Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissue
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.22/14138 |
Resumo: | Purpose Determining optimal b-value pair for differentiation between normal and prostate cancer (PCa) tissues. Methods Forty-three patients with diagnosis or PCa symptoms were included. Apparent diffusion coefficient (ADC) was estimated using minimum and maximum b-values of 0, 50, 100, 150, 200, 500 s/mm2 and 500, 800, 1100, 1400, 1700 and 2000s/mm2, respectively. Diagnostic performances were evaluated when Area-under-the-curve (AUC) > 95%. Results 15 of the 35 b-values pair surpassed this AUC threshold. The pair (50, 2000 s/mm2) provided the highest AUC (96%) with ADC cutoff 0.89 × 10–3 mm2/s, sensitivity 95.5%, specificity 93.2% and accuracy 94.4%. Conclusions The best b-value pair was b = 50, 2000 s/mm2. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissueDiffusion weighted imagingDiffusion Magnetic Resonance ImagingProstateProstatic NeoplasmsPurpose Determining optimal b-value pair for differentiation between normal and prostate cancer (PCa) tissues. Methods Forty-three patients with diagnosis or PCa symptoms were included. Apparent diffusion coefficient (ADC) was estimated using minimum and maximum b-values of 0, 50, 100, 150, 200, 500 s/mm2 and 500, 800, 1100, 1400, 1700 and 2000s/mm2, respectively. Diagnostic performances were evaluated when Area-under-the-curve (AUC) > 95%. Results 15 of the 35 b-values pair surpassed this AUC threshold. The pair (50, 2000 s/mm2) provided the highest AUC (96%) with ADC cutoff 0.89 × 10–3 mm2/s, sensitivity 95.5%, specificity 93.2% and accuracy 94.4%. Conclusions The best b-value pair was b = 50, 2000 s/mm2.ElsevierRepositório Científico do Instituto Politécnico do PortoAdubeiro, NunoNogueira, Maria LuísaNunes, Rita G.Ferreira, Hugo AlexandreRibeiro, EduardoLa Fuente, José Maria Ferreira2019-06-27T16:42:00Z20182018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/14138eng10.1016/j.clinimag.2017.09.004info: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:RCAAP2023-03-13T12:56:45Zoai:recipp.ipp.pt:10400.22/14138Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:33:57.829774Repositório 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 |
Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissue |
title |
Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissue |
spellingShingle |
Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissue Adubeiro, Nuno Diffusion weighted imaging Diffusion Magnetic Resonance Imaging Prostate Prostatic Neoplasms |
title_short |
Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissue |
title_full |
Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissue |
title_fullStr |
Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissue |
title_full_unstemmed |
Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissue |
title_sort |
Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissue |
author |
Adubeiro, Nuno |
author_facet |
Adubeiro, Nuno Nogueira, Maria Luísa Nunes, Rita G. Ferreira, Hugo Alexandre Ribeiro, Eduardo La Fuente, José Maria Ferreira |
author_role |
author |
author2 |
Nogueira, Maria Luísa Nunes, Rita G. Ferreira, Hugo Alexandre Ribeiro, Eduardo La Fuente, José Maria Ferreira |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Adubeiro, Nuno Nogueira, Maria Luísa Nunes, Rita G. Ferreira, Hugo Alexandre Ribeiro, Eduardo La Fuente, José Maria Ferreira |
dc.subject.por.fl_str_mv |
Diffusion weighted imaging Diffusion Magnetic Resonance Imaging Prostate Prostatic Neoplasms |
topic |
Diffusion weighted imaging Diffusion Magnetic Resonance Imaging Prostate Prostatic Neoplasms |
description |
Purpose Determining optimal b-value pair for differentiation between normal and prostate cancer (PCa) tissues. Methods Forty-three patients with diagnosis or PCa symptoms were included. Apparent diffusion coefficient (ADC) was estimated using minimum and maximum b-values of 0, 50, 100, 150, 200, 500 s/mm2 and 500, 800, 1100, 1400, 1700 and 2000s/mm2, respectively. Diagnostic performances were evaluated when Area-under-the-curve (AUC) > 95%. Results 15 of the 35 b-values pair surpassed this AUC threshold. The pair (50, 2000 s/mm2) provided the highest AUC (96%) with ADC cutoff 0.89 × 10–3 mm2/s, sensitivity 95.5%, specificity 93.2% and accuracy 94.4%. Conclusions The best b-value pair was b = 50, 2000 s/mm2. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018 2018-01-01T00:00:00Z 2019-06-27T16:42:00Z |
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 |
http://hdl.handle.net/10400.22/14138 |
url |
http://hdl.handle.net/10400.22/14138 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1016/j.clinimag.2017.09.004 |
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 |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
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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1817554569957212160 |