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In vivo microstructural heterogeneity of white matter lesions in Alzheimer’s disease using tissue compositional analysis of diffusion MRI data

View ORCID ProfileRemika Mito, View ORCID ProfileThijs Dhollander, Ying Xia, David Raffelt, Olivier Salvado, Leonid Churilov, Christopher C Rowe, Amy Brodtmann, Victor L Villemagne, Alan Connelly
doi: https://doi.org/10.1101/623124
Remika Mito
1Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
2Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia
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  • ORCID record for Remika Mito
  • For correspondence: remika.mito@florey.edu.au
Thijs Dhollander
1Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
2Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia
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Ying Xia
3CSIRO, Health & Biosecurity, The Australian eHealth Research Centre, Brisbane, Queensland, Australia
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David Raffelt
1Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
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Olivier Salvado
3CSIRO, Health & Biosecurity, The Australian eHealth Research Centre, Brisbane, Queensland, Australia
4CSIRO Data61, Sydney, New South Wales, Australia
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Leonid Churilov
1Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
2Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia
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Christopher C Rowe
1Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
5Department of Medicine, Austin Health, University of Melbourne, Victoria, Australia
6Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, Victoria, Australia
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Amy Brodtmann
1Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
2Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia
7Eastern Clinical Research Unit, Monash University, Box Hill Hospital, Melbourne, Victoria, Australia
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Victor L Villemagne
1Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
5Department of Medicine, Austin Health, University of Melbourne, Victoria, Australia
6Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, Victoria, Australia
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Alan Connelly
1Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
2Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia
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Abstract

White matter hyperintensities (WMH) are commonly observed in elderly individuals, and are typically more prevalent in Alzheimer’s disease subjects than in healthy subjects. These lesions can be identified on fluid attenuated inversion recovery (FLAIR) MRI, on which they are hyperintense compared to their surroundings. These MRI-visible lesions appear homogeneously hyperintense despite known heterogeneity in their pathological underpinnings, and are commonly regarded as surrogate markers of small vessel disease in in vivo studies. Consequently, the extent to which these lesions contribute to Alzheimer’s disease remains unclear, likely due to the somewhat limited way in which these lesions are assessed in vivo. Diffusion MRI is sensitive to white matter microstructure, and might thus be used to investigate microstructural changes within WMH. In this study, we applied a method called single-shell 3-tissue constrained spherical deconvolution, which models white matter microstructure while also accounting for other tissue compartments, to investigate WMH in vivo. Diffusion MRI data and FLAIR images were obtained from Alzheimer’s disease (n = 48) and healthy elderly control (n = 94) subjects from the Australian Imaging, Biomarkers and Lifestyle study of ageing. WMH were automatically segmented and classified as periventricular or deep lesions from FLAIR images based on their continuity with the lateral ventricles, and the 3-tissue profile of different classes of WMH was characterised by three metrics, which together characterised the relative tissue profile in terms of the white matter-, grey matter-, and fluid-like characteristics of the diffusion signal. Our findings revealed that periventricular and deep lesion classes could be distinguished from one another, and from normal-appearing white matter based on their 3-tissue profile, with substantially higher free water content in periventricular lesions than deep. Given the higher lesion load of periventricular lesions in Alzheimer’s disease patients, the 3-tissue profile of these WMH could be interpreted as reflecting the more deleterious pathological underpinnings that are associated with disease. However, when alternatively classifying lesion sub-regions in terms of distance contours from the ventricles to account for potential heterogeneity within confluent lesions, we found that the highest fluid content was present in lesion areas most proximal to the ventricles, which were common to both Alzheimer’s disease subjects and healthy controls. We argue that whatever classification scheme is used when investigating WMH, failure to account for heterogeneity within lesions may result in classification-scheme dependent conclusions. Future studies of WMH in Alzheimer’s Disease would benefit from inclusion of microstructural information when characterising lesions.

  • Abbreviations

    AIBL
    Australian Imaging Biomarkers and Lifestyle study of ageing
    CSD
    Constrained spherical deconvolution
    CSF
    cerebrospinal fluid
    DTI
    Diffusion tensor imaging
    DWI
    Diffusion-weighted imaging
    FLAIR
    Fluid-attenuated inversion recovery
    FOD
    Fibre orientation distribution
    GM
    grey matter
    HIST
    HyperIntensity Segmentation Tool
    NAWM
    Normal-appearing white matter
    SS3T-CSD
    Single-shell 3-tissue constrained spherical deconvolution
    TC
    Cerebrospinal fluid-like signal fraction
    TG
    Grey matter-like signal fraction
    TW
    White matter-like signal fraction
    WM
    white matter
    WMH
    White matter hyperintensities
  • Copyright 
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    Posted May 03, 2019.
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    In vivo microstructural heterogeneity of white matter lesions in Alzheimer’s disease using tissue compositional analysis of diffusion MRI data
    Remika Mito, Thijs Dhollander, Ying Xia, David Raffelt, Olivier Salvado, Leonid Churilov, Christopher C Rowe, Amy Brodtmann, Victor L Villemagne, Alan Connelly
    bioRxiv 623124; doi: https://doi.org/10.1101/623124
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    In vivo microstructural heterogeneity of white matter lesions in Alzheimer’s disease using tissue compositional analysis of diffusion MRI data
    Remika Mito, Thijs Dhollander, Ying Xia, David Raffelt, Olivier Salvado, Leonid Churilov, Christopher C Rowe, Amy Brodtmann, Victor L Villemagne, Alan Connelly
    bioRxiv 623124; doi: https://doi.org/10.1101/623124

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