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Lambert, Christian, Chowdhury, Rumana, Fitzgerald, Thomas H. B. 
ORCID: https://orcid.org/0000-0002-3855-1591, Fleming, Stephen M., Lutti, Antoine, Hutton, Chloe, Draganski, Bogdan, Frackowiak, Richard and Ashburner, John
(2013)
Characterizing aging in the human brainstem using quantitative multimodal MRI analysis.
Frontiers in Human Neuroscience, 7.
ISSN 1662-5161
Abstract
Aging is ubiquitous to the human condition. The MRI correlates of healthy aging have been extensively investigated using a range of modalities, including volumetric MRI, quantitative MRI (qMRI), and diffusion tensor imaging. Despite this, the reported brainstem related changes remain sparse. This is, in part, due to the technical and methodological limitations in quantitatively assessing and statistically analyzing this region. By utilizing a new method of brainstem segmentation, a large cohort of 100 healthy adults were assessed in this study for the effects of aging within the human brainstem in vivo. Using qMRI, tensor-based morphometry (TBM), and voxel-based quantification (VBQ), the volumetric and quantitative changes across healthy adults between 19 and 75 years were characterized. In addition to the increased R2* in substantia nigra corresponding to increasing iron deposition with age, several novel findings were reported in the current study. These include selective volumetric loss of the brachium conjunctivum, with a corresponding decrease in magnetization transfer and increase in proton density (PD), accounting for the previously described "midbrain shrinkage." Additionally, we found increases in R1 and PD in several pontine and medullary structures. We consider these changes in the context of well-characterized, functional age-related changes, and propose potential biophysical mechanisms. This study provides detailed quantitative analysis of the internal architecture of the brainstem and provides a baseline for further studies of neurodegenerative diseases that are characterized by early, pre-clinical involvement of the brainstem, such as Parkinson's and Alzheimer's diseases.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being |
| Faculty \ School: | Faculty of Social Sciences > School of Psychology |
| Depositing User: | Pure Connector |
| Date Deposited: | 14 Apr 2016 09:00 |
| Last Modified: | 07 Mar 2024 01:57 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/58233 |
| DOI: | 10.3389/fnhum.2013.00462 |
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