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Endocrine

, Volume 61, Issue 2, pp 285–292 | Cite as

Medullary thyroid carcinoma: Application of Thyroid Imaging Reporting and Data System (TI-RADS) Classification

  • Gabin Yun
  • Yeo Koon KimEmail author
  • Sang Il Choi
  • Ji-hoon Kim
Original Article
  • 241 Downloads

Abstract

Purpose

To evaluate the applicability of ultrasound (US)-based Thyroid Imaging Reporting and Data System (TI-RADS) for evaluating medullary thyroid carcinoma (MTC).

Materials and methods

US images and medical records of patients with cytopathology-confirmed MTC between June 2003 and November 2016 were retrospectively reviewed. Four independent reviewers (two experienced and two inexperienced radiologists) evaluated 57 pre-operative US images of patients with MTC for shape, composition, echogenicity, margin, calcification of the MTC nodules, and categorized the nodules using TI-RADS classification. Weighted Kappa statistics was used to determine the inter-observer agreement of TI-RADS. Univariate and multivariate analyses were performed to assess US findings associated with lymph node metastasis.

Results

Ninety-five percent of nodules were classified as either high suspicion (68%) or intermediate suspicion (26%). The overall inter-rater agreement was good (Kappa 0.84, agreement 91.52%), and inexperienced reviewers also showed good agreements with the most experienced reviewer (weighted Kappa 0.73 and 0.81). According to the univariate analysis, TI-RADS category 5, shape, microcalcification, and extrathyroid extension were significantly associated with lymph node metastasis in MTC patients (p = 0.003, 0.008, 0.001, and 0.021, respectively). As per the multivariate analysis, the presence of microcalcification and the irregular shape of the nodule were significantly associated with metastatic lymph nodes in MTC patients (odds ratio, 26.6; 95% CI, 2.7–263.7, p = 0.005, odds ratio, 14.7; 95% CI, 1.3–170, p = 0.031, respectively).

Conclusion

TI-RADS is applicable for the evaluation of MTC nodules with good inter-observer agreement.

Keywords

Medullary thyroid carcinoma TI-RADS Lymph node metastasis Microcalcification 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Informed consent

This retrospective study was approved by the institutional review board of Seoul National University Bundang Hospital and informed consent was waived.

References

  1. 1.
    B.R. Haugen, E.K. Alexander, K.C. Bible, G.M. Doherty, S.J. Mandel, Y.E. Nikiforov, F. Pacini, G.W. Randolph, A.M. Sawka, M. Schlumberger, K.G. Schuff, S.I. Sherman, J.A. Sosa, D.L. Steward, R.M. Tuttle, L. Wartofsky, 2015 American Thyroid Association Management Guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: The American Thyroid Association Guidelines Task Force on thyroid nodules and differentiated thyroid cancer. Thyroid.: Off. J. Am. Thyroid. Assoc. 26(1), 1–133 (2016).  https://doi.org/10.1089/thy.2015.0020 CrossRefGoogle Scholar
  2. 2.
    S.I. Sherman, Thyroid carcinoma. Lancet (Lond., Engl.) 361(9356), 501–511 (2003)CrossRefGoogle Scholar
  3. 3.
    H.J. Moon, E.K. Kim, J.H. Yoon, J.Y. Kwak, Malignancy risk stratification in thyroid nodules with nondiagnostic results at cytologic examination: combination of thyroid imaging reporting and data system and the Bethesda System. Radiology 274(1), 287–295 (2015).  https://doi.org/10.1148/radiol.14140359 CrossRefPubMedGoogle Scholar
  4. 4.
    D.G. Na, J.H. Baek, J.Y. Sung, J.H. Kim, J.K. Kim, Y.J. Choi, H. Seo, Thyroid Imaging Reporting and Data System risk stratification of thyroid nodules: Categorization based on solidity and echogenicity. Thyroid.: Off. J. Am. Thyroid. Assoc. 26(4), 562–572 (2016).  https://doi.org/10.1089/thy.2015.0460 CrossRefGoogle Scholar
  5. 5.
    E.B. Mendelson, M. Böhm-Vélez, W.A. Berg, et al. ACR BI-RADS® Ultrasound. In: ACR BI-RADS® Atlas, Breast Imaging Reporting and Data System. Reston, VA, American College of Radiology (2013).Google Scholar
  6. 6.
    E.J. Ha, W.J. Moon, D.G. Na, Y.H. Lee, N. Choi, S.J. Kim, J.K. Kim, A. Multicenter Prospective, Validation study for the Korean Thyroid Imaging Reporting and Data System in patients with thyroid nodules. Korean J. Radiol. 17(5), 811–821 (2016).  https://doi.org/10.3348/kjr.2016.17.5.811 CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    P. Trimboli, L. Giovanella, A. Crescenzi, F. Romanelli, S. Valabrega, G. Spriano, N. Cremonini, R. Guglielmi, E. Papini, Medullary thyroid cancer diagnosis: an appraisal. Head Neck. 36(8), 1216–1223 (2014).  https://doi.org/10.1002/hed.23449 CrossRefPubMedGoogle Scholar
  8. 8.
    B. Gorman, J.W. Charboneau, E.M. James, C.C. Reading, L.E. Wold, C.S. Grant, H. Gharib, I.D. Hay, Medullary thyroid carcinoma: role of high-resolution US. Radiology 162(1 Pt 1), 147–150 (1987).  https://doi.org/10.1148/radiology.162.1.3538147 CrossRefPubMedGoogle Scholar
  9. 9.
    S. Lee, J.H. Shin, B.K. Han, E.Y. Ko, Medullary thyroid carcinoma: comparison with papillary thyroid carcinoma and application of current sonographic criteria. AJR Am. J. Roentgenol. 194(4), 1090–1094 (2010).  https://doi.org/10.2214/ajr.09.3276 CrossRefPubMedGoogle Scholar
  10. 10.
    P. Valderrabano, D.L. Klippenstein, J.B. Tourtelot, Z. Ma, Z.J. Thompson, H.S. Lilienfeld, B. McIver, New American Thyroid Association Sonographic Patterns for thyroid nodules perform well in medullary thyroid carcinoma: institutional experience, systematic review, and meta-Analysis. Thyroid.: Off. J. Am. Thyroid. Assoc. 26(8), 1093–1100 (2016).  https://doi.org/10.1089/thy.2016.0196 CrossRefGoogle Scholar
  11. 11.
    D. Ganeshan, E. Paulson, C. Duran, M.E. Cabanillas, N.L. Busaidy, C. Charnsangavej, Current update on medullary thyroid carcinoma. AJR Am. J. Roentgenol. 201(6), W867–876 (2013).  https://doi.org/10.2214/AJR.12.10370 CrossRefPubMedGoogle Scholar
  12. 12.
    H. Gharib, E. Papini, R. Paschke, D.S. Duick, R. Valcavi, L. Hegedus, P. Vitti, American Association of Clinical Endocrinologists, Associazione Medici Endocrinologi, and European Thyroid Association Medical Guidelines for clinical practice for the diagnosis and management of thyroid nodules. J. Endocrinol. Invest. 33(5 Suppl), 1–50 (2010)PubMedGoogle Scholar
  13. 13.
    J.P. Brito, M.R. Gionfriddo, A. Al Nofal, K.R. Boehmer, A.L. Leppin, C. Reading, M. Callstrom, T.A. Elraiyah, L.J. Prokop, M.N. Stan, M.H. Murad, J.C. Morris, V.M. Montori, The accuracy of thyroid nodule ultrasound to predict thyroid cancer: systematic review and meta-analysis. J. Clin. Endocrinol. Metab. 99(4), 1253–1263 (2014).  https://doi.org/10.1210/jc.2013-2928 CrossRefPubMedGoogle Scholar
  14. 14.
    S.H. Kim, B.S. Kim, S.L. Jung, J.W. Lee, P.S. Yang, B.J. Kang, H.W. Lim, J.Y. Kim, I.Y. Whang, H.S. Kwon, C.K. Jung, Ultrasonographic findings of medullary thyroid carcinoma: a comparison with papillary thyroid carcinoma. Korean J. Radiol. 10(2), 101–105 (2009).  https://doi.org/10.3348/kjr.2009.10.2.101 CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    P. Trimboli, L. Giovanella, S. Valabrega, M. Andrioli, R. Baldelli, N. Cremonini, F. Rossi, L. Guidobaldi, A. Barnabei, F. Rota, A. Paoloni, L. Rizza, G. Fattorini, M. Latini, C. Ventura, P. Falasca, F. Orlandi, A. Crescenzi, F. D’Ambrosio, V. Cantisani, F. Romanelli, R. Negro, E. Saggiorato, M. Appetecchia, Ultrasound features of medullary thyroid carcinoma correlate with cancer aggressiveness: a retrospective multicenter study. J. Exp. Clin. Cancer Res.: CR 33, 87 (2014).  https://doi.org/10.1186/s13046-014-0087-4 CrossRefPubMedGoogle Scholar
  16. 16.
    C. Kim, J.H. Baek, E. Ha, J.H. Lee, Y.J. Choi, D.E. Song, J.K. Kim, K.W. Chung, W.B. Kim, Y.K. Shong, Ultrasonography features of medullary thyroid cancer as predictors of its biological behavior. Acta Radiol. (Stockh., Swed.: 1987) 58(4), 414–422 (2017).  https://doi.org/10.1177/0284185116656491 CrossRefGoogle Scholar
  17. 17.
    J.E. Ahn, J.H. Lee, J.S. Yi, Y.K. Shong, S.J. Hong, D.H. Lee, C.G. Choi, S.J. Kim, Diagnostic accuracy of CT and ultrasonography for evaluating metastatic cervical lymph nodes in patients with thyroid cancer. World J. Surg. 32(7), 1552 (2008)CrossRefPubMedGoogle Scholar
  18. 18.
    S. Roman, R. Lin, J.A. Sosa, Prognosis of medullary thyroid carcinoma: demographic, clinical, and pathologic predictors of survival in 1252 cases. Cancer 107(9), 2134–2142 (2006).  https://doi.org/10.1002/cncr.22244 CrossRefPubMedGoogle Scholar
  19. 19.
    K.E. Cho, H.M. Gweon, A.Y. Park, M.R. Yoo, J. Kim, J.H. Youk, Y.M. Park, E.J. Son, Ultrasonographic features of medullary thyroid carcinoma: Do they correlate with pre and postoperative calcitonin levels? Asian Pac. J. Cancer Prev.: APJCP 17(7), 3357–3362 (2016)PubMedGoogle Scholar
  20. 20.
    P. Trimboli, N. Nasrollah, S. Amendola, F. Rossi, G. Ramacciato, F. Romanelli, P. Aurello, A. Crescenzi, O. Laurenti, E. Condorelli, C. Ventura, S. Valabrega, Should we use ultrasound features associated with papillary thyroid cancer in diagnosing medullary thyroid cancer? Endocr. J. 59(6), 503–508 (2012)CrossRefPubMedGoogle Scholar
  21. 21.
    C. Scollo, E. Baudin, J.P. Travagli, B. Caillou, N. Bellon, S. Leboulleux, M. Schlumberger, Rationale for central and bilateral lymph node dissection in sporadic and hereditary medullary thyroid cancer. J. Clin. Endocrinol. Metab. 88(5), 2070–2075 (2003).  https://doi.org/10.1210/jc.2002-021713 CrossRefPubMedGoogle Scholar
  22. 22.
    J.H. Yoon, H.S. Lee, E.K. Kim, H.J. Moon, J.Y. Kwak, Malignancy risk stratification of thyroid nodules: Comparison between the Thyroid Imaging Reporting and Data System and the 2014 American Thyroid Association Management Guidelines. Radiology 278(3), 917–924 (2016).  https://doi.org/10.1148/radiol.2015150056 CrossRefPubMedGoogle Scholar
  23. 23.
    J.H. Shin, J.H. Baek, J. Chung, E.J. Ha, J.-h Kim, Y.H. Lee, H.K. Lim, W.-J. Moon, D.G. Na, J.S. Park, Y.J. Choi, S.Y. Hahn, S.J. Jeon, S.L. Jung, D.W. Kim, E.-K. Kim, J.Y. Kwak, C.Y. Lee, H.J. Lee, J.H. Lee, J.H. Lee, K.H. Lee, S.-W. Park, J.Y. Sung, Ultrasonography diagnosis and imaging-based management of thyroid nodules: Revised Korean Society of Thyroid Radiology Consensus Statement and Recommendations. Korean J. Radiol. 17(3), 370–395 (2016)CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    J.R. Landis, G.G. Koch, The measurement of observer agreement for categorical data. Biometrics 33(1), 159–174 (1977).CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    M. Fukushima, Y. Ito, M. Hirokawa, A. Miya, K. Kobayashi, H. Akasu, K. Shimizu, A. Miyauchi, Excellent prognosis of patients with nonhereditary medullary thyroid carcinoma with ultrasonographic findings of follicular tumor or benign nodule. World J. Surg. 33(5), 963–968 (2009).  https://doi.org/10.1007/s00268-009-9939-z CrossRefPubMedGoogle Scholar
  26. 26.
    C. Daumerie, D. Maiter, D. Gruson, Serum calcitonin estimation in medullary thyroid cancer: basal or stimulated levels? Thyroid Res. 6(Suppl 1), S4 (2013).  https://doi.org/10.1186/1756-6614-6-S1-S4 CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    L. Zhou, B. Chen, M. Zhao, H. Zhang, B. Liang, Sonographic features of medullary thyroid carcinomas according to tumor size: comparison with papillary thyroid carcinomas. J. Ultrasound Med.: Off. J. Am. Inst. Ultrasound Med. 34(6), 1003–1009 (2015).  https://doi.org/10.7863/ultra.34.6.1003 CrossRefGoogle Scholar
  28. 28.
    T. McCook, C. Putman, J. Dale, S. Wells, Medullary carcinoma of the thyroid: radiographic features of a unique tumor. Am. J. Roentgenol. 139(1), 149–155 (1982)CrossRefGoogle Scholar
  29. 29.
    F. Pombo, E. Rodriguez, J. Cao, C. Martinez-Isla, Cervical lymph node metastases of medullary thyroid carcinoma: CT findings. Eur. Radiol. 7(1), 99–101 (1997)CrossRefPubMedGoogle Scholar
  30. 30.
    B. Saller, L. Moeller, R. Gorges, O.E. Janssen, K. Mann, Role of conventional ultrasound and color Doppler sonography in the diagnosis of medullary thyroid carcinoma. Exp. Clin. Endocrinol. Diabetes.: Off. J., Ger. Soc. Endocrinol. Ger. Diabetes. Assoc. 110(8), 403–407 (2002).  https://doi.org/10.1055/s-2002-36546 CrossRefGoogle Scholar
  31. 31.
    V.Y. Park, E.K. Kim, H.J. Moon, J.H. Yoon, J.Y. Kwak, The thyroid imaging reporting and data system on US, but not the BRAFV600E mutation in fine-needle aspirates, is associated with lateral lymph node metastasis in PTC. Medicine 95(29), e4292 (2016).  https://doi.org/10.1097/md.0000000000004292 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of RadiologySeoul National University Bundang HospitalSeoulKorea
  2. 2.Department of RadiologySeoul National University HospitalSeoulKorea

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