Use this URL to cite or link to this record in EThOS:
Title: The prognostic value of advanced MR in gliomas
Author: Kenning, Lawrence
ISNI:       0000 0004 5363 6635
Awarding Body: University of Hull
Current Institution: University of Hull
Date of Award: 2014
Availability of Full Text:
Access from EThOS:
Access from Institution:
This work examines the prognostic value of advanced MR at selected time points during the early stages of treatment in glioma patients. In this thesis, serial imaging of glioma patients was conducted using diffusion tensor imaging (DTI), dynamic contrast enhanced (DCE) and dynamic susceptibility contrast (DSC) MRI. A methodology for the processing and registration of multiparametric MRI was developed in order to simultaneously sample whole tumour measurements of multiple MR parameters with the same volume of interest. Differences between glioma grades were investigated using functional MR parameters and tested using Kruskal-Wallis tests. A 2-stage logistic regression model was developed to grade lesions from the preoperative MR, with the model retaining the apparent diffusion coefficient, radial diffusivity, anisotropic component of diffusion, vessel permeability and extravascular extracellular space parameters for glioma grading. A multi-echo single voxel spectroscopic sequence was independently investigated for the classification of gliomas into different grades. From preoperative MR, progression-free survival was predicted using the multiparametric MR data. Individual parameters were investigated using Kaplan-Meier survival analysis, before Cox regression modelling was used for a multiparametric analysis. Radial diffusivity, spin–lattice relaxation rate and blood volume fraction calculated from the DTI and DCE MRI were retained in the final model. MR parameter values were also investigated during the early stages of adjuvant treatment. Patients were scanned before and after chemoradiotherapy, with the change in MR parameters as well as the absolute values investigated for their prognostic information. Cox regression analysis was also performed for the adjuvant treatment imaging, with measures of the apparent diffusion coefficient, spin–lattice relaxation rate, vessel permeability and extravascular extracellular space, derived from the DTI and DCE datasets most predictive of progression-free survival. In conclusion, this thesis demonstrates multiparametric MR of gliomas during the early stages of treatment contains useful prognostic information relating to grade and progression-free survival interval.
Supervisor: Lowry, Martin; Pickles, Martin Darren Sponsor: Yorkshire Cancer Research Campaign
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Medicine