Deep Learning and Automatic Differentiation of Pancreatic Lesions in Endoscopic Ultrasound: A Transatlantic Study.

Journal: Clinical and translational gastroenterology
PMID: 39324610

Abstract

INTRODUCTION: Endoscopic ultrasound (EUS) allows for characterization and biopsy of pancreatic lesions. Pancreatic cystic neoplasms (PCN) include mucinous (M-PCN) and nonmucinous lesions (NM-PCN). Pancreatic ductal adenocarcinoma (P-DAC) is the commonest pancreatic solid lesion (PSL), followed by pancreatic neuroendocrine tumor (P-NET). Although EUS is preferred for pancreatic lesion evaluation, its diagnostic accuracy is suboptimal. This multicentric study aims to develop a convolutional neural network (CNN) for detecting and distinguishing PCN (namely M-PCN and NM-PCN) and PSL (particularly P-DAC and P-NET).

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.
  • Mariano González-Haba
    Hospital Universitario Puerta de Hierro Majadahonda, Madrid, Spain.
  • Jessica Widmer
    New York University Langone Hospital, New York, New York, USA.
  • Francisco Mendes
    Precision Medicine Unit, Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, 4200-427 Porto, Portugal.
  • Tamas Gonda
    Division of Gastroenterology and Hepatology, New York University, NY, USA.
  • Belen Agudo
    Hospital Universitario Puerta de Hierro Majadahonda, Madrid, Spain.
  • Tiago Ribeiro
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • Antonio Costa
    Department of Pharmaceutical Sciences, University of Connecticut, Storrs, CT 06269, USA.
  • Yousef Fazel
    New York University Langone Hospital, New York, New York, USA.
  • Marcos Eduardo Lera
    Hospital Das Clinicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
  • Eduardo Horneaux de Moura
    Hospital Das Clinicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
  • Matheus Ferreira de Carvalho
    Hospital Das Clinicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
  • Alexandre Bestetti
    Hospital Das Clinicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
  • João Afonso
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • Miguel Martins
    Precision Medicine Unit, Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, 4200-427 Porto, Portugal.
  • Maria João Almeida
    Department of Gastroenterology, Precision Medicine Unit, São João University Hospital, Porto, Portugal.
  • Filipe Vilas-Boas
    Department of Gastroenterology, Precision Medicine Unit, São João University Hospital, Porto, Portugal.
  • Pedro Moutinho-Ribeiro
    Department of Gastroenterology, Precision Medicine Unit, São João University Hospital, Porto, Portugal.
  • Susana Lopes
    Department of Gastroenterology, Precision Medicine Unit, São João University Hospital, Porto, Portugal.
  • Joana Fernandes
    Faculty of Engineering of the University of Porto, Porto, Portugal.
  • João Ferreira
    Department of Mechanical Engineering, Faculty of Engineering of the University of Porto, Porto, Portugal.
  • Guilherme Macedo
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.

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