Machine learning defined diagnostic criteria for differentiating pituitary metastasis from autoimmune hypophysitis in patients undergoing immune checkpoint blockade therapy.

Journal: European journal of cancer (Oxford, England : 1990)
PMID: 31415986

Abstract

PURPOSE: New-onset pituitary gland lesions are observed in up to 18% of cancer patients undergoing treatment with immune checkpoint blockers (ICB). We aimed to develop and validate an imaging-based decision-making algorithm for use by the clinician that helps differentiate pituitary metastasis (PM) from ICB-induced autoimmune hypophysitis (HP).

Authors

  • Ahmed Mekki
    Department of Radiology, Gustave Roussy Cancer Campus, Villejuif, France; Université Paris-Saclay, Paris, France; Department of Neuroradiology, C.H.U Bicêtre AP-HP, Le Kremlin-Bicêtre, France. Electronic address: ahmekki@gmail.com.
  • Laurent Dercle
    Department of Radiology, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032; Gustave Roussy, Université Paris-Saclay, Université Paris-Saclay, Département D'imagerie Médicale, Villejuif, France.
  • Philip Lichtenstein
    Department of Radiology, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032.
  • Ghaida Nasser
    Department of Neuroradiology, C.H.U Bicêtre AP-HP, Le Kremlin-Bicêtre, France.
  • Aurélien Marabelle
    Drug Development Department, Gustave Roussy, Villejuif, France.
  • Stéphane Champiat
    Drug Development Department, Gustave Roussy, Villejuif, France.
  • Emilie Chouzenoux
    Center for Visual Computing, CentraleSupelec, INRIA Saclay, Gif-sur-Yvette, 91190, France.
  • Corinne Balleyguier
    Department of Radiology, Gustave Roussy Cancer Campus, Villejuif, France; Université Paris-Saclay, Paris, France.
  • Samy Ammari
    Service de Radiologie, Gustave-Roussy, Université Paris-Saclay, Villejuif, France.

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