Background: Early identification of cervical lymph node (LN) metastases cervical lymph node metastases (CLNM) is crucial in the management of differentiated thyroid cancer differentiated thyroid cancer (DTC) as it influences the indication and the extent of surgery with an impact on the recurrence risk and overall survival. The present review focused on novel sensitive and specific diagnostic techniques, by searching through online databases like MEDLINE and Scopus up to February 2022.
Areas covered: The techniques identified included contrast-enhanced ultrasound (CEUS), dosage of fragment 21-1 of cytokeratin 19 (CYFRA 21-1) in lymph node fine needle aspiration washout, sentinel LN biopsy (SNB), and artificial intelligence (AI) - deep learning applied to ultrasonography and computed tomography. These methods displayed widely varying sensitivity and specificity results, ranging from approximately 60-100%. This variability is mainly due to the operator's experience because of the great complexity of execution of these new techniques, which require a long-learning curve.
Expert opinion: Despite the appearance of many candidate methods to improve the detection of metastatic lymph nodes, none seem to be clearly superior to the tools currently used in clinical practice and FNA-Tg measurement remains the more accurate tool to detect neck recurrences and CLNM from DTC.
Keywords: Artificial intelligence (AI) - deep learning; CYFRA 21-1; Thyroid cancer; contrast-enhanced ultrasound; fine needle aspiration washout; lymph node metastases; sentinel lymph node biopsy; thyroglobulin.