ArticleNeuroImage. Clinical2018
FDG-PET and CSF biomarker accuracy in prediction of conversion to different dementias in a large multicentre MCI cohort.
Article in NeuroImage. Clinical, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 77 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Treatment of Periodontitis to Prevent Dementia in Older Adults With Asymptomatic Carotid Artery Stenosis and Mild Cognitive Impairment
Pilot Study About Extra Virgin Oil "Coratina" (Evoo-c) in Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD) Patients (EVOO-c in MCI/AD)
Who cites it
77 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Associations between cerebrospinal fluid markers and cognition in ageing and dementia: A systematic review.The European journal of neuroscience · 2022Pooled it
- 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.Journal of Alzheimer's disease : JAD · 2018Pooled it
- Amyloid-β PET Radioligands in Alzheimer's Disease: From Plaque Detection to Biomarker-Guided Patient Stratification and Therapeutic Monitoring.Molecular diagnosis & therapy · 2026Review
- APOE4 negates the effects of ovarian hormones on cerebrovascular endothelial and mitochondrial function.The Journal of physiology · 2026Article
- Resolving Heterogeneity in the Diagnosis of Alzheimer's Disease and its Progression Using Multimodal Data.Journal of molecular neuroscience : MN · 2026Article
- Clinical translation of fluid, imaging, and digital biomarkers for Alzheimer's disease.Alzheimer's research & therapy · 2026Review
- Mapping Alzheimer's disease heterogeneity with molecular imaging biomarkers.European journal of clinical investigation · 2026Review
- FDG-PET brain glucose hypometabolism predicts Alzheimer's disease progression pathways in cognitively normal adults: A longitudinal competing risks modeling.Metabolism open · 2025Article
- Article
- A Review of FDG-PET in Progressive Supranuclear Palsy and Corticobasal Syndrome.International journal of molecular sciences · 2025Review
- Fueling the brain - the role of apolipoprotein E in brain energy metabolism and its implications for Alzheimer's disease.Translational psychiatry · 2025Review
- Circulating medium- and long-chain acylcarnitines are associated with plasma P-tau181 in cognitively normal older adults.Journal of neurochemistry · 2025Article
- Blood-derived APLP1Science advances · 2025Article
- Statistical Method for Identification of Alzheimer Disease With Multimodal Predictive Markers Mild Cognitive Impairment.Basic and clinical neuroscience · 2025Article
- Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Alterations of the blood-brain barrier during aging.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2024Review
- The use of individual-based FDG-PET volume of interest in predicting conversion from mild cognitive impairment to dementia.BMC medical imaging · 2024Article
- Interaction between Aβ and tau on reversion and conversion in mild cognitive impairment patients: After 2-year follow-up.Heliyon · 2024Article
- New horizons in the diagnosis and management of Alzheimer's Disease in older adults.Age and ageing · 2024Review
- Distinguishing features of depression in dementia from primary psychiatric disease.Discover mental health · 2024Review
17 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background/aims: In this multicentre study in clinical settings, we assessed the accuracy of optimized procedures for FDG-PET brain metabolism and CSF classifications in predicting or excluding the conversion to Alzheimer's disease (AD) dementia and non-AD dementias. Methods: We included 80 MCI subjects with neurological and neuropsychological assessments, FDG-PET scan and CSF measures at entry, all with clinical follow-up. FDG-PET data were analysed with a validated voxel-based SPM method. Resulting single-subject SPM maps were classified by five imaging experts according to the disease-specific patterns, as "typical-AD", "atypical-AD" (i.e. posterior cortical atrophy, asymmetric logopenic AD variant, frontal-AD variant), "non-AD" (i.e. behavioural variant FTD, corticobasal degeneration, semantic variant FTD; dementia with Lewy bodies) or "negative" patterns. To perform the statistical analyses, the individual patterns were grouped either as "AD dementia vs. non-AD dementia (all diseases)" or as "FTD vs. non-FTD (all diseases)". Aβ42, total and phosphorylated Tau CSF-levels were classified dichotomously, and using the Erlangen Score algorithm. Multivariate logistic models tested the prognostic accuracy of FDG-PET-SPM and CSF dichotomous classifications. Accuracy of Erlangen score and Erlangen Score aided by FDG-PET SPM classification was evaluated. Results: The multivariate logistic model identified FDG-PET "AD" SPM classification (Expβ = 19.35, 95% C.I. 4.8-77.8, p < 0.001) and CSF Aβ42 (Expβ = 6.5, 95% C.I. 1.64-25.43, p < 0.05) as the best predictors of conversion from MCI to AD dementia. The "FTD" SPM pattern significantly predicted conversion to FTD dementias at follow-up (Expβ = 14, 95% C.I. 3.1-63, p < 0.001). Overall, FDG-PET-SPM classification was the most accurate biomarker, able to correctly differentiate either the MCI subjects who converted to AD or FTD dementias, and those who remained stable or reverted to normal cognition (Expβ = 17.9, 95% C.I. 4.55-70.46, p < 0.001). Conclusions: Our results support the relevant role of FDG-PET-SPM classification in predicting progression to different dementia conditions in prodromal MCI phase, and in the exclusion of progression, outperforming CSF biomarkers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.