ArticleNeuroImage. Clinical2017
Multiparametric MRI to distinguish early onset Alzheimer's disease and behavioural variant of frontotemporal dementia.
Article in NeuroImage. Clinical, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.
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Who cites it
31 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Genuine Memory Deficits as Assessed by the Free and Cued Selective Reminding Test (FCSRT) in the Behavioural Variant of Frontotemporal Dementia. A Systematic Review and Meta-analysis Study.Neuropsychology review · 2024Pooled it
- A Systematic Review and Implementation of IoT-Based Pervasive Sensor-Enabled Tracking System for Dementia Patients.Journal of medical systems · 2019Pooled it
- Morphometric MRI as a diagnostic biomarker of frontotemporal dementia: A systematic review to determine clinical applicability.NeuroImage. Clinical · 2018Pooled it
- Dissociable, species-specific impact of Aβ on static and dynamic functional connectomes.bioRxiv : the preprint server for biology · 2026Article
- Combining plasma neurofilament light chain and frontotemporal atrophy improves differentiation of bvFTD from primary psychiatric disorders.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Mapping Knowledge Landscapes and Emerging Trends in AI for Dementia Biomarkers: Bibliometric and Visualization Analysis.Journal of medical Internet research · 2024Article
- Diagnostic and predictive power of plasma proteins in Alzheimer's disease: a cross-sectional and longitudinal study in China.Scientific reports · 2024Article
- Fronto-striatal alterations correlate with apathy severity in behavioral variant frontotemporal dementia.Brain imaging and behavior · 2024Article
- Atrophy in behavioural variant frontotemporal dementia spans multiple large-scale prefrontal and temporal networks.Brain : a journal of neurology · 2023Article
- Classifying Alzheimer's disease and frontotemporal dementia using machine learning with cross-sectional and longitudinal magnetic resonance imaging data.Human brain mapping · 2023Article
- Alterations via inter-regional connective relationships in Alzheimer's disease.Frontiers in human neuroscience · 2023Article
- Functional connectivity in behavioral variant frontotemporal dementia.Brain and behavior · 2022Review
- A Multivariate Functional Connectivity Approach to Mapping Brain Networks and Imputing Neural Activity in Mice.Cerebral cortex (New York, N.Y. : 1991) · 2022Article
- White matter microstructure alterations in frontotemporal dementia: Phenotype-associated signatures and single-subject interpretation.Brain and behavior · 2022Article
- Quantified Brain Magnetic Resonance Imaging Volumes Differentiate Behavioral Variant Frontotemporal Dementia from Early-Onset Alzheimer's Disease.Journal of Alzheimer's disease : JAD · 2022Article
- Ventricular features as reliable differentiators between bvFTD and other dementias.NeuroImage. Clinical · 2022Article
- Distinct network topology in Alzheimer's disease and behavioral variant frontotemporal dementia.Alzheimer's research & therapy · 2021Article
- Insight in frontotemporal dementia and progressive supranuclear palsy.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2020Article
- Recommendations to distinguish behavioural variant frontotemporal dementia from psychiatric disorders.Brain : a journal of neurology · 2020Review
- Contribution of CSF biomarkers to early-onset Alzheimer's disease and frontotemporal dementia neuroimaging signatures.Human brain mapping · 2020Article
Corrections and comments
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10 authors.
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Abstract
This prospective study explored whether an approach combining structural [cortical thickness and white matter (WM) microstructure] and resting state functional MRI can aid differentiation between 62 early onset Alzheimer's disease (EOAD) and 27 behavioural variant of frontotemporal dementia (bvFTD) patients. Random forest and receiver operator characteristic curve analyses assessed the ability of MRI in classifying the two clinical syndromes. All patients showed a distributed pattern of brain alterations relative to controls. Compared to bvFTD, EOAD patients showed bilateral inferior parietal cortical thinning and decreased default mode network functional connectivity. Compared to EOAD, bvFTD patients showed bilateral orbitofrontal and temporal cortical thinning, and WM damage of the corpus callosum, bilateral uncinate fasciculus, and left superior longitudinal fasciculus. Random forest analysis revealed that left inferior parietal cortical thickness (accuracy 0.78, specificity 0.76, sensitivity 0.83) and WM integrity of the right uncinate fasciculus (accuracy 0.81, specificity 0.96, sensitivity 0.43) were the best predictors of clinical diagnosis. The combination of cortical thickness and DT MRI measures was able to distinguish patients with EOAD and bvFTD with accuracy 0.82, specificity 0.76, and sensitivity 0.96. The diagnostic ability of MRI models was confirmed in a subsample of patients with biomarker-based clinical diagnosis. Multiparametric MRI is useful to identify brain alterations which are specific to EOAD and bvFTD. A severe cortical involvement is suggestive of EOAD, while a prominent WM damage is indicative of bvFTD.
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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 OpenQuestion graph.