Using Ultrasound Features and Radiomics Analysis to Predict Lymph Node Metastasis in Patients with Thyroid Cancer

Overview

Journal BMC Surg

Publisher Biomed Central

Specialty General Surgery

Date 2020 Dec 5

PMID 33276765

Citations 34

Authors

Fu Li

Denghua Pan

Yun He

Yuquan Wu

Jinbo Peng

Jiehua Li

Ye Wang

Hong Yang

Junqiang Chen

Affiliations

Soon will be listed here.

Abstract

Background: Lymph node metastasis (LNM) is an important factor for thyroid cancer patients' treatment and prognosis. The aim of this study was to explore the clinical value of ultrasound features and radiomics analysis in predicting LNM in thyroid cancer patients before surgery.

Methods: The characteristics of ultrasound images of 150 thyroid nodules were retrospectively analysed. All nodules were confirmed as thyroid cancer. Among the assessed patients, only one hundred and twenty-six patients underwent lymph node dissection. All patients underwent an ultrasound examination before surgery. In the radiomic analysis, the area of interest was identified from selected ultrasound images by using ITK-SNAP software. The radiomic features were extracted by using Ultrosomics software. Then, the data were classified into a training set and a validation set. Hypothetical tests and bagging were used to build the model. The diagnostic performance of different ultrasound features was assessed, a radiomic analysis was conducted, and a receiver operating characteristic (ROC) curve analysis was performed to explore the diagnostic accuracy.

Results: Regarding the prediction of LNM, the ROC curves showed that the area under the curve (AUC) values of an irregular shape and microcalcification were 0.591 (P = 0.059) and 0.629 (P = 0.007), respectively. In the radiomics analysis, in the training set, the AUC value of LNM was 0.759, with a sensitivity of 0.90 and a specificity of 0.860. In the verification set, the AUC was 0.803, with a sensitivity of 0.727 and a specificity of 0.800.

Conclusions: Microcalcification and an irregular shape are predictors of LNM in thyroid carcinoma patients. In addition, radiomics analysis has promising value in screening meaningful ultrasound features in thyroid cancer patients with LNM. Therefore, the prediction of LNM based on ultrasound features and radiomic features is useful for making appropriate decisions regarding surgery and interventions before thyroid carcinoma surgery.

Citing Articles

The application of a clinical-multimodal ultrasound radiomics model for predicting cervical lymph node metastasis of thyroid papillary carcinoma.

Liu C, Yang S, Xue T, Zhang Q, Zhang Y, Zhao Y Front Oncol. 2025; 14:1507953.

PMID: 39896179 PMC: 11782237. DOI: 10.3389/fonc.2024.1507953.

Combined model integrating clinical, radiomics, BRAF and ultrasound for differentiating between benign and malignant indeterminate cytology (Bethesda III) thyroid nodules: a bi-center retrospective study.

Zhong L, Shi L, Lai J, Hu Y, Gu L Gland Surg. 2024; 13(11):1954-1964.

PMID: 39678423 PMC: 11635559. DOI: 10.21037/gs-24-310.

Preoperative High Level of Circulating Tumor Cells is an Independent Risk Factor for Central Lymph Node Metastasis in Papillary Thyroid Carcinoma with Maximum Lesion Diameter ≤1.0 cm.

Yu M, Deng J, Gu Y, Lai Y Int J Gen Med. 2024; 17:4907-4916.

PMID: 39473633 PMC: 11520918. DOI: 10.2147/IJGM.S487992.

Radiomics and deep learning for large volume lymph node metastasis in papillary thyroid carcinoma.

Ni Z, Zhou T, Fang H, Lin X, Xing Z, Li X Gland Surg. 2024; 13(9):1639-1649.

PMID: 39421056 PMC: 11480870. DOI: 10.21037/gs-24-308.

Machine learning model for non-alcoholic steatohepatitis diagnosis based on ultrasound radiomics.

Xia F, Wei W, Wang J, Duan Y, Wang K, Zhang C BMC Med Imaging. 2024; 24(1):221.

PMID: 39164667 PMC: 11334577. DOI: 10.1186/s12880-024-01398-y.

References

Wu S, Zheng J, Li Y, Yu H, Shi S, Xie W . A Radiomics Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Bladder Cancer. Clin Cancer Res. 2017; 23(22):6904-6911. DOI: 10.1158/1078-0432.CCR-17-1510. View

Kim E, Park C, Chung W, Oh K, Kim D, Lee J . New sonographic criteria for recommending fine-needle aspiration biopsy of nonpalpable solid nodules of the thyroid. AJR Am J Roentgenol. 2002; 178(3):687-91. DOI: 10.2214/ajr.178.3.1780687. View

Jeong H, Baek C, Son Y, Choi J, Kim H, Ko Y . Integrated 18F-FDG PET/CT for the initial evaluation of cervical node level of patients with papillary thyroid carcinoma: comparison with ultrasound and contrast-enhanced CT. Clin Endocrinol (Oxf). 2006; 65(3):402-7. DOI: 10.1111/j.1365-2265.2006.02612.x. View

Kumar V, Gu Y, Basu S, Berglund A, Eschrich S, Schabath M . Radiomics: the process and the challenges. Magn Reson Imaging. 2012; 30(9):1234-48. PMC: 3563280. DOI: 10.1016/j.mri.2012.06.010. View

Watanabe K, Igarashi T, Ashida H, Ogiwara S, Ohta T, Uchiyama M . Diagnostic value of ultrasonography and TI-201/Tc-99m dual scintigraphy in differentiating between benign and malignant thyroid nodules. Endocrine. 2018; 63(2):301-309. DOI: 10.1007/s12020-018-1768-0. View

Abbasian Ardakani A, Reiazi R, Mohammadi A . A Clinical Decision Support System Using Ultrasound Textures and Radiologic Features to Distinguish Metastasis From Tumor-Free Cervical Lymph Nodes in Patients With Papillary Thyroid Carcinoma. J Ultrasound Med. 2018; 37(11):2527-2535. DOI: 10.1002/jum.14610. View

Li H, Mendel K, Lan L, Sheth D, Giger M . Digital Mammography in Breast Cancer: Additive Value of Radiomics of Breast Parenchyma. Radiology. 2019; 291(1):15-20. PMC: 6445042. DOI: 10.1148/radiol.2019181113. View

Kim E, Park J, Son K, Kim J, Jeon S, Na D . Preoperative diagnosis of cervical metastatic lymph nodes in papillary thyroid carcinoma: comparison of ultrasound, computed tomography, and combined ultrasound with computed tomography. Thyroid. 2008; 18(4):411-8. DOI: 10.1089/thy.2007.0269. View

Liu T, Zhou S, Yu J, Guo Y, Wang Y, Zhou J . Prediction of Lymph Node Metastasis in Patients With Papillary Thyroid Carcinoma: A Radiomics Method Based on Preoperative Ultrasound Images. Technol Cancer Res Treat. 2019; 18:1533033819831713. PMC: 6429647. DOI: 10.1177/1533033819831713. View

10.

Maksimovic S, Jakovljevic B, Gojkovic Z . Lymph Node Metastases Papillary Thyroid Carcinoma and their Importance in Recurrence of Disease. Med Arch. 2018; 72(2):108-111. PMC: 5911164. DOI: 10.5455/medarh.2018.72.108-111. View

11.

Zheng C, Ji Y, Song C, Ge M, Tae K . Number of Metastatic Lymph Nodes and Ratio of Metastatic Lymph Nodes to Total Number of Retrieved Lymph Nodes Are Risk Factors for Recurrence in Patients With Clinically Node Negative Papillary Thyroid Carcinoma. Clin Exp Otorhinolaryngol. 2017; 11(1):58-64. PMC: 5831665. DOI: 10.21053/ceo.2017.00472. View

12.

Feng S, Jia Y, Liao B, Huang B, Zhou Q, Li X . Preoperative prediction of microvascular invasion in hepatocellular cancer: a radiomics model using Gd-EOB-DTPA-enhanced MRI. Eur Radiol. 2019; 29(9):4648-4659. DOI: 10.1007/s00330-018-5935-8. View

13.

Kim S, Kwak J, Kim E, Yoon J, Moon H . Association of Preoperative US Features and Recurrence in Patients with Classic Papillary Thyroid Carcinoma. Radiology. 2015; 277(2):574-83. DOI: 10.1148/radiol.2015142470. View

14.

Cho E, Kim E, Moon H, Yoon J, Park V, Kwak J . High suspicion US pattern on the ATA guidelines, not cytologic diagnosis, may be a predicting marker of lymph node metastasis in patients with classical papillary thyroid carcinoma. Am J Surg. 2017; 216(3):562-566. DOI: 10.1016/j.amjsurg.2017.12.006. View

15.

Liu J, Zheng D, Li Q, Tang X, Luo Z, Yuan Z . A predictive model of thyroid malignancy using clinical, biochemical and sonographic parameters for patients in a multi-center setting. BMC Endocr Disord. 2018; 18(1):17. PMC: 5842594. DOI: 10.1186/s12902-018-0241-7. View

16.

Cooper D, Doherty G, Haugen B, Hauger B, Kloos R, Lee S . Revised American Thyroid Association management guidelines for patients with thyroid nodules and differentiated thyroid cancer. Thyroid. 2009; 19(11):1167-214. DOI: 10.1089/thy.2009.0110. View

17.

Lambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, van Stiphout R, Granton P . Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012; 48(4):441-6. PMC: 4533986. DOI: 10.1016/j.ejca.2011.11.036. View

18.

Suh C, Baek J, Choi Y, Lee J . Performance of CT in the Preoperative Diagnosis of Cervical Lymph Node Metastasis in Patients with Papillary Thyroid Cancer: A Systematic Review and Meta-Analysis. AJNR Am J Neuroradiol. 2016; 38(1):154-161. PMC: 7963646. DOI: 10.3174/ajnr.A4967. View

19.

Choi Y, Yun J, Kook S, Jung E, Park Y . Clinical and imaging assessment of cervical lymph node metastasis in papillary thyroid carcinomas. World J Surg. 2010; 34(7):1494-9. DOI: 10.1007/s00268-010-0541-1. View

20.

Lee J, Ha E, Kim J . Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT. Eur Radiol. 2019; 29(10):5452-5457. DOI: 10.1007/s00330-019-06098-8. View