Healthy Brain Aging is Associated with Decreased White Matter Tract Integrity

Poster No:

1622 

Submission Type:

Abstract Submission 

Authors:

Kauê Duarte1, Abhijot Sidhu1, Cheryl McCreary2, Marina Saluzzi2, Louis Lauzon2, Richard Frayne2

Institutions:

1University of Calgary, Calgary, AL, 2University of Calgary, Calgary, Alberta

First Author:

Kauê Duarte  
University of Calgary
Calgary, AL

Co-Author(s):

Abhijot Sidhu  
University of Calgary
Calgary, AL
Cheryl McCreary  
University of Calgary
Calgary, Alberta
Marina Saluzzi  
University of Calgary
Calgary, Alberta
Louis Lauzon  
University of Calgary
Calgary, Alberta
Richard Frayne, Ph.D.  
University of Calgary
Calgary, Alberta

Introduction:

The functional gray matter regions of the brain are interconnected by white matter (WM) fiber tracts that across between various regions of the central nervous system. These fibers enable communication between regions that is vital for sensory and associative functions. Diffusion imaging studies suggest that the integrity of WM tracts follows an inverted "U-shaped" trajectory across adulthood, where WM maturation peaks occur in middle age, plateaus, and then decreases in late adulthood [1,2]. This study examines the aging trajectories of 31 major WM tracts. We hypothesize WM tract integrity fractional anisotropy (FA) follows an inverse "U-shape" increases until middle age, plateaus, and subsequently declines in older adulthood (i.e., "inverted U-shaped" trajectory). Conversely, mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) are hypothesized to follow a "U-shaped" trajectory.

Methods:

Cross-sectional DWI data of 263 presumed healthy individuals (48.7±18.4y, 55% female) from the Calgary Normative Study were acquired on a 3-T MR system with b-value = 1000 s/mm2 with 30 non-colinear diffusion directions [3]. Diffusion data were processed using MRtrix3 with standard BATMAN and included denoising, Gibbs artifact removal, brain extraction, eddy current and motion correction, and diffusion tensor estimation. Rigid transformation (six degrees of freedom) was applied to transform the images to MNI152 space. Tractseg [4] was used to generate WM tract masks which were visually inspected. Preprocessed diffusion, FA masks, and WM tracts were visually inspected. Mean FA, MD, RD, and AD were computed for these tracts. Corresponding left and right WM tract masks were merged into a single mask file, the fornix was excluded due to poor segmentation results, and the corpus callosum was analyzed as one tract rather than as multiple subsegments. Linear models were fit to investigate the FA, MD, RD, and AD as response variables and age, age2, sex, and age×sex interaction for each tract. Results were adjusted for multiple comparisons using Holm-Bonferroni correction.

Results:

Age2 exhibited a significant effect on average FA, MD, and RD for all 31 examined tracts, as shown in Figure 1 and summarised in Table 1. Age2 also exhibited a significant effect on average AD for 28 tracts with age2 effects not surviving multiple comparisons correction for MCP, ICP and SCP. FA displayed an "inverted U-shaped" trajectory, where FA increases from young adulthood and peaks, on average, around 45.2±3.1 y, plateaus, and then declines in older adulthood across all 31 tracts. MD and RD displayed a "U-shaped" trajectory, where MD and RD both increase from young adulthood, reach a minimum, on average, at 34.7±5.3 y and 36.2±5.1 y, respectively, and then increases into older adulthood across all 31 tracts. Except in 3 tracts, AD displayed a "U-Shaped" trajectory, where AD increases from young adulthood, reaches a minimum, on average, at 30.2±6.1 y, plateaus, and then increases into older adulthood across all tracts. No significant sex or age×sex interactions effects were found.
Supporting Image: plot_scatter_.png
   ·Figure 1. FA, MD, RD, and AD trends for four representative WM tracts (blue: Arcuate fascicle; red: Middle cerebellar peduncle; yellow: Striato-postcentral; purple: Striato-occipital)
Supporting Image: table.PNG
   ·Table 1. Tract names and descriptions. Fit beta coefficients for the age2 term are reported with p-value. The inflection point (peak for FA, troughs for AD, MD, and RD) are also reported. * = p<0.001
 

Conclusions:

This work investigated in a large group aging effects on four diffusion tensor measures (FA, MD, AD, RD) for 31 WM tracts across the healthy adult lifespan. FA exhibited an "inverted U-shaped" trajectory across adulthood, whereas MD, and RD displayed a "U-shaped trajectory" for all 31 tracts. Similarly, AD also displayed a "U-shaped" trajectory, however, this effect was observed in 28 of 31 tracts after multiple comparisons correction. These trajectories possibly indicate underlying age-associated changes in WM integrity. The homogeneity of our results suggests that age-associated differences in WM integrity reflect more global or whole-brain mechanism rather than region-specific changes. The absence of significant sex differences or age by sex interaction effects also suggests that the observed patterns are consistent across both sexes.

Lifespan Development:

Aging 2

Modeling and Analysis Methods:

Diffusion MRI Modeling and Analysis 1

Keywords:

Data analysis
White Matter
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC

1|2Indicates the priority used for review

Provide references using author date format

[1] Liu H, Yang Y, Xia Y, Zhu W, Leak RK, Wei Z, Wang J, Hu X. (2017) Aging of cerebral white matter. Ageing Res Rev. Mar;34:64-76. doi: 10.1016/j.arr.2016.11.006.
[2] Westlye L , Walhovd K, Dale A, et al (2010) Life-Span Changes of the Human Brain White Matter: Diffusion Tensor Imaging (DTI) and Volumetry, Cerebral Cortexm Volume 20, Issue 9, Pages 2055–2068, https://doi.org/10.1093/cercor/bhp280.
[3] McCreary, C. (2020), Calgary normative study: Design of a prospective longitudinal study to characterise potential quantitative MR biomarkers of neurodegeneration over the adult lifespan, BMJ Open, vol. 10, no. 8.
[4] J Wasserthal, P Neher, K Maier-Hein (2018) TractSeg - Fast and accurate white matter tract segmentation, NeuroImage, Volume 183, Pages 239-253,https://doi.org/10.1016/j.neuroimage.2018.07.070.