Development of an artificial intelligence-based convolutional neural network for sellar barrier classification using magnetic resonance imaging.

Radiology Pediatrics Endocrinology
Journal: Surgical neurology international
Published Date: Jan 1, 2025

Abstract

BACKGROUND: This study aims to develop an artificial intelligence (AI) model using convolutional neural networks and transfer learning to classify sellar barriers as strong, mixed, or weak based on magnetic resonance imaging (MRI). Accurate classification is essential for surgical planning in endoscopic endonasal approaches for pituitary adenomas, as variations in the sellar barrier can lead to complications such as cerebrospinal fluid leaks.

Authors

  • Lautaro Ezequiel De Bartolo Villar
    Faculty of Medicine, University of Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina.
  • Matias Baldoncini
    Department of Neurosurgery, San Fernando Hospital, San Fernando, Argentina.
  • Alvaro Campero
    Department of Neurosurgery, Hospital Padilla de Tucuman, Tucuman, Argentina.
  • Mickaela Echavarria Demichelis
    Department of Neurosurgery, San Fernando Hospital, San Fernando, Argentina.

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