Abstract
Alzheimer’s disease (AD) is the most common neurodegenerative disorder pathologically characterized by amyloid-beta (Aβ) plaques and neurofibrillary tangles. The aggregation of Aβ precedes tau pathologies in AD; however, the causal relation between the two pathologies and the mechanisms by which aggregated forms of Aβ contribute to cortical thinning are not fully understood. We proposed quantitative Aβ-weighted cortical thickness analysis to investigate the regional relationship between cortical thinning and amyloid plaque deposition using magnetic resonance (MR) and Pittsburg Compound B (PiB) positron emission tomography (PET) images in patients with AD, mild cognitive impairment (MCI), and subjects with normal cognition. We hypothesized that there are cortical areas that have prominent changes associated with Aβ deposition and there are areas that are relatively independent from Aβ deposition where pathologies other than Aβ (such as tau) are predominant. The study was performed using MRI and PiB PET data from the Alzheimer’s Disease Neuroimaging Initiative. We measured accuracy of classification models in three different pairs of groups comparing AD, MCI, and normal cognition. Classification models that used Aβ-weighted cortical thickness were not inferior to classification models that used only cortical thickness or amyloid deposition. In addition, based on timing of changes in cortical thinning and Aβ deposition such as Aβ deposition after cortical thinning; cortical thinning after Aβ deposition, or concurrent Aβ deposition and cortical thinning, we identified three types of relationships between cortical thinning and Aβ deposition: (1) Aβ-associated cortical thinning; (2) Aβ-independent cortical thinning; and (3) Aβ deposition only without cortical thinning. Taken together, these findings suggest that Aβ-weighted cortical thickness values can be used as an objective biomarker of structural changes caused by amyloid pathology in the brain.
Keywords: Alzheimer’s disease, Amyloid beta, amyloid imaging, Aβ-weighted cortical thickness, magnetic resonance imaging, mild cognitive impairment, normal cognition, tau.
Current Alzheimer Research
Title:Amyloid Beta-Weighted Cortical Thickness: A New Imaging Biomarker in Alzheimer's Disease
Volume: 12 Issue: 6
Author(s): Chan Mi Kim, Jihye Hwang, Jong-Min Lee, Jee Hoon Roh, Jae-Hong Lee, Jae-Young Koh and Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Affiliation:
Keywords: Alzheimer’s disease, Amyloid beta, amyloid imaging, Aβ-weighted cortical thickness, magnetic resonance imaging, mild cognitive impairment, normal cognition, tau.
Abstract: Alzheimer’s disease (AD) is the most common neurodegenerative disorder pathologically characterized by amyloid-beta (Aβ) plaques and neurofibrillary tangles. The aggregation of Aβ precedes tau pathologies in AD; however, the causal relation between the two pathologies and the mechanisms by which aggregated forms of Aβ contribute to cortical thinning are not fully understood. We proposed quantitative Aβ-weighted cortical thickness analysis to investigate the regional relationship between cortical thinning and amyloid plaque deposition using magnetic resonance (MR) and Pittsburg Compound B (PiB) positron emission tomography (PET) images in patients with AD, mild cognitive impairment (MCI), and subjects with normal cognition. We hypothesized that there are cortical areas that have prominent changes associated with Aβ deposition and there are areas that are relatively independent from Aβ deposition where pathologies other than Aβ (such as tau) are predominant. The study was performed using MRI and PiB PET data from the Alzheimer’s Disease Neuroimaging Initiative. We measured accuracy of classification models in three different pairs of groups comparing AD, MCI, and normal cognition. Classification models that used Aβ-weighted cortical thickness were not inferior to classification models that used only cortical thickness or amyloid deposition. In addition, based on timing of changes in cortical thinning and Aβ deposition such as Aβ deposition after cortical thinning; cortical thinning after Aβ deposition, or concurrent Aβ deposition and cortical thinning, we identified three types of relationships between cortical thinning and Aβ deposition: (1) Aβ-associated cortical thinning; (2) Aβ-independent cortical thinning; and (3) Aβ deposition only without cortical thinning. Taken together, these findings suggest that Aβ-weighted cortical thickness values can be used as an objective biomarker of structural changes caused by amyloid pathology in the brain.
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Cite this article as:
Kim Mi Chan, Hwang Jihye, Lee Jong-Min, Roh Jee Hoon, Lee Jae-Hong, Koh Jae-Young and Alzheimer’s Disease Neuroimaging Initiative (ADNI) , Amyloid Beta-Weighted Cortical Thickness: A New Imaging Biomarker in Alzheimer's Disease, Current Alzheimer Research 2015; 12 (6) . https://dx.doi.org/10.2174/1567205012666150530202124
DOI https://dx.doi.org/10.2174/1567205012666150530202124 |
Print ISSN 1567-2050 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5828 |
Call for Papers in Thematic Issues
New Advances in the Prevention, Diagnosis, Treatment, and Rehabilitation of Alzheimer's Disease
Aims and Scope: Introduction: Alzheimer's disease (AD) poses a significant global health challenge, with an increasing prevalence that demands concerted efforts to advance our understanding and strategies for prevention, diagnosis, treatment, and rehabilitation. This thematic issue aims to bring together cutting-edge research and innovative approaches from multidisciplinary perspectives to address ...read more
Current updates on the Role of Neuroinflammation in Neurodegenerative Disorders
Neuroinflammation is an invariable hallmark of chronic and acute neurodegenerative disorders and has long been considered a potential drug target for Alzheimer?s disease (AD) and dementia. Significant evidence of inflammatory processes as a feature of AD is provided by the presence of inflammatory markers in plasma, CSF and postmortem brain ...read more
Deep Learning for Advancing Alzheimer's Disease Research
Alzheimer's disease (AD) poses a significant global health challenge, with an increasing number of individuals affected yearly. Deep learning, a subfield of artificial intelligence, has shown immense potential in various domains, including healthcare. This thematic issue of Current Alzheimer Research explores the application of deep learning techniques in advancing our ...read more
Diagnostic and therapeutic biomarkers of dementia
Dementia affects 18 million people worldwide. Dementia is a syndrome of symptoms caused by brain disease, usually chronic or progressive, clinically characterized by multiple impairments of higher cortical functions such as memory, thinking, orientation, and learning. In addition, in the course of dementia, cognitive deficits are observed, which often hinder ...read more
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