Using Neuroimaging to Explore the Alzheimer’s Disease and Related Dementia (AD/ADRD)

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurodegenerative Diseases".

Deadline for manuscript submissions: closed (20 December 2024) | Viewed by 1300

Special Issue Editor


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Guest Editor
1. Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Atlanta, GA 30303, USA
2. Georgia Institute of Technology, Emory University, Atlanta, GA 30303, USA
3. Department of Computer Science, Georgia State University, Atlanta, GA 30303, USA
Interests: signal processing; advanced machine learning; neuroimaging

Special Issue Information

Dear Colleagues,

Neuroimaging tools including MRI, functional MRI, diffusion MRI, PET, and SPECT are pivotal in determining imaging biomarkers for the early detection, staging, diagnostic and prognostic classification, progression prediction, and therapeutic assessment of Alzheimer’s disease and related dementia (AD/ADRD). Previous neuroimaging studies have demonstrated differential patterns of atrophy and hypometabolism in AD and ADRDs including frontotemporal dementia, vascular dementia, Parkinson’s disease, Huntington’s disease, Lewy body dementia, and Creutzfeldt–Jakob disease. In order to advance dementia science, this topic welcomes the submission of high-quality original research, reviews, clinical case studies, and perspectives on the use of neuroimaging to understand the underlying anatomical and functional brain changes in AD/ADRD. The topics of interest include, but are not limited to, the development of new innovative neuroimaging modalities, data processing and analytical methodologies for AD/ADRD, the development of novel clinical applications to increase the accuracy of differential diagnosis and enhance the preclinical detection rates of AD/ADRD, and interventional AD/ADRD studies to benefit at-risk individuals.

Dr. Anees Abrol
Guest Editor

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Keywords

  • Alzheimer's disease (AD)
  • Alzheimer's disease and related dementia (ADRD)
  • neuroimaging
  • preclinical AD/ADRD
  • preclinical biomarkers
  • early diagnosis
  • precision medicine
  • magnetic resonance imaging (MRI)
  • structural MRI (sMRI)
  • functional MRI (fMRI)
  • diffusion-weighted MRI (dMRI)
  • positron emission tomography (PET)
  • single-photon emission computed tomography (SPECT)

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Published Papers (1 paper)

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Research

19 pages, 4957 KiB  
Article
A Comparison of the Brain Parameters of Thais with Normal Cognition, Mild Cognitive Impairment, and Dementia
by Pariwat Wisetwongsa, Sitha Piyaselakul, Yudthaphon Vichianin, Pipat Chiewvit, Chatchawan Rattanabannakit, Saowalak Hunnangkul, Natthamon Wongkom, Pathitta Dujada and Vorapun Senanarong
Brain Sci. 2025, 15(2), 105; https://doi.org/10.3390/brainsci15020105 - 23 Jan 2025
Viewed by 927
Abstract
Objectives: This study examined the differences in brain volume and cortical thickness among individuals with normal cognition (NC) and those with NCDs, including mild cognitive impairment (MCI) and dementia. The aim was to identify the brain parameters supporting clinical decision-making for NCDs. Method: [...] Read more.
Objectives: This study examined the differences in brain volume and cortical thickness among individuals with normal cognition (NC) and those with NCDs, including mild cognitive impairment (MCI) and dementia. The aim was to identify the brain parameters supporting clinical decision-making for NCDs. Method: A total of 116 participants were categorized into dementia, MCI, and NC groups, and their brain scans using structural magnetic resonance imaging (MRI) were processed and automatedly analyzed with FreeSurfer to obtain the absolute brain volume, volume normalized by intracranial volume (ICV), and cortical thickness. Patients with dementia exhibited a significantly smaller brain volume and cortical thickness than the MCI and NC groups. Results: The left amygdala/ICV ratio demonstrated excellent performance in diagnosing early NCDs, with a cutpoint of ≤0.089, providing 83.30% sensitivity, 84.20% specificity, and 83.82% accuracy. For MCI, a cutpoint of ≤0.099 for the left amygdala/ICV yielded 96.70% sensitivity, 83.30% specificity, and 88.46% accuracy. Conclusions: The findings suggested that reductions in brain volume and cortical thickness correlate with cognitive decline. Utilizing FreeSurfer and MRI data, particularly the left amygdala/ICV ratio, may serve as a valuable biomarker for the early identification of individuals at risk for developing NCDs. Full article
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