Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity

Detalhes bibliográficos
Autor(a) principal: Dionísio,F.C.F.
Data de Publicação: 2020
Outros Autores: Oliveira,L.S., Hernandes,M.A., Engel,E.E., Rangayyan,R.M., Azevedo-Marques,P.M., Nogueira-Barbosa,M.H.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Medical and Biological Research
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2020000200605
Resumo: The aims of this study were to evaluate the intra- and interobserver reproducibility of manual segmentation of bone sarcomas in magnetic resonance imaging (MRI) studies and to compare manual and semiautomatic segmentation methods. This retrospective study included twelve osteosarcoma and eight Ewing sarcoma MRI studies performed prior to any therapeutic intervention. All cases were histopathologically confirmed. Three radiologists used 3D-Slicer software to perform manual segmentation of bone sarcomas in a blinded and independent manner. One radiologist segmented manually and also performed semiautomatic segmentation with the GrowCut tool. Segmentation exercises were timed for comparison. The dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to evaluate similarity between the segmentation results and further statistical analyses were performed to compare DSC, HD, and volumetric results. Manual segmentation was reproducible with intraobserver DSC varying from 0.83 to 0.97 and HD from 3.37 to 28.73 mm. Interobserver DSC of manual segmentation showed variation from 0.73 to 0.97 and HD from 3.93 to 33.40 mm. Semiautomatic segmentation compared to manual segmentation resulted in DSCs of 0.71−0.96 and HDs of 5.38−31.54 mm. Semiautomatic segmentation required significantly less time compared to manual segmentation (P value ≤0.05). Among all situations compared, tumor volumetry did not show significant statistical differences (P value >0.05). We found excellent intra- and interobserver agreement for manual segmentation of osteosarcoma and Ewing sarcoma. There was high similarity between manual and semiautomatic segmentation, with a significant reduction of segmentation time using the semiautomatic method.
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spelling Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarityEwing sarcomaOsteosarcomaManual segmentationSemiautomatic segmentationThe aims of this study were to evaluate the intra- and interobserver reproducibility of manual segmentation of bone sarcomas in magnetic resonance imaging (MRI) studies and to compare manual and semiautomatic segmentation methods. This retrospective study included twelve osteosarcoma and eight Ewing sarcoma MRI studies performed prior to any therapeutic intervention. All cases were histopathologically confirmed. Three radiologists used 3D-Slicer software to perform manual segmentation of bone sarcomas in a blinded and independent manner. One radiologist segmented manually and also performed semiautomatic segmentation with the GrowCut tool. Segmentation exercises were timed for comparison. The dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to evaluate similarity between the segmentation results and further statistical analyses were performed to compare DSC, HD, and volumetric results. Manual segmentation was reproducible with intraobserver DSC varying from 0.83 to 0.97 and HD from 3.37 to 28.73 mm. Interobserver DSC of manual segmentation showed variation from 0.73 to 0.97 and HD from 3.93 to 33.40 mm. Semiautomatic segmentation compared to manual segmentation resulted in DSCs of 0.71−0.96 and HDs of 5.38−31.54 mm. Semiautomatic segmentation required significantly less time compared to manual segmentation (P value ≤0.05). Among all situations compared, tumor volumetry did not show significant statistical differences (P value >0.05). We found excellent intra- and interobserver agreement for manual segmentation of osteosarcoma and Ewing sarcoma. There was high similarity between manual and semiautomatic segmentation, with a significant reduction of segmentation time using the semiautomatic method.Associação Brasileira de Divulgação Científica2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2020000200605Brazilian Journal of Medical and Biological Research v.53 n.2 2020reponame:Brazilian Journal of Medical and Biological Researchinstname:Associação Brasileira de Divulgação Científica (ABDC)instacron:ABDC10.1590/1414-431x20198962info:eu-repo/semantics/openAccessDionísio,F.C.F.Oliveira,L.S.Hernandes,M.A.Engel,E.E.Rangayyan,R.M.Azevedo-Marques,P.M.Nogueira-Barbosa,M.H.eng2020-01-29T00:00:00Zoai:scielo:S0100-879X2020000200605Revistahttps://www.bjournal.org/https://old.scielo.br/oai/scielo-oai.phpbjournal@terra.com.br||bjournal@terra.com.br1414-431X0100-879Xopendoar:2020-01-29T00:00Brazilian Journal of Medical and Biological Research - Associação Brasileira de Divulgação Científica (ABDC)false
dc.title.none.fl_str_mv Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity
title Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity
spellingShingle Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity
Dionísio,F.C.F.
Ewing sarcoma
Osteosarcoma
Manual segmentation
Semiautomatic segmentation
title_short Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity
title_full Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity
title_fullStr Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity
title_full_unstemmed Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity
title_sort Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity
author Dionísio,F.C.F.
author_facet Dionísio,F.C.F.
Oliveira,L.S.
Hernandes,M.A.
Engel,E.E.
Rangayyan,R.M.
Azevedo-Marques,P.M.
Nogueira-Barbosa,M.H.
author_role author
author2 Oliveira,L.S.
Hernandes,M.A.
Engel,E.E.
Rangayyan,R.M.
Azevedo-Marques,P.M.
Nogueira-Barbosa,M.H.
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Dionísio,F.C.F.
Oliveira,L.S.
Hernandes,M.A.
Engel,E.E.
Rangayyan,R.M.
Azevedo-Marques,P.M.
Nogueira-Barbosa,M.H.
dc.subject.por.fl_str_mv Ewing sarcoma
Osteosarcoma
Manual segmentation
Semiautomatic segmentation
topic Ewing sarcoma
Osteosarcoma
Manual segmentation
Semiautomatic segmentation
description The aims of this study were to evaluate the intra- and interobserver reproducibility of manual segmentation of bone sarcomas in magnetic resonance imaging (MRI) studies and to compare manual and semiautomatic segmentation methods. This retrospective study included twelve osteosarcoma and eight Ewing sarcoma MRI studies performed prior to any therapeutic intervention. All cases were histopathologically confirmed. Three radiologists used 3D-Slicer software to perform manual segmentation of bone sarcomas in a blinded and independent manner. One radiologist segmented manually and also performed semiautomatic segmentation with the GrowCut tool. Segmentation exercises were timed for comparison. The dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to evaluate similarity between the segmentation results and further statistical analyses were performed to compare DSC, HD, and volumetric results. Manual segmentation was reproducible with intraobserver DSC varying from 0.83 to 0.97 and HD from 3.37 to 28.73 mm. Interobserver DSC of manual segmentation showed variation from 0.73 to 0.97 and HD from 3.93 to 33.40 mm. Semiautomatic segmentation compared to manual segmentation resulted in DSCs of 0.71−0.96 and HDs of 5.38−31.54 mm. Semiautomatic segmentation required significantly less time compared to manual segmentation (P value ≤0.05). Among all situations compared, tumor volumetry did not show significant statistical differences (P value >0.05). We found excellent intra- and interobserver agreement for manual segmentation of osteosarcoma and Ewing sarcoma. There was high similarity between manual and semiautomatic segmentation, with a significant reduction of segmentation time using the semiautomatic method.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2020000200605
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1414-431x20198962
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Associação Brasileira de Divulgação Científica
publisher.none.fl_str_mv Associação Brasileira de Divulgação Científica
dc.source.none.fl_str_mv Brazilian Journal of Medical and Biological Research v.53 n.2 2020
reponame:Brazilian Journal of Medical and Biological Research
instname:Associação Brasileira de Divulgação Científica (ABDC)
instacron:ABDC
instname_str Associação Brasileira de Divulgação Científica (ABDC)
instacron_str ABDC
institution ABDC
reponame_str Brazilian Journal of Medical and Biological Research
collection Brazilian Journal of Medical and Biological Research
repository.name.fl_str_mv Brazilian Journal of Medical and Biological Research - Associação Brasileira de Divulgação Científica (ABDC)
repository.mail.fl_str_mv bjournal@terra.com.br||bjournal@terra.com.br
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