tumor consists of a large multilocular cystic mass with a pseudocapsule and a spongy appearance on the cut surface. Microscopically, the cysts are lined by a single layer of cuboid/columnar cells. The cytoplasm has the characteristics of acinar cells, with eosinophilic granules in the apex and prominent nucleoli. Immunohistochemically, the cells express alpha1-antitrypsin, trypsin, and lipase in their cytoplasm, thus confirming the acinar origin of the tumor. A review of the literature revealed only 5 other cases of this tumor reported since its first description in 1981. Follow-up data are available for 4 of these; all of the affected patients had metastases at presentation or a few months later, and 2 died of the disease, at 13 and 37 months after diagnosis. Although this variant of adenocarcinoma of the pancreas is not prognostically different from the classic solid type (few patients survive more than 5 years), we believe that it is important because of its extreme rarity.
Available from: Tomoko Mitsuhashi
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ABSTRACT: Pancreatic ductal adenocarcinoma (PDA) with cystic change is classified into several types according to the features of the cysts; however, those tumors do not constitute a uniform group, and the classification is controversial. In this study, we have described a series of cystic PDAs that show distinctive and previously unreported morphologic and immunohistochemical features.
We analyzed 200 cases of PDA treated surgically at a single institution, and extracted the clinical and histopathological features of 7 tumors showing multiple large cystic (MLC) structure.
Preoperative radiographic images revealed a multilocular mass in the pancreas which was similar to intraductal papillary mucinous neoplasm or mucinous cystic neoplasm. These tumors were associated with more than 5 large cystic structures and numerous intratumoral microcysts lined by epithelial cells with various degrees of atypia. The average maximal diameter of the cysts (3.7 cm) was much larger than that of previously reported. Immunohistochemically, the cyst-lining epithelia were almost negative for mucin core protein (MUC) 1, MUC2, and MUC6, and showed only focal staining for MUC5AC. Maspin, CEA, and p53 were strongly positive, and the Ki-67 labeling index was high in both cells in solid areas and cyst-lining epithelia.
We considered the MLC structures in PDA to be a mixture of ectatic neoplastic glands and retention cysts with ductal cancerization or pancreatic intraepithelial neoplasia (PanIN); however, they might represent a new entity of cystic PDA because of the unusually large size of the dilated cysts.
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ABSTRACT: In magnetic resonance imaging (MRI), surface coils have the advantage of higher signal to noise ratio (SNR) but suffer from image inhomogeneity due to the non-uniform sensitivity profile. To remove bright spots caused by non-uniform sensitivity profiles, a gradient weighted smoothing method is discussed in this work. A partial differential equations (PDE) based model is applied for this locally adaptive smoothing. The filtered gradient of the corrupted image is used as the weight for smoothing. For accuracy evaluation, the energy of the histogram spectrum difference and the correlation of the intensity corrected image with the image acquired using the body coil are used as quantitative criteria. Clinical data collected on various MRI systems are used for evaluation of stability. The experimental results show that the proposed method is accurate and robust for intensity correction, and outperforms non-adaptive methods.
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