Poster No:
235
Submission Type:
Abstract Submission
Authors:
Nicola Slater1, Daniel Myall2, Kyla-Louise Horne1, Campbell Le Heron3, Ross Keenan4, Ian Kirk5, Wassilios Meissner6, Tim Anderson3, Tracy Melzer7, John Dalrymple-Alford7
Institutions:
1University of Otago / New Zealand Brain Research Institute, Christchurch, New Zealand, 2New Zealand Brain Research Institute, Christchurch, New Zealand, 3University of Otago / New Zealand Brain Research Institute / Christchurch Hospital, Christchurch, New Zealand, 4Pacific Radiology Canterbury, Christchurch, New Zealand, 5University of Auckland, Auckland, New Zealand, 6University of Bordeaux, Bordeaux, France, 7University of Canterbury / New Zealand Brain Research Institute, Christchurch, New Zealand
First Author:
Nicola Slater
University of Otago / New Zealand Brain Research Institute
Christchurch, New Zealand
Co-Author(s):
Daniel Myall
New Zealand Brain Research Institute
Christchurch, New Zealand
Kyla-Louise Horne
University of Otago / New Zealand Brain Research Institute
Christchurch, New Zealand
Campbell Le Heron
University of Otago / New Zealand Brain Research Institute / Christchurch Hospital
Christchurch, New Zealand
Ross Keenan
Pacific Radiology Canterbury
Christchurch, New Zealand
Tim Anderson
University of Otago / New Zealand Brain Research Institute / Christchurch Hospital
Christchurch, New Zealand
Tracy Melzer
University of Canterbury / New Zealand Brain Research Institute
Christchurch, New Zealand
John Dalrymple-Alford
University of Canterbury / New Zealand Brain Research Institute
Christchurch, New Zealand
Introduction:
Reduced integrity in the medial septal region of the cholinergic basal forebrain (Ch1-2) and the associated septohippocampal pathway may play a role in cognitive impairment in Parkinson's disease (PD). Microstructural changes in the Ch1-2 region have been associated with impaired cognition in PD (Gargouri et al., 2019; Ray et al., 2023), as have macrostructural changes (Berlot et al., 2021). However, most assessments of Ch1-2 volume have not shown a difference between PD and controls, though studies often included none to a very small number of cognitively impaired PD participants (Berlot et al., 2021; Legault-Denis et al., 2024; Pereira et al., 2020; Ray et al., 2018, 2023). There is no evidence septohippcampal pathway connection density varies between PD and controls (Gargouri et al., 2019). Given both the challenge of isolating this pathway and the limited evaluation in PD, this study sought to further investigate septohippocampal pathway integrity using tensor and fixel-based measures of white matter integrity in a sample of PD participants with a broad range of cognitive abilities.
Methods:
Structural and diffusion-weighted MRI and neuropsychological assessments were acquired from a convenience sample of 108 PD patients (mean age = 71.3 years, SD = 6.8), of whom 59 showed normal cognition (PD-N), 37 met criteria for mild cognitive impairment (MDS Level II criteria; PD-MCI), and 12 with Parkinson's disease dementia (PDD), compared with 41 control participants (mean age = 70.6 years, SD = 9.0). A global cognitive score was determined for each participant across the domains of attention/working memory, executive function, episodic memory, and visuospatial function. Intracranial volume-adjusted grey matter volume of Ch1-2, as defined by Kilimann et al. (2014), was calculated by summing grey matter voxel values from modulated normalized grey matter segments. Diffusion-weighted images were acquired with a HARDI sequence, 150 directions (8/25/50/75 volumes with b = 0/1000/2000/2700 s/mm2, TR 3600ms, TE 106ms, 90deg flip angle, 126 × 126 × 72 acquisition matrix, 240 mm FOV, 1.9 × 1.9 × 2 mm3 voxel size, MB = 3, with inverted phase-encoded images). MRtrix3.0 was used for all diffusion processing (Tournier et al., 2019). After preprocessing, multi-shell multi-tissue, ACT-informed constrained spherical deconvolution (MSMT-CSD) was used to estimate fibre orientation distribution functions which were intensity normalised and then used to generate tractograms. Diffusion metrics were extracted from the septohippocampal pathway, i.e., streamlines connecting Ch1-2 and the hippocampus (as defined in the AAL3; Rolls et al. [2020]). The relationship between diffusion metrics and global cognitive ability was investigate using Bayesian regression models, accounting for age and sex.
Results:
Lower Ch1-2 volume was associated with lower global cognition for PD participants (β = 0.3 [0.1, 0.5], P(β>0) = 99%), but not for controls (β = 0.4 [-0.1, 0.9], P(β>0) < 95%). Both lower mean septohippocampal pathway fibre density (FD) and fibre density and cross section (FDC) were associated with lower global cognition for PD participants (FD: β = 0.3 [0.1, 0.4], P (β>0) > 99%; FDC: β = 0.3 [0.1, 0.4], P (β>0) = 99%), but not for controls (FD: β = 0.2 [-0.2, 0.6], P (β>0) < 95%; FDC: β = 0.2 [-0.2, 0.6], P (β>0) < 95%). We found no evidence for an association between reduced pathway fractional anisotropy (FA), or increased mean diffusivity (MD) or free water (FW) for PD participants or controls.
Conclusions:
The association of reduced fibre density with lower cognition suggests that integrity of the septohippocampal pathway may contribute to cognitive heterogeneity in PD. However, the modest effect size suggests that other neural systems, including the NBM to cortex pathways, will also contribute to cognition in PD. Longitudinal studies are required to determine the timing and progression of such changes with respect to cognitive decline in PD.
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:
Acetylcholine
Degenerative Disease
DISORDERS
STRUCTURAL MRI
White Matter
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
1|2Indicates the priority used for review
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Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
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Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
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Please indicate which methods were used in your research:
Structural MRI
Diffusion MRI
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
SPM
FSL
Other, Please list
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MRtrix3.0
Provide references using APA citation style.
Berlot, R., et al. (2021). Cholinergic basal forebrain and hippocampal structure influence visuospatial memory in Parkinson’s disease. Brain Imaging and Behavior, 1, 3.
Gargouri, F., et al. (2019). Multimodal magnetic resonance imaging investigation of basal forebrain damage and cognitive deficits in Parkinson’s disease. Movement Disorders, 34(4), 516–525.
Kilimann, I., et al. (2014). Subregional Basal Forebrain Atrophy in Alzheimer’s Disease: A Multicenter Study. Journal of Alzheimer’s Disease, 40(3), 687–700.
Legault-Denis, C., et al. (2024). Parkinson’s disease CA2-CA3 hippocampal atrophy is accompanied by increased cholinergic innervation in patients with normal cognition but not in patients with mild cognitive impairment. Brain Imaging and Behavior, 1–11.
Pereira, J. B., et al. (2020). Longitudinal degeneration of the basal forebrain predicts subsequent dementia in Parkinson’s disease. Neurobiology of Disease, 139, 104831.
Ray, N. J., et al. (2018). In vivo cholinergic basal forebrain atrophy predicts cognitive decline in de novo Parkinson’s disease. Brain, 141(1), 165–176.
Ray, N. J., et al. (2023). Free-water imaging of the cholinergic basal forebrain and pedunculopontine nucleus in Parkinson’s disease. Brain, 146(3), 1053–1064.
Rolls, E. T., et al. (2020). Automated anatomical labelling atlas 3. NeuroImage, 206, 116189.
Tournier, J.-D., et al. (2019). MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. NeuroImage, 202, 116137.
No