Pancreatic CancerNCT07439757
AI-Powered Precision Decision-Making for Pancreatic Diseases
An observational study of Pancreatic Cancer and Diagnose Disease, run by Changhai Hospital at 1 site in China.
Trial summary
This multicenter clinical trial evaluates an artificial intelligence (AI) system designed to assist in the diagnosis and management of pancreatic diseases. Using contrast-enhanced CT scans, the study compares the AI's recommendations against the decisions of experienced clinicians to verify the system's accuracy and… Read more about this study
- Who is it for?
- Ages 18 to 80 years
- Conditions the study is for
- Pancreatic Cancer, Diagnose Disease, IPMN, Pancreatic
- What is being tested?
- Diagnosis by Artificial Intelligence model
- How many people
- 2,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Mar 2026to 31 Oct 2029
- How long will I take part?
- 1 Year
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The study enrolls patients with clinically suspected pancreatic disease who have available contrast-enhanced CT scans and provide informed consent. Patients are excluded if they have a history of pancreatic surgery, contraindications to contrast media, suboptimal image quality, or other conditions deemed unsuitable by the investigator (e.g., pregnancy, cognitive impairment, or concurrent trial participation).
Who may be able to join
- Clinically suspected pancreatic disease.
- Scheduled to undergo contrast-enhanced CT.
- Signed informed consent form indicating agreement to participate.
Who cannot join
- History of pancreatic surgery.
- Contraindications to contrast-enhanced CT, including known hypersensitivity to iodinated contrast media or severe renal/hepatic dysfunction.
- Suboptimal image quality affecting diagnosis.
- Concurrent participation in another interventional clinical trial.
- Unsuitability for participation as determined by the investigator, including but not limited to: pregnancy or lactation, severe psychiatric disorders or cognitive impairment, significant comorbidities that may interfere with study results or patient safety.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Changhai Hospital
Shanghai, 200433
Beilei Wang, Doctor, +86 13774238083, lilly_wang@126.com
About this study
Official title: A Multicenter Clinical Study on AI-Powered Precision Decision-Making Management for Pancreatic Diseases Using Contrast-Enhanced CT
This multicenter clinical trial evaluates an artificial intelligence (AI) system designed to assist in the diagnosis and management of pancreatic diseases. Using contrast-enhanced CT scans, the study compares the AI's recommendations against the decisions of experienced clinicians to verify the system's accuracy and safety in a real-world setting. Patients are categorized into three management groups: Intervention (surgery/treatment), Intensive Surveillance (close monitoring), or Routine Surveillance (standard follow-up). The primary goal is to determine if the AI system can reliably classify patients, reduce the risk of missing malignant lesions, and prevent unnecessary surgeries, thereby improving clinical decision-making for pancreatic conditions.
Read the detailed description
MEHTOD： This multicenter clinical trial evaluates the reliability and effectiveness of an AI system for patients with pancreatic diseases in a real-world clinical environment. The study calculates the AI system's classification accuracy using pathological diagnosis (biopsy/surgery results) or long-term follow-up as the "gold standard" for comparison. Additionally, the safety and clinical utility of the management strategies recommended by the AI are assessed by measuring the risk of missing malignant lesions, the rate of unnecessary surgeries for pancreatic diseases, and the level of agreement with traditional clinical decisions.
STUDY DESIGN
All contrast-enhanced CT images from patients with pancreatic diseases are analyzed by the AI system to generate a classification result (Intervention, Intensive Surveillance, or Routine Surveillance). Simultaneously, clinical doctors review the same data and categorize patients into these three groups to determine their actual care plan:
- INTERVENTION: Patients assessed by doctors as needing "Intervention" are recommended for further surgical evaluation or treatment.
- INTENSIVE SURVEILLANCE: Patients assessed by doctors as needing "Intensive Surveillance" receive a personalized, high-frequency follow-up plan until the study endpoint.
- ROUTINE SURVEILLANCE: Patients assessed by doctors as needing "Routine Surveillance" undergo follow-up for at least one year. If abnormalities arise during this period, the patient is transferred to the appropriate "Intervention" or "Intensive Surveillance" protocol.
OUTCOMES： The study compares the performance of the AI system against clinical doctors regarding classification accuracy, the risk of missed diagnoses, unnecessary surgery rates, and decision consistency. These metrics are used to validate the AI system's value, safety, and utility in the clinical management of pancreatic diseases.
- Conditions
- Pancreatic Cancer, Diagnose Disease, IPMN, Pancreatic, Pancreatic Cystic Lesions, Chronic Pancreatitis, Pancreatic Neuroendocrine Tumor
- Being tested
- Diagnosis by Artificial Intelligence model
- Keywords
- Artificial Intelligence (AI), Deep Learning, Contrast-Enhanced CT, Multicenter Clinical Trial, Real-World Study
- Medical subject headings
- Pancreatic Neoplasms, Pancreatic Intraductal Neoplasms, Pancreatitis, Chronic, Adenoma, Islet Cell, Pancreatitis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Diagnosis by Artificial Intelligence modelDiagnostic test
To develop an artificial intelligence-based classification management system for pancreatic diseases, achieving automated and precise classification. Contrast-enhanced CT images from all study subjects will be analyzed by the AI system to generate classification results, categorizing patients into three groups: INTERVENTIOM, INTENSIVE SURVEILLANCE or ROUTINE SURVEILLANCE.
| Study group | Role | What they receive |
|---|---|---|
| AI group | Diagnosis by Artificial Intelligence model Receives: Diagnostic Test: Diagnosis by Artificial Intelligence model | |
| Clinicians group | Diagnosis by clinicians |
What is being measured
The primary outcome is the main question the study is designed to answer.
Classification accuracy
The percentage of cases correctly classified by AI out of the total number of cases.
Measured: From date of contrast-enhanced CT scan to 1 year
Secondary outcomes (3)
Agreement rate with clinical decisions
The proportion of total cases where AI and clinician classification results are in agreement.
Measured: From date of contrast-enhanced CT scan to 1 year
Percentage decrease in unnecessary surgical procedures
The percentage reduction in the unnecessary surgery rate achieved by AI decision-making compared to traditional decision-making.
Measured: From date of contrast-enhanced CT scan to 1 year
Malignancy miss rate
The proportion of cases classified by AI as non-surgical that actually required surgery.
Measured: From date of contrast-enhanced CT scan to 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Feb 2026
- Study start1 Mar 2026 (estimated)
- Primary completion31 Oct 2029 (estimated)
- Study completion31 Oct 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pancreatic CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 2,000 participants (estimated)
- Target duration
- 1 Year
Sponsor and investigators
- Lead sponsor
- Changhai Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- The First Affiliated Hospital with Nanjing Medical University, The Affiliated People's Hospital of Ningbo University, The Second Affiliated Hospital of Jiaxing University, Shanghai Changzheng Hospital, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shengjing Hospital, Shanghai Fourth People's Hospital Tongji University, First Affiliated Hospital of Zhejiang University, Shanghai Fudan University Cancer Center
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07439757
- Sponsor's protocol ID
- Prospective PRISM
- Status last verified
- Feb 2026
- First submitted
- 23 Feb 2026
- Last updated
- 27 Feb 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 27 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Multicenter Clinical Study on AI-Powered Precision Decision-Making Management for Pancreatic Diseases Using Contrast-Enhanced CT
- ClinicalTrials.gov ID
- NCT07439757
- Acronym / sponsor ID
- Prospective PRISM
- Conditions
- Pancreatic Cancer, Diagnose Disease, IPMN, Pancreatic, Pancreatic Cystic Lesions, Chronic Pancreatitis, Pancreatic Neuroendocrine Tumor
- Keywords
- Artificial Intelligence (AI), Deep Learning, Contrast-Enhanced CT, Multicenter Clinical Trial, Real-World Study
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 2,000 participants (estimated)
- Lead sponsor
- Changhai HospitalUniversity, hospital or other
- Collaborators
- The First Affiliated Hospital with Nanjing Medical University, The Affiliated People's Hospital of Ningbo University, The Second Affiliated Hospital of Jiaxing University, Shanghai Changzheng Hospital, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shengjing Hospital, Shanghai Fourth People's Hospital Tongji University, First Affiliated Hospital of Zhejiang University, Shanghai Fudan University Cancer Center
- Study start
- 1 Mar 2026 (estimated)
- Primary completion
- 31 Oct 2029 (estimated)
- Study completion
- 31 Oct 2029 (estimated)
- First posted
- 27 Feb 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This multicenter clinical trial evaluates an artificial intelligence (AI) system designed to assist in the diagnosis and management of pancreatic diseases. Using contrast-enhanced CT scans, the study compares the AI's recommendations against the decisions of experienced clinicians to verify the system's accuracy and safety in a real-world setting. Patients are categorized into three management groups: Intervention (surgery/treatment), Intensive Surveillance (close monitoring), or Routine Surveillance (standard follow-up). The primary goal is to determine if the AI system can reliably classify patients, reduce the risk of missing malignant lesions, and prevent unnecessary surgeries, thereby improving clinical decision-making for pancreatic conditions.
Detailed description
MEHTOD： This multicenter clinical trial evaluates the reliability and effectiveness of an AI system for patients with pancreatic diseases in a real-world clinical environment. The study calculates the AI system's classification accuracy using pathological diagnosis (biopsy/surgery results) or long-term follow-up as the "gold standard" for comparison. Additionally, the safety and clinical utility of the management strategies recommended by the AI are assessed by measuring the risk of missing malignant lesions, the rate of unnecessary surgeries for pancreatic diseases, and the level of agreement with traditional clinical decisions.
STUDY DESIGN
All contrast-enhanced CT images from patients with pancreatic diseases are analyzed by the AI system to generate a classification result (Intervention, Intensive Surveillance, or Routine Surveillance). Simultaneously, clinical doctors review the same data and categorize patients into these three groups to determine their actual care plan:
- INTERVENTION: Patients assessed by doctors as needing "Intervention" are recommended for further surgical evaluation or treatment.
- INTENSIVE SURVEILLANCE: Patients assessed by doctors as needing "Intensive Surveillance" receive a personalized, high-frequency follow-up plan until the study endpoint.
- ROUTINE SURVEILLANCE: Patients assessed by doctors as needing "Routine Surveillance" undergo follow-up for at least one year. If abnormalities arise during this period, the patient is transferred to the appropriate "Intervention" or "Intensive Surveillance" protocol.
OUTCOMES： The study compares the performance of the AI system against clinical doctors regarding classification accuracy, the risk of missed diagnoses, unnecessary surgery rates, and decision consistency. These metrics are used to validate the AI system's value, safety, and utility in the clinical management of pancreatic diseases.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 1 Year
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI group | – | Diagnostic Test: Diagnosis by Artificial Intelligence modelDiagnosis by Artificial Intelligence model |
| Clinicians group | – | –Diagnosis by clinicians |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The study enrolls patients with clinically suspected pancreatic disease who have available contrast-enhanced CT scans and provide informed consent. Patients are excluded if they have a history of pancreatic surgery, contraindications to contrast media, suboptimal image quality, or other conditions deemed unsuitable by the investigator (e.g., pregnancy, cognitive impairment, or concurrent trial participation).
Key inclusion criteria (3 listed)
- Clinically suspected pancreatic disease.
- Scheduled to undergo contrast-enhanced CT.
- Signed informed consent form indicating agreement to participate.
Key exclusion criteria (5 listed)
- History of pancreatic surgery.
- Contraindications to contrast-enhanced CT, including known hypersensitivity to iodinated contrast media or severe renal/hepatic dysfunction.
- Suboptimal image quality affecting diagnosis.
- Concurrent participation in another interventional clinical trial.
- Unsuitability for participation as determined by the investigator, including but not limited to: pregnancy or lactation, severe psychiatric disorders or cognitive impairment, significant comorbidities that may interfere with study results or patient safety.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Diagnosis by Artificial Intelligence modelTo develop an artificial intelligence-based classification management system for pancreatic diseases, achieving automated and precise classification. Contrast-enhanced CT images from all study subjects will be analyzed by the AI system to generate classification results, categorizing patients into three groups: INTERVENTIOM, INTENSIVE SURVEILLANCE or ROUTINE SURVEILLANCE. | Diagnostic test | AI group |
Primary outcome
Classification accuracy
Time frame: From date of contrast-enhanced CT scan to 1 year
The percentage of cases correctly classified by AI out of the total number of cases.
3 secondary outcomes
Agreement rate with clinical decisions
Time frame: From date of contrast-enhanced CT scan to 1 year
Percentage decrease in unnecessary surgical procedures
Time frame: From date of contrast-enhanced CT scan to 1 year
Malignancy miss rate
Time frame: From date of contrast-enhanced CT scan to 1 year
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 27 Feb 2026.
- Individual participant dataSharing planned: No
Related trials for Pancreatic Cancer
Active, not recruitingPhase 1/2
A Beta-only IL-2 ImmunoTherapY Study
Advanced Solid Tumor, Unresectable Solid Tumor
RecruitingPhase 1
A Study of MGC030 in Participants With Advanced Solid Tumors
Urothelial Cancer, GastroEsophageal Cancer
Recruiting
Implementation of a Pain Management Plan in Major Open Abdominal Surgeries.
Abdomen Cancer, Pancreas Adenocarcinoma (MSI-H)
Active, not recruitingPhase 2
Pembrolizumab With Olaparib as Combined Therapy in Metastatic Pancreatic Cancer
Pancreatic Cancer
RecruitingPhase 2/3
Zanzalintinib Versus Everolimus in Participants With Locally Advanced or Metastatic Neuroendocrine Tumors
Pancreatic Neuroendocrine Tumor (pNET), Extra-Pancreatic Neuroendocrine Tumor (epNET)
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Pancreatic Cancer and Diagnose Disease, run by Changhai Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 27 Feb 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Beilei Wang, Doctor (+86 13774238083, lilly_wang@126.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Classification accuracy (time frame: From date of contrast-enhanced CT scan to 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 27 Feb 2026.