Artificial Intelligence-powered Low-Dose Computed Tomography for Screening of Pancreatic Cancer

Condition(s) studied

Investigational drug(s) / intervention(s)

Diagnostic Evaluation for Positive AI Findings: MDT will review positive AI findings (including PDAC, pancreatic precursor lesions and benign lesion) cases to determine next steps: (1) Suspected PDAC and pancreatic precursor lesions are referred for hospital examination with diagnostic results collected; (2) Benign lesion cases receive personalized monitoring until endpoint events or study end; (3) Cases with positive AI findings but MDT-confirmed normal pancreatic issues receive at least one year of follow-up. If any abnormal results arise, management will transition to either plan (1) or (2).

Study summary

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with early diagnosis crucial for improving survival. Due to the absence of effective screening methods, most patients are diagnosed at advanced stages. The population undergoing low-dose computed tomography (LDCT) screening significantly overlaps with those at high risk for PDAC; however, traditional imaging methods have limited sensitivity for detecting pancreatic lesions. This study utilizes the Pancreatic Cancer Detection with Artificial Intelligence (PANDA) system to enhance LDCT for pancreatic cancer screening in a prospective, multicenter, observational cohort. PANDA will analyze LDCT images, followed by a multidisciplinary team (MDT) reassessment of abnormal interpretations. Based on MDT evaluation, individuals will be recalled for further examination, placed under a personalized follow-up plan, or monitored for at least one year. The primary outcomes include pancreatic cancer detection rate, positive predictive value, consensus rate, and recall rate, while secondary outcomes focus on early-stage cancers, resectable tumors, and safety indicators such as false positive rates and unnecessary procedures. This study aims to assess the effectiveness and safety of AI-assisted LDCT for PDAC detection, providing a practical solution for improving public health and enhancing early diagnostic capabilities.

Eligibility

Primary outcome measure(s)

• Pancreatic cancer detection rate — 2 years
  The proportion of individuals with abnormal AI assessment confirmed as pancreatic cancer or precancerous lesions among the total screened population
• Positive predictive value — 2 years
  The proportion of individuals with abnormal AI assessment confirmed as pancreatic cancer or precancerous lesions among all individuals with abnormal AI assessment
• Consensus rate — 2 years
  The proportion of individuals with abnormal AI assessment deemed suspicious for pancreatic cancer or precancerous lesions by MDT requiring recall among the total screened population.
• Recall rate — 2 years
  The proportion of individuals actually recalled among the total screened population.

Trial sites (5)

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