Establishing Regional Aβ Cutoffs andExploring Subgroup Prevalence Across Cognitive Stages Using BeauBrain Amylo®
10.12779/dnd.2025.24.2.135
- Author:
Seongbeom PARK
1
;
Kyoungmin KIM
;
Soyeon YOON
;
Seongmi KIM
;
Jehyun AHN
;
Kyoung Yoon LIM
;
Hyemin JANG
;
Duk L. NA
;
Hee Jin KIM
;
Seung Hwan MOON
;
Jun Pyo KIM
;
Sang Won SEO
;
Jaeho KIM
;
Kichang KWAK
Author Information
1. BeauBrain Healthcare, Inc., Seoul, Korea
- Publication Type:Original Article
- From:Dementia and Neurocognitive Disorders
2025;24(2):135-146
- CountryRepublic of Korea
- Language:English
-
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.
