Research of the Application of Pancreatic Cancer Screening Artificial Intelligence Model "PANDAPro"
NCT06643715 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 100000
Last updated 2026-05-22
Summary
The purpose of this study is to build upon the previously developed deep learning-based non-contrast CT pancreatic cancer screening model, PANDA. The model will first undergo training and enhancement, followed by external validation across multiple centers. Subsequently, a large-scale real-world validation will be conducted at Zhejiang University's First Affiliated Hospital , the study will be divided into two rounds. In the first round, the performance of the PANDA model and the upgraded PANDA Pro model will be compared on consecutive retrospective real-world CT scans. In the second round, physicians will record the PANDA Pro results in real time to identify potential pancreatic lesions that may have been clinically missed. By leveraging clinical big data across different scenarios at Zhejiang University's First Affiliated Hospital, the study aims to validate the model's role in prompting and supplementing the diagnosis of PDAC in clinical practice, thereby laying the foundation for large-scale opportunistic screening of PDAC.
Conditions
Interventions
- DEVICE
-
PANDA Pro
Patients with PANDA Pro-reported PDAC positivity but no pancreatic lesions indicated in the imaging report, or those with positive pancreatic findings in the imaging report but no subsequent clinical intervention, will be identified as requiring follow-up. These patients will be recalled to the First Affiliated Hospital of Zhejiang University for further examination and diagnosis.
Sponsors & Collaborators
-
Lishui Municipal Central Hospital
collaborator OTHER_GOV -
Second Affiliated Hospital of Nanchang University
collaborator OTHER -
Zhejiang University
lead OTHER
Study Design
- Allocation
- NA
- Purpose
- DIAGNOSTIC
- Masking
- NONE
- Model
- SINGLE_GROUP
Eligibility
- Min Age
- 18 Years
- Max Age
- 90 Years
- Sex
- ALL
- Healthy Volunteers
- Yes
Timeline & Regulatory
- Start
- 2025-11-18
- Primary Completion
- 2026-05-18
- Completion
- 2027-08-01
Countries
- China
Study Locations
More Related Trials
-
Clinical Research on a Novel Deep-learning Based System in Pancreatic Endoscopic Ultrasound Scanning
NCT05792267 ·Status: RECRUITING ·Phase: NA
-
Validation of an AI-Assisted Pancreatic EUS System for Training Improvement: a Prospective, Multi-Center, Randomized Trial
NCT06790134 ·Status: RECRUITING ·Phase: NA
-
AI Assisted the Diagnosis of Pancreatic Solid Lesions
NCT05706415 ·Status: UNKNOWN
-
Multimodal Deep Learning Model Predicts Pancreatic Cancer Prognosis
NCT06760234 ·Status: COMPLETED
-
Diagnosis and Survival Prediction of Pancreatic Cancer by Machine Learning of Image Data
NCT05313854 ·Status: UNKNOWN
-
A Prospective Study of Liquid Biopsy for Pancreatic Cancer Early Detection
NCT06166147 ·Status: RECRUITING
-
A Cohort Study on Screening and Follow-up of High-risk Population of PDAC Based on EUS
NCT05621824 ·Status: NOT_YET_RECRUITING
-
A Multi-center Study on the Efficacy and Safety of AI-assisted Navigation System for Biliopancreatic EUS
NCT04892329 ·Status: UNKNOWN ·Phase: NA
-
Related Studies of Imaging Features and Prognosis Between Pancreatic Neuroendocrine Tumors and Pancreatic Cancer
NCT04977596 ·Status: COMPLETED
-
AI Derived Biomarker to Select Neoadjuvant Treatment for Borderline Resectable Pancreatic Ductal Adenocarcinoma
NCT06320717 ·Status: RECRUITING
-
Assessment of Early Pancreatic Cancer Prognosis by Minimal Residual Disease Using Multi-omics Approach
NCT06151691 ·Status: NOT_YET_RECRUITING
-
Investigate Role of Metabolic Imaging in Predicting Tumor Response/Outcome After Pancreatic CA Tx
NCT00767273 ·Status: COMPLETED ·Phase: NA
-
Establishment of a Predictive Model for Immunotherapy Response in Pancreatic Cancer
NCT07271823 ·Status: ACTIVE_NOT_RECRUITING
-
Comparison Between Base and Cover Slide From Endoscopic Ultrasound Guided Fine Needle Aspiration for Pancreatic Cancer
NCT02190071 ·Status: COMPLETED
-
Radiomics Based on Multimodal Imaging in Predicting Staging and Prognosis of Pancreatic Cancer
NCT04954378 ·Status: COMPLETED
-
Early Detection of Pancreatic Cancer
NCT05596435 ·Status: UNKNOWN
-
Artificial Intelligence-based Early Screening of Pancreatic Cancer and High Risk Tracing (ESPRIT-AI)
NCT04743479 ·Status: RECRUITING
-
A CT-based Radiomics Model to Predict Survival-graded Fibrosis in PDAC
NCT06267690 ·Status: COMPLETED
-
Endoscopic Ultrasound (EUS) Intratumoral Injection of CAR-NK Cells in the Treatment of Advanced Pancreatic Cancer
NCT06478459 ·Status: RECRUITING ·Phase: EARLY_PHASE1
-
A Deep Learning Radiomics Model for Predicting Occult Peritoneal Metastases of Pancreatic Adenocarcinoma
NCT06336694 ·Status: COMPLETED
-
Personalized Precision Diagnosis and Treatment of Pancreatic Cancer
NCT04373928 ·Status: UNKNOWN ·Phase: NA
-
Sequential Nutrition Intervention for Pancreatic Cancer Patients Undergoing CyberKnife Radiotherapy
NCT07057843 ·Status: COMPLETED ·Phase: NA
-
Differentiation Benign and Malignant Pancreatic Lesions
NCT06641947 ·Status: COMPLETED
-
Computed Tomography in Diagnosing Patients With Pancreatic or Hepatobiliary Cancer
NCT02361320 ·Status: RECRUITING ·Phase: NA
-
CCR2 PET for Pancreatic Cancer Imaging and Prediction of Response to Standard and CCR2-Targeted Therapy
NCT03851237 ·Status: COMPLETED ·Phase: PHASE1