Skip to main content
Log in

Clinico-pathological Correlation of Thyroid Nodule Ultrasound and Cytology Using the TIRADS and Bethesda Classifications

  • Original Scientific Report
  • Published:
World Journal of Surgery Aims and scope Submit manuscript

Abstract

Background

Clinico-pathological correlation of thyroid nodules is not routinely performed as until recently there was no objective classification system for reporting thyroid nodules on ultrasound. We compared the Thyroid Imaging Reporting and Data System (TIRADS) of classifying thyroid nodules on ultrasound with the findings on fine-needle aspiration cytology (FNAC) reported using the Bethesda System.

Methods

A retrospective analysis of 100 consecutive cases over 1 year (Jan–Dec 2015) was performed comparing single-surgeon-performed bedside thyroid nodule ultrasound findings based on the TIRADS classification to the FNAC report based on the Bethesda Classification. TIRADS 1 (normal thyroid gland) and biopsy-proven malignancy referred by other clinicians were excluded. Benign-appearing nodules were reported as TIRADS 2 and 3. Indeterminate or suspected follicular lesions were reported as TIRADS 4, and malignant-appearing nodules were classified as TIRADS 5 during surgeon-performed bedside ultrasound. All the nodules were subjected to ultrasound-guided FNAC, and TIRADS findings were compared to Bethesda FNAC Classification.

Results

Of the 100 cases, 74 were considered benign or probably benign, 20 were suspicious for malignancy, and 6 were indeterminate on ultrasound. Overall concordance rate with FNAC was 83% with sensitivity and specificity of 70.6 and 90.4%, respectively. The negative predictive value was 93.8%.

Conclusion

It is essential for clinicians performing bedside ultrasound thyroid and guided FNAC to document their sonographic impression of the nodule in an objective fashion using the TIRADS classification and correlate with the gold standard cytology to improve their learning curve and audit their results.

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

Access this article

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Grant EG, Tessler FN, Hoang JK et al (2015) Thyroid ultrasound reporting lexicon: white paper of the ACR thyroid imaging, reporting and data system (TIRADS) committee. J Am Coll Radiol 12(12 Pt A):1272–1279

    Article  PubMed  Google Scholar 

  2. Horvath E, Majlis S, Rossi R et al (2009) An ultrasonogram reporting system for thyroid nodules stratifying cancer risk for clinical management. J Clin Endocrinol Metab 94(5):1748–1751

    Article  CAS  PubMed  Google Scholar 

  3. Kwak JY, Han KH, Yoon JH et al (2011) Thyroid imaging reporting and data system for US features of nodules: a step in establishing better stratification of cancer risk. Radiology 260(3):892–899

    Article  PubMed  Google Scholar 

  4. Geller BM, Barlow WE, Ballard-Barbash R et al (2002) Use of the American college of radiology BI-RADS to report on the mammographic evaluation of women with signs and symptoms of breast disease. Radiology 222(2):536–542

    Article  PubMed  Google Scholar 

  5. Dixon A, Jha P (2013) Thyroid image reporting and data system (TIRADS). Retrieved from http://radiopaedia.org/articles/thyroid-image-reporting-and-data-system-tirads/

  6. Moifo B, Takoeto EO, Tambe J et al (2013) Reliability of thyroid imaging reporting and data system (TIRADS) classification in differentiating benign from malignant thyroid nodules. Open J Radiol 3:103–107

    Article  Google Scholar 

  7. Yoon JH, Lee HS, Kim EK et al (2015) Thyroid nodules: nondiagnostic cytologic results according to thyroid imaging reporting and data system before and after application of the Bethesda system. Radiology 276(2):579–587

    Article  PubMed  Google Scholar 

  8. Chng CL, Kurzawinski TR, Beale T (2015) Value of sonographic features in predicting malignancy in thyroid nodules diagnosed as follicular neoplasm on cytology. Clin Endocrinol (Oxf) 83(5):711–716

    Article  Google Scholar 

  9. Chandramohan A, Khurana A, Pushpa BT et al (2016) Is TIRADS a practical and accurate system for use in daily clinical practice? Indian J Radiol Imaging 26(1):145–152

    Article  PubMed  PubMed Central  Google Scholar 

  10. Srinivas MN, Amogh VN, Gautam MS et al (2016) A prospective study to evaluate the reliability of thyroid imaging reporting and data system in differentiation between benign and malignant thyroid lesions. J Clin Imaging Sci 6:5

    Article  PubMed  PubMed Central  Google Scholar 

  11. Park JY, Lee HJ, Jang HW et al (2009) A proposal for a thyroid imaging reporting and data system for ultrasound features of thyroid carcinomoa. Thyroid 19(11):1257–1264

    Article  PubMed  Google Scholar 

  12. Ghate SV, Baker JA, Kim CE et al (2012) Using the BI-RADS lexicon in a restrictive form of double reading as a strategy for minimizing screening mammography recall rates. AJR Am J Roentgenol 198(4):962–970

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to R. M. Singaporewalla.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Singaporewalla, R.M., Hwee, J., Lang, T.U. et al. Clinico-pathological Correlation of Thyroid Nodule Ultrasound and Cytology Using the TIRADS and Bethesda Classifications. World J Surg 41, 1807–1811 (2017). https://doi.org/10.1007/s00268-017-3919-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00268-017-3919-5

Keywords

Navigation