Dataset Information

Longitudinal changes in brain oxygen extraction fraction (OEF) in older adults: Relationship to markers of vascular and Alzheimer's pathology.

ABSTRACT:

Introduction

Oxygen extraction fraction (OEF) reflects the balance between oxygen delivery and consumption. We longitudinally measured OEF in older adults to examine the relationship with markers of Alzheimer's disease (AD) and vascular pathology.

Methods

One hundred thirty-seven participants were studied at two time-points at an interval of 2.16 years. OEF was measured using T₂ -relaxation-under-spin-tagging (TRUST) magnetic resonance imaging (MRI). The association between OEF and vascular risks, white matter hyperintensities (WMH), cerebrospinal fluid (CSF) measures of amyloid beta (Aβ), total tau (t-tau), and phosphorylated tau 181 (p-tau181) was examined.

Results

OEF increased from baseline to follow-up. The increase in OEF was more prominent in individuals with high vascular risks compared to those with low vascular risks, and was associated with progression of vascular risks and the growth in WMH volume. OEF change was not related to CSF markers of AD pathology or their progression.

Discussion

Longitudinal OEF change in older adults is primarily related to vascular pathology.

SUBMITTER: Lin Z

PROVIDER: S-EPMC10838398 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Publications

Longitudinal changes in brain oxygen extraction fraction (OEF) in older adults: Relationship to markers of vascular and Alzheimer's pathology.

Lin Zixuan Z Lim Chantelle C Jiang Dengrong D Soldan Anja A Pettigrew Corinne C Oishi Kumiko K Zhu Yuxin Y Moghekar Abhay A Liu Peiying P Albert Marilyn M Lu Hanzhang H

Alzheimer's & dementia : the journal of the Alzheimer's Association 20220706 2

<h4>Introduction</h4>Oxygen extraction fraction (OEF) reflects the balance between oxygen delivery and consumption. We longitudinally measured OEF in older adults to examine the relationship with markers of Alzheimer's disease (AD) and vascular pathology.<h4>Methods</h4>One hundred thirty-seven participants were studied at two time-points at an interval of 2.16 years. OEF was measured using T<sub>2</sub> -relaxation-under-spin-tagging (TRUST) magnetic resonance imaging (MRI). The association bet ...[more]

PMID: 35791732

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Project description:Oxygen extraction fraction (OEF), the fraction of oxygen that tissue extracts from blood, is an essential biomarker used to directly assess tissue viability and function in neurologic disorders. In ischemic stroke, for example, increased OEF can indicate the presence of penumbra-tissue with low perfusion yet intact cellular integrity-making it a primary therapeutic target. However, practical OEF mapping methods are not currently available in clinical settings, owing to the impractical data acquisitions in positron emission tomography (PET) and the limitations of existing MRI techniques. Recently, a novel MRI-based OEF mapping technique, termed QQ, was proposed. It shows high potential for clinical use by utilizing a routine sequence and removing the need for impractical multiple gas inhalations. However, QQ relies on the assumptions of Gaussian noise in susceptibility and multi-echo gradient echo (mGRE) magnitude signals for OEF estimation. This assumption is unreliable in low signal-to-noise ratio (SNR) regions like disease-related lesions, risking inaccurate OEF estimation and potentially impacting clinical decisions. Addressing this, our study presents a novel multi-echo complex QQ (mcQQ) that models realistic Gaussian noise in mGRE complex signals. We implemented mcQQ using a deep learning framework (mcQQ-NET) and compared it with the existing QQ-NET in simulations, ischemic stroke patients, and healthy subjects, using identical training and testing datasets and schemes. In simulations, mcQQ-NET provided more accurate OEF than QQ-NET. In the subacute stroke patients, mcQQ-NET showed a lower average OEF ratio in lesions relative to unaffected contralateral normal tissue than QQ-NET. In the healthy subjects, mcQQ-NET provided uniform OEF maps, similar to QQ-NET, but without unrealistically high OEF outliers in areas of low SNR, such as SNR ≤ 15 (dB). Therefore, mcQQ-NET improves OEF accuracy by more accurately reflecting realistic Gaussian noise in complex mGRE signals. Its enhanced sensitivity to OEF abnormalities, based on more realistic biophysics modeling, suggests that mcQQ-NET has potential for investigating tissue variability in neurologic disorders.

Project description:Magnetic resonance imaging (MRI) offers the possibility to non-invasively map the brain's metabolic oxygen consumption (CMRO2), which is essential for understanding and monitoring neural function in both health and disease. However, in depth study of oxygen metabolism with MRI has so far been hindered by the lack of robust methods. One MRI method of mapping CMRO2 is based on the simultaneous acquisition of cerebral blood flow (CBF) and blood oxygen level dependent (BOLD) weighted images during respiratory modulation of both oxygen and carbon dioxide. Although this dual-calibrated methodology has shown promise in the research setting, current analysis methods are unstable in the presence of noise and/or are computationally demanding. In this paper, we present a machine learning implementation for the multi-parametric assessment of dual-calibrated fMRI data. The proposed method aims to address the issues of stability, accuracy, and computational overhead, removing significant barriers to the investigation of oxygen metabolism with MRI. The method utilizes a time-frequency transformation of the acquired perfusion and BOLD-weighted data, from which appropriate feature vectors are selected for training of machine learning regressors. The implemented machine learning methods are chosen for their robustness to noise and their ability to map complex non-linear relationships (such as those that exist between BOLD signal weighting and blood oxygenation). An extremely randomized trees (ET) regressor is used to estimate resting blood flow and a multi-layer perceptron (MLP) is used to estimate CMRO2 and the oxygen extraction fraction (OEF). Synthetic data with additive noise are used to train the regressors, with data simulated to cover a wide range of physiologically plausible parameters. The performance of the implemented analysis method is compared to published methods both in simulation and with in-vivo data (n=30). The proposed method is demonstrated to significantly reduce computation time, error, and proportional bias in both CMRO2 and OEF estimates. The introduction of the proposed analysis pipeline has the potential to not only increase the detectability of metabolic difference between groups of subjects, but may also allow for single subject examinations within a clinical context.

Project description:BackgroundAlzheimer's disease and vascular cognitive impairment (VCI), as well as their concurrence, represent the most common types of cognitive dysfunction. Treatment strategies for these two conditions are quite different; however, there exists a considerable overlap in their clinical manifestations, and most biomarkers reveal similar abnormalities between these two conditions.PurposeTo evaluate the potential of cerebral oxygen extraction fraction (OEF) as a biomarker for differential diagnosis of Alzheimer's disease and VCI. We hypothesized that in Alzheimer's disease OEF will be reduced (decreased oxygen consumption due to decreased neural activity), while in vascular diseases OEF will be elevated (increased oxygen extraction due to abnormally decreased blood flow).Study typeProspective cross-sectional.PopulationSixty-five subjects aged 52-89 years, including 33 mild cognitive impairment (MCI), 7 dementia, and 25 cognitively normal subjects.Field strength/sequence3T T2 -relaxation-under-spin-tagging (TRUST) and fluid-attenuated inversion recovery imaging (FLAIR).AssessmentOEF, consensus diagnoses of cognitive impairment, vascular risk factors (such as hypertension, hypercholesterolemia, diabetes, smoking, and obesity), cognitive assessments, and cerebrospinal fluid concentration of amyloid and tau were assessed.Statistical testsMultiple linear regression analyses of OEF with diagnostic category (normal, MCI, or dementia), vascular risks, cognitive performance, amyloid and tau pathology.ResultsWhen evaluating the entire group, OEF was found to be lower with more severe cognitive impairment (β = -2.70 ± 1.15, T = -2.34, P = 0.02), but was higher with greater vascular risk factors (β = 1.36 ± 0.55, T = 2.48, P = 0.02). Further investigation of the subgroup of participants with low vascular risks (N = 44) revealed that lower OEF was associated with worse cognitive performance (β = 0.04 ± 0.01, T = 3.27, P = 0.002) and greater amyloid burden (β = 92.12 ± 41.23, T = 2.23, P = 0.03). Among cognitively impaired individuals (N = 40), higher OEF was associated with greater vascular risk factors (β = 2.19 ± 0.71, T = 3.08, P = 0.004).Data conclusionThese findings suggest that OEF is differentially affected by Alzheimer's disease and VCI pathology and may be useful in etiology-based diagnosis of cognitive impairment.Level of evidence1 TECHNICAL EFFICACY: Stage 3 J. MAGN. RESON. IMAGING 2020;52:1829-1837.

Project description:We analysed the importance of systemic and peripheral arteriovenous O2 difference ( a-v¯O2 difference and a-vf O2 difference, respectively) and O2 extraction fraction for maximal oxygen uptake ( V˙O2max ). Fick law of diffusion and the Piiper and Scheid model were applied to investigate whether diffusion versus perfusion limitations vary with V˙O2max . Articles (n = 17) publishing individual data (n = 154) on V˙O2max , maximal cardiac output ( Q˙max ; indicator-dilution or the Fick method), a-v¯O2 difference (catheters or the Fick equation) and systemic O2 extraction fraction were identified. For the peripheral responses, group-mean data (articles: n = 27; subjects: n = 234) on leg blood flow (LBF; thermodilution), a-vf O2 difference and O2 extraction fraction (arterial and femoral venous catheters) were obtained. Q˙max and two-LBF increased linearly by 4.9-6.0 L · min-1 per 1 L · min-1 increase in V˙O2max (R2 = .73 and R2 = .67, respectively; both P < .001). The a-v¯O2 difference increased from 118-168 mL · L-1 from a V˙O2max of 2-4.5 L · min-1 followed by a reduction (second-order polynomial: R2 = .27). After accounting for a hypoxemia-induced decrease in arterial O2 content with increasing V˙O2max (R2 = .17; P < .001), systemic O2 extraction fraction increased up to ~90% ( V˙O2max : 4.5 L · min-1 ) with no further change (exponential decay model: R2 = .42). Likewise, leg O2 extraction fraction increased with V˙O2max to approach a maximal value of ~90-95% (R2 = .83). Muscle O2 diffusing capacity and the equilibration index Y increased linearly with V˙O2max (R2 = .77 and R2 = .31, respectively; both P < .01), reflecting decreasing O2 diffusional limitations and accentuating O2 delivery limitations. In conclusion, although O2 delivery is the main limiting factor to V˙O2max , enhanced O2 extraction fraction (≥90%) contributes to the remarkably high V˙O2max in endurance-trained individuals.

Dataset Information

Longitudinal changes in brain oxygen extraction fraction (OEF) in older adults: Relationship to markers of vascular and Alzheimer's pathology.

Introduction

Methods

Results

Discussion

Publications

Longitudinal changes in brain oxygen extraction fraction (OEF) in older adults: Relationship to markers of vascular and Alzheimer's pathology.

Similar Datasets

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