Follicular thyroid lesions: Is there a discriminatory potential in the computerized nuclear analysis?

Detalhes bibliográficos
Autor(a) principal: Valentim, F
Data de Publicação: 2018
Outros Autores: Coelho, B, Miot, H, Hayashi, C, Jaune, D, Oliveira, CC, Marques, M, Tagliarini, J, Castilho, E, Soares, P, Mazeto, G
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/126491
Resumo: Background: Computerized image analysis seems to represent a promising diagnostic possibility for thyroid tumors. Our aim was to evaluate the discriminatory diagnostic efficiency of computerized image analysis of cell nuclei from histological materials of follicular tumors. Methods: We studied paraffin-embedded materials from 42 follicular adenomas (FA), 47 follicular variants of papillary carcinomas (FVPC) and 20 follicular carcinomas (FC) by the software ImageJ. Based on the nuclear morphometry and chromatin texture, the samples were classified as FA, FC or FVPC using the Classification and Regression Trees method. Results: We observed high diagnostic sensitivity and specificity rates (FVPC: 89.4% and 100%; FC: 95.0% and 92.1%; FA: 90.5 and 95.5%, respectively). When the tumors were compared by pairs (FC vs FA, FVPC vs FA), 100% of the cases were classified correctly. Conclusion: The computerized image analysis of nuclear features showed to be a useful diagnostic support tool for the histological differentiation between follicular adenomas, follicular variants of papillary carcinomas and follicular carcinomas.
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spelling Follicular thyroid lesions: Is there a discriminatory potential in the computerized nuclear analysis?AdenocarcinomaCarcinomaCell nucleusFollicularHistologyPapillaryThyroid neoplasmsBackground: Computerized image analysis seems to represent a promising diagnostic possibility for thyroid tumors. Our aim was to evaluate the discriminatory diagnostic efficiency of computerized image analysis of cell nuclei from histological materials of follicular tumors. Methods: We studied paraffin-embedded materials from 42 follicular adenomas (FA), 47 follicular variants of papillary carcinomas (FVPC) and 20 follicular carcinomas (FC) by the software ImageJ. Based on the nuclear morphometry and chromatin texture, the samples were classified as FA, FC or FVPC using the Classification and Regression Trees method. Results: We observed high diagnostic sensitivity and specificity rates (FVPC: 89.4% and 100%; FC: 95.0% and 92.1%; FA: 90.5 and 95.5%, respectively). When the tumors were compared by pairs (FC vs FA, FVPC vs FA), 100% of the cases were classified correctly. Conclusion: The computerized image analysis of nuclear features showed to be a useful diagnostic support tool for the histological differentiation between follicular adenomas, follicular variants of papillary carcinomas and follicular carcinomas.BioScientifica20182018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10216/126491eng2049-361410.1530/EC-18-0237Valentim, FCoelho, BMiot, HHayashi, CJaune, DOliveira, CCMarques, MTagliarini, JCastilho, ESoares, PMazeto, Ginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T16:06:31Zoai:repositorio-aberto.up.pt:10216/126491Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:37:54.843478Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Follicular thyroid lesions: Is there a discriminatory potential in the computerized nuclear analysis?
title Follicular thyroid lesions: Is there a discriminatory potential in the computerized nuclear analysis?
spellingShingle Follicular thyroid lesions: Is there a discriminatory potential in the computerized nuclear analysis?
Valentim, F
Adenocarcinoma
Carcinoma
Cell nucleus
Follicular
Histology
Papillary
Thyroid neoplasms
title_short Follicular thyroid lesions: Is there a discriminatory potential in the computerized nuclear analysis?
title_full Follicular thyroid lesions: Is there a discriminatory potential in the computerized nuclear analysis?
title_fullStr Follicular thyroid lesions: Is there a discriminatory potential in the computerized nuclear analysis?
title_full_unstemmed Follicular thyroid lesions: Is there a discriminatory potential in the computerized nuclear analysis?
title_sort Follicular thyroid lesions: Is there a discriminatory potential in the computerized nuclear analysis?
author Valentim, F
author_facet Valentim, F
Coelho, B
Miot, H
Hayashi, C
Jaune, D
Oliveira, CC
Marques, M
Tagliarini, J
Castilho, E
Soares, P
Mazeto, G
author_role author
author2 Coelho, B
Miot, H
Hayashi, C
Jaune, D
Oliveira, CC
Marques, M
Tagliarini, J
Castilho, E
Soares, P
Mazeto, G
author2_role author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Valentim, F
Coelho, B
Miot, H
Hayashi, C
Jaune, D
Oliveira, CC
Marques, M
Tagliarini, J
Castilho, E
Soares, P
Mazeto, G
dc.subject.por.fl_str_mv Adenocarcinoma
Carcinoma
Cell nucleus
Follicular
Histology
Papillary
Thyroid neoplasms
topic Adenocarcinoma
Carcinoma
Cell nucleus
Follicular
Histology
Papillary
Thyroid neoplasms
description Background: Computerized image analysis seems to represent a promising diagnostic possibility for thyroid tumors. Our aim was to evaluate the discriminatory diagnostic efficiency of computerized image analysis of cell nuclei from histological materials of follicular tumors. Methods: We studied paraffin-embedded materials from 42 follicular adenomas (FA), 47 follicular variants of papillary carcinomas (FVPC) and 20 follicular carcinomas (FC) by the software ImageJ. Based on the nuclear morphometry and chromatin texture, the samples were classified as FA, FC or FVPC using the Classification and Regression Trees method. Results: We observed high diagnostic sensitivity and specificity rates (FVPC: 89.4% and 100%; FC: 95.0% and 92.1%; FA: 90.5 and 95.5%, respectively). When the tumors were compared by pairs (FC vs FA, FVPC vs FA), 100% of the cases were classified correctly. Conclusion: The computerized image analysis of nuclear features showed to be a useful diagnostic support tool for the histological differentiation between follicular adenomas, follicular variants of papillary carcinomas and follicular carcinomas.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/10216/126491
url https://hdl.handle.net/10216/126491
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2049-3614
10.1530/EC-18-0237
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv BioScientifica
publisher.none.fl_str_mv BioScientifica
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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