Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization.
PURPOSE:Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural meas...
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Public Library of Science (PLoS)
2017-01-01
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Online Access: | http://europepmc.org/articles/PMC5460822?pdf=render |
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author | David Molina Julián Pérez-Beteta Alicia Martínez-González Juan Martino Carlos Velasquez Estanislao Arana Víctor M Pérez-García |
author_facet | David Molina Julián Pérez-Beteta Alicia Martínez-González Juan Martino Carlos Velasquez Estanislao Arana Víctor M Pérez-García |
author_sort | David Molina |
collection | DOAJ |
description | PURPOSE:Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. MATERIALS AND METHODS:Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. RESULTS:No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). CONCLUSION:Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images. |
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issn | 1932-6203 |
language | English |
last_indexed | 2024-04-12T00:36:14Z |
publishDate | 2017-01-01 |
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spelling | doaj.art-6dcdd344f4a044129feffc12b9d3b7362022-12-22T03:55:09ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01126e017884310.1371/journal.pone.0178843Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization.David MolinaJulián Pérez-BetetaAlicia Martínez-GonzálezJuan MartinoCarlos VelasquezEstanislao AranaVíctor M Pérez-GarcíaPURPOSE:Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. MATERIALS AND METHODS:Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. RESULTS:No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). CONCLUSION:Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images.http://europepmc.org/articles/PMC5460822?pdf=render |
spellingShingle | David Molina Julián Pérez-Beteta Alicia Martínez-González Juan Martino Carlos Velasquez Estanislao Arana Víctor M Pérez-García Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization. PLoS ONE |
title | Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization. |
title_full | Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization. |
title_fullStr | Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization. |
title_full_unstemmed | Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization. |
title_short | Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization. |
title_sort | lack of robustness of textural measures obtained from 3d brain tumor mris impose a need for standardization |
url | http://europepmc.org/articles/PMC5460822?pdf=render |
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