The introduction of 18F-fluorodeoxyglucose (FDG) to medicine has been revolutionary during the past 5 decades, and its impact rivals that of other technical advances that have been made in medicine during the past century. Therefore, it is timely to celebrate the impact of this unique tracer and its critical role in so many domains of medicine, including the assessment and management of many serious diseases and disorders in the brain but also the entire body. FDG has lived up to the title molecule of the century. With the invention of total body PET instruments, the future looks just as promising.

Fibromyalgia (FM) is a chronic overlapping pain condition that impairs quality of life (QOL). Adapted physical activity (APA) is recommended as a key non-pharmacological intervention, though its implementation and underlying mechanisms remain limited. Fibromyactiv, a prospective, randomised, single-blind clinical and neuroimaging study, evaluated the efficacy and mechanisms of a structured, supervised APA program in FM. Seventy-nine adults were assigned to supervised APA (n = 39) or standard care (n = 40) and followed for 12 months. The intervention consisted of diversified, low-intensity, fractionated sessions three times weekly for 6 months. Outcomes included the Fibromyalgia Impact Questionnaire (FIQ, primary endpoint at M6), clinical and psychological scales, functional tests, pedometer monitoring, and mechanistic measures (¹⁸F-FDG PET, blood/urine biomarkers). Supervised APA produced significantly greater FIQ improvement and broader benefits across PGIC, Widespread Pain Index, Symptom Severity Scale, tender points, mean pain, sleep quality, flexibility, and daily step counts. Immediate symptom relief occurred after each session. Brain PET revealed increased metabolism in the right cerebellum in the APA group, correlating positively with step-count improvement. This interdisciplinary trial demonstrates that a reproducible supervised APA program yields sustained improvements in QOL, symptoms, and functional activity in FM, potentially mediated by cerebellar modulation of motor and behavioural engagement.ClinicalTrials.govIdentifier: NCT03640806 N°IDRCB:2017-A03011-52. Sponsor: Assistance Publique Hôpitaux De Marseille (Marseille Public Hospital System). Other Study ID Numbers: 2017-57.

Subjective cognitive complaints are heterogeneous and may occur with normal, subtle, or objectively abnormal cognitive testing. Fluorodeoxyglucose (FDG) PET can help explore their metabolic substrate, particularly in subjective cognitive decline within the Alzheimer's disease continuum. In mild traumatic brain injury and long coronavirus disease (COVID), available studies suggest possible metabolic-network abnormalities but involve more heterogeneous populations and should be interpreted cautiously within multimodal, clinically characterized frameworks.

Brain [18F]FDG PET can reveal metabolic abnormalities that precede, exceed, or clarify structural MR imaging findings. Among inflammatory brain diseases, the strongest clinical rationale is currently in autoimmune encephalitis, where fluorodeoxyglucose (FDG) PET increases diagnostic sensitivity, supports syndrome-oriented metabolic pattern recognition, and may contribute to selected follow-up. In viral encephalitis, use is selective rather than routine. In post-coronavirus infectious disease (COVID) condition and related postinfectious syndromes, FDG PET may support biological stratification and differential diagnosis in a subset of patients. Interpretation remains highly dependent on clinical context and methods. Translocator protein (TSPO) PET adds mechanistic information on neuroimmune activation but belongs mainly to the research domain.

[18F]FDG PET is entering a new phase shaped by changes in representation, validation, and clinical integration. Beyond regional interpretation, network-based and computational approaches aim to provide more explicit and individualized descriptions of brain dysfunction. At the same time, dynamic [18F]FDG PET and total-body PET expand the field toward temporal physiology and systemic brain-body interactions. The clinical impact of these advances will depend on standardized, reproducible, and scalable frameworks that support multicenter deployment and clinically meaningful interpretation. In this evolving biomarker ecosystem, [18F]FDG PET is well positioned to serve as a functional anchor.

Over 5 decades, fluorine-18-labeled fluorodeoxyglucose ([18F]FDG) PET has transformed clinical practice in central nervous system (CNS) disorders by enabling in vivo assessment of brain metabolism as a surrogate of functional integrity. Beyond structural imaging, it provides reproducible, pattern-based biomarkers that improve diagnostic accuracy in dementia, epilepsy, and selected neuroinflammatory conditions. In the evolving biomarker landscape, [18F]FDG PET remains uniquely positioned to capture downstream network dysfunction and phenotypic expression of disease. Supported by standardized methodologies and expanding analytical approaches, it continues to play a central role in differential diagnosis, prognostic assessment, and integrated precision neurology.

Abnormal brain accumulation of amyloid-β peptides, represents one of the earliest biological indicators of Alzheimer’s disease (AD) risk. Estimation on amyloid positivity (A+) prevalence among older adults without dementia are needed to assess the epidemiological impact of AD diagnosis solely through biological markers. We combined data from the French MEMENTO clinical cohort, where amyloid status was assessed through reference procedures, with the nationally representative SHARE-HCAP survey. Using stabilized inverse odds of selection weights, we adjusted the MEMENTO sample to estimate the prevalence of A+ in the French population aged 65–85 without dementia and their five-year risk of developing AD dementia. A+ prevalence was 21.4% (95% CI: 18.4–24.7) in French adults aged 65–85 without dementia i.e. approximately 2.5 million individuals, reaching 27.5% in the 80–85 age group. Over five years of follow-up, the cumulative incidence of AD dementia was 22.7% among A+ individuals, 8.0% among cognitively normal A+ adults and 62.3% among those with mild cognitive impairment. While A+ is common in older adults without dementia, most do not develop dementia within five years. Defining AD by A+ could substantially increase diagnoses, raising major public health, ethical, and health system challenges, especially as new anti-amyloid therapies emerge.

Feature ranking for Alzheimer's disease (AD) classification often suffers from instability and inconsistent performance due to variations across neuroimaging datasets and analytic approaches. This study evaluates individual feature-ranking methods, simple aggregation techniques, and graph-based consensus approaches for AD classification. Significant discrepancies across individual ranking methods reveal their distinct sensitivities to data characteristics, underscoring the need for robust integration strategies. Aggregation-based approaches effectively leverage complementary insights to enhance stability and predictive accuracy. Among them, graph-based consensus methods-particularly our proposed multi-cutoff graph representations with Sinkhorn aggregation-demonstrate a principled capacity to capture complex feature dependencies and yield interpretable, high-fidelity consensus rankings. By advancing reliable feature selection and improving model transparency, this work contributes to strengthening computational tools that support early disease detection and facilitate more informed clinical decisionmaking in neurodegenerative disorders.

Introduction:The COVID-19 pandemic has profoundly affected mental health, with lockdown periods particularly exacerbating negative emotions such as fear, sadness, and uncertainty. This study examines brain metabolic changes associated with the psychological context of the first French COVID-19 lockdown in vulnerable individuals. Methods:As a proxy measure of the psychological context, we used a composite negative-emotion score derived from an open-source X/Twitter dataset ("The First French COVID-19 Lockdown Twitter Dataset"), designed to capture public sentiment over the 55-day lockdown. This score was day-by-day correlated with whole-brain voxel-based [18F]FDG PET imaging in 95 patients with neurological conditions, using statistical parametric mapping (SPM) (p-voxel < 0.001, k > 108). Results:A significant negative correlation was found between daily negative-emotion scores and metabolism in the right ventromedial prefrontal cortex (vmPFC) and anterior cingulate cortex (ACC), key regions of the brain's fear circuit. Inter-regional correlation analysis (IRCA) of metabolic connectivity from the right vmPFC/ACC further revealed a right limbic-dominant network including the amygdala, hippocampus, thalamus, and basal ganglia. Discussion:These findings highlight the sensitivity of the right vmPFC/ACC to societal emotional stressors, suggesting a potential cerebral substrate for the increase in psychological and psychiatric disorders observed during the pandemic. Further research is needed to validate these results in larger populations and to explore their longitudinal implications, to better understand the neurological impact of collective stress.

This article overviews common methods of assessing MC and elaborates the contribution of MC studies to understanding the brain's network organization in health and neurologic disorders. Future promising directions include single-subject connectivity analyses and whole-body PET imaging for brain-organ interactions, as for the gutbrain axis. As for functional connectivity using fMR imaging, MC provides a valuable and distinct approach for network analysis, offering both clinical relevance and new avenues for personalized diagnostics.

A hypometabolic brain pattern has been reported in patients with post-COVID condition (PCC). The aim of this study was to investigate reorganization in metabolic connectivity in patients with PCC. One hundred eighty-eight patients who underwent brain 18F-FDG PET for PCC were retrospectively included from two university hospital centres. These patients were age- and sex-matched to 120 healthy controls who underwent brain 18F-FDG PET before the COVID-19 outbreak. A voxel-based group comparison between patients and controls was performed (p-voxel at 0.005 uncorrected, p-cluster at 0.05 FWE corrected). Interregional correlation analyses of the identified clusters as well as sparse inverse covariance estimations at whole-brain scaling were also conducted. Both analyses were performed at the group level for all patients and then secondarily according to the postinfection delay; 88 and 100 patients, respectively, had a delay of less than or greater than 9 months (± 9 M). Three hypometabolic clusters, namely, the right frontotemporal, right and left cerebellar, were identified from the voxel-based group comparisons of PCC patients. Within this hypometabolic PCC pattern, a modification in metabolic connectivity was observed in patients compared with controls, which was more marked in the + 9 M group than in the − 9 M group. On the other hand, the graph analysis revealed a decrease in connectivity efficiency metrics in the PCC. Metabolic connectivity is modified in patients with PCC within the hypometabolic post-COVID-19 network, with lasting reorganization evolving over time, suggesting functional adaptation.

The introduction of hybrid SPECT/CT systems with 3D multi-head gantries and CZT crystal detectors offers significant clinical potential, especially for brain imaging. These advancements allow for reduced activity/time requirements, improved spatial resolution, contrast, and the ability to study early perfusion phases and enable 4D acquisitions. Approximately 200 systems have been installed worldwide, prompting individual centers to optimize acquisition and reconstruction protocols. A European effort was attempted in this paper to separately harmonize protocols for each system, facilitating multicentric clinical studies and the development of a standardized database. To harmonize the protocols for StarGuide (GE HealthCare) system, four online meetings were held involving nuclear medicine experts from seven European centers. These meetings focused on standardizing acquisition and reconstruction parameters based on experts’ opinion and phantom testing. To harmonize the protocols for Veriton (Spectrum Dynamics Medical) results of a prospective study (VERIDAT) were used. Specific acquisition and reconstruction parameters have been detailed for both systems. Significant heterogeneity was found in the initial acquisition/reconstruction protocols among the participating centers. After discussions and phantom testing, standard parameters were established for both systems. For the StarGuide, a scan time of 20 min with an energy window of 159 keV (−6.5