Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging
Autor(a) principal: | |
---|---|
Data de Publicação: | 2020 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Clinics |
Texto Completo: | https://www.revistas.usp.br/clinics/article/view/174199 |
Resumo: | OBJECTIVE: Dual-energy X-ray absorptiometry (DXA)-derived bone mineral density (BMD) often fails to predict fragility fractures. Quantitative textural analysis using magnetic resonance imaging (MRI) may potentially yield useful radiomic features to predict fractures. We aimed to investigate the correlation between BMD and texture attributes (TAs) extracted from MRI scans and the interobserver reproducibility of the analysis. METHODS: Forty-nine volunteers underwent lumbar spine 1.5-T MRI and DXA. Three-dimensional (3-D) graylevel co-occurrence matrices were measured from routine sagittal T2 fast spin-echo images using the IBEX software. Twenty-two TAs were extracted from 3-D segmented L3 vertebrae. The estimated concordance coefficient was calculated using linear regression analysis. A Pearson correlation coefficient analysis was performed to evaluate the correlation between BMD and the TAs. Interobserver reproducibility was assessed with the concordance coefficient described by Lin. RESULTS: The results revealed a fair-to-moderate significant correlation between BMD and 13 TAs (r= 0.20 to 0.39; po0.05). Eight TAs (autocorrelation, energy, homogeneity 1, homogeneity 1.1, maximum probability, sum average, sum variance, and inverse difference normalized) negatively correlated with BMD (r= 0.20 to 0.38; po0.05), whereas five TAs (dissimilarity, difference entropy, entropy, sum entropy, and information measure corr 1) positively correlated with BMD (r=0.29–0.39; po0.05). The interobserver agreement was almost perfect for all significant TAs (95% confidence interval, 0.92–1.00; po0.05). CONCLUSION: Specific TAs could be reliably extracted from routine MRI and correlated with BMD. Our results encourage future evaluation of the potential usefulness of quantitative texture measurements from MRI scans for predicting fragility fractures. |
id |
USP-19_ec1f2fb90ba29b2956da6a3672ed7dda |
---|---|
oai_identifier_str |
oai:revistas.usp.br:article/174199 |
network_acronym_str |
USP-19 |
network_name_str |
Clinics |
repository_id_str |
|
spelling |
Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imagingMagnetic Resonance ImagingTextural AttributeBone Mineral DensityOBJECTIVE: Dual-energy X-ray absorptiometry (DXA)-derived bone mineral density (BMD) often fails to predict fragility fractures. Quantitative textural analysis using magnetic resonance imaging (MRI) may potentially yield useful radiomic features to predict fractures. We aimed to investigate the correlation between BMD and texture attributes (TAs) extracted from MRI scans and the interobserver reproducibility of the analysis. METHODS: Forty-nine volunteers underwent lumbar spine 1.5-T MRI and DXA. Three-dimensional (3-D) graylevel co-occurrence matrices were measured from routine sagittal T2 fast spin-echo images using the IBEX software. Twenty-two TAs were extracted from 3-D segmented L3 vertebrae. The estimated concordance coefficient was calculated using linear regression analysis. A Pearson correlation coefficient analysis was performed to evaluate the correlation between BMD and the TAs. Interobserver reproducibility was assessed with the concordance coefficient described by Lin. RESULTS: The results revealed a fair-to-moderate significant correlation between BMD and 13 TAs (r= 0.20 to 0.39; po0.05). Eight TAs (autocorrelation, energy, homogeneity 1, homogeneity 1.1, maximum probability, sum average, sum variance, and inverse difference normalized) negatively correlated with BMD (r= 0.20 to 0.38; po0.05), whereas five TAs (dissimilarity, difference entropy, entropy, sum entropy, and information measure corr 1) positively correlated with BMD (r=0.29–0.39; po0.05). The interobserver agreement was almost perfect for all significant TAs (95% confidence interval, 0.92–1.00; po0.05). CONCLUSION: Specific TAs could be reliably extracted from routine MRI and correlated with BMD. Our results encourage future evaluation of the potential usefulness of quantitative texture measurements from MRI scans for predicting fragility fractures.Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo2020-08-27info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/xmlhttps://www.revistas.usp.br/clinics/article/view/17419910.6061/clinics/2020/e1766Clinics; Vol. 75 (2020); e1766Clinics; v. 75 (2020); e1766Clinics; Vol. 75 (2020); e17661980-53221807-5932reponame:Clinicsinstname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/clinics/article/view/174199/163048https://www.revistas.usp.br/clinics/article/view/174199/163049Copyright (c) 2020 Clinicsinfo:eu-repo/semantics/openAccessMaciel, Jamilly GomesAraújo, Iana Mizumukai deTrazzi, Lucio C.Azevedo-Marques, Paulo Mazzoncini deSalmon, Carlos Ernesto GarridoPaula, Francisco José Albuquerque deNogueira-Barbosa, Marcello Henrique2020-08-27T22:07:10Zoai:revistas.usp.br:article/174199Revistahttps://www.revistas.usp.br/clinicsPUBhttps://www.revistas.usp.br/clinics/oai||clinics@hc.fm.usp.br1980-53221807-5932opendoar:2020-08-27T22:07:10Clinics - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging |
title |
Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging |
spellingShingle |
Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging Maciel, Jamilly Gomes Magnetic Resonance Imaging Textural Attribute Bone Mineral Density |
title_short |
Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging |
title_full |
Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging |
title_fullStr |
Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging |
title_full_unstemmed |
Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging |
title_sort |
Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging |
author |
Maciel, Jamilly Gomes |
author_facet |
Maciel, Jamilly Gomes Araújo, Iana Mizumukai de Trazzi, Lucio C. Azevedo-Marques, Paulo Mazzoncini de Salmon, Carlos Ernesto Garrido Paula, Francisco José Albuquerque de Nogueira-Barbosa, Marcello Henrique |
author_role |
author |
author2 |
Araújo, Iana Mizumukai de Trazzi, Lucio C. Azevedo-Marques, Paulo Mazzoncini de Salmon, Carlos Ernesto Garrido Paula, Francisco José Albuquerque de Nogueira-Barbosa, Marcello Henrique |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Maciel, Jamilly Gomes Araújo, Iana Mizumukai de Trazzi, Lucio C. Azevedo-Marques, Paulo Mazzoncini de Salmon, Carlos Ernesto Garrido Paula, Francisco José Albuquerque de Nogueira-Barbosa, Marcello Henrique |
dc.subject.por.fl_str_mv |
Magnetic Resonance Imaging Textural Attribute Bone Mineral Density |
topic |
Magnetic Resonance Imaging Textural Attribute Bone Mineral Density |
description |
OBJECTIVE: Dual-energy X-ray absorptiometry (DXA)-derived bone mineral density (BMD) often fails to predict fragility fractures. Quantitative textural analysis using magnetic resonance imaging (MRI) may potentially yield useful radiomic features to predict fractures. We aimed to investigate the correlation between BMD and texture attributes (TAs) extracted from MRI scans and the interobserver reproducibility of the analysis. METHODS: Forty-nine volunteers underwent lumbar spine 1.5-T MRI and DXA. Three-dimensional (3-D) graylevel co-occurrence matrices were measured from routine sagittal T2 fast spin-echo images using the IBEX software. Twenty-two TAs were extracted from 3-D segmented L3 vertebrae. The estimated concordance coefficient was calculated using linear regression analysis. A Pearson correlation coefficient analysis was performed to evaluate the correlation between BMD and the TAs. Interobserver reproducibility was assessed with the concordance coefficient described by Lin. RESULTS: The results revealed a fair-to-moderate significant correlation between BMD and 13 TAs (r= 0.20 to 0.39; po0.05). Eight TAs (autocorrelation, energy, homogeneity 1, homogeneity 1.1, maximum probability, sum average, sum variance, and inverse difference normalized) negatively correlated with BMD (r= 0.20 to 0.38; po0.05), whereas five TAs (dissimilarity, difference entropy, entropy, sum entropy, and information measure corr 1) positively correlated with BMD (r=0.29–0.39; po0.05). The interobserver agreement was almost perfect for all significant TAs (95% confidence interval, 0.92–1.00; po0.05). CONCLUSION: Specific TAs could be reliably extracted from routine MRI and correlated with BMD. Our results encourage future evaluation of the potential usefulness of quantitative texture measurements from MRI scans for predicting fragility fractures. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-08-27 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.revistas.usp.br/clinics/article/view/174199 10.6061/clinics/2020/e1766 |
url |
https://www.revistas.usp.br/clinics/article/view/174199 |
identifier_str_mv |
10.6061/clinics/2020/e1766 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/clinics/article/view/174199/163048 https://www.revistas.usp.br/clinics/article/view/174199/163049 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2020 Clinics info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2020 Clinics |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/xml |
dc.publisher.none.fl_str_mv |
Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo |
publisher.none.fl_str_mv |
Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo |
dc.source.none.fl_str_mv |
Clinics; Vol. 75 (2020); e1766 Clinics; v. 75 (2020); e1766 Clinics; Vol. 75 (2020); e1766 1980-5322 1807-5932 reponame:Clinics instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Clinics |
collection |
Clinics |
repository.name.fl_str_mv |
Clinics - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
||clinics@hc.fm.usp.br |
_version_ |
1800222765211451392 |