ArticleScientific reports2020
Spatial patterns of correlation between cortical amyloid and cortical thickness in a tertiary clinical population with memory deficit.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Beyond FDG: a paradigm shift in precision localization of epileptogenic zones in refractory epilepsy using multimodal molecular imaging (PET/CT) and isotropic 3D MRI fusion.Journal of neurology · 2026Review
- Multimodal neuroimaging approach for cognitive impairment in Alzheimer's disease.medRxiv : the preprint server for health sciences · 2026Article
- Generative AI for amyloid PET from MRI: research promise and clinical considerations.European radiology · 2026Article
- Article
- Longitudinal brain atrophy and CSF biomarkers in early-onset Alzheimer's disease.NeuroImage. Clinical · 2021Article
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6 authors.
Funding
Abstract
To estimate regional Alzheimer disease (AD) pathology burden clinically, analysis methods that enable tracking brain amyloid or tau positron emission tomography (PET) with magnetic resonance imaging (MRI) measures are needed. We therefore developed a robust MRI analysis method to identify brain regions that correlate linearly with regional amyloid burden in congruent PET images. This method was designed to reduce data variance and improve the sensitivity of the detection of cortical thickness-amyloid correlation by using whole brain modeling, nonlinear image coregistration, and partial volume correction. Using this method, a cross-sectional analysis of 75 tertiary memory clinic AD patients was performed to test our hypothesis that regional amyloid burden and cortical thickness are inversely correlated in medial temporal neocortical regions. Medial temporal cortical thicknesses were not correlated with their regional amyloid burden, whereas cortical thicknesses in the lateral temporal, lateral parietal, and frontal regions were inversely correlated with amyloid burden. This study demonstrates the robustness of our technique combining whole brain modeling, nonlinear image coregistration, and partial volume correction to track the differential correlation between regional amyloid burden and cortical thinning in specific brain regions. This method could be used with amyloid and tau PET to assess corresponding cortical thickness changes.
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