In this section
@article{King:2016:10.12688/f1000research.9355.1,
author = {King, MD and Grech-Sollars, M},
doi = {10.12688/f1000research.9355.1},
journal = {F1000 Research},
title = {A Bayesian spatial random effects model characterisation of tumour heterogeneity implemented using Markov chain Monte Carlo (MCMC) simulation},
url = {http://dx.doi.org/10.12688/f1000research.9355.1},
volume = {5},
year = {2016}
}
TY - JOUR
AB - The focus of this study is the development of a statistical modelling procedure for characterisingintra-tumour heterogeneity, motivated by recent clinical literature indicating that a varietyof tumours exhibit a considerable degree of genetic spatial variability. A formal spatial statisticalmodel has been developed and used to characterise the structural heterogeneity of anumber of supratentorial primitive neuroecto-dermal tumours (PNETs), based on diffusionweightedmagnetic resonance imaging. Particular attention is paid to the spatial dependenceof diffusion close to the tumour boundary, in order to determine whether the data providestatistical evidence to support the proposition that water diffusivity in the boundary region ofsome tumours exhibits a deterministic dependence on distance from the boundary, in excessof an underlying random 2D spatial heterogeneity in diffusion. Tumour spatial heterogeneitymeasures were derived from the diffusion parameter estimates obtained using a Bayesianspatial random effects model. The analyses were implemented using Markov chain MonteCarlo (MCMC) simulation. Posterior predictive simulation was used to assess the adequacyof the statistical model. The main observations are that the previously reported relationshipbetween diffusion and boundary proximity remains observable and achieves statistical significanceafter adjusting for an underlying random 2D spatial heterogeneity in the diffusionmodel parameters. A comparison of the magnitude of the boundary-distance effect with theunderlying random 2D boundary heterogeneity suggests that both are important sources ofvariation in the vicinity of the boundary. No consistent pattern emerges from a comparison ofthe boundary and core spatial heterogeneity, with no indication of a consistently greater levelof heterogeneity in one region compared with the other. The results raise the possibility thatDWI might provide a surrogate marker of intra-tumour genetic regional heterogeneity, whichwould
AU - King,MD
AU - Grech-Sollars,M
DO - 10.12688/f1000research.9355.1
PY - 2016///
SN - 2046-1402
TI - A Bayesian spatial random effects model characterisation of tumour heterogeneity implemented using Markov chain Monte Carlo (MCMC) simulation
T2 - F1000 Research
UR - http://dx.doi.org/10.12688/f1000research.9355.1
UR - http://hdl.handle.net/10044/1/38604
VL - 5
ER -
For enquiries about the MRI Physics Initiative, please contact:
Senior MR Physicist
Mary Finnegan
Imperial Research Fellow
Matthew Grech-Sollars
BRC MR Physics Fellow
Pete Lally