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Diagnostic Value of Real-Time Shear Wave Elastography in Diagnosing Thyroid Cancer

Authors :
Maria Cristina Oprea
Lazar Fulger
Mihaela Vlad
Ioan Sporea
Ioana Golu
Source :
Revista de Chimie. 68:2818-2822
Publication Year :
2018
Publisher :
Revista de Chimie SRL, 2018.

Abstract

Thyroid nodules are a common pathology found in 50 to 60% of otherwise healthy people. Diagnostic imaging techniques are help discriminating between benign and malignant nodules, while fine needle aspiration is still a gold standard. Shear wave elastography, a recent imaging technique, holds the promise to become reliable diagnostic tools and is currently used in combination with ultrasound. We here report data obtained in a series of 52 thyroid nodules analysed by means of elastography, as well as conventional and Doppler ultrasound. We found no differences in age, nodule and thyroid volume, length, width, thickness and maximum diameter between benign and malignant lesions. Several sonographic patterns are considered to be predictive of malignancy, out of which we only found the intranodular blood flow to be statistically significant. By the means of shear wave elastography we have first assessed tissue elasticities, which are shown in a range of colours, depending on tissue elasticity/stiffness. Then, we have measured and recorded four parameters automatically displayed by the system, namely SWE-mean, SWE-max, SWE-SD and SWE-ratio. Data analysis showed all these quantitative parameters had good sensitivity, specificity, positive predictive value, negative predictive value and area under the curve, as calculated by the ROC curve. As with these parameters, the cut-off points were lower than in literature, still able to indicate reliable diagnoses, which were confirmed by histopathological exam. Our conclusion is that shear wave elastography has great potential for reliably and accurately diagnosing thyroid malignancies.

Details

ISSN :
26688212 and 00347752
Volume :
68
Database :
OpenAIRE
Journal :
Revista de Chimie
Accession number :
edsair.doi...........6088e66763c16697137cb7ebe60bbc43