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Utility of Ultrasound Elastography to Differentiate Benign from Malignant Cervical Lymph Nodes

BACKGROUND: The purpose of this study was to evaluate the usefulness of strain elastography and acoustic radiation force impulse (ARFI) imaging in the differentiation of benign and malignant cervical lymph nodes (LNs). MATERIALS AND METHODS: In this prospective study, 50 enlarged cervical LNs (33 be...

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Autores principales: Kanagaraju, Vikrant, Rakshith, A. V. B., Devanand, B., Rajakumar, R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7446693/
https://www.ncbi.nlm.nih.gov/pubmed/32874867
http://dx.doi.org/10.4103/JMU.JMU_72_19
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author Kanagaraju, Vikrant
Rakshith, A. V. B.
Devanand, B.
Rajakumar, R.
author_facet Kanagaraju, Vikrant
Rakshith, A. V. B.
Devanand, B.
Rajakumar, R.
author_sort Kanagaraju, Vikrant
collection PubMed
description BACKGROUND: The purpose of this study was to evaluate the usefulness of strain elastography and acoustic radiation force impulse (ARFI) imaging in the differentiation of benign and malignant cervical lymph nodes (LNs). MATERIALS AND METHODS: In this prospective study, 50 enlarged cervical LNs (33 benign and 17 malignant) were examined by B-mode ultrasound (US), color Doppler, and strain elastography. Elastographic patterns (1–5) were categorized based on distribution of hard area within LN. The shear wave velocity (SWV) of LNs was evaluated by ARFI imaging. Diagnostic performance of sonoelastographic parameters was compared taking histopathology of LN as a reference standard. Optimal cutoff value of the mean SWV values for predicting malignancy was determined using receiver operating characteristic curve analysis. RESULTS: Among US parameters, borders of LN had the highest diagnostic accuracy (80%), while echogenicity had the least (48%). Majority of benign LNs (n = 31) had elastography patterns 1 and 2, while majority of malignant LNs (n = 16) had patterns 3–5 (P = 0.000). The sensitivity, specificity, and accuracy of elastography were 94.1%, 93.9%, and 94%, respectively. The mean SWV of benign LNs (1.670 ± 0.367 m/s) differed significantly from malignant LNs (2.965 ± 0.826 m/s; P = 0.000). A cutoff value of 2.05 m/s predicted malignancy with 88.2% sensitivity and 84.8% specificity and gave an area under the curve of 0.949 (95% confidence interval: 0.70–1.20). CONCLUSION: Elastography has high diagnostic accuracy in differentiating benign and malignant cervical LNs and can be potentially useful in selecting the LN with high probability of malignancy, on which fine-needle aspiration cytology/biopsy can be performed.
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spelling pubmed-74466932020-08-31 Utility of Ultrasound Elastography to Differentiate Benign from Malignant Cervical Lymph Nodes Kanagaraju, Vikrant Rakshith, A. V. B. Devanand, B. Rajakumar, R. J Med Ultrasound Original Article BACKGROUND: The purpose of this study was to evaluate the usefulness of strain elastography and acoustic radiation force impulse (ARFI) imaging in the differentiation of benign and malignant cervical lymph nodes (LNs). MATERIALS AND METHODS: In this prospective study, 50 enlarged cervical LNs (33 benign and 17 malignant) were examined by B-mode ultrasound (US), color Doppler, and strain elastography. Elastographic patterns (1–5) were categorized based on distribution of hard area within LN. The shear wave velocity (SWV) of LNs was evaluated by ARFI imaging. Diagnostic performance of sonoelastographic parameters was compared taking histopathology of LN as a reference standard. Optimal cutoff value of the mean SWV values for predicting malignancy was determined using receiver operating characteristic curve analysis. RESULTS: Among US parameters, borders of LN had the highest diagnostic accuracy (80%), while echogenicity had the least (48%). Majority of benign LNs (n = 31) had elastography patterns 1 and 2, while majority of malignant LNs (n = 16) had patterns 3–5 (P = 0.000). The sensitivity, specificity, and accuracy of elastography were 94.1%, 93.9%, and 94%, respectively. The mean SWV of benign LNs (1.670 ± 0.367 m/s) differed significantly from malignant LNs (2.965 ± 0.826 m/s; P = 0.000). A cutoff value of 2.05 m/s predicted malignancy with 88.2% sensitivity and 84.8% specificity and gave an area under the curve of 0.949 (95% confidence interval: 0.70–1.20). CONCLUSION: Elastography has high diagnostic accuracy in differentiating benign and malignant cervical LNs and can be potentially useful in selecting the LN with high probability of malignancy, on which fine-needle aspiration cytology/biopsy can be performed. Wolters Kluwer - Medknow 2019-12-10 /pmc/articles/PMC7446693/ /pubmed/32874867 http://dx.doi.org/10.4103/JMU.JMU_72_19 Text en Copyright: © 2019 Journal of Medical Ultrasound http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Kanagaraju, Vikrant
Rakshith, A. V. B.
Devanand, B.
Rajakumar, R.
Utility of Ultrasound Elastography to Differentiate Benign from Malignant Cervical Lymph Nodes
title Utility of Ultrasound Elastography to Differentiate Benign from Malignant Cervical Lymph Nodes
title_full Utility of Ultrasound Elastography to Differentiate Benign from Malignant Cervical Lymph Nodes
title_fullStr Utility of Ultrasound Elastography to Differentiate Benign from Malignant Cervical Lymph Nodes
title_full_unstemmed Utility of Ultrasound Elastography to Differentiate Benign from Malignant Cervical Lymph Nodes
title_short Utility of Ultrasound Elastography to Differentiate Benign from Malignant Cervical Lymph Nodes
title_sort utility of ultrasound elastography to differentiate benign from malignant cervical lymph nodes
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7446693/
https://www.ncbi.nlm.nih.gov/pubmed/32874867
http://dx.doi.org/10.4103/JMU.JMU_72_19
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