An [18F]FDG-PET/CT deep learning method for fully automated detection of pathological mediastinal lymph nodes in lung cancer patients.

Journal: European journal of nuclear medicine and molecular imaging
Published Date: Sep 14, 2021

Abstract

PURPOSE: The identification of pathological mediastinal lymph nodes is an important step in the staging of lung cancer, with the presence of metastases significantly affecting survival rates. Nodes are currently identified by a physician, but this process is time-consuming and prone to errors. In this paper, we investigate the use of artificial intelligence-based methods to increase the accuracy and consistency of this process.

Authors

  • David Wallis
    Laboratoire D'Imagerie Translationnelle en Oncologie, U1288 Inserm, Institut Curie, PSL, Université Paris Saclay, Paris, France. wallisphd@gmail.com.
  • Michaël Soussan
    Department of Nuclear Medicine, Avicenne Hospital, APHP, Bobigny, Paris, France.
  • Maxime Lacroix
    Department of Nuclear Medicine, Avicenne Hospital, APHP, Bobigny, Paris, France.
  • Pia Akl
    Laboratoire D'Imagerie Translationnelle en Oncologie, U1288 Inserm, Institut Curie, PSL, Université Paris Saclay, Paris, France.
  • Clément Duboucher
    Department of Nuclear Medicine, Avicenne Hospital, APHP, Bobigny, Paris, France.
  • Irène Buvat
    Imagerie Moléculaire In Vivo, CEA, Inserm, Univ Paris Sud, CNRS, Université Paris Saclay, Orsay, France.

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