Role of elastography strain ratio and TIRADS score in predicting malignant thyroid nodule.

Abstract

Ultrasonography (US) is the most accurate and cost-effective imaging method in diagnosis of thyroid nodules. A practical thyroid imaging reporting and data system (TIRADS) for thyroid nodules has been proposed to classify nodules of the thyroid gland to solve the problem of nodule selection for fine needle aspiration cytology (FNAC). Real-time elastography and strain ratio (SR) is a method used to assess the stiffness and predict the malignancy of thyroid nodules. The objective of this study was to assess the role of elastography and SR and the TIRADS scoring system in discriminating malignant from benign thyroid nodules. From 2015 to 2018 at Cairo University Hospital, a series of 409 patients with thyroid nodules was referred to undergo thyroid ultrasound. Categorization of each nodule according to the TIRADS ranged from 1 to 5. The qualitative elastography score and semiquantitative SR of the nodules were evaluated. Final diagnosis was done by either post-thyroidectomy histopathological examination or US-guided FNAC. Our study included 409 patients with thyroid nodules. Their mean age was 39 ± 10 SD; 36 were males and 373 were females. There were 22 malignant nodules and 387 benign nodules. There were statistical differences between benign and malignant nodules regarding TIRADS classification, SR, anteroposterior/transverse ratio, degree of echogenicity, border, presence of calcification, and absence of halo sign (P < 0.001). The elastic properties of thyroid nodules proved to be a good discriminator between malignant and benign nodules (P- < 0.001) at a cut off value of > 2.32 with 95.2% sensitivity and 86.5% specificity. For every unit increase in SR, the risk of malignancy increased by nearly 2 times. Patients with irregular borders had nearly 17 times increased risk of malignancy than those with regular borders. Elastography and SR proved to be of high significant value in discriminating benign from malignant nodules, so we recommend adding it to the TIRADS classification.