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• Clinical Article •
The value of preoperative multi-parametric MR features using surface coil exclusive designed for thyroid gland in predicting the metastatic status of regional lymph nodes in thyroid cancer
XIE Yongsheng  WANG Shixu  ZHANG Miaoru  LIU Zhou  Huerman•Bahebietike   LIANG Longfei  LONG Li  DENG Wenming  WEI Minghui  LUO Dehong 

#Co first author: WANG Shixu DOI:10.12015/issn.1674-8034.2021.04.004.


[Abstract] Objective To investigate the value of preoperative multi-parametric magnetic resonance imaging (MRI) features using surface coil exclusively designed for thyroid gland in predicting the metastatic status of regional lymph nodes in thyroid cancer. Materials andMethods In this retrospective analysis, 51 patients with pathologically confirmed thyroid cancer was enrolled. All patients had undertaken thyroid lesion resection with radical neck dissection and preoperative 3.0 T contrast enhanced MRI scan. With pathology as reference, MR findings of non-metastatic and metastatic lymph nodes had been analyzed to construct a predicting model for diagnosing the metastatic status of each lymph node. The quantitative data were compared by Mann-Whitney U test or t test, while the categorical data were compared by χ2 test. Multivariate logistic regression was used to construct a combined model for predicting the metastatic status of each lymph node, with diagnostic performance evaluated using receiver operating characteristic curve.Results In total, we analyzed 135 lymph nodes in 51 patients, including 74 metastatic lymph nodes and 61 non-metastatic lymph nodes. There was statistically significant difference between metastatic and non-metastatic lymph nodes in size, ADC value, signal intensity on T1-wighted and fat-suppression T2-weighted imaging, shape, margin, presence of cystic degeneration, the degree of enhancement (all P<0.05). Furthermore, heterogeneous signal intensity on fat-suppression T2-weighted imaging, marked enhancement, and low ADC value (<0.91×10-3 mm2/s) were identified as three independent predictive factors of metastatic lymph nodes. A model combining these independent factors yielded the diagnostic performance with an area under the curve of 0.93, a sensitivity of 82.4% and a specificity of 88.5%. The size including long and short-axis diameter of non-metastatic level VI lymph nodes in cases of thyroid cancer complicated with Hashimoto's thyroiditis were larger than that of thyroid cancer cases without Hashimoto's thyroiditis.Conclusions The preoperative multi-parametric MR features have shown satisfactory diagnostic performance in predicting the status of regional lymph nodes in thyroid cancer. In particular, metastatic lymph nodes tend to have heterogeneous signal intensity on fat-suppression T2-weighted imaging, marked enhancement and lower ADC value, which could provide valuable evidence in assisting preoperatively clinical decision-making.
[Keywords] thyroid cancer；lymph nodes metastasis；magnetic resonance imaging；surface coil

XIE Yongsheng1   WANG Shixu2   ZHANG Miaoru1   LIU Zhou1   Huerman•Bahebietike 2   LIANG Longfei2   LONG Li1   DENG Wenming1   WEI Minghui2*   LUO Dehong1, 3*  

1 National Cancer Center/National Clinical Research Center for Cancer/Department of Radiology, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518000, China

2 National Cancer Center/National Clinical Research Center for Cancer/Department of Head and Neck Surgery, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518000, China

3 National Cancer Center/National Clinical Research Center for Cancer/Department of Radiology, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China

Luo DH, E-mail: cjr.luodehong@vip.163.com Wei MH, E-mail: Minghuiwei@163.com

Conflicts of interest   None.

This work was part of Cancer Hospital, Chinese Academy of Medical Sciences, Shenzhen Center/ShenZhen Cancer Hospital Research Project (No. SZ2020ZD005).
Received  2020-09-05
Accepted  2020-11-18
DOI: 10.12015/issn.1674-8034.2021.04.004
#Co first author: WANG Shixu DOI:10.12015/issn.1674-8034.2021.04.004.

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