18F-FDG PET/CT of advanced gastric carcinoma and association of HER2 expression with standardized uptake value

Document Type: Original Article

Authors

1 Department of Nuclear Medicine, Konyang University College of Medicine, Daejeon, Korea

2 Department of Pathology, Konyang University College of Medicine, Daejeon, Korea

Abstract

Objective(s): Expression of HER2 in gastric carcinoma has direct prognostic and therapeutic implications in patient management. The aim of this study is to determine whether a relationship exists between standardized uptake value
(SUV) and expression of HER2 in advanced gastric carcinoma.
Methods: We analyzed the 18F-FDG PET/CT results of 109 patients that underwent gastrectomy for advanced gastric carcinoma. The 18F-FDG PET/CT imaging was requested at the initial staging before surgery. The examinations were evaluated semi-quantitatively, with calculation of maximum standardized uptake values (SUVmax). The clinicopathologic factors, including HER2 overexpression, were determined from tissue obtained from the primary tumor.
Metabolic and clincopathologic parameters were correlated using a t-test, one way ANOVA and chi-square test.
Results: Immunohistochemically, 26 patients (23.8%) showed HER2 overexpression. This overexpression was significantly associated with high SUV level (P=0.02). The SUV level was significantly correlated with tumor size
(P=0.02) and differentiation (P<0.001), and Lauren histologic type (P=0.04).
Multivariate analysis showed HER2 overexpression, large tumor size, and differentiation (P=0.022, P=0.002, P<0.001) were significantly correlated with the high level of SUV in advanced gastric carcinoma. No association was found between SUV and T stage and lymph node metastasis. A receiver-operating characteristic curve demonstrated a SUVmax of 3.5 to be the optimal cutoff for predicting HER2 overexpression (sensitivity; 76.9%, specificity; 60.2%).
Conclusion: An association exists between high SUV and HER2 overexpression and 18F-FDG PET/CT could be a useful tool to predict the biological characteristics of gastric carcinoma.

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