ArticleJournal of neurology2020
Spatial metabolic profiles to discriminate dementia with Lewy bodies from Alzheimer disease.
Article in Journal of neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.
What it found
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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
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Who cites it
11 citing papers in PubMed, 3 syntheses or guidelines pooled it, 20 citations in OpenAlex.
- Diagnostic performance of molecular imaging methods in predicting the progression from mild cognitive impairment to dementia: an updated systematic review.European journal of nuclear medicine and molecular imaging · 2024Pooled it
- (Dis-)Connected Dots in Dementia with Lewy Bodies-A Systematic Review of Connectivity Studies.Movement disorders : official journal of the Movement Disorder Society · 2023Pooled it
- Neuroimaging alterations in dementia with Lewy bodies and neuroimaging differences between dementia with Lewy bodies and Alzheimer's disease: An activation likelihood estimation meta-analysis.CNS neuroscience & therapeutics · 2022Pooled it
- Metabolic brain networks in dementia with Lewy bodies: from prodromal to manifest disease stages.Journal of neurology, neurosurgery, and psychiatry · 2026Article
- Applications of artificial intelligence in dementia.Geriatrics & gerontology international · 2024Review
- Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission.European journal of nuclear medicine and molecular imaging · 2024Article
- Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer's disease-related pattern.EJNMMI research · 2023Article
- The identification and cognitive correlation of perfusion patterns measured with arterial spin labeling MRI in Alzheimer's disease.Alzheimer's research & therapy · 2023Article
- Functional brain networks in the evaluation of patients with neurodegenerative disorders.Nature reviews. Neurology · 2023Review
- Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment.GeroScience · 2022Article
- Combined 18F-FDG PET-CT markers in dementia with Lewy bodies.Alzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo differentiate dementia with Lewy bodies (DLB) from Alzheimer disease (AD) using a single imaging modality is challenging, because of their common hypometabolic findings. Scaled subprofile modeling/principal component analysis (SSM/PCA), an unsupervised artificial intelligence, has the potential to offer an alternative to image analysis.
objectiveWe aimed to produce spatial metabolic profiles to discriminate DLB from AD and to identify the characteristics of the profiles.
methodsFifty individuals each with DLB, AD, and normal cognition (NL) underwent
resultsThe DLB-AD discrimination profile significantly differentiated DLB from AD with comparable accuracy to that of discriminating DLB and AD from NL. The AD- and DLB-related profiles comprised metabolic imaging features typical of each pathology. In contrast, the DLB-AD discrimination profile emphasized preservation in the posterior cingulate cortex (cingulate island sign) and medial temporal lobe, and occipital hypometabolism. Common hypometabolic findings between DLB and AD were less noticeable in the profile. The DLB-related profile significantly correlated with cognitive function and three core features of DLB, whereas the DLB-AD discrimination profile did not.
conclusionsSpatial metabolic profile that could discriminate DLB from AD emphasized different imaging features and eliminated common findings between DLB and AD. Neither cognitive function nor core features were associated with the profile.
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