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Erschienen in:
01.10.2014 | Original Article
Value of 18F-FDG uptake on PET/CT and CEA level to predict epidermal growth factor receptor mutations in pulmonary adenocarcinoma
Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging | Ausgabe 10/2014
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Purpose
The identification of the mutation status of the epidermal growth factor receptor (EGFR) is important for the optimization of treatment in patients with pulmonary adenocarcinoma. The acquisition of adequate tissues for EGFR mutational analysis is sometimes not feasible, especially in advanced-stage patients. The aim of this study was to predict EGFR mutation status in patients with pulmonary adenocarcinoma based on 18F-fluorodeoxyglucose (FDG) uptake and imaging features in positron emission tomography/computed tomography (PET/CT), as well as on the serum carcinoembryonic antigen (CEA) level.
Methods
We retrospectively reviewed 132 pulmonary adenocarcinoma patients who underwent EGFR mutation testing, pretreatment FDG PET/CT and serum CEA analysis. The associations between EGFR mutations and patient characteristics, maximal standard uptake value (SUVmax) of primary tumors, serum CEA level and CT imaging features were analyzed. Receiver-operating characteristic (ROC) curve analysis was performed to quantify the predictive value of these factors.
Results
EGFR mutations were identified in 69 patients (52.2 %). Patients with SUVmax ≥6 (p = 0.002) and CEA level ≥5 (p = 0.013) were more likely to have EGFR mutations. The CT characteristics of larger tumors (≥3 cm) (p = 0.023) and tumors with a nonspiculated margin (p = 0.026) were also associated with EGFR mutations. Multivariate analysis showed that higher SUVmax and CEA level, never smoking and a nonspiculated tumor margin were the most significant predictors of EGFR mutation. The combined use of these four criteria yielded a higher area under the ROC curve (0.82), suggesting a good discrimination.
Conclusion
The combined evaluation of FDG uptake, CEA level, smoking status and tumor margins may be helpful in predicting EGFR mutation status in patients with pulmonary adenocarcinoma, especially when the tumor sample is inadequate for genetic analysis or genetic testing is not available. Further large-scale prospective studies are needed to validate these results.