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Haralick texture feature analysis for quantifying radiation response heterogeneity in murine models observed using Raman spectroscopic mapping

Tumour heterogeneity plays a large role in the response of tumour tissues to radiation therapy. Inherent biological, physical, and even dose deposition heterogeneity all play a role in the resultant observed response. We here implement the use of Haralick textural analysis to quantify the observed g...

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Autores principales: Vrbik, Irene, Van Nest, Samantha J., Meksiarun, Phiranuphon, Loeppky, Jason, Brolo, Alexandre, Lum, Julian J., Jirasek, Andrew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377107/
https://www.ncbi.nlm.nih.gov/pubmed/30768630
http://dx.doi.org/10.1371/journal.pone.0212225
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author Vrbik, Irene
Van Nest, Samantha J.
Meksiarun, Phiranuphon
Loeppky, Jason
Brolo, Alexandre
Lum, Julian J.
Jirasek, Andrew
author_facet Vrbik, Irene
Van Nest, Samantha J.
Meksiarun, Phiranuphon
Loeppky, Jason
Brolo, Alexandre
Lum, Julian J.
Jirasek, Andrew
author_sort Vrbik, Irene
collection PubMed
description Tumour heterogeneity plays a large role in the response of tumour tissues to radiation therapy. Inherent biological, physical, and even dose deposition heterogeneity all play a role in the resultant observed response. We here implement the use of Haralick textural analysis to quantify the observed glycogen production response, as observed via Raman spectroscopic mapping, of tumours irradiated within a murine model. While an array of over 20 Haralick features have been proposed, we here concentrate on five of the most prominent features: homogeneity, local homogeneity, contrast, entropy, and correlation. We show that these Haralick features can be used to quantify the inherent heterogeneity of the Raman spectroscopic maps of tumour response to radiation. Furthermore, our results indicate that Haralick-calculated textural features show a statistically significant dose dependent variation in response heterogeneity, specifically, in glycogen production in tumours irradiated with clinically relevant doses of ionizing radiation. These results indicate that Haralick textural analysis provides a quantitative methodology for understanding the response of murine tumours to radiation therapy. Future work in this area can, for example, utilize the Haralick textural features for understanding the heterogeneity of radiation response as measured by biopsied patient tumour samples, which remains the standard of patient tumour investigation.
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spelling pubmed-63771072019-03-01 Haralick texture feature analysis for quantifying radiation response heterogeneity in murine models observed using Raman spectroscopic mapping Vrbik, Irene Van Nest, Samantha J. Meksiarun, Phiranuphon Loeppky, Jason Brolo, Alexandre Lum, Julian J. Jirasek, Andrew PLoS One Research Article Tumour heterogeneity plays a large role in the response of tumour tissues to radiation therapy. Inherent biological, physical, and even dose deposition heterogeneity all play a role in the resultant observed response. We here implement the use of Haralick textural analysis to quantify the observed glycogen production response, as observed via Raman spectroscopic mapping, of tumours irradiated within a murine model. While an array of over 20 Haralick features have been proposed, we here concentrate on five of the most prominent features: homogeneity, local homogeneity, contrast, entropy, and correlation. We show that these Haralick features can be used to quantify the inherent heterogeneity of the Raman spectroscopic maps of tumour response to radiation. Furthermore, our results indicate that Haralick-calculated textural features show a statistically significant dose dependent variation in response heterogeneity, specifically, in glycogen production in tumours irradiated with clinically relevant doses of ionizing radiation. These results indicate that Haralick textural analysis provides a quantitative methodology for understanding the response of murine tumours to radiation therapy. Future work in this area can, for example, utilize the Haralick textural features for understanding the heterogeneity of radiation response as measured by biopsied patient tumour samples, which remains the standard of patient tumour investigation. Public Library of Science 2019-02-15 /pmc/articles/PMC6377107/ /pubmed/30768630 http://dx.doi.org/10.1371/journal.pone.0212225 Text en © 2019 Vrbik et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Vrbik, Irene
Van Nest, Samantha J.
Meksiarun, Phiranuphon
Loeppky, Jason
Brolo, Alexandre
Lum, Julian J.
Jirasek, Andrew
Haralick texture feature analysis for quantifying radiation response heterogeneity in murine models observed using Raman spectroscopic mapping
title Haralick texture feature analysis for quantifying radiation response heterogeneity in murine models observed using Raman spectroscopic mapping
title_full Haralick texture feature analysis for quantifying radiation response heterogeneity in murine models observed using Raman spectroscopic mapping
title_fullStr Haralick texture feature analysis for quantifying radiation response heterogeneity in murine models observed using Raman spectroscopic mapping
title_full_unstemmed Haralick texture feature analysis for quantifying radiation response heterogeneity in murine models observed using Raman spectroscopic mapping
title_short Haralick texture feature analysis for quantifying radiation response heterogeneity in murine models observed using Raman spectroscopic mapping
title_sort haralick texture feature analysis for quantifying radiation response heterogeneity in murine models observed using raman spectroscopic mapping
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377107/
https://www.ncbi.nlm.nih.gov/pubmed/30768630
http://dx.doi.org/10.1371/journal.pone.0212225
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