Fixel-based white matter differences in subjective cognitive decline and cognitive impairment
Poster No:
125
Submission Type:
Abstract Submission
Authors:
Zheng Long Lee1, Mervin Tee2, Wei Ying Tan2, Xiangyuan Huang2, Charly Billaud1, Junhong Yu1, Saima Hilal2
Institutions:
1Nanyang Technological University, Singapore, Singapore, 2National University of Singapore, Singapore, Singapore
First Author:
Co-Author(s):
Introduction:
White matter (WM) structure is commonly studied with the diffusion tensor imaging (DTI) model. However, DTI is modelled on a voxel level and do not correctly account for crossing fibres (Dhollander et al., 2021; Jeurissen et al., 2012). Fixel-based analysis (FBA) instead models individual fibres within each voxel, providing a better understanding of WM structures (Dhollander et al., 2021). FBA provides three metrics: fibre density (FD), fibre-bundle cross-section (FBC), and fibre density and cross-section (FDC). While previous studies have focused on FBA metrics in Alzheimer's disease (AD) and mild cognitive impairment (MCI) (Mito et al., 2018), fewer studies have examined FBA metrics in subjective cognitive decline (SCD). SCD is an important group to study because they are at a higher risk of developing MCI (van Harten et al., 2018). Additionally, there are limited studies examing FBA metris in cognitive impairment in an Asian population. Hence, this study examined FBA metrics in middle-aged and older participants with SCD and cognitive impairment in Singapore, a multiracial Southeast Asian country.
Methods:
We examined data from 247 participants from two studies at the National University of Singapore: Neurological Biomarker of Blood, MRI and Cognition Study (NEURO-BMC; n = 190; mean age = 59.5) and Multidimensional Healthy Ageing in Population-based Study (MAPS; n = 57; mean age = 77.2). They were divided into three groups based on diagnoses: healthy control (HC, N=98), SCD (N=96), and cognitive impairment, no dementia (CIND, N=53). Multi-shelled diffusion-weighted images (DWI) were acquired on a Siemens Magnetom Prisma scanner (b=0, 200, 500, 1000, 2000s/mm2). We preprocessed and conducted the FBA using MRtrix3 (Dhollander et al., 2021). We estimated the fibre orientation distribution (FOD) functions and created a study-specific FOD template with random samples of 30 subjects from each group. Whole-brain fibre tractography was conducted using the FOD template. Whole-brain group comparisons were run using connectivity-based fixel enhancement on the smoothed fixel data with 5000 permutations and family-wise error correction of 0.05 (Raffelt et al., 2015). Based on these analyses, we extracted tracts of interest in the corpus callosum (CC) and cerebellum using TractSeg (Wasserthal et al., 2018). We conducted multinomial logistic regression on the average FBA metrics in these tracts. Sex and age were controlled for all analyses, and the log of intracranial volume was adjusted when predicting log(FBC) and FDC (Smith et al., 2019).
Results:
Our whole-brain FBA found significant WM alterations in the CC and cerebellum when comparing the groups (Figure 1; streamlines coloured based on absolute effect sizes). Specifically, the FBC was higher in the isthmus of the CC in SCD than in HC and the cerebellum in HC and SCD than in CIND. The FD was higher in the splenium and rostral body of the CC in HC than in CIND. For our tracts of interest analysis, the odds ratios for the CC tracts are displayed in Figure 2. FBA metrics in the inferior, middle and superior cerebellar peduncles were not significant at p=.05. The FBC and FDC of several CC tracts were positively linked to SCD, and the FD of several CC tracts was negatively linked to CIND. However, no tract-wise effect was significant after applying a false discovery rate correction.
·Figure 1
·Figure 2
Conclusions:
Based on the results, cognitive impairment is likely linked to WM structural changes in the CC and the cerebellum. However, the present effects are weak, possibly due to the sample's characteristics-heterogeneity within the CIND group. The result also suggests that the WM structural abnormalities in the isthmus of the CC might underline SCD. The higher FBC in CC regions in the SCD than in HC might suggest axonal dystrophy-e.g., swelling of axons due to amyloid-beta (Salvadores et al., 2020)-which precedes neurodegeneration (Wei et al., 2024). Future research can examine the FBC of the isthmus as a potential biomarker for SCD.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Lifespan Development:
Aging
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis
Novel Imaging Acquisition Methods:
Diffusion MRI 2
Keywords:
Aging
Degenerative Disease
White Matter
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
1|2Indicates the priority used for review
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Provide references using APA citation style.
Jeurissen, B. (2012). Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging. Human Brain Mapping, 34(11), 2747–2766. https://doi.org/10.1002/hbm.22099
Mito, R. (2018). Fibre-specific white matter reductions in Alzheimer’s disease and mild cognitive impairment. Brain, 141(3), 888–902. https://doi.org/10.1093/brain/awx355
Raffelt, D. (2015). Connectivity-based fixel enhancement: Whole-brain statistical analysis of diffusion MRI measures in the presence of crossing fibres. Neuroimage, 117, 40–55. https://doi.org/10.1016/j.neuroimage.2015.05.039
Salvadores, N. (2020). Axonal Degeneration in AD: The Contribution of Aβ and Tau. Frontiers in Aging Neuroscience, 12, Article 581767. https://doi.org/10.3389/fnagi.2020.581767
Smith, R. (2019). On the regression of intracranial volume in Fixel-Based Analysis. Proceedings of the International Society for Magnetic Resonance in Medicine 27th, 3385.
van Harten, A. C. (2018). Subjective cognitive decline and risk of MCI. Neurology, 91(4), e300–e312. https://doi.org/10.1212/WNL.0000000000005863
Wasserthal, J., Neher, P., & Maier-Hein, K. H. (2018). TractSeg—Fast and accurate white matter tract segmentation. NeuroImage, 183, 239–253. https://doi.org/10.1016/j.neuroimage.2018.07.070
Wei, Y.-C. (2024). White matter alterations and their associations with biomarkers and behavior in subjective cognitive decline individuals: A fixel-based analysis. Behavioral and Brain Functions: BBF, 20, Article 12. https://doi.org/10.1186/s12993-024-00238-x