EVALUATING THE DIAGNOSTIC EFFICIENCY OF ULTRASOUND AND THYROID PROFILE IN HASHIMOTO’S THYROIDITIS

Abstract

Introduction: Hashimoto’s thyroiditis (HT) is the most common autoimmune thyroid disorder and is frequently associated with thyroid nodules, which may complicate malignancy risk assessment. Differentiating benign from malignant nodules in the background of HT remains clinically challenging due to diffuse inflammatory changes that affect ultrasound interpretation.

Objective: This systematic literature review aimed to evaluate the diagnostic efficiency of ultrasound modalities and thyroid profile parameters in detecting and differentiating thyroid nodules in patients with Hashimoto’s thyroiditis.

Methodology: A systematic literature review was conducted following PRISMA guidelines. Electronic databases including PubMed, Google Scholar, and Scopus were searched for relevant studies published after 2015. Eighteen eligible studies were selected based on predefined inclusion and exclusion criteria. Data were extracted and categorized into conventional ultrasound systems, advanced imaging techniques, artificial intelligence models, and laboratory biomarkers.

Results: Conventional TI-RADS systems showed high sensitivity but moderate specificity. Advanced techniques such as contrast-enhanced ultrasound and elastography improved diagnostic accuracy. Radiomics and deep learning models demonstrated the highest predictive performance, with AUC values exceeding 0.90 in several studies. Serum thyroid antibodies supported diagnosis but had limited independent sensitivity.

Conclusion: A multimodal diagnostic approach integrating advanced ultrasound and AI-based models provides improved accuracy in evaluating thyroid nodules in HT.