Quantitative evaluation of white matter tract DTI parameter changes in gliomas using nonlinear registration

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Abstract

Diffusion tensor imaging (DTI) has been used extensively to investigate white matter architecture in the brain. In the context of neurological disease, quantification of DTI data sets enables objective characterisation of the associated pathological changes. The aim of this study is to propose a method of evaluating DTI parameter changes in gliomas in the internal capsule using nonlinear registration to delineate the white matter and enable quantitative assessment of DTI derived parameters. 20 patients selected pre-operatively with probable grade 2 or grade 3 glioma on structural MRI along with ten normal volunteers were included in this study. DTI fractional anisotropy (FA) maps were used to define a common segmented FA skeleton that was projected back onto the original individual FA maps. Objective segment classification as normal or abnormal was achieved by comparison to prediction intervals of FA and mean diffusivity (MD) defined in normal subjects. The internal capsules of each patient were segmented into 10 regions of interest (ROI) with 20 and 16 segments across the group having significantly increased or decreased FA and MD values respectively. Seven glioma patients had abnormal DTI parameters in the internal capsule. We show that the classification of tract segments was consistent with disruption, oedema or compression. The results suggest that this method could be used to detect changes in eloquent white matter tracts in individual patients.

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