Magnetic resonance imaging: dynamic contrast enhancement and diffusion-weighted imaging to identify malignant cervical lymph nodes
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Radiologia Brasileira (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842018000200071 |
Resumo: | Abstract Objective: To examine the potential of two magnetic resonance imaging (MRI) techniques-dynamic contrast enhancement (DCE) and diffusion-weighted imaging (DWI)-for the detection of malignant cervical lymph nodes. Materials and Methods: Using DCE and DWI, we evaluated 33 cervical lymph nodes. For the DCE technique, the maximum relative enhancement, relative enhancement, time to peak enhancement, wash-in rate, wash-out rate, brevity of enhancement, and area under the curve were calculated from a semi-quantitative analysis. For the DWI technique, apparent diffusion coefficients (ADCs) were acquired in the region of interest of each lymph node. Cystic or necrotic parts were excluded. All patients underwent neck dissection or node biopsy. Imaging results were correlated with the histopathological findings. None of the patients underwent neoadjuvant treatment before neck dissection. Results: Relative enhancement, maximum relative enhancement, and the wash-in rate were significantly higher in malignant lymph nodes than in benign lymph nodes (p < 0.009; p < 0.05; and p < 0.03, respectively). The time to peak enhancement was significantly shorter in the malignant lymph nodes (p < 0.02). In the multivariate analysis, the variables identified as being the most capable of distinguishing between benign and malignant lymph nodes were time to peak enhancement (sensitivity, 73.7%; specificity, 69.2%) and relative enhancement (sensitivity, 89.2%; specificity, 69.2%). Conclusion: Although DCE was able to differentiate between benign and malignant lymph nodes, there is still no consensus regarding the use of a semi-quantitative analysis, which is difficult to apply in a clinical setting. Low ADCs can predict metastatic disease, although inflammatory processes might lead to false-positive results. |
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Radiologia Brasileira (Online) |
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Magnetic resonance imaging: dynamic contrast enhancement and diffusion-weighted imaging to identify malignant cervical lymph nodesLymph nodes/diagnostic imagingLymphatic metastasis/diagnostic imagingMagnetic resonance imaging/methodsDiffusion magnetic resonance imagingAbstract Objective: To examine the potential of two magnetic resonance imaging (MRI) techniques-dynamic contrast enhancement (DCE) and diffusion-weighted imaging (DWI)-for the detection of malignant cervical lymph nodes. Materials and Methods: Using DCE and DWI, we evaluated 33 cervical lymph nodes. For the DCE technique, the maximum relative enhancement, relative enhancement, time to peak enhancement, wash-in rate, wash-out rate, brevity of enhancement, and area under the curve were calculated from a semi-quantitative analysis. For the DWI technique, apparent diffusion coefficients (ADCs) were acquired in the region of interest of each lymph node. Cystic or necrotic parts were excluded. All patients underwent neck dissection or node biopsy. Imaging results were correlated with the histopathological findings. None of the patients underwent neoadjuvant treatment before neck dissection. Results: Relative enhancement, maximum relative enhancement, and the wash-in rate were significantly higher in malignant lymph nodes than in benign lymph nodes (p < 0.009; p < 0.05; and p < 0.03, respectively). The time to peak enhancement was significantly shorter in the malignant lymph nodes (p < 0.02). In the multivariate analysis, the variables identified as being the most capable of distinguishing between benign and malignant lymph nodes were time to peak enhancement (sensitivity, 73.7%; specificity, 69.2%) and relative enhancement (sensitivity, 89.2%; specificity, 69.2%). Conclusion: Although DCE was able to differentiate between benign and malignant lymph nodes, there is still no consensus regarding the use of a semi-quantitative analysis, which is difficult to apply in a clinical setting. Low ADCs can predict metastatic disease, although inflammatory processes might lead to false-positive results.Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem2018-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842018000200071Radiologia Brasileira v.51 n.2 2018reponame:Radiologia Brasileira (Online)instname:Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR)instacron:CBR10.1590/0100-3984.2017.0005info:eu-repo/semantics/openAccessCintra,Murilo BicudoRicz,HiltonMafee,Mahmood F.Santos,Antonio Carlos doseng2018-05-23T00:00:00Zoai:scielo:S0100-39842018000200071Revistahttps://www.scielo.br/j/rb/https://old.scielo.br/oai/scielo-oai.phpradiologiabrasileira@cbr.org.br1678-70990100-3984opendoar:2018-05-23T00:00Radiologia Brasileira (Online) - Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR)false |
dc.title.none.fl_str_mv |
Magnetic resonance imaging: dynamic contrast enhancement and diffusion-weighted imaging to identify malignant cervical lymph nodes |
title |
Magnetic resonance imaging: dynamic contrast enhancement and diffusion-weighted imaging to identify malignant cervical lymph nodes |
spellingShingle |
Magnetic resonance imaging: dynamic contrast enhancement and diffusion-weighted imaging to identify malignant cervical lymph nodes Cintra,Murilo Bicudo Lymph nodes/diagnostic imaging Lymphatic metastasis/diagnostic imaging Magnetic resonance imaging/methods Diffusion magnetic resonance imaging |
title_short |
Magnetic resonance imaging: dynamic contrast enhancement and diffusion-weighted imaging to identify malignant cervical lymph nodes |
title_full |
Magnetic resonance imaging: dynamic contrast enhancement and diffusion-weighted imaging to identify malignant cervical lymph nodes |
title_fullStr |
Magnetic resonance imaging: dynamic contrast enhancement and diffusion-weighted imaging to identify malignant cervical lymph nodes |
title_full_unstemmed |
Magnetic resonance imaging: dynamic contrast enhancement and diffusion-weighted imaging to identify malignant cervical lymph nodes |
title_sort |
Magnetic resonance imaging: dynamic contrast enhancement and diffusion-weighted imaging to identify malignant cervical lymph nodes |
author |
Cintra,Murilo Bicudo |
author_facet |
Cintra,Murilo Bicudo Ricz,Hilton Mafee,Mahmood F. Santos,Antonio Carlos dos |
author_role |
author |
author2 |
Ricz,Hilton Mafee,Mahmood F. Santos,Antonio Carlos dos |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Cintra,Murilo Bicudo Ricz,Hilton Mafee,Mahmood F. Santos,Antonio Carlos dos |
dc.subject.por.fl_str_mv |
Lymph nodes/diagnostic imaging Lymphatic metastasis/diagnostic imaging Magnetic resonance imaging/methods Diffusion magnetic resonance imaging |
topic |
Lymph nodes/diagnostic imaging Lymphatic metastasis/diagnostic imaging Magnetic resonance imaging/methods Diffusion magnetic resonance imaging |
description |
Abstract Objective: To examine the potential of two magnetic resonance imaging (MRI) techniques-dynamic contrast enhancement (DCE) and diffusion-weighted imaging (DWI)-for the detection of malignant cervical lymph nodes. Materials and Methods: Using DCE and DWI, we evaluated 33 cervical lymph nodes. For the DCE technique, the maximum relative enhancement, relative enhancement, time to peak enhancement, wash-in rate, wash-out rate, brevity of enhancement, and area under the curve were calculated from a semi-quantitative analysis. For the DWI technique, apparent diffusion coefficients (ADCs) were acquired in the region of interest of each lymph node. Cystic or necrotic parts were excluded. All patients underwent neck dissection or node biopsy. Imaging results were correlated with the histopathological findings. None of the patients underwent neoadjuvant treatment before neck dissection. Results: Relative enhancement, maximum relative enhancement, and the wash-in rate were significantly higher in malignant lymph nodes than in benign lymph nodes (p < 0.009; p < 0.05; and p < 0.03, respectively). The time to peak enhancement was significantly shorter in the malignant lymph nodes (p < 0.02). In the multivariate analysis, the variables identified as being the most capable of distinguishing between benign and malignant lymph nodes were time to peak enhancement (sensitivity, 73.7%; specificity, 69.2%) and relative enhancement (sensitivity, 89.2%; specificity, 69.2%). Conclusion: Although DCE was able to differentiate between benign and malignant lymph nodes, there is still no consensus regarding the use of a semi-quantitative analysis, which is difficult to apply in a clinical setting. Low ADCs can predict metastatic disease, although inflammatory processes might lead to false-positive results. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-04-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842018000200071 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842018000200071 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0100-3984.2017.0005 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem |
publisher.none.fl_str_mv |
Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem |
dc.source.none.fl_str_mv |
Radiologia Brasileira v.51 n.2 2018 reponame:Radiologia Brasileira (Online) instname:Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR) instacron:CBR |
instname_str |
Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR) |
instacron_str |
CBR |
institution |
CBR |
reponame_str |
Radiologia Brasileira (Online) |
collection |
Radiologia Brasileira (Online) |
repository.name.fl_str_mv |
Radiologia Brasileira (Online) - Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR) |
repository.mail.fl_str_mv |
radiologiabrasileira@cbr.org.br |
_version_ |
1754208939783749632 |