NCT06055010Recruiting
Improving Pancreatic Cancer Care by the Use of Computational Science and Technology
Source: ClinicalTrials.gov · Last updated 26 Sept 2023 · Not updated for over 12 months - ask the site whether it is still open
Brief summary (registry, in English)
The goal of the IMPACT project is to set up a data sharing infrastructure between expert centers for pancreatic surgery that enables training, testing and validation of computer science tools to improve quality of care for patients with pancreatic cancer.
- Status (registry)
- Recruiting
- Study type
- Observational
- Enrollment
- 5000 (estimated)
- First submitted
- 30 May 2023
- Start date
- 1 Jan 2014
- Primary completion date
- 31 Dec 2029
- Lead sponsor
- UMC Utrecht
- Diseases
- Pancreatic cancer, Childhood cancers
- NCT number
- NCT06055010
What you commit to
- Study type: Observational
- Planned participants: 5000
- From 1 Jan 2014 to the primary completion date, 31 Dec 2029
- 1 site in 1 country
- Visits and tests: ask the trial team, the registry does not list them
Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.
Who cannot take part
Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.
Other
- \- Subjects who object to the use of their data for the purpose of scientific research
Who the study is looking for
- ≥18 years of age
- Patients who received diagnostic procedures and/or treatment for (suspected) benign and malignant pancreatic lesions as registered in the Dutch Pancreatic Cancer Project (PACAP) audit database and healthy individuals who received an abdominal CT-scan (controls)
Sex: All · Accepts healthy volunteers
Sites (1)
Sites in registry order. Pick your city on the disease page to sort them by distance.
| Site | City | Country | Site status |
|---|---|---|---|
| Regional Academic Cancer Center Utrecht Coordinator of this site? Confirm its status | Utrecht | Netherlands | Recruiting |
Related publications
- MKNet-family architectures for auto-segmentation of the residual pancreas after pancreatic resection: a deep learning comparative study.Abdom Radiol (NY) · 2026 · PMID 41307673
This page is information, not medical advice. Discuss any trial with your doctor.