Quantitative contrast-enhanced harmonic EUS in differential diagnosis of focal pancreatic masses (with videos)

Background The role of EUS with contrast agents can be expanded through the use of time-intensity curve (TIC) analysis and computer-aided interpretation. Objective To validate the use of parameters derived from TIC analysis in an artificial neural network (ANN) classification model designed to diagnose pancreatic carcinoma (PC) and chronic pancreatitis (CP). Setting Prospective, multicenter, observational trial—endoscopy units from Romania, Denmark, Germany, and Spain. Patients A total of 167 consecutive patients with PC or CP. Interventions Contrast-enhanced harmonic EUS (CEH-EUS) and EUS-guided FNA (EUS-FNA), TIC analysis, and ANN processing. Main Outcome Measurements Sensitivity, specificity, positive and negative predictive values (PPV, NPV) for EUS-FNA, CEH-EUS, and the ANN. Results After excluding all of the recordings that did not meet the technical and procedural criteria, 112 cases of PC and 55 cases of CP were included. EUS-FNA was performed in 129 patients, and the diagnosis was confirmed by surgery (n = 15) or follow-up (n = 23) in the remaining cases. Its sensitivity and specificity were 84.82% and 100%, respectively, whereas the PPV and NPV were 100% and 76.63%, respectively. The sensitivity of real-time quantitative assessment of CEH-EUS was 87.5%, specificity 92.72%, PPV 96.07%, and NPV 78.46%. Peak enhancement, wash-in area under the curve, wash-in rate, and the wash-in perfusion index were significantly different between the groups. No significant differences were found between rise time, mean transit time, and time to peak. For the ANN, sensitivity was 94.64%, specificity 94.44%, PPV 97.24%, and NPV 89.47%. Limitations Only PC and CP lesions were included. Conclusion Parameters obtained through TIC analysis can differentiate between PC and CP cases and can be used in an automated computer-aided diagnostic system with good diagnostic results. (Clinical trial registration number: NCT01315548.)