Shear wave elastography of lymph nodes in dogs with head and neck cancer: A pilot study.
Vet Comp Oncol
; 20(2): 521-528, 2022 Jun.
Article
em En
| MEDLINE
| ID: mdl-35080328
ABSTRACT
Shear wave elastography (SWE) is a novel ultrasound imaging technique, used in human medicine to differentiate metastatic from non-metastatic lymph nodes (LNs) based on higher tissue stiffness. The objective of this pilot study was to evaluate whether canine metastatic LNs were stiffer compared to non-metastatic LNs. SWE of sentinel or regional LNs in dogs with head and neck cancer was performed. Ten elastograms of each LN were acquired. In each elastogram, mean, median, and maximum shear wave velocities (SWVs) were calculated in the most elastic region, the stiffest region, and the entire LN. The means of those SWVs for each region of each LN were subsequently calculated. Furthermore, a stepwise subsampling was performed to assess the effect of the number of acquired elastograms on the consistency of the classification of a LN as metastatic or not. Twenty-four LNs in 15 dogs with head and neck cancer were included, of which 10 LNs were metastatic. Metastatic medial retropharyngeal and mandibular LNs were successfully distinguished from non-metastatic LNs based on higher mean and median SWVs in the stiffest region and higher maximum SWVs in entire LNs. Furthermore, maximum SWVs in the stiffest region of mandibular LNs were higher in metastatic LNs compared to non-metastatic LNs. Downstream analyses demonstrated that at least eight elastograms were necessary to perform reliable analyses. This pilot trial demonstrated that SWE has potential to discriminate metastatic from non-metastatic LNs; however, LN status should be based on at least eight elastograms in future clinical trials.
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Texto completo:
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Doenças do Cão
/
Técnicas de Imagem por Elasticidade
/
Neoplasias de Cabeça e Pescoço
Tipo de estudo:
Diagnostic_studies
Limite:
Animals
Idioma:
En
Revista:
Vet Comp Oncol
Ano de publicação:
2022
Tipo de documento:
Article