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DC Field | Value | Language |
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dc.contributor.author | Mito, Remika | - |
dc.contributor.author | Dhollander, Thijs | - |
dc.contributor.author | Xia, Ying | - |
dc.contributor.author | Raffelt, David | - |
dc.contributor.author | Salvado, Olivier | - |
dc.contributor.author | Churilov, Leonid | - |
dc.contributor.author | Rowe, Christopher C | - |
dc.contributor.author | Brodtmann, Amy | - |
dc.contributor.author | Villemagne, Victor L | - |
dc.contributor.author | Connelly, Alan | - |
dc.date | 2020-10-26 | - |
dc.date.accessioned | 2021-01-13T03:00:23Z | - |
dc.date.available | 2021-01-13T03:00:23Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | NeuroImage. Clinical 2020; 28: 102479 | en |
dc.identifier.uri | https://ahro.austin.org.au/austinjspui/handle/1/25636 | - |
dc.description.abstract | White matter hyperintensities (WMH) are regions of high signal intensity typically identified on fluid attenuated inversion recovery (FLAIR). Although commonly observed in elderly individuals, they are more prevalent in Alzheimer's disease (AD) patients. Given that WMH appear relatively homogeneous on FLAIR, they are commonly partitioned into location- or distance-based classes when investigating their relevance to disease. Since pathology indicates that such lesions are often heterogeneous, probing their microstructure in vivo may provide greater insight than relying on such arbitrary classification schemes. In this study, we investigated WMH in vivo using an advanced diffusion MRI method known as single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), which models white matter microstructure while accounting for grey matter and CSF compartments. Diffusion MRI data and FLAIR images were obtained from AD (n = 48) and healthy elderly control (n = 94) subjects. WMH were automatically segmented, and classified: (1) as either periventricular or deep; or (2) into three distance-based contours from the ventricles. The 3-tissue profile of WMH enabled their characterisation in terms of white matter-, grey matter-, and fluid-like characteristics of the diffusion signal. Our SS3T-CSD findings revealed substantial heterogeneity in the 3-tissue profile of WMH, both within lesions and across the various classes. Moreover, this heterogeneity information indicated that the use of different commonly used WMH classification schemes can result in different disease-based conclusions. We conclude that future studies of WMH in AD would benefit from inclusion of microstructural information when characterising lesions, which we demonstrate can be performed in vivo using SS3T-CSD. | en |
dc.language.iso | eng | |
dc.subject | 3-tissue | en |
dc.subject | Alzheimer’s disease | en |
dc.subject | Diffusion MRI | en |
dc.subject | Heterogeneity | en |
dc.subject | White matter hyperintensities | en |
dc.title | In vivo microstructural heterogeneity of white matter lesions in healthy elderly and Alzheimer's disease participants using tissue compositional analysis of diffusion MRI data. | en |
dc.type | Journal Article | en |
dc.identifier.journaltitle | NeuroImage. Clinical | en |
dc.identifier.affiliation | Molecular Imaging and Therapy | en |
dc.identifier.affiliation | Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia | en |
dc.identifier.affiliation | CSIRO, Health & Biosecurity, The Australian eHealth Research Centre, Brisbane, Queensland, Australia | en |
dc.identifier.affiliation | CSIRO Data61, Sydney, New South Wales, Australia | en |
dc.identifier.affiliation | Eastern Clinical Research Unit, Monash University, Box Hill Hospital, Melbourne, Victoria, Australia | en |
dc.identifier.affiliation | Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia | en |
dc.identifier.affiliation | Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia | en |
dc.identifier.affiliation | Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia | en |
dc.identifier.affiliation | Medicine (University of Melbourne) | en |
dc.identifier.affiliation | Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia | en |
dc.identifier.affiliation | CSIRO, Health & Biosecurity, The Australian eHealth Research Centre, Brisbane, Queensland, Australia | en |
dc.identifier.doi | 10.1016/j.nicl.2020.102479 | en |
dc.type.content | Text | en |
dc.identifier.pubmedid | 33395971 | |
local.name.researcher | Brodtmann, Amy | |
item.languageiso639-1 | en | - |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.openairetype | Journal Article | - |
crisitem.author.dept | Medicine (University of Melbourne) | - |
crisitem.author.dept | The Florey Institute of Neuroscience and Mental Health | - |
crisitem.author.dept | Molecular Imaging and Therapy | - |
crisitem.author.dept | The Florey Institute of Neuroscience and Mental Health | - |
crisitem.author.dept | Molecular Imaging and Therapy | - |
Appears in Collections: | Journal articles |
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