Screening to improve early detection of pancreatic cancer in high-risk adults
MC250406 Feasibility Study: Automated Risk Stratification, Serial AI-Augmented Imaging, and Biobanking for Early Detection of Sporadic Pancreatic Cancer (AI-PACED)
This program tests whether repeated contrast-enhanced CT scans combined with blood draws and AI can find pancreatic cancer earlier in people aged 50–85 with recent-onset diabetes and a high ENDPAC score.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 100 (estimated) |
| Ages | 50 Years to 85 Years |
| Sex | All |
| Sponsor | Mayo Clinic Academic / other |
| Locations | 1 site (Rochester, Minnesota) |
| Trial ID | NCT07324096 on ClinicalTrials.gov |
What this trial studies
The program enrolls adults aged 50–85 with glycemically-defined new-onset diabetes (onset within 180 days) and an ENDPAC score of 3 or higher to undergo repeated contrast-enhanced CT imaging, blood collection, and AI-assisted image review. Imaging is read by radiologists and processed by AI algorithms while blood samples are used for biomarker analysis and biobanking. People with prior pancreatic cancer, known hereditary cancer syndromes, prior pancreatic surgery, current pancreatic cyst surveillance, or contraindications to contrast CT are excluded. The work is based at Mayo Clinic in Rochester and aims to create a practical surveillance pathway to detect sporadic pancreatic cancer earlier in a defined high-risk group.
Who should consider this trial
Good fit: Adults 50 to 85 years old with glycemically-defined new-onset diabetes within the past 180 days and an ENDPAC score ≥ 3 who can undergo contrast-enhanced CT and provide consent.
Not a fit: People with a prior pancreatic cancer diagnosis, known hereditary cancer syndromes, prior pancreatic surgery, current pancreatic cyst surveillance, contraindications to contrast CT, or those outside the age or new-onset diabetes window are unlikely to benefit from this program.
Why it matters
Potential benefit: If successful, this approach could detect pancreatic cancer earlier in high-risk people, improving the chance of curative treatment and better survival.
How similar studies have performed: Risk models like ENDPAC have been validated to identify higher-risk patients, but combining repeated contrast CT, AI image analysis, and blood biomarkers in glycemically-defined new-onset diabetes is a relatively novel approach without established outcome-proof in this exact setting.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Age ≥ 50 and ≤ 85 years * Glycemically-defined new-onset diabetes (gNOD) with onset ≤ 180 days preceding enrollment * Enriching New-onset Diabetes for Pancreatic Cancer (ENDPAC) score ≥ 3, based on validated risk stratification models * Provide written or remote informed consent Exclusion Criteria: * Prior diagnosis of pancreatic ductal adenocarcinoma (PDA) * Known hereditary cancer syndromes (e.g., BRCA1/2, Lynch syndrome, Peutz-Jeghers) * Prior history of pancreatic surgery * Pancreatic cyst surveillance at time of registration * Contraindications to contrast-enhanced CT imaging per standard clinical practice at time of registration
Where this trial is running
Rochester, Minnesota
- Mayo Clinic in Rochester — Rochester, Minnesota, United States (Recruiting)
Study contacts
- Principal investigator: Ajit H. Goenka, MD — Mayo Clinic in Rochester
- Study coordinator: Clinical Trials Referral Office
- Email: mayocliniccancerstudies@mayo.edu
- Phone: 855-776-0015
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.