Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis

Abstract Lacunarity, a quantitative morphological measure of how shapes fill space, and fractal dimension, a morphological measure of the complexity of pixel arrangement, have shown relationships with outcome across a variety of cancers. However, the application of these metrics to glioblastoma (GBM...

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Autores principales:	Lee Curtin, Paula Whitmire, Haylye White, Kamila M. Bond, Maciej M. Mrugala, Leland S. Hu, Kristin R. Swanson
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/73ba47c006284393a3b1eb8368e28ba3
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spelling	oai:doaj.org-article:73ba47c006284393a3b1eb8368e28ba32021-12-05T12:13:01ZShape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis10.1038/s41598-021-02495-62045-2322https://doaj.org/article/73ba47c006284393a3b1eb8368e28ba32021-12-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-02495-6https://doaj.org/toc/2045-2322Abstract Lacunarity, a quantitative morphological measure of how shapes fill space, and fractal dimension, a morphological measure of the complexity of pixel arrangement, have shown relationships with outcome across a variety of cancers. However, the application of these metrics to glioblastoma (GBM), a very aggressive primary brain tumor, has not been fully explored. In this project, we computed lacunarity and fractal dimension values for GBM-induced abnormalities on clinically standard magnetic resonance imaging (MRI). In our patient cohort (n = 402), we connect these morphological metrics calculated on pretreatment MRI with the survival of patients with GBM. We calculated lacunarity and fractal dimension on necrotic regions (n = 390), all abnormalities present on T1Gd MRI (n = 402), and abnormalities present on T2/FLAIR MRI (n = 257). We also explored the relationship between these metrics and age at diagnosis, as well as abnormality volume. We found statistically significant relationships to outcome for all three imaging regions that we tested, with the shape of T2/FLAIR abnormalities that are typically associated with edema showing the strongest relationship with overall survival. This link between morphological and survival metrics could be driven by underlying biological phenomena, tumor location or microenvironmental factors that should be further explored.Lee CurtinPaula WhitmireHaylye WhiteKamila M. BondMaciej M. MrugalaLeland S. HuKristin R. SwansonNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Lee Curtin Paula Whitmire Haylye White Kamila M. Bond Maciej M. Mrugala Leland S. Hu Kristin R. Swanson Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis
description	Abstract Lacunarity, a quantitative morphological measure of how shapes fill space, and fractal dimension, a morphological measure of the complexity of pixel arrangement, have shown relationships with outcome across a variety of cancers. However, the application of these metrics to glioblastoma (GBM), a very aggressive primary brain tumor, has not been fully explored. In this project, we computed lacunarity and fractal dimension values for GBM-induced abnormalities on clinically standard magnetic resonance imaging (MRI). In our patient cohort (n = 402), we connect these morphological metrics calculated on pretreatment MRI with the survival of patients with GBM. We calculated lacunarity and fractal dimension on necrotic regions (n = 390), all abnormalities present on T1Gd MRI (n = 402), and abnormalities present on T2/FLAIR MRI (n = 257). We also explored the relationship between these metrics and age at diagnosis, as well as abnormality volume. We found statistically significant relationships to outcome for all three imaging regions that we tested, with the shape of T2/FLAIR abnormalities that are typically associated with edema showing the strongest relationship with overall survival. This link between morphological and survival metrics could be driven by underlying biological phenomena, tumor location or microenvironmental factors that should be further explored.
format	article
author	Lee Curtin Paula Whitmire Haylye White Kamila M. Bond Maciej M. Mrugala Leland S. Hu Kristin R. Swanson
author_facet	Lee Curtin Paula Whitmire Haylye White Kamila M. Bond Maciej M. Mrugala Leland S. Hu Kristin R. Swanson
author_sort	Lee Curtin
title	Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis
title_short	Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis
title_full	Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis
title_fullStr	Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis
title_full_unstemmed	Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis
title_sort	shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/73ba47c006284393a3b1eb8368e28ba3
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Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis

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