Advances in imaging techniques for thyroid disease: ultrasound, elastography, and beyond – A prospective observational cross-sectional study.
DOI:
https://doi.org/10.51168/sjhrafrica.v7i2.2656Cuvinte cheie:
Thyroid nodules, ultrasonography, elastography, diagnostic imaging, thyroid cancer, FNACRezumat
Background
Accurate differentiation of benign and malignant thyroid nodules is essential for appropriate management and early detection of thyroid cancer. While ultrasonography (USG) is the primary imaging modality for thyroid evaluation, its specificity is limited by overlapping features between benign and malignant lesions. Elastography and other advanced imaging techniques have emerged as valuable adjuncts to improve diagnostic accuracy.
Methods
This prospective observational cross-sectional study included 110 adult patients with suspected thyroid disease over 11 months. All participants underwent conventional ultrasonography and elastography, while selected cases received advanced imaging, including contrast-enhanced ultrasonography and Doppler vascularity assessment. Imaging findings were correlated with fine-needle aspiration cytology (FNAC) and histopathological examination. Diagnostic performance was assessed using sensitivity, specificity, accuracy, and Chi-square testing, with p<0.05 considered statistically significant.
Results
Among the 110 patients, 78 (70.9%) had benign lesions, and 32 (29.1%) had malignant lesions. Ultrasonography demonstrated a sensitivity of 85.2%, specificity of 72.5%, and accuracy of 78.9%. Elastography showed superior performance with a sensitivity of 90.6%, specificity of 84.3%, and accuracy of 87.3%. The combined use of ultrasonography and elastography achieved the highest diagnostic accuracy (90.9%) and showed a statistically significant improvement compared with individual modalities (p=0.008). Elastography scores of 4–5 were significantly associated with malignancy (p=0.001). Hypoechogenicity, microcalcifications, and irregular margins were also significantly associated with malignant lesions.
Conclusion
Elastography significantly enhances the diagnostic performance of conventional ultrasonography. A multimodal imaging approach improves diagnostic accuracy and may reduce unnecessary invasive procedures.
Recommendation
Routine incorporation of elastography alongside conventional ultrasonography is recommended for comprehensive evaluation of thyroid nodules and improved early detection of thyroid malignancy.
Referințe
Dudea SM, Botar-jid C. Ultrasound elastography in thyroid disease. Med Ultrason. 2015;17(1):74-96. https://doi.org/10.11152/mu.2013.2066.171.smd
Chaudhary V, Bano S. Thyroid ultrasound. Indian J Endocrinol Metab. 2013;17(2):1-9. https://doi.org/10.4103/2230-8210.109667
Zhao C, Xu H. Ultrasound elastography of the thyroid : principles and current status. Ultrasonography. 2019;38(April):106-24. https://doi.org/10.14366/usg.18037
Sigrist RMS, Liau J, Kaffas A El, Chammas MC, Willmann JK. Ultrasound Elastography : Review of Techniques and Clinical Applications. Theranostics. 2017;7(5):1-27. https://doi.org/10.7150/thno.18650
Abukhalil AAO and T. Ultrasound Elastography : Methods, Clinical Applications, and Limitations : A Review Article. Appl Sci. 2024;14(4308):1-17. https://doi.org/10.3390/app14104308
Angelopoulos N, Tessler FN, Goulis DG, Chrisogonidis I, Iakovou I. Elastography Enhances Diagnostic Accuracy of ACR TI-RADS in Thyroid Nodule Evaluation. J Clin Endocrinol Metab [Internet]. 2025;00(September):1-10. Available from: https://doi.org/10.1210/clinem/dgaf670
Shi J, Zhou W, Zhang H, Shen Y, Zhang H, Li T. Advancements and challenges of ultrasound imaging in the management of thyroid-associated ophthalmopathy. World J Radiol. 2025;17(11):1-12. https://doi.org/10.4329/wjr.v17.i11.112638
Zhao H, Xue T, Zhang Y, Lu Y, Wang D, Yin P, et al. Artificial intelligence in the diagnosis of thyroid diseases : applications and challenges. Front Radiol. 2026;6(April):1-20. https://doi.org/10.3389/fradi.2026.1740915
Liang X, Cai Y, Yu J, Liao J, Chen Z. Update on thyroid ultrasound : a narrative review from diagnostic criteria to artificial intelligence techniques. Chin Med J (Engl). 2019;132(16):1974-82. https://doi.org/10.1097/CM9.0000000000000346
Barzegar-golmoghani E, Mohebi M, Gohari Z, Aram S, Moradian S, Ahmadi M, et al. ELTIRADS framework for thyroid nodule classification integrating elastography, TIRADS, and radiomics with interpretable machine learning. Sci Rep. 2025;15(8763):1-15. https://doi.org/10.1038/s41598-025-93226-8
McQueen AS, Bhatia KSS. Thyroid nodule ultrasound : technical advances and future horizons. Insights Imaging. 2015;6:173-88. https://doi.org/10.1007/s13244-015-0398-9
Descărcări
Publicat
Număr
Secțiune
Licență
Copyright (c) 2026 Shikhar Saxena, Parul Sachan, Daya Shankar, Rohini Srivastava

TAceastă lucrare este licențiată în temeiul Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.














