Steventon, Jessica, Trueman, Rebecca C., Rosser, Anne Elizabeth ORCID: https://orcid.org/0000-0002-4716-4753 and Jones, Derek K. ORCID: https://orcid.org/0000-0003-4409-8049 2016. Robust MR-based approaches to quantifying white matter structure and structure/function alterations in Huntington's disease. Journal of Neuroscience Methods 265 , pp. 2-12. 10.1016/j.jneumeth.2015.08.027 |
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Abstract
BACKGROUND: Huge advances have been made in understanding and addressing confounds in diffusion MRI data to quantify white matter microstructure. However, there has been a lag in applying these advances in clinical research. Some confounds are more pronounced in HD which impedes data quality and interpretability of patient-control differences. This study presents an optimised analysis pipeline and addresses specific confounds in a HD patient cohort. METHOD: 15 HD gene-positive and 13 matched control participants were scanned on a 3T MRI system with two diffusion MRI sequences. An optimised post processing pipeline included motion, eddy current and EPI correction, rotation of the B matrix, free water elimination (FWE) and tractography analysis using an algorithm capable of reconstructing crossing fibres. The corpus callosum was examined using both a region-of-interest and a deterministic tractography approach, using both conventional diffusion tensor imaging (DTI)-based and spherical deconvolution analyses. RESULTS: Correcting for CSF contamination significantly altered microstructural metrics and the detection of group differences. Reconstructing the corpus callosum using spherical deconvolution produced a more complete reconstruction with greater sensitivity to group differences, compared to DTI-based tractography. Tissue volume fraction (TVF) was reduced in HD participants and was more sensitive to disease burden compared to DTI metrics. CONCLUSION: Addressing confounds in diffusion MR data results in more valid, anatomically faithful white matter tract reconstructions with reduced within-group variance. TVF is recommended as a complementary metric, providing insight into the relationship with clinical symptoms in HD not fully captured by conventional DTI metrics.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Biosciences Cardiff University Brain Research Imaging Centre (CUBRIC) Medicine Neuroscience and Mental Health Research Institute (NMHRI) Psychology MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG) |
Subjects: | R Medicine > R Medicine (General) |
Publisher: | Elsevier |
ISSN: | 0165-0270 |
Funders: | Wellcome Trust |
Date of First Compliant Deposit: | 30 March 2016 |
Date of Acceptance: | 20 August 2015 |
Last Modified: | 03 May 2023 18:21 |
URI: | https://orca.cardiff.ac.uk/id/eprint/76748 |
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