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Title: Applied voxel-based morphometry in health and neurological disease
Author: Good, Catriona Diana
ISNI:       0000 0001 3504 7229
Awarding Body: University of London
Current Institution: University College London (University of London)
Date of Award: 2004
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The importance of brain structure is indisputable. It forms the framework on which functional parameters can be mapped and referenced. The classical region of interest based morphometric methods that have hitherto formed the mainstay of structural neuroimaging have a number of drawbacks not least because they are spatially constrained and operator dependent. In light of substantial advances in magnetic resonance imaging techniques and concomitant computational post processing innovations, new insights into brain structure are now possible. A new generation of whole brain imaging techniques can now inform about brain structure in a more holistic way with enhanced precision. Computational neuroanatomy is a new method employing the versatile framework of statistic parametric mapping and volumetric high-resolution magnetic resonance images of the brain. It consists of a triad of interactive techniques: voxel-based morphometry (VBM) which provides voxel-wise inferences about regional grey and white matter, deformation-based morphometry (DBM) which characterises global brain shape differences and tensor-based morphometry (TBM) which characterises local shape differences with high precision. This thesis examines the application and usefulness of voxel-based morphometry with particular reference to its practicality, reproducibility, validity and sensitivity to characterise brain structure. VBM is first applied to a large normative catabase to characterise physiological variations in normal brain structure in order to create a canonical framework against which pathology can be measured. VBM is then rigorously compared with classical morphometrics in patients with two distinct forms of dementia and in patients with mesial temporal sclerosis in order to establish validity and sensitivity. VBM is then applied to a variety of disease groups where classical morphometrics have failed to reveal consistent brain structural phenotypes in order to reveal morphological changes in functionally implicated regions. Finally VBM is used is a tool to allow genotype-phenotype mapping. The strengths and weaknesses of this new technique are discussed with reference to its applicability and usefulness for neurologists and neuroradiologists.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available