Cerebral Metabolic Rate For Glucose Research Articles

Deficits in brain glucose transport among younger adults with obesity.

Obesity is associated with alterations in eating behavior and neurocognitive function. In this study, we investigate the effect of obesity on brain energy utilization, including brain glucose transport and metabolism. A total of 11 lean participants and 7 young healthy participants with obesity (mean age, 27 years) underwent magnetic resonance spectroscopy scanning coupled with a hyperglycemic clamp (target, ~180 mg/dL) using [1-13C] glucose to measure brain glucose uptake and metabolism, as well as peripheral markers of insulin resistance. Individuals with obesity demonstrated an ~20% lower ratio of brain glucose uptake to cerebral glucose metabolic rate (Tmax/CMRglucose) than lean participants (2.12 ± 0.51 vs. 2.67 ± 0.51; p = 0.04). The cerebral tricarboxylic acid cycle flux (VTCA) was similar between the two groups (p = 0.64). There was a negative correlation between total nonesterified fatty acids and Tmax/CMRglucose (r = -0.477; p = 0.045). We conclude that CMRglucose is unlikely to differ between groups due to similar VTCA, and, therefore, the glucose transport Tmax is lower in individuals with obesity. These human findings suggest that obesity is associated with reduced cerebral glucose transport capacity even at a young age and in the absence of other cardiometabolic comorbidities, which may have implications for long-term brain function and health.

Non-invasive assessment of stimulation-specific changes in cerebral glucose metabolism with functional PET.

Functional positron emission tomography (fPET) with [18F]FDG allows quantification of stimulation-induced changes in glucose metabolism independent of neurovascular coupling. However, the gold standard for quantification requires invasive arterial blood sampling, limiting its widespread use. Here, we introduce a novel fPET method without the need for an input function. We validated the approach using two datasets (DS). For DS1, 52 volunteers (23.2 ± 3.3years, 24 females) performed Tetris® during a [18F]FDG fPET scan (bolus + constant infusion). For DS2, 18 participants (24.2 ± 4.3years, 8 females) performed an eyes-open/finger tapping task (constant infusion). Task-specific changes in metabolism were assessed with the general linear model (GLM) and cerebral metabolic rate of glucose (CMRGlu) was quantified with the Patlak plot as reference. We then estimated simplified outcome parameters, including GLM beta values and percent signal change (%SC), and compared them, region and whole-brain-wise. We observed higher agreement with the reference for DS1 than DS2. Both DS resulted in strong correlations between regional task-specific beta estimates and CMRGlu (r = 0.763…0.912). %SC of beta values exhibited strong agreement with %SC of CMRGlu (r = 0.909…0.999). Average activation maps showed a high spatial similarity between CMRGlu and beta estimates (Dice = 0.870…0.979) as well as %SC (Dice = 0.932…0.997), respectively. The non-invasive method reliably estimates task-specific changes in glucose metabolism without blood sampling. This streamlines fPET, albeit with the trade-off of being unable to quantify baseline metabolism. The simplification enhances its applicability in research and clinical settings.

Simultaneous estimation of a model-derived input function for quantifying cerebral glucose metabolism with [18F]FDG PET

BackgroundQuantification of the cerebral metabolic rate of glucose (CMRGlu) by dynamic [18F]FDG PET requires invasive arterial sampling. Alternatives to using an arterial input function (AIF) include the simultaneous estimation (SIME) approach, which models the image-derived input function (IDIF) by a series of exponentials with coefficients obtained by fitting time activity curves (TACs) from multiple volumes-of-interest. A limitation of SIME is the assumption that the input function can be modelled accurately by a series of exponentials. Alternatively, we propose a SIME approach based on the two-tissue compartment model to extract a high signal-to-noise ratio (SNR) model-derived input function (MDIF) from the whole-brain TAC. The purpose of this study is to present the MDIF approach and its implementation in the analysis of animal and human data.MethodsSimulations were performed to assess the accuracy of the MDIF approach. Animal experiments were conducted to compare derived MDIFs to measured AIFs (n = 5). Using dynamic [18F]FDG PET data from neurologically healthy volunteers (n = 18), the MDIF method was compared to the original SIME-IDIF. Lastly, the feasibility of extracting parametric images was investigated by implementing a variational Bayesian parameter estimation approach.ResultsSimulations demonstrated that the MDIF can be accurately extracted from a whole-brain TAC. Good agreement between MDIFs and measured AIFs was found in the animal experiments. Similarly, the MDIF-to-IDIF area-under-the-curve ratio from the human data was 1.02 ± 0.08, resulting in good agreement in grey matter CMRGlu: 24.5 ± 3.6 and 23.9 ± 3.2 mL/100 g/min for MDIF and IDIF, respectively. The MDIF method proved superior in characterizing the first pass of [18F]FDG. Groupwise parametric images obtained with the MDIF showed the expected spatial patterns.ConclusionsA model-driven SIME method was proposed to derive high SNR input functions. Its potential was demonstrated by the good agreement between MDIFs and AIFs in animal experiments. In addition, CMRGlu estimates obtained in the human study agreed to literature values. The MDIF approach requires fewer fitting parameters than the original SIME method and has the advantage that it can model the shape of any input function. In turn, the high SNR of the MDIFs has the potential to facilitate the extraction of voxelwise parameters when combined with robust parameter estimation methods such as the variational Bayesian approach.

Dynamic Human Brain Imaging with a Portable PET Camera: Comparison to a Standard Scanner.

Portable, cost-effective PET cameras can radically expand the applicability of PET. We present here a within-participant comparison of fully quantified [18F]FDG dynamic scans in healthy volunteers using the standard Biograph mCT scanner and portable CerePET scanner. Methods: Each of 20 healthy volunteers underwent dynamic [18F]FDG imaging with both scanners (1-154 d apart) and concurrent arterial blood sampling. Tracer SUV, net influx rate (Ki), and the corresponding cerebral metabolic rate of glucose (CMRglu) were quantified at regional and voxel levels. Results: At the regional level, CerePET outcome measure estimates within participants robustly correlated with Biograph mCT estimates in the neocortex, wherein the average Pearson correlation coefficients across participants ± SD were 0.83 ± 0.07 (SUV) and 0.85 ± 0.08 (Ki and CMRglu). There was also strong agreement between CerePET and Biograph mCT estimates, wherein the average regression slopes across participants were 0.84 ± 0.17 (SUV), 0.83 ± 0.17 (Ki), and 0.85 ± 0.18 (CMRglu). There was similar bias across participants but higher correlation and less variability in subcortical regions than in cortical regions. Pearson correlation coefficients for subcortical regions equaled 0.97 ± 0.02 (SUV) and 0.97 ± 0.03 (Ki and CMRglu), and average regression slopes equaled 0.79 ± 0.14 (SUV), 0.83 ± 0.11 (Ki), and 0.86 ± 0.11 (CMRglu). In voxelwise assessment, CerePET and Biograph mCT estimates across outcome measures were significantly different only in a cluster of left frontal white matter. Conclusion: Our results indicate robust correlation and agreement between semi- and fully quantitative brain glucose metabolism measurements from portable CerePET and standard Biograph mCT scanners. The results obtained with a portable PET scanner in this comparison in humans require follow-up but lend confidence to the feasibility of more flexible and portable brain imaging with PET.

Functional FDG-PET: Measurement of Task Related Neural Activity in Humans-A Compartment Model Approach and Comparison to fMRI.

Neuroimaging holds an essential position in global healthcare, as brain-related disorders are a substantial and growing burden. Non-degenerative disorders such as stress, depression and anxiety share common function related traits of diffuse and fluctuating changes, such as change in brain-based functions of mood, behavior and cognitive abilities, where underlying physiological mechanism remain unresolved. In this study we developed a novel application for studying intra-subject task-activated brain function by the quantitative physiological measurement of the change in glucose metabolism in a single scan setup. Data were acquired on a PET/MR-scanner. We implemented a functional [18F]-FDG PET-scan with double boli-tracer administration and finger-tapping activation, as proof-of-concept, in five healthy participants. The [18F]-FDG data were analyzed using a two-tissue compartment double boli kinetic model with an image-derived input function. For stand-alone visual reference, blood oxygenation level dependent (BOLD) functional MRI (fMRI) was acquired in the same session and analyzed separately. We were able to measure the cerebral glucose metabolic rate during baseline as well as activation. Results showed increased glucose metabolic rate during activation by 36.3-87.9% mean 62.0%, locally in the peak seed region of M1 in the brain, on an intra-subject level, as well as very good spatial accuracy on group level, and localization compared to the BOLD fMRI result at subject and group level. Our novel method successfully determined the relative increase in the cerebral metabolic rate of glucose on a voxel level with good visual association to fMRI at the subject-level, holding promise for future individual clinical application. This approach will be easily adapted in future clinical perspectives and pharmacological interventions studies.

A convolutional neural network-based system to estimate the arterial plasma radioactivity curve in 18F-FDG dynamic brain PET study.

Quantitative images of metabolic activity can be derived through dynamic PET. However, the conventional approach necessitates invasive blood sampling to acquire the input function, thus limiting its noninvasive nature. The aim of this study was to devise a system based on convolutional neural network (CNN) capable of estimating the time-radioactivity curve of arterial plasma and accurately quantify the cerebral metabolic rate of glucose (CMRGlc) directly from PET data, thereby eliminating the requirement for invasive sampling. This retrospective investigation analyzed 29 patients with neurological disorders who underwent comprehensive whole-body 18F-FDG-PET/CT examinations. Each patient received an intravenous infusion of 185 MBq of 18F-FDG, followed by dynamic PET data acquisition and arterial blood sampling. A CNN architecture was developed to accurately estimate the time-radioactivity curve of arterial plasma. The CNN estimated the time-radioactivity curve using the leave-one-out technique. In all cases, there was at least one frame with a prediction error within 10% in at least one frame. Furthermore, the correlation coefficient between CMRGlc obtained from the sampled blood and CNN yielded a highly significant value of 0.99. The time-radioactivity curve of arterial plasma and CMRGlc was determined from 18F-FDG dynamic brain PET data using a CNN. The utilization of CNN has facilitated noninvasive measurements of input functions from dynamic PET data. This method can be applied to various forms of quantitative analysis of dynamic medical image data.

P.001 Application of low-intensity transcranial focused unltrasound to the hippocampus in Alzheimer’s Disease

Background: The purpose of this study was to evaluate the safety and efficacy of low-intensity tFUS under the threshold for BBB disruption in patients with AD. In addition, we assessed changes in the regional cerebral metabolic rate of glucose (rCMRglu) using F-18 fluoro-2-deoxyglucose positron emission tomography (FDG-PET) and cognitive function after tFUS. Methods: Eight AD patients were recruited. We applied low-intensity tFUS to the right hippocampus for 3 minutes using an image-guided tFUS system. For multi-modal neuroimaging guidance, MRI and CT data were spatially co-registered using the maximization of normalized mutual information. The subjectspecific coordinates of the hippocampus in the right hemisphere were identified as the tFUS target location. Results: Radiological evidence of contrast enhancement associated with BBB opening was not found in neither the visual inspection nor the ICA of the DCE-MRI data. No adverse events were observed during the hospitalization and follow-up outpatient visits for 5 to 24 months. The immediate recall and recognition memory on the SVLT were significantly improved after the sonication. The PET analysis showed the increased level of rCMRglu in the right hippocampus. Conclusions: Application of low-intensity tFUS to the hippocampus with MB did not open blood brain barrier but increased hippocampal glucose metabolism and memory function.

A longitudinal 18F‐FDG PET study in asymptomatic stage of genetic Creutzfeldt–Jakob disease

AbstractBackgroundPathogenic prion protein may start to deposit in some brain regions and cause functional alterations in the asymptomatic stages in Creutzfeldt–Jakob disease patients. However, the disease trajectory of Creutzfeldt–Jakob disease in the asymptomatic stage and when and where the degenerative process begins are still not clear.MethodsAt baseline, we enrolled five asymptomatic mutation carriers, six affected genetic Creutzfeldt–Jakob diseasepatients, and 23 healthy controls from whom 18F fluorodeoxyglucose‐positron emission tomography, clinical, and neuropsychological measures were acquired. Only five asymptomatic mutation carriers had completed longitudinal follow‐up. We set three‐time points to identify the changing trajectory in asymptomatic carriers group including baseline, 2‐year and 4‐year follow‐up.ResultsAt baseline, the cerebral glucose metabolic rate, measured as the standardized uptake value rate ratio, clinical and neuropsychological scales in all 5 asymptomatic cases were normal. In the 4‐years follow‐up, hypometabolic brain regions in asymptomatic genetic Creutzfeldt–Jakob disease group were found in the insula, frontal, parietal, and temporal lobes (false discovery rate corrected p<0.01). The standardized uptake value rate ratio changing trajectories of all asymptomatic cases were within the range between the healthy controls and affected patients. Notably, the metabolism values of one asymptomatic individual whose baseline age was older than the expected age of onset showed a rapid decline and approached the mean value of genetic Creutzfeldt–Jakob disease condition at the last follow‐up.ConclusionOur study illustrates that neurodegenerative process associated with genetic Creutzfeldt–Jakob disease may involve the insula, frontal, temporal, and parietal lobes before clinical presentation of the disease, and the decline will accelerate when close to the expected age of onset. Although there are no effective means to cure this fatal disease, the time interval before clinical disease onset may aid important trials or therapies intended to slow or halt the disease process.

Comparison of cardiac image-derived input functions for quantitative whole body [18F]FDG imaging with arterial blood sampling.

Introduction: Dynamic positron emission tomography (PET) and the application of kinetic models can provide important quantitative information based on its temporal information. This however requires arterial blood sampling, which can be challenging to acquire. Nowadays, state-of-the-art PET/CT systems offer fully automated, whole-body (WB) kinetic modelling protocols using image-derived input functions (IDIF) to replace arterial blood sampling. Here, we compared the validity of an automatic WB kinetic model protocol to the reference standard arterial input function (AIF) for both clinical and research settings. Methods: Sixteen healthy participants underwent dynamic WB [18F]FDG scans using a continuous bed motion PET/CT system with simultaneous arterial blood sampling. Multiple processing pipelines that included automatic and manually generated IDIFs derived from the aorta and left ventricle, with and without motion correction were compared to the AIF. Subsequently generated quantitative images of glucose metabolism were compared to evaluate performance of the different input functions. Results: We observed moderate to high correlations between IDIFs and the AIF regarding area under the curve (r = 0.49-0.89) as well as for the cerebral metabolic rate of glucose (CMRGlu) (r = 0.68-0.95). Manual placing of IDIFs and motion correction further improved their similarity to the AIF. Discussion: In general, the automatic vendor protocol is a feasible approach for the quantification of CMRGlu for both, clinical and research settings where expertise or time is not available. However, we advise on a rigorous inspection of the placement of the volume of interest, the resulting IDIF, and the quantitative values to ensure valid interpretations. In protocols requiring longer scan times or where cohorts are prone to involuntary movement, manual IDIF definition with additional motion correction is recommended, as this has greater accuracy and reliability.

The effects of acute Methylene Blue administration on cerebral blood flow and metabolism in humans and rats.

Methylene Blue (MB) is a brain-penetrating drug with putative neuroprotective, antioxidant and metabolic enhancing effects. In vitro studies suggest that MB enhances mitochondrial complexes activity. However, no study has directly assessed the metabolic effects of MB in the human brain. We used in vivo neuroimaging to measure the effect of MB on cerebral blood flow (CBF) and brain metabolism in humans and in rats. Two doses of MB (0.5 and 1 mg/kg in humans; 2 and 4 mg/kg in rats; iv) induced reductions in global cerebral blood flow (CBF) in humans (F(1.74, 12.17)5.82, p = 0.02) and rats (F(1,5)26.04, p = 0.0038). Human cerebral metabolic rate of oxygen (CMRO2) was also significantly reduced (F(1.26, 8.84)8.01, p = 0.016), as was the rat cerebral metabolic rate of glucose (CMRglu) (t = 2.6(16) p = 0.018). This was contrary to our hypothesis that MB will increase CBF and energy metrics. Nevertheless, our results were reproducible across species and dose dependent. One possible explanation is that the concentrations used, although clinically relevant, reflect MB's hormetic effects, i.e., higher concentrations produce inhibitory rather than augmentation effects on metabolism. Additionally, here we used healthy volunteers and healthy rats with normal cerebral metabolism where MB's ability to enhance cerebral metabolism might be limited.

Cerebral Metabolic Rate of Glucose and Cognitive Tests in Long COVID Patients.

Common long-term sequelae after COVID-19 include fatigue and cognitive impairment. Although symptoms interfere with daily living, the underlying pathology is largely unknown. Previous studies report relative hypometabolism in frontal, limbic and cerebellar regions suggesting focal brain involvement. We aimed to determine whether absolute hypometabolism was present and correlated to same day standardized neurocognitive testing. Fourteen patients included from a long COVID clinic had cognitive testing and quantitative dynamic [18F]FDG PET of the brain on the same day to correlate cognitive function to metabolic glucose rate. We found no hypometabolism in frontal, limbic and cerebellar regions in cognitively impaired relative to cognitive intact patients. In contrast, the cognitive impaired patients showed higher cerebellar metabolism (p = 0.03), which correlated with more severe deficits in working memory and executive function (p = 0.03). Hypermetabolism in the cerebellum may reflect inefficient brain processing and play a role in cognitive impairments after COVID-19.

Mirror writing and cortical hypometabolism in Parkinson's disease.

Mirror writing (MW) is the production of individual letters, words, or word strings in the reverse direction. Parkinson's disease (PD) is a progressive neurodegenerative disorder, and high MW rates have been reported in patients with PD. Thus, the present study sought to identify the factors that cause MW in patients with PD. We examined the frequency of MW in patients with PD and investigated the area of the brain where such frequency inversely correlates with reduced regional cerebral metabolic rates of glucose (rCMRglc). We also examined whether this area satisfied the motor and visual monitoring hypotheses of MW that have been presented in previous studies. Thirty-six subjects with idiopathic PD and 23 healthy controls were included in the study. We asked the participants to write down words, numerals, and sentences from left to right using their dominant and non-dominant hands. Patients with PD underwent an 18F-fluorodeoxyglucose positron emission tomography scan to measure the rCMRglc. Neither the patients with PD nor the healthy subjects exhibited MW in the use of the right hand. In the use of the left hand, MW occurred in 15 of the 36 patients with PD, but in none of the healthy controls. The right intraparietal sulcus was identified as the area where rCMRglc was inversely correlated with the number of left-right reversed characters. Previous functional imaging studies have suggested that the right superior parietal cortex and intraparietal sulcus play an important role in recognizing left-right reversed letters. Therefore, dysfunction in the intraparietal sulcus may hinder the recognition of left-right reversed characters, resulting in MW. Consequently, our findings in patients with PD are consistent with the visual-monitoring hypothesis of MW.

The PIONEER Study: A Multi‐center, Randomized, Double‐blind, Placebo‐controlled Phase 2 Trial of the Effects of T3D‐959 on Safety, Cognition, Function and Plasma Biomarkers in Mild to Moderate Alzheimer’s Disease Subjects: Study Update.

AbstractBackgroundT3D‐959 is a novel (non‐amyloid/non‐tau‐directed) new chemical entity aimed at improving dysfunctional brain glucose energy and lipid metabolism in Alzheimer’s disease (AD). Dysfunctional brain metabolism in AD results from increasing resistance to insulin. Insulin resistance contributes to amyloid plaque formation, tau tangle formation and inflammation. T3D‐959, a brain‐penetrant, small molecule dual nuclear receptor agonist, acts as an insulin sensitizer to overcome insulin resistance to restore and maintain metabolic homeostasis.MethodPIONEER is a randomized, double‐blind, placebo‐controlled, Phase 2 trial involving 256 mild to moderate AD patients (MMSE = 14‐26) dosed orally once‐a‐day for 24‐weeks in 4 parallel arms (T3D‐959 15mg, 30mg, 45mg and placebo QD in a 1:1:1:1 ratio). Co‐primary outcome measures include the ADAS‐cog11 cognition and global function ADCS‐CGIC measures. Secondary outcome measures include DSCT and plasma Aβ 42/40 ratio. Exploratory outcome measures include plasma NfL tau, ptau217 and ptau181, apathy as measured by the NPI, expressive language function as measured by CFT, physical activity as measured by RAPA, plasma metabolomic and proteomic biomarkers and change in absolute regional, and whole brain, cerebral metabolic rate for glucose (CMRgl) as assayed by FDG‐PET.ResultPIONEER commenced in March 2021. The study is two‐thirds enrolled and ongoing [See ClinicalTrials.gov identifier NCT04251182]. Blinded, grouped, summary cognitive and functional endpoint data, as well safety data will be presented and discussed.ConclusionPIONEER is designed to evaluate the efficacy and safety of multiple dose strengths of T3D‐959 in patients with mild to moderate severity AD. Topline results are expected in 2023.

Cortical diffusivity associates with early neuronal damage

AbstractBackgroundDiffusion weighted imaging can provide a marker a microstructural damage which cannot be detected by conventional structural MRI. Changes in cortical diffusivity may be a value marker of neuronal breakdown, which predates macrostructural damage. We aimed to evaluate the efficacy of cortical diffusivity in predicting the extent of metabolic changes in different stages of Alzheimer’s disease progression.Method90 participants diagnosed with mild to moderate Alzheimer’s disease were recruited at Imperial College London. A median split was conducted to categorise participants into ‘Early’ (MMSE ≥ 25, n = 42) and ‘Late’ stage of AD groups (MMSE < 25, n = 48) to reflect different stages of disease progression. All participants underwent [18F]fluorodeoxyglucose imaging with arterial input, t1‐weighted MRI images and diffusion weighted images were also acquired. Spectral analysis was conducted to calculate the cerebral metabolic rate of glucose (CMRglc). CMRglc and mean diffusivity maps were spatially normalised to MNI space and individualised grey matter object maps were created for all participants. Linear regression was conducted between CMRglc and mean diffusivity maps. Mean diffusivity and CMRglc values within the temporal lobe were extracted to confirm voxelwise results.ResultIn this cohort, voxel‐wise statistics revealed a significant relationship between cortical diffusivity and reduced CMRglc, particularly in our ‘early’ stage AD group. Most notable correlations were located within temporal lobe regions. Regional analysis revealed that increased temporal lobe mean diffusivity was strongly correlated with decreased CMRglc in ‘early’ AD participants (r=‐0.525, p<0.001, 95% CI: ‐0.263 to ‐0.715). We found evidence of a weaker correlation in the ‘late’ AD group between increased diffusivity and CMRglc reductions within the temporal lobe (r=‐0.322, p=0.026, 95% CI: ‐0.042 to ‐0.555).ConclusionCortical mean diffusivity is a valuable predictor of early neuronal damage measured by cerebral glucose metabolism in Alzheimer’s disease. This association was strongest in earlier stages of the disease trajectory, as such, we establish that cortical mean diffusivity as an early biomarker in Alzheimer’s disease which reflects early changes in tissue integrity and cell/organelle breakdown.

Differential impact of body mass index and leptin on baseline and longitudinal positron emission tomography measurements of the cerebral metabolic rate for glucose in amnestic mild cognitive impairment.

Several studies have suggested that greater adiposity in older adults is associated with a lower risk of Alzheimer's disease (AD) related cognitive decline, some investigators have postulated that this association may be due to the protective effects of the adipose tissue-derived hormone leptin. In this study we sought to demonstrate that higher body mass indices (BMIs) are associated with greater baseline FDG PET measurements of the regional cerebral metabolic rate for glucose (rCMRgl), a marker of local neuronal activity, slower rCMRgl declines in research participants with amnestic mild cognitive impairment (aMCI). We then sought to clarify the extent to which those relationships are attributable to cerebrospinal fluid (CSF) or plasma leptin concentrations. We used baseline PET images from 716 73 ± 8 years-old aMCI participants from the AD Neuroimaging Initiative (ADNI) of whom 453 had follow up images (≥6 months; mean follow up time 3.3 years). For the leptin analyses, we used baseline CSF samples from 81 of the participants and plasma samples from 212 of the participants. As predicted, higher baseline BMI was associated with greater baseline CMRgl measurements and slower declines within brain regions preferentially affected by AD. In contrast and independently of BMI, CSF, and plasma leptin concentrations were mainly related to less baseline CMRgl within mesocorticolimbic brain regions implicated in energy homeostasis. While higher BMIs are associated with greater baseline CMRgl and slower declines in persons with aMCI, these associations appear not to be primarily attributable to leptin concentrations.

Lower brain glucose metabolism in normal ageing is predominantly frontal and temporal: A systematic review and pooled effect size and activation likelihood estimates meta-analyses.

This review provides a qualitative and quantitative analysis of cerebral glucose metabolism in ageing. We undertook a systematic literature review followed by pooled effect size and activation likelihood estimates (ALE) meta-analyses. Studies were retrieved from PubMed following the PRISMA guidelines. After reviewing 635 records, 21 studies with 22 independent samples (n= 911 participants) were included in the pooled effect size analyses. Eight studies with eleven separate samples (n= 713 participants) were included in the ALE analyses. Pooled effect sizes showed significantly lower cerebral metabolic rates of glucose for older versus younger adults for the whole brain, as well as for the frontal, temporal, parietal, and occipital lobes. Among the sub-cortical structures, the caudate showed a lower metabolic rate among older adults. In sub-group analyses controlling for changes in brain volume or partial volume effects, the lower glucose metabolism among older adults in the frontal lobe remained significant, whereas confidence intervals crossed zero for the other lobes and structures. The ALE identified nine clusters of lower glucose metabolism among older adults, ranging from 200 to 2640 mm3 . The two largest clusters were in the left and right inferior frontal and superior temporal gyri and the insula. Clusters were also found in the inferior temporal junction, the anterior cingulate and caudate. Taken together, the results are consistent with research showing less efficient glucose metabolism in the ageing brain. The findings are discussed in the context of theories of cognitive ageing and are compared to those found in neurodegenerative disease.

Cerebral Glucose Metabolism in Patients with Chronic Disorders of Consciousness.

To measure regional cerebral metabolic rate of glucose (CMRGlu) in patients with chronic disorders of consciousness (DOCs) using 18F-fluorodeoxyglucose positron emission tomography (FDG-PET). This retrospective cohort study examined 50 patients (mean age: 40.9 ± 20.1 years) with traumatic brain injury (TBI)-induced chronic DOCs [minimally conscious state (MCS)+, n = 20; MCS-, n = 15 and vegetative state (VS), n = 15]. We measured FDG-PET-based CMRGlu values in 12 regions of both brain hemispheres and compared those among MCS+, MCS - and VS patients. In both hemispheres, the regional CMRGlu reduced with consciousness deterioration in 11 of 12 regions (91.7%). In seven right hemisphere regions, CMRGlu values were markedly higher in MCS+ patients than in MCS- patients. Furthermore, CMRGlu was suggestively higher in the left occipital region in MCS- patients than in VS patients. Functional preservation in the left occipital region in patients with chronic DOCs might reflect an awareness of external environments, whereas extensive functional preservation in the right cerebral hemisphere might reflect communication motivation.

Non-Invasive Glucose Metabolism Quantification Method Based on Unilateral ICA Image Derived Input Function by Hybrid PET/MR in Ischemic Cerebrovascular Disease.

The non-invasive quantification of the cerebral metabolic rate for glucose (CMRGlc) and the characterization of cerebral metabolism in the cerebrovascular territories are helpful in understanding ischemic cerebrovascular disease (ICVD). Firstly, we investigated a non-invasive quantification approach based on an image-derived input function (IDIF) in ICVD. Second, we studied the metabolic changes in CMRGlc after surgical intervention. We evaluated the hypothesis that the IDIF method based on the unilateral internal carotid artery could address challenges in ICVD quantification. The CMRGlc and standardized uptake value ratio (SUVR) were used to measure glucose metabolism activity. Healthy controls showed no significant differences in CMRGlc values between bilateral and unilateral IDIF measurements (intraclass correlation coefficient [ICC]: 0.91-0.98). Patients with ICVD showed significantly increased CMRGlc values after surgical intervention for all territories (percentage changes: 7.4%-22.5%). In contrast, SUVR showed minor differences between postoperative and preoperative patients, indicating that it was a poor biomarker for the diagnosis of ICVD. A significant association between CMRGlc and the National Institutes of Health Stroke Scale (NIHSS) scores was observed (r=-0.54). Our findings suggested that IDIF could be a valuable tool for CMRGlc quantification in patients with ICVD and may advance personalized precision interventions.

Effect of cognitive reserve on amnestic mild cognitive impairment due to Alzheimer's disease defined by fluorodeoxyglucose-positron emission tomography.

This study aimed to investigate the effect of cognitive reserve (CR) on the rate of cognitive decline and cerebral glucose metabolism in amnestic mild cognitive impairment (MCI) using the Study on Diagnosis of Early Alzheimer’s Disease-Japan (SEAD-J) dataset. The patients in SEAD-J underwent cognitive tests and fluorodeoxyglucose-positron emission tomography (FDG-PET). MCI to be studied was classified as amnestic MCI due to Alzheimer’s disease (AD) with neurodegeneration. A total of 57 patients were visually interpreted as having an AD pattern (P1 pattern, Silverman’s classification). The 57 individuals showing the P1 pattern were divided into a high-education group (years of school education ≥13, N = 18) and a low-education group (years of school education ≤12, N = 39). Voxel-based statistical parametric mapping revealed more severe hypometabolism in the high-education group than in the low-education group. Glucose metabolism in the hippocampus and temporoparietal area was inversely associated with the years of school education in the high- and low-education groups (N = 57). General linear mixed model analyses demonstrated that cognitive decline was more rapid in the high-education group during 3-year follow-up. These results suggest that the cerebral glucose metabolism is lower and cognitive function declines faster in patients with high CR of amnestic MCI due to AD defined by FDG-PET.

Modelling the Effects of Medium-Chain Triglycerides on Cerebral Ketone Body Metabolism

Alzheimer’s Disease (AD) is a neurodegenerative disorder that causes drastic structural brain atrophy and affects multiple brain functions. Cerebral glucose hypometabolism, associated with senile plaque density formation, is a pre-symptomatic feature of AD and significantly contributes to AD’s future development and progression. As cerebral glucose metabolism gradually slows down due to advanced aging, a healthy adult brain experiences an 8% decrease in cerebral glucose metabolic rate (CGMR) compared to a decline of 20%–40% CGMR in AD patients. To bridge the increasing brain energy gap caused by glucose hypometabolism, ketone bodies (KBs) are used as a supplementary source of energy as cerebral KB metabolism remains unaffected in AD patients. Ketogenic interventions such as Medium-Chain Triglyceride (MCT)-induced treatment can help augment the brain’s energy source availability and might delay further cognitive decline. With this, we constructed a mathematical model on cerebral glucose and KB metabolism to illustrate the drastic effects of glucose hypometabolism on healthy aging individuals, Mild Cognitive Impairment (MCI) subjects, and AD patients. Through the generated simulations, we have shown that KB concentration levels rise during prolonged starvation, and in consideration of glucose hypometabolism, MCT-induced intervention increases the concentration levels of acetyl-CoA (AC) in MCI/AD patients. Furthermore, MCT-induced supplement helps increase the AC concentration levels in healthy adults under normal conditions.