Skip to main content
SpringerLink
Log in

SuperSonic shear imaging for the differentiation between benign and malignant thyroid nodules: a meta-analysis

  • Original Article
  • Published:
Journal of Endocrinological Investigation Aims and scope Submit manuscript

Abstract

Purpose

To assess the diagnostic value of SuperSonic shear imaging (SSI) for the differentiation between benign and malignant thyroid nodules through meta-analysis.

Methods

Online database searches were performed on PubMed, EMBASE, the Cochrane Library, and the Web of Science until 31 July 2021. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to assess the quality of the included studies. Three measures of diagnostic test performance were used to examine the value of SSI, including the summary area under the receiver operating characteristic curve (AUROC), the summary diagnostic odds ratio (DOR), and the summary sensitivity and specificity. Heterogeneity was explored using meta-regression and subgroup analyses.

Results

Finally, 21 studies with 3376 patients were included in this study. There were a total of 4296 thyroid nodules, in which 1806 malignant nodules and 2490 benign ones were involved. Thyroid nodules exhibited a malignancy rate of 42.0% (range 5.6–79.8%), 95.1% of which were of papillary variant. SSI showed a summary sensitivity of 74% [95% confidence interval (CI) 67–79%], specificity of 82% (95% CI 77–87%) and AUROC of 0.85 (95% CI 0.82–0.88) for the differentiation between benign and malignant thyroid nodules. The summary positive likelihood ratio (LR), negative LR, and DOR were 4.2 (95% CI 3.3–5.3), 0.32 (95% CI 0.26–0.40), and 13 (95% CI 9–18), respectively.

Conclusions

SSI showed high accuracy in the diagnostic differentiation between benign and malignant thyroid nodules and can be served as a noninvasive and important adjunct for thyroid nodule evaluation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Koh J, Lee E, Han K et al (2020) Diagnosis of thyroid nodules on ultrasonography by a deep convolutional neural network. Sci Rep 10:15245

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Sebag F, Vaillant-Lombard J, Berbis J et al (2010) Shear wave elastography: a new ultrasound imaging mode for the differential diagnosis of benign and malignant thyroid nodules. J Clin Endocrinol Metab 95:5281–5288

    Article  CAS  PubMed  Google Scholar 

  3. Burman KD, Wartofsky L (2015) Clinical practice. Thyroid nodules. N Engl J Med 373:2347–2356

    Article  CAS  PubMed  Google Scholar 

  4. Zhou H, Jin Y, Dai L et al (2020) Differential diagnosis of benign and malignant thyroid nodules using deep learning radiomics of thyroid ultrasound images. Eur J Radiol 127:108992

    Article  PubMed  Google Scholar 

  5. Angell TE, Maurer R, Wang Z et al (2019) A cohort analysis of clinical and ultrasound variables predicting cancer risk in 20,001 consecutive thyroid nodules. J Clin Endocrinol Metab 104:5665–5672

    Article  PubMed  Google Scholar 

  6. Zhang F, Yu X, Lin Z et al (2021) Using tumor-infiltrating immune cells and a ceRNA network model to construct a prognostic analysis model of thyroid carcinoma. Front Oncol 11:658165

    Article  PubMed  PubMed Central  Google Scholar 

  7. Wong R, Farrell SG, Grossmann M (2018) Thyroid nodules: diagnosis and management. Med J Aust 209:92–98

    Article  PubMed  Google Scholar 

  8. Cappelli C, Pirola I, Agosti B et al (2017) Complications after fine-needle aspiration cytology: a retrospective study of 7449 consecutive thyroid nodules. Br J Oral Maxillofac Surg 55:266–269

    Article  CAS  PubMed  Google Scholar 

  9. Moon WJ, Jung SL, Lee JH et al (2008) Benign and malignant thyroid nodules: US differentiation–multicenter retrospective study. Radiology 247:762–770

    Article  PubMed  Google Scholar 

  10. Grani G, Sponziello M, Pecce V et al (2020) Contemporary thyroid nodule evaluation and management. J Clin Endocrinol Metab 105:2869–2883

    Article  PubMed Central  Google Scholar 

  11. Roth MY, Witt RL, Steward DL (2018) Molecular testing for thyroid nodules: review and current state. Cancer 124:888–898

    Article  PubMed  Google Scholar 

  12. Bongiovanni M, Spitale A, Faquin WC et al (2012) The Bethesda system for reporting thyroid cytopathology: a meta-analysis. Acta Cytol 56:333–339

    Article  PubMed  Google Scholar 

  13. Shiina T, Nightingale KR, Palmeri ML et al (2015) WFUMB guidelines and recommendations for clinical use of ultrasound elastography: part 1: basic principles and terminology. Ultrasound Med Biol 41:1126–1147

    Article  PubMed  Google Scholar 

  14. Filho RHC, Pereira FL, Iared W (2020) Diagnostic accuracy evaluation of two-dimensional shear wave elastography in the differentiation between benign and malignant thyroid nodules: systematic review and meta-analysis. J Ultrasound Med 39:1729–1741

    Article  PubMed  Google Scholar 

  15. Swan KZ, Nielsen VE, Bonnema SJ (2021) Evaluation of thyroid nodules by shear wave elastography: a review of current knowledge. J Endocrinol Invest 44:2043–2056

    Article  CAS  PubMed  Google Scholar 

  16. Cosgrove D, Barr R, Bojunga J et al (2017) WFUMB guidelines and recommendations on the clinical use of ultrasound elastography: part 4. thyroid. Ultrasound Med Biol 43:4–26

    Article  PubMed  Google Scholar 

  17. Pei S, Zhang B, Cong S et al (2020) Ultrasound real-time tissue elastography improves the diagnostic performance of the ACR Thyroid Imaging Reporting and Data System in differentiating malignant from benign thyroid nodules: a summary of 1525 thyroid nodules. Int J Endocrinol 2020:1749351

    Article  PubMed  PubMed Central  Google Scholar 

  18. Bhatia KS, Tong CS, Cho CC et al (2012) Shear wave elastography of thyroid nodules in routine clinical practice: preliminary observations and utility for detecting malignancy. Eur Radiol 22:2397–2406

    Article  PubMed  Google Scholar 

  19. McInnes MDF, Moher D, Thombs BD et al (2018) Preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: the PRISMA-DTA statement. JAMA 319:388–396

    Article  PubMed  Google Scholar 

  20. Whiting PF, Rutjes AW, Westwood ME et al (2011) QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 155:529–536

    Article  PubMed  Google Scholar 

  21. Veyrieres JB, Albarel F, Lombard JV et al (2012) A threshold value in Shear Wave elastography to rule out malignant thyroid nodules: a reality? Eur J Radiol 81:3965–3972

    Article  PubMed  Google Scholar 

  22. Kim H, Kim JA, Son EJ et al (2013) Quantitative assessment of shear-wave ultrasound elastography in thyroid nodules: diagnostic performance for predicting malignancy. Eur Radiol 23:2532–2537

    Article  PubMed  Google Scholar 

  23. Szczepanek-Parulska E, Wolinski K, Stangierski A et al (2014) Biochemical and ultrasonographic parameters influencing thyroid nodules elasticity. Endocrine 47:519–527

    Article  CAS  PubMed  Google Scholar 

  24. Liu BX, Xie XY, Liang JY et al (2014) Shear wave elastography versus real-time elastography on evaluation thyroid nodules: a preliminary study. Eur J Radiol 83:1135–1143

    Article  PubMed  Google Scholar 

  25. Liu B, Liang J, Zheng Y et al (2015) Two-dimensional shear wave elastography as promising diagnostic tool for predicting malignant thyroid nodules: a prospective single-centre experience. Eur Radiol 25:624–634

    Article  PubMed  Google Scholar 

  26. Park AY, Son EJ, Han K et al (2015) Shear wave elastography of thyroid nodules for the prediction of malignancy in a large scale study. Eur J Radiol 84:407–412

    Article  PubMed  Google Scholar 

  27. Samir AE, Dhyani M, Anvari A et al (2015) Shear-wave elastography for the preoperative risk stratification of follicular-patterned lesions of the thyroid: diagnostic accuracy and optimal measurement plane. Radiology 277:565–573

    Article  PubMed  Google Scholar 

  28. Liu B, Liang J, Zhou L et al (2015) Shear wave elastography in the diagnosis of thyroid nodules with coexistent chronic autoimmune hashimoto’s thyroiditis. Otolaryngol Head Neck Surg 153:779–785

    Article  PubMed  Google Scholar 

  29. Duan SB, Yu J, Li X et al (2016) Diagnostic value of two-dimensional shear wave elastography in papillary thyroid microcarcinoma. Onco Targets Ther 9:1311–1317

    PubMed  PubMed Central  Google Scholar 

  30. Dobruch-Sobczak K, Zalewska EB, Guminska A et al (2016) Diagnostic performance of shear wave elastography parameters alone and in combination with conventional B-mode ultrasound parameters for the characterization of thyroid nodules: a prospective, dual-center study. Ultrasound Med Biol 42:2803–2811

    Article  PubMed  Google Scholar 

  31. He YP, Xu HX, Wang D et al (2017) First experience of comparisons between two different shear wave speed imaging systems in differentiating malignant from benign thyroid nodules. Clin Hemorheol Microcirc 65:349–361

    Article  PubMed  Google Scholar 

  32. Chen M, Zhang KQ, Xu YF et al (2016) Shear wave elastography and contrast-enhanced ultrasonography in the diagnosis of thyroid malignant nodules. Mol Clin Oncol 5:724–730

    Article  PubMed  PubMed Central  Google Scholar 

  33. Liu Z, Jing H, Han X et al (2017) Shear wave elastography combined with the thyroid imaging reporting and data system for malignancy risk stratification in thyroid nodules. Oncotarget 8:43406–43416

    Article  PubMed  PubMed Central  Google Scholar 

  34. Zhao CK, Chen SG, Alizad A et al (2018) Three-dimensional shear wave elastography for differentiating benign from malignant thyroid nodules. J Ultrasound Med 37:1777–1788

    Article  PubMed  Google Scholar 

  35. Kyriakidou G, Friedrich-Rust M, Bon D et al (2018) Comparison of strain elastography, point shear wave elastography using acoustic radiation force impulse imaging and 2D-shear wave elastography for the differentiation of thyroid nodules. PLoS ONE 13:e0204095

    Article  PubMed  PubMed Central  Google Scholar 

  36. Kim HJ, Kwak MK, Choi IH et al (2019) Utility of shear wave elastography to detect papillary thyroid carcinoma in thyroid nodules: efficacy of the standard deviation elasticity. Korean J Intern Med 34:850–857

    Article  CAS  PubMed  Google Scholar 

  37. Farghadani M, Tabatabaei SA, Barikbin R et al (2019) Comparing the sensitivity and specificity of two-dimensional shear wave elastography and fine needle aspiration in determining malignant thyroid nodules. Adv Biomed Res 8:30

    Article  PubMed  PubMed Central  Google Scholar 

  38. Han RJ, Du J, Li FH et al (2019) Comparisons and combined application of two-dimensional and three-dimensional real-time shear wave elastography in diagnosis of thyroid nodules. J Cancer 10:1975–1984

    Article  PubMed  PubMed Central  Google Scholar 

  39. Shang H, Wu B, Liu Z et al (2020) The effectiveness of shear wave elastography in the diagnosis of PTMC. Technol Health Care 28:221–226

    Article  PubMed  Google Scholar 

  40. Nattabi HA, Sharif NM, Yahya N et al (2017) Is diagnostic performance of quantitative 2D-shear wave elastography optimal for clinical classification of benign and malignant thyroid nodules?: a systematic review and meta-analysis. Acad Radiol S1076–6332(17):30369

    Google Scholar 

  41. Zhao CK, Ren TT, Yin YF et al (2021) A comparative analysis of two machine learning-based diagnostic patterns with thyroid imaging reporting and data system for thyroid nodules: diagnostic performance and unnecessary biopsy rate. Thyroid 31:470–481

    Article  CAS  PubMed  Google Scholar 

  42. Lin P, Chen M, Liu B et al (2014) Diagnostic performance of shear wave elastography in the identification of malignant thyroid nodules: a meta-analysis. Eur Radiol 24:2729–2738

    Article  PubMed  Google Scholar 

  43. Magri F, Chytiris S, Capelli V et al (2012) Shear wave elastography in the diagnosis of thyroid nodules: feasibility in the case of coexistent chronic autoimmune Hashimoto’s thyroiditis. Clin Endocrinol (Oxf) 76:137–141

    Article  Google Scholar 

  44. Zhan J, Jin JM, Diao XH et al (2015) Acoustic radiation force impulse imaging (ARFI) for differentiation of benign and malignant thyroid nodules: a meta-analysis. Eur J Radiol 84:2181–2186

    Article  PubMed  Google Scholar 

  45. Cantisani V, David E, Grazhdani H et al (2019) Prospective evaluation of semiquantitative strain ratio and quantitative 2D ultrasound shear wave elastography (SWE) in association with TIRADS classification for thyroid nodule characterization. Ultraschall Med 40:495–503

    Article  PubMed  Google Scholar 

  46. Xu SL, Tian YY, Zhou Y et al (2020) Diagnostic value of circulating microRNAs in thyroid carcinoma: a systematic review and meta-analysis. Clin Endocrinol (Oxf) 93:489–498

    Article  CAS  Google Scholar 

  47. Magri F, Chytiris S, Chiovato L (2016) The role of elastography in thyroid ultrasonography. Curr Opin Endocrinol Diabetes Obes 23:416–422

    Article  PubMed  Google Scholar 

Download references

Funding

This work was supported by Sciences and Technology project of Fujian Provincial Department (2019J01166), Innovative medical research project of Fujian Province (2018-CX-33) and High-level talent program of sciences and technology project of Quanzhou (2018C044R).

Author information

Authors and Affiliations

  1. Department of Endocrinology, The Second Affiliated Hospital of Fujian Medical University, No. 34 North Zhongshan Road, Quanzhou, 362000, Fujian, China

    Y. Chen, Z. Jiang, Q. Cai, L. Huang & H. Huang

  2. Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China

    B. Dong

Authors
  1. Y. Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. B. Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Z. Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Q. Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. L. Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. H. Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to H. Huang.

Ethics declarations

Conflict of interest

The authors report no conflict of interest.

Research involving human participants and/or animals

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

For this type of study, formal consent is not required.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Y., Dong, B., Jiang, Z. et al. SuperSonic shear imaging for the differentiation between benign and malignant thyroid nodules: a meta-analysis. J Endocrinol Invest 45, 1327–1339 (2022). https://doi.org/10.1007/s40618-022-01765-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40618-022-01765-y

Keywords

Search

Navigation