ArticleDementia and neurocognitive disorders2025
Establishing Regional Aβ Cutoffs and Exploring Subgroup Prevalence Across Cognitive Stages Using BeauBrain Amylo
Article in Dementia and neurocognitive disorders, 2025. 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.
- Comparative performance of semi-quantitative methods for amyloid deposition in preclinical autosomal dominant Alzheimer's disease.Alzheimer's research & therapy · 2026Article
- Integrative analysis of AT classification, plasma biomarkers, and cognitive trajectories across diverse dementia syndromes.Scientific reports · 2025Article
- Prognostic Value of A/T/N Biomarkers: Comparing Plasma and Imaging Modalities in Alzheimer Disease.Clinical nuclear medicine · 2025Article
- CT-derived brain volumes and plasma p-Tau217 for risk stratification of amyloid positivity in early-stage Alzheimer's disease.Alzheimer's research & therapy · 2025Article
- Integrating visual assessments and quantification methods for tau PET staging.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
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Authors and funding
14 authors.
Funding
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Abstract
Background and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer's disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification. To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer's type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(-)regional(+) were more frequent in non-dementia stages, while global(+)striatal(-) was primarily observed in CU individuals. Conclusions: Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.
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