Journal article
Test-Retest Reliability of Diffusion Tensor Imaging in Huntington’s Disease
PLoS currents, Vol.6
03/21/2014
PMCID: PMC3962450
PMID: 24672743
Abstract
Diffusion tensor imaging (DTI) has shown microstructural abnormalities in patients with Huntington’s Disease (HD) and work is underway to characterise how these abnormalities change with disease progression. Using methods that will be applied in longitudinal research, we sought to establish the reliability of DTI in early HD patients and controls. Test-retest reliability, quantified using the intraclass correlation coefficient (ICC), was assessed using region-of-interest (ROI)-based white matter atlas and voxelwise approaches on repeat scan data from 22 participants (10 early HD, 12 controls). T1 data was used to generate further ROIs for analysis in a reduced sample of 18 participants. The results suggest that fractional anisotropy (FA) and other diffusivity metrics are generally highly reliable, with ICCs indicating considerably lower within-subject compared to between-subject variability in both HD patients and controls. Where ICC was low, particularly for the diffusivity measures in the caudate and putamen, this was partly influenced by outliers. The analysis suggests that the specific DTI methods used here are appropriate for cross-sectional research in HD, and give confidence that they can also be applied longitudinally, although this requires further investigation. An important caveat for DTI studies is that test-retest reliability may not be evenly distributed throughout the brain whereby highly anisotropic white matter regions tended to show lower relative within-subject variability than other white or grey matter regions.
Details
- Title: Subtitle
- Test-Retest Reliability of Diffusion Tensor Imaging in Huntington’s Disease
- Creators
- James H Cole - Imperial College LondonRuth E Farmer - University of LondonElin M Rees - UCL Institute of NeurologyHans J Johnson - University of IowaChris Frost - University of LondonRachael I Scahill - UCL Institute of NeurologyNicola Z Hobbs - UCL Institute of Neurology
- Resource Type
- Journal article
- Publication Details
- PLoS currents, Vol.6
- Publisher
- Public Library of Science
- PMID
- 24672743
- PMCID
- PMC3962450
- ISSN
- 2157-3999
- eISSN
- 2157-3999
- Language
- English
- Date published
- 03/21/2014
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Psychiatry
- Record Identifier
- 9984185467602771
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