18F-FDG Is a Superior Indicator of Cognitive Performance Compared to 18F-Florbetapir in Alzheimer’s Disease and Mild Cognitive Impairment Evaluation: A Global Quantitative Analysis

Efficacy and Safety of Exogenous Ketones in People with Mild Neurocognitive Disorder and Alzheimer's Disease: A Systematic Literature Review

CONTEXT

Mild neurocognitive disorder (NCD), formally known as mild cognitive impairment, is usually the clinical stage preceding the development of Alzheimer's disease (AD), the most prevalent major NCD, and other causes of dementia. Glucose is a major source of energy for human brain metabolism and the uptake of glucose is reduced in patients with mild NCD, AD, and other NCDs. Unlike glucose, the uptake of ketones remains normal in people with mild NCD and AD, suggesting that the use of ketone bodies may compensate for glucose energy deficiency in patients with mild NCD and AD.

OBJECTIVE

The aim of this systematic review was to summarize the efficacy and safety of exogenic ketones, including medium chain triglycerides (MCTs), on cognitive function in patients with mild NCD and AD.

DATA SOURCES

The Embase, MEDLINE, MEDLINE In-Process, PubMed Ahead-of-Print, Cochrane Central Register of Controlled Trials, Europe PMC databases were searched from inception to April 2022. Studies reporting cognitive function efficacy and safety outcomes from randomized controlled trials of exogenic ketones in patients with mild NCD and AD were included.

DATA EXTRACTION

Data were extracted by 1 reviewer and checked by a second reviewer. Risk of bias was assessed using the Cochrane risk of bias tool, version 2.

DATA ANALYSIS

This review identified 13 individual trials investigating the efficacy and safety of MCT or coconut oil for patients with mild NCD or with AD. Because of the heterogeneity of the studies, a narrative synthesis was used.

CONCLUSION

Overall, improvements associated with exogenic ketones were observed in multiple aspects of cognitive abilities, although the large heterogeneity between the included studies makes it difficult to draw firm conclusions from the current literature. Although some studies investigated the impact of the apolipoprotein E ε4 allele status on treatment efficacy, the current data are insufficient to conclude whether such an effect is present.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration No. CRD42022336664.

The relationship of 18F-FDG-PET to other common biomarkers of dementia in a clinical cohort with memory deficits

Background

Early biomarker-based diagnosis of Alzheimer's disease (AD) is essential, particularly with the increasing availability of new therapeutic options. However, the relationship between imaging and cerebrospinal fluid (CSF) biomarkers, especially in the context of 18Fluorine-fluorodeoxyglucose positron emission tomography (18F-FDG-PET), remains insufficiently understood.

Objective

The aim of this study was the evaluation of the relationship between 18F-FDG-PET and other common fluid and imaging AD-biomarkers in a clinical cohort of patients with cognitive decline and suspected AD.

Methods

We included n = 90 patients with cognitive decline and clinically suspected AD that underwent 18F-FDG-PET imagining at our facility. Clinical and imaging data including patient characteristics, CSF biomarkers, Mini-Mental State Examination (MMSE), 18F-FDG-PET and 18F-Florbetaben-PET were retrospectively analyzed. PET images were quantified in several brain regions.

Results

18F-FDG uptake correlated with CSF amyloid-β (Aβ)40, Aβ42, and the Aβ42/40 ratio in several brain regions, but not with regional 18F-Florbetaben uptake. 18F-FDG uptake inversely correlated with t-tau and p-tau in CSF. Furthermore, a correlation between MMSE and 18F-FDG uptake was also detected in several brain regions. 18F-FDG-PET and its combination with CSF markers showed the highest predictive power for disease severity.

Conclusions

The study highlights the potential of integrating 18F-FDG-PET with CSF biomarkers to improve the diagnosis, prognosis, and monitoring of AD, emphasizing the complexity and regional specificity of biomarker interactions in neurodegeneration.

Evaluating clinical meaningfulness of anti-β-amyloid therapies amidst amyloid-related imaging abnormalities concern in Alzheimer's disease

Alzheimer's disease is the most prevalent form of dementia in the elderly, which is clinically characterized by a gradual and progressive deterioration of cognitive functions. The central and early role of β-amyloid in the pathogenesis of Alzheimer's disease is supported by a plethora of studies including genetic analyses, biomarker research and genome-wide association studies in both familial (early-onset) and sporadic (late-onset) forms of Alzheimer's. Monoclonal antibodies directed against β-amyloid demonstrate slowing of the clinical deterioration of patients with early Alzheimer's disease. Aducanumab, lecanemab and donanemab clinical trials showed slowing of Alzheimer's disease progression on composite scores by 25-40% based on the measure used. Anti-β-amyloid antibodies can cause side effects of bleeding and swelling in the brain, called amyloid-related imaging abnormalities. Amyloid-related imaging abnormalities typically occur early in treatment and are often asymptomatic, and though in rare cases, they can lead to serious or life-threatening events. The aim of this review is to evaluate the clinical meaningfulness of anti-β-amyloid therapies amidst amyloid-related imaging abnormalities concern in Alzheimer's disease.

Neuronal viability/astrocyte activity ratio in the dorsolateral prefrontal cortex as a biomarker of Alzheimer's dementia: a proton magnetic resonance spectroscopy study

N-acetyl-aspartate (NAA) and myo-inositol (mI) are neurometabolites reflecting neuronal viability and astrocyte activity, respectively. These are quantified using proton magnetic resonance spectroscopy (1H-MRS) and may be biomarkers for Alzheimer's disease dementia (AD). Our objectives were: 1) Compare dorsolateral prefrontal cortex (DLPFC) NAA and mI levels between AD and cognitively healthy control participants (HC) 2) assess if NAA/mI ratio can distinguish groups, and 3) explore the relationship between metabolites and cognition. The study included 64 participants over 55, 41 with AD. Bilateral DLPFC NAA and mI levels were quantified using 3 T 1H-MRS and normalized to H2O. NAA and NAA/mI ratio were lower in AD vs. HC. mI was unchanged. The NAA/mI ratio at a cut-off value of 1.69 showed 59% sensitivity and 87% specificity at distinguishing AD from HC. NAA was associated positively with cognition. In conclusion, DLPFC metabolite changes suggest altered mitochondrial function in AD. NAA/mI ratio shows good specificity in distinguishing AD from HC, suggesting its role in complementing other biomarkers. Future studies should evaluate NAA/mI ratio with other disease specific biomarkers.

Cerebral glucose metabolism in Alzheimer's disease

18F-fluoro-deoxy-glucose positron emission tomography (FDG-PET) is a useful paraclinical exam for the diagnosis of Alzheimer's disease (AD). In this narrative review, we report seminal studies in clinically probable AD that have shown the importance of posterior brain metabolic decrease and the paradoxical variability of the hippocampal metabolism. The FDG-PET pattern was a sensitive indicator of AD in pathologically confirmed cases and it was used for differential diagnosis of dementia conditions. In prodromal AD, the AD FDG-PET pattern was observed in converters and predicted conversion. Automated data analysis techniques provided variable accuracy according to the reported indices and machine learning methods showed variable reliability of results. FDG-PET could confirm AD clinical heterogeneity and image data driven analyses identified hypometabolic subtypes with variable involvement of the hippocampus, reminiscent if the paradoxical FDG uptake. In studies dedicated to clinical and metabolic correlations, episodic memory was related to metabolism in the default mode network (and Papez's circuit) in prodromal and mild AD stages, and specific cognitive processes were associated to precisely distributed brain metabolism. Cerebral metabolic correlates of anosognosia could also be related to current neuropsychological models. AD FDG-PET pattern was reported in preclinical AD stages and related to cognition or to conversion to mild cognitive impairment (MCI). Using other biomarkers, the AD FDG-PET pattern was confirmed in AD participants with positive PET-amyloid. Intriguing observations reported increased metabolism related to brain amyloid and/or tau deposition. Preserved glucose metabolism sometimes appear as a compensation, but it was frequently detrimental and the nature of such a preservation of glucose metabolism remains an open question. Limbic metabolic involvement was frequently related to non-AD biomarkers profile and clinical stability, and it was reported in non-AD pathologies, such as the limbic predominant age-related encephalopathy (LATE). FDG-PET abnormalities observed in the absence of classical AD proteinopathies can be useful to search for pathological mechanisms and differential diagnosis of AD.

The Association Between Brain Metabolic Biomarkers Using 18F-FDG and Cognition and Vascular Risk Factors, as well as Its Usefulness in the Diagnosis and Staging of Alzheimer's Disease

Background

18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) is valuable in Alzheimer's disease (AD) workup.

Objective

To explore the effectiveness of 18F-FDG PET in differentiating and staging AD and associations between brain glucose metabolism and cognitive functions and vascular risk factors.

Methods

107 participates including 19 mild cognitive impairment (MCI), 38 mild AD, 24 moderate AD, 15 moderate-severe AD, and 11 frontotemporal dementia (FTD) were enrolled. Visual and voxel-based analysis procedures were utilized. Cognitive conditions, including 6 cognitive function scores and 7 single-domain cognitive performances, and vascular risk factors linked to hypertension, hyperlipidemia, diabetes, and obesity were correlated with glucose metabolism in AD dementia using age as a covariate.

Results

18F-FDG PET effectively differentiated AD from FTD and also differentiated MCI from AD subtypes with significantly different hypometabolism (except for mild AD) (height threshold p < 0.001, all puncorr < 0.05, the same below). The cognitive function scores, notably Mini-Mental State Examination and Montreal Cognitive Assessment, correlated significantly with regional glucose metabolism in AD participants (all p < 0.05), whereas the single-domain cognitive performance and vascular risk factors were significantly associated with regional glucose metabolism in MCI patients (all p < 0.05).

Conclusions

This study underlines the vital role of 18F-FDG PET in identifying and staging AD. Brain glucose metabolism is associated with cognitive status in AD dementia and vascular risk factors in MCI, indicating that 18F-FDG PET might be promising for predicting cognitive decline and serve as a visual framework for investigating underlying mechanism of vascular risk factors influencing the conversion from MCI to AD.

Donanemab, another anti-Alzheimer's drug with risk and uncertain benefit

Based on "reducing amyloid plaques in the brain", the U.S. Food and Drug Administration has granted accelerated and full approval for two monoclonal anti-Alzheimer's antibodies, aducanumab and lecanemab, respectively. Approval of a third antibody, donanemab, is pending. Moreover, lecanemab and donanemab are claimed to cause delay in the cognitive decline that characterizes the disease. We believe that these findings are subject to misinterpretation and statistical bias. Donanemab is claimed to cause removal of up to 86 % of cerebral amyloid and 36 % delay in cognitive decline compared to placebo. In reality, these are very small changes on an absolute scale and arguably less than what can be achieved with cholinesterase inhibitor/memantine therapy. Moreover, the "removal" of amyloid, based on the reduced accumulation of amyloid-PET tracer, most likely also reflects therapy-related tissue damage. This would also correlate with the minimal clinical effect, the increased frequency of amyloid-related imaging abnormalities, and the accelerated loss of brain volume in treated compared to placebo patients observed with these antibodies. We recommend halting approvals of anti-AD antibodies until these issues are fully understood to ensure that antibody treatment does not cause more harm than benefit to patients.

Multiparametric hippocampal signatures for early diagnosis of Alzheimer's disease using 18F-FDG PET/MRI Radiomics

PURPOSE

This study aimed to explore the utility of hippocampal radiomics using multiparametric simultaneous positron emission tomography (PET)/magnetic resonance imaging (MRI) for early diagnosis of Alzheimer's disease (AD).

METHODS

A total of 53 healthy control (HC) participants, 55 patients with amnestic mild cognitive impairment (aMCI), and 51 patients with AD were included in this study. All participants accepted simultaneous PET/MRI scans, including 18F-fluorodeoxyglucose (18F-FDG) PET, 3D arterial spin labeling (ASL), and high-resolution T1-weighted imaging (3D T1WI). Radiomics features were extracted from the hippocampus region on those three modal images. Logistic regression models were trained to classify AD and HC, AD and aMCI, aMCI and HC respectively. The diagnostic performance and radiomics score (Rad-Score) of logistic regression models were evaluated from 5-fold cross-validation.

RESULTS

The hippocampal radiomics features demonstrated favorable diagnostic performance, with the multimodal classifier outperforming the single-modal classifier in the binary classification of HC, aMCI, and AD. Using the multimodal classifier, we achieved an area under the receiver operating characteristic curve (AUC) of 0.98 and accuracy of 96.7% for classifying AD from HC, and an AUC of 0.86 and accuracy of 80.6% for classifying aMCI from HC. The value of Rad-Score differed significantly between the AD and HC (p < 0.001), aMCI and HC (p < 0.001) groups. Decision curve analysis showed superior clinical benefits of multimodal classifiers compared to neuropsychological tests.

CONCLUSION

Multiparametric hippocampal radiomics using PET/MRI aids in the identification of early AD, and may provide a potential biomarker for clinical applications.

PET/CT/MRI in Clinical Trials of Alzheimer's Disease

With the advent of PET imaging in 1976, 2-deoxy-2-[18F]fluoro-D-glucose (FDG)-PET became the preferred method for in vivo investigation of cerebral processes, including regional hypometabolism in Alzheimer's disease. With the emergence of amyloid-PET tracers, [11C]Pittsburgh Compound-B in 2004 and later [18F]florbetapir, [18F]florbetaben, and [18F]flumetamol, amyloid-PET has replaced FDG-PET in Alzheimer's disease anti-amyloid clinical trial treatments to ensure "amyloid positivity" as an entry criterion, and to measure treatment-related decline in cerebral amyloid deposits. MRI has been used to rule out other brain diseases and screen for 'amyloid-related imaging abnormalities' (ARIAs) of two kinds, ARIA-E and ARIA-H, characterized by edema and micro-hemorrhage, respectively, and, to a lesser extent, to measure changes in cerebral volumes. While early immunotherapy trials of Alzheimer's disease showed no clinical effects, newer monoclonal antibody trials reported decreases of 27% to 85% in the cerebral amyloid-PET signal, interpreted by the Food and Drug Administration as amyloid removal expected to result in a reduction in clinical decline. However, due to the lack of diagnostic specificity of amyloid-PET tracers, amyloid positivity cannot prevent the inclusion of non-Alzheimer's patients and even healthy subjects in these clinical trials. Moreover, the "decreasing amyloid accumulation" assessed by amyloid-PET imaging has questionable quantitative value in the presence of treatment-related brain damage (ARIAs). Therefore, future Alzheimer's clinical trials should disregard amyloid-PET imaging and focus instead on assessment of regional brain function by FDG-PET and MRI monitoring of ARIAs and brain volume loss in all trial patients.

Passive Alzheimer's immunotherapy: A promising or uncertain option?

The US Food and Drug Administration (FDA)'s recent accelerated approval of two anti-amyloid antibodies for treatment of Alzheimer's disease (AD), aducanumab and lecanemab, has caused substantial debate. To inform this debate, we reviewed the literature on randomized clinical trials conducted with eight such antibodies focusing on clinical efficacy, cerebral amyloid removal, amyloid-related imaging abnormalities (ARIAs) and cerebral volumes to the extent such measurements have been reported. Two antibodies, donanemab and lecanemab, have demonstrated clinical efficacy, but these results remain uncertain. We further argue that the decreased amyloid PET signal in these trials is unlikely to be a one-to-one reflection of amyloid removal, but rather a reflection of increased therapy-related brain damage, as supported by the increased incidence of ARIAs and reported loss of brain volume. Due to these uncertainties of benefit and risk, we recommend that the FDA pauses existing approvals and approval of new antibodies until results of phase 4 studies with these drugs are available to inform on these risk-benefit uncertainties. We recommend that the FDA prioritize FDG PET and detection of ARIAs and accelerated brain volume loss with MRI in all trial patients, and neuropathological examination of all patients who die in these phase 4 trials.

18F-FDG-PET Radiomics Based on White Matter Predicts The Progression of Mild Cognitive Impairment to Alzheimer Disease: A Machine Learning Study

RATIONALE AND OBJECTIVES

To build a model using white-matter radiomics features on positron-emission tomography (PET) and machine learning methods to predict progression from mild cognitive impairment (MCI) to Alzheimer disease (AD).

MATERIALS AND METHODS

We analyzed the data of 341 MCI patients from the Alzheimer's Disease Neuroimaging Initiative, of whom 102 progressed to AD during an 8-year follow-up. The patients were divided into the training (238 patients) and test groups (103 patients). PET-based radiomics features were extracted from the white matter in the training group, and dimensionally reduced to construct a psychoradiomics signature (PS), which was combined with multimodal data using machine learning methods to construct an integrated model. Model performance was evaluated using receiver operating characteristic curves in the test group.

RESULTS

Clinical Dementia Rating (CDR) scores, Alzheimer's Disease Assessment Scale (ADAS) scores, and PS independently predicted MCI progression to AD on multivariate logistic regression. The areas under the curve (AUCs) of the CDR, ADAS and PS in the training and test groups were 0.683, 0.755, 0.747 and 0.737, 0.743, 0.719 respectively, and were combined using a support vector machine to construct an integrated model. The AUC of the integrated model in the training and test groups was 0.868 and 0.865, respectively (sensitivity, 0.873 and 0.839, respectively; specificity, 0.784 and 0.806, respectively). The AUCs of the integrated model significantly differed from those of other predictors in both groups (p < 0.05, Delong test).

CONCLUSION

Our psych radiomics signature based on white-matter PET data predicted MCI progression to AD. The integrated model built using multimodal data and machine learning identified MCI patients at a high risk of progression to AD.

FDG PET (and MRI) for Monitoring Immunotherapy in Alzheimer Disease

ABSTRACT

Passive immunotherapy for Alzheimer disease has been tried for over 10 years without success. However, in 2021 and most recently in January 2023, the US Food and Drug Administration granted accelerated approval of 2 antibodies for this purpose, aducanumab and lecanemab. In both cases, the approval was based on a presumed therapy-related removal of amyloid deposits from the brain and, in the case of lecanemab, also some delay in cognitive decline. We question the validity of the evidence for the removal of amyloid in particular as assessed by amyloid PET imaging, believing that what is observed is more likely a large nonspecific amyloid PET signal in the white matter that diminishes during immunotherapy-in line with dose-dependent increases in amyloid-related imaging abnormalities and increased loss of cerebral volume in treated compared with placebo patients. To investigate this further, we recommend repeat FDG PET and MRI in all future immunotherapy trials.

Generation of Conventional 18F-FDG PET Images from 18F-Florbetaben PET Images Using Generative Adversarial Network: A Preliminary Study Using ADNI Dataset

Background and Objectives: ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) (PET_FDG) image can visualize neuronal injury of the brain in Alzheimer's disease. Early-phase amyloid PET image is reported to be similar to PET_FDG image. This study aimed to generate PET_FDG images from ¹⁸F-florbetaben PET (PET_FBB) images using a generative adversarial network (GAN) and compare the generated PET_FDG (PET_GE-FDG) with real PET_FDG (PET_RE-FDG) images using the structural similarity index measure (SSIM) and the peak signal-to-noise ratio (PSNR). Materials and Methods: Using the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, 110 participants with both PET_FDG and PET_FBB images at baseline were included. The paired PET_FDG and PET_FBB images included six and four subset images, respectively. Each subset image had a 5 min acquisition time. These subsets were randomly sampled and divided into 249 paired PET_FDG and PET_FBB subset images for the training datasets and 95 paired subset images for the validation datasets during the deep-learning process. The deep learning model used in this study is composed of a GAN with a U-Net. The differences in the SSIM and PSNR values between the PET_GE-FDG and PET_RE-FDG images in the cycleGAN and pix2pix models were evaluated using the independent Student's t-test. Statistical significance was set at p ≤ 0.05. Results: The participant demographics (age, sex, or diagnosis) showed no statistically significant differences between the training (82 participants) and validation (28 participants) groups. The mean SSIM between the PET_GE-FDG and PET_RE-FDG images was 0.768 ± 0.135 for the cycleGAN model and 0.745 ± 0.143 for the pix2pix model. The mean PSNR was 32.4 ± 9.5 and 30.7 ± 8.0. The PET_GE-FDG images of the cycleGAN model showed statistically higher mean SSIM than those of the pix2pix model (p < 0.001). The mean PSNR was also higher in the PET_GE-FDG images of the cycleGAN model than those of pix2pix model (p < 0.001). Conclusions: We generated PET_FDG images from PET_FBB images using deep learning. The cycleGAN model generated PET_GE-FDG images with a higher SSIM and PSNR values than the pix2pix model. Image-to-image translation using deep learning may be useful for generating PET_FDG images. These may provide additional information for the management of Alzheimer's disease without extra image acquisition and the consequent increase in radiation exposure, inconvenience, or expenses.

FDG-PET versus Amyloid-PET Imaging for Diagnosis and Response Evaluation in Alzheimer's Disease: Benefits and Pitfalls

In June 2021, the US Federal Drug and Food Administration (FDA) granted accelerated approval for the antibody aducanumab and, in January 2023, also for the antibody lecanemab, based on a perceived drug-induced removal of cerebral amyloid-beta as assessed by amyloid-PET and, in the case of lecanemab, also a presumption of limited clinical efficacy. Approval of the antibody donanemab is awaiting further data. However, published trial data indicate few, small and uncertain clinical benefits, below what is considered "clinically meaningful" and similar to the effect of conventional medication. Furthermore, a therapy-related decrease in the amyloid-PET signal may also reflect increased cell damage rather than simply "amyloid removal". This interpretation is more consistent with increased rates of amyloid-related imaging abnormalities and brain volume loss in treated patients, relative to placebo. We also challenge the current diagnostic criteria for AD based on amyloid-PET imaging biomarkers and recommend that future anti-AD therapy trials apply: (1) diagnosis of AD based on the co-occurrence of cognitive decline and decreased cerebral metabolism assessed by FDA-approved FDG-PET, (2) therapy efficacy determined by favorable effect on cognitive ability, cerebral metabolism by FDG-PET, and brain volumes by MRI, and (3) neuropathologic examination of all deaths occurring in these trials.

Should artificial intelligence be used in conjunction with Neuroimaging in the diagnosis of Alzheimer's disease?

Alzheimer's disease (AD) is a progressive, neurodegenerative disorder that affects memory, thinking, behavior, and other cognitive functions. Although there is no cure, detecting AD early is important for the development of a therapeutic plan and a care plan that may preserve cognitive function and prevent irreversible damage. Neuroimaging, such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), has served as a critical tool in establishing diagnostic indicators of AD during the preclinical stage. However, as neuroimaging technology quickly advances, there is a challenge in analyzing and interpreting vast amounts of brain imaging data. Given these limitations, there is great interest in using artificial Intelligence (AI) to assist in this process. AI introduces limitless possibilities in the future diagnosis of AD, yet there is still resistance from the healthcare community to incorporate AI in the clinical setting. The goal of this review is to answer the question of whether AI should be used in conjunction with neuroimaging in the diagnosis of AD. To answer the question, the possible benefits and disadvantages of AI are discussed. The main advantages of AI are its potential to improve diagnostic accuracy, improve the efficiency in analyzing radiographic data, reduce physician burnout, and advance precision medicine. The disadvantages include generalization and data shortage, lack of in vivo gold standard, skepticism in the medical community, potential for physician bias, and concerns over patient information, privacy, and safety. Although the challenges present fundamental concerns and must be addressed when the time comes, it would be unethical not to use AI if it can improve patient health and outcome.

The Key Role of Mitochondrial Function in Health and Disease

The role of mitochondrial function in health and disease has become increasingly recognized, particularly in the last two decades. Mitochondrial dysfunction as well as disruptions of cellular bioenergetics have been shown to be ubiquitous in some of the most prevalent diseases in our society, such as type 2 diabetes, cardiovascular disease, metabolic syndrome, cancer, and Alzheimer's disease. However, the etiology and pathogenesis of mitochondrial dysfunction in multiple diseases have yet to be elucidated, making it one of the most significant medical challenges in our history. However, the rapid advances in our knowledge of cellular metabolism coupled with the novel understanding at the molecular and genetic levels show tremendous promise to one day elucidate the mysteries of this ancient organelle in order to treat it therapeutically when needed. Mitochondrial DNA mutations, infections, aging, and a lack of physical activity have been identified to be major players in mitochondrial dysfunction in multiple diseases. This review examines the complexities of mitochondrial function, whose ancient incorporation into eukaryotic cells for energy purposes was key for the survival and creation of new species. Among these complexities, the tightly intertwined bioenergetics derived from the combustion of alimentary substrates and oxygen are necessary for cellular homeostasis, including the production of reactive oxygen species. This review discusses different etiological mechanisms by which mitochondria could become dysregulated, determining the fate of multiple tissues and organs and being a protagonist in the pathogenesis of many non-communicable diseases. Finally, physical activity is a canonical evolutionary characteristic of humans that remains embedded in our genes. The normalization of a lack of physical activity in our modern society has led to the perception that exercise is an "intervention". However, physical activity remains the modus vivendi engrained in our genes and being sedentary has been the real intervention and collateral effect of modern societies. It is well known that a lack of physical activity leads to mitochondrial dysfunction and, hence, it probably becomes a major etiological factor of many non-communicable diseases affecting modern societies. Since physical activity remains the only stimulus we know that can improve and maintain mitochondrial function, a significant emphasis on exercise promotion should be imperative in order to prevent multiple diseases. Finally, in populations with chronic diseases where mitochondrial dysfunction is involved, an individualized exercise prescription should be crucial for the "metabolic rehabilitation" of many patients. From lessons learned from elite athletes (the perfect human machines), it is possible to translate and apply multiple concepts to the betterment of populations with chronic diseases.

Hybrid PET/MRI with Flutemetamol and FDG in Alzheimer's Disease Clinical Continuum

AIMS

We aimed to investigate the interaction between β -amyloid (Aβ) accumulation and cerebral glucose metabolism, cerebral perfusion, and cerebral structural changes in the Alzheimer's disease (AD) clinical continuum.

BACKGROUND

Utility of positron emission tomography (PET) / magnetic resonance imaging (MRI) hybrid imaging for diagnostic categorization of the AD clinical continuum including subjective cognitive decline (SCD), amnestic mild cognitive impairment (aMCI) and Alzheimer's disease dementia (ADD) has not been fully crystallized.

OBJECTIVE

To evaluate the interaction between Aβ accumulation and cerebral glucose metabolism, cerebral perfusion, and cerebral structural changes such as cortex thickness or cerebral white matter disease burden and to detect the discriminative yields of these imaging modalities in the AD clinical continuum.

METHODS

Fifty patients (20 women and 30 men; median age: 64 years) with clinical SCD (n=11), aMCI (n=17) and ADD (n=22) underwent PET/MRI with [18F]-fluoro-D-glucose (FDG) and [18F]- Flutemetamol in addition to cerebral blood flow (CBF) and quantitative structural imaging along with detailed cognitive assessment.

RESULTS

High Aβ deposition (increased temporal [18F]-Flutemetamol standardized uptake value ratio (SUVr) and centiloid score), low glucose metabolism (decreased temporal lobe and posterior cingulate [18F]-FDG SUVr), low parietal CBF and right hemispheric cortical thickness were independent predictors of low cognitive test performance.

CONCLUSION

Integrated use of structural, metabolic, molecular (Aβ) and perfusion (CBF) parameters contribute to the discrimination of SCD, aMCI, and ADD.

Additive value of [18F]PI-2620 perfusion imaging in progressive supranuclear palsy and corticobasal syndrome

PURPOSE

Early after [18F]PI-2620 PET tracer administration, perfusion imaging has potential for regional assessment of neuronal injury in neurodegenerative diseases. This is while standard late-phase [18F]PI-2620 tau-PET is able to discriminate the 4-repeat tauopathies progressive supranuclear palsy and corticobasal syndrome (4RTs) from disease controls and healthy controls. Here, we investigated whether early-phase [18F]PI-2620 PET has an additive value for biomarker based evaluation of 4RTs.

METHODS

Seventy-eight patients with 4RTs (71 ± 7 years, 39 female), 79 patients with other neurodegenerative diseases (67 ± 12 years, 35 female) and twelve age-matched controls (69 ± 8 years, 8 female) underwent dynamic (0-60 min) [18F]PI-2620 PET imaging. Regional perfusion (0.5-2.5 min p.i.) and tau load (20-40 min p.i.) were measured in 246 predefined brain regions [standardized-uptake-value ratios (SUVr), cerebellar reference]. Regional SUVr were compared between 4RTs and controls by an ANOVA including false-discovery-rate (FDR, p < 0.01) correction. Hypoperfusion in resulting 4RT target regions was evaluated at the patient level in all patients (mean value - 2SD threshold). Additionally, perfusion and tau pattern expression levels were explored regarding their potential discriminatory value of 4RTs against other neurodegenerative disorders, including validation in an independent external dataset (n = 37), and correlated with clinical severity in 4RTs (PSP rating scale, MoCA, activities of daily living).

RESULTS

Patients with 4RTs had significant hypoperfusion in 21/246 brain regions, most dominant in thalamus, caudate nucleus, and anterior cingulate cortex, fitting to the topology of the 4RT disease spectrum. However, single region hypoperfusion was not specific regarding the discrimination of patients with 4RTs against patients with other neurodegenerative diseases. In contrast, perfusion pattern expression showed promise for discrimination of patients with 4RTs from other neurodegenerative diseases (AUC: 0.850). Discrimination by the combined perfusion-tau pattern expression (AUC: 0.903) exceeded that of the sole tau pattern expression (AUC: 0.864) and the discriminatory power of the combined perfusion-tau pattern expression was replicated in the external dataset (AUC: 0.917). Perfusion but not tau pattern expression was associated with PSP rating scale (R = 0.402; p = 0.0012) and activities of daily living (R =  - 0.431; p = 0.0005).

CONCLUSION

[18F]PI-2620 perfusion imaging mirrors known topology of regional hypoperfusion in 4RTs. Single region hypoperfusion is not specific for 4RTs, but perfusion pattern expression may provide an additive value for the discrimination of 4RTs from other neurodegenerative diseases and correlates closer with clinical severity than tau pattern expression.

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

Introduction

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.

Materials and methods

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.

Results

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.

Discussion

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.

Development of a deep learning network for Alzheimer’s disease classification with evaluation of imaging modality and longitudinal data

Objective. Neuroimaging uncovers important information about disease in the brain. Yet in Alzheimer’s disease (AD), there remains a clear clinical need for reliable tools to extract diagnoses from neuroimages. Significant work has been done to develop deep learning (DL) networks using neuroimaging for AD diagnosis. However, no particular model has emerged as optimal. Due to a lack of direct comparisons and evaluations on independent data, there is no consensus on which modality is best for diagnostic models or whether longitudinal information enhances performance. The purpose of this work was (1) to develop a generalizable DL model to distinguish neuroimaging scans of AD patients from controls and (2) to evaluate the influence of imaging modality and longitudinal data on performance. Approach. We trained a 2-class convolutional neural network (CNN) with and without a cascaded recurrent neural network (RNN). We used datasets of 772 (N AD = 364, N control = 408) 3D 18F-FDG PET scans and 780 (N AD = 280, N control = 500) T1-weighted volumetric-3D MR images (containing 131 and 144 patients with multiple timepoints) from the Alzheimer’s Disease Neuroimaging Initiative, plus an independent set of 104 (N AD = 63, N NC = 41) 18F-FDG PET scans (one per patient) for validation. Main Results. ROC analysis showed that PET-trained models outperformed MRI-trained, achieving maximum AUC with the CNN + RNN model of 0.93 ± 0.08, with accuracy 82.5 ± 8.9%. Adding longitudinal information offered significant improvement to performance on 18F-FDG PET, but not on T1-MRI. CNN model validation with an independent 18F-FDG PET dataset achieved AUC of 0.99. Layer-wise relevance propagation heatmaps added CNN interpretability. Significance. The development of a high-performing tool for AD diagnosis, with the direct evaluation of key influences, reveals the advantage of using 18F-FDG PET and longitudinal data over MRI and single timepoint analysis. This has significant implications for the potential of neuroimaging for future research on AD diagnosis and clinical management of suspected AD patients.

Pepinemab antibody blockade of SEMA4D in early Huntington's disease: a randomized, placebo-controlled, phase 2 trial

SIGNAL is a multicenter, randomized, double-blind, placebo-controlled phase 2 study (no. NCT02481674) established to evaluate pepinemab, a semaphorin 4D (SEMA4D)-blocking antibody, for treatment of Huntington's disease (HD). The trial enrolled a total of 265 HD gene expansion carriers with either early manifest (EM, n = 179) or late prodromal (LP, n = 86) HD, randomized (1:1) to receive 18 monthly infusions of pepinemab (n = 91 EM, 41 LP) or placebo (n = 88 EM, 45 LP). Pepinemab was generally well tolerated, with a relatively low frequency of serious treatment-emergent adverse events of 5% with pepinemab compared to 9% with placebo, including both EM and LP participants. Coprimary efficacy outcome measures consisted of assessments within the EM cohort of (1) a two-item HD cognitive assessment family comprising one-touch stockings of Cambridge (OTS) and paced tapping (PTAP) and (2) clinical global impression of change (CGIC). The differences between pepinemab and placebo in mean change (95% confidence interval) from baseline at month 17 for OTS were -1.98 (-4.00, 0.05) (one-sided P = 0.028), and for PTAP 1.43 (-0.37, 3.23) (one-sided P = 0.06). Similarly, because a significant treatment effect was not observed for CGIC, the coprimary endpoint, the study did not meet its prespecified primary outcomes. Nevertheless, a number of other positive outcomes and post hoc subgroup analyses-including additional cognitive measures and volumetric magnetic resonance imaging and fluorodeoxyglucose-positron-emission tomography imaging assessments-provide rationale and direction for the design of a phase 3 study and encourage the continued development of pepinemab in patients diagnosed with EM HD.

Commentary: Aducanumab-Related ARIA: Paean or Lament?

ABSTRACT

Høilund-Carlsen and colleagues raise important issues related to amyloid PET, diagnosis of Alzheimer disease, and recently approved antiamyloid treatment aducanumab. We discuss new developments that may direct us to methods of presymptomatic detection of Alzheimer disease and development of effective prevention and therapy.

Identification and validation of Alzheimer's disease-related metabolic brain pattern in biomarker confirmed Alzheimer's dementia patients

Metabolic brain biomarkers have been incorporated in various diagnostic guidelines of neurodegenerative diseases, recently. To improve their diagnostic accuracy a biologically and clinically homogeneous sample is needed for their identification. Alzheimer's disease-related pattern (ADRP) has been identified previously in cohorts of clinically diagnosed patients with dementia due to Alzheimer's disease (AD), meaning that its diagnostic accuracy might have been reduced due to common clinical misdiagnosis. In our study, we aimed to identify ADRP in a cohort of AD patients with CSF confirmed diagnosis, validate it in large out-of-sample cohorts and explore its relationship with patients' clinical status. For identification we analyzed 2-[18F]FDG PET brain scans of 20 AD patients and 20 normal controls (NCs). For validation, 2-[18F]FDG PET scans from 261 individuals with AD, behavioral variant of frontotemporal dementia, mild cognitive impairment and NC were analyzed. We identified an ADRP that is characterized by relatively reduced metabolic activity in temporoparietal cortices, posterior cingulate and precuneus which co-varied with relatively increased metabolic activity in the cerebellum. ADRP expression significantly differentiated AD from NC (AUC = 0.95) and other dementia types (AUC = 0.76-0.85) and its expression correlated with clinical measures of global cognition and neuropsychological indices in all cohorts.

Neuropsychological Performance Is Correlated With Tau Protein Deposition and Glucose Metabolism in Patients With Alzheimer’s Disease

Objective

This study characterizes glucose metabolism and tau protein deposition distribution in patients with Alzheimer’s disease (AD) and to evaluate the relationships between neuropsychological performance and tau protein deposition or glucose metabolism using ¹⁸F-FDG and ¹⁸F-AV1451 positron emission tomography/computed tomography (PET/CT).

Methods

Sixty-four patients with β-amyloid-positive (Aβ+) AD and twenty-five healthy participants were enrolled in this study. All participants underwent ¹⁸F-FDG and ¹⁸F-AV1451 PET/CT. Clinical data and neuropsychological scores were collected. Patients with AD were divided into mild, moderate, and severe groups according to mini-mental state examination (MMSE) scores. The standardized uptake value ratios (SUVRs) for both FDG and AV1451 PET images were calculated using the cerebellar vermis as reference. The SUVRs of the whole cerebral cortex and each brain region were calculated. The volume of interest (VOI) was obtained using automated anatomical atlas (AAL) and Brodmann regions. Student’s t-test was used to perform intergroup comparisons of SUVR. The partial correlation coefficient between SUVR and neuropsychological scores was computed in an inter-subject manner using age and education as covariates.

Results

The mild subgroup showed a reduction in glucose metabolism and aggregation of tau protein in the temporoparietal cortex. With a decline in neuropsychiatric performance, the SUVR on FDG PET decreased and SUVR on tau PET increased gradually. The areas of glucose metabolism reduction and tau protein deposition appeared first in the parietal cortex, followed by the temporal and frontal cortex, successively. Both FDG and tau SUVRs significantly correlated with MMSE, Montreal cognitive assessment (MOCA), auditory verbal learning test (AVLT), Boston naming test (BNT), clock drawing task (CDT), and verbal fluency test (VFT) (p < 0.05). The SUVR on FDG PET significantly correlated with activities of daily living (ADL) and the Hamilton depression scale (HAMD). There was no significant correlation between the tau SUVRs and ADL or HAMD.

Conclusion

The extension of tau protein deposition was similar but not exactly consistent with the area of glucose metabolism reduction. Both tau and FDG SUVRs correlated with cognitive function in domain-specific patterns, and the results of FDG PET more closely correlated with neuropsychological function than tau PET results did.

Dementia is associated with medial temporal atrophy even after accounting for neuropathologies

Brain atrophy is associated with degenerative neuropathologies and the clinical status of dementia. Whether dementia is associated with atrophy independent of neuropathologies is not known. In this study, we examined the pattern of atrophy associated with dementia while accounting for the most common dementia-related neuropathologies. We used data from National Alzheimer's Coordinating Center (n = 129) and Alzheimer's Disease Neuroimaging Initiative (n = 47) participants with suitable in vivo 3D-T1w MRI and autopsy data. We determined dementia status at the visit closest to MRI. We examined the following dichotomized neuropathological variables: Alzheimer's disease neuropathology, hippocampal sclerosis, Lewy bodies, cerebral amyloid angiopathy and atherosclerosis. Voxel-based morphometry identified areas associated with dementia after accounting for neuropathologies. Identified regions of interest were further analysed. We used multiple linear regression models adjusted for neuropathologies and demographic variables. We also examined models with dementia and Clinical Dementia Rating sum of the boxes as the outcome and explored the potential mediating effect of medial temporal lobe structure volumes on the relationship between pathology and cognition. We found strong associations for dementia with volumes of the hippocampus, amygdala and parahippocampus (semi-partial correlations ≥ 0.28, P < 0.0001 for all regions in National Alzheimer's Coordinating Center; semi-partial correlations ≥ 0.35, P ≤ 0.01 for hippocampus and parahippocampus in Alzheimer's Disease Neuroimaging Initiative). Dementia status accounted for more unique variance in atrophy in these structures (∼8%) compared with neuropathological variables; the only exception was hippocampal sclerosis which accounted for more variance in hippocampal atrophy (10%). We also found that the volumes of the medial temporal lobe structures contributed towards explaining the variance in Clinical Dementia Rating sum of the boxes (ranging from 5% to 9%) independent of neuropathologies and partially mediated the association between Alzheimer's disease neuropathology and cognition. Even after accounting for the most common neuropathologies, dementia still had among the strongest associations with atrophy of medial temporal lobe structures. This suggests that atrophy of the medial temporal lobe is most related to the clinical status of dementia rather than Alzheimer's disease or other neuropathologies, with the potential exception of hippocampal sclerosis.

Riluzole, a glutamate modulator, slows cerebral glucose metabolism decline in patients with Alzheimer's disease

Dysregulation of glutamatergic neural circuits has been implicated in a cycle of toxicity, believed among the neurobiological underpinning of Alzheimer's disease. Previously, we reported preclinical evidence that the glutamate modulator riluzole, which is FDA approved for the treatment of amyotrophic lateral sclerosis, has potential benefits on cognition, structural and molecular markers of ageing and Alzheimer's disease. The objective of this study was to evaluate in a pilot clinical trial, using neuroimaging biomarkers, the potential efficacy and safety of riluzole in patients with Alzheimer's disease as compared to placebo. A 6-month phase 2 double-blind, randomized, placebo-controlled study was conducted at two sites. Participants consisted of males and females, 50 to 95 years of age, with a clinical diagnosis of probable Alzheimer's disease, and Mini-Mental State Examination between 19 and 27. Ninety-four participants were screened, 50 participants who met inclusion criteria were randomly assigned to receive 50 mg riluzole (n = 26) or placebo (n = 24) twice a day. Twenty-two riluzole-treated and 20 placebo participants completed the study. Primary end points were baseline to 6 months changes in (i) cerebral glucose metabolism as measured with fluorodeoxyglucose-PET in prespecified regions of interest (hippocampus, posterior cingulate, precuneus, lateral temporal, inferior parietal, frontal); and (ii) changes in posterior cingulate levels of the neuronal viability marker N-acetylaspartate as measured with in vivo proton magnetic resonance spectroscopy. Secondary outcome measures were neuropsychological testing for correlation with neuroimaging biomarkers and in vivo measures of glutamate in posterior cingulate measured with magnetic resonance spectroscopy as a potential marker of target engagement. Measures of cerebral glucose metabolism, a well-established Alzheimer's disease biomarker and predictor of disease progression, declined significantly less in several prespecified regions of interest with the most robust effect in posterior cingulate, and effects in precuneus, lateral temporal, right hippocampus and frontal cortex in riluzole-treated participants in comparison to the placebo group. No group effect was found in measures of N-acetylaspartate levels. A positive correlation was observed between cognitive measures and regional cerebral glucose metabolism. A group × visit interaction was observed in glutamate levels in posterior cingulate, potentially suggesting engagement of glutamatergic system by riluzole. In vivo glutamate levels positively correlated with cognitive performance. These findings support our main primary hypothesis that cerebral glucose metabolism would be better preserved in the riluzole-treated group than in the placebo group and provide a rationale for more powered, longer duration studies of riluzole as a potential intervention for Alzheimer's disease.

Multimodal Classification of Alzheimer's Disease and Amnestic Mild Cognitive Impairment: Integrated 18F-FDG PET and DTI Study

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by cognitive decline and memory impairment. Amnestic mild cognitive impairment (aMCI) is the intermediate stage between normal cognitive aging and early dementia caused by AD. It can be challenging to differentiate aMCI patients from healthy controls (HC) and mild AD patients.

OBJECTIVE

To validate whether the combination of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) and diffusion tensor imaging (DTI) will improve classification performance compared with that based on a single modality.

METHODS

A total of thirty patients with AD, sixty patients with aMCI, and fifty healthy controls were included. AD was diagnosed according to the National Institute of Neurological and Communicative Diseases and Stroke/Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria for probable. aMCI diagnosis was based on Petersen's criteria. The 18F-FDG PET and DTI measures were each used separately or in combination to evaluate sensitivity, specificity, and accuracy for differentiating HC, aMCI, and AD using receiver operating characteristic analysis together with binary logistic regression. The rate of accuracy was based on the area under the curve (AUC).

RESULTS

For classifying AD from HC, we achieve an AUC of 0.96 when combining two modalities of biomarkers and 0.93 when using 18F-FDG PET individually. For classifying aMCI from HC, we achieve an AUC of 0.79 and 0.76 using the best individual modality of biomarkers.

CONCLUSION

Our results show that the combination of two modalities improves classification performance, compared with that using any individual modality.

Sex differences in Alzheimer's disease: metabolic reprogramming and therapeutic intervention

Studies on the sporadic form of Alzheimer's disease (AD) have revealed three classes of risk factor: age, genetics, and sex. These risk factors point to a metabolic dysregulation as the origin of AD. Adaptive alterations in cerebral metabolism are the rationale for the Metabolic Reprogramming (MR) Theory of the origin of AD. The theory contends that the progression toward AD involves three adaptive events: a hypermetabolic phase, a prolonged prodromal phase, and a metabolic collapse. This article exploits the MR Theory to elucidate the effect of hormonal changes on the origin and progression of AD in women. The theory invokes bioenergetic signatures of the menopausal transition to propose sex-specific diagnostic program and therapeutic strategies.

Brain metabolism in tau and amyloid mouse models of Alzheimer's disease: An MRI study

Alzheimer's disease (AD) is the leading cause of cognitive impairment and dementia in elderly individuals. According to the current biomarker framework for "unbiased descriptive classification", biomarkers of neurodegeneration, "N", constitute a critical component in the tri-category "A/T/N" system. Current biomarkers of neurodegeneration suffer from potential drawbacks such as requiring invasive lumbar puncture, involving ionizing radiation, or representing a late, irreversible marker. Recent human studies have suggested that reduced brain oxygen metabolism may be a new functional marker of neurodegeneration in AD, but the heterogeneity and the presence of mixed pathology in human patients did not allow a full understanding of the role of oxygen extraction and metabolism in AD. In this report, global brain oxygen metabolism and related physiological parameters were studied in two AD mouse models with relatively pure pathology, using advanced MRI techniques including T2 -relaxation-under-spin-tagging (TRUST) and phase contrast (PC) MRI. Additionally, regional cerebral blood flow (CBF) was determined with pseudocontinuous arterial spin labeling. Reduced global oxygen extraction fraction (by -18.7%, p = 0.008), unit-mass cerebral metabolic rate of oxygen (CMRO2 ) (by -17.4%, p = 0.04) and total CMRO2 (by -30.8%, p < 0.001) were observed in Tau4RΔK mice-referred to as the tau AD model-which manifested pronounced neurodegeneration, as measured by diminished brain volume (by -15.2%, p < 0.001). Global and regional CBF in these mice were not different from those of wild-type mice (p > 0.05), suggesting normal vascular function. By contrast, in B6;SJL-Tg [APPSWE]2576Kha (APP) mice-referred to as the amyloid AD model-no brain volume reduction, as well as relatively intact brain oxygen extraction and metabolism, were found (p > 0.05). Consistent with the imaging data, behavioral measures of walking distance were impaired in Tau4RΔK mice (p = 0.004), but not in APP mice (p = 0.88). Collectively, these findings support the hypothesis that noninvasive MRI measurement of brain oxygen metabolism may be a promising biomarker of neurodegeneration in AD.

Mitochondrial links between brain aging and Alzheimer's disease

Advancing age is a major risk factor for Alzheimer's disease (AD). This raises the question of whether AD biology mechanistically diverges from aging biology or alternatively represents exaggerated aging. Correlative and modeling studies can inform this question, but without a firm grasp of what drives aging and AD it is difficult to definitively resolve this quandary. This review speculates over the relevance of a particular hallmark of aging, mitochondrial function, to AD, and further provides background information that is pertinent to and provides perspective on this speculation.

Patterns of cognitive decline and somatosensory processing in a mouse model of amyloid accumulation

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Despite copious amyloid plaques, 5XFAD mice show modest signs of cognitive decline.

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At ages 2 to 13 months old 5XFAD mice show no signs of sensory or pain dysfunctions.

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5XFAD mice may not be a valid model for pain abnormalities in the context of AD.

Pain and cognitive decline increase with age. In particular, there is a troubling relationship between dementia and pain, with some studies showing higher prevalence and inadequate treatment of pain in this population. Alzheimer’s disease (AD) is one of the most common causes of dementia in older adults. Amyloid plaques are a hallmark of AD. The downstream processes these plaques promote are believed to affect neuronal and glial health and activity. There is a need to better understand how the neuropathological changes of AD shape neural activity and pain sensitivity. Here, we use the 5XFAD mouse model, in which dense amyloid accumulations occur at early ages, and in which previous studies reported signs of cognitive decline. We hypothesized that 5XFAD mice develop sensory and pain processing dysfunctions. Although amyloid burden was high throughout the brain, including in regions involved with sensory processing, we identified no functionally significant differences in reflexive or spontaneous signs of pain. Furthermore, expected signs of cognitive decline were modest; a finding consistent with variable results in the literature. These data suggest that models recapitulating other pathological features of Alzheimer’s disease might be better suited to studying differences in pain perception in this disease.

Global brain glucose uptake on 18F-FDG-PET/CT is influenced by chronic cardiovascular risk

PURPOSE

The goal of this study was to assess global cerebral glucose uptake in subjects with known cardiovascular risk factors by employing a quantitative 18F-fluorodeoxyglucose-PET/computed tomography (FDG-PET/CT) technique. We hypothesized that at-risk subjects would demonstrate decreased global brain glucose uptake compared to healthy controls.

METHODS

We compared 35 healthy male controls and 14 male subjects at increased risk for cardiovascular disease (CVD) as assessed by the systematic coronary risk evaluation (SCORE) tool. All subjects were grouped into two age-matched cohorts: younger (<50 years) and older (≥50 years). The global standardized uptake value mean (Avg SUVmean) was measured by mapping regions of interest of the entire brain across the supratentorial structures and cerebellum. Wilcoxon's rank-sum test was used to assess the differences in Avg SUVmean between controls and at-risk subjects.

RESULTS

Younger subjects demonstrated higher brain Avg SUVmean than older subjects. In addition, in both age strata, the 10-year risk for fatal CVD according to the SCORE tool was significantly greater in the at-risk groups than in healthy controls (younger: P = 0.0304; older: P = 0.0436). In the younger cohort, at-risk subjects demonstrated significantly lower brain Avg SUVmean than healthy controls (P = 0.0355). In the older cohort, at-risk subjects similarly had lower Avg SUVmean than controls (P = 0.0343).

CONCLUSIONS

Global brain glucose uptake appears to be influenced by chronic cardiovascular risk factors. Therefore, FDG-PET/CT may play a role in determining the importance of CVD on brain function and has potential for monitoring the efficacy of various therapeutic interventions.

Sex differences in the IntelliCage and the Morris water maze in the APP/PS1 mouse model of amyloidosis

Transgenic rodent models were created to decipher pathogenic mechanisms associated with Alzheimer’s disease (AD), and behavioral apparatuses such as the Morris water maze (MWM) are used to assess cognition in mice. The IntelliCage was designed to circumvent issues of traditional behavioral tests, such as frequent human handling. The motivation to complete IntelliCage tasks is water consumption, which is less stressful than escaping from a pool in the MWM. Here, we examined behavioral performances of mice in the IntelliCage and MWM tasks. Twelve-month-old male and female APP/PS1 and non-transgenic mice first underwent 42 days of IntelliCage testing to assess prefrontal cortical and hippocampal function followed by MWM testing for six days. We found that females performed better in the IntelliCage while males performed superiorly in the MWM. Mechanistically, female APP/PS1 mice had a higher Amyloid-β plaque load throughout the brain, which is inconsistent with their performance in the IntelliCage. Collectively, these results inform scientists about the sex-based differences when testing animals in different behavioral paradigms that tap similar cognitive functions.

Correlation Between Brain 18F-AV45 and 18F-FDG PET Distribution Characteristics and Cognitive Function in Patients with Mild and Moderate Alzheimer's Disease

BACKGROUND

Florbetapir (AV45) and fluorodeoxyglucose (FDG) PET imaging are valuable techniques to detect the amyloid-β (Aβ) load and brain glucose metabolism in patients with Alzheimer's disease (AD).

OBJECTIVE

The purpose of this study is to access the characteristics of Aβ load and FDG metabolism in brain for further investigating their relationships with cognitive impairment in AD patients.

METHODS

Twenty-seven patients with AD (average 70.6 years old, N = 13 male, N = 14 female) were enrolled in this study. These AD patients underwent the standard clinical assessment and received detailed imaging examinations of the nervous system by using Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MOCA), 18F-AV45, and 18F-FDG PET scans.

RESULTS

Of 27 AD patients, 22 patients (81.5%) showed significantly increases in Aβ load and 26 patients (96.3%) had significantly reductions in FDG metabolism. The moderate AD patients had more brain areas of reduced FDG metabolism and more severe reductions in some regions compared to mild AD patients, with no differences in Aβ load observed. Moreover, the range and degree of reduced FDG metabolism in several regions were positively correlated with the total score of MMSE or MOCA, whereas the range of Aβ load did not. No correlation was found between the range of Aβ load and the range of reduced FDG metabolism in this study.

CONCLUSION

The reduction in FDG metabolisms captured by 18F-FDG imaging can be used as a potential biomarker for AD diagnosis in the future. 18F-AV45 imaging did not present valuable evidence for evaluating AD patient in this study.

Protective Factors Modulate the Risk of Beta Amyloid in Alzheimer's Disease

Aim

To identify the factors protecting Abeta-positive subjects with normal cognition (NC) or mild cognitive impairment (MCI) from conversion to Alzheimer's disease (AD).

Methods

Subjects with MCI in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, with baseline data for neuropsychological tests, brain beta amyloid (Abeta), magnetic resonance imaging (MRI), APOE genotyping, and 18F-FDG-PET (FDG), were included for analysis.

Results

Elevated brain amyloid was associated with a higher risk of conversion from MCI to AD (41.5%) relative to Abeta levels of <1.231 (5.5%) but was not associated with conversion from NC to AD (0.0 vs. 1.4%). In the multivariate Cox regression analyses, elevated Abeta increased the risk of AD, while higher whole-brain cerebral glucose metabolism (CGM) assessed by FDG decreased the risk of AD in subjects with the same amount of Abeta. Even in the patients with heavily elevated brain amyloid, those with FDG > 5.946 had a lower risk of AD. ApoE4 carrier status did not influence the protective effect.

Conclusion

Higher average CGM based on FDG modified the progression to AD, indicating a protective function. The results suggest that the inclusion of this CGM measured by FDG would enrich clinical trial design and that increasing CGM along with the use of anti-Abeta agents might be a potential prevention strategy for AD.

FDG PET Data is Associated with Cognitive Performance in Patients from a Memory Clinic

BACKGROUND

Various reasons may lead to cognitive symptoms in elderly, including the development of cognitive decline and dementia. Often, mixed pathologies such as neurodegeneration and cerebrovascular disease co-exist in these patients. Diagnostic work-up commonly includes imaging modalities such as FDG PET, MRI, and CT, each delivering specific information.

OBJECTIVE

To study the informative value of neuroimaging-based data supposed to reflect neurodegeneration (FDG PET), cerebral small vessel disease (MRI), and cerebral large vessel atherosclerosis (CT) with regard to cognitive performance in patients presenting to our memory clinic.

METHODS

Non-parametric partial correlations and an ordinal logistic regression model were run to determine relationships between scores for cortical hypometabolism, white matter hyperintensities, calcified plaque burden, and results from Mini-Mental State Examination (MMSE). The final study group consisted of 162 patients (female: 94; MMSE: 6-30).

RESULTS

Only FDG PET data was linked to and predicted cognitive performance (r(157) = -0.388, p < 0.001). Overall, parameters linked to cerebral small and large vessel disease showed no significant association with cognition. Further findings demonstrated a relationship between white matter hyperintensities and FDG PET data (r(157) = 0.230, p = 0.004).

CONCLUSION

Only FDG PET imaging mirrors cognitive performance, presumably due to the examination's ability to reflect neurodegeneration and vascular dysfunction, thus capturing a broader spectrum of pathologies. This makes the examination a useful imaging-based diagnostic tool in the work-up of patients presenting to a memory clinic. Parameters of vascular dysfunction alone as depicted by conventional MRI and CT are less adequate in such a situation, most likely because they reflect one pathology complex only.

PET amyloid in normal aging: direct comparison of visual and automatic processing methods

Assessment of amyloid deposits is a critical step for the identification of Alzheimer disease (AD) signature in asymptomatic elders. Whether the different amyloid processing methods impacts on the quality of clinico-radiological correlations is still unclear. We directly compared in 155 elderly controls with extensive neuropsychological testing at baseline and 4.5 years follow-up three approaches: (i) operator-dependent standard visual reading, (ii) operator-independent automatic SUVR with four different reference regions, and (iii) novel operator and region of reference-independent automatic Aβ-index. The coefficient of variance was used to examine inter-individual variability for each processing method. Using visually-established amyloid positivity as the gold standard, the area under the receiver operating characteristic curve (ROC) was computed. Linear regression models were used to assess the association between changes in continuous cognitive score and amyloid uptake values. In SUVR analyses, the coefficient of variance varied from 1.718 to 1.762 according to the area of reference and was of − 3.045 for the Aβ-index method. Compared to the visual rating, Aβ-index method showed the largest area under the ROC curve [0.9568 (95% CI 0.9252, 0.98833)]. The best cut-off score was of − 0.3359 with sensitivity and specificity values of 0.97 and 0.83, respectively. Only the Aß-index was related to more severe decrement of cognitive performances [regression coefficient: 9.103 (95% CI 1.148, 17.058)]. The Aβ-index is considered as preferred option in asymptomatic elders, since it is operator-independent, avoids the selection of reference area, is closer to established visual scoring and correlates with the evolution of cognitive performances.

Reinventing Molecular Imaging with Total-Body PET, Part II: Clinical Applications

Total-body PET scans will initiate a new era for the PET clinic. The benefits of 40-fold effective sensitivity improvement provide new capabilities to image with lower radiation dose, perform delayed imaging, and achieve improved temporal resolution. These technical features are detailed in the first of this 2-part series. In this part, the clinical impacts of the novel features of total-body PET scans are further explored. Applications of total-body PET scans focus on the real-time interrogation of systemic disease manifestations in a variety of practical clinical contexts. Total-body PET scans make clinical systems biology imaging a reality.

Significance of Blood and Cerebrospinal Fluid Biomarkers for Alzheimer's Disease: Sensitivity, Specificity and Potential for Clinical Use

Alzheimer's disease (AD) is the most common type of dementia, affecting more than 5 million Americans, with steadily increasing mortality and incredible socio-economic burden. Not only have therapeutic efforts so far failed to reach significant efficacy, but the real pathogenesis of the disease is still obscure. The current theories are based on pathological findings of amyloid plaques and tau neurofibrillary tangles that accumulate in the brain parenchyma of affected patients. These findings have defined, together with the extensive neurodegeneration, the diagnostic criteria of the disease. The ability to detect changes in the levels of amyloid and tau in cerebrospinal fluid (CSF) first, and more recently in blood, has allowed us to use these biomarkers for the specific in-vivo diagnosis of AD in humans. Furthermore, other pathological elements of AD, such as the loss of neurons, inflammation and metabolic derangement, have translated to the definition of other CSF and blood biomarkers, which are not specific of the disease but, when combined with amyloid and tau, correlate with the progression from mild cognitive impairment to AD dementia, or identify patients who will develop AD pathology. In this review, we discuss the role of current and hypothetical biomarkers of Alzheimer's disease, their specificity, and the caveats of current high-sensitivity platforms for their peripheral detection.

Brain energy rescue: an emerging therapeutic concept for neurodegenerative disorders of ageing

The brain requires a continuous supply of energy in the form of ATP, most of which is produced from glucose by oxidative phosphorylation in mitochondria, complemented by aerobic glycolysis in the cytoplasm. When glucose levels are limited, ketone bodies generated in the liver and lactate derived from exercising skeletal muscle can also become important energy substrates for the brain. In neurodegenerative disorders of ageing, brain glucose metabolism deteriorates in a progressive, region-specific and disease-specific manner - a problem that is best characterized in Alzheimer disease, where it begins presymptomatically. This Review discusses the status and prospects of therapeutic strategies for countering neurodegenerative disorders of ageing by improving, preserving or rescuing brain energetics. The approaches described include restoring oxidative phosphorylation and glycolysis, increasing insulin sensitivity, correcting mitochondrial dysfunction, ketone-based interventions, acting via hormones that modulate cerebral energetics, RNA therapeutics and complementary multimodal lifestyle changes.

Potential Applications of PET-Based Novel Quantitative Techniques in Pediatric Diseases and Disorders

The progress made in hybrid PET imaging during the past decades has significantly expanded the role of this modality in both clinical and research applications. Semi-quantitative PET/CT has been the workhorse of clinical PET/CT due to its simplicity and availability. In addition to semi-quantitative PET/CT, volumetric PET and global metabolic activity have recently shown promise in a more accurate assessment of various diseases. PET/CT has been widely used in pediatric oncologic and non-oncologic diseases. Here we have highlighted few of the pitfalls in the quantitative PET/CT and their potential remedies which have potential in PET/CT evaluation of pediatric diseases.

Improved Risk Stratification for Progression from Mild Cognitive Impairment to Alzheimer's Disease with a Multi-Analytical Evaluation of Amyloid-β Positron Emission Tomography

BACKGROUND

Amyloid-β (Aβ) accumulation in brain of patients with suspected Alzheimer's disease (AD) can be assessed by positron emission tomography (PET) in vivo. While visual classification prevails in the clinical routine, semiquantitative PET analyses may enable more reliable evaluation of cases with a visually uncertain, borderline Aβ accumulation.

OBJECTIVE

We evaluated different analysis approaches (visual/semiquantitative) to find the most accurate and sensitive interpretation of Aβ-PET for predicting risk of progression from mild cognitive impairment (MCI) to AD.

METHODS

Based on standard uptake value (SUV) ratios of a cortical-composite volume of interest of 18F-AV45-PET from MCI subjects (n = 396, ADNI database), we compared three different reference region (cerebellar grey matter, CBL; brainstem, BST; white matter, WM) normalizations and the visual read by receiver operator characteristics for calculating a hazard ratio (HR) for progression to Alzheimer's disease dementia (ADD).

RESULTS

During a mean follow-up time of 45.6±13.0 months, 28% of the MCI cases (110/396) converted to ADD. Among the tested methods, the WM reference showed best discriminatory power and progression-risk stratification (HRWM of 4.4 [2.6-7.6]), but the combined results of the visual and semiquantitative analysis with all three reference regions showed an even higher discriminatory power.

CONCLUSION

A multi-analytical composite of visual and semiquantitative reference tissue analyses of 18F-AV45-PET gave improved risk stratification for progression from MCI to ADD relative to performance of single read-outs. This optimized approach is of special interest for prospective treatment trials, which demand a high accuracy.