Prediagnostic Image Data, Artificial Intelligence, and Pancreatic Cancer: A Tell-Tale Sign to Early Detection.

Journal: Pancreas
Published Date:

Abstract

Pancreatic cancer continues to be one of the deadliest malignancies and is the third leading cause of cancer-related mortality in the United States. Based on several models, it is projected to become the second leading cause of cancer-related deaths by 2030. Although the overall survival rate for patients diagnosed with pancreatic cancer is less than 10%, survival rates are increasing in those whose cancers are detected at an early stage, when intervention is possible. There are, however, no reliable biomarkers or imaging technology that can detect early-stage pancreatic cancer or accurately identify precursors that are likely to progress to malignancy. The Alliance of Pancreatic Cancer Consortia, a virtual consortium of researchers, clinicians, and advocacies focused on early diagnosis of pancreatic cancer, was formed in 2016 to provide a platform and resources to discover and validate biomarkers and imaging methods for early detection. The focus of discussion at the most recent alliance meeting was on imaging methods and the use of artificial intelligence for early detection of pancreatic cancer.

Authors

  • Matthew R Young
    From the Cancer Biomarker Research Group, Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Rockville, MD.
  • Natalie Abrams
  • Sharmistha Ghosh
  • Jo Ann S Rinaudo
  • Guillermo Marquez
  • Sudhir Srivastava
    Department of Biochemistry and Molecular Medicine, George Washington University, Washington, DC 20037, USA, Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Center for Bioinformatics and Information Technology, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20892-9760, USA, NASA Jet Propulsion Laboratory, Pasadena, CA, USA, Division of Cancer Prevention, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20892-9760, USA, Wellcome Trust Sanger Institute, Cambridge, UK and McCormick Genomic and Proteomic Center, George Washington University, Washington, DC 20037, USA.