Author/Editor     Grimes, David Robert; Kannan, Pavitra; Warren, Daniel R.; Markelc, Boštjan; Bates, Russell; Muschel, Ruth J.; Partridge, Mike
Title     Estimating oxygen distribution from vasculature in three-dimensional tumour tissue
Type     članek
Vol. and No.     Letnik 13, št. 116
Publication year     2016
Volume     str. 1-12
ISSN     1742-5689 - Journal of the Royal Society, Interface / the Royal Society
Language     eng
Abstract     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 18F-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.
Keywords     onkologija
hipoksija
modeliranje
radioterapija
cancer
hypoxia
modelling
radiotherapy