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Brain Microstructure Changes in Healthy Aging Revealed by Quantitative Multi-parametric MRI1Department of Neurology, School of Medicine, Emory University, Atlanta, GA, United States, 2Department of Radiology and Imaging Sciences, School of Medicine, Emory University, Atlanta, GA, United States, 3Joint Department of BioMedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States
Synopsis
This study aims to reveal the alterations of biologically relevant measurements in healthy aging using multi-parametric quantitative MRI. Multi-parametric quantitative MRI scans of the whole brain were performed in 20 healthy elderly and 21 young adults. Whole-brain voxel-wise analysis showed increased quantitative T1 value in the right hippocampus and right insula, and widespread increases in the subcortical and cortical area of R2*, suggesting microstructural alteration associated with healthy aging in these regions. Quantitative multi-parametric measurements might provide sensitive neuroimaging biomarkers for the microstructure changes during normal aging and related neurodegeneration diseases.
Introduction
Normal aging is associated with changes in various brain tissue properties. These include both macroscopic morphological alterations such as tissue loss and atrophy and microstructural changes like demyelination, iron deposition, which is closely related to the declines in neural and cognitive functions1,2. There is a large body of the studies that employ MR techniques to evaluate morphological changes in normal aging as well as in Alzheimer’s Disease (AD)1,3,4. Quantitative MR relaxometry however might be more sensitive to early changes associated with aging or AD before morphological changes such as hippocampal or cortical atrophy become apparent. For example, quantitative T1 measurement has been shown to be sensitive to tissue loss or increase, myelination and cellularity etc.5,6, whereas R2* is strongly related to local iron levels that are known to increase with aging in certain brain regions7,8. Here, we utilized a variable flip-angle9 multi-echo GRE protocol to perform quantitative T1 and R2* mappings and studied differences between a group of amyloid-beta negative healthy elderly and a group of young healthy adults.Materials & Methods
Participants: A cohort of 21young subjects (mean ± SD age: 25.70 ± 4.50; 8 males) and 20 cognitively normal elderly (mean ± SD age: 62.21 ± 13.21 years; 9 males) were included from the ongoing Emory Brain Image Project, a component of the Emory Healthy Brain Study.
MRI acquisition: All scans were performed on a Siemens Magnetom Prisma 3T scanner with a 32-channel phased-array head coil. A variable flip-angle multi-echo 3D Spoiled Gradient Echo (ME-GRE) protocol was acquired with following parameters: voxel size = 0.72 × 0.72 × 1.44 mm3, TR = 37 ms, two flip angles: 15° and 40°, each flip-angle with 5 echoes, TE = 6.61, 12.85, 19.09, 25.33, 31.57 ms. An additional low resolution 2D fast Double-Angle EPI sequence were acquired to calculate the B1 transmit field with following parameters: two flip angle 30° and 60°, TR=10000 ms, TE=23 ms, voxel size 3.5 × 3.5 × 4.2 mm3.
Data analysis: First, B1 transmit inhomogeneous maps were calculated from the 2D double flip-angle EPI scan and quantitative T1 values were calculated by using the variable-flip angles T1 mapping method from the double-flip angle ME-GRE scans according to DESPOT methods9 and averaged across the 5 echoes (Figure.1). The R2* values were calculated by fitting a monoexponential function to the magnitude signals of the 5 echo from the ME-GRE. Then quantitative T1 and R2* volumes were spatially normalized to the MNI space using the nonlinear registration of Advanced Normalization Tools10 followed by voxel-wised analysis to evaluate brain regions with significantly different T1 or R2* values between the young and elderly groups (Figure.1).
Statistical analysis: For the voxel-wise analysis, permutation tests (N = 10000) using the randomise tools of FSL were performed with Threshold-Free Cluster Enhancement (TFCE) to correct for the multiple comparisons. A corrected p-value of <0.05 was considered statistically significant.
Results
Figure 2 shows quantitative T1 and R2* maps from a young and an elderly adult subjects. The gray matter showed higher T1 values compared to the white matter as expected, and the subcortical and white matter regions show higher R2* value compared to the grey matter. Voxel-based analysis showed significantly increased quantitative T1 value in the elderly group compared to the young group in the right hippocampus, the right parahippocampus gyrus and the right insula areas (Figure 3.A). Voxel-based analysis of R2* showed a more widespread increase in the elder group compared to the young group (Figure 3.B). Most notably, we found large areas of increased R2* in the basal ganglia regions including bilateral globus pallidum, bilateral putamen and bilateral caudate. Additionally, we also found significantly increased R2* in cortical areas such as the posterior cingulate and white matter regions.Discussion & Conclusion
In this study, we used a variable flip angle ME-GRE sequence to perform the quantitative T1 and R2* mapping in a group of healthy elderly and demonstrated a widespread difference in the microstructure of the human brain. Quantitative T1 value is increased in the right hippocampus, the right para-hippocampus gyrus which is closely related to the memory function11, and the right insula which is part of the salience network that has been found to be affected in MCI12. R2* were significantly increased in most of the basal ganglia regions, suggesting remarked iron increases in these regions. The quantitative MRI offers a promising opportunity for simultaneously investigating various tissue properties and could be potential imaging biomarkers for the microstructure changes during normal aging and related neurodegeneration diseases.Acknowledgements
No acknowledgement found.References
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