Cargando…
Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI
Tumor heterogeneity can be elucidated by mapping subregions of the lesion with differential imaging characteristics, called habitats. Dynamic Contrast Enhanced (DCE-)MRI can depict the tumor microenvironments by identifying areas with variable perfusion and vascular permeability, since individual tu...
Autores principales: | , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5575347/ https://www.ncbi.nlm.nih.gov/pubmed/28851989 http://dx.doi.org/10.1038/s41598-017-09932-5 |
_version_ | 1783260024549670912 |
---|---|
author | Chang, Yu-Cherng Channing Ackerstaff, Ellen Tschudi, Yohann Jimenez, Bryan Foltz, Warren Fisher, Carl Lilge, Lothar Cho, HyungJoon Carlin, Sean Gillies, Robert J. Balagurunathan, Yoganand Yechieli, Raphael L. Subhawong, Ty Turkbey, Baris Pollack, Alan Stoyanova, Radka |
author_facet | Chang, Yu-Cherng Channing Ackerstaff, Ellen Tschudi, Yohann Jimenez, Bryan Foltz, Warren Fisher, Carl Lilge, Lothar Cho, HyungJoon Carlin, Sean Gillies, Robert J. Balagurunathan, Yoganand Yechieli, Raphael L. Subhawong, Ty Turkbey, Baris Pollack, Alan Stoyanova, Radka |
author_sort | Chang, Yu-Cherng Channing |
collection | PubMed |
description | Tumor heterogeneity can be elucidated by mapping subregions of the lesion with differential imaging characteristics, called habitats. Dynamic Contrast Enhanced (DCE-)MRI can depict the tumor microenvironments by identifying areas with variable perfusion and vascular permeability, since individual tumor habitats vary in the rate and magnitude of the contrast uptake and washout. Of particular interest is identifying areas of hypoxia, characterized by inadequate perfusion and hyper-permeable vasculature. An automatic procedure for delineation of tumor habitats from DCE-MRI was developed as a two-part process involving: (1) statistical testing in order to determine the number of the underlying habitats; and (2) an unsupervised pattern recognition technique to recover the temporal contrast patterns and locations of the associated habitats. The technique is examined on simulated data and DCE-MRI, obtained from prostate and brain pre-clinical cancer models, as well as clinical data from sarcoma and prostate cancer patients. The procedure successfully identified habitats previously associated with well-perfused, hypoxic and/or necrotic tumor compartments. Given the association of tumor hypoxia with more aggressive tumor phenotypes, the obtained in vivo information could impact management of cancer patients considerably. |
format | Online Article Text |
id | pubmed-5575347 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-55753472017-09-01 Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI Chang, Yu-Cherng Channing Ackerstaff, Ellen Tschudi, Yohann Jimenez, Bryan Foltz, Warren Fisher, Carl Lilge, Lothar Cho, HyungJoon Carlin, Sean Gillies, Robert J. Balagurunathan, Yoganand Yechieli, Raphael L. Subhawong, Ty Turkbey, Baris Pollack, Alan Stoyanova, Radka Sci Rep Article Tumor heterogeneity can be elucidated by mapping subregions of the lesion with differential imaging characteristics, called habitats. Dynamic Contrast Enhanced (DCE-)MRI can depict the tumor microenvironments by identifying areas with variable perfusion and vascular permeability, since individual tumor habitats vary in the rate and magnitude of the contrast uptake and washout. Of particular interest is identifying areas of hypoxia, characterized by inadequate perfusion and hyper-permeable vasculature. An automatic procedure for delineation of tumor habitats from DCE-MRI was developed as a two-part process involving: (1) statistical testing in order to determine the number of the underlying habitats; and (2) an unsupervised pattern recognition technique to recover the temporal contrast patterns and locations of the associated habitats. The technique is examined on simulated data and DCE-MRI, obtained from prostate and brain pre-clinical cancer models, as well as clinical data from sarcoma and prostate cancer patients. The procedure successfully identified habitats previously associated with well-perfused, hypoxic and/or necrotic tumor compartments. Given the association of tumor hypoxia with more aggressive tumor phenotypes, the obtained in vivo information could impact management of cancer patients considerably. Nature Publishing Group UK 2017-08-29 /pmc/articles/PMC5575347/ /pubmed/28851989 http://dx.doi.org/10.1038/s41598-017-09932-5 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Chang, Yu-Cherng Channing Ackerstaff, Ellen Tschudi, Yohann Jimenez, Bryan Foltz, Warren Fisher, Carl Lilge, Lothar Cho, HyungJoon Carlin, Sean Gillies, Robert J. Balagurunathan, Yoganand Yechieli, Raphael L. Subhawong, Ty Turkbey, Baris Pollack, Alan Stoyanova, Radka Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI |
title | Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI |
title_full | Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI |
title_fullStr | Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI |
title_full_unstemmed | Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI |
title_short | Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI |
title_sort | delineation of tumor habitats based on dynamic contrast enhanced mri |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5575347/ https://www.ncbi.nlm.nih.gov/pubmed/28851989 http://dx.doi.org/10.1038/s41598-017-09932-5 |
work_keys_str_mv | AT changyucherngchanning delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT ackerstaffellen delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT tschudiyohann delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT jimenezbryan delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT foltzwarren delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT fishercarl delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT lilgelothar delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT chohyungjoon delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT carlinsean delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT gilliesrobertj delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT balagurunathanyoganand delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT yechieliraphaell delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT subhawongty delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT turkbeybaris delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT pollackalan delineationoftumorhabitatsbasedondynamiccontrastenhancedmri AT stoyanovaradka delineationoftumorhabitatsbasedondynamiccontrastenhancedmri |