Single-center validation study of the American College of Radiology Thyroid Imaging Reporting and Data System in a Turkish adult population

Yıl 2019, Cilt: 29 Sayı: 3, 126 - 133, 25.09.2019

Bülent Çolakoğlu Deniz Alış

Öz

Objectives: This study aims to evaluate diagnostic performance of the American College of Radiology Thyroid Imaging Reporting and Data System ACR-TIRADS in the Turkish adult population. Patients and Methods: A total of 422 thyroid nodules of 368 patients 103 males, 265 females; mean age 46.43 years; range, 18 to 81 years diagnosed by fine needle aspiration biopsy FNAB or surgical pathology were retrospectively analyzed. The decisions for FNABs were mostly made by the experts of our hospital without using the ACR-TIRADS. The observers assessed five different aspects of thyroid nodules: echogenicity, shape, composition, margin, and echogenic foci. Nodules with 0 points were categorized as TR1, 2 points as TR2, 3 points as TR3, 4-6 points as TR4, and ≥7 points as TR5. The sensitivity, specificity, and diagnostic accuracy of ACR and the proportion of benign nodules and malignant nodules to be biopsied according to the ACRTIRADS were calculated. Results: The ACR-TIRADS identified 47 of 54 malignant nodules and identified 264 of 368 benign nodules yielding 73.6% diagnostic accuracy. Using the ACR-TIRADS would have spared 64.1% of benign nodules from FNAB. Of 54 malignant nodules, 23 were to be biopsied, 30 to be followed, and one malignant nodule was not planned to be biopsied or followed according to the ACR-TIRADS recommendations. Conclusion: Despite its robustness in sparing a substantial number of benign nodules from FNAB, the use of ACR-TIRADS would prevent 55.5% of malignant nodules from FNAB. We suggest that FNAB threshold levels of the ACR-TIRADS should be extensively reviewed by the Turkish radiologists, endocrinologists, general surgeons, and ear, nose and throat surgeons before integrating the system to their daily practice.

Anahtar Kelimeler

ACR-TIRADS, fine needle aspiration biopsy, risk stratification, thyroid nodules, ultrasound

Kaynakça

• Singer PA. Evaluation and management of the solitary thyroid nodule. Otolaryngol Clin North Am 1996;29:577-91.
• Guth S, Theune U, Aberle J, Galach A, Bamberger CM. Very high prevalence of thyroid nodules detected by high frequency (13 MHz) ultrasound examination. Eur J Clin Invest 2009;39:699-706.
• Haugen BR, Alexander EK, Bible KC, Doherty GM, Mandel SJ, Nikiforov YE, et al. 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 2016;26:1-133.
• Reading CC, Charboneau JW, Hay ID, Sebo TJ. Sonography of thyroid nodules: a “classic pattern” diagnostic approach. Ultrasound Q 2005;21:157-65.
• Tessler FN, Middleton WD, Grant EG, Hoang JK, Berland LL, Teefey SA, et al. ACR Thyroid Imaging, Reporting and Data System (TI-RADS): White Paper of the ACR TI-RADS Committee. J Am Coll Radiol 2017;14:587-95.
• Horvath E, Majlis S, Rossi R, Franco C, Niedmann JP, Castro A, et al. An ultrasonogram reporting system for thyroid nodules stratifying cancer risk for clinical management. J Clin Endocrinol Metab 2009;94:1748-51.
• Shin JH, Baek JH, Chung J, Ha EJ, Kim JH, Lee YH, et al. Ultrasonography diagnosis and imaging- based management of thyroid nodules: revised korean society of thyroid radiology consensus statement and recommendations. Korean J Radiol 2016;17:370-95.
• Russ G, Bonnema SJ, Erdogan MF, Durante C, Ngu R, Leenhardt L. European Thyroid Association Guidelines for Ultrasound Malignancy Risk Stratification of Thyroid Nodules in Adults: The EU-TIRADS. Eur Thyroid J 2017;6:225-37.
• Middleton WD, Teefey SA, Reading CC, Langer JE, Beland MD, Szabunio MM, et al. Multiinstitutional Analysis of Thyroid Nodule Risk Stratification Using the American College of Radiology Thyroid Imaging Reporting and Data System. AJR Am J Roentgenol 2017;208:1331-41.
• Middleton WD, Teefey SA, Reading CC, Langer JE, Beland MD, Szabunio MM, et al. Comparison of Performance Characteristics of American College of Radiology TI-RADS, Korean Society of Thyroid Radiology TIRADS, and American Thyroid Association Guidelines. AJR Am J Roentgenol 2018;210:1148-54.
• Lauria Pantano A, Maddaloni E, Briganti SI, Beretta Anguissola G, Perrella E, Taffon C, et al. Differences between ATA, AACE/ACE/AME and ACR TI-RADS ultrasound classifications performance in identifying cytological high-risk thyroid nodules. Eur J Endocrinol 2018;178:595-603.
• Xu T, Wu Y, Wu RX, Zhang YZ, Gu JY, Ye XH, et al. Validation and comparison of three newly-released Thyroid Imaging Reporting and Data Systems for cancer risk determination. Endocrine 2019;64:299-307.
• Zheng Y, Xu S, Kang H, Zhan W. A Single-Center Retrospective Validation Study of the American College of Radiology Thyroid Imaging Reporting and Data System. Ultrasound Q 2018;34:77-83.
• Hoang JK, Middleton WD, Farjat AE, Langer JE, Reading CC, Teefey SA, et al. Reduction in Thyroid Nodule Biopsies and Improved Accuracy with American College of Radiology Thyroid Imaging Reporting and Data System. Radiology 2018;287:185-93.
• Liao S, Shindo M. Management of well-differentiated thyroid cancer. Otolaryngol Clin North Am 2012;45:1163-79.