Glymphatic and Blood-Brain Barrier Alterations in Aging with Multimodal MRI
Poster No:
921
Submission Type:
Abstract Submission
Authors:
Anjan Bhattarai1, Yufei Zhu1, Barah Albuhwailah1, Pauline Maillard1, Charles DeCarli1, Audrey Fan1
Institutions:
1University of California, Davis, Davis, CA
First Author:
Co-Author(s):
Introduction:
Aging is associated with impaired glymphatic clearance in preclinical models (Kress et al., 2014), but its impact on blood-brain barrier (BBB) health and glymphatic function in humans remains unclear. Diffusion-prepared arterial spin labeling (DP-ASL), a non-contrast MRI technique, allows us to estimate the water exchange rate (Kw) across the BBB, a surrogate measure of BBB health (Shao et al., 2019). Kw has been associated with a diffusion tensor imaging (DTI)-based extracellular white matter free water (FW) measure in older adults, indicating its role in CSF clearance (Pappas et al., 2024). DTI along the perivascular pathway (DTI-ALPS) provides a surrogate measurement of glymphatic activity in the brain (Taoka et al., 2017). In this study, we aimed to uncover multimodal MRI insights into BBB health, white matter free water accumulation and glymphatic clearance in healthy aging. The findings could pave the way for advancing MRI biomarkers aimed at preserving cognitive health in aging populations.
Methods:
N= 22 participants, including 10 younger (26.1 ± 3.0 years) and 12 nondemented older individuals (74.3 ± 6.6 years), underwent MRI scans on a 3T Siemens Prisma scanner. DWI, DP-ASL, and structural MRI data were acquired with the following acquisition parameters: DWI with resolution = 2 × 2 × 2 mm3, 65 directions at b-values = 0, 500, 1000, and 2000 s/mm2; DP-ASL with post-label delay = 1800 ms, labeling duration = 1500 ms, resolution = 3.5 × 3.5 × 8 mm3, 3D GRASE readout, diffusion weighting of 50s/mm²; and FEAST ASL with b-value = 14 s/mm2.
Kw images were processed using the water exchange quantification toolbox (Mutsaerts et al., 2020) to derive whole-brain mean Kw. DWI images were pre-processed and fit to tensor models using MRtrix3 (Tournier et al., 2019) and FSL's dtifit (Jenkinson et al., 2012). ROIs were placed in the projection and association areas along the perivascular space guided by color-coded fractional anisotropy maps. Bilateral DTI-ALPS measures were estimated for each participant. DWI images were processed to compute FW maps (Maillard et al., 2022), which were used to compute mean bilateral white matter FW measures. Linear regression and mixed effect models were used to analyze group differences (between younger and older) and associations between Kw (as a predictor), FW, and DTI-ALPS measures.
Kw images were processed using the water exchange quantification toolbox (Mutsaerts et al., 2020) to derive whole-brain mean Kw. DWI images were pre-processed and fit to tensor models using MRtrix3 (Tournier et al., 2019) and FSL's dtifit (Jenkinson et al., 2012). ROIs were placed in the projection and association areas along the perivascular space guided by color-coded fractional anisotropy maps. Bilateral DTI-ALPS measures were estimated for each participant. DWI images were processed to compute FW maps (Maillard et al., 2022), which were used to compute mean bilateral white matter FW measures. Linear regression and mixed effect models were used to analyze group differences (between younger and older) and associations between Kw (as a predictor), FW, and DTI-ALPS measures.
Results:
We observed a significantly reduced DTI-ALPS index in older participants compared to younger participants (p = 0.001) (Figure 1). Conversely, significantly increased mean white matter free water accumulation was observed in older participants (p < 0.001) and was negatively correlated with the DTI-ALPS index (β = -1.44, p = 0.047).
Group differences were also evident in diffusion coefficients, with a significantly reduced diffusion coefficient along the x-axis in the projection fibers (Dxxproj) in older participants (p = 0.009). Although not statistically significant, increased diffusion coefficient values were noted in older participants along the y-axis in the projection fibers (Dyyproj) (p = 0.057) and along the z-axis in the association fibers (Dzzasso) (p = 0.058).
Significantly reduced whole-brain Kw measures were observed in older participants (p = 0.005), which were negatively correlated with mean FW (β = -0.953×10−3, p = 0.074) and positively associated with the DTI-ALPS index (β = 0.402×10−2, p = 0.051) (Figure 2).
Group differences were also evident in diffusion coefficients, with a significantly reduced diffusion coefficient along the x-axis in the projection fibers (Dxxproj) in older participants (p = 0.009). Although not statistically significant, increased diffusion coefficient values were noted in older participants along the y-axis in the projection fibers (Dyyproj) (p = 0.057) and along the z-axis in the association fibers (Dzzasso) (p = 0.058).
Significantly reduced whole-brain Kw measures were observed in older participants (p = 0.005), which were negatively correlated with mean FW (β = -0.953×10−3, p = 0.074) and positively associated with the DTI-ALPS index (β = 0.402×10−2, p = 0.051) (Figure 2).
Conclusions:
This study provides novel multimodal MRI insights into the relationship between BBB integrity and glymphatic function. Reductions in Kw may reflect impaired BBB function, while reduced DTI-ALPS and increased FW suggest impaired glymphatic clearance in older individuals. Overall, our results show that BBB health is compromised in healthy aging and can potentially predict impaired glymphatic clearance.
Lifespan Development:
Aging 1
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis 2
Other Methods
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity
Novel Imaging Acquisition Methods:
Imaging Methods Other
Keywords:
Aging
Cerebro Spinal Fluid (CSF)
MRI
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Other - Glymphatic; Blood-Brain Barrier; DTI-ALPS; Free Water; Arterial Spin Labeling (ASL), Diffusion-Prepared ASL
1|2Indicates the priority used for review
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Provide references using APA citation style.
Kress, B. T. et al. (2014). Impairment of paravascular clearance pathways in the aging brain. Annals of Neurology, 76(6), 845–861.
Maillard, P. et al. (2022). Instrumental validation of free water, peak‐width of skeletonized mean diffusivity, and white matter hyperintensities: MarkVCID neuroimaging kits. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 14(1), e12261.
Mutsaerts, H. J. M. M. et al. (2020). ExploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies. NeuroImage, 219, 117031.
Pappas, C. et al. (2024). MRI free water mediates the association between water exchange rate across the blood brain barrier and executive function among older adults. Imaging Neuroscience, 2, 1–15.
Shao, X. et al. (2019). Mapping water exchange across the blood–brain barrier using 3D diffusion‐prepared arterial spin labeled perfusion MRI. Magnetic Resonance in Medicine, 81(5), 3065–3079.
Taoka, T. et al. (2017). Evaluation of glymphatic system activity with the diffusion MR technique: Diffusion tensor image analysis along the perivascular space (DTI-ALPS) in Alzheimer’s disease cases. Japanese Journal of Radiology, 35(4), 172–178.
Tournier, J.-D. et al. (2019). MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. NeuroImage, 202, 116137.