Ultrasound Elastography in Differentiating Benign and Malignant Thyroid Lesions and its Correlation with Fine Needle Aspiration Cytology or Biopsy Results
Journal Title: Journal of Clinical and Diagnostic Research - Year 2018, Vol 12, Issue 12
Abstract
ABSTRACT Introduction: Ultrasound Elastography is a newly developed, non-invasive imaging technique that can be used as an adjunct in assessment of the thyroid lesions. Aim: To evaluate the diagnostic performance of ultrasound elastography in characterising thyroid lesions as benign/malignant and to correlate with FNAC/biopsy results. Materials and Methods: A hospital based prospective diagnostic study on ultrasound elastography was done on 88 pathologically proven thyroid lesions in 86 patients of 20 years or above of age on SIEMENS ACUSON S 2000 machine. Elasticity Imaging (EI) scores and Shear Wave Velocity (SWV) values were assessed and the findings were correlated with FNAC or Biopsy results. Receiver Operating Characteristic (ROC) curve analysis was done to find sensitivity and specificity values. Areas under ROC curves, best cut-off values and 95% confidence intervals were calculated. Results: Out of 88 lesions, 15 lesions were malignant and 73 lesions were benign on FNAC or biopsy. On EI, 5 lesions had score of 1, 58 lesions had score of 2, 13 lesions had score of 3, 10 lesions had score of 4 and 2 lesions had score of 5. The optimal cut-off point for SWV values was 2.87 m/s. The mean SWVs were 2.17±0.84 m/s for benign and 6.17±2.72 m/s for malignant lesions and was statistically significant (p<0.001). The sensitivity and specificity were 93.3%, and 84.9% for EI scores and 86.7% and 94.5% respectively for SWV values. Conclusion: Ultrasound Thyroid Elastography (Shear > Strain) has high potential to satisfactorily differentiate benign from malignant lesions, thereby reducing the need of unnecessary invasive FNAC/biopsy procedures.
Authors and Affiliations
Pradeep Madhichettiar Dhayalan, Dilip Shankar Phansalkar, CM Kiran, Himagirish Rao, Prince K Philip, Mohnish Palanisamy, Sabari Ramesh, Archana Koshy
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