Effectiveness of Artificial Intelligence in detecting sinonasal pathology using clinical imaging modalities: a systematic review.

Journal: Rhinology
Published Date: Aug 1, 2025

Abstract

BACKGROUND: Sinonasal pathology can be complex and requires a systematic and meticulous approach. Artificial Intelligence (AI) has the potential to improve diagnostic accuracy and efficiency in sinonasal imaging, but its clinical applicability remains an area of ongoing research. This systematic review evaluates the methodologies and clinical relevance of AI in detecting sinonasal pathology through radiological imaging.

Authors

  • D-P Petsiou
    Department of Otolaryngology - Head and Neck Surgery, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece.
  • D Spinos
    Department of Cancer and Genomics, School of Medicine, University of Birmingham, Birmingham, United Kingdom.
  • A Martinos
    Department of Otolaryngology - Head and Neck Surgery, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece.
  • J Muzaffar
    Department of Otolaryngology, Head and Neck Surgery, University Hospitals of Birmingham, Birmingham, United Kingdom.
  • G Garas
    Surgical Innovation Centre, Department of Surgery and Cancer, Imperial College London, St. Mary's Hospital, London, United Kingdom.
  • C Georgalas
    Department of Head, School of Medicine, University of Nicosia, Nicosia, Cyprus.

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