Signatures of white matter degeneration in Lewy body diseases and prodromal iRBD

Poster No:

177 

Submission Type:

Abstract Submission 

Authors:

Ajay Konuri1, Jack Anderson1, Lachlan Churchill1, Anna Ignatavicius1, Simon Lewis2, Ramon Landin-Romero1, Elie Matar1

Institutions:

1University of Sydney, Sydney, NSW, 2Macquarie University, Sydney, NSW

First Author:

Ajay Konuri  
University of Sydney
Sydney, NSW

Co-Author(s):

Jack Anderson  
University of Sydney
Sydney, NSW
Lachlan Churchill, Bsc  
University of Sydney
Sydney, NSW
Anna Ignatavicius, BSc  
University of Sydney
Sydney, NSW
Simon Lewis  
Macquarie University
Sydney, NSW
Ramon Landin-Romero  
University of Sydney
Sydney, NSW
Elie Matar  
University of Sydney
Sydney, NSW

Introduction:

Lewy body diseases (LBD) include Parkinson's disease (PD), dementia with Lewy body (DLB) and Parkinson's disease dementia, all characterised by overlapping clinical and pathological features. PD is diagnosed based on the onset of motor symptoms while DLB is diagnosed when cognitive impairment precedes motor manifestations by at least one year (McKeith et al., 2017; Postuma et al., 2015) Evidence suggests that white matter changes may occur earlier than grey matter atrophy (Wong et al., 2019) in synucleinopathies, positioning diffusion imaging as a promising modality for early detection.
Furthermore, idiopathic rapid eye movement behaviour disorder (iRBD), has been recognised as a prodromal marker for DLB (McKeith et al., 2017) with longitudinal studies revealing that 75% of individuals with iRBD progress to either DLB or PD within 12 years (Postuma et al., 2019). This study aimed to identify the earliest patterns of neurodegeneration within the LBD spectrum and its prodromal phases. While previous research using fixel-based analysis (FBA) in the PD population has highlighted degeneration in critical white matter tracts such as superior longitudinal fasciculi, thalamocortical circuit and cingulum (Liao et al., 2023; Rau et al., 2019), its application to iRBDs and DLBs remains novel.

Methods:

This study included 16 PD patients (age = 60.7 ± 9.2, disease duration = 2.6 ± 2.9), 12 DLB patients (Age =75 ± 6.7, Disease duration = 0.7 ± 1.06), 16 iRBD patients (Age = 66 ± 7.6, Disease duration=3.5 ± 4.5), and 7 healthy controls (Age = 76.66 ± 6.59). Diffusion-weighted imaging data was acquired using a 3T GE scanner with 30 gradient directions at b=1000m/s2. Following preprocessing, the standard MRtrix3 FBA pipeline (Tournier et al., 2019) was applied. A group fibre orientation distribution template was constructed using data from 20 participants (5 from each group) and a peak threshold of 0.12 was applied for fixel image generation. Whole brain FBA was conducted to compute fibre density and cross-section (FDC) as markers of white matter degeneration across the groups. Group differences were analysed using a general linear model adjusted for age.

Results:

We observed significantly reduced FDC (p<0.01 uncorrected) in the inferior longitudinal fasciculi, left cerebellar peduncle, cingulum bundle and the right corticospinal tract in DLBs compared to healthy controls. Similarly reduced FDC was seen in the postcentral gyrus in PDs compared to controls and in the corticospinal tract in individuals with iRBD compared to controls (Figure 1). Direct comparisons between synucleinopathies and prodromal iRBD also revealed FDC reductions (p<0.01 uncorrected) in several regions. Specifically, reductions in the corpus callosum, arcuate fasciculi and left inferior longitudinal fasciculi were identified in DLBs compared to iRBD while individuals with PD exhibited degeneration in the left superior longitudinal fasciculi compared to iRBDs (Figure 2).
Supporting Image: Figure1.jpg
   ·Figure 1: Fibre density and cross-section maps of DLB, PD and iRBD vs controls. Coloured fixels represent white matter tract segments where FDC reductions are seen in diseased groups compared to contr
Supporting Image: Figure2.jpg
   ·Figure 2: Fibre density and cross-section maps of synucleinopathies (DLB and PD) vs iRBD. Coloured fixels represent white matter tract segments where FDC reductions are seen in PD and DLB compared to
 

Conclusions:

Our preliminary findings highlight distinct patterns of white matter degeneration across synucleinopathies. DLBs exhibited degeneration predominantly in the cerebellum and corticospinal tracts, whereas PD was characterised by degeneration in the postcentral gyrus. The early degeneration of corticospinal tracts observed in iRBD highlights the potential of FBA metrics in these fibres as a potential biomarker for identifying individuals at risk for PD. Future investigations will examine fibre cross-section (FC) and fibre density (FD) in these populations while increasing the sample size to improve the robustness and generalisability of these findings.

Disorders of the Nervous System:

Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1

Modeling and Analysis Methods:

Diffusion MRI Modeling and Analysis 2

Keywords:

MRI
Neurological
STRUCTURAL MRI
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC

1|2Indicates the priority used for review

Abstract Information

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Please indicate below if your study was a "resting state" or "task-activation” study.

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Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Patients

Was this research conducted in the United States?

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Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.

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Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

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Please indicate which methods were used in your research:

Diffusion MRI

For human MRI, what field strength scanner do you use?

3.0T

Which processing packages did you use for your study?

Other, Please list  -   MRtrix3

Provide references using APA citation style.

1. Liao, T. W. (2023). A fixel-based analysis of white matter reductions early detects Parkinson disease with mild cognitive impairment. Biomedical Journal, 47(5), 100678. https://doi.org/10.1016/J.BJ.2023.100678
2. McKeith, I. G.(2017). Diagnosis and management of dementia with Lewy bodies: Fourth consensus report of the DLB Consortium. Neurology, 89(1), 88–100. https://doi.org/10.1212/WNL.0000000000004058
3. Postuma, R. B. (2015). MDS clinical diagnostic criteria for Parkinson’s disease. Movement Disorders : Official Journal of the Movement Disorder Society, 30(12), 1591–1601. https://doi.org/10.1002/MDS.26424
4. Postuma, R. B. (2019). Risk and predictors of dementia and parkinsonism in idiopathic REM sleep behaviour disorder: a multicentre study. Brain : A Journal of Neurology, 142(3), 744–759. https://doi.org/10.1093/BRAIN/AWZ030
5. Rau, Y. A. (2019). A longitudinal fixel-based analysis of white matter alterations in patients with Parkinson’s disease. NeuroImage : Clinical, 24, 102098. https://doi.org/10.1016/J.NICL.2019.102098
6. Tournier, J. D. (2019). MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. NeuroImage, 202, 116137. https://doi.org/10.1016/J.NEUROIMAGE.2019.116137
7. Wong, Y. C. (2019). Neuronal Vulnerability in Parkinson Disease and Putative Therapeutics: Should the focus be on axonal and synaptic terminals? Movement Disorders : Official Journal of the Movement Disorder Society, 34(10), 1406. https://doi.org/10.1002/MDS.27823

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