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Comparative Study
. 2020 Aug 27;12(16):16195-16210.
doi: 10.18632/aging.103629. Epub 2020 Aug 27.

Cortical aging - new insights with multiparametric quantitative MRI

Affiliations
Comparative Study

Cortical aging - new insights with multiparametric quantitative MRI

Alexander Seiler et al. Aging (Albany NY). .

Abstract

Understanding the microstructural changes related to physiological aging of the cerebral cortex is pivotal to differentiate healthy aging from neurodegenerative processes. The aim of this study was to investigate the age-related global changes of cortical microstructure and regional patterns using multiparametric quantitative MRI (qMRI) in healthy subjects with a wide age range. 40 healthy participants (age range: 2nd to 8th decade) underwent high-resolution qMRI including T1, PD as well as T2, T2* and T2' mapping at 3 Tesla. Cortical reconstruction was performed with the FreeSurfer toolbox, followed by tests for correlations between qMRI parameters and age. Cortical T1 values were negatively correlated with age (p=0.007) and there was a widespread age-related decrease of cortical T1 involving the frontal and the parietotemporal cortex, while T2 was correlated positively with age, both in frontoparietal areas and globally (p=0.004). Cortical T2' values showed the most widespread associations across the cortex and strongest correlation with age (r= -0.724, p=0.0001). PD and T2* did not correlate with age. Multiparametric qMRI allows to characterize cortical aging, unveiling parameter-specific patterns. Quantitative T2' mapping seems to be a promising imaging biomarker of cortical age-related changes, suggesting that global cortical iron deposition is a prominent process in healthy aging.

Keywords: cortical aging; iron deposition; quantitative MRI; surface-based analysis; tissue microstructure.

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Conflict of interest statement

CONFLICTS OF INTEREST: The authors report no conflicts of interest relevant to this study. Dr H Steinmetz has received speaker’s honoraria from Bayer, Sanofi and Boehringer Ingelheim. Dr Elke Hattingen has received speaker’s honoraria from BRACCO.

Figures

Figure 1
Figure 1
Scatterplots illustrating the relationship between global cortical qMRI parameters/cortical thickness and age. (A) relationship between T1 and age; (B) relationship between PD and age; (CE) relationships of T2, T2* and T2' with age; (F) relationship between cortical thickness and age. ms: milliseconds; p.u.: percentage units; mm: millimeters.
Figure 2
Figure 2
Cortical clusters indicating a significant association between age and cortical quantitative T1 values. The scale bar displays the level of significance. Cold colors demonstrate a negative association with age in the respective regions. L: left; R: right; Lat.: lateral; Med.: medial.
Figure 3
Figure 3
Cortical clusters exhibiting a significant relationship between age and cortical quantitative T2 (A) and T2′ values (B). The scale bar displays the level of significance. Hot colors demonstrate a positive and cold colors a negative association with age in the respective regions. L: left; R: right; Lat.: lateral; Med.: medial.
Figure 4
Figure 4
Cortical clusters indicating a significant relationship between age and cortical thickness. The scale bar indicates the level of significance. Cold colors demonstrate a negative association with age in the respective regions. L: left; R: right; Lat.: lateral; Med.: medial.
Figure 5
Figure 5
Scatterplots illustrating the relationship between regional cortical qMRI parameters/cortical thickness and age in the cortical subregions (lobes). (A) relationship between T1 and age; (B) relationship between PD and age; (CE) relationships of T2, T2* and T2' with age; (F) relationship between cortical thickness and age. In each plot, the four different colors denote the respective cortical subregions. ms: milliseconds; p.u.: percentage units; mm: millimeters.

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