Artificial intelligence for automatic diagnosis of biliary stricture malignancy status in single-operator cholangioscopy: a pilot study.

Journal: Gastrointestinal endoscopy
Published Date: Feb 1, 2022

Abstract

BACKGROUND AND AIMS: The diagnosis and characterization of biliary strictures (BSs) is challenging. The introduction of digital single-operator cholangioscopy (DSOC) that allows direct visual inspection of the lesion and targeted biopsy sampling significantly improved the diagnostic yield in patients with indeterminate BSs. However, the diagnostic efficiency of DSOC remains suboptimal. Convolutional neural networks (CNNs) have shown great potential for the interpretation of medical images. We aimed to develop a CNN-based system for automatic detection of malignant BSs in DSOC images.

Authors

  • Miguel Mascarenhas Saraiva
    Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, 4200-427, Porto, Portugal; WGO Gastroenterology and Hepatology Training Center, Porto, Portugal; Faculty of Medicine of the University of Porto, Alameda Professor Hernâni Monteiro, Porto 4200-427, Portugal.
  • Tiago Ribeiro
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • João P S Ferreira
    Department of Mechanical Engineering, Faculty of Engineering of the University of Porto, Porto, Portugal.
  • Filipe Vilas Boas
    Department of Gastroenterology, São João University Hospital, Porto, Portugal; WGO Gastroenterology and Hepatology Training Center, Porto, Portugal; Department of Gastroenterology, Faculty of Medicine, University of Porto, Porto, Portugal.
  • João Afonso
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • Ana Luísa Santos
    Department of Gastroenterology, São João University Hospital, Porto, Portugal; WGO Gastroenterology and Hepatology Training Center, Porto, Portugal; Department of Gastroenterology, Faculty of Medicine, University of Porto, Porto, Portugal.
  • Marco P L Parente
    Department of Mechanical Engineering, Faculty of Engineering of the University of Porto, Porto, Portugal.
  • Renato N Jorge
    Department of Mechanical Engineering, Faculty of Engineering of the University of Porto, Porto, Portugal.
  • Pedro Pereira
    Department of Gastroenterology, São João University Hospital, Porto, Portugal; WGO Gastroenterology and Hepatology Training Center, Porto, Portugal; Department of Gastroenterology, Faculty of Medicine, University of Porto, Porto, Portugal.
  • Guilherme Macedo
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.

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