Background Detection of hepatic metastases during EUS is an important component of tumor staging. Objective To describe our experience with EUS-guided FNA (EUS-FNA) of solid hepatic masses and derive and validate criteria to help distinguish between benign and malignant hepatic masses. Design Retrospective study, survey. Setting Single, tertiary-care referral center. Patients Medical records were reviewed for all patients undergoing EUS-FNA of solid hepatic masses over a 12-year period. Interventions EUS-FNA of solid hepatic masses. Main Outcome Measurements Masses were deemed benign or malignant according to predetermined criteria. EUS images from 200 patients were used to create derivation and validation cohorts of 100 cases each, matched by cytopathologic diagnosis. Ten expert endosonographers blindly rated 15 initial endosonographic features of each of the 100 images in the derivation cohort. These data were used to derive an EUS scoring system that was then validated by using the validation cohort by the expert endosonographer with the highest diagnostic accuracy. Results A total of 332 patients underwent EUS-FNA of a hepatic mass. Interobserver agreement regarding the initial endosonographic features among the expert endosonographers was fair to moderate, with a mean diagnostic accuracy of 73% (standard deviation 5.6). A scoring system incorporating 7 EUS features was developed to distinguish benign from malignant hepatic masses by using the derivation cohort with an area under the receiver operating curve (AUC) of 0.92; when applied to the validation cohort, performance was similar (AUC 0.86). The combined positive predictive value of both cohorts was 88%. Limitations Single center, retrospective, only one expert endosonographer deriving and validating the EUS criteria. Conclusion An EUS scoring system was developed that helps distinguish benign from malignant hepatic masses. Further study is required to determine the impact of these EUS criteria among endosonographers of all experience.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging