Glucose Metabolism echoes Long-Range Temporal Correlations in the Human Brain.

Intrinsic brain activity is characterized by pervasive long-range temporal correlations. While these scale-invariant dynamics are a fundamental hallmark of brain function, their implications for individual-level metabolic regulation remain poorly understood. Here, we address this gap by integrating resting-state functional Magnetic Resonance Imaging (fMRI) and dynamic [F]FDG Positron Emission Tomography (PET) data acquired from the same cohort of participants.

Aging and the Spectral Properties of Brain Hemodynamics.

Cerebral glucose metabolism (CMRGlc) systematically decreases with advancing age. We sought to identify correlates of decreased CMRGlc in the spectral properties of fMRI signals imaged in the task-free state. Lifespan resting-state fMRI data acquired in 455 healthy adults (ages 18-87 years) and cerebral metabolic data acquired in a separate cohort of 94 healthy adults (ages 25-45 years, 65-85 years) were analyzed.

Unveiling functional-metabolic synergy in the healthy brain: multivariate integration of dynamic [F]FDG-PET and resting-state fMRI.

Introduction: Despite accounting for only 2% of body weight, the human brain requires significant amounts of glucose, even at rest, underscoring the importance of functional-metabolic relationships. Previous studies revealed moderate associations between resting-state fMRI functional connectivity (FC) and local metabolism via [F]FDG-PET, yet much remains to be understood, particularly regarding their coupling between functional and metabolic networks.

Methods: To this end, we employed multivariate Partial Least Squares Correlation (PLSC) to investigate the functional-metabolic relationship at both nodal and network level.

The brain's "dark energy" puzzle : [F]FDG uptake, delivery and phosphorylation, and their coupling with resting-state brain activity.

The brain's resting-state energy consumption is expected to be driven by spontaneous activity. We previously used 50 resting-state fMRI (rs-fMRI) features to predict [F]FDG SUVR as a proxy of glucose metabolism. Here, we expanded on our effort by estimating [F]FDG kinetic parameters (irreversible uptake), (delivery), (phosphorylation) in a large healthy control group (n = 47).

Precision measurements of brain oxygen utilization with positron emission tomography.

Oxygen utilization is important for studies of brain metabolism, alongside other measurements such as for glucose metabolism. Oxygen and other measurements with [ O] tracers and PET, however, are significantly more challenging than measurements of [ F]fluorodeoxyglucose, the standard for probing tissue glucose metabolism in vivo, in part due to the much shorter radioactive half-life of [ O]. This work examines details of precision measurement of [ O] tracers and their kinetics.

EMATA: a toolbox for the automatic extraction and modeling of arterial inputs for tracer kinetic analysis in [F]FDG brain studies.

Purpose: PET imaging is a pivotal tool for biomarker research aimed at personalized medicine. Leveraging the quantitative nature of PET requires knowledge of plasma radiotracer concentration. Typically, the arterial input function (AIF) is obtained through arterial cannulation, an invasive and technically demanding procedure.

Aging and the Spectral Properties of Brain Hemodynamics.

Cerebral glucose metabolism (CMRGlc) systematically decreases with advancing age. We sought to identify correlates of decreased CMRGlc in the spectral properties of fMRI signals imaged in the task-free state. We analyzed lifespan resting-state fMRI data acquired in 455 healthy adults (ages 18-87 years) and cerebral metabolic data acquired in a separate cohort of 94 healthy adults (ages 25-45 years, 65-85 years).

Individual-level metabolic connectivity from dynamic [F]FDG PET reveals glioma-induced impairments in brain architecture and offers novel insights beyond the SUVR clinical standard.

Purpose: This study evaluates the potential of within-individual Metabolic Connectivity (wi-MC), from dynamic [F]FDG PET data, based on the Euclidean Similarity method. This approach leverages the biological information of the tracer's full temporal dynamics, enabling the direct extraction of individual metabolic connectomes. Specifically, the proposed framework, applied to glioma pathology, seeks to assess sensitivity to metabolic dysfunctions in the whole brain, while simultaneously providing further insights into the pathophysiological mechanisms regulating glioma progression.

The brain's "dark energy" puzzle : [F]FDG uptake, delivery and phosphorylation, and their coupling with resting-state brain activity.

The brain's resting-state energy consumption is expected to be mainly driven by spontaneous activity. In our previous work, we extracted a wide range of features from resting-state fMRI (rs-fMRI), and used them to predict [F]FDG PET SUVR as a proxy of glucose metabolism. Here, we expanded upon our previous effort by estimating [F]FDG kinetic parameters according to Sokoloff's model, i.

Multi-Tracer Studies of Brain Oxygen and Glucose Metabolism Using a Time-of-Flight Positron Emission Tomography - Computed Tomography Scanner.

The authors have developed a paradigm using positron emission tomography (PET) with multiple radiopharmaceutical tracers that combines measurements of cerebral metabolic rate of glucose (CMRGlc), cerebral metabolic rate of oxygen (CMRO2), cerebral blood flow (CBF), and cerebral blood volume (CBV), culminating in estimates of brain aerobic glycolysis (AG). These in vivo estimates of oxidative and non-oxidative glucose metabolism are pertinent to the study of the human brain in health and disease. The latest positron emission tomography-computed tomography (PET-CT) scanners provide time-of-flight (TOF) imaging and critical improvements in spatial resolution and reduction of artifacts.

The brain's "dark energy" puzzle: How strongly is glucose metabolism linked to resting-state brain activity?

Brain glucose metabolism, which can be investigated at the macroscale level with [F]FDG PET, displays significant regional variability for reasons that remain unclear. Some of the functional drivers behind this heterogeneity may be captured by resting-state functional magnetic resonance imaging (rs-fMRI). However, the full extent to which an fMRI-based description of the brain's spontaneous activity can describe local metabolism is unknown.

Accuracy of TrUE-Net in comparison to established white matter hyperintensity segmentation methods: An independent validation study.

White matter hyperintensities (WMH) are nearly ubiquitous in the aging brain, and their topography and overall burden are associated with cognitive decline. Given their numerosity, accurate methods to automatically segment WMH are needed. Recent developments, including the availability of challenge data sets and improved deep learning algorithms, have led to a new promising deep-learning based automated segmentation model called TrUE-Net, which has yet to undergo rigorous independent validation.

A new framework for metabolic connectivity mapping using bolus [F]FDG PET and kinetic modeling.

Metabolic connectivity (MC) has been previously proposed as the covariation of static [F]FDG PET images across participants, i.e., MC (ai-MC).

Brain aerobic glycolysis and resilience in Alzheimer disease.

The distribution of brain aerobic glycolysis (AG) in normal young adults correlates spatially with amyloid-beta (Aβ) deposition in individuals with symptomatic and preclinical Alzheimer disease (AD). Brain AG decreases with age, but the functional significance of this decrease with regard to the development of AD symptomatology is poorly understood. Using PET measurements of regional blood flow, oxygen consumption, and glucose utilization-from which we derive AG-we find that cognitive impairment is strongly associated with loss of the typical youthful pattern of AG.

Modeling venous plasma samples in [F] FDG PET studies: a nonlinear mixed-effects approach.

The gold-standard approach to quantifying dynamic PET images relies on using invasive measures of the arterial plasma tracer concentration. An attractive alternative is to employ an image-derived input function (IDIF), corrected for spillover effects and rescaled with venous plasma samples. However, venous samples are not always available for every participant.

Comparison of the Ekblom-Bak Submaximal Test to a Maximal Test in a Cohort of Healthy Younger and Older Adults in the United States.

Cardiorespiratory fitness (CRF) is routinely investigated in diverse populations, including in older adults of varying physical activity levels. Commonly performed maximal exercise testing protocols might be contraindicated and/or inadequate for older individuals who have physical or cognitive impairment. Moreover, early termination of an attempted maximal exercise test could result in underestimation of CRF in this population.

Spatiotemporal relationship between subthreshold amyloid accumulation and aerobic glycolysis in the human brain.

In Alzheimer's disease, brain amyloid deposition has a distinct topography that correlates with aerobic glycolysis (AG), that is, the use of glucose beyond that predicted by oxygen consumption. The causes for this relationship remain unclear but might provide crucialinsight into how amyloid deposition begins. Here we develop methods to study the earliest topography of amyloid deposition based on amyloid imaging and investigate its spatiotemporal evolution with respect to the topography of AG in adults.

Comparison of Pittsburgh compound B and florbetapir in cross-sectional and longitudinal studies.

Introduction: Quantitative measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B-based and florbetapir-based amyloid imaging in the same participants from two independent cohorts using a crossover design.

A systematic meta-analysis of oxygen-to-glucose and oxygen-to-carbohydrate ratios in the resting human brain.

Glucose is the predominant fuel supporting brain function. If the brain's entire glucose supply is consumed by oxidative phosphorylation, the molar ratio of oxygen to glucose consumption (OGI) is equal to 6. An OGI of less than 6 is evidence of non-oxidative glucose metabolism.

Utilizing the Centiloid scale in cross-sectional and longitudinal PiB PET studies.

Amyloid imaging is a valuable tool for research and diagnosis in dementing disorders. Successful use of this tool is limited by the lack of a common standard in the quantification of amyloid imaging data. The Centiloid approach was recently proposed to address this problem and in this work, we report our implementation of this approach and evaluate the impact of differences in underlying image analysis methodologies using both cross-sectional and longitudinal datasets.

Aerobic glycolysis and tau deposition in preclinical Alzheimer's disease.

Research of the human brain metabolism in vivo has largely focused on total glucose use (via fluorodeoxyglucose positron emission tomography) and, until recently, did not examine the use of glucose outside oxidative phosphorylation, which is known as aerobic glycolysis (AG). AG supports important functions including biosynthesis and neuroprotection but decreases dramatically with aging. This multitracer positron emission tomography study evaluated the relationship between AG, total glucose use (CMRGlc), oxygen metabolism (CMRO), tau, and amyloid deposition in 42 individuals, including those at preclinical and symptomatic stages of Alzheimer's disease.