Discrimiating low grade Intraductal papillary mucinous neoplasms (IPMN) from high grade IPMN/beginning invasive pancreatic cancer in endosonographic ultrasound images using artificial intelligence

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00035682

Enrollment

150

Registered

2024-12-12

Start date

2024-06-01

Completion date

Unknown

Last updated

2026-01-12

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

C25.3

Interventions

Group 1: Retrospective survey of patients who underwent endosonography not older than 6 months and surgical resection due to an IPMN. Collection of data over 8 years at all participating sites. Subseq

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: Surgery due to an IPMN in one of the including centers, available EUS examination not older than 6 months.

Exclusion criteria

Exclusion criteria: Already high-grade pancreatic carcinoma without cystic part on staging CT.

Design outcomes

Primary

Measure	Time frame
Development and testing of an artificial intelligence to differentiate low grade from high grade IPMN/invasive carcinoma with high diagnostic accuracy.	—

Countries

Germany, Italy, United States

Contacts

Public ContactDominik Schulz

Universitätsklinikum Augsburg

Dominik.Schulz@uk-augsburg.de0821 400-0

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026