AI-powered Early Detection for Pancreatic Cancer Via Non-contrast CT in Opportunistic Screening Cohort

Summary

Pancreatic ductal adenocarcinoma (PDAC) remains a therapeutic challenge with 5-year survival rates of 13%, primarily attributable to advanced-stage diagnosis (AJCC Stage III/IV in \>80% of cases). This prospective, observational, multi-center study will evaluate the performance of an AI-powered opportunistic screening system utilizing non-contrast computed tomography (NCCT) acquired during routine clinical encounters or health check-ups. The proposed AI model will perform automated detection of pancreatic parenchymal abnormalities, including PDAC and precursor lesions (intraductal papillary mucinous neoplasms \[IPMN\], mucinous cystic neoplasms \[MCN\]). Algorithm-positive cases will be independently reviewed by two radiologists. Highly suspected individuals will undergo further diagnostic verification, including serological tests and multimodal imaging confirmation. Patients with confirmed positive diagnosis will receive multidisciplinary consultation and specialized treatment, whereas those with negative results will undergo at least one-year clinical follow-up. This study will quantitatively evaluate the AI system's performance, and aims to advance PDAC early detection, improve patient outcomes, and make it accessible in underserved populations.

Conditions

• Pancreatic Cancer
• Pancreatic Ductal Adenocarcinoma
• Pancreatic Intraepithelial Neoplasias
• Intraductal Papillary Mucinous Neoplasm
• Mucinous Cystic Neoplasm

Interventions

DIAGNOSTIC_TEST

PDAC

Participants with algorithm-identified PDAC will be independently reviewed by two radiologists. Those highly suspected will be recalled for further diagnostic evaluation, including serological tests (e.g., CA19-9, CEA) and imaging (e.g., contrast-enhanced CT/MRI, EUS-FNA). Participants with a confirmed positive diagnosis will undergo multidisciplinary consultation and specialized treatment, while those with a negative diagnosis will be followed clinically for at least one year.

DIAGNOSTIC_TEST

Pancreatic precursor lesions

Participants with algorithm-identified pancreatic precursor lesions will be independently reviewed by two radiologists. Those highly suspected will be recalled for further diagnostic evaluation, including serological tests (e.g., CA19-9, CEA) and imaging (e.g., contrast-enhanced CT/MRI, EUS-FNA). Participants with a confirmed positive diagnosis will undergo multidisciplinary consultation and specialized treatment, while those with a negative diagnosis will be followed clinically for at least one year.

Sponsors & Collaborators

• Yinzhou Hospital Affiliated to Medical School of Ningbo University

  collaborator OTHER

• The Second Affiliated Hospital of Jiaxing University

  collaborator OTHER

• Central Hospital of Lishui City

  collaborator UNKNOWN

• Jingning County People's Hospital

  collaborator UNKNOWN

• Alibaba DAMO Academy

  collaborator UNKNOWN

• Changhai Hospital

  lead OTHER

Principal Investigators

• Jin Gang, M.D. · Changhai Hospital

• Wang Bei Lei, M.D. · Changhai Hospital

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2024-08-03

Primary Completion

2029-12-31

Completion

2030-12-31

Countries

• China

Study Locations