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Brain structural abnormalities in the preclinical stage of Machado–Joseph disease/spinocerebellar ataxia type 3 (MJD/SCA3): evaluation by MRI morphometry, diffusion tensor imaging and neurite orientation dispersion and density imaging

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Abstract

Objective

To investigate whether neurite orientation dispersion and density imaging (NODDI) could provide the added value for detecting brain microstructural alterations in the preclinical stage of Machado–Joseph disease/spinocerebellar ataxia type 3 (MJD/SCA3) compared with MRI morphometry and diffusion tensor imaging (DTI).

Methods

Twenty preclinical MJD/SCA3 patients and 21 healthy controls were enrolled. Three b values DWI and 3D T1-weighted images were acquired at 3.0 T. Tract-based spatial statistics (TBSS) approach was used to investigate the white matter (WM) alterations in the DTI metrics and NODDI metrics. Gray matter-based spatial statistics (GBSS) approach was used to investigate the grey matter (GM) alterations in the NODDI metrics. Voxel-based morphometry (VBM) approach was performed on the 3D T1-weighted images. The relationship between the cytosine–adenine–guanine (CAG) repeat length and brain microstructural alterations of preclinical MJD/SCA3 was identified.

Results

Compared with healthy controls, the preclinical MJD/SCA3 patients showed decreased FA and NDI as well as increased MD, AD, and RD in the WM of cerebellum and brainstem (corrected P < 0.05), and decreased NDI in the GM of cerebellar vermis (corrected P < 0.05). The CAG repeat length in preclinical MJD/SCA3 patients was negatively correlated with the reduced FA and NDI of the infratentorial WM and the reduced NDI of the cerebellum, and positively with the increased MD and RD of the infratentorial WM.

Conclusions

NOODI can provide novel quantitative microstructural changes in MJD/SCA3 carriers, expanding our understanding of the gray and white matter (axons and dendrites) degeneration in this frequent ataxia syndrome.

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Data availability

The data sets used or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

AD:

Axial diffusivity

CAG:

Cytosine–adenine–guanine

CSF:

Cerebrospinal fluid

DTI:

Diffusion tensor imaging

DWI:

Diffusion weighted imaging

FA:

Fractional anisotropy

FWE:

Familywise error

GBSS:

Gray matter-based spatial statistics

GM:

Grey matter

ICP:

Inferior cerebellar peduncle

MCP:

Middle cerebellar peduncle

MD:

Mean diffusivity

MJD:

Machado–Joseph disease

ML:

Medial lemniscus

NDI:

Neurite density index

NODDI:

Neurite orientation dispersion and density imaging

ODI:

Orientation dispersion index

PVE:

Partial volume effect

RD:

Radial diffusivity

SARA:

Scale for the assessment and rating of ataxia

SCA:

Spinocerebellar ataxia

SCP:

Superior cerebellar peduncle

TBSS:

Tract-based spatial statistics

VBM:

Voxel-based morphometry

Viso:

Volume fraction of isotropic

WM:

White matter

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Funding

This work was supported by the National Nature Science Foundation of Fujian Province (No. 2019J01435) to JPH and the National Nature Science Foundation of China (81971082, Beijing) to SRG.

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Contributions

JPH, XYC, and SRG were responsible for study design and conception and drafting of the manuscript. JPH and MCL was responsible for statistical analysis. MCL, HLX, ZQH, NPC, and YQT contributed to data collection and drafting of the manuscript.

Corresponding authors

Correspondence to Shirui Gan or Jianping Hu.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in the study.

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Li, M., Chen, X., Xu, HL. et al. Brain structural abnormalities in the preclinical stage of Machado–Joseph disease/spinocerebellar ataxia type 3 (MJD/SCA3): evaluation by MRI morphometry, diffusion tensor imaging and neurite orientation dispersion and density imaging. J Neurol 269, 2989–2998 (2022). https://doi.org/10.1007/s00415-021-10890-2

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  • DOI: https://doi.org/10.1007/s00415-021-10890-2

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