Oncoradiology, Volume. 34, Issue 3, 290(2025)
Application and significance of multimodal ultrasound for preoperative assessment of metastasis in lymph nodes posterior to the right recurrent laryngeal nerve in papillary carcinoma of the thyroid
The incidence of thyroid cancer has gradually increased in recent years. The lymph node posterior to the right recurrent laryngeal nerve (LN-prRLN), which is characterized by higher metastasis rate, poor preoperative diagnosis rate, and high correlation with cancer progression, is one of the important pathways for lymph node metastasis in papillary carcinoma of the thyroid (PTC). Due to the complication accompanying LN-prRLN dissection, accurate evaluation of LN-prRLN involvement is significant for the surgical approach and patient prognosis. Ultrasound, as the primary choice for PTC and its cervical lymph node metastasis, plays an important role in the preoperative diagnosis and evaluation of LN-prRLN and has a broad application prospect with the development of artificial intelligence. Conventional ultrasound can directly identify and localize suspicious lymph nodes, combined with contrastenhanced ultrasound and ultrasound elastography to increase the accuracy of assessment. Lymphatic contrast-enhanced ultrasound is extremely advantageous for the display of LN-prRLN, and emerging ultrasound imaging histology can objectively and quantitatively extract features to construct a joint prediction model for LN-prRLN metastasis to aid in diagnosis. This article reviewed the current status of the application of ultrasound and its new technologies in the preoperative diagnosis and evaluation of LN-prRLN metastasis.
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ZHENG Yiman, XU Chaoli, YE Xinhua. Application and significance of multimodal ultrasound for preoperative assessment of metastasis in lymph nodes posterior to the right recurrent laryngeal nerve in papillary carcinoma of the thyroid[J]. Oncoradiology, 2025, 34(3): 290
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Received: Jan. 22, 2025
Accepted: Aug. 22, 2025
Published Online: Aug. 22, 2025
The Author Email: YE Xinhua (yexh-0125@163.com)