Korean Journal of Radiology

The Korean Society of Radiology (대한영상의학회)
권호 표지
DOI QR코드

DOI QR Code

Image Reporting and Characterization System for Ultrasound Features of Thyroid Nodules: Multicentric Korean Retrospective Study

  • Kwak, Jin Young (Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine) ;
  • Jung, Inkyung (Department of Biostatistics, Yonsei University College of Medicine) ;
  • Baek, Jung Hwan (Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine) ;
  • Baek, Seon Mi (Department of Radiology, Haeundae Healings Hospital) ;
  • Choi, Nami (Department of Radiology, Konkuk University Medical Center, Konkuk University School of Medicine) ;
  • Choi, Yoon Jung (Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University) ;
  • Jung, So Lyung (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Kim, Eun-Kyung (Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine) ;
  • Kim, Jeong-Ah (Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine) ;
  • Kim, Ji-Hoon (Department of Radiology, Seoul National University Hospital) ;
  • Kim, Kyu Sun (Department of Radiology, Thyroid Center, Daerim St. Mary's Hospital) ;
  • Lee, Jeong Hyun (Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine) ;
  • Lee, Joon Hyung (Department of Radiology, Dong-A University Medical Center) ;
  • Moon, Hee Jung (Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine) ;
  • Moon, Won-Jin (Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University) ;
  • Park, Jeong Seon (Department of Radiology, Hanyang University Hospital, Hanyang University College of Medicine) ;
  • Ryu, Ji Hwa (Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine) ;
  • Shin, Jung Hee (Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Son, Eun Ju (Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine) ;
  • Sung, Jin Yong (Department of Radiology, Thyroid Center, Daerim St. Mary's Hospital) ;
  • Na, Dong Gyu (Department of Radiology, Human Medical Imaging and Intervention Center) ;
  • Korean Society of Thyroid Radiology (KSThR) (Korean Society of Thyroid Radiology (KSThR)) ;
  • Korean Society of Radiology (Korean Society of Radiology)
  • Published : 2013.02.01
⟨ Previous Next ⟩

Abstract

Objective: The objective of this retrospective study was to develop and validate a simple diagnostic prediction model by using ultrasound (US) features of thyroid nodules obtained from multicenter retrospective data. Materials and Methods: Patient data were collected from 20 different institutions and the data included 2000 thyroid nodules from 1796 patients. For developing a diagnostic prediction model to estimate the malignant risk of thyroid nodules using suspicious malignant US features, we developed a training model in a subset of 1402 nodules from 1260 patients. Several suspicious malignant US features were evaluated to create the prediction model using a scoring tool. The scores for such US features were estimated by calculating odds ratios, and the risk score of malignancy for each thyroid nodule was defined as the sum of these individual scores. Later, we verified the usefulness of developed scoring system by applying into the remaining 598 nodules from 536 patients. Results: Among 2000 tumors, 1268 were benign and 732 were malignant. In our multiple regression analysis models, the following US features were statistically significant for malignant nodules when using the training data set: hypoechogenicity, marked hypoechogenicity, non-parallel orientation, microlobulated or spiculated margin, ill-defined margins, and microcalcifications. The malignancy rate was 7.3% in thyroid nodules that did not have suspicious-malignant features on US. Area under the receiver operating characteristic (ROC) curve was 0.867, which shows that the US risk score help predict thyroid malignancy well. In the test data set, the malignancy rates were 6.2% in thyroid nodules without malignant features on US. Area under the ROC curve of the test set was 0.872 when using the prediction model. Conclusion: The predictor model using suspicious malignant US features may be helpful in risk stratification of thyroid nodules.

Keywords

References

  1. Park, SH, Kim, SJ, Kim, EK, Kim, MJ, Son, EJ, Kwak, JY,Interobserver agreement in assessing the sonographic and elastographic features of malignant thyroid nodules, AJR Am J Roentgenol, 193, 1, W416-W423(2009) https://doi.org/10.2214/AJR.09.2541
  2. Wienke, JR, Chong, WK, Fielding, JR, Zou, KH, Mittelstaedt, CA,Sonographic features of benign thyroid nodules: interobserver reliability and overlap with malignancy, J Ultrasound Med, 22, 2, 1027-1031(2003) https://doi.org/10.7863/jum.2003.22.10.1027
  3. Choi, SH, Kim, EK, Kwak, JY, Kim, MJ, Son, EJ,Interobserver and intraobserver variations in ultrasound assessment of thyroid nodules, Thyroid, 20, 3, 167-172(2010) https://doi.org/10.1089/thy.2008.0354
  4. Lee, MJ, Hong, SW, Chung, WY, Kwak, JY, Kim, MJ, Kim, EK,Cytological results of ultrasound-guided fine-needle aspiration cytology for thyroid nodules: emphasis on correlation with sonographic findings, Yonsei Med J, 52, 4, 838-844(2011) https://doi.org/10.3349/ymj.2011.52.5.838
  5. Horvath, E, Majlis, S, Rossi, R, Franco, C, Niedmann, JP, Castro, A,An ultrasonogram reporting system for thyroid nodules stratifying cancer risk for clinical management, J Clin Endocrinol Metab, 94, 5, 1748-1751(2009) https://doi.org/10.1210/jc.2008-1724
  6. Park, JY, Lee, HJ, Jang, HW, Kim, HK, Yi, JH, Lee, W,A proposal for a thyroid imaging reporting and data system for ultrasound features of thyroid carcinoma, Thyroid, 19, 6, 1257-1264(2009) https://doi.org/10.1089/thy.2008.0021
  7. Kwak, JY, Han, KH, Yoon, JH, Moon, HJ, Son, EJ, Park, SH,Thyroid imaging reporting and data system for US features of nodules: a step in establishing better stratification of cancer risk, Radiology, 260, 7, 892-899(2011) https://doi.org/10.1148/radiol.11110206
  8. Hambly, NM, Gonen, M, Gerst, SR, Li, D, Jia, X, Mironov, S,Implementation of evidence-based guidelines for thyroid nodule biopsy: a model for establishment of practice standards, AJR Am J Roentgenol, 196, 8, 655-660(2011) https://doi.org/10.2214/AJR.10.4577
  9. American College of Radiology. Breast imaging reporting and data system, breast imaging atlas. 4th ed. Reston: American College of Radiology, 2003
  10. Cibas, ES, Ali, SZ,The Bethesda System for Reporting Thyroid Cytopathology, Thyroid, 19, 10, 1159-1165(2009) https://doi.org/10.1089/thy.2009.0274
  11. Moon, WJ, Jung, SL, Lee, JH, Na, DG, Baek, JH, Lee, YH,Benign and malignant thyroid nodules: US differentiation--multicenter retrospective study, Radiology, 247, 11, 762-770(2008) https://doi.org/10.1148/radiol.2473070944
  12. Thyroid Association (ATA) Guidelines Taskforce on Thyroid Nodules and Differentiated Thyroid Cancer, American,Revised American Thyroid Association management guidelines for patients with thyroid nodules and differentiated thyroid cancer, Thyroid, 19, 12, 1167-1214(2009) https://doi.org/10.1089/thy.2009.0110
  13. Brauer, VF, Eder, P, Miehle, K, Wiesner, TD, Hasenclever, H, Paschke, R,Interobserver variation for ultrasound determination of thyroid nodule volumes, Thyroid, 15, 13, 1169-1175(2005) https://doi.org/10.1089/thy.2005.15.1169
  14. Frates, MC, Benson, CB, Charboneau, JW, Cibas, ES, Clark, OH, Coleman, BG,Management of thyroid nodules detected at US: Society of Radiologists in Ultrasound consensus conference statement, Radiology, 237, 14, 794-800(2005) https://doi.org/10.1148/radiol.2373050220
  15. Gharib, H, Papini, E, Paschke, R, Duick, DS, Valcavi, R, Hegedus, L,American Association of Clinical Endocrinologists, Associazione Medici Endocrinologi, and EuropeanThyroid Association Medical Guidelines for Clinical Practice for the Diagnosis and Management of Thyroid Nodules, Endocr Pract, 16, 15, 1-43(2010)
  16. Kim, EK, Park, CS, Chung, WY, Oh, KK, Kim, DI, Lee, JT,New sonographic criteria for recommending fine-needle aspiration biopsy of nonpalpable solid nodules of the thyroid, AJR Am J Roentgenol, 178, 16, 687-691(2002) https://doi.org/10.2214/ajr.178.3.1780687
  17. Papini, E, Guglielmi, R, Bianchini, A, Crescenzi, A, Taccogna, S, Nardi, F,Risk of malignancy in nonpalpable thyroid nodules: predictive value of ultrasound and color-Doppler features, J Clin Endocrinol Metab, 87, 17, 1941-1946(2002) https://doi.org/10.1210/jcem.87.5.8504
  18. Moon, WJ, Baek, JH, Jung, SL, Kim, DW, Kim, EK, Kim, JY,Ultrasonography and the ultrasound-based management of thyroid nodules: consensus statement and recommendations, Korean J Radiol, 12, 18, 1-14(2011) https://doi.org/10.3348/kjr.2011.12.1.1
  19. Cappelli, C, Castellano, M, Pirola, I, Cumetti, D, Agosti, B, Gandossi, E,The predictive value of ultrasound findings in the management of thyroid nodules, QJM, 100, 19, 29-35(2007)
  20. Cappelli, C, Castellano, M, Pirola, I, Gandossi, E, De Martino, E, Cumetti, D,Thyroid nodule shape suggests malignancy, Eur J Endocrinol, 155, 20, 27-31(2006) https://doi.org/10.1530/eje.1.02177
  21. Chan, BK, Desser, TS, McDougall, IR, Weigel, RJ, Jeffrey, RB,Common and uncommon sonographic features of papillary thyroid carcinoma, J Ultrasound Med, 22, 21, 1083-1090(2003) https://doi.org/10.7863/jum.2003.22.10.1083
  22. Caruso, D, Mazzaferri, EL,Fine needle aspiration biopsy in the management of thyroid nodules, Endocrinologist, 1, 22, 194-202(1991) https://doi.org/10.1097/00019616-199106000-00009
  23. Kwak, JY, Koo, H, Youk, JH, Kim, MJ, Moon, HJ, Son, EJ,Value of US correlation of a thyroid nodule with initially benign cytologic results, Radiology, 254, 23, 292-300(2010) https://doi.org/10.1148/radiol.2541090460
  24. Gharib, H, Goellner, JR,Fine-needle aspiration biopsy of the thyroid: an appraisal, Ann Intern Med, 118, 24, 282-289(1993) https://doi.org/10.7326/0003-4819-118-4-199302150-00007
  25. Hamburger, JI, Hamburger, SW,Fine needle biopsy of thyroid nodules: avoiding the pitfalls, N Y State J Med, 86, 25, 241-249(1986)
  26. Chung, WY, Chang, HS, Kim, EK, Park, CS,Ultrasonographic mass screening for thyroid carcinoma: a study in women scheduled to undergo a breast examination, Surg Today, 31, 26, 763-767(2001) https://doi.org/10.1007/s005950170044
  27. Moon WJ, Kwag HJ, Na DG. Are there any specific ultrasound findings of nodular hyperplasia ("leave me alone" lesion) to differentiate it from follicular adenoma? Acta Radiol 2009;50:383-388 https://doi.org/10.1080/02841850902740940

Cited by

  1. Indications for Fine Needle Aspiration in Thyroid Nodules vol.28, pp.2, 2013, https://doi.org/10.3803/enm.2013.28.2.81
  2. Thyroid Imaging Reporting and Data System (TIRADS) vol.6, pp.2, 2013, https://doi.org/10.11106/jkta.2013.6.2.106
  3. A Model to Discriminate Malignant from Benign Thyroid Nodules Using Artificial Neural Network vol.8, pp.12, 2013, https://doi.org/10.1371/journal.pone.0082211
  4. Application of the Thyroid Imaging Reporting and Data System in thyroid ultrasonography interpretation by less experienced physicians vol.33, pp.1, 2013, https://doi.org/10.14366/usg.13016
  5. Malignancy Risk Stratification in Thyroid Nodules with Benign Results on Cytology: Combination of Thyroid Imaging Reporting and Data System and Bethesda System vol.21, pp.6, 2014, https://doi.org/10.1245/s10434-014-3556-2
  6. Thyroid Incidentalomas: Epidemiology, Risk Stratification with Ultrasound and Workup vol.3, pp.3, 2013, https://doi.org/10.1159/000365289
  7. Thyroid nodules with initially non-diagnostic, fine-needle aspiration results: comparison of core-needle biopsy and repeated fine-needle aspiration vol.24, pp.11, 2014, https://doi.org/10.1007/s00330-014-3325-4
  8. Ex Vivo Estimation of Photoacoustic Imaging for Detecting Thyroid Microcalcifications vol.9, pp.11, 2013, https://doi.org/10.1371/journal.pone.0113358
  9. Radiofrequency Ablation for Autonomously Functioning Thyroid Nodules: A Multicenter Study vol.25, pp.1, 2015, https://doi.org/10.1089/thy.2014.0100
  10. Evaluation of the Clinical Usefulness of BRAFV600E Mutation Analysis of Core-Needle Biopsy Specimens in Thyroid Nodules with Previous Atypia of Undetermined Significance or Follicular Lesio vol.25, pp.8, 2013, https://doi.org/10.1089/thy.2014.0606
  11. Web-Based Malignancy Risk Estimation for Thyroid Nodules Using Ultrasonography Characteristics: Development and Validation of a Predictive Model vol.25, pp.12, 2015, https://doi.org/10.1089/thy.2015.0188
  12. Malignancy risk stratification in thyroid nodules with nondiagnostic results at cytologic examination: combination of thyroid imaging reporting and data system and the Bethesda System. vol.274, pp.1, 2013, https://doi.org/10.1148/radiol.14140359
  13. Ultrasound-Guided Fine Needle Aspiration of Thyroid Nodules: A Consensus Statement by the Korean Society of Thyroid Radiology vol.16, pp.2, 2013, https://doi.org/10.3348/kjr.2015.16.2.391
  14. Radiofrequency versus Ethanol Ablation for Treating Predominantly Cystic Thyroid Nodules: A Randomized Clinical Trial vol.16, pp.6, 2015, https://doi.org/10.3348/kjr.2015.16.6.1332
  15. Thyroid autoimmunity and risk of malignancy in thyroid nodules submitted to fine‐needle aspiration cytology vol.37, pp.2, 2015, https://doi.org/10.1002/hed.23587
  16. Grey-Scale Analysis Improves the Ultrasonographic Evaluation of Thyroid Nodules vol.94, pp.27, 2015, https://doi.org/10.1097/md.0000000000001129
  17. Treatment of Benign Thyroid Nodules: Comparison of Surgery with Radiofrequency Ablation vol.36, pp.7, 2013, https://doi.org/10.3174/ajnr.a4276
  18. The Author's Reply: ‘Thyroid nodules diagnosed as follicular neoplasm: do not forget Doppler US and correlation to previous imaging findings’ vol.83, pp.2, 2013, https://doi.org/10.1111/cen.12743
  19. Intrathyroidal Ectopic Thymus in Children : Retrospective Analysis of Grayscale and Doppler Sonographic Features vol.34, pp.9, 2013, https://doi.org/10.7863/ultra.15.14.10041
  20. Value of sonographic features in predicting malignancy in thyroid nodules diagnosed as follicular neoplasm on cytology vol.83, pp.5, 2013, https://doi.org/10.1111/cen.12692
  21. Association between neck ultrasonographic findings and clinico‐pathological features in the follicular variant of papillary thyroid carcinoma vol.83, pp.6, 2013, https://doi.org/10.1111/cen.12674
  22. Evaluation of Thyroid Nodules by a Scoring and Categorizing Method Based on Sonographic Features vol.34, pp.12, 2013, https://doi.org/10.7863/ultra.14.11041
  23. The Role of Core-Needle Biopsy as a First-Line Diagnostic Tool for Initially Detected Thyroid Nodules vol.26, pp.3, 2013, https://doi.org/10.1089/thy.2015.0404
  24. Thyroid Imaging Reporting and Data System Risk Stratification of Thyroid Nodules: Categorization Based on Solidity and Echogenicity vol.26, pp.4, 2016, https://doi.org/10.1089/thy.2015.0460
  25. Application of high-resolution ultrasound, real-time elastography, and contrast-enhanced ultrasound in differentiating solid thyroid nodules vol.95, pp.45, 2013, https://doi.org/10.1097/md.0000000000005329
  26. Application of Thyroid Imaging Reporting and Data System in the Ultrasound Assessment of Thyroid Nodules According to Physician Experience vol.32, pp.2, 2016, https://doi.org/10.1097/ruq.0000000000000189
  27. JOURNAL CLUB: Retrospective Evaluation of Ultrasound Features of Thyroid Nodules to Assess Malignancy Risk: A Step Toward TIRADS vol.207, pp.3, 2013, https://doi.org/10.2214/ajr.15.15121
  28. How to Develop, Validate, and Compare Clinical Prediction Models Involving Radiological Parameters: Study Design and Statistical Methods vol.17, pp.3, 2013, https://doi.org/10.3348/kjr.2016.17.3.339
  29. Ultrasonography Diagnosis and Imaging-Based Management of Thyroid Nodules: Revised Korean Society of Thyroid Radiology Consensus Statement and Recommendations vol.17, pp.3, 2013, https://doi.org/10.3348/kjr.2016.17.3.370
  30. A Multicenter Prospective Validation Study for the Korean Thyroid Imaging Reporting and Data System in Patients with Thyroid Nodules vol.17, pp.5, 2013, https://doi.org/10.3348/kjr.2016.17.5.811
  31. A Prospective Study to Evaluate the Reliability of Thyroid Imaging Reporting and Data System in Differentiation between Benign and Malignant Thyroid Lesions vol.6, pp.1, 2013, https://doi.org/10.4103/2156-7514.177551
  32. Electronic Synoptic Reporting of Thyroid Nodules: Potential for Reduction in Number of Patients Undergoing Thyroid Nodule Biopsies vol.6, pp.3, 2013, https://doi.org/10.4236/ojrad.2016.63031
  33. A Modified Thyroid Imaging Reporting and Data System (mTI-RADS) For Thyroid Nodules in Coexisting Hashimoto’s Thyroiditis vol.6, pp.None, 2013, https://doi.org/10.1038/srep26410
  34. Risk stratification of thyroid nodules on ultrasonography with the French TI-RADS: description and reflections vol.35, pp.1, 2016, https://doi.org/10.14366/usg.15027
  35. Thyroid Nodules Detected by Contrast-Enhanced Magnetic Resonance Angiography: Prevalence and Clinical Significance vol.11, pp.2, 2016, https://doi.org/10.1371/journal.pone.0149811
  36. Initial clinical experience with BRAFV600E mutation analysis of core‐needle biopsy specimens from thyroid nodules vol.84, pp.4, 2013, https://doi.org/10.1111/cen.12866
  37. Quantitative Evaluation for Differentiating Malignant and Benign Thyroid Nodules Using Histogram Analysis of Grayscale Sonograms vol.35, pp.4, 2016, https://doi.org/10.7863/ultra.15.05055
  38. The Diagnostic Performance of Thyroid US in Each Category of the Bethesda System for Reporting Thyroid Cytopathology vol.11, pp.6, 2013, https://doi.org/10.1371/journal.pone.0155898
  39. Subcategorization of atypia of undetermined significance/follicular lesion of undetermined significance (AUS/FLUS): a study applying Thyroid Imaging Reporting and Data System (TIRADS) vol.85, pp.2, 2013, https://doi.org/10.1111/cen.12987
  40. Malignant-looking thyroid nodules with size reduction: core needle biopsy results vol.35, pp.4, 2013, https://doi.org/10.14366/usg.15082
  41. The predictive value of sonographic images of follicular lesions – a comparison with nodules unequivocal in FNA – single centre prospective study vol.16, pp.1, 2016, https://doi.org/10.1186/s12902-016-0151-5
  42. A retrospective study of ultrasound and FNA cytology investigation of thyroid nodules: working towards combined risk stratification vol.274, pp.6, 2017, https://doi.org/10.1007/s00405-017-4488-9
  43. Risk Stratification of Thyroid Nodules on Ultrasonography: Current Status and Perspectives vol.27, pp.12, 2017, https://doi.org/10.1089/thy.2016.0654
  44. Detection of Malignancy Among Suspicious Thyroid Nodules <1 cm on Ultrasound with Various Thyroid Image Reporting and Data Systems vol.27, pp.10, 2013, https://doi.org/10.1089/thy.2017.0034
  45. Detection of Malignancy Among Suspicious Thyroid Nodules <1 cm on Ultrasound with Various Thyroid Image Reporting and Data Systems vol.27, pp.10, 2013, https://doi.org/10.1089/thy.2017.0034
  46. Validation of Three Scoring Risk-Stratification Models for Thyroid Nodules vol.27, pp.12, 2013, https://doi.org/10.1089/thy.2017.0363
  47. Ultrasonography-Based Classification and Reporting System for the Malignant Risk of Thyroid Nodules vol.84, pp.3, 2017, https://doi.org/10.1272/jnms.84.118
  48. Core‐needle biopsy versus repeat fine‐needle aspiration for thyroid nodules initially read as atypia/follicular lesion of undetermined significance vol.39, pp.2, 2013, https://doi.org/10.1002/hed.24597
  49. First-Line Use of Core Needle Biopsy for High-Yield Preliminary Diagnosis of Thyroid Nodules vol.38, pp.2, 2013, https://doi.org/10.3174/ajnr.a5007
  50. Diagnostic accuracy of Thyroid Imaging Reporting and Data System in the prediction of malignancy in nodules with atypia and follicular lesion of undetermined significance cytologies vol.86, pp.4, 2013, https://doi.org/10.1111/cen.13274
  51. Likelihood of malignancy in thyroid nodules according to a proposed Thyroid Imaging Reporting and Data System (TI-RADS) classification merging suspicious and benign ultrasound features vol.61, pp.3, 2013, https://doi.org/10.1590/2359-3997000000262
  52. Size of thyroid carcinoma by histotype and variants: A population‐based study in a mildly iodine‐deficient area vol.39, pp.10, 2017, https://doi.org/10.1002/hed.24877
  53. Cytologically indeterminate thyroid nodules: increased diagnostic performance with combination of US TI-RADS and a new scoring system vol.7, pp.None, 2013, https://doi.org/10.1038/s41598-017-07353-y
  54. Differentiation of the Follicular Variant of Papillary Thyroid Carcinoma From Classic Papillary Thyroid Carcinoma: An Ultrasound Analysis and Complement to Fine-Needle Aspiration Cytology : Follicular vol.37, pp.3, 2013, https://doi.org/10.1002/jum.14377
  55. Combination of Maximum Shear Wave Elasticity Modulus and TIRADS Improves the Diagnostic Specificity in Characterizing Thyroid Nodules: A Retrospective Study vol.2018, pp.None, 2018, https://doi.org/10.1155/2018/4923050
  56. Complementary Role of Elastography Using Carotid Artery Pulsation in the Ultrasonographic Assessment of Thyroid Nodules: A Prospective Study vol.19, pp.5, 2018, https://doi.org/10.3348/kjr.2018.19.5.992
  57. Correlation between Ultrasound-based TIRADS and Bethesda System for Reporting Thyroid-cytopathology: 2-year Experience at a Tertiary Care Center in India vol.22, pp.5, 2013, https://doi.org/10.4103/ijem.ijem_27_18
  58. Assessment of Malignancy Risk in Thyroid Nodules Using a Practical Ultrasound Predictor Model: “Alpha Score” vol.8, pp.4, 2013, https://doi.org/10.4236/ojrad.2018.84022
  59. Pathologic basis of the sonographic differences between thyroid cancer and noninvasive follicular thyroid neoplasm with papillary-like nuclear features vol.37, pp.2, 2013, https://doi.org/10.14366/usg.17045
  60. Web‐based thyroid imaging reporting and data system: Malignancy risk of atypia of undetermined significance or follicular lesion of undetermined significance thyroid nodules calculated by a comb vol.40, pp.9, 2013, https://doi.org/10.1002/hed.25173
  61. Use of the ultrasound-based total malignancy score in the management of thyroid nodules vol.37, pp.4, 2013, https://doi.org/10.14366/usg.17063
  62. A Glimpse on Trends and Characteristics of Recent Articles Published in the Korean Journal of Radiology vol.20, pp.12, 2019, https://doi.org/10.3348/kjr.2019.0928
  63. The Diagnostic Performance of Afirma Gene Expression Classifier for the Indeterminate Thyroid Nodules: A Meta-Analysis vol.2019, pp.None, 2013, https://doi.org/10.1155/2019/7150527
  64. Integration of Sonoelastography Into the TIRADS Lexicon Could Influence the Classification vol.10, pp.None, 2013, https://doi.org/10.3389/fendo.2019.00127
  65. A new ultrasound nomogram for differentiating benign and malignant thyroid nodules vol.90, pp.2, 2019, https://doi.org/10.1111/cen.13898
  66. Risk Stratification of Thyroid Nodules Using the Thyroid Imaging Reporting and Data System (TIRADS): The Omission of Thyroid Scintigraphy Increases the Rate of Falsely Suspected Lesions vol.60, pp.3, 2019, https://doi.org/10.2967/jnumed.118.211912
  67. Comparisons and Combined Application of Two-Dimensional and Three-Dimensional Real-time Shear Wave Elastography in Diagnosis of Thyroid Nodules vol.10, pp.9, 2013, https://doi.org/10.7150/jca.30135
  68. Validation of web‐based thyroid imaging reporting and data system in atypia or follicular lesion of undetermined significance thyroid nodules vol.41, pp.7, 2013, https://doi.org/10.1002/hed.25677
  69. The Diagnostic Efficiency of Ultrasound Computer-Aided Diagnosis in Differentiating Thyroid Nodules: A Systematic Review and Narrative Synthesis vol.11, pp.11, 2019, https://doi.org/10.3390/cancers11111759
  70. British Thyroid Association 2014 classification ultrasound scoring of thyroid nodules in predicting malignancy: Diagnostic performance and inter-observer agreement vol.28, pp.1, 2013, https://doi.org/10.1177/1742271x19865001
  71. The value of conventional sonography and ultrasound elastography in decision-making for thyroid nodules in different categories of the Bethesda system for reporting thyroid cytopathology vol.74, pp.3, 2013, https://doi.org/10.3233/ch-180533
  72. Diagnostic Value of Six Thyroid Imaging Reporting and Data Systems (TIRADS) in Cytologically Equivocal Thyroid Nodules vol.9, pp.7, 2013, https://doi.org/10.3390/jcm9072281
  73. Development and validation of a Web‐based malignancy risk‐stratification system of thyroid nodules vol.93, pp.6, 2013, https://doi.org/10.1111/cen.14255
  74. Discriminating Malignancy in Thyroid Nodules: The Nomogram Versus the Kwak and ACR TI-RADS vol.163, pp.6, 2020, https://doi.org/10.1177/0194599820939071
  75. Reproducibility and Interobserver Agreement of Different Thyroid Imaging and Reporting Data Systems (TIRADS) vol.10, pp.2, 2013, https://doi.org/10.1159/000508959
  76. 2021 Korean Thyroid Imaging Reporting and Data System and Imaging-Based Management of Thyroid Nodules: Korean Society of Thyroid Radiology Consensus Statement and Recommendations vol.22, pp.None, 2021, https://doi.org/10.3348/kjr.2021.0713
  77. Diagnostic performance evaluation of different TI-RADS using ultrasound computer-aided diagnosis of thyroid nodules: An experience with adjusted settings vol.16, pp.1, 2013, https://doi.org/10.1371/journal.pone.0245617
  78. Applications of machine learning and deep learning to thyroid imaging: where do we stand? vol.40, pp.1, 2021, https://doi.org/10.14366/usg.20068