Clinical validity of brain fluorodeoxyglucose positron emission tomography as a biomarker for Alzheimer's disease in the context of a structured 5-phase development framework

Diagnostic performance of molecular imaging methods in predicting the progression from mild cognitive impairment to dementia: an updated systematic review

PURPOSE

Epidemiological and logistical reasons are slowing the clinical validation of the molecular imaging biomarkers in the initial stages of neurocognitive disorders. We provide an updated systematic review of the recent advances (2017-2022), highlighting methodological shortcomings.

METHODS

Studies reporting the diagnostic accuracy values of the molecular imaging techniques (i.e., amyloid-, tau-, [18F]FDG-PETs, DaT-SPECT, and cardiac [123I]-MIBG scintigraphy) in predicting progression from mild cognitive impairment (MCI) to dementia were selected according to the Preferred Reporting Items for a Systematic Review and Meta-Analysis (PRISMA) method and evaluated with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Main eligibility criteria were as follows: (1) ≥ 50 subjects with MCI, (2) follow-up ≥ 3 years, (3) gold standard: progression to dementia or diagnosis on pathology, and (4) measures of prospective accuracy.

RESULTS

Sensitivity (SE) and specificity (SP) in predicting progression to dementia, mainly to Alzheimer's dementia were 43-100% and 63-94% for [18F]FDG-PET and 64-94% and 48-93% for amyloid-PET. Longitudinal studies were lacking for less common disorders (Dementia with Lewy bodies-DLB and Frontotemporal lobe degeneration-FTLD) and for tau-PET, DaT-SPECT, and [123I]-MIBG scintigraphy. Therefore, the accuracy values from cross-sectional studies in a smaller sample of subjects (n > 20, also including mild dementia stage) were chosen as surrogate outcomes. DaT-SPECT showed 47-100% SE and 71-100% SP in differentiating Lewy body disease (LBD) from non-LBD conditions; tau-PET: 88% SE and 100% SP in differentiating DLB from Posterior Cortical Atrophy. [123I]-MIBG scintigraphy differentiated LBD from non-LBD conditions with 47-100% SE and 71-100% SP.

CONCLUSION

Molecular imaging has a moderate-to-good accuracy in predicting the progression of MCI to Alzheimer's dementia. Longitudinal studies are sparse in non-AD conditions, requiring additional efforts in these settings.

PET Imaging in Dementia: Mini-Review and Canadian Perspective for Clinical Use

PET imaging is increasingly recognized as an important diagnostic tool to investigate patients with cognitive disturbances of possible neurodegenerative origin. PET with 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG), assessing glucose metabolism, provides a measure of neurodegeneration and allows a precise differential diagnosis among the most common neurodegenerative diseases, such as Alzheimer's disease, frontotemporal dementia or dementia with Lewy bodies. PET tracers specific for the pathological deposits characteristic of different neurodegenerative processes, namely amyloid and tau deposits typical of Alzheimer's Disease, allow the visualization of these aggregates in vivo. [18F]FDG and amyloid PET imaging have reached a high level of clinical validity and are since 2022 investigations that can be offered to patients in standard clinical care in most of Canada.This article will briefly review and summarize the current knowledge on these diagnostic tools, their integration into diagnostic algorithms as well as perspectives for future developments.

Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning

Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.

Comparison of 18F-FDG PET and arterial spin labeling MRI in evaluating Alzheimer's disease and amnestic mild cognitive impairment using integrated PET/MR

BACKGROUND

Developing biomarkers for early stage AD patients is crucial. Glucose metabolism measured by 18F-FDG PET is the most common biomarker for evaluating cellular energy metabolism to diagnose AD. Arterial spin labeling (ASL) MRI can potentially provide comparable diagnostic information to 18F-FDG PET in patients with neurodegenerative disorders. However, the conclusions about the diagnostic performance of AD are still controversial between 18F-FDG PET and ASL. This study aims to compare quantitative cerebral blood flow (CBF) and glucose metabolism measured by 18F-FDG PET diagnostic values in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) using integrated PET/MR.

RESULTS

Analyses revealed overlapping between decreased regional rCBF and 18F-FDG PET SUVR in patients with AD compared with NC participants in the bilateral parietotemporal regions, frontal cortex, and cingulate cortex. Compared with NC participants, patients with aMCI exclusively demonstrated lower 18F-FDG PET SUVR in the bilateral temporal cortex, insula cortex, and inferior frontal cortex. Comparison of the rCBF in patients with aMCI and NC participants revealed no significant difference (P > 0.05). The ROC analysis of rCBF in the meta-ROI could diagnose patients with AD (AUC, 0.87) but not aMCI (AUC, 0.61). The specificity of diagnosing aMCI has been improved to 75.56% when combining rCBF and 18F-FDG PET SUVR.

CONCLUSION

ASL could detect similar aberrant patterns of abnormalities compared to 18F-FDG PET in patients with AD compared with NC participants but not in aMCI. The diagnostic efficiency of 18F-FDG-PET for AD and aMCI patients remained higher to ASL. Our findings support that applying 18F-FDG PET may be preferable for diagnosing AD and aMCI.

Harmonization of brain PET images in multi-center PET studies using Hoffman phantom scan

BACKGROUND

Image harmonization has been proposed to minimize heterogeneity in brain PET scans acquired in multi-center studies. However, standard validated methods and software tools are lacking. Here, we assessed the performance of a framework for the harmonization of brain PET scans in a multi-center European clinical trial.

METHOD

Hoffman 3D brain phantoms were acquired in 28 PET systems and reconstructed using site-specific settings. Full Width at Half Maximum (FWHM) of the Effective Image Resolution (EIR) and harmonization kernels were estimated for each scan. The target EIR was selected as the coarsest EIR in the imaging network. Using "Hoffman 3D brain Analysis tool," indicators of image quality were calculated before and after the harmonization: The Coefficient of Variance (COV%), Gray Matter Recovery Coefficient (GMRC), Contrast, Cold-Spot RC, and left-to-right GMRC ratio. A COV% ≤ 15% and Contrast ≥ 2.2 were set as acceptance criteria. The procedure was repeated to achieve a 6-mm target EIR in a subset of scans. The method's robustness against typical dose-calibrator-based errors was assessed.

RESULTS

The EIR across systems ranged from 3.3 to 8.1 mm, and an EIR of 8 mm was selected as the target resolution. After harmonization, all scans met acceptable image quality criteria, while only 13 (39.4%) did before. The harmonization procedure resulted in lower inter-system variability indicators: Mean ± SD COV% (from 16.97 ± 6.03 to 7.86 ± 1.47%), GMRC Inter-Quartile Range (0.040-0.012), and Contrast SD (0.14-0.05). Similar results were obtained with a 6-mm FWHM target EIR. Errors of ± 10% in the DRO activity resulted in differences below 1 mm in the estimated EIR.

CONCLUSION

Harmonizing the EIR of brain PET scans significantly reduced image quality variability while minimally affecting quantitative accuracy. This method can be used prospectively for harmonizing scans to target sharper resolutions and is robust against dose-calibrator errors. Comparable image quality is attainable in brain PET multi-center studies while maintaining quantitative accuracy.

Brain MRI in Progressive Supranuclear Palsy with Richardson's Syndrome and Variant Phenotypes

BACKGROUND

Brain magnetic resonance imaging (MRI) is used to support the diagnosis of progressive supranuclear palsy (PSP). However, the value of visual descriptive, manual planimetric, automatic volumetric MRI markers and fully automatic categorization is unclear, particularly regarding PSP predominance types other than Richardson's syndrome (RS).

OBJECTIVES

To compare different visual reading strategies and automatic classification of T1-weighted MRI for detection of PSP in a typical clinical cohort including PSP-RS and (non-RS) variant PSP (vPSP) patients.

METHODS

Forty-one patients (21 RS, 20 vPSP) and 46 healthy controls were included. Three readers using three strategies performed MRI analysis: exclusively visual reading using descriptive signs (hummingbird, morning-glory, Mickey-Mouse), visual reading supported by manual planimetry measures, and visual reading supported by automatic volumetry. Fully automatic classification was performed using a pre-trained support vector machine (SVM) on the results of atlas-based volumetry.

RESULTS

All tested methods achieved higher specificity than sensitivity. Limited sensitivity was driven to large extent by false negative vPSP cases. Support by automatic volumetry resulted in the highest accuracy (75.1% ± 3.5%) among the visual strategies, but performed not better than the midbrain area (75.9%), the best single planimetric measure. Automatic classification by SVM clearly outperformed all other methods (accuracy, 87.4%), representing the only method to provide clinically useful sensitivity also in vPSP (70.0%).

CONCLUSIONS

Fully automatic classification of volumetric MRI measures using machine learning methods outperforms visual MRI analysis without and with planimetry or volumetry support, particularly regarding diagnosis of vPSP, suggesting the use in settings with a broad phenotypic PSP spectrum. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Automatic covariance pattern analysis outperforms visual reading of 18 F-fluorodeoxyglucose-positron emission tomography (FDG-PET) in variant progressive supranuclear palsy

BACKGROUND

To date, studies on positron emission tomography (PET) with 18 F-fluorodeoxyglucose (FDG) in progressive supranuclear palsy (PSP) usually included PSP cohorts overrepresenting patients with Richardson's syndrome (PSP-RS).

OBJECTIVES

To evaluate FDG-PET in a patient sample representing the broad phenotypic PSP spectrum typically encountered in routine clinical practice.

METHODS

This retrospective, multicenter study included 41 PSP patients, 21 (51%) with RS and 20 (49%) with non-RS variants of PSP (vPSP), and 46 age-matched healthy controls. Two state-of-the art methods for the interpretation of FDG-PET were compared: visual analysis supported by voxel-based statistical testing (five readers) and automatic covariance pattern analysis using a predefined PSP-related pattern.

RESULTS

Sensitivity and specificity of the majority visual read for the detection of PSP in the whole cohort were 74% and 72%, respectively. The percentage of false-negative cases was 10% in the PSP-RS subsample and 43% in the vPSP subsample. Automatic covariance pattern analysis provided sensitivity and specificity of 93% and 83% in the whole cohort. The percentage of false-negative cases was 0% in the PSP-RS subsample and 15% in the vPSP subsample.

CONCLUSIONS

Visual interpretation of FDG-PET supported by voxel-based testing provides good accuracy for the detection of PSP-RS, but only fair sensitivity for vPSP. Automatic covariance pattern analysis outperforms visual interpretation in the detection of PSP-RS, provides clinically useful sensitivity for vPSP, and reduces the rate of false-positive findings. Thus, pattern expression analysis is clinically useful to complement visual reading and voxel-based testing of FDG-PET in suspected PSP. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

A zero-dose synthetic baseline for the personalized analysis of 2-Deoxy-2-[18F]fluoroglucose: Application in Alzheimer’s disease

Purpose

Brain 2-Deoxy-2-[18F]fluoroglucose ([18F]FDG-PET) is widely used in the diagnostic workup of Alzheimer’s disease (AD). Current tools for uptake analysis rely on non-personalized templates, which poses a challenge as decreased glucose uptake could reflect neuronal dysfunction, or heterogeneous brain morphology associated with normal aging. Overcoming this, we propose a deep learning method for synthesizing a personalized [18F]FDG-PET baseline from the patient’s own MRI, and showcase its applicability in detecting AD pathology.

Methods

We included [18F]FDG-PET/MRI data from 123 patients of a local cohort and 600 patients from ADNI. A supervised, adversarial model with two connected Generative Adversarial Networks (GANs) was trained on cognitive normal (CN) patients with transfer-learning to generate full synthetic baseline volumes (sbPET) (192 × 192 × 192) which reflect healthy uptake conditioned on brain anatomy. Synthetic accuracy was measured by absolute relative %-difference (Abs%), relative %-difference (RD%), and peak signal-to-noise ratio (PSNR). Lastly, we deployed the sbPET images in a fully personalized method for localizing metabolic abnormalities.

Results

The model achieved a spatially uniform Abs% of 9.4%, RD% of 0.5%, and a PSNR of 26.3 for CN subjects. The sbPET images conformed to the anatomical information dictated by the MRI and proved robust in presence of atrophy. The personalized abnormality method correctly mapped the pathology of AD subjects while showing little to no anomalies for CN subjects.

Conclusion

This work demonstrated the feasibility of synthesizing fully personalized, healthy-appearing [18F]FDG-PET images. Using these, we showcased a promising application in diagnosing AD, and theorized the potential value of sbPET images in other neuroimaging routines.

FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder

BACKGROUND AND OBJECTIVES

¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) combined with principal component analysis (PCA) has been applied to identify disease-related brain patterns in neurodegenerative disorders such as Parkinson's disease (PD), Dementia with Lewy Bodies (DLB) and Alzheimer's disease (AD). These patterns are used to quantify functional brain changes at the single subject level. This is especially relevant in determining disease progression in idiopathic REM sleep behavior disorder (iRBD), a prodromal stage of PD and DLB. However, the PCA method is limited in discriminating between neurodegenerative conditions. More advanced machine learning algorithms may provide a solution. In this study, we apply Generalized Matrix Learning Vector Quantization (GMLVQ) to FDG-PET scans of healthy controls, and patients with AD, PD and DLB. Scans of iRBD patients, scanned twice with an approximate 4 year interval, were projected into GMLVQ space to visualize their trajectory.

METHODS

We applied a combination of SSM/PCA and GMLVQ as a classifier on FDG-PET data of healthy controls, AD, DLB, and PD patients. We determined the diagnostic performance by performing a ten times repeated ten fold cross validation. We analyzed the validity of the classification system by inspecting the GMLVQ space. First by the projection of the patients into this space. Second by representing the axis, that span this decision space, into a voxel map. Furthermore, we projected a cohort of RBD patients, whom have been scanned twice (approximately 4 years apart), into the same decision space and visualized their trajectories.

RESULTS

The GMLVQ prototypes, relevance diagonal, and decision space voxel maps showed metabolic patterns that agree with previously identified disease-related brain patterns. The GMLVQ decision space showed a plausible quantification of FDG-PET data. Distance traveled by iRBD subjects through GMLVQ space per year (i.e. velocity) was correlated with the change in motor symptoms per year (Spearman's rho =0.62, P=0.004).

CONCLUSION

In this proof-of-concept study, we show that GMLVQ provides a classification of patients with neurodegenerative disorders, and may be useful in future studies investigating speed of progression in prodromal disease stages.

Biomarkers for Alzheimer's Disease: Context of Use, Qualification, and Roadmap for Clinical Implementation

Background and Objectives: The US Food and Drug Administration (FDA) defines a biomarker as a characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention. Biomarkers may be used in clinical care or as drug development tools (DDTs) in clinical trials. The goal of this review and perspective is to provide insight into the regulatory guidance for the use of biomarkers in clinical trials and clinical care. Materials and Methods: We reviewed FDA guidances relevant to biomarker use in clinical trials and their transition to use in clinical care. We identified instructive examples of these biomarkers in Alzheimer's disease (AD) drug development and their application in clinical practice. Results: For use in clinical trials, biomarkers must have a defined context of use (COU) as a risk/susceptibility, diagnostic, monitoring, predictive, prognostic, pharmacodynamic, or safety biomarker. A four-stage process defines the pathway to establish the regulatory acceptance of the COU for a biomarker including submission of a letter of intent, description of the qualification plan, submission of a full qualification package, and acceptance through a qualification recommendation. Biomarkers used in clinical care may be companion biomarkers, in vitro diagnostic devices (IVDs), or laboratory developed tests (LDTs). A five-phase biomarker development process has been proposed to structure the biomarker development process. Conclusions: Biomarkers are increasingly important in drug development and clinical care. Adherence to regulatory guidance for biomarkers used in clinical trials and patient care is required to advance these important drug development and clinical tools.

Validity of cingulate–precuneus–temporo-parietal hypometabolism for single-subject diagnosis of biomarker-proven atypical variants of Alzheimer’s Disease

The aim of our study was to establish empirically to what extent reduced glucose uptake in the precuneus, posterior cingulate and/or temporo-parietal cortex (PCTP), which is thought to indicate brain amyloidosis in patients with dementia or MCI due to Alzheimer’s Disease (AD), permits to distinguish amyloid-positive from amyloid-negative patients with non-classical AD phenotypes at the single-case level. We enrolled 127 neurodegenerative patients with cognitive impairment and a positive (n. 63) or negative (n. 64) amyloid marker (cerebrospinal fluid or amy-PET). Three rating methods of FDG-PET scan were applied: purely qualitative visual interpretation of uptake images (VIUI), and visual reading assisted by a semi-automated and semi-quantitative tool: INLAB, provided by the Italian National Research Council, or Cortex ID Suite, marketed by GE Healthcare. Fourteen scans (11.0%) patients remained unclassified by VIUI or INLAB procedures, therefore, validity values were computed on the remaining 113 cases. The three rating approaches showed good total accuracy (77–78%), good to optimal sensitivity (81–93%), but poorer specificity (62–75%). VIUI showed the highest sensitivity and the lowest specificity, and also the highest proportion of unclassified cases. Cases with asymmetric temporo-parietal hypometabolism and a progressive aphasia or corticobasal clinical profile, in particular, tended to be rated as AD-like, even if biomarkers indicated non-amyloid pathology. Our findings provide formal support to the value of PCTP hypometabolism for single-level diagnosis of amyloid pathophysiology in atypical AD, but also highlight the risk of qualitative assessment to misclassify patients with non-AD PPA or CBS underpinned by asymmetric temporo-parietal hypometabolism.

Lights and Shadows of Cerebrospinal Fluid Biomarkers in the Current Alzheimer's Disease Framework

BACKGROUND

The most significant biomarkers that are included in the Alzheimer's disease (AD) research framework are amyloid-β plaques deposition, p-tau, t-tau, and neurodegeneration.Although cerebrospinal fluid (CSF) biomarkers are included in the most recent AD research criteria, their use is increasing in the routine clinical practice and is applied also to the preclinical phases of AD, including mild cognitive impairment. The role of these biomarkers is still unclear concerning the preclinical stage of AD diagnosis, the CSF methodology, and the costs-benefits of the biomarkers' tests. The controversies regarding the use of biomarkers in the clinical practice are related to the concepts of analytical validity, clinical validity, and clinical utility and to the question of whether they are able to diagnose AD without the support of AD clinical phenotypes.

OBJECTIVE

The objective of the present work is to expose the strengths and weaknesses of the use of CSF biomarkers in the diagnosis of AD in a clinical context.

METHODS

We used PubMed as main source for articles published and the final reference list was generated on the basis of relevance to the topics covered in this work.

RESULTS

The use of CSF biomarkers for AD diagnosis is certainly important but its indication in routine clinical practice, especially for prodromal conditions, needs to be regulated and also contextualized considering the variety of possible clinical AD phenotypes.

CONCLUSION

We suggest that the diagnosis of AD should be understood both as clinical and pathological.

EANM procedure guidelines for brain PET imaging using [18F]FDG, version 3

The present procedural guidelines summarize the current views of the EANM Neuro-Imaging Committee (NIC). The purpose of these guidelines is to assist nuclear medicine practitioners in making recommendations, performing, interpreting, and reporting results of [¹⁸F]FDG-PET imaging of the brain. The aim is to help achieve a high-quality standard of [¹⁸F]FDG brain imaging and to further increase the diagnostic impact of this technique in neurological, neurosurgical, and psychiatric practice. The present document replaces a former version of the guidelines that have been published in 2009. These new guidelines include an update in the light of advances in PET technology such as the introduction of digital PET and hybrid PET/MR systems, advances in individual PET semiquantitative analysis, and current broadening clinical indications (e.g., for encephalitis and brain lymphoma). Further insight has also become available about hyperglycemia effects in patients who undergo brain [¹⁸F]FDG-PET. Accordingly, the patient preparation procedure has been updated. Finally, most typical brain patterns of metabolic changes are summarized for neurodegenerative diseases. The present guidelines are specifically intended to present information related to the European practice. The information provided should be taken in the context of local conditions and regulations.

Vascular endothelial growth factor associated dissimilar cerebrovascular phenotypes in two different mouse models of Alzheimer's Disease

Vascular perturbations and cerebral hypometabolism are emerging as important components of Alzheimer's disease (AD). While various in vivo imaging modalities have been designed to detect changes of cerebral perfusion and metabolism in AD patients and animal models, study results were often heterogenous with respect to imaging techniques and animal models. We therefore evaluated cerebral perfusion and glucose metabolism of two popular transgenic AD mouse strains, TgCRND8 and 5xFAD, at 7 and 12 months-of-age under identical conditions and analyzed possible molecular mechanisms underlying heterogeneous cerebrovascular phenotypes. Results revealed disparate findings in these two strains, displaying important aspects of AD progression. TgCRND8 mice showed significantly decreased cerebral blood flow and glucose metabolism with unchanged cerebral blood volume (CBV) at 12 months-of-age whereas 5xFAD mice showed unaltered glucose metabolism with significant increase in CBV at 12 months-of-age and a biphasic pattern of early hypoperfusion followed by a rebound to normal cerebral blood flow in late disease. Finally, immunoblotting assays suggested that VEGF dependent vascular tone change may restore normoperfusion and increase CBV in 5xFAD.

The validation status of blood biomarkers of amyloid and phospho-tau assessed with the 5-phase development framework for AD biomarkers

PURPOSE

The development of blood biomarkers that reflect Alzheimer's disease (AD) pathophysiology (phosphorylated tau and amyloid-β) has offered potential as scalable tests for dementia differential diagnosis and early detection. In 2019, the Geneva AD Biomarker Roadmap Initiative included blood biomarkers in the systematic validation of AD biomarkers.

METHODS

A panel of experts convened in November 2019 at a two-day workshop in Geneva. The level of maturity (fully achieved, partly achieved, preliminary evidence, not achieved, unsuccessful) of blood biomarkers was assessed based on the Biomarker Roadmap methodology and discussed fully during the workshop which also evaluated cerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers.

RESULTS

Plasma p-tau has shown analytical validity (phase 2 primary aim 1) and first evidence of clinical validity (phase 3 primary aim 1), whereas the maturity level for Aβ remains to be partially achieved. Full and partial achievement has been assigned to p-tau and Aβ, respectively, in their associations to ante-mortem measures (phase 2 secondary aim 2). However, only preliminary evidence exists for the influence of covariates, assay comparison and cut-off criteria.

CONCLUSIONS

Despite the relative infancy of blood biomarkers, in comparison to CSF biomarkers, much has already been achieved for phases 1 through 3 - with p-tau having greater success in detecting AD and predicting disease progression. However, sufficient data about the effect of covariates on the biomarker measurement is lacking. No phase 4 (real-world performance) or phase 5 (assessment of impact/cost) aim has been tested, thus not achieved.

Clinical validity of second-generation tau PET tracers as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework

PURPOSE

In 2017, the Geneva Alzheimer's disease (AD) strategic biomarker roadmap initiative proposed a framework of the systematic validation AD biomarkers to harmonize and accelerate their development and implementation in clinical practice. Here, we use this framework to examine the translatability of the second-generation tau PET tracers into the clinical context.

METHODS

All available literature was systematically searched based on a set of search terms that related independently to analytic validity (phases 1-2), clinical validity (phase 3-4), and clinical utility (phase 5). The progress on each of the phases was determined based on scientific criteria applied for each phase and coded as fully, partially, preliminary achieved or not achieved at all.

RESULTS

The validation of the second-generation tau PET tracers has successfully passed the analytical phase 1 of the strategic biomarker roadmap. Assay definition studies showed evidence on the superiority over first-generation tau PET tracers in terms of off-target binding. Studies have partially achieved the primary aim of the analytical validity stage (phase 2), and preliminary evidence has been provided for the assessment of covariates on PET signal retention. Studies investigating of the clinical validity in phases 3, 4, and 5 are still underway.

CONCLUSION

The current literature provides overall preliminary evidence on the establishment of the second-generation tau PET tracers into the clinical context, thereby successfully addressing some methodological issues from the tau PET tracer of the first generation. Nevertheless, bigger cohort studies, longitudinal follow-up, and examination of diverse disease population are still needed to gauge their clinical validity.

PET Neuroimaging of Alzheimer's Disease: Radiotracers and Their Utility in Clinical Research

Alzheimer's Disease (AD), the leading cause of senile dementia, is a progressive neurodegenerative disorder affecting millions of people worldwide and exerting tremendous socioeconomic burden on all societies. Although definitive diagnosis of AD is often made in the presence of clinical manifestations in late stages, it is now universally believed that AD is a continuum of disease commencing from the preclinical stage with typical neuropathological alterations appearing decades prior to its first symptom, to the prodromal stage with slight symptoms of amnesia (amnestic mild cognitive impairment, aMCI), and then to the terminal stage with extensive loss of basic cognitive functions, i.e., AD-dementia. Positron emission tomography (PET) radiotracers have been developed in a search to meet the increasing clinical need of early detection and treatment monitoring for AD, with reference to the pathophysiological targets in Alzheimer's brain. These include the pathological aggregations of misfolded proteins such as β-amyloid (Aβ) plagues and neurofibrillary tangles (NFTs), impaired neurotransmitter system, neuroinflammation, as well as deficient synaptic vesicles and glucose utilization. In this article we survey the various PET radiotracers available for AD imaging and discuss their clinical applications especially in terms of early detection and cognitive relevance.

Brain Glucose Metabolism in Health, Obesity, and Cognitive Decline-Does Insulin Have Anything to Do with It? A Narrative Review

Imaging brain glucose metabolism with fluorine-labelled fluorodeoxyglucose ([¹⁸F]-FDG) positron emission tomography (PET) has long been utilized to aid the diagnosis of memory disorders, in particular in differentiating Alzheimer’s disease (AD) from other neurological conditions causing cognitive decline. The interest for studying brain glucose metabolism in the context of metabolic disorders has arisen more recently. Obesity and type 2 diabetes—two diseases characterized by systemic insulin resistance—are associated with an increased risk for AD. Along with the well-defined patterns of fasting [¹⁸F]-FDG-PET changes that occur in AD, recent evidence has shown alterations in fasting and insulin-stimulated brain glucose metabolism also in obesity and systemic insulin resistance. Thus, it is important to clarify whether changes in brain glucose metabolism are just an epiphenomenon of the pathophysiology of the metabolic and neurologic disorders, or a crucial determinant of their pathophysiologic cascade. In this review, we discuss the current knowledge regarding alterations in brain glucose metabolism, studied with [¹⁸F]-FDG-PET from metabolic disorders to AD, with a special focus on how manipulation of insulin levels affects brain glucose metabolism in health and in systemic insulin resistance. A better understanding of alterations in brain glucose metabolism in health, obesity, and neurodegeneration, and the relationships between insulin resistance and central nervous system glucose metabolism may be an important step for the battle against metabolic and cognitive disorders.

Clinical validity of increased cortical binding of tau ligands of the THK family and PBB3 on PET as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework

PURPOSE

The research community has focused on defining reliable biomarkers for the early detection of the pathological hallmarks of Alzheimer's disease (AD). In 2017, the Geneva AD Biomarker Roadmap initiative adapted the framework for the systematic validation of oncological biomarkers to AD, with the aim to accelerate their development and implementation in clinical practice. The aim of this work was to assess the validation status of tau PET ligands of the THK family and PBB3 as imaging biomarkers for AD, based on the Biomarker Roadmap methodology.

METHODS

A panel of experts in AD biomarkers convened in November 2019 at a 2-day workshop in Geneva. The level of clinical validity of tau PET ligands of the THK family and PBB3 was assessed based on the 5-phase development framework before the meeting and discussed during the workshop.

RESULTS

PET radioligands of the THK family discriminate well between healthy controls and patients with AD dementia (phase 2; partly achieved) and recent evidence suggests an accurate diagnostic accuracy at the mild cognitive impairment (MCI) stage of the disease (phase 3; partly achieved). The phases 2 and 3 were considered not achieved for PBB3 since no evidence exists about the ligand's diagnostic accuracy. Preliminary evidence exists about the secondary aims of each phase for all ligands.

CONCLUSION

Much work remains for completing the aims of phases 2 and 3 and replicating the available evidence. However, it is unlikely that the validation process for these tracers will be completed, given the presence of off-target binding and the development of second-generation tracers with improved binding and pharmacokinetic properties.

The strategic biomarker roadmap for the validation of Alzheimer's diagnostic biomarkers: methodological update

Background

The 2017 Alzheimer’s disease (AD) Strategic Biomarker Roadmap (SBR) structured the validation of AD diagnostic biomarkers into 5 phases, systematically assessing analytical validity (Phases 1–2), clinical validity (Phases 3–4), and clinical utility (Phase 5) through primary and secondary Aims. This framework allows to map knowledge gaps and research priorities, accelerating the route towards clinical implementation. Within an initiative aimed to assess the development of biomarkers of tau pathology, we revised this methodology consistently with progress in AD research.

Methods

We critically appraised the adequacy of the 2017 Biomarker Roadmap within current diagnostic frameworks, discussed updates at a workshop convening the Alzheimer’s Association and 8 leading AD biomarker research groups, and detailed the methods to allow consistent assessment of aims achievement for tau and other AD diagnostic biomarkers.

Results

The 2020 update applies to all AD diagnostic biomarkers. In Phases 2–3, we admitted a greater variety of study designs (e.g., cross-sectional in addition to longitudinal) and reference standards (e.g., biomarker confirmation in addition to clinical progression) based on construct (in addition to criterion) validity. We structured a systematic data extraction to enable transparent and formal evidence assessment procedures. Finally, we have clarified issues that need to be addressed to generate data eligible to evidence-to-decision procedures.

Discussion

This revision allows for more versatile and precise assessment of existing evidence, keeps up with theoretical developments, and helps clinical researchers in producing evidence suitable for evidence-to-decision procedures. Compliance with this methodology is essential to implement AD biomarkers efficiently in clinical research and diagnostics.

2020 update on the clinical validity of cerebrospinal fluid amyloid, tau, and phospho-tau as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework

Purpose

In the last decade, the research community has focused on defining reliable biomarkers for the early detection of Alzheimer’s disease (AD) pathology. In 2017, the Geneva AD Biomarker Roadmap Initiative adapted a framework for the systematic validation of oncological biomarkers to cerebrospinal fluid (CSF) AD biomarkers—encompassing the 42 amino-acid isoform of amyloid-β (Aβ42), phosphorylated-tau (P-tau), and Total-tau (T-tau)—with the aim to accelerate their development and clinical implementation. The aim of this work is to update the current validation status of CSF AD biomarkers based on the Biomarker Roadmap methodology.

Methods

A panel of experts in AD biomarkers convened in November 2019 at a 2-day workshop in Geneva. The level of maturity (fully achieved, partly achieved, preliminary evidence, not achieved, unsuccessful) of CSF AD biomarkers was assessed based on the Biomarker Roadmap methodology before the meeting and presented and discussed during the workshop.

Results

By comparison to the previous 2017 Geneva Roadmap meeting, the primary advances in CSF AD biomarkers have been in the area of a unified protocol for CSF sampling, handling and storage, the introduction of certified reference methods and materials for Aβ42, and the introduction of fully automated assays. Additional advances have occurred in the form of defining thresholds for biomarker positivity and assessing the impact of covariates on their discriminatory ability.

Conclusions

Though much has been achieved for phases one through three, much work remains in phases four (real world performance) and five (assessment of impact/cost). To a large degree, this will depend on the availability of disease-modifying treatments for AD, given these will make accurate and generally available diagnostic tools key to initiate therapy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05258-7.

Outcomes of clinical utility in amyloid-PET studies: state of art and future perspectives

PURPOSE

To review how outcomes of clinical utility are operationalized in current amyloid-PET validation studies, to prepare for formal assessment of clinical utility of amyloid-PET-based diagnosis.

METHODS

Systematic review of amyloid-PET research studies published up to April 2020 that included outcomes of clinical utility. We extracted and analyzed (a) outcome categories, (b) their definition, and (c) their methods of assessment.

RESULTS

Thirty-two studies were eligible. (a) Outcome categories were clinician-centered (found in 25/32 studies, 78%), patient-/caregiver-centered (in 9/32 studies, 28%), and health economics-centered (5/32, 16%). (b) Definition: Outcomes were mainly defined by clinical researchers; only the ABIDE study expressly included stakeholders in group discussions. Clinician-centered outcomes mainly consisted of incremental diagnostic value (25/32, 78%) and change in patient management (17/32, 53%); patient-/caregiver-centered outcomes considered distress after amyloid-pet-based diagnosis disclosure (8/32, 25%), including quantified burden of procedure for patients' outcomes (n = 8) (1/8, 12.5%), impact of disclosure of results (6/8, 75%), and psychological implications of biomarker-based diagnosis (75%); and health economics outcomes focused on costs to achieve a high-confidence etiological diagnosis (5/32, 16%) and impact on quality of life (1/32, 3%). (c) Assessment: all outcome categories were operationalized inconsistently across studies, employing 26 different tools without formal rationale for selection.

CONCLUSION

Current studies validating amyloid-PET already assessed outcomes for clinical utility, although non-clinician-based outcomes were inconsistent. A wider participation of stakeholders may help produce a more thorough and systematic definition and assessment of outcomes of clinical utility and help collect evidence informing decisions on reimbursement of amyloid-PET.

A Comparison of Two Statistical Mapping Tools for Automated Brain FDG-PET Analysis in Predicting Conversion to Alzheimer's Disease in Subjects with Mild Cognitive Impairment

OBJECTIVE

Automated voxel-based analysis methods are used to detect cortical hypometabolism typical of Alzheimer's Disease (AD) on FDG-PET brain scans. We compared the accuracy of two clinically validated tools for their ability to identify those MCI subjects progressing to AD at followup, to evaluate the impact of the analysis method on FDG-PET diagnostic performance.

METHODS

SPMGrid and BRASS (Hermes Medical Solutions, Stockholm, Sweden) were tested on 131 MCI and elderly healthy controls from the EADC PET dataset. The concordance between the tools was tested by correlating the quantitative parameters (z- and t-values), calculated by the two software tools, and by measuring the topographical overlap of the abnormal regions (Dice score). Three independent expert readers blindly assigned a diagnosis based on the two map sets. We used conversion to AD dementia as the gold standard.

RESULTS

The t-map and z-map calculated with SPMGrid and BRASS, respectively, showed a good correlation (R > .50) for the majority of individual cases (128/131) and for the majority of selected regions of interest (ROIs) (98/116). The overlap of the hypometabolic patterns from the two tools was, however, poor (Dice score .36). The diagnostic performance was comparable, with BRASS showing significantly higher sensitivity (.82 versus .59) and SPMGrid showing higher specificity (.87 versus .52).

CONCLUSION

Despite similar diagnostic performance in predicting conversion to AD in MCI subjects, the two tools showed significant differences, and the maps provided by the tools showed limited overlap. These results underline the urgency for standardization across FDG-PET analysis methods for their use in clinical practice.

Clinical validity of increased cortical uptake of [18F]flortaucipir on PET as a biomarker for Alzheimer's disease in the context of a structured 5-phase biomarker development framework

PURPOSE

In 2017, the Geneva Alzheimer's disease (AD) Biomarker Roadmap initiative adapted the framework of the systematic validation of oncological diagnostic biomarkers to AD biomarkers, with the aim to accelerate their development and implementation in clinical practice. With this work, we assess the maturity of [¹⁸F]flortaucipir PET and define its research priorities.

METHODS

The level of maturity of [¹⁸F]flortaucipir was assessed based on the AD Biomarker Roadmap. The framework assesses analytical validity (phases 1-2), clinical validity (phases 3-4), and clinical utility (phase 5).

RESULTS

The main aims of phases 1 (rationale for use) and 2 (discriminative ability) have been achieved. [¹⁸F]Flortaucipir binds with high affinity to paired helical filaments of tau and has favorable kinetic properties and excellent discriminative accuracy for AD. The majority of secondary aims of phase 2 were fully achieved. Multiple studies showed high correlations between ante-mortem [¹⁸F]flortaucipir PET and post-mortem tau (as assessed by histopathology), and also the effects of covariates on tracer binding are well studied. The aims of phase 3 (early detection ability) were only partially or preliminarily achieved, and the aims of phases 4 and 5 were not achieved.

CONCLUSION

Current literature provides partial evidence for clinical utility of [¹⁸F]flortaucipir PET. The aims for phases 1 and 2 were mostly achieved. Phase 3 studies are currently ongoing. Future studies including representative MCI populations and a focus on healthcare outcomes are required to establish full maturity of phases 4 and 5.

CCCDTD5: Clinical role of neuroimaging and liquid biomarkers in patients with cognitive impairment

Since 1989, four Canadian Consensus Conferences on the Diagnosis and Treatment of Dementia (CCCDTDs) have provided evidence-based dementia diagnostic and treatment guidelines for Canadian clinicians and researchers. We present the results from the Neuroimaging and Fluid Biomarkers Group of the 5th CCCDTD (CCCDTD5), which addressed topics chosen by the steering committee to reflect advances in the field and build on our previous guidelines. Recommendations on Imaging and Fluid Biomarker Use from this Conference cover a series of different fields. Prior structural imaging recommendations for both computerized tomography (CT) and magnetic resonance imaging (MRI) remain largely unchanged, but MRI is now more central to the evaluation than before, with suggested sequences described here. The use of visual rating scales for both atrophy and white matter anomalies is now included in our recommendations. Molecular imaging with [18F]-fluorodeoxyglucose ([18F]-FDG) Positron Emisson Tomography (PET) or [99mTc]-hexamethylpropyleneamine oxime/ethylene cysteinate dimer ([99mTc]-HMPAO/ECD) Single Photon Emission Tomography (SPECT), should now decidedly favor PET. The value of [18F]-FDG PET in the assessment of neurodegenerative conditions has been established with greater certainty since the previous conference, and it has now been recognized as a useful biomarker to establish the presence of neurodegeneration by a number of professional organizations around the world. Furthermore, the role of amyloid PET has been clarified and our recommendations follow those from other groups in multiple countries. SPECT with [123I]-ioflupane (DaTscanTM) is now included as a useful study in differentiating Alzheimer's disease (AD) from Lewy body disease. Finally, liquid biomarkers are in a rapid phase of development and, could lead to a revolution in the assessment AD and other neurodegenerative conditions at a reasonable cost. We hope these guidelines will be useful for clinicians, researchers, policy makers, and the lay public, to inform a current and evidence-based approach to the use of neuroimaging and liquid biomarkers in clinical dementia evaluation and management.

Psychedelics as a Treatment for Alzheimer's Disease Dementia

Currently, there are no disease-modifying treatments for Alzheimer's disease (AD) or any other dementia subtype. The renaissance in psychedelic research in recent years, in particular studies involving psilocybin and lysergic acid diethylamide (LSD), coupled with anecdotal reports of cognitive benefits from micro-dosing, suggests that they may have a therapeutic role in a range of psychiatric and neurological conditions due to their potential to stimulate neurogenesis, provoke neuroplastic changes and reduce neuroinflammation. This inevitably makes them interesting candidates for therapeutics in dementia. This mini-review will look at the basic science and current clinical evidence for the role of psychedelics in treating dementia, especially early AD, with a particular focus on micro-dosing of the classical psychedelics LSD and psilocybin.

Amyloidogenic Nanoplaques in Blood Serum of Patients with Alzheimer's Disease Revealed by Time-Resolved Thioflavin T Fluorescence Intensity Fluctuation Analysis

BACKGROUND

Biomarkers are central to current research on molecular mechanisms underlying Alzheimer's disease (AD). Their further development is of paramount importance for understanding pathophysiological processes that eventually lead to disease onset. Biomarkers are also crucial for early disease detection, before clinical manifestation, and for development of new disease modifying therapies.

OBJECTIVE

The overall aim of this work is to develop a minimally invasive method for fast, ultra-sensitive and cost-effective detection of structurally modified peptide/protein self-assemblies in the peripheral blood and in other biological fluids. Specifically, we focus here on using this method to detect structured amyloidogenic oligomeric aggregates in the blood serum of apparently healthy individuals and patients in early AD stage, and measure their concentration and size.

METHODS

Time-resolved detection of Thioflavin T (ThT) fluorescence intensity fluctuations in a sub-femtoliter observation volume element was used to identify in blood serum ThT-active structured amyloidogenic oligomeric aggregates, hereafter called nanoplaques, and measure with single-particle sensitivity their concentration and size.

RESULTS

The concentration and size of structured amyloidogenic nanoplaques are significantly higher in the blood serum of individuals diagnosed with AD than in control subjects.

CONCLUSION

A new method with the ultimate, single-particle sensitivity was successfully developed. The proposed approach neither relies on the use of immune-based probes, nor on the use of radiotracers, signal-amplification or protein separation techniques, and provides a minimally invasive test for fast and cost-effective early determination of structurally modified peptides/proteins in the peripheral blood, as shown here, but also in other biological fluids.

Microglial activation and tau burden predict cognitive decline in Alzheimer's disease

Tau pathology, neuroinflammation, and neurodegeneration are key aspects of Alzheimer's disease. Understanding whether these features predict cognitive decline, alone or in combination, is crucial to develop new prognostic measures and enhanced stratification for clinical trials. Here, we studied how baseline assessments of in vivo tau pathology (measured by 18F-AV-1451 PET), neuroinflammation (measured by 11C-PK11195 PET) and brain atrophy (derived from structural MRI) predicted longitudinal cognitive changes in patients with Alzheimer's disease pathology. Twenty-six patients (n = 12 with clinically probable Alzheimer's dementia and n = 14 with amyloid-positive mild cognitive impairment) and 29 healthy control subjects underwent baseline assessment with 18F-AV-1451 PET, 11C-PK11195 PET, and structural MRI. Cognition was examined annually over the subsequent 3 years using the revised Addenbrooke's Cognitive Examination. Regional grey matter volumes, and regional binding of 18F-AV-1451 and 11C-PK11195 were derived from 15 temporo-parietal regions characteristically affected by Alzheimer's disease pathology. A principal component analysis was used on each imaging modality separately, to identify the main spatial distributions of pathology. A latent growth curve model was applied across the whole sample on longitudinal cognitive scores to estimate the rate of annual decline in each participant. We regressed the individuals' estimated rate of cognitive decline on the neuroimaging components and examined univariable predictive models with single-modality predictors, and a multi-modality predictive model, to identify the independent and combined prognostic value of the different neuroimaging markers. Principal component analysis identified a single component for the grey matter atrophy, while two components were found for each PET ligand: one weighted to the anterior temporal lobe, and another weighted to posterior temporo-parietal regions. Across the whole-sample, the single-modality models indicated significant correlations between the rate of cognitive decline and the first component of each imaging modality. In patients, both stepwise backward elimination and Bayesian model selection revealed an optimal predictive model that included both components of 18F-AV-1451 and the first (i.e. anterior temporal) component for 11C-PK11195. However, the MRI-derived atrophy component and demographic variables were excluded from the optimal predictive model of cognitive decline. We conclude that temporo-parietal tau pathology and anterior temporal neuroinflammation predict cognitive decline in patients with symptomatic Alzheimer's disease pathology. This indicates the added value of PET biomarkers in predicting cognitive decline in Alzheimer's disease, over and above MRI measures of brain atrophy and demographic data. Our findings also support the strategy for targeting tau and neuroinflammation in disease-modifying therapy against Alzheimer's disease.

Impairment of Glycolysis-Derived l-Serine Production in Astrocytes Contributes to Cognitive Deficits in Alzheimer's Disease

Alteration of brain aerobic glycolysis is often observed early in the course of Alzheimer's disease (AD). Whether and how such metabolic dysregulation contributes to both synaptic plasticity and behavioral deficits in AD is not known. Here, we show that the astrocytic l-serine biosynthesis pathway, which branches from glycolysis, is impaired in young AD mice and in AD patients. l-serine is the precursor of d-serine, a co-agonist of synaptic NMDA receptors (NMDARs) required for synaptic plasticity. Accordingly, AD mice display a lower occupancy of the NMDAR co-agonist site as well as synaptic and behavioral deficits. Similar deficits are observed following inactivation of the l-serine synthetic pathway in hippocampal astrocytes, supporting the key role of astrocytic l-serine. Supplementation with l-serine in the diet prevents both synaptic and behavioral deficits in AD mice. Our findings reveal that astrocytic glycolysis controls cognitive functions and suggest oral l-serine as a ready-to-use therapy for AD.

Direct prospective comparison of 18F-FDG PET and arterial spin labelling MR using simultaneous PET/MR in patients referred for diagnosis of dementia

PURPOSE

¹⁸F-FDG PET is routinely used as an imaging marker in the early and differential diagnosis of dementing disorders and has incremental value over the clinical neurological and neuropsychological evaluation. Perfusion MR imaging by means of arterial spin labelling (ASL) is an alternative modality to indirectly measure neuronal functioning and could be used as complement measurement in a single MR session in the workup of dementia. Using simultaneous PET-MR, we performed a direct head-to-head comparison between enhanced multiplane tagging ASL (eASL) and ¹⁸F-FDG PET in a true clinical context of subjects referred for suspicion of neurodegenerative dementia.

METHODS

Twenty-seven patients underwent a 20-min ¹⁸F-FDG PET/MR and simultaneously acquired eASL on a GE Signa PET/MR. Data were compared with 30 screened age- and gender-matched healthy controls. Both integral eASL and ¹⁸F-FDG datasets were analysed visually by two readers unaware of the final clinical diagnosis, either in normal/abnormal classes, or full differential diagnosis (normal, Alzheimer type dementia [AD], dementia with Lewy Bodies [LBD], frontotemporal dementia [FTD] or other). Reader confidence was assessed with a rating scale (range 1-4). Data were also analysed semiquantitatively by VOI and voxel-based analyses.

RESULTS

The ground truth diagnosis for the patient group resulted in 14 patients with a neurodegenerative cognitive disorder (AD, FTD, LBD) and 13 patients with no arguments for an underlying neurodegenerative cause. Visual analysis resulted in equal specificity (0.70) for differentiating normal and abnormal cases between the two modalities, but in a higher sensitivity (0.93), confidence rating (0.64) and interobserver agreement for ¹⁸F-FDG PET compared with eASL. The same was true for assigning a specific differential diagnosis (sensitivity: and 0.39 for ¹⁸F-FDG PET and eASL, respectively). Semiquantitative analyses revealed prototypical patterns for AD and FTD, with both higher volumes of abnormality and intensity differences on ¹⁸F-FDG PET.

CONCLUSION

In a direct head-to-head comparison on a simultaneous GE Signa PET/MR, ¹⁸F-FDG PET performed better compared with ASL in terms of sensitivity and reader confidence, as well as volume and intensity of abnormalities. However, using pure semiquantitative analysis, similar diagnostic accuracy between the two modalities was obtained. Therefore, ASL may still serve as complement to neuroreceptor or protein deposition PET studies when a single simultaneous investigation is warranted.

Diagnosis of Mild Cognitive Impairment Due to Alzheimer's Disease with Transcranial Magnetic Stimulation

BACKGROUND

Considering the increasing evidence that disease-modifying treatments for Alzheimer's disease (AD) must be administered early in the disease course, the development of diagnostic tools capable of accurately identifying AD at early disease stages has become a crucial target. In this view, transcranial magnetic stimulation (TMS) has become an effective tool to discriminate between different forms of neurodegenerative dementia.

OBJECTIVE

To determine whether a TMS multi-paradigm approach can be used to correctly identify mild cognitive impairment (MCI) due to AD (AD MCI).

METHODS

A sample of 69 subjects with MCI were included and classified as AD MCI or MCI unlikely due to AD (non-AD MCI) based on 1) extensive neurological and neuropsychological evaluation, 2) MRI imaging, and 3) cerebrospinal fluid analysis or/and amyloid PET imaging. A paired-pulse TMS multi-paradigm approach assessing short interval intracortical inhibition-facilitation (SICI-ICF), dependent on GABAergic and glutamatergic intracortical circuits, respectively, and short latency afferent inhibition (SAI), dependent on cholinergic circuits, was performed.

RESULTS

We observed a significant impairment of SAI and unimpaired SICI and ICF in AD MCI as compared to non-AD MCI. According to ROC curve analysis, the SICI-ICF / SAI index differentiated AD MCI from non-AD MCI with a specificity of 87.9% and a sensitivity of 94.4%.

CONCLUSIONS

The assessment of intracortical connectivity with TMS could aid in the characterization of MCI subtypes, correctly identifying AD pathophysiology. TMS can be proposed as an adjunctive, non-invasive, inexpensive, and time-saving screening tool in MCI differential diagnosis.

18F-FDG PET for Prediction of Conversion to Alzheimer's Disease Dementia in People with Mild Cognitive Impairment: An Updated Systematic Review of Test Accuracy

Background:

A previous Cochrane systematic review concluded there is insufficient evidence to support the routine use of ¹⁸F-FDG PET in clinical practice in people with mild cognitive impairment (MCI).

Objectives:

To update the evidence and reassess the accuracy of ¹⁸F-FDG-PET for detecting people with MCI at baseline who would clinically convert to Alzheimer’s disease (AD) dementia at follow-up.

Methods:

A systematic review including comprehensive search of electronic databases from January 2013 to July 2017, to update original searches (1999 to 2013). All key review steps, including quality assessment using QUADAS 2, were performed independently and blindly by two review authors. Meta-analysis could not be conducted due to heterogeneity across studies.

Results:

When all included studies were examined across all semi-quantitative and quantitative metrics, exploratory analysis for conversion of MCI to AD dementia (n = 24) showed highly variable accuracy; half the studies failed to meet four or more of the seven sets of QUADAS 2 criteria. Variable accuracy for all metrics was also found across eleven newly included studies published in the last 5 years (range: sensitivity 56–100%, specificity 24–100%). The most consistently high sensitivity and specificity values (approximately ≥80%) were reported for the sc-SPM (single case statistical parametric mapping) metric in 6 out of 8 studies.

Conclusion:

Systematic and comprehensive assessment of studies of ¹⁸FDG-PET for prediction of conversion from MCI to AD dementia reveals many studies have methodological limitations according to Cochrane diagnostic test accuracy gold standards, and shows accuracy remains highly variable, including in the most recent studies. There is some evidence, however, of higher and more consistent accuracy in studies using computer aided metrics, such as sc-SPM, in specialized clinical settings. Robust, methodologically sound prospective longitudinal cohort studies with long (≥5 years) follow-up, larger consecutive samples, and defined baseline threshold(s) are needed to test these promising results. Further evidence of the clinical validity and utility of ¹⁸F-FDG PET in people with MCI is needed.

Evaluation of Task-Related Brain Activity: Is There a Role for 18F FDG-PET Imaging?

Positron emission tomography (PET) with 2-[18F]-fluorodeoxyglucose (FDG) has been widely used for the evaluation of cortical glucose metabolism in several neurodegenerative disorders while its potential role in the evaluation of cortical and subcortical activity during a task in the healthy and pathological brain still remains to be a matter of debate. Few studies have been carried out in order to investigate the potential role of this radiotracer for the evaluation of brain glucose consumption during dynamic brain activation. The aim of this review is to provide a general overview of the applications of FDG-PET in the evaluation of cortical activation at rest and during tasks, describing first the physiological basis of FDG distribution in brain and its kinetic in vivo. An overview of the imaging protocols and image interpretation will be provided as well. As a last aspect, the results of the main studies in this field will be summarized and the results of PET findings performed in healthy subjects and patients suffering from various diseases will be reported.

Factors affecting the harmonization of disease-related metabolic brain pattern expression quantification in [18F]FDG-PET (PETMETPAT)

Introduction

The implementation of spatial-covariance [¹⁸F]fluorodeoxyglucose positron emission tomography–based disease-related metabolic brain patterns as biomarkers has been hampered by intercenter imaging differences. Within the scope of the JPND-PETMETPAT working group, we illustrate the impact of these differences on Parkinson's disease–related pattern (PDRP) expression scores.

Methods

Five healthy controls, 5 patients with idiopathic rapid eye movement sleep behavior disorder, and 5 patients with Parkinson's disease were scanned on one positron emission tomography/computed tomography system with multiple image reconstructions. In addition, one Hoffman 3D Brain Phantom was scanned on several positron emission tomography/computed tomography systems using various reconstructions. Effects of image contrast on PDRP scores were also examined.

Results

Human and phantom raw PDRP scores were systematically influenced by scanner and reconstruction effects. PDRP scores correlated inversely to image contrast. A Gaussian spatial filter reduced contrast while decreasing intercenter score differences.

Discussion

Image contrast should be considered in harmonization efforts. A Gaussian filter may reduce noise and intercenter effects without sacrificing sensitivity. Phantom measurements will be important for correcting PDRP score offsets.

Plasma MicroRNAs Are Altered Early and Consistently in a Mouse Model of Tauopathy

Pathological accumulation of tau protein in brain cells is the hallmark of a group of neurodegenerative diseases called tauopathies. Accumulation of tau protein begins years before the onset of symptoms, which include deficits in cognition, behavior and movement. The pre-symptomatic phase of tauopathy may be the best time to deliver disease-modifying treatments, but this is only possible if prognostic, pre-symptomatic biomarkers are identified. Here we describe the profiling of blood plasma microRNAs in a mouse model of tauopathy, in order to identify biomarkers of pre-symptomatic tauopathy. Circulating RNAs were isolated from blood plasma of 16-week-old and 53-week-old hTau mice and age-matched wild type controls (n = 28). Global microRNA profiling was performed using small RNA sequencing (Illumina) and selected microRNAs were validated using individual TaqMan RT-qPCR. The area under the receiver operating characteristic curve (AUC) was used to evaluate discriminative accuracy. We identified three microRNAs (miR-150-5p, miR-155-5p, miR-375-3p) that were down-regulated in 16-week-old hTau mice, which do not yet exhibit a behavioral phenotype and therefore represent pre-symptomatic tauopathy. The discriminative accuracy was AUC 0.98, 0.95 and 1, respectively. Down-regulation of these microRNAs persisted at 53 weeks of age, when hTau mice exhibit cognitive deficits and advanced neuropathology. Bioinformatic analysis showed that these three microRNAs converge on pathways associated with neuronal signaling and phosphorylation of tau. Thus, these circulating microRNAs appear to reflect neuropathological change and are promising candidates in the development of biomarkers of pre-symptomatic tauopathy.

Dementia in Down syndrome: unique insights for Alzheimer disease research

Virtually all adults with Down syndrome (DS) show the neuropathological changes of Alzheimer disease (AD) by the age of 40 years. This association is partially due to overexpression of amyloid precursor protein, encoded by APP, as a result of the location of this gene on chromosome 21. Amyloid-β accumulates in the brain across the lifespan of people with DS, which provides a unique opportunity to understand the temporal progression of AD and the epigenetic factors that contribute to the age of dementia onset. This age dependency in the development of AD in DS can inform research into the presentation of AD in the general population, in whom a longitudinal perspective of the disease is not often available. Comparison of the risk profiles, biomarker profiles and genetic profiles of adults with DS with those of individuals with AD in the general population can help to determine common and distinct pathways as well as mechanisms underlying increased risk of dementia. This Review evaluates the similarities and differences between the pathological cascades and genetics underpinning DS and AD with the aim of providing a platform for common exploration of these disorders.

Brain glucose metabolism in Lewy body dementia: implications for diagnostic criteria

BACKGROUND

[18F]FDG-PET hypometabolism patterns are indicative of different neurodegenerative conditions, even from the earliest disease phase. This makes [18F]FDG-PET a valuable tool in the diagnostic workup of neurodegenerative diseases. The utility of [18F]FDG-PET in dementia with Lewy bodies (DLB) needs further validation by considering large samples of patients and disease comparisons and applying state-of-the-art statistical methods. Here, we aimed to provide an extensive validation of the [18F]FDG-PET metabolic signatures in supporting DLB diagnosis near the first clinical assessment, which is characterized by high diagnostic uncertainty, at the single-subject level.

METHODS

In this retrospective study, we included N = 72 patients with heterogeneous clinical classification at entry (mild cognitive impairment, atypical parkinsonisms, possible DLB, probable DLB, and other dementias) and an established diagnosis of DLB at a later follow-up. We generated patterns of [18F]FDG-PET hypometabolism in single cases by using a validated voxel-wise analysis (p < 0.05, FWE-corrected). The hypometabolism patterns were independently classified by expert raters blinded to any clinical information. The final clinical diagnosis at follow-up (2.94 ± 1.39 [0.34-6.04] years) was considered as the diagnostic reference and compared with clinical classification at entry and with [18F]FDG-PET classification alone. In addition, we calculated the diagnostic accuracy of [18F]FDG-PET maps in the differential diagnosis of DLB with Alzheimer's disease dementia (ADD) (N = 60) and Parkinson's disease (PD) (N = 36).

RESULTS

The single-subject [18F]FDG-PET hypometabolism pattern, showing temporo-parietal and occipital involvement, was highly consistent across DLB cases. Clinical classification at entry produced several misclassifications with an agreement of only 61.1% with the diagnostic reference. On the contrary, [18F]FDG-PET hypometabolism maps alone accurately predicted diagnosis of DLB at follow-up (88.9%). The high power of the [18F]FDG-PET hypometabolism signature in predicting the final clinical diagnosis allowed a ≈ 50% increase in accuracy compared to the first clinical assessment alone. Finally, [18F]FDG-PET hypometabolism maps yielded extremely high discriminative power, distinguishing DLB from ADD and PD conditions with an accuracy of > 90%.

CONCLUSION

The present validation of the diagnostic and prognostic accuracy of the disease-specific brain metabolic signature in DLB at the single-subject level argues for the consideration of [18F]FDG-PET in the early phase of the DLB diagnostic flowchart. The assessment of the [18F]FDG-PET hypometabolism pattern at entry may shorten the diagnostic time, resulting in benefits for treatment options and management of patients.

Hyperbaric oxygen therapy for Alzheimer's dementia with positron emission tomography imaging: a case report

A 58-year-old female was diagnosed with Alzheimer's dementia (AD) which was rapidly progressive in the 8 months prior to initiation of hyperbaric oxygen therapy (HBOT). ¹⁸Fluorodeoxyglucose (¹⁸FDG) positron emission tomography (PET) brain imaging demonstrated global and typical metabolic deficits in AD (posterior temporal-parietal watershed and cingulate areas). An 8-week course of HBOT reversed the patient's symptomatic decline. Repeat PET imaging demonstrated a corresponding 6.5-38% regional and global increase in brain metabolism, including increased metabolism in the typical AD diagnostic areas of the brain. Continued HBOT in conjunction with standard pharmacotherapy maintained the patient's symptomatic level of function over an ensuing 22 months. This is the first reported case of simultaneous HBOT-induced symptomatic and ¹⁸FDG PET documented improvement of brain metabolism in AD and suggests an effect on global pathology in AD.

An Automated Pipeline for the Analysis of PET Data on the Cortical Surface

We present a fully automatic pipeline for the analysis of PET data on the cortical surface. Our pipeline combines tools from FreeSurfer and PETPVC, and consists of (i) co-registration of PET and T1-w MRI (T1) images, (ii) intensity normalization, (iii) partial volume correction, (iv) robust projection of the PET signal onto the subject's cortical surface, (v) spatial normalization to a template, and (vi) atlas statistics. We evaluated the performance of the proposed workflow by performing group comparisons and showed that the approach was able to identify the areas of hypometabolism characteristic of different dementia syndromes: Alzheimer's disease (AD) and both the semantic and logopenic variants of primary progressive aphasia. We also showed that these results were comparable to those obtained with a standard volume-based approach. We then performed individual classifications and showed that vertices can be used as features to differentiate cognitively normal and AD subjects. This pipeline is integrated into Clinica, an open-source software platform for neuroscience studies available at www.clinica.run.

Aβ and the dementia syndrome: Simple versus complex perspectives

BACKGROUND

The amyloid cascade hypothesis (ACH) has dominated strategy in dementia research for decades despite evidence of its limitations including known heterogeneity of the dementia syndrome in the population and the narrow focus on a single molecule - the amyloid beta protein (Aβ) as causal for all Alzheimer-type dementia. Other hypotheses relevant to Aβ are the presenilin (PS) hypothesis (PSH) relating to the involvement of PS in the generation of Aβ, and the amyloid precursor protein (APP) matrix approach (AMA), relating to the complex and dynamic breakdown of APP, from which Aβ derives.

MATERIALS AND METHODS

In this article we explore perspectives relating to complex disorders occurring mainly in older populations through a detailed case study of the role of Aβ in AD.

RESULTS

Scrutiny of the evidence generated so far reveals and a lack of understanding of the wider APP proteolytic system and how narrow research into the dementia syndrome has been to date. Confounding factors add significant limitations to the understanding of the current evidence base.

CONCLUSIONS

A better characterisation of the entire APP proteolytic system in the human brain is urgently required to place Aβ in its complex physiological context. From a molecular perspective, a combination of the alternative hypotheses, the PSH and the AMA may better describe the complexity of the APP proteolytic system leading to new therapeutic approaches. The reductionist approach is widespread throughout biomedical research and this example highlights how neglect of complexity can undermine investigations of complex disorders, particularly those arising in the oldest in our populations.

AMYPAD Diagnostic and Patient Management Study: Rationale and design

INTRODUCTION

Reimbursement of amyloid-positron emission tomography (PET) is lagging due to the lack of definitive evidence on its clinical utility and cost-effectiveness. The Amyloid Imaging to Prevent Alzheimer's Disease-Diagnostic and Patient Management Study (AMYPAD-DPMS) is designed to fill this gap.

METHODS

AMYPAD-DPMS is a phase 4, multicenter, prospective, randomized controlled study. Nine hundred patients with subjective cognitive decline plus, mild cognitive impairment, and dementia possibly due to Alzheimer's disease will be randomized to ARM1, amyloid-PET performed early in the diagnostic workup; ARM2, amyloid-PET performed after 8 months; and ARM3, amyloid-PET performed whenever the physician chooses to do so.

ENDPOINTS

The primary endpoint is the difference between ARM1 and ARM2 in the proportion of patients receiving a very-high-confidence etiologic diagnosis after 3 months. Secondary endpoints address diagnosis and diagnostic confidence, diagnostic/therapeutic management, health economics and patient-related outcomes, and methods for image quantitation.

EXPECTED IMPACTS

AMYPAD-DPMS will supply physicians and health care payers with real-world data to plan management decisions.

European Association of Nuclear Medicine and European Academy of Neurology recommendations for the use of brain 18 F-fluorodeoxyglucose positron emission tomography in neurodegenerative cognitive impairment and dementia: Delphi consensus

BACKGROUND AND PURPOSE

Recommendations for using fluorodeoxyglucose positron emission tomography (FDG-PET) to support the diagnosis of dementing neurodegenerative disorders are sparse and poorly structured.

METHODS

Twenty-one questions on diagnostic issues and on semi-automated analysis to assist visual reading were defined. Literature was reviewed to assess study design, risk of bias, inconsistency, imprecision, indirectness and effect size. Critical outcomes were sensitivity, specificity, accuracy, positive/negative predictive value, area under the receiver operating characteristic curve, and positive/negative likelihood ratio of FDG-PET in detecting the target conditions. Using the Delphi method, an expert panel voted for/against the use of FDG-PET based on published evidence and expert opinion.

RESULTS

Of the 1435 papers, 58 papers provided proper quantitative assessment of test performance. The panel agreed on recommending FDG-PET for 14 questions: diagnosing mild cognitive impairment due to Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD) or dementia with Lewy bodies (DLB); diagnosing atypical AD and pseudo-dementia; differentiating between AD and DLB, FTLD or vascular dementia, between DLB and FTLD, and between Parkinson's disease and progressive supranuclear palsy; suggesting underlying pathophysiology in corticobasal degeneration and progressive primary aphasia, and cortical dysfunction in Parkinson's disease; using semi-automated assessment to assist visual reading. Panellists did not support FDG-PET use for pre-clinical stages of neurodegenerative disorders, for amyotrophic lateral sclerosis and Huntington disease diagnoses, and for amyotrophic lateral sclerosis or Huntington-disease-related cognitive decline.

CONCLUSIONS

Despite limited formal evidence, panellists deemed FDG-PET useful in the early and differential diagnosis of the main neurodegenerative disorders, and semi-automated assessment helpful to assist visual reading. These decisions are proposed as interim recommendations.

Effect of starvation on brain glucose metabolism and 18F-2-fluoro-2-deoxyglucose uptake: an experimental in-vivo and ex-vivo study

BACKGROUND

The close connection between neuronal activity and glucose consumption accounts for the clinical value of 18F-fluoro-2-deoxyglucose (FDG) imaging in neurodegenerative disorders. Nevertheless, brain metabolic response to starvation (STS) might hamper the diagnostic accuracy of FDG PET/CT when the cognitive impairment results in a severe food deprivation.

METHODS

Thirty six-week-old BALB/c female mice were divided into two groups: "control" group (n = 15) were kept under standard conditions and exposed to fasting for 6 h before the study; the remaining "STS" mice were submitted to 48 h STS (absence of food and free access to water) before imaging. In each group, nine mice were submitted to dynamic micro-PET imaging to estimate brain and skeletal muscle glucose consumption (C- and SM-MRGlu*) by Patlak approach, while six mice were sacrificed for ex vivo determination of the lumped constant, defined as the ratio between CMRGlu* and glucose consumption measured by glucose removal from the incubation medium (n = 3) or biochemical analyses (n = 3), respectively.

RESULTS

CMRGlu* was lower in starved than in control mice (46.1 ± 23.3 vs 119.5 ± 40.2 nmol × min^-1 × g^-1, respectively, p < 0.001). Ex vivo evaluation documented a remarkable stability of lumped constant as documented by the stability of GLUT expression, G6Pase activity, and kinetic features of hexokinase-catalyzed phosphorylation. However, brain SUV in STS mice was even (though not significantly) higher with respect to control mice. Conversely, a marked decrease in both SM-MRGlu* and SM-SUV was documented in STS mice with respect to controls.

CONCLUSIONS

STS markedly decreases brain glucose consumption without altering measured FDG SUV in mouse experimental models. This apparent paradox does not reflect any change in lumped constant. Rather, it might be explained by the metabolic response of the whole body: the decrease in FDG sequestration by the skeletal muscle is as profound as to prolong tracer persistence in the bloodstream and thus its availability for brain uptake.