Application of the diffusion kurtosis model for the study of breast lesions
Autor(a) principal: | |
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Data de Publicação: | 2014 |
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/10400.22/14206 |
Resumo: | Objectives To evaluate diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in the differentiation and characterisation of breast lesions. Methods Thirty-six women underwent breast magnetic resonance imaging (MRI) including a DWI sequence with multiple b-values (50–3,000 s/mm2). Mean values for apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) were calculated by lesion type and histological subtype. Differences and correlation between parameters were determined. Results Forty-four lesions were found. There were significant differences between benign and malignant lesions for all parameters (ADC, p = 0.017; MD, p = 0.028; MK, p = 0.017). ADC and MD were higher for benign (1.96 ± 0.41 × 10−3 and 2.17 ± 0.42 × 10−3 mm2/s, respectively) than for malignant lesions (1.33 ± 0.18 × 10−3 and 1.52 ± 0.50 × 10−3 mm2/s). MK was higher for malignant (0.61 ± 0.27) than benign lesions (0.37 ± 0.18). We found differences between invasive ductal carcinoma (IDC) and fibroadenoma (FA) for all parameters (ADC, MD and MK): p = 0.016, 0.022 and 0.016, respectively. FA and fibrocystic change (FC) showed differences only in MK (p = 0.016). Conclusions Diffusion in breast lesions follows a non-Gaussian distribution. MK enables differentiation and characterisation of breast lesions, providing new insights into microstructural complexity. To confirm these results, further investigation in a broader sample should be performed. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Application of the diffusion kurtosis model for the study of breast lesionsBreast NeoplasmsDiagnosis, DifferentialDiffusion Magnetic Resonance ImagingFemaleFollow-Up StudiesImage Interpretation, Computer-AssistedMiddle AgedProspective StudiesReproducibility of ResultsAlgorithmsObjectives To evaluate diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in the differentiation and characterisation of breast lesions. Methods Thirty-six women underwent breast magnetic resonance imaging (MRI) including a DWI sequence with multiple b-values (50–3,000 s/mm2). Mean values for apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) were calculated by lesion type and histological subtype. Differences and correlation between parameters were determined. Results Forty-four lesions were found. There were significant differences between benign and malignant lesions for all parameters (ADC, p = 0.017; MD, p = 0.028; MK, p = 0.017). ADC and MD were higher for benign (1.96 ± 0.41 × 10−3 and 2.17 ± 0.42 × 10−3 mm2/s, respectively) than for malignant lesions (1.33 ± 0.18 × 10−3 and 1.52 ± 0.50 × 10−3 mm2/s). MK was higher for malignant (0.61 ± 0.27) than benign lesions (0.37 ± 0.18). We found differences between invasive ductal carcinoma (IDC) and fibroadenoma (FA) for all parameters (ADC, MD and MK): p = 0.016, 0.022 and 0.016, respectively. FA and fibrocystic change (FC) showed differences only in MK (p = 0.016). Conclusions Diffusion in breast lesions follows a non-Gaussian distribution. MK enables differentiation and characterisation of breast lesions, providing new insights into microstructural complexity. To confirm these results, further investigation in a broader sample should be performed.SpringerRepositório Científico do Instituto Politécnico do PortoNogueira, LuísaBrandão, SofiaMatos, EduardaNunes, Rita GouveiaLoureiro, JoanaRamos, IsabelFerreira, Hugo Alexandre2019-07-01T16:03:45Z20142014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/14206eng10.1007/s00330-014-3146-5info: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:RCAAP2023-03-13T12:56:54Zoai:recipp.ipp.pt:10400.22/14206Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:34:01.939937Repositório 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 |
Application of the diffusion kurtosis model for the study of breast lesions |
title |
Application of the diffusion kurtosis model for the study of breast lesions |
spellingShingle |
Application of the diffusion kurtosis model for the study of breast lesions Nogueira, Luísa Breast Neoplasms Diagnosis, Differential Diffusion Magnetic Resonance Imaging Female Follow-Up Studies Image Interpretation, Computer-Assisted Middle Aged Prospective Studies Reproducibility of Results Algorithms |
title_short |
Application of the diffusion kurtosis model for the study of breast lesions |
title_full |
Application of the diffusion kurtosis model for the study of breast lesions |
title_fullStr |
Application of the diffusion kurtosis model for the study of breast lesions |
title_full_unstemmed |
Application of the diffusion kurtosis model for the study of breast lesions |
title_sort |
Application of the diffusion kurtosis model for the study of breast lesions |
author |
Nogueira, Luísa |
author_facet |
Nogueira, Luísa Brandão, Sofia Matos, Eduarda Nunes, Rita Gouveia Loureiro, Joana Ramos, Isabel Ferreira, Hugo Alexandre |
author_role |
author |
author2 |
Brandão, Sofia Matos, Eduarda Nunes, Rita Gouveia Loureiro, Joana Ramos, Isabel Ferreira, Hugo Alexandre |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Nogueira, Luísa Brandão, Sofia Matos, Eduarda Nunes, Rita Gouveia Loureiro, Joana Ramos, Isabel Ferreira, Hugo Alexandre |
dc.subject.por.fl_str_mv |
Breast Neoplasms Diagnosis, Differential Diffusion Magnetic Resonance Imaging Female Follow-Up Studies Image Interpretation, Computer-Assisted Middle Aged Prospective Studies Reproducibility of Results Algorithms |
topic |
Breast Neoplasms Diagnosis, Differential Diffusion Magnetic Resonance Imaging Female Follow-Up Studies Image Interpretation, Computer-Assisted Middle Aged Prospective Studies Reproducibility of Results Algorithms |
description |
Objectives To evaluate diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in the differentiation and characterisation of breast lesions. Methods Thirty-six women underwent breast magnetic resonance imaging (MRI) including a DWI sequence with multiple b-values (50–3,000 s/mm2). Mean values for apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) were calculated by lesion type and histological subtype. Differences and correlation between parameters were determined. Results Forty-four lesions were found. There were significant differences between benign and malignant lesions for all parameters (ADC, p = 0.017; MD, p = 0.028; MK, p = 0.017). ADC and MD were higher for benign (1.96 ± 0.41 × 10−3 and 2.17 ± 0.42 × 10−3 mm2/s, respectively) than for malignant lesions (1.33 ± 0.18 × 10−3 and 1.52 ± 0.50 × 10−3 mm2/s). MK was higher for malignant (0.61 ± 0.27) than benign lesions (0.37 ± 0.18). We found differences between invasive ductal carcinoma (IDC) and fibroadenoma (FA) for all parameters (ADC, MD and MK): p = 0.016, 0.022 and 0.016, respectively. FA and fibrocystic change (FC) showed differences only in MK (p = 0.016). Conclusions Diffusion in breast lesions follows a non-Gaussian distribution. MK enables differentiation and characterisation of breast lesions, providing new insights into microstructural complexity. To confirm these results, further investigation in a broader sample should be performed. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014 2014-01-01T00:00:00Z 2019-07-01T16:03:45Z |
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/10400.22/14206 |
url |
http://hdl.handle.net/10400.22/14206 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1007/s00330-014-3146-5 |
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 |
Springer |
publisher.none.fl_str_mv |
Springer |
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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1799131432270954496 |