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Utility of FDG-PET Imaging for Risk Stratification of Pancreatic Neuroendocrine Tumors in MEN1
Elena R Kornaczewski Jackson1, Owen P Pointon2, Robert Bohmer3
1Department of Diabetes and Endocrinology, Royal Hobart Hospital, Hobart, Tasmania 7000, Australia.
Context:
Patients with multiple endocrine neoplasia type 1 (MEN1) are at high risk of malignant pancreatic neuroendocrine tumors (pNETs). Structural imaging is typically used to screen for pNETs but is suboptimal for stratifying malignant potential.
Objective:
To determine the utility of fluorodeoxyglucose (18F) positron emission tomography/computed tomography (18F-FDG PET/CT) for predicting the malignant potential of pNETs in MEN1.
Design:
Retrospective observational study.
Setting:
Tertiary referral hospital.
Patients:
Forty-nine adult patients with MEN1 carrying a common MEN1 mutation who underwent 18F-FDG PET/CT for MEN1 surveillance between 1 January 2010 and 30 September 2016.
Interventions:
Structural and functional imaging (magnetic resonance imaging, CT, ultrasonography, and 18F-FDG PET/CT) and surgical histopathology.
Main Outcome Measures:
pNET size, behavior, and histopathology.
Results:
Twenty-five (51.0%) of 49 patients studied had pancreatic lesions on structural imaging. Five (25%) of these had 18F-FDG-PET-avid lesions. In addition, two had solitary FDG-avid liver lesions, and one a pancreatic focus without structural correlate. Eight patients with pNETs underwent surgery (three FDG-avid lesions and five nonavid pNETs). The Ki-67 index was ≥5% in FDG-avid pNETs and <2% in nonavid pNETs. Overall, six of the eight (75%) patients with FDG-avid hepatopancreatic lesions harbored aggressive or metastatic NETs compared with one of 41 patients (2.4%) without hepatopancreatic FDG avidity [P < 0.001; sensitivity; 85.7% (95% confidence interval [CI], 48.7% to 99.3%); specificity, 95.2% (95% CI, 84.2% to 99.2%)].
Conclusion:
18F-FDG PET/CT is an effective screening modality in MEN1 for identifying pNETs of increased malignant potential. Surgical resection is recommended for FDG-avid pNETs.
