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Trial Title:
Artificial Intelligence-based Early Screening of Pancreatic Cancer and High Risk Tracing 2 (ESPRIT-AI-2)
NCT ID:
NCT06638866
Condition:
Pancreatic Cancer
Pancreatic Ductal Adenocarcinoma
Cancer Diagnosis
Conditions: Official terms:
Pancreatic Neoplasms
Disease
Conditions: Keywords:
Early Screening
Early Diagnosis
Non-contrast CT
Artificial Intelligence
Pancreatic Cancer
Pancreatic Lesion
PDAC
Study type:
Interventional
Study phase:
N/A
Overall status:
Recruiting
Study design:
Allocation:
N/A
Intervention model:
Single Group Assignment
Intervention model description:
All subjects underwent an abdominal or chest non-contrast CT scan, and their CT images
were automatically interpreted by AI.
Primary purpose:
Screening
Masking:
None (Open Label)
Intervention:
Intervention type:
Diagnostic Test
Intervention name:
Pancreatic imaging AI model
Description:
Subjects identified with pancreatic lesions by the AI model, which include PDAC and
non-PDAC subtypes, will be required to undergo questionnaire, blood tests (including
CA19-9, CA125, CEA, etc.) and further imaging examinations (including contrast CT, MRI,
EUS, etc.) to confirm the final status of the pancreatic lesion.
Arm group label:
Pancreatic imaging AI screening
Other name:
AI model
Summary:
Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with a very low
survival rate due to its covert onset and low early diagnosis rate. This study uses a
pancreatic imaging AI model to improve early detection and high-risk monitoring of
pancreatic cancer through non-contrast CT scans. The goal is to validate the AI model's
diagnostic performance, particularly in identifying early-stage resectable PDAC.
Detailed description:
PDAC is one of the most aggressive malignancies, with a dismal 5-year survival rate of
merely 13%. The poor prognosis is primarily due to its insidious onset and low early
diagnosis rate. Clinical studies have shown that 51% of pancreatic cancer patients
present with distant metastasis at the time of diagnosis, with a 5-year survival rate of
less than 5%; in contrast, patients at stage IA demonstrate a clear therapeutic benefit,
with a postoperative 5-year survival rate of up to 83.7%. Early detection of pancreatic
cancer is crucial for improving survival rates. In this study, investigators will utilize
our developed pancreatic imaging AI model to conduct prospective clinical trials, aiming
to validate the model's diagnostic performance in real-world applications, particularly
its efficacy in detecting early-stage PDAC.
This study is led by Jin Gang, Director of Department of General Surgery of Shanghai
Changhai Hospital, in collaboration with Yinzhou Hospital Affiliated to Medical School of
Ningbo University, The Second Affiliated Hospital of Jiaxing University, The Central
Hospital of Lishui City, Jingning County People's Hospital, Meinian Onehealth Health
Examination Center, and the Medical AI Imaging Laboratory Team at Alibaba DAMO Academy.
This is a translational study focused on early detection and high-risk monitoring of
pancreatic cancer based on artificial intelligence, and it will directly impact clinical
care pathways. The study population consists of individuals who have undergone
non-contrast abdominal or chest CT scans at medical institutions or health examination
centers, defined as an opportunistic screening population. The pancreatic imaging AI
model will be used to automatically detect pancreatic lesions, including PDAC and
non-PDAC subtypes. Subjects identified with positive lesions by the AI model will be
required to undergo questionnaire, blood tests (including tumor marker analysis) and
further imaging examinations (such as contrast CT, MRI, and EUS) to confirm the final
pancreatic lesion status and formulate a treatment plan. The ultimate aim is to assess
the AI model's diagnostic performance, particularly its detection rate for early
resectable pancreatic cancer.
Criteria for eligibility:
Criteria:
Inclusion Criteria:
- 1.The subject has undergone an abdominal or chest non-contrast CT scan, categorized
as follows:
1. Physical exam population
2. Outpatient population
3. Inpatient population
4. Emergency department population
Exclusion Criteria:
- 1.The subject has been diagnosed with pancreatic cancer or other malignant tumors
within the last 5 years.
- 2.The subject has any medical condition that contraindicates the use of contrast in
MRI/CT scans.
- 3.The subject cannot be followed up or is participating in other clinical trials.
Gender:
All
Minimum age:
18 Years
Maximum age:
85 Years
Healthy volunteers:
Accepts Healthy Volunteers
Locations:
Facility:
Name:
Shanghai Changhai Hospital
Address:
City:
Shanghai
Zip:
200433
Country:
China
Status:
Recruiting
Contact:
Last name:
Wang Beilei, M.D.
Phone:
86-13774238083
Email:
lilly_wang@126.com
Investigator:
Last name:
Jin Gang, M.D.
Email:
Principal Investigator
Start date:
August 3, 2024
Completion date:
August 3, 2030
Lead sponsor:
Agency:
Changhai Hospital
Agency class:
Other
Collaborator:
Agency:
Yinzhou Hospital Affiliated to Medical School of Ningbo University
Agency class:
Other
Collaborator:
Agency:
The Second Affiliated Hospital of Jiaxing University
Agency class:
Other
Collaborator:
Agency:
Jingning County People's Hospital
Agency class:
Other
Collaborator:
Agency:
The Central Hospital of Lishui City
Agency class:
Other
Collaborator:
Agency:
Meinian Onehealth Health Examination Center
Agency class:
Other
Collaborator:
Agency:
Alibaba DAMO Academy
Agency class:
Other
Source:
Changhai Hospital
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT06638866
