Searching for indicators of malignancy in pancreatic intraductal papillary mucinous neoplasms: the value of 18FDG-PET confirmed
- PMID: 22752369
- DOI: 10.1245/s10434-012-2234-5
Searching for indicators of malignancy in pancreatic intraductal papillary mucinous neoplasms: the value of 18FDG-PET confirmed
Abstract
Background: Malignancy in intraductal papillary mucinous neoplasms (IPMN) of the pancreas may be predicted on the basis of a number of clinical and radiologic features, which have raised sensitivity but result in a specificity as low as 20-50%. We sought to confirm the additional value of (18)F-18-fluorodeoxyglucose-positron emission tomography ((18)FDG-PET) in diagnostic accuracy of imaging-based IPMN malignancy assessment.
Methods: This prospective uncontrolled case series contained 44 patients with IPMN undergoing comprehensive diagnostic evaluation, including magnetic resonance cholangiopancreatography and (18)FDG-PET. Average follow-up time was 39.3 months (range 3-97 months). Diagnostic performance regarding the diagnosis of malignancy was evaluated for the classic preoperative assessment, including clinical signs, CA 19-9, imaging (computed tomography and magnetic resonance cholangiopancreatography), and International Consensus Guidelines criteria, as well as (18)FDG-PET scan.
Results: Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 100, 22, 32, 100, and 43%, and 83, 100, 100, 94, and 96%, respectively, for comprehensive assessment without and with (18)FDG-PET [maximum standardized uptake value (SUV(max)) cutoff of 2.5 MBq]. Elevated CA 19-9 values and positive PET scan were the only independent prognostic factors for malignancy (odds ratio 2.11, 95% confidence interval 1.15-2.74 and 5.49, 95% confidence interval 3.98-21.44, respectively).
Conclusions: (18)FDG-PET is useful for detection of malignancy in IPMN, improving the differential diagnosis with benign cases by functional data. The choice of SUV(max) cutoff should maximize specificity.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Medical
