Establishing Regional Aβ Cutoffs and Exploring Subgroup Prevalence Across Cognitive Stages Using BeauBrain Amylo®.

Dementia and neurocognitive disorders Pub Date : 2025-04-01 Epub Date: 2025-04-09 DOI:10.12779/dnd.2025.24.2.135
Seongbeom Park, 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
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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.

使用BeauBrain Amylo®建立区域Aβ截断并探索认知阶段的亚群患病率。
背景和目的:淀粉样蛋白- β (Aβ)斑块是阿尔茨海默病(AD)的关键,Aβ正电子发射断层成像可以实现无创量化。为了解决区域Aβ沉积问题,我们开发了区域Centiloid scales (rdcCL),并通过基于计算机断层扫描(CT)的BeauBrain Amylo平台将其商业化,从而消除了对三维T1磁共振成像(MRI)的需求。目的:我们旨在利用商业化的BeauBrain Amylo平台建立强大的区域Aβ切断,并探索由整体、区域和纹状体Aβ切断定义的亚群在认知阶段的流行程度。方法:我们从韩国克服痴呆和加速痴呆研究项目登记处招募了2428名个体。我们使用高斯混合模型计算区域Aβ截止点。参与者根据认知阶段(认知未受损[CU]、轻度认知障碍和阿尔茨海默氏型痴呆)的整体、区域和纹状体Aβ阳性程度被分为亚组。结果:基于mri和基于ct的全局Aβ截止值与先前报道的Centiloid值高度可比性和一致性。区域截止点揭示了MRI和ct方法之间的异同,反映了特定模式的分割过程。整体(-)、区域(+)等亚群在非痴呆期更常见,而整体(+)纹状体(-)主要在CU个体中观察到。结论:我们的研究使用基于ct的rdcCL方法建立了强大的区域a β切断,并证明了其在跨认知阶段分类淀粉样蛋白亚群的临床应用。这些发现强调了区域Aβ定量在理解淀粉样蛋白病理及其对AD生物标志物指导诊断和治疗的意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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