Single article

DOI: 10.47026/2413-4864-2021-4-29-38

Stepanov V.G., Timofeeva L.A., Alekseev S.V., Yusova M.A.

Evaluation of Predictive Capabilities of TIRADS, EU-TIRADS, TLA_RU systems in the Ultrasound Diagnosis of Thyroid Nodular Pathology

Keywords: thyroid gland, nodular masses, multiparametric ultrasound examination, stratification systems TIRADS, EU-TIRADS, TLA_RU

The aim of the study was to evaluate the prognostic capabilities of EU-TIRADS, TIRADS, TLA_RU systems in ultrasound diagnostics of thyroid nodular masses. A retrospective independent continuous blind study of ultrasound examination protocols was conducted in 665 patients, 241 patients had benign non-cancerous thyroid diseases, 86 patients had benign tumors (adenomas), 338 patients had thyroid cancer. During the preoperative examination, all patients underwent a multiparametric ultrasound examination of the neck organs according to the standard procedure, with the registration of identified thyroid nodes, with examining the prognostic capabilities of stratification systems – TIRADS, EU-TIRADS, TLA_RU. It was found that the TIRADS system has a sensitivity of 91.04%, specificity – 91.41%. Focusing on the scale of AUC values reflecting the quality of the diagnostic test, it can be stated that TIRADS is a test with excellent quality (AUC =0.972). Basing on the results of the analyzing the data obtained by the EU-TIRADS system, it was revealed that it is a high-quality test (AUC=0.826), but its predictive capabilities are worse than those of TIRADS. The original TLA_RU model has 87.5% sensitivity and 95.7% specificity. During the ROC analysis, it was found that the AUC is equal to 0.954±0.00894, which suggests that the TLA_RU model is an excellent quality test in the differential diagnosis of thyroid nodular masses. Multivariate statistical comparative analysis of thyroid imaging assessment systems (TIRADS, EU-TIRADS and TLA_RU) from the standpoint of evidence-based medicine has shown that thyroid cancer risk stratification systems based on the assessment of multiparametric ultrasound signs have great diagnostic capabilities.

References

  1. Aleksandrov Yu.K., Yanovskaya E.A., Shubin L.B., Dyakiv A.D. Effektivnost’ stratifikatsionnykh sistem v diagnostike uzlovykh zabolevanii shchitovidnoi zhelezy [The effec-tiveness of risk stratification systems in diagnosis of nodular thyroid disorders]. Problems of Endocrinology, 2019, vol. 65, no. 4, pp. 216–226. DOI: https://doi.org/10.14341/probl10087.
  2. Borsukov A.V. Analiz amerikanskoi i Evropeiskoi versii TI-RADS-2017: vozmozhnosti vosproizvodimosti v kabinete ul’trazvukovoi diagnostiki [Analysis of the American and European Versions of TI-RADS-2017: Adaptability In Russian Endocrinology. Vestnik novykh meditsinskikh tekhnologii, 2019, vol. 26, no. 2, pp. 25–28. DOI: 10.24411/1609-2163-2019-16388.
  3. Timofeeva L.A. Sposob prognozirovaniya veroyatnosti zlokachestvennosti uzla shchitovidnoi zhelezy [A method for predicting the probability of malignancy of the thyroid nodule]. Patent RF, no. 2706948, 2019.
  4. Sencha A.N., Sencha E.A., Penyaeva E.I., Timofeeva L.A. Ul’trazvukovoe issledovanie shchi¬tovidnoi zhelezy. Shag za shagom. Ot prostogo k slozhnomu [Ultrasound examination of the thyroid gland. Step by step. From simple to complex]. Moscow, MEDpress-inform Publ., 2019, 208 p.
  5. Sinyukova G.T., Gudilina E.A., Danzanova T.Yu., Sholokhov V.N., Lepedatu P.I., Allakhverdieva G.F., Kostyakova L.A., Berdnikov S.N. Sovremennye tekhnologii ul’trazvukovoi vizualizatsii v diagnostike mestnogo retsidiva raka shchitovidnoi zhelezy [Modern Technologies of Ultrasound Imaging in the Diagnostics of Local Recurrence of Thyroid Carcinoma]. Mezhdunarodnyi nauchno-issledovatel’skii zhurnal, 2016, vol. 9-3, no. 51, pp. 81–84.
  6. Timofeeva L.A. Differentsial’naya diagnostika uzlovykh novoobrazovanii shchitovidnoi zhelezy: mul’tiparametricheskoe ul’trazvukovoe issledovanie v paradigme stratifikatsionnykh riskov: dis. … d-a med. nauk [Differential diagnosis of nodular neoplasms of the thyroid gland: multiparametric ultrasound in the paradigm of stratification risks: Doct. Diss.]. Moscow, 2019, 329 p.
  7. Timofeeva L.A. Mul’tiparametricheskoe ul’trazvukovoe issledovanie v differentsial’noi diagnostike uzlovykh novoobrazovanii shchitovidnoi zhelezy [Multiparametric ultrasound in differential diagnosis of nodular neoplasms of the thyroid gland]. Cheboksary, Chuvash University Publ., 2018, 180 p.
  8. Tukhbatullin M.G., Safiullina L.R., Galeeva Z.M., Khamzina F.T. et al. Ekhografiya v dia-gnostike zabolevanii vnutrennikh i poverkhnostno raspolozhennykh organov [Echography in the diagnosis of diseases of internal and superficially located organs]. Kazan, Meditsinskaya kniga Publ., 2016, 208 p.
  9. Fisenko E.P., Sencha A.N., Katrich A.N., Sych Yu.P., Tsvetkova N.V., Borsukov A.V., Kostromina E.V. On the need to introduce the TI-RADS classification in Russia. Clinical and experimental thyroidology, 2019, vol. 15, no. 2, pp. 55–63. DOI: https://doi.org/10.14341/ket10115.
  10. Choi Y.J., Baek J.H., Park H.S., Shim W.H., Kim T.Y., Shong Y.K., Lee J.H. A Computer-Aided Diagnosis System Using Artificial Intelligence for the Diagnosis and Characterization of Thyroid Nodules on Ultrasound: Initial Clinical Assessment. Thyroid., 2017, vol. 27(4), pp. 546–552. DOI: 10.1089/thy.2016.0372.
  11. Horvath E., Majlis S., Rossi R., Franco C, Niedman J.P., Dominguez M. An ultrasonogram reporting system for thyroid nodules stratifying cancer risk for clinical management. Clin. Endocrinol. Metab., 2009, vol. 94(5), pp. 1748–1751.
  12. Liu B.J., Zhang Y.F., Zhao C.K., Wang H.X., Li M.X., Xu H.X. Conventional ultrasound characteristics, TI-RADS category and shear wave speed measurement between follicular adenoma and follicular thyroid carcinoma. Hemorheol. Microcirc., 2020, vol. 75, pp. 291–301. DOI: 10.3233/CH-190750.
  13. Ou D, Yao J, Jin J, Yan M, Shi K, Zheng Q, Yang C, Xu D. Ultrasonic identification and regression analysis of 294 thyroid follicular tumors. J Cancer Res Ther., 2020, vol. 16(5), pp. 1056–1062. DOI: 10.4103/jcrt.JCRT_913_19.
  14. Russ G., Bigorgne C., Royer B., Rouxel A., Bienvenu-Perrard M. The Thyroid Imaging Reporting and Data System (TIRADS) for ultrasound of the thyroid. Radiol., 2011, vol. 92(7-8), pp. 701–713. DOI: 10.1016/j.jradio.2011.03.022.
  15. Russ G., Bonnema S.J., Erdogan M.F., Durante C., Ngu R., Leenhardt L. European Thyroid Association Guidelines for Ultrasound Malignancy Risk Stratification of Thyroid Nodules in Adults: The EU-TIRADS. Thyroid. J., 2017, vol. 6, pp. 225–237.
  16. Yoon J.H., Lee H.S., Kim E.K., Moon H.J., Kwak J.Y. Malignancy risk stratification of thyroid nodules: comparison between the Thyroid Imaging Reporting and Data System and the 2014 American Thyroid Association management guidelines. Radiology, 2016, vol. 278, pp. 917–924.

About authors

Stepanov Vladimir G.
Minister, Ministry of Health of the Chuvash Republic, Russia, Cheboksary (medicin_prm@cap.ru; )
Timofeeva Lyubov A.
Doctor of Medical Sciences, Professor, Department of Propedaedeutics of Internal Diseases with Radio Diagnosis Course, Chuvash State University, Russia, Cheboksary (adabai@mail.ru; ORCID: https://orcid.org/0000-0002-4707-8214)
Alekseev Sergey V.
Oncologist, Head of Oncological Department No. 2 (Head and Neck Tumors), Republican Clinical Oncology Dispensary, Russia, Cheboksary (rkod@med.cap.ru; )
Yusova Marina A.
Post-Graduate Student, Department of Propedaedeutics of Internal Diseases with Radio Diagnosis Course, Chuvash State University, Russia, Cheboksary (yusova2012@mail.ru; ORCID: https://orcid.org/0000-0002-8034-5337)

Article link

Stepanov V.G., Timofeeva L.A., Alekseev S.V., Yusova M.A. Evaluation of Predictive Capabilities of TIRADS, EU-TIRADS, TLA_RU systems in the Ultrasound Diagnosis of Thyroid Nodular Pathology [Electronic resource] // Acta medica Eurasica. – 2021. – №4. P. 29-38. – URL: https://acta-medica-eurasica.ru/en/single/2021/4/4/. DOI: 10.47026/2413-4864-2021-4-29-38.