Beyond genomics: artificial intelligence-powered diagnostics for indeterminate thyroid nodules-a systematic review and meta-analysis.

Journal: Frontiers in endocrinology
Published Date: Jan 1, 2025

Abstract

INTRODUCTION: In recent years, artificial intelligence (AI) tools have become widely studied for thyroid ultrasonography (USG) classification. The real-world applicability of these developed tools as pre-operative diagnostic aids is limited due to model overfitting, clinician trust, and a lack of gold standard surgical histology as ground truth class label. The ongoing dilemma within clinical thyroidology is surgical decision making for indeterminate thyroid nodules (ITN). Genomic sequencing classifiers (GSC) have been utilised for this purpose; however, costs and availability preclude universal adoption creating an inequity gap. We conducted this review to analyse the current evidence of AI in ITN diagnosis without the use of GSC.

Authors

  • Karishma Jassal
    Monash University Endocrine Surgery Unit, Department of General Surgery, Alfred Hospital, Melbourne, Victoria, Australia.
  • Melissa Edwards
    Department of Surgery, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
  • Afsaneh Koohestani
    Monash University Endocrine Surgery Unit, Department of General Surgery, Alfred Hospital, Melbourne, Victoria, Australia.
  • Wendy Brown
    Department of Surgery, Central Clinical School, Monash University, Melbourne, Victoria, Australia.
  • Jonathan W Serpell
    Monash University Endocrine Surgery Unit, Alfred Hospital, Melbourne, VIC, Australia.
  • James C Lee
    Monash University Endocrine Surgery Unit, Department of General Surgery, Alfred Hospital, Melbourne, Victoria, Australia.

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