Age-Related Alterations in DTI Metrics in the Human Brain—Consequences for Age Correction

Background: Over the life span, the diffusion metrics in brain MRI show different, partly nonlinear changes. These age-dependent changes also seem to exhibit regional differences with respect to the brain anatomy. The age correction of a study cohort's diffusion metrics might thus require consi...

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Main Authors: Anna Behler, Jan Kassubek, Hans-Peter Müller
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-06-01
Series:Frontiers in Aging Neuroscience
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fnagi.2021.682109/full
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spelling doaj-0f9fa1c2a9c140689f2d1d74d92ab4792021-06-15T05:57:56ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652021-06-011310.3389/fnagi.2021.682109682109Age-Related Alterations in DTI Metrics in the Human Brain—Consequences for Age CorrectionAnna BehlerJan KassubekHans-Peter MüllerBackground: Over the life span, the diffusion metrics in brain MRI show different, partly nonlinear changes. These age-dependent changes also seem to exhibit regional differences with respect to the brain anatomy. The age correction of a study cohort's diffusion metrics might thus require consideration of age-related factors.Methods: Diffusion tensor imaging data sets were acquired from 219 healthy participants at ages between 19 and 81 years. Fractional anisotropy (FA), mean diffusivity (MD), and axial and radial diffusivity (AD and RD, respectively) maps were analyzed by a tract of interest-based fiber tracking approach. To describe diffusion metrics as a function of the participant age, linear splines were used to perform curve fitting in 21 specific tract systems covering different functional areas and diffusion directions.Results: In the majority of tracts, an interpolation with a change of alteration rate during adult life described the diffusion properties more accurately than a linear model. Consequently, the diffusion properties remained relatively stable until a decrease (of FA) or increase (of MD, AD, and RD) started at a region-specific time point, whereas a uniform change of diffusion properties was observed only in a few tracts. Single tracts, e.g., located in the cerebellum, remained nearly unaltered throughout the ages between 19 and 81 years.Conclusions: Age corrections of diffusion properties should not be applied to all white matter regions and all age spans in the same way. Therefore, we propose three different approaches for age correction based on fiber tracking techniques, i.e., no correction for areas that do not experience age-related changes and two variants of an age correction depending on the age range of the cohort and the tracts considered.https://www.frontiersin.org/articles/10.3389/fnagi.2021.682109/fulldiffusion tensor imagingage dependencemagnetic resonance imagingfractional anisotropydiffusivity
collection DOAJ
language English
format Article
sources DOAJ
author Anna Behler
Jan Kassubek
Hans-Peter Müller
spellingShingle Anna Behler
Jan Kassubek
Hans-Peter Müller
Age-Related Alterations in DTI Metrics in the Human Brain—Consequences for Age Correction
Frontiers in Aging Neuroscience
diffusion tensor imaging
age dependence
magnetic resonance imaging
fractional anisotropy
diffusivity
author_facet Anna Behler
Jan Kassubek
Hans-Peter Müller
author_sort Anna Behler
title Age-Related Alterations in DTI Metrics in the Human Brain—Consequences for Age Correction
title_short Age-Related Alterations in DTI Metrics in the Human Brain—Consequences for Age Correction
title_full Age-Related Alterations in DTI Metrics in the Human Brain—Consequences for Age Correction
title_fullStr Age-Related Alterations in DTI Metrics in the Human Brain—Consequences for Age Correction
title_full_unstemmed Age-Related Alterations in DTI Metrics in the Human Brain—Consequences for Age Correction
title_sort age-related alterations in dti metrics in the human brain—consequences for age correction
publisher Frontiers Media S.A.
series Frontiers in Aging Neuroscience
issn 1663-4365
publishDate 2021-06-01
description Background: Over the life span, the diffusion metrics in brain MRI show different, partly nonlinear changes. These age-dependent changes also seem to exhibit regional differences with respect to the brain anatomy. The age correction of a study cohort's diffusion metrics might thus require consideration of age-related factors.Methods: Diffusion tensor imaging data sets were acquired from 219 healthy participants at ages between 19 and 81 years. Fractional anisotropy (FA), mean diffusivity (MD), and axial and radial diffusivity (AD and RD, respectively) maps were analyzed by a tract of interest-based fiber tracking approach. To describe diffusion metrics as a function of the participant age, linear splines were used to perform curve fitting in 21 specific tract systems covering different functional areas and diffusion directions.Results: In the majority of tracts, an interpolation with a change of alteration rate during adult life described the diffusion properties more accurately than a linear model. Consequently, the diffusion properties remained relatively stable until a decrease (of FA) or increase (of MD, AD, and RD) started at a region-specific time point, whereas a uniform change of diffusion properties was observed only in a few tracts. Single tracts, e.g., located in the cerebellum, remained nearly unaltered throughout the ages between 19 and 81 years.Conclusions: Age corrections of diffusion properties should not be applied to all white matter regions and all age spans in the same way. Therefore, we propose three different approaches for age correction based on fiber tracking techniques, i.e., no correction for areas that do not experience age-related changes and two variants of an age correction depending on the age range of the cohort and the tracts considered.
topic diffusion tensor imaging
age dependence
magnetic resonance imaging
fractional anisotropy
diffusivity
url https://www.frontiersin.org/articles/10.3389/fnagi.2021.682109/full
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AT jankassubek agerelatedalterationsindtimetricsinthehumanbrainconsequencesforagecorrection
AT hanspetermuller agerelatedalterationsindtimetricsinthehumanbrainconsequencesforagecorrection
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