The Diagnostic Accuracy of Strain Elastography in Differentiating Benign and Malignant Thyroid Lesions Keeping Histopathology as Gold Standard
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Elastography represents a contemporary technique employed in the assessment of thyroid nodules through the comparison of tissue elasticity. Strain and shear wave elastography are two varieties of elastography currently utilized in clinical settings. The objective of this investigation was to ascertain the diagnostic precision of strain ultrasound elastography in distinguishing between benign and malignant thyroid nodules, utilizing histopathology as the definitive standard. Objective: To determine the diagnostic accuracy of strain ultrasound elastography in differentiation between benign and malignant thyroid lesions keeping histopathology as gold standard. Methodology: The study at Radiology Department, Mayo Hospital, Lahore from 28 February 2024 to 27 August 2024, included 170 patients with thyroid nodules. Strain ultrasound elastography distinguished benign and malignant nodules by comparing findings with histopathology. Analysis was done using SPSS 25.0 with 2×2 contingency table for sensitivity, specificity, predictive values, and diagnostic accuracy compared to histopathology. Results: In this investigation, a cohort of 170 individuals presenting with thyroid nodules was examined. Among these subjects, 57.6% were identified as male and 42.4% as female, with ages spanning from 18 to 80 years, yielding a mean age of 52.95±10.785. Strain elastography exhibited a sensitivity of 86.7%, specificity of 92.0%, positive predictive value of 96.2%, negative predictive value of 74.1%, and an overall accuracy of 88.2% in differentiating benign from malignant lesions. Conclusion: Strain elastography represents a noninvasive technique utilized to differentiate between benign and malignant thyroid nodules, in addition to discerning patients who necessitate surgical intervention.
Authors: Saba Sabahat, Irum Shahzad, Zeeshan Ahmad
Institution: Mayo Hospital
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4408338192