Literature DB >> 18043368

Hepatoid adenocarcinoma: computed tomographic imaging findings with histopathologic correlation in 6 cases.

Zhiyuan Wu1, Manavendra Upadhyaya, Hui Zhu, Zhongwei Qiao, Kemin Chen, Fei Miao.   

Abstract

OBJECTIVE: Hepatoid adenocarcinoma (HAC) is a special type of primary tumor with aberrant hepatocellular differentiation occurring in extrahepatic organs. Our objective was to review the computed tomographic findings of HAC and to correlate the imaging features with histopathologic findings. Institutional review board approval was obtained for this study.
METHODS: The computed tomographic findings images in 6 consecutive patients with pathologically proven HAC were reviewed retrospectively. Five patients were men and 1 was a woman (mean age, 56 years; age range, 36-68 years). All patients underwent contrast-enhanced computed tomography (CT) performed on a 4-slice multidetector row CT scanner. The mean time interval between CT and surgery was 5 days. Two radiologists who were unaware of the final histological diagnosis reviewed all computed tomographic images retrospectively. Lesion characteristic (ie, number, location, size, density, enhancement, heterogeneity, margin, distribution, presence of necrosis, lymphadenopathy, and distant metastasis) were evaluated. The correlation between the imaging and the pathological findings was analyzed.
RESULTS: Most patients had elevated serum alpha-fetoprotein levels (n = 4). The HAC appeared as large tumors (mean size, 4.2 x 3.4 x 3.9 cm), isodense at unenhanced CT (n = 4), moderately enhanced (n= 5), with necrotic areas (n = 6), regional lymphadenopathy (n = 5), and distant metastases (n = 4). The heterogeneity on computed tomographic images correlated well with the presence of hemorrhage and necrosis.
CONCLUSIONS: In an old patient with a large necrotic and moderately vascular tumor, the presence of distant metastases, regional lymphadenopathy, and characteristic increased serum alpha-fetoprotein level may suggest a diagnosis of HAC.

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Year:  2007        PMID: 18043368     DOI: 10.1097/RCT.0b013e318038f6dd

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  19 in total

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