Synopsis

Keywords: Oxygenation, Aging

Oxygen Extraction Fraction (OEF) is a valuable indicator of brain physiology influenced by cognitive impairment and vascular pathology in older adults. Our objective is to explore age-related OEF change for cognitively normal (CN) and Mild-Cognitive-Impairment (MCI) subjects. In this study, 56 elderly participants were recruited. Individuals with MCI resulted in higher OEF compared to CN participants, especially in the occipital lobe (p=0.007). In parietal lobe, we observed an inverse correlation between OEF and age (p=0.026) in CN and positive association between OEF and executive function (p=0.023) in MCI. The results showed an effect of aging and cognitive impairment on OEF

INTRODUCTION

Oxygen extraction fraction (OEF) is an important physiological biomarker for brain hemodynamic impairment, especially for Alzheimer’s Disease (AD) and vascular cognitive impairment, and dementia (VCID)^1,2. Previous studies have suggested that OEF is affected by AD and VCID^1,3. OEF is decreased in AD-related impairment, while OEF is elevated with higher vascular risk patients. However, changes in OEF between cognitively normal (CN) and Mild Cognitive Impairment (MCI) with vascular risk in older adults have not been investigated. Therefore, in this study, we quantify OEF in the elderly cohort using non-invasive Asymmetric Spin Echo (ASE) MRI scans and quantitative BOLD (qBOLD) modeling. We hypothesized that OEF would be pathologically elevated for MCI compared to CN. Additionally, we also hypothesized that CN group had a stronger association with age than MCI with decreased OEF.

METHODS

Participants:
A total of 56 participants (75.4±7.0yrs, 37F), including 46 CN individuals (75.2±7.3yrs, 29F) and 10 MCI patients (76.0±6.1yrs, 7F), were recruited from UC Davis Alzheimer’s Disease Research Center cohort.

MRI Acquisitions:
All MRI acquisitions were acquired on a 3T scanner (Siemens Tim Trio) with a 32-channel head coil. The MR protocols included a Gradient Echo Slice Excitation Profile Imaging Asymmetric Spin Echo (GASE)⁴ scan and a T1-weighted MPRAGE. The imaging parameters for GASE included TR/TE, 2800/66ms; 96x96 matrix, 20 slabs; 2.3x2.3.x1.3mm³ resolution; FOV, 224mm with 13 values of the spin echo displacement time, τ, from 0 to 52ms in the step of 4ms with spin echo scan at τ=0. Each slab was constructed by averaging four 1.25mm slices to correct for macroscopic field gradient.

Image processing:
T1-weighted images were processed to create regions of interest (ROI), including gray matter (GM) and white matter (WM), using FSL FAST⁵. GASE data from each participant were preprocessed and quantified OEF using a two-compartment qBOLD model⁶ with Variational Bayesian framework^7–9 that fit data for a whole range of τ. Deoxygenated blood volume (DBV) and transverse relaxation rate (R₂^’) were estimated directly from the model and then used to quantify OEF with known constant:
$$OEF = \frac{3\times R_2^{'}}{DBV\times \gamma \times 4 \times \pi \times \triangle \chi_{0} \times Hct \times B_{0}}$$
where γ is the proton gyromagnetic ratio, Δχ₀ is the susceptibility difference between fully oxygenated and deoxygenated red blood cells (0.264ppm), Hct is the hematocrit (0.40), and B₀ is the field strength. All parameter maps were then registered to Montreal Neurological Institute (MNI) template space to create group-level average maps.

Statistical analysis:
Average OEF values were calculated for each ROI (GM, WM, frontal, parietal, occipital, and temporal lobes) and were compared between CN and MCI groups in each region using pairwise t-tests with Bonferroni correction. The correlations between OEF and age, and OEF and executive scores from the Spanish and English Neuropsychological Assessment Scales (SENAS)¹⁰ for each ROI were assessed using a linear mixed effects model in MATLAB that accounted for subject clustering.

RESULTS

Compared to CN, reduced DBV and increased OEF were observed on the group average level (Figure 1). The changes in OEF between CN and MCI groups for each region were plotted in Figure 2 and Table 1. We observed increased OEF in MCI groups compared to CN in all regions, especially significant in the occipital lobe (p=0.007). The correlations between OEF and age in selected regions were plotted in Figure 3, indicating that OEF was inversely correlated with age in the parietal lobe for CN group (p=0.026). In contrast, there was a positive trend between OEF and age for MCI subjects across all regions. With the mixed linear effect model, the correlation between OEF and the executive score (Figure 4) indicates that OEF was inversely correlated with the executive score in occipital lobe for CN group (p=0.052); however, there is an opposite trend in parietal lobe for MCI group (p=0.023).

DISCUSSION

Negative correlations between age and OEF in the CN older adults (Figure 3) are consistent with the results from previous PET and MRI studies^3,11. The lack of a significant association of age with OEF in the MCI group may suggest that age effects are surpassed by disease-related effects on brain oxygen metabolism from amyloid-beta (Aβ)-induced neuronal toxicity in mitochondrial dysfunction¹². However, our study has a limited number of MCI patients. Higher OEF in MCI than CN may reflect a compensatory increase in brain metabolism reported on PET in MCI with decreased blood flow^13–15, increased white matter hyperintensities, or vascular injury. Additionally, the positive correlation between OEF and executive score in MCI (Figure 4) may indicate brain dysfunction associated with lower executive function. In future analysis, white matter hyperintensities and vascular risk factors should be considered as separate pathologies.

CONCLUSION

In conclusion, this study showed an increase in OEF for patients with MCI, and older age was associated with decreased OEF in CN individuals. Higher brain OEF in MCI individuals may reflect changes in oxygen metabolism because of underlying pathology, including vascular injury. Both age and executive function have associations with brain oxygen extraction that are differently affected by normal aging and MCI.

Acknowledgements

This study was supported by NIH R00-NS102884 and UC Davis Alzheimer’s Disease Research Center.

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