Analysis of Age-Related White Matter Microstructures Based on Diffusion Tensor Imaging

Abstract

Population aging has become a serious social problem. Accordingly, many researches are focusing on changes in brains of the elderly. In this study, we used multiple parameters to analyze age-related changes in white matter fibers. A sample cohort of 58 individuals was divided into young and middle-age groups and tract-based spatial statistics (TBSS) were used to analyze the differences in fractional anisotropy (FA), mean diffusion (MD), axial diffusion (AD), and radial diffusion (RD) between the two groups. Deterministic fiber tracking was used to investigate the correlation between fiber number and fiber length with age. The TBSS analysis revealed significant differences in FA, MD, AD, and RD in multiple white matter fibers between the two groups. In the middle-age group FA and AD were lower than in young people, whereas the MD and RD values were higher. Deterministic fiber tracking showed that the fiber length of some fibers correlated positively with age. These fibers were observed in the splenium of corpus callosum (SCC), the posterior limb of internal capsule (PLIC), the right posterior corona radiata (PCR_R), the anterior corona radiata (ACR), the left posterior thalamic radiation (include optic radiation; PTR_L), and the left superior longitudinal fasciculus (SLF_L), among others. The results showed that the SCC, PLIC, PCR_R, ACR, PTR_L, and SLF_L significantly differed between young and middle-age people. Therefore, we believe that these fibers could be used as image markers of age-related white matter changes.

In search of a unifying theory of white matter aging: improving the understanding of tract-wise degeneration using multi-parametric signatures of morphometry and microstructure

“…As a result, more comprehensive modeling of age-related WM changes offers a tool to detect degeneration at earlier stages. Consistent changes in white matter structure and histology have been demonstrated in advancing age (Baker et al, 2014;Bastin et al, 2010;Choy et al, 2020;Ouyang et al, 2021;Tang et al, 1997), with overall volume decreases identified in normal aging (Bastin et al, 2010;Piguet et al, 2009;Tang et al, 1997). Notably, WM volume decreases by up to 28% in adult aging , but there is still a limited understanding of the microstructural variations underlying this volume reduction.…”

“…However, to what degree this potential effect contributes to changes in WM volume, considering the general atrophy of brain volume with age (Azevedo et al, 2019; Fjell et al, 2009, 2014; Sala et al, 2012), is unclear. Individual fiber tracts in the white matter exhibit varying degrees of vulnerability to age-related fiber culling (Choy et al, 2020), potentially giving rise to previous observations of both decreasing and increasing fiber length in specific major white matter bundles including the splenium and superior longitudinal fasciculus (Ouyang et al, 2021), calling into question the assumption that overall decreases in fiber length correspond to regional decreases in tract length. Moreover, the tools with which living WM can be accurately delineated into discrete tracts are both relatively new and continually improving (Maffei et al, 2021).…”

Structural and Functional Brain Connectivity Uniquely Contribute to Episodic Memory Performance in Older Adults

“…Nonetheless, the positive hippocampal cingulum – memory relationship was seen in our previous study in this cohort (for a longer discussion on the direction of this effect, see Alm et al, 2020 ), and two recent studies also reported negative correlations between functional connectivity and memory in non-demented older adults ( Edde et al, 2020 ), as well as subjective cognitive decline and MCI patients ( Xue et al, 2021 ). While it is true that RD generally increases ( Lebel et al, 2012 ; Madden et al, 2012 ; Chen et al, 2013 ; Fjell et al, 2017 ; Ouyang et al, 2021 ) and functional connectivity generally decreases with age ( Fjell et al, 2015 , 2017 ; Sala-Llonch et al, 2015 ; Damoiseaux, 2017 ; Tsang et al, 2017 ), it is important to note that there are many exceptions to this general pattern (for reviews, see Ferreira and Busatto, 2013 ; Antonenko and Flöel, 2014 ). There have also been reports of increases and decreases in structural and functional connectivity in older adults within a single study, depending on the ROI/network ( Madden et al, 2012 ; Tomasi and Volkow, 2012 ; Song et al, 2014 ; Ouyang et al, 2021 ; Xue et al, 2021 ; Pur et al, 2022 ) and whether within or between network connectivity is considered ( Betzel et al, 2014 ; Song et al, 2014 ; Damoiseaux, 2017 ).…”

“…While it is true that RD generally increases ( Lebel et al, 2012 ; Madden et al, 2012 ; Chen et al, 2013 ; Fjell et al, 2017 ; Ouyang et al, 2021 ) and functional connectivity generally decreases with age ( Fjell et al, 2015 , 2017 ; Sala-Llonch et al, 2015 ; Damoiseaux, 2017 ; Tsang et al, 2017 ), it is important to note that there are many exceptions to this general pattern (for reviews, see Ferreira and Busatto, 2013 ; Antonenko and Flöel, 2014 ). There have also been reports of increases and decreases in structural and functional connectivity in older adults within a single study, depending on the ROI/network ( Madden et al, 2012 ; Tomasi and Volkow, 2012 ; Song et al, 2014 ; Ouyang et al, 2021 ; Xue et al, 2021 ; Pur et al, 2022 ) and whether within or between network connectivity is considered ( Betzel et al, 2014 ; Song et al, 2014 ; Damoiseaux, 2017 ). In fact, Xue et al (2021) found that specifically in the salience network, the direction of the functional connectivity – memory relationship in subjective cognitive decline and MCI patients depended on which salience network nodes were examined.…”

Compartmentalized ciliation changes of oligodendrocytes in aged mouse optic nerve

“…The accelerated rate of loss of retinal ganglion cells in aging is a hallmark of glaucoma, a neurodegenerative disease of the optic nerve that leads to irreversible blindness (Ehrlich & Moroi, 2017; Garway‐Heath et al., 1997; Guedes et al., 2011; Jammal et al., 2020; Li, Ning, et al., 2018; Liu et al., 2018; Ramirez et al., 2020). In the brain, in addition to neuron loss, aging also significantly impacts the white matter, which predominantly consists of myelinated axons (Liu et al., 2017; Nasrabady et al., 2018; Ouyang et al., 2021; Peters, 2009). Previous studies have suggested that the degeneration of myelin sheaths contributes to age‐associated white matter volume decline, and further results in demyelinating diseases in humans and rodents.…”