Nodular Thyroid Disease in the Era of Precision Medicine.

Journal: Frontiers in endocrinology
Published Date:

Abstract

Management of thyroid nodules in the era of precision medicine is continuously changing. Neck ultrasound plays a pivotal role in the diagnosis and several ultrasound stratification systems have been proposed in order to predict malignancy and help clinicians in therapeutic and follow-up decision. Ultrasound elastosonography is another powerful diagnostic technique and can be an added value to stratify the risk of malignancy of thyroid nodules. Moreover, the development of new techniques in the era of "Deep Learning," has led to a creation of machine-learning algorithms based on ultrasound examinations that showed similar accuracy to that obtained by expert radiologists. Despite new technologies in thyroid imaging, diagnostic surgery in 50-70% of patients with indeterminate cytology is still performed. Molecular tests can increase accuracy in diagnosis when performed on "indeterminate" nodules. However, the more updated tools that can be used to this purpose in order to "rule out" (Afirma GSC) or "rule in" (Thyroseq v3) malignancy, have a main limitation: the high costs. In the last years various image-guided procedures have been proposed as alternative and less invasive approaches to surgery for symptomatic thyroid nodules. These minimally invasive techniques (laser and radio-frequency ablation, high intensity focused ultrasound and percutaneous microwave ablation) results in nodule shrinkage and improvement of local symptoms, with a lower risk of complications and minor costs compared to surgery. Finally, ultrasound-guided ablation therapy was introduced with promising results as a feasible treatment for low-risk papillary thyroid microcarcinoma or cervical lymph node metastases.

Authors

  • Dario Tumino
    Endocrinology Unit, Department of Clinical and Experimental Medicine, Garibaldi-Nesima Medical Center, University of Catania, Catania, Italy.
  • Giorgio Grani
    Department of Translational and Precision Medicine, Sapienza University of Rome, Rome, Italy.
  • Marta Di Stefano
    Division of Endocrine and Metabolic Diseases, Department of Clinical Sciences and Community Health, IRCCS Istituto Auxologico Italiano, Università degli Studi di Milano, Milan, Italy.
  • Maria Di Mauro
    Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy.
  • Maria Scutari
    Endocrinology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.
  • Teresa Rago
    Endocrinology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.
  • Laura Fugazzola
    Division of Endocrine and Metabolic Diseases, Department of Clinical Sciences and Community Health, IRCCS Istituto Auxologico Italiano, Università degli Studi di Milano, Milan, Italy.
  • Maria Grazia Castagna
    Department of Medical, Surgical and Neurological Sciences, University of Siena, Siena, Italy.
  • Fabio Maino
    Department of Medical, Surgical and Neurological Sciences, University of Siena, Siena, Italy.

Keywords

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