Microvascular invasion in hepatocellular carcinoma: is it predictable with quantitative computed tomography parameters?

Detalhes bibliográficos
Autor(a) principal: Lahan-Martins,Daniel
Data de Publicação: 2019
Outros Autores: Perales,Simone Reges, Gallani,Stephanie Kilaris, Costa,Larissa Bastos Eloy da, Lago,Eduardo Andreazza Dal, Boin,Ilka de Fátima Santana Ferreira, Caserta,Nelson Marcio Gomes, Ataide,Elaine Cristina de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Radiologia Brasileira (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842019000500287
Resumo: Abstract Objective: To investigate whether quantitative computed tomography (CT) measurements can predict microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Materials and Methods: This was a retrospective analysis of 200 cases of surgically proven HCCs in 125 consecutive patients evaluated between March 2010 and November 2017. We quantitatively measured regions of interest in lesions and adjacent areas of the liver on unenhanced CT scans, as well as in the arterial, portal venous, and equilibrium phases on contrast-enhanced CT scans. Enhancement profiles were analyzed and compared with histopathological references of MVI. Univariate and multivariate logistic regression analyses were used in order to evaluate CT parameters as potential predictors of MVI. Results: Of the 200 HCCs, 77 (38.5%) showed evidence of MVI on histopathological analysis. There was no statistical difference between HCCs with MVI and those without, in terms of the percentage attenuation ratio in the portal venous phase (114.7 vs. 115.8) and equilibrium phase (126.7 vs. 128.2), as well as in terms of the relative washout ratio, also in the portal venous and equilibrium phases (15.0 vs. 8.2 and 31.4 vs. 26.3, respectively). Conclusion: Quantitative dynamic CT parameters measured in the preoperative period do not appear to correlate with MVI in HCC.
id CBR-1_fca0618a0371cc25e2a0080806bcbd4e
oai_identifier_str oai:scielo:S0100-39842019000500287
network_acronym_str CBR-1
network_name_str Radiologia Brasileira (Online)
repository_id_str
spelling Microvascular invasion in hepatocellular carcinoma: is it predictable with quantitative computed tomography parameters?Carcinoma, hepatocellularTomography, X-ray computedLiver neoplasms/surgeryLiver transplantationAbstract Objective: To investigate whether quantitative computed tomography (CT) measurements can predict microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Materials and Methods: This was a retrospective analysis of 200 cases of surgically proven HCCs in 125 consecutive patients evaluated between March 2010 and November 2017. We quantitatively measured regions of interest in lesions and adjacent areas of the liver on unenhanced CT scans, as well as in the arterial, portal venous, and equilibrium phases on contrast-enhanced CT scans. Enhancement profiles were analyzed and compared with histopathological references of MVI. Univariate and multivariate logistic regression analyses were used in order to evaluate CT parameters as potential predictors of MVI. Results: Of the 200 HCCs, 77 (38.5%) showed evidence of MVI on histopathological analysis. There was no statistical difference between HCCs with MVI and those without, in terms of the percentage attenuation ratio in the portal venous phase (114.7 vs. 115.8) and equilibrium phase (126.7 vs. 128.2), as well as in terms of the relative washout ratio, also in the portal venous and equilibrium phases (15.0 vs. 8.2 and 31.4 vs. 26.3, respectively). Conclusion: Quantitative dynamic CT parameters measured in the preoperative period do not appear to correlate with MVI in HCC.Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem2019-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842019000500287Radiologia Brasileira v.52 n.5 2019reponame:Radiologia Brasileira (Online)instname:Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR)instacron:CBR10.1590/0100-3984.2018.0123info:eu-repo/semantics/openAccessLahan-Martins,DanielPerales,Simone RegesGallani,Stephanie KilarisCosta,Larissa Bastos Eloy daLago,Eduardo Andreazza DalBoin,Ilka de Fátima Santana FerreiraCaserta,Nelson Marcio GomesAtaide,Elaine Cristina deeng2019-10-21T00:00:00Zoai:scielo:S0100-39842019000500287Revistahttps://www.scielo.br/j/rb/https://old.scielo.br/oai/scielo-oai.phpradiologiabrasileira@cbr.org.br1678-70990100-3984opendoar:2019-10-21T00:00Radiologia Brasileira (Online) - Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR)false
dc.title.none.fl_str_mv Microvascular invasion in hepatocellular carcinoma: is it predictable with quantitative computed tomography parameters?
title Microvascular invasion in hepatocellular carcinoma: is it predictable with quantitative computed tomography parameters?
spellingShingle Microvascular invasion in hepatocellular carcinoma: is it predictable with quantitative computed tomography parameters?
Lahan-Martins,Daniel
Carcinoma, hepatocellular
Tomography, X-ray computed
Liver neoplasms/surgery
Liver transplantation
title_short Microvascular invasion in hepatocellular carcinoma: is it predictable with quantitative computed tomography parameters?
title_full Microvascular invasion in hepatocellular carcinoma: is it predictable with quantitative computed tomography parameters?
title_fullStr Microvascular invasion in hepatocellular carcinoma: is it predictable with quantitative computed tomography parameters?
title_full_unstemmed Microvascular invasion in hepatocellular carcinoma: is it predictable with quantitative computed tomography parameters?
title_sort Microvascular invasion in hepatocellular carcinoma: is it predictable with quantitative computed tomography parameters?
author Lahan-Martins,Daniel
author_facet Lahan-Martins,Daniel
Perales,Simone Reges
Gallani,Stephanie Kilaris
Costa,Larissa Bastos Eloy da
Lago,Eduardo Andreazza Dal
Boin,Ilka de Fátima Santana Ferreira
Caserta,Nelson Marcio Gomes
Ataide,Elaine Cristina de
author_role author
author2 Perales,Simone Reges
Gallani,Stephanie Kilaris
Costa,Larissa Bastos Eloy da
Lago,Eduardo Andreazza Dal
Boin,Ilka de Fátima Santana Ferreira
Caserta,Nelson Marcio Gomes
Ataide,Elaine Cristina de
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Lahan-Martins,Daniel
Perales,Simone Reges
Gallani,Stephanie Kilaris
Costa,Larissa Bastos Eloy da
Lago,Eduardo Andreazza Dal
Boin,Ilka de Fátima Santana Ferreira
Caserta,Nelson Marcio Gomes
Ataide,Elaine Cristina de
dc.subject.por.fl_str_mv Carcinoma, hepatocellular
Tomography, X-ray computed
Liver neoplasms/surgery
Liver transplantation
topic Carcinoma, hepatocellular
Tomography, X-ray computed
Liver neoplasms/surgery
Liver transplantation
description Abstract Objective: To investigate whether quantitative computed tomography (CT) measurements can predict microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Materials and Methods: This was a retrospective analysis of 200 cases of surgically proven HCCs in 125 consecutive patients evaluated between March 2010 and November 2017. We quantitatively measured regions of interest in lesions and adjacent areas of the liver on unenhanced CT scans, as well as in the arterial, portal venous, and equilibrium phases on contrast-enhanced CT scans. Enhancement profiles were analyzed and compared with histopathological references of MVI. Univariate and multivariate logistic regression analyses were used in order to evaluate CT parameters as potential predictors of MVI. Results: Of the 200 HCCs, 77 (38.5%) showed evidence of MVI on histopathological analysis. There was no statistical difference between HCCs with MVI and those without, in terms of the percentage attenuation ratio in the portal venous phase (114.7 vs. 115.8) and equilibrium phase (126.7 vs. 128.2), as well as in terms of the relative washout ratio, also in the portal venous and equilibrium phases (15.0 vs. 8.2 and 31.4 vs. 26.3, respectively). Conclusion: Quantitative dynamic CT parameters measured in the preoperative period do not appear to correlate with MVI in HCC.
publishDate 2019
dc.date.none.fl_str_mv 2019-10-01
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=S0100-39842019000500287
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842019000500287
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0100-3984.2018.0123
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.52 n.5 2019
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_ 1754208940253511680