Effectiveness of Radiomics-Based Machine Learning Models in Differentiating Pancreatitis and Pancreatic Ductal Adenocarcinoma: Systematic Review and Meta-Analysis.

Journal: Journal of medical Internet research
Published Date: Jul 31, 2025

Abstract

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) and mass-forming pancreatitis (MFP) share similar clinical, laboratory, and imaging features, making accurate diagnosis challenging. Nevertheless, PDAC is highly malignant with a poor prognosis, whereas MFP is an inflammatory condition typically responding well to medical or interventional therapies. Some investigators have explored radiomics-based machine learning (ML) models for distinguishing PDAC from MFP. However, systematic evidence supporting the feasibility of these models is insufficient, presenting a notable challenge for clinical application.

Authors

  • Lechang Zhang
    Department of Gastroenterology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 324 Jingwu Weiqi Rd, Jinan, 250021, China, 86 13853121769.
  • Dewei Li
    School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, China.
  • Tong Su
    Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
  • Tong Xiao
    College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, PR China; Shanghai Aquatic Product Processing and Storage Engineering Technology Research Center, Shanghai 201306, PR China; Laboratory of Quality and Safety Risk Assessment of Aquatic Products Storage and Preservation, Ministry of Agriculture, Shanghai 201306, PR China.
  • Shulei Zhao
    Department of Gastroenterology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 324 Jingwu Weiqi Rd, Jinan, 250021, China, 86 13853121769.

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