Cerebral Metabolic Rate For Glucose Research Articles

Simultaneous assessment of cerebral glucose and oxygen metabolism and perfusion in rats using interleaved deuterium (2H) and oxygen-17 (17O) MRS.

Cerebral glucose and oxygen metabolism and blood perfusion play key roles in neuroenergetics and oxidative phosphorylation to produce adenosine triphosphate (ATP) energy molecules in supporting cellular activity and brain function. Their impairments have been linked to numerous brain disorders. This study aimed to develop an in vivo magnetic resonance spectroscopy (MRS) method capable of simultaneously assessing and quantifying the major cerebral metabolic rates of glucose (CMRGlc) and oxygen (CMRO2) consumption, lactate formation (CMRLac), and tricarboxylic acid (TCA) cycle (VTCA); cerebral blood flow (CBF); and oxygen extraction fraction (OEF) via a single dynamic MRS measurement using an interleaved deuterium (2H) and oxygen-17 (17O) MRS approach. We introduced a single-loop multifrequency radio-frequency (RF) surface coil that can be used to acquire proton (1H) magnetic resonance imaging (MRI) or interleaved low-γ X-nuclei 2H and 17O MRS. By combining this RF coil with a modified MRS pulse sequence, 17O-isotope-labeled oxygen gas inhalation, and intravenous 2H-isotope-labeled glucose administration, we demonstrate for the first time the feasibility of simultaneously and quantitatively measuring six important physiological parameters, CMRGlc, CMRO2, CMRLac, VTCA, CBF, and OEF, in rat brains at 16.4T. The interleaved 2H-17O MRS technique should be readily adapted to image and study cerebral energy metabolism and perfusion in healthy and diseased brains.

Quantitative brain [18F]FDG PET beyond normal blood glucose levels

Introduction SUV measurements from static brain [18F]FDG PET acquisitions are a commonly used tool in preclinical research, providing a simple alternative for kinetic modelling, which requires complex and time-consuming dynamic acquisitions. However, SUV can be severely affected by the animal handling and preconditioning protocols, primarily by those that may induce changes in blood glucose levels (BGL). Here, we aimed at developing and investigating the feasibility of SUV-based approaches for a wide range of BGL far beyond normal values, and consequently, to develop and validate a new model to generate standardized and reproducible SUV measurements for any BGL.Material and methods We performed dynamic and static brain [18F]FDG PET acquisitions in 52 male Sprague-Dawley rats sorted into control (n = 10), non-fasting (n = 14), insulin-induced hypoglycemia (n = 12) and glucagon-induced hyperglycemia (n = 16) groups. Brain [18F]FDG PET images were cropped, aligned and co-registered to a standard template to calculate whole-brain and regional SUV. Cerebral Metabolic Rate of Glucose (CMRglc) was also estimated from 2-Tissue Compartment Model (2TCM) and Patlak plot for validation purposes.Results Our results showed that BGL=100±6 mg/dL can be considered a reproducible reference value for normoglycemia. Furthermore, we successfully established a 2nd-degree polynomial model (C1=0.66E-4, C2=-0.0408 and C3=7.298) relying exclusively on BGL measures at pre-[18F]FDG injection time, that characterizes more precisely the relationship between SUV and BGL for a wide range of BGL values (from 10 to 338 mg/dL). We confirmed the ability of this model to generate corrected SUV estimations that are highly correlated to CMRglc estimations (R2= 0.54 2TCM CMRgluc and R2= 0.49 Patlak CMRgluc). Besides, slight regional differences in SUV were found in animals from extreme BGL groups, showing that [18F]FDG uptake is mostly directed toward central regions of the brain when BGLs are significantly decreased.Conclusion Our study successfully established a non-linear model that relies exclusively on pre-scan BGL measurements to characterize the relationship between [18F]FDG SUV and BGL. The extensive validation confirmed its ability to generate SUV-based surrogates of CMRglu along a wide range of BGL and it holds the potential to be adopted as a standard protocol by the preclinical neuroimaging community using brain [18F]FDG PET imaging.

Hyperglycemia selectively increases cerebral non-oxidative glucose consumption without affecting blood flow.

Multiple studies have shown that hyperglycemia increases the cerebral metabolic rate of glucose (CMRglc) in subcortical white matter. This observation remains unexplained. Using positron emission tomography (PET) and euinsulinaemic glucose clamps, we found, for the first time, that acute hyperglycemia increases non-oxidative CMRglc (i.e., aerobic glycolysis (AG)) in subcortical white mater as well as in medial temporal lobe structures, cerebellum and brainstem, all areas with low euglycemic CMRglc. Surprisingly, hyperglycemia did not change regional cerebral blood flow (CBF), the cerebral metabolic rate of oxygen (CMRO2), or the blood-oxygen-level-dependent (BOLD) response. Regional gene expression data reveal that brain regions where CMRglc increased have greater expression of hexokinase 2 (HK2). Simulations of glucose transport revealed that, unlike hexokinase 1, HK2 is not saturated at euglycemia, thus accommodating increased AG during hyperglycemia.

18F-FDG PET can effectively rule out conversion to dementia and the presence of CSF biomarker of neurodegeneration: a real-world data analysis

BackgroundPrecisely defining the delay in onset of dementia is a particular challenge for early diagnosis. Brain [18F] fluoro-2-deoxy-2-D-glucose (18F-FDG) Positron Emission Tomography (PET) is a particularly interesting tool for the early diagnosis of neurodegenerative diseases, through the measurement of the cerebral glucose metabolic rate. There is currently a lack of longitudinal studies under real-life conditions, with sufficient patients, to accurately evaluate the predictive values of brain 18F-FDG PET scans. Here, we aimed to estimate the value of brain 18F-FDG PET for predicting the risk of dementia conversion and the risk of occurrence of a neurodegenerative pathology.MethodsLongitudinal data for a cohort of patients with no diagnosis of dementia at the time of recruitment referred by a tertiary memory clinic for brain 18F-FDG PET were matched with (Prince M, Wimo A, Guerchet Maëlenn, Ali G-C, Wu Y-T et al. World Alzheimer Report 2015. The Global Impact of Dementia: An analysis of prevalence, incidence, cost and trends. [Research Report] Alzheimer’s Disease International. 2015. 2015.) data from the French National Health Data System (NHDS), (Jack CR, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease. Alzheimers Dement. 2018;14(4):535–62.) data from the National Alzheimer Bank (NAB), and (Davis M, O`Connell T, Johnson S, Cline S, Merikle E, Martenyi F, et al. Estimating Alzheimer’s Disease Progression Rates from Normal Cognition Through Mild Cognitive Impairment and Stages of Dementia. CAR. 2018;15(8):777–88.) lumbar puncture (LP) biomarker data. The criteria for dementia conversion were the designation, within the three years after the brain 18F-FDG PET scan, of a long-term condition for dementia in the NHDS and a dementia stage of cognitive impairment in the NAB. The criterion for the identification of a neurodegenerative disease in the medical records was the determination of LP biomarker levels.ResultsAmong the 403 patients (69.9 ± 11.4 years old, 177 women) from the initial cohort with data matched with the NHDS data, 137 were matched with the NAB data, and 61 were matched with LP biomarker data. Within three years of the scan, a 18F-FDG PET had negative predictive values of 85% for dementia conversion (according to the NHDS and NAB datasets) and 95% for the presence of LP neurodegeneration biomarkers.ConclusionA normal brain 18F-FDG PET scan can help rule out the risk of dementia conversion and the presence of cerebrospinal fluid (CSF) biomarker of neurodegeneration early with high certainty, allowing modifications to patient management regimens in the short term.Trial registrationClinical Trials database (NCT04804722). March 18, 2021. Retrospectively registered.

Peripheral insulin resistance attenuates cerebral glucose metabolism and impairs working memory in healthy adults

People with insulin resistance are at increased risk for cognitive decline. Insulin resistance has previously been considered primarily a condition of ageing but it is increasingly seen in younger adults. It is possible that impaired insulin function in early adulthood has both proximal effects and moderates or even accelerates changes in cerebral metabolism in ageing. Thirty-six younger (mean 27.8 years) and 43 older (mean 75.5) participants completed a battery of tests, including blood sampling, cognitive assessment and a simultaneous PET/MR scan. Cortical thickness and cerebral metabolic rates of glucose were derived for 100 regions and 17 functional networks. Older adults had lower rates of regional cerebral glucose metabolism than younger adults across the brain even after adjusting for lower cortical thickness in older adults. Higher fasting blood glucose was also associated with lower regional cerebral glucose metabolism in older adults. In younger adults, higher insulin resistance was associated with lower rates of regional cerebral glucose metabolism but this was not seen in older adults. The largest effects of insulin resistance in younger adults were in prefrontal, parietal and temporal regions; and in the control, salience ventral attention, default and somatomotor networks. Higher rates of network glucose metabolism were associated with lower reaction time and psychomotor speed. Higher levels of insulin resistance were associated with lower working memory. Our results underscore the importance of insulin sensitivity and glycaemic control to brain health and cognitive function across the adult lifespan, even in early adulthood.

The association of regional cerebral blood flow and glucose metabolism in normative ageing and insulin resistance

Rising rates of insulin resistance and an ageing population are set to exact an increasing toll on individuals and society. Here we examine the contribution of age and insulin resistance to the association of cerebral blood flow and glucose metabolism; both critical process in the supply of energy for the brain. Thirty-four younger (20–42 years) and 41 older (66–86 years) healthy adults underwent a simultaneous resting state MR/PET scan, including arterial spin labelling. Rates of cerebral blood flow and glucose metabolism were derived using a functional atlas of 100 brain regions. Older adults had lower cerebral blood flow than younger adults in 95 regions, reducing to 36 regions after controlling for cortical atrophy and blood pressure. Lower cerebral blood flow was also associated with worse working memory and slower reaction time in tasks requiring cognitive flexibility and response inhibition. Younger and older insulin sensitive adults showed small, negative correlations between relatively high rates of regional cerebral blood flow and glucose metabolism. This pattern was inverted in insulin resistant older adults, who showed hypoperfusion and hypometabolism across the cortex, and a positive correlation. In insulin resistant younger adults, the association showed inversion to positive correlations, although not to the extent seen in older adults. Our findings suggest that the normal course of ageing and insulin resistance alter the rates of and associations between cerebral blood flow and glucose metabolism. They underscore the criticality of insulin sensitivity to brain health across the adult lifespan.

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. This has led to significantly improved imaging with lower radiotracer doses. Optimized methods for the latest PET-CT scanners involve administering a sequence of inhaled 15O-labeled carbon monoxide (CO) and oxygen (O2), intravenous 15O-labeled water (H2O), and 18F-deoxyglucose (FDG)-all within 2-h or 3-h scan sessions that yield high-resolution, quantitative measurements of CMRGlc, CMRO2, CBF, CBV, and AG. This methods paper describes practical aspects of scanning designed for quantifying brain metabolism with tracer kinetic models and arterial blood samples and provides examples of imaging measurements of human brain metabolism.

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

PurposeFunctional 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.MethodsWe validated the approach using two datasets (DS). For DS1, 52 volunteers (23.2 ± 3.3 years, 24 females) performed Tetris® during a [18F]FDG fPET scan (bolus + constant infusion). For DS2, 18 participants (24.2 ± 4.3 years, 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.ResultsWe 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.ConclusionThe 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.