DOI: http://dx.doi.org/10.18203/2349-2902.isj20205866

Combined preoperative serum thyroglobulin level and ACR-thyroid imaging reporting and data system scoring could accurately define malignant thyroid nodules

Waseem A. Shoda

Abstract


Background: Evaluation of diagnostic ability of preoperative estimation of serum thyroglobulin (TG) to detect malignant thyroid nodules (TN) in comparison to the American College of Radiology, Thyroid imaging reporting and data system (ACR-TIRADS), fine needle aspiration cytology (FNAC) and intraoperative frozen section (IO-FS).

Methods: 34 patients with ACR-TIRADS 2-4 TN were evaluated preoperatively for identification of malignancy and all underwent total thyroidectomy with bilateral neck block dissection if indicated. Results of preoperative investigations were statistically analyzed using the Receiver operating characteristics (ROC) curve analysis as predictors for malignancy in comparison to postoperative paraffin sections.

Results: Preoperative serum TG levels had 100% sensitivity and negative predictive value, while ACR-TIRADS scoring had 100% specificity and positive predictive value with accuracy rates of 95.35% and 97.67% for TG and TIRADS, respectively. ROC curve analysis defined preoperative ACR-TIRADS class and serum TG as highly diagnostic than FNAC for defining malignancy with non-significant difference between areas under curve for TIRADS and TG. For cases had intermediate risk of malignancy on TIRADS, IO-FS had missed 3, FNAC missed 4, while serum TG levels were very high in the 13 cases and were defined by ROC curve as the only significant predictor for malignancy.

Conclusions: Preoperative estimation of serum TG showed higher diagnostic validity than FNAC, high predictability of cancer and ability to verify the intermediate findings on TIRADS. Combined preoperative TIRADS and TG estimation could accurately discriminate malignant TN with high accuracy and spare the need for preoperative FNAC or IO-FS.

 


Keywords


Thyroid nodules, Thyroid imaging reporting and data system classification, Thyroglobulin, Fine needle aspiration cytology, Frozen section, Prediction of malignancy

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References


Chang L, Fu C, Wu Z, Liu W, Yang S. Data-Driven Analysis of Radiologists' Behavior for Diagnosing Thyroid Nodules. IEEE J Biomed Health Inform. 2020;24(11):3111-123.

Kaderli R, Trepp R: [From thyroid nodules to thyroid cancer]. Ther Umsch. 2020;77(9):419-25.

Lloyd R, Osamura R, Klöppel G, Rosai J. WHO classification of tumours of endocrine organs, 4th ed., International Agency for Research on Cancer (IARC), Lyon, France.

Foppiani L, Sola S, Cabria M, Bottoni G, Piccardo A. Unstimulated Serum Thyroglobulin Levels after Thyroidectomy and Radioiodine Therapy for Intermediate-Risk Thyroid Cancer Are Not Always a Reliable Marker of Lymph Node Recurrence: Case Report and a Lesson for Clinicians. Case Rep Endocrinol. 2020;2020:8827503.

Ataide E, Ponugoti N, Illanes A, Schenke S, Kreissl M, Friebe M. Thyroid Nodule Classification for Physician Decision Support Using Machine Learning-Evaluated Geometric and Morphological Features. Sensors (Basel). 2020;20(21):6110.

Hoang J, Middleton W, Tessler F: Update on ACR TI-RADS: Successes, Challenges and Future Directions, From the AJR Special Series on Radiology Reporting and Data Systems. AJR Am J Roentgenol. 2020.

Kim P, Suh C, Baek J, Chung S, Choi Y, Lee J. Unnecessary thyroid nodule biopsy rates under four ultrasound risk stratification systems: a systematic review and meta-analysis. Eur Radiol. 2020.

Citterio C, Morishita Y, Dakka N, Veluswamy B, Arvan P. Relationship between the dimerization of thyroglobulin and its ability to form triiodothyronine. J Biol Chem. 2018;293(13):4860-869.

Wright M, Kouba L, Plate L. Thyroglobulin interactome profiling defines altered proteostasis topology associated with thyroid dyshormonogenesis. Mol Cell Proteomics. 2020; mcp.RA120.002168.

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.

Jain V. Safe and Optimum Steps for Total / Hemi Thyroidectomy. Otolaryngol Open Access J. 2016;1(4):000120.

Grani G, Lamartina L, Ascoli V, Bosco D, Biffoni M, Giacomelli L et al. Reducing the Number of Unnecessary Thyroid Biopsies While Improving Diagnostic Accuracy: Toward the "Right" TIRADS. J Clin Endocrinol Metab. 2019;104(1):95-102.

Grani G, Brenta G, Trimboli P, Falcone R, Ramundo V, Maranghi M, et al. Sonographic Risk Stratification Systems for Thyroid Nodules as Rule-Out Tests in Older Adults. Cancers (Basel). 2020;12(9):2458.

Zhang W, Xu H, Zhang Y, Guo L, Xu S, Zhao C et al. Comparisons of ACR TI-RADS, ATA guidelines, Kwak TI-RADS, and KTA/KSThR guidelines in malignancy risk stratification of thyroid nodules. Clin Hemorheol Microcirc. 2020;75(2):219-32.

Hasukic B, Jakubovic-Cickusic A, Sehanovic E, Osmic H. Fine Needle Aspiration Cytology and Thyroglobulin Antibodies in Preoperative Diagnosis of Thyroid Malignancy. Med Arch. 2019;73(6):382-85.

DU Y, Gao Y, Feng Z, Meng F, Fan L, Sun D. Serum Thyroglobulin-A Sensitive Biomarker of Iodine Nutrition Status and Affected by Thyroid Abnormalities and Disease in Adult Populations. Biomed Environ Sci. 2017;30(7):508-16.

Patell R, Mikhael A, Tabet M, Bena J, Berber E, Nasr C. Assessing the utility of preoperative serum thyroglobulin in differentiated thyroid cancer: a retrospective cohort study. Endocrine. 2018;61(3):506-10.

Zhong Y, He J, Zhang C, Ardlee B. Treatment of Differentiated Thyroid Cancer and Recurrent Laryngeal Nerve Function with 131 Iodine Based on PET / CT Image Segmentation Algorithm. World Neurosurg. 2020;S1878-8750(20)32362-7.

Hulikal N, Re A, Banoth M, Chowhan A, Yutla M, Sachan A. Can preoperative serum thyroglobulin levels predict the risk of malignancy? Results from prospective analysis of biochemical predictors of malignancy in thyroid nodules. Acta Otorhinolaryngol Ital. 2020;40(1):33-37.

Tkachuk N: Thyroid and Pseudothyroid Dysfunction as a Cause that is Promoting the Relapse of Benign Focal Thyroid Pathology. J Med Life. 2020;13(3):426-30.

Yu Q, Liu K, Xie C, Ma D, Wu Y, Jiang H, Dai W. Development and validation of a preoperative prediction model for follicular thyroid carcinoma. Clin Endocrinol (Oxf). 2019;91(2):348-55.

Miao S, Jing M, Sheng R, Cui D, Lu S, Zhang X et al. The analysis of differential diagnosis of benign and malignant thyroid nodules based on ultrasound reports. Gland Surg. 2020;9(3):653-60.