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.

Background: and Purpose: Mild cognitive impairment (MCI) is a transitional stage to dementia, Alzheimer’s disease being a major cause. Although amyloid beta-positive (Aβ+) MCI has been well-characterized, Aβ-negative (Aβ−) MCI has not. This study compared the comprehensive clinical and behavioral characteristics of Aβ+ and Aβ− MCI in a large multicenter cohort to better understand the heterogeneity of MCI, and to identify contributing factors to cognitive impairment. Methods: A total of 686 MCI participants were included. Aβ positivity was determined using Aβ positron emission tomography imaging with a direct conversion Centiloid cutoff value of 25.5. Standardized assessment and questionnaires were used to collect a wide range of clinical information, including vascular risk factors, cognition, daily living function, neuropsychiatric symptoms, and lifestyle behavior. Groups were compared using independent t-tests and χ2 tests. Results: Aβ+ participants (n=406) were older, predominantly female, and more likely to be ApoE4 carriers. In contrast, Aβ− participants (n=280) showed higher vascular risk factors, including diabetes, elevated body mass index, and higher C-reactive protein levels.Aβ+ participants exhibited worse global cognition and functional decline, with a higher prevalence of delusions and appetite disturbances. Meanwhile, Aβ− participants reported greater social engagement, but poorer sleep quality. Conclusions This study highlights the distinct clinical and lifestyle profiles of Aβ+ and Aβ− MCI, illuminating the heterogeneity of MCI and its underlying factors in the Korean population.

Background: and Purpose The National Brain Biobank of Korea (NBBK) is a brain bank consortium supported by the Korea Disease Control and Prevention Agency and the Korea National Institute of Health, and was launched in 2015 to support research into neurodegenerative disease dementia (NDD). This study aimed to introduce the NBBK and describes clinicopathological correlations based on analyses of data collected from the NBBK. Methods: Four hospital-based brain banks have been established in South Korea: Samsung Medical Center Brain Bank (SMCBB), Seoul National University Hospital Brain Bank (SNUHBB), Pusan National University Hospital Brain Bank (PNUHBB), and Myongji Hospital Brain Bank (MJHBB). Clinical and pathological data were collected from these brain banks using standardized protocols. The prevalence rates of clinical and pathological diagnoses were analyzed in order to characterize the clinicopathological correlations. Results: Between August 2016 and December 2023, 185 brain specimens were collected and pathologically evaluated (SNUHBB: 117; PNUHBB: 27; SMCBB: 34; MJHBB: 7). The age at consent was 70.8±12.6 years, and the age at autopsy was 71.7±12.4 years. The four-most-common clinical diagnoses were Alzheimer’s disease (AD) dementia (20.0%), idiopathic Parkinson’s disease (15.1%), unspecified dementia (11.9%), and cognitively unimpaired (CU) (11.4%).Most cases of unspecified dementia had a pathological diagnosis of central nervous system (CNS) vasculopathy (31.8%) or AD (31.8%). Remarkably, only 14.2% of CU cases had normal pathological findings. The three-most-common pathological diagnoses were AD (26.5%), CNS vasculopathy (14.1%), and Lewy body disease (13.5%). Conclusions These clinical and neuropathological findings provide a deeper understanding of the mechanisms underlying NDD in South Korea.

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.

Background: and Purpose: Mild cognitive impairment (MCI) is a transitional stage to dementia, Alzheimer’s disease being a major cause. Although amyloid beta-positive (Aβ+) MCI has been well-characterized, Aβ-negative (Aβ−) MCI has not. This study compared the comprehensive clinical and behavioral characteristics of Aβ+ and Aβ− MCI in a large multicenter cohort to better understand the heterogeneity of MCI, and to identify contributing factors to cognitive impairment. Methods: A total of 686 MCI participants were included. Aβ positivity was determined using Aβ positron emission tomography imaging with a direct conversion Centiloid cutoff value of 25.5. Standardized assessment and questionnaires were used to collect a wide range of clinical information, including vascular risk factors, cognition, daily living function, neuropsychiatric symptoms, and lifestyle behavior. Groups were compared using independent t-tests and χ2 tests. Results: Aβ+ participants (n=406) were older, predominantly female, and more likely to be ApoE4 carriers. In contrast, Aβ− participants (n=280) showed higher vascular risk factors, including diabetes, elevated body mass index, and higher C-reactive protein levels.Aβ+ participants exhibited worse global cognition and functional decline, with a higher prevalence of delusions and appetite disturbances. Meanwhile, Aβ− participants reported greater social engagement, but poorer sleep quality. Conclusions This study highlights the distinct clinical and lifestyle profiles of Aβ+ and Aβ− MCI, illuminating the heterogeneity of MCI and its underlying factors in the Korean population.

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.

Background: and Purpose: Mild cognitive impairment (MCI) is a transitional stage to dementia, Alzheimer’s disease being a major cause. Although amyloid beta-positive (Aβ+) MCI has been well-characterized, Aβ-negative (Aβ−) MCI has not. This study compared the comprehensive clinical and behavioral characteristics of Aβ+ and Aβ− MCI in a large multicenter cohort to better understand the heterogeneity of MCI, and to identify contributing factors to cognitive impairment. Methods: A total of 686 MCI participants were included. Aβ positivity was determined using Aβ positron emission tomography imaging with a direct conversion Centiloid cutoff value of 25.5. Standardized assessment and questionnaires were used to collect a wide range of clinical information, including vascular risk factors, cognition, daily living function, neuropsychiatric symptoms, and lifestyle behavior. Groups were compared using independent t-tests and χ2 tests. Results: Aβ+ participants (n=406) were older, predominantly female, and more likely to be ApoE4 carriers. In contrast, Aβ− participants (n=280) showed higher vascular risk factors, including diabetes, elevated body mass index, and higher C-reactive protein levels.Aβ+ participants exhibited worse global cognition and functional decline, with a higher prevalence of delusions and appetite disturbances. Meanwhile, Aβ− participants reported greater social engagement, but poorer sleep quality. Conclusions This study highlights the distinct clinical and lifestyle profiles of Aβ+ and Aβ− MCI, illuminating the heterogeneity of MCI and its underlying factors in the Korean population.

Background: and Purpose The National Brain Biobank of Korea (NBBK) is a brain bank consortium supported by the Korea Disease Control and Prevention Agency and the Korea National Institute of Health, and was launched in 2015 to support research into neurodegenerative disease dementia (NDD). This study aimed to introduce the NBBK and describes clinicopathological correlations based on analyses of data collected from the NBBK. Methods: Four hospital-based brain banks have been established in South Korea: Samsung Medical Center Brain Bank (SMCBB), Seoul National University Hospital Brain Bank (SNUHBB), Pusan National University Hospital Brain Bank (PNUHBB), and Myongji Hospital Brain Bank (MJHBB). Clinical and pathological data were collected from these brain banks using standardized protocols. The prevalence rates of clinical and pathological diagnoses were analyzed in order to characterize the clinicopathological correlations. Results: Between August 2016 and December 2023, 185 brain specimens were collected and pathologically evaluated (SNUHBB: 117; PNUHBB: 27; SMCBB: 34; MJHBB: 7). The age at consent was 70.8±12.6 years, and the age at autopsy was 71.7±12.4 years. The four-most-common clinical diagnoses were Alzheimer’s disease (AD) dementia (20.0%), idiopathic Parkinson’s disease (15.1%), unspecified dementia (11.9%), and cognitively unimpaired (CU) (11.4%).Most cases of unspecified dementia had a pathological diagnosis of central nervous system (CNS) vasculopathy (31.8%) or AD (31.8%). Remarkably, only 14.2% of CU cases had normal pathological findings. The three-most-common pathological diagnoses were AD (26.5%), CNS vasculopathy (14.1%), and Lewy body disease (13.5%). Conclusions These clinical and neuropathological findings provide a deeper understanding of the mechanisms underlying NDD in South Korea.

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.

Background: and Purpose: Mild cognitive impairment (MCI) is a transitional stage to dementia, Alzheimer’s disease being a major cause. Although amyloid beta-positive (Aβ+) MCI has been well-characterized, Aβ-negative (Aβ−) MCI has not. This study compared the comprehensive clinical and behavioral characteristics of Aβ+ and Aβ− MCI in a large multicenter cohort to better understand the heterogeneity of MCI, and to identify contributing factors to cognitive impairment. Methods: A total of 686 MCI participants were included. Aβ positivity was determined using Aβ positron emission tomography imaging with a direct conversion Centiloid cutoff value of 25.5. Standardized assessment and questionnaires were used to collect a wide range of clinical information, including vascular risk factors, cognition, daily living function, neuropsychiatric symptoms, and lifestyle behavior. Groups were compared using independent t-tests and χ2 tests. Results: Aβ+ participants (n=406) were older, predominantly female, and more likely to be ApoE4 carriers. In contrast, Aβ− participants (n=280) showed higher vascular risk factors, including diabetes, elevated body mass index, and higher C-reactive protein levels.Aβ+ participants exhibited worse global cognition and functional decline, with a higher prevalence of delusions and appetite disturbances. Meanwhile, Aβ− participants reported greater social engagement, but poorer sleep quality. Conclusions This study highlights the distinct clinical and lifestyle profiles of Aβ+ and Aβ− MCI, illuminating the heterogeneity of MCI and its underlying factors in the Korean population.