Quantitative Ultrasound Image Analysis of Axillary Lymph Nodes to Diagnose Metastatic Involvement in Breast Cancer

This study aimed to assess the potential of state-of-the-art ultrasound analysis techniques to non-invasively diagnose axillary lymph nodes involvement in breast cancer. After exclusion criteria, 105 patients were selected from two different hospitals. The 118 lymph node ultrasound images taken from...

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Autores: Coronado Gutiérrez, David, Santamaría, Gorane, Ganau, Sergi, Bargalló, Xavier, Orlando, Stefania, Oliva Brañas, M. Eulalia, Pérez Moreno, Álvaro, Burgos Artizzu, Xavier P.
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2019
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositório:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/216332
Acesso em linha:https://hdl.handle.net/2445/216332
Access Level:Acceso aberto
Palavra-chave:Ecografia
Metàstasi
Diagnòstic per la imatge
Càncer de mama
Nodes limfàtics
Aprenentatge automàtic
Ultrasonic imaging
Metastasis
Diagnostic imaging
Breast cancer
Lymph nodes
Machine learning
id ES_1d6fdd7b9cd1f71276fc6e0a08577f2b
oai_identifier_str oai:recercat.cat:2445/216332
network_acronym_str ES
network_name_str España
repository_id_str
spelling Quantitative Ultrasound Image Analysis of Axillary Lymph Nodes to Diagnose Metastatic Involvement in Breast CancerCoronado Gutiérrez, DavidSantamaría, GoraneGanau, SergiBargalló, XavierOrlando, StefaniaOliva Brañas, M. EulaliaPérez Moreno, ÁlvaroBurgos Artizzu, Xavier P.EcografiaMetàstasiDiagnòstic per la imatgeCàncer de mamaNodes limfàticsAprenentatge automàticUltrasonic imagingMetastasisDiagnostic imagingBreast cancerLymph nodesMachine learningThis study aimed to assess the potential of state-of-the-art ultrasound analysis techniques to non-invasively diagnose axillary lymph nodes involvement in breast cancer. After exclusion criteria, 105 patients were selected from two different hospitals. The 118 lymph node ultrasound images taken from these patients were divided into 53 cases and 65 controls, which made up the study series. The clinical outcome of each node was verified by ultrasound-guided fine needle aspiration, core needle biopsy or surgical biopsy. The achieved accuracy of the proposed method was 86.4%, with 84.9% sensitivity and 87.7% specificity. When tested on breast cancer patients only, the proposed method improved the accuracy of the sonographic assessment of axillary lymph nodes performed by expert radiologists by 9% (87.0% vs 77.9%). In conclusion, the results demonstrate the potential of ultrasound image analysis to detect the microstructural and compositional changes that occur in lymph nodes because of metastatic involvement.Elsevier2024202420192024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion14 p.application/pdfhttps://hdl.handle.net/2445/216332Articles publicats en revistes (Fonaments Clínics)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.1016/j.ultrasmedbio.2019.07.413Ultrasound in Medicine and Biology, 2019, vol. 45, num.11, p. 2932-2945https://doi.org/10.1016/j.ultrasmedbio.2019.07.413cc-by (c) Coronado Gutiérrez, David et al., 2019http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:2445/2163322026-05-29T05:05:01Z
dc.title.none.fl_str_mv Quantitative Ultrasound Image Analysis of Axillary Lymph Nodes to Diagnose Metastatic Involvement in Breast Cancer
title Quantitative Ultrasound Image Analysis of Axillary Lymph Nodes to Diagnose Metastatic Involvement in Breast Cancer
spellingShingle Quantitative Ultrasound Image Analysis of Axillary Lymph Nodes to Diagnose Metastatic Involvement in Breast Cancer
Coronado Gutiérrez, David
Ecografia
Metàstasi
Diagnòstic per la imatge
Càncer de mama
Nodes limfàtics
Aprenentatge automàtic
Ultrasonic imaging
Metastasis
Diagnostic imaging
Breast cancer
Lymph nodes
Machine learning
title_short Quantitative Ultrasound Image Analysis of Axillary Lymph Nodes to Diagnose Metastatic Involvement in Breast Cancer
title_full Quantitative Ultrasound Image Analysis of Axillary Lymph Nodes to Diagnose Metastatic Involvement in Breast Cancer
title_fullStr Quantitative Ultrasound Image Analysis of Axillary Lymph Nodes to Diagnose Metastatic Involvement in Breast Cancer
title_full_unstemmed Quantitative Ultrasound Image Analysis of Axillary Lymph Nodes to Diagnose Metastatic Involvement in Breast Cancer
title_sort Quantitative Ultrasound Image Analysis of Axillary Lymph Nodes to Diagnose Metastatic Involvement in Breast Cancer
dc.creator.none.fl_str_mv Coronado Gutiérrez, David
Santamaría, Gorane
Ganau, Sergi
Bargalló, Xavier
Orlando, Stefania
Oliva Brañas, M. Eulalia
Pérez Moreno, Álvaro
Burgos Artizzu, Xavier P.
author Coronado Gutiérrez, David
author_facet Coronado Gutiérrez, David
Santamaría, Gorane
Ganau, Sergi
Bargalló, Xavier
Orlando, Stefania
Oliva Brañas, M. Eulalia
Pérez Moreno, Álvaro
Burgos Artizzu, Xavier P.
author_role author
author2 Santamaría, Gorane
Ganau, Sergi
Bargalló, Xavier
Orlando, Stefania
Oliva Brañas, M. Eulalia
Pérez Moreno, Álvaro
Burgos Artizzu, Xavier P.
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Ecografia
Metàstasi
Diagnòstic per la imatge
Càncer de mama
Nodes limfàtics
Aprenentatge automàtic
Ultrasonic imaging
Metastasis
Diagnostic imaging
Breast cancer
Lymph nodes
Machine learning
topic Ecografia
Metàstasi
Diagnòstic per la imatge
Càncer de mama
Nodes limfàtics
Aprenentatge automàtic
Ultrasonic imaging
Metastasis
Diagnostic imaging
Breast cancer
Lymph nodes
Machine learning
description This study aimed to assess the potential of state-of-the-art ultrasound analysis techniques to non-invasively diagnose axillary lymph nodes involvement in breast cancer. After exclusion criteria, 105 patients were selected from two different hospitals. The 118 lymph node ultrasound images taken from these patients were divided into 53 cases and 65 controls, which made up the study series. The clinical outcome of each node was verified by ultrasound-guided fine needle aspiration, core needle biopsy or surgical biopsy. The achieved accuracy of the proposed method was 86.4%, with 84.9% sensitivity and 87.7% specificity. When tested on breast cancer patients only, the proposed method improved the accuracy of the sonographic assessment of axillary lymph nodes performed by expert radiologists by 9% (87.0% vs 77.9%). In conclusion, the results demonstrate the potential of ultrasound image analysis to detect the microstructural and compositional changes that occur in lymph nodes because of metastatic involvement.
publishDate 2019
dc.date.none.fl_str_mv 2019
2024
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/216332
url https://hdl.handle.net/2445/216332
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1016/j.ultrasmedbio.2019.07.413
Ultrasound in Medicine and Biology, 2019, vol. 45, num.11, p. 2932-2945
https://doi.org/10.1016/j.ultrasmedbio.2019.07.413
dc.rights.none.fl_str_mv cc-by (c) Coronado Gutiérrez, David et al., 2019
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by (c) Coronado Gutiérrez, David et al., 2019
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 14 p.
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv Articles publicats en revistes (Fonaments Clínics)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869404279683416064
score 15.812429

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