Combination of GI-RADS and 3D-CEUS for differential diagnosis of ovarian masses
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista da Associação Médica Brasileira (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-42302019000700959 |
Resumo: | SUMMARY OBJECTIVE The purpose of this study is to evaluate the efficacy of the combination of gynecologic imaging reporting and data system (GI-RADS) ultrasonographic stratification and three-dimensional contrast-enhanced ultrasonography (3D-CEUS) in order to distinguish malignant from benign ovarian masses. METHODS In this study, 102 patients with ovarian masses were examined by both two-dimensional ultrasound(2D-US) and 3D-CEUS. Sonographic features of ovarian masses obtained from 3D-CEUS were analyzed and compared with 2D-US. All patients with ovarian masses were confirmed by operational pathology or long-term follow-up results. RESULTS (1)The Chi-square test and multiple Logistic regression analysis confirmed that there were only eight independent predictors of malignant masses, including thick septa (≥3mm), thick papillary projections(≥7mm), solid areas, presence of ascites, central vascularization, contrast enhancement, distribution of contrast agent, and vascular characteristics of the solid part and their odds ratios which were 5.52, 5.39, 4.94, 4.34, 5.92, 7.44, 6.09, and 7.67, respectively (P<0.05). (2)These eight signs were used to combine the GI-RADS with 3D-CEUS scoring system in which the corresponding value of the area under the curve (AUC) was 0.969, which was superior to using GI-RADS lonely (Z-value=1.64, P<0.025). Using 4 points as the cut-off, the scoring system showed the performance was clearly better than using GI-RADS alone (P<0.05). (3) The Kappa value was 0.872 for two different clinicians with equal experience. CONCLUSIONS The combination of GI-RADS and 3D-CEUS scoring system would be a more effective method to distinguish malignant from benign ovarian masses. |
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Combination of GI-RADS and 3D-CEUS for differential diagnosis of ovarian massesNeoplasias ovarianasDoenças ovarianasUltrasonographyImaging, three-dimensional/methodsSUMMARY OBJECTIVE The purpose of this study is to evaluate the efficacy of the combination of gynecologic imaging reporting and data system (GI-RADS) ultrasonographic stratification and three-dimensional contrast-enhanced ultrasonography (3D-CEUS) in order to distinguish malignant from benign ovarian masses. METHODS In this study, 102 patients with ovarian masses were examined by both two-dimensional ultrasound(2D-US) and 3D-CEUS. Sonographic features of ovarian masses obtained from 3D-CEUS were analyzed and compared with 2D-US. All patients with ovarian masses were confirmed by operational pathology or long-term follow-up results. RESULTS (1)The Chi-square test and multiple Logistic regression analysis confirmed that there were only eight independent predictors of malignant masses, including thick septa (≥3mm), thick papillary projections(≥7mm), solid areas, presence of ascites, central vascularization, contrast enhancement, distribution of contrast agent, and vascular characteristics of the solid part and their odds ratios which were 5.52, 5.39, 4.94, 4.34, 5.92, 7.44, 6.09, and 7.67, respectively (P<0.05). (2)These eight signs were used to combine the GI-RADS with 3D-CEUS scoring system in which the corresponding value of the area under the curve (AUC) was 0.969, which was superior to using GI-RADS lonely (Z-value=1.64, P<0.025). Using 4 points as the cut-off, the scoring system showed the performance was clearly better than using GI-RADS alone (P<0.05). (3) The Kappa value was 0.872 for two different clinicians with equal experience. CONCLUSIONS The combination of GI-RADS and 3D-CEUS scoring system would be a more effective method to distinguish malignant from benign ovarian masses.Associação Médica Brasileira2019-07-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-42302019000700959Revista da Associação Médica Brasileira v.65 n.7 2019reponame:Revista da Associação Médica Brasileira (Online)instname:Associação Médica Brasileira (AMB)instacron:AMB10.1590/1806-9282.65.7.959info:eu-repo/semantics/openAccessWang,XialiShupingYang,Lv,GuorongLiao,JianmeiWu,ShufenZhang,Weinaeng2019-08-02T00:00:00Zoai:scielo:S0104-42302019000700959Revistahttps://ramb.amb.org.br/ultimas-edicoes/#https://old.scielo.br/oai/scielo-oai.php||ramb@amb.org.br1806-92820104-4230opendoar:2019-08-02T00:00Revista da Associação Médica Brasileira (Online) - Associação Médica Brasileira (AMB)false |
dc.title.none.fl_str_mv |
Combination of GI-RADS and 3D-CEUS for differential diagnosis of ovarian masses |
title |
Combination of GI-RADS and 3D-CEUS for differential diagnosis of ovarian masses |
spellingShingle |
Combination of GI-RADS and 3D-CEUS for differential diagnosis of ovarian masses Wang,Xiali Neoplasias ovarianas Doenças ovarianas Ultrasonography Imaging, three-dimensional/methods |
title_short |
Combination of GI-RADS and 3D-CEUS for differential diagnosis of ovarian masses |
title_full |
Combination of GI-RADS and 3D-CEUS for differential diagnosis of ovarian masses |
title_fullStr |
Combination of GI-RADS and 3D-CEUS for differential diagnosis of ovarian masses |
title_full_unstemmed |
Combination of GI-RADS and 3D-CEUS for differential diagnosis of ovarian masses |
title_sort |
Combination of GI-RADS and 3D-CEUS for differential diagnosis of ovarian masses |
author |
Wang,Xiali |
author_facet |
Wang,Xiali ShupingYang, Lv,Guorong Liao,Jianmei Wu,Shufen Zhang,Weina |
author_role |
author |
author2 |
ShupingYang, Lv,Guorong Liao,Jianmei Wu,Shufen Zhang,Weina |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Wang,Xiali ShupingYang, Lv,Guorong Liao,Jianmei Wu,Shufen Zhang,Weina |
dc.subject.por.fl_str_mv |
Neoplasias ovarianas Doenças ovarianas Ultrasonography Imaging, three-dimensional/methods |
topic |
Neoplasias ovarianas Doenças ovarianas Ultrasonography Imaging, three-dimensional/methods |
description |
SUMMARY OBJECTIVE The purpose of this study is to evaluate the efficacy of the combination of gynecologic imaging reporting and data system (GI-RADS) ultrasonographic stratification and three-dimensional contrast-enhanced ultrasonography (3D-CEUS) in order to distinguish malignant from benign ovarian masses. METHODS In this study, 102 patients with ovarian masses were examined by both two-dimensional ultrasound(2D-US) and 3D-CEUS. Sonographic features of ovarian masses obtained from 3D-CEUS were analyzed and compared with 2D-US. All patients with ovarian masses were confirmed by operational pathology or long-term follow-up results. RESULTS (1)The Chi-square test and multiple Logistic regression analysis confirmed that there were only eight independent predictors of malignant masses, including thick septa (≥3mm), thick papillary projections(≥7mm), solid areas, presence of ascites, central vascularization, contrast enhancement, distribution of contrast agent, and vascular characteristics of the solid part and their odds ratios which were 5.52, 5.39, 4.94, 4.34, 5.92, 7.44, 6.09, and 7.67, respectively (P<0.05). (2)These eight signs were used to combine the GI-RADS with 3D-CEUS scoring system in which the corresponding value of the area under the curve (AUC) was 0.969, which was superior to using GI-RADS lonely (Z-value=1.64, P<0.025). Using 4 points as the cut-off, the scoring system showed the performance was clearly better than using GI-RADS alone (P<0.05). (3) The Kappa value was 0.872 for two different clinicians with equal experience. CONCLUSIONS The combination of GI-RADS and 3D-CEUS scoring system would be a more effective method to distinguish malignant from benign ovarian masses. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-07-01 |
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=S0104-42302019000700959 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-42302019000700959 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1806-9282.65.7.959 |
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 |
Associação Médica Brasileira |
publisher.none.fl_str_mv |
Associação Médica Brasileira |
dc.source.none.fl_str_mv |
Revista da Associação Médica Brasileira v.65 n.7 2019 reponame:Revista da Associação Médica Brasileira (Online) instname:Associação Médica Brasileira (AMB) instacron:AMB |
instname_str |
Associação Médica Brasileira (AMB) |
instacron_str |
AMB |
institution |
AMB |
reponame_str |
Revista da Associação Médica Brasileira (Online) |
collection |
Revista da Associação Médica Brasileira (Online) |
repository.name.fl_str_mv |
Revista da Associação Médica Brasileira (Online) - Associação Médica Brasileira (AMB) |
repository.mail.fl_str_mv |
||ramb@amb.org.br |
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1754212834267365376 |