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Journal articleKing MD, Grech-Sollars M, 2016,
A Bayesian spatial random effects model characterisation of tumour heterogeneity implemented using Markov chain Monte Carlo (MCMC) simulation
, F1000 Research, Vol: 5, ISSN: 2046-1402The 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
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Journal articleReynolds HM, Williams S, Zhang A, et al., 2015,
Development of a registration framework to validate MRI with histology for prostate focal therapy
, Medical Physics, Vol: 42, Pages: 7078-7089, ISSN: 0094-2405<jats:sec><jats:title>Purpose:</jats:title><jats:p>Focal therapy has been proposed as an alternative method to whole‐gland treatment for prostate cancer when aiming to reduce treatment side effects. The authors recently validated a radiobiological model which takes into account tumor location and tumor characteristics including tumor cell density, Gleason score, and hypoxia in order to plan optimal dose distributions for focal therapy. The authors propose that this model can be informed using multiparametric MRI (mpMRI) and in this study present a registration framework developed to map prostate mpMRI and histology data, where histology will provide the “ground truth” data regarding tumor location and biology. The authors aim to apply this framework to a growing database to develop a prostate biological atlas which will enable MRI based planning for prostate focal therapy treatment.</jats:p></jats:sec><jats:sec><jats:title>Methods:</jats:title><jats:p>Six patients scheduled for routine radical prostatectomy were used in this proof‐of‐concept study. Each patient underwent mpMRI scanning prior to surgery, after which the excised prostate specimen was formalin fixed and mounted in agarose gel in a custom designed sectioning box. T2‐weighted MRI of the specimen in the sectioning box was acquired, after which 5 mm sections of the prostate were cut and histology sections were microtomed. A number of image processing and registration steps were used to register histology images with <jats:italic>ex vivo</jats:italic> MRI and deformable image registration (DIR) was applied to 3D T2w images to align the <jats:italic>in vivo</jats:italic> and <jats:italic>ex vivo</jats:italic> MRI data. Dice coefficient metrics and corresponding feature points from two independent annotators were selected in order to assess the DIR accuracy.</jats:p></jats:sec><jats:sec&g
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Journal articleGrech-Sollars M, Hales PW, Miyazaki K, et al., 2015,
Multi-centre reproducibility of diffusion MRI parameters for clinical sequences in the brain.
, NMR in Biomedicine, Vol: 28, Pages: 468-485, ISSN: 0952-3480The purpose of this work was to assess the reproducibility of diffusion imaging, and in particular the apparent diffusion coefficient (ADC), intra-voxel incoherent motion (IVIM) parameters and diffusion tensor imaging (DTI) parameters, across multiple centres using clinically available protocols with limited harmonization between sequences. An ice-water phantom and nine healthy volunteers were scanned across fives centres on eight scanners (four Siemens 1.5T, four Philips 3T). The mean ADC, IVIM parameters (diffusion coefficient D and perfusion fraction f) and DTI parameters (mean diffusivity MD and fractional anisotropy FA), were measured in grey matter, white matter and specific brain sub-regions. A mixed effect model was used to measure the intra- and inter-scanner coefficient of variation (CV) for each of the five parameters. ADC, D, MD and FA had a good intra- and inter-scanner reproducibility in both grey and white matter, with a CV ranging between 1% and 7.4%; mean 2.6%. Other brain regions also showed high levels of reproducibility except for small structures such as the choroid plexus. The IVIM parameter f had a higher intra-scanner CV of 8.4% and inter-scanner CV of 24.8%. No major difference in the inter-scanner CV for ADC, D, MD and FA was observed when analysing the 1.5T and 3T scanners separately. ADC, D, MD and FA all showed good intra-scanner reproducibility, with the inter-scanner reproducibility being comparable or faring slightly worse, suggesting that using data from multiple scanners does not have an adverse effect compared with using data from the same scanner. The IVIM parameter f had a poorer inter-scanner CV when scanners of different field strengths were combined, and the parameter was also affected by the scan acquisition resolution. This study shows that the majority of diffusion MRI derived parameters are robust across 1.5T and 3T scanners and suitable for use in multi-centre clinical studies and trials.
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Journal articleGallagher JJ, Finnegan ME, Grehan B, et al., 2012,
Modest Amyloid Deposition is Associated with Iron Dysregulation, Microglial Activation, and Oxidative Stress
, Journal of Alzheimer's Disease, Vol: 28, Pages: 147-161, ISSN: 1387-2877 -
Journal articleAntharam V, Collingwood JF, Bullivant J-P, et al., 2012,
High field magnetic resonance microscopy of the human hippocampus in Alzheimer's disease: Quantitative imaging and correlation with iron
, NeuroImage, Vol: 59, Pages: 1249-1260, ISSN: 1053-8119 -
Journal articleUgarte M, Grime GW, Lord G, et al., 2012,
Concentration of various trace elements in the rat retina and their distribution in different structures
, Metallomics, Vol: 4, Pages: 1245-1245, ISSN: 1756-5901
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