Title:Ultrasound-based Radiomics for Predicting Metastasis in the Lymph Nodes
Posterior to the Right Recurrent Laryngeal Nerve in Patients with Papillary
Thyroid Cancer
Volume: 20
Author(s): Bo Shen, Chao Zhou, Chaoli Xu*, Bin Yang, Xiaoman Wu, Xiaodan Fu, Siyue Liu, Jiaying Sun, Yingdong Xie and Zheng Zhu
Affiliation:
- Department of Ultrasound Diagnostics, The First Affiliated Hospital of Nanjing Medical University, Nanjing Jiangsu 210029, P. R. China
Keywords:
Radiomics, Papillary thyroid carcinoma, PTC, Lymph nodes posterior to the right recurrent laryngeal nerve, LN-prRLNs, Ultrasound.
Abstract:
Background:
Dissection of the lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLNs) in papillary thyroid cancer (PTC) remains
controversial.
Objective:
This study aimed to determine the capability of ultrasonography (US)-based radiomics for presurgical prediction of metastasis in LN-prRLNs in
PTC.
Methods:
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, were also
developed for the presurgical prediction of metastasis in LN-prRLNs.
Results:
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: 0.826) and radiomics model (AUC: 0.759).
Conclusion:
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 in decision-making regarding LN-prRLN dissection.