Using computer analysis of endoscopic ultrasound images to predict pancreatic cancer outcomes
Builds and tests an AI tool on ultrasound images from pancreatic cancer patients.
Plain-language title generated from the registry record
Registry title: EUS-Based Artificial Intelligence to Predict Outcomes in Pancreatic Cancer
Key facts
- Where
- Milan, ItalySee the site
AI summary: who the study is looking for
From the trial's eligibility criteria. Machine-read from the registry text on this page, so it can be wrong. The registry text below and the trial team decide who can take part.
The trial is looking for adults with pancreatic cancer confirmed by a tissue sample taken during an endoscopic ultrasound. They need at least 6 months of follow-up after diagnosis.
- Age
- 18 years or older
- Sex
- All sexes can join
- Disease stage
- Pancreatic cancer confirmed by pathology report after endoscopic ultrasound-guided tissue sampling (EUS-FNA or EUS-FNB)
Main reasons for not taking part
- Other cancers at the same time
- Less than 6 months of follow-up after diagnosis
- Cannot understand and make informed decisions
- Refuses to take part
- Under 18 years old
Read by machine on 13 November 2026.
Where in Italy
- IRCCS Ospedale San RaffaeleMilan, ItalyContact: Laura ApadulaNo longer taking part
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Contact the study team: see the registry record → Contacts and Locations
Print a page for my doctorTrial details
- Who runs it
- IRCCS San Raffaele
- Trial code
- NCT07803770
- Record updated
- 4 September 2026
- Original description
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).Read full original descriptionShow less
An Observational Study on the Application of Artificial Intelligence Model to Predict Diagnosis, Prognosis, and Molecular Alterations in Pancreatic Cancer
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.
Inclusion: 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.
Exclusion: Age<18 years; All patients who underwent endoscopic ultrasound with tissue sampling at the Pancreato-Biliary Endoscopy and Endoscopic Ultrasound Unit of IRCCS San Raffaele Hospital but do not meet the inclusion criteria will be excluded from the final analysis cohorts; Inability to understand and make informed decisions; Refusal to participate in the study.