Ultrasound-based Radiomics for Predicting Metastasis in the Lymph Nodes Posterior to the Right Recurrent Laryngeal Nerve in Patients with Papillary Thyroid Cancer.

Abstract

Dissection of the lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLNs) in papillary thyroid cancer (PTC) remains controversial. This study aimed to determine the capability of ultrasonography (US)-based radiomics for presurgical prediction of metastasis in LN-prRLNs in PTC. Patients were retrospectively enrolled and pathologically confirmed as LN-prRLN metastasis with PTC after surgery. Radiomic analysis based on preoperative US images with manual segmentation of targets was used to develop a radiomics model. US features described in ACR TI-RADS were collected to construct a clinical model. The Radiomics model, a combined model integrating radiomics and clinical model, was also developed for the presurgical prediction of metastasis in LN-prRLNs. A total of 570 patients, including 488 patients with non-LN-prRLN metastasis and 82 with LN-prRLN metastasis, were assessed. The 15 topperforming features finally remained significant for constructing the radiomics model. The combined model showed that US measured tumor size (OR: 1.036, P = 0.044), US suspected lateral lymph node metastasis (OR: 2.247, P = 0.009), multifocality (OR: 1.920, P = 0.021), Delphian lymph node metastasis (DLNM) (OR: 2.300, P = 0.039), VIa compartment metastasis (OR: 5.357, P = 0.000), the radiomics score (OR: 1.003, P = 0.001) were significant risk factors for predicting LN-prRLN metastasis. The combined model achieved a higher AUC of 0.849 than that of the clinical model (AUC: 0.759) and radiomics model (AUC: 0.826). The US-based radiomics combined model can more effectively predict LN-prRLN metastasis in PTCs patients preoperatively. This approach had the potential to assist surgeons indecision-making regarding LN-prRLN dissection.