EANM-EAN recommendations for the use of brain 18 F-Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) in neurodegenerative cognitive impairment and dementia: Delphi consensus

BACKGROUND: Recommendations for using FDG-PET to support the diagnosis of dementing neurodegenerative disorders are sparse and poorly structured. METHODS: We defined 21 questions on diagnostic issues and on semi-automated analysis to assist visual reading. 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 receiving 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 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 pseudodementia; differentiating between AD and DLB, FTLD, or vascular dementia, between DLB and FTLD, and between Parkinson's disease (PD) and progressive supranuclear palsy; suggesting underlying pathophysiology in corticobasal degeneration and progressive primary aphasia, and cortical dysfunction in PD; using semi-automated assessment to assist visual reading. Panelists did not support FDG-PET use for preclinical stages of neurodegenerative disorders, for amyotrophic lateral sclerosis (ALS) and Huntington disease (HD) diagnoses, and ALS or HD-related cognitive decline. CONCLUSIONS: Despite limited formal evidence, panelists deemed FDG-PET useful in the early and differential diagnosis of the main neurodegenerative disorders, and semiautomated assessment helpful to assist visual reading. These decisions are proposed as interim recommendations. This article is protected by copyright. All rights reserved

Early identification of MCI converting to AD: a FDG PET study

Purpose: Mild cognitive impairment (MCI) is a transitional pathological stage between normal ageing (NA) and Alzheimer's disease (AD). Although subjects with MCI show a decline at different rates, some individuals remain stable or even show an improvement in their cognitive level after some years. We assessed the accuracy of FDG PET in discriminating MCI patients who converted to AD from those who did not. Methods: FDG PET was performed in 42 NA subjects, 27 MCI patients who had not converted to AD at 5 years (nc-MCI; mean follow-up time 7.5 ± 1.5 years), and 95 MCI patients who converted to AD within 5 years (MCI-AD; mean conversion time 1.8 ± 1.1 years). Relative FDG uptake values in 26 meta-volumes of interest were submitted to ANCOVA and support vector machine analyses to evaluate regional differences and discrimination accuracy. Results: The MCI-AD group showed significantly lower FDG uptake values in the temporoparietal cortex than the other two groups. FDG uptake values in the nc-MCI group were similar to those in the NA group. Support vector machine analysis discriminated nc-MCI from MCI-AD patients with an accuracy of 89% (AUC 0.91), correctly detecting 93% of the nc-MCI patients. Conclusion: In MCI patients not converting to AD within a minimum follow-up time of 5 years and MCI patients converting within 5 years, baseline FDG PET and volume-based analysis identified those who converted with an accuracy of 89%. However, further analysis is needed in patients with amnestic MCI who convert to a dementia other than AD

Measuring cortical connectivity in Alzheimer's disease as a brain neural network pathology: Toward clinical applications

Objectives: The objective was to review the literature on diffusion tensor imaging as well as resting-state functional magnetic resonance imaging and electroencephalography (EEG) to unveil neuroanatomical and neurophysiological substrates of Alzheimer’s disease (AD) as a brain neural network pathology affecting structural and functional cortical connectivity underlying human cognition. Methods: We reviewed papers registered in PubMed and other scientific repositories on the use of these techniques in amnesic mild cognitive impairment (MCI) and clinically mild AD dementia patients compared to cognitively intact elderly individuals (Controls). Results: Hundreds of peer-reviewed (cross-sectional and longitudinal) papers have shown in patients with MCI and mild AD compared to Controls (1) impairment of callosal (splenium), thalamic, and anterior–posterior white matter bundles; (2) reduced correlation of resting state blood oxygen level-dependent activity across several intrinsic brain circuits including default mode and attention-related networks; and (3) abnormal power and functional coupling of resting state cortical EEG rhythms. Clinical applications of these measures are still limited. Conclusions: Structural and functional (in vivo) cortical connectivity measures represent a reliable marker of cerebral reserve capacity and should be used to predict and monitor the evolution of AD and its relative impact on cognitive domains in pre-clinical, prodromal, and dementia stages of AD. (JINS, 2016, 22, 138–163

Integrating cerebrospinal fluid and [18F]-fluorodeoxyglucose positron emission tomography to diagnose Alzheimer's disease and research its pathophysiological substrates

Revealing the complex interactions and assessing potential integration between biomarkers is essential, especially in the early stages of AD, when biomarker alterations may serve to stage patients throughout the disease spectrum, improve phenotyping, and indicate the likelihood of progression to dementia. In this research, the integration of [18F]-FDG-PET and CSF biomarkers, two of the most used biomarkers in centers focused on neurocognitive disorders, enabled us to collect evidence on their analytical and diagnostic performance when used in a step-wise fashion. As part of the ongoing endeavor to create a common diagnostic chart for the precise and cost-effective use of biomarkers in neurocognitive diseases with neurodegenerative origin, these data gain further significance. Additionally, by combining semiquantitative [18F]-FDG-PET and CSF data, we were able to identify precise topographic correlations between metabolic values and CSF proteins that indicated distinct underlying disease processes. These findings add to the knowledge regarding the distribution of hypometabolism linked to neuronal loss, which is distinct from metabolic changes reflecting synaptic or axonal injury, and provide an indirect insight of the pathological processes taking place at various times in different parts of the brain. These results will be expanded into bigger cohorts in future research, which will also integrate additional newly discovered synaptopathy-expressing proteins for diagnostic and prognostic purposes

Frequency and longitudinal clinical outcomes of Alzheimer's AT(N) biomarker profiles: A longitudinal study.

INTRODUCTION: We aimed to estimate the frequency of each AT(N) (β-amyloid deposition [A], pathologic tau [T], and neurodegeneration [N]) profile in different clinical diagnosis groups and to describe the longitudinal change in clinical outcomes of individuals in each group. METHODS: Longitudinal change in clinical outcomes and conversion risk of AT(N) profiles are assessed using linear mixed-effects models and multivariate Cox proportional-hazard models, respectively. RESULTS: Participants with A+T+N+ showed faster clinical progression than those with A-T-N- and A+T±N-. Compared with A-T-N-, participants with A+T+N± had an increased risk of conversion from cognitively normal (CN) to incident prodromal stage of Alzheimer's disease (AD), and from MCI to AD dementia. A+T+N+ showed an increased conversion risk when compared with A+T±N-. DISCUSSION: The 2018 research framework may provide prognostic information of clinical change and progression. It may also be useful for targeted recruitment of participants with AD into clinical trials