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

Gastrointest Endosc. 2015 Jul;82(1):59-69. doi: 10.1016/j.gie.2014.11.040. Epub 2015 Mar 16.

Abstract

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.).

Publication types

  • Comparative Study
  • Multicenter Study
  • Observational Study
  • Research Support, Non-U.S. Gov't
  • Video-Audio Media

MeSH terms

  • Adenocarcinoma / diagnostic imaging*
  • Adenocarcinoma / pathology
  • Adult
  • Aged
  • Aged, 80 and over
  • Contrast Media
  • Diagnosis, Computer-Assisted / methods*
  • Diagnosis, Differential
  • Endoscopic Ultrasound-Guided Fine Needle Aspiration
  • Endosonography / methods*
  • Female
  • Follow-Up Studies
  • Humans
  • Male
  • Middle Aged
  • Neural Networks, Computer
  • Pancreatic Neoplasms / diagnostic imaging*
  • Pancreatic Neoplasms / pathology
  • Pancreatitis, Chronic / diagnostic imaging*
  • Pancreatitis, Chronic / pathology
  • Prospective Studies
  • Sensitivity and Specificity

Substances

  • Contrast Media

Associated data

  • ClinicalTrials.gov/NCT01315548