Thyroid Nodule Characterization: Overview and State of the Art of Diagnosis with Recent Developments, from Imaging to Molecular Diagnosis and Artificial Intelligence.
Emanuele DavidHektor GrazhdaniGiuliana TattaresuAlessandra PittariPietro Valerio FotiStefano PalmucciCorrado SpatolaMaria Chiara Lo GrecoCorrado InìFrancesco TiralongoDavide CastiglioneGiampiero MastroeniSilvia GigliAntonio BasilePublished in: Biomedicines (2024)
Ultrasound (US) is the primary tool for evaluating patients with thyroid nodules, and the risk of malignancy assessed is based on US features. These features help determine which patients require fine-needle aspiration (FNA) biopsy. Classification systems for US features have been developed to facilitate efficient interpretation, reporting, and communication of thyroid US findings. These systems have been validated by numerous studies and are reviewed in this article. Additionally, this overview provides a comprehensive description of the clinical and laboratory evaluation of patients with thyroid nodules, various imaging modalities, grayscale US features, color Doppler US, contrast-enhanced US (CEUS), US elastography, FNA biopsy assessment, and the recent introduction of molecular testing. The potential of artificial intelligence in thyroid US is also discussed.
Keyphrases
- drug induced
- artificial intelligence
- fine needle aspiration
- ultrasound guided
- machine learning
- deep learning
- big data
- contrast enhanced
- magnetic resonance imaging
- end stage renal disease
- high resolution
- computed tomography
- chronic kidney disease
- ejection fraction
- newly diagnosed
- prognostic factors
- peritoneal dialysis
- diffusion weighted
- single molecule
- contrast enhanced ultrasound
- diffusion weighted imaging
- fluorescence imaging
- electronic health record