EUS-Based Artificial Intelligence to Predict Outcomes in Pancreatic Cancer
EUS-AI-R
An Observational Study on the Application of Artificial Intelligence Model to Predict Diagnosis, Prognosis, and Molecular Alterations in Pancreatic Cancer
1 other identifier
observational
700
1 country
1
Brief Summary
The EUS-AI-R study is an observational, single-center, two-phase (retrospective-prospective) study designed to develop and validate artificial intelligence (AI) models for predicting chemotherapy response and oncological outcomes in patients with pancreatic ductal adenocarcinoma (PDAC). Patients who underwent endoscopic ultrasound (EUS) with tissue acquisition (EUS-FNA/FNB) for suspected pancreatic lesions at IRCCS San Raffaele Hospital between January 1st, 2019 and January 2026 will be retrospectively included. All patients have a histologically confirmed diagnosis of PDAC and a minimum follow-up of six months. These data derive from an IRB-approved institutional study (BIOPANCREAS; NCT06552078). Retrospective multimodal data, including EUS imaging (B-mode, elastography, contrast-enhanced EUS), clinical and laboratory variables, CT/MRI imaging, digital pathology, and molecular data when available, will be used to develop and internally validate multiple AI models. In the prospective phase, the best-performing AI model will be applied to an independent cohort of patients undergoing EUS at the same institution to evaluate feasibility, calibration, and real-world performance. No additional procedures beyond standard clinical practice will be performed.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Oct 2026
Typical duration for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
April 22, 2026
CompletedFirst Posted
Study publicly available on registry
September 4, 2026
CompletedStudy Start
First participant enrolled
October 31, 2026
ExpectedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2028
Study Completion
Last participant's last visit for all outcomes
December 31, 2028
September 4, 2026
September 1, 2026
2.2 years
April 22, 2026
September 2, 2026
Conditions
Outcome Measures
Primary Outcomes (1)
Development of an AI algorithm predicting chemotherapy response in patients with pancreatic cancer
Development of AI models to predict chemotherapy response in patients with PDAC by evaluating the predictive performance of: 1. An EUS-based AI model (pre-treatment EUS images/videos) 2. A clinical/exposome-based AI model (pre-treatment clinical and laboratory variables) 3. A radiology-based AI model (pre-treatment CT/MRI radiomics) 4. A digital pathology-based AI model (histopathology slides) 5. A multimodal AI model combining all available data sources (EUS + clinical/exposome + CT/MRI radiomics + digital pathology ± molecular data when available) Chemotherapy response will be defined according to radiological response criteria (RECIST) and biochemical response assessed by CA19-9 levels. Model performance will be assessed using AUC-ROC, sensitivity, and specificity.
6 months
Secondary Outcomes (3)
Recurrence-Free Survival (RFS) Rate based on AI Models
From the date of histological diagnosis of pancreatic cancer until the date of first documented recurrence or death from any cause, whichever came first, assessed up to 6 months
Progression-Free Survival (PFS) Rate based on AI Models
From the date of histological diagnosis of pancreatic cancer until the date of first documented disease progression or death from any cause, whichever came first, assessed up to 6 months
Overall Survival (OS) Rate based on AI Models
From the date of histological diagnosis of pancreatic cancer until the date of death from any cause, assessed up to 6 months
Other Outcomes (3)
Diagnostic Accuracy and Discrimination (AUC-ROC)
1 year
Diagnostic Accuracy (Sensitivity and Specificity) of AI Models
1 year
Model Calibration, Stability, and Prospective Feasibility
1 year
Study Arms (1)
All patients who underwent EUS at the Pancreato-Biliary Endoscopy and Endoscopic Ultrasound Unit of
Interventions
Endoscopic ultrasound (EUS), with or without tissue acquisition (EUS-FNA/FNB), performed according to standard clinical practice. No study-specific intervention is introduced.
Eligibility Criteria
All patients who underwent EUS at the Pancreato-Biliary Endoscopy and Endoscopic Ultrasound Unit of IRCCS San Raffaele Hospital with an histological diagnosis of PDAC.
You may qualify if:
- Pathologically confirmed diagnosis (final pathology report) of pancreatic cancer obtained through endoscopic ultrasound-guided tissue sampling (EUS-FNA or EUS-FNB)
- Age ≥ 18 years at the time of diagnosis
- Minimum follow-up duration of 6 months after diagnosis
- Absence of other concomitant neoplastic diseases
- Age\>= 18 years
- Capacity to understand and make informed decisions
- Written informed consent provided by the patient
You may not qualify if:
- Age\<18 years
- Inability to understand and make informed decisions
- Refusal to participate in the study
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
IRCCS Ospedale San Raffaele
Milan, Lombardy, 20132, Italy
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- OTHER
- Target Duration
- 6 Months
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Director, Pancreatico-Biliary Endoscopy and Endosonography Division
Study Record Dates
First Submitted
April 22, 2026
First Posted
September 4, 2026
Study Start (Estimated)
October 31, 2026
Primary Completion (Estimated)
December 31, 2028
Study Completion (Estimated)
December 31, 2028
Last Updated
September 4, 2026
Record last verified: 2026-09