Cargando…

Estimating oxygen distribution from vasculature in three-dimensional tumour tissue

Regions of tissue which are well oxygenated respond better to radiotherapy than hypoxic regions by up to a factor of three. If these volumes could be accurately estimated, then it might be possible to selectively boost dose to radio-resistant regions, a concept known as dose-painting. While imaging...

Descripción completa

Detalles Bibliográficos
Autores principales: Grimes, David Robert, Kannan, Pavitra, Warren, Daniel R., Markelc, Bostjan, Bates, Russell, Muschel, Ruth, Partridge, Mike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4843681/
https://www.ncbi.nlm.nih.gov/pubmed/26935806
http://dx.doi.org/10.1098/rsif.2016.0070
_version_ 1782428669647519744
author Grimes, David Robert
Kannan, Pavitra
Warren, Daniel R.
Markelc, Bostjan
Bates, Russell
Muschel, Ruth
Partridge, Mike
author_facet Grimes, David Robert
Kannan, Pavitra
Warren, Daniel R.
Markelc, Bostjan
Bates, Russell
Muschel, Ruth
Partridge, Mike
author_sort Grimes, David Robert
collection PubMed
description Regions of tissue which are well oxygenated respond better to radiotherapy than hypoxic regions by up to a factor of three. If these volumes could be accurately estimated, then it might be possible to selectively boost dose to radio-resistant regions, a concept known as dose-painting. While imaging modalities such as (18)F-fluoromisonidazole positron emission tomography (PET) allow identification of hypoxic regions, they are intrinsically limited by the physics of such systems to the millimetre domain, whereas tumour oxygenation is known to vary over a micrometre scale. Mathematical modelling of microscopic tumour oxygen distribution therefore has the potential to complement and enhance macroscopic information derived from PET. In this work, we develop a general method of estimating oxygen distribution in three dimensions from a source vessel map. The method is applied analytically to line sources and quasi-linear idealized line source maps, and also applied to full three-dimensional vessel distributions through a kernel method and compared with oxygen distribution in tumour sections. The model outlined is flexible and stable, and can readily be applied to estimating likely microscopic oxygen distribution from any source geometry. We also investigate the problem of reconstructing three-dimensional oxygen maps from histological and confocal two-dimensional sections, concluding that two-dimensional histological sections are generally inadequate representations of the three-dimensional oxygen distribution.
format Online
Article
Text
id pubmed-4843681
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher The Royal Society
record_format MEDLINE/PubMed
spelling pubmed-48436812016-04-26 Estimating oxygen distribution from vasculature in three-dimensional tumour tissue Grimes, David Robert Kannan, Pavitra Warren, Daniel R. Markelc, Bostjan Bates, Russell Muschel, Ruth Partridge, Mike J R Soc Interface Life Sciences–Physics interface Regions of tissue which are well oxygenated respond better to radiotherapy than hypoxic regions by up to a factor of three. If these volumes could be accurately estimated, then it might be possible to selectively boost dose to radio-resistant regions, a concept known as dose-painting. While imaging modalities such as (18)F-fluoromisonidazole positron emission tomography (PET) allow identification of hypoxic regions, they are intrinsically limited by the physics of such systems to the millimetre domain, whereas tumour oxygenation is known to vary over a micrometre scale. Mathematical modelling of microscopic tumour oxygen distribution therefore has the potential to complement and enhance macroscopic information derived from PET. In this work, we develop a general method of estimating oxygen distribution in three dimensions from a source vessel map. The method is applied analytically to line sources and quasi-linear idealized line source maps, and also applied to full three-dimensional vessel distributions through a kernel method and compared with oxygen distribution in tumour sections. The model outlined is flexible and stable, and can readily be applied to estimating likely microscopic oxygen distribution from any source geometry. We also investigate the problem of reconstructing three-dimensional oxygen maps from histological and confocal two-dimensional sections, concluding that two-dimensional histological sections are generally inadequate representations of the three-dimensional oxygen distribution. The Royal Society 2016-03 /pmc/articles/PMC4843681/ /pubmed/26935806 http://dx.doi.org/10.1098/rsif.2016.0070 Text en © 2016 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Life Sciences–Physics interface
Grimes, David Robert
Kannan, Pavitra
Warren, Daniel R.
Markelc, Bostjan
Bates, Russell
Muschel, Ruth
Partridge, Mike
Estimating oxygen distribution from vasculature in three-dimensional tumour tissue
title Estimating oxygen distribution from vasculature in three-dimensional tumour tissue
title_full Estimating oxygen distribution from vasculature in three-dimensional tumour tissue
title_fullStr Estimating oxygen distribution from vasculature in three-dimensional tumour tissue
title_full_unstemmed Estimating oxygen distribution from vasculature in three-dimensional tumour tissue
title_short Estimating oxygen distribution from vasculature in three-dimensional tumour tissue
title_sort estimating oxygen distribution from vasculature in three-dimensional tumour tissue
topic Life Sciences–Physics interface
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4843681/
https://www.ncbi.nlm.nih.gov/pubmed/26935806
http://dx.doi.org/10.1098/rsif.2016.0070
work_keys_str_mv AT grimesdavidrobert estimatingoxygendistributionfromvasculatureinthreedimensionaltumourtissue
AT kannanpavitra estimatingoxygendistributionfromvasculatureinthreedimensionaltumourtissue
AT warrendanielr estimatingoxygendistributionfromvasculatureinthreedimensionaltumourtissue
AT markelcbostjan estimatingoxygendistributionfromvasculatureinthreedimensionaltumourtissue
AT batesrussell estimatingoxygendistributionfromvasculatureinthreedimensionaltumourtissue
AT muschelruth estimatingoxygendistributionfromvasculatureinthreedimensionaltumourtissue
AT partridgemike estimatingoxygendistributionfromvasculatureinthreedimensionaltumourtissue