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ID 119325
Title Alternative
アルツハイマー病における灰白質容積ネットワークの同定と検証
Author
Chuluunbat, Munkhzaya Tokushima University
Matsuda, Daiki Tokushima University
Kudo, Kohsuke Hokkaido University
Keywords
Alzheimer's disease
Hippocampus
Multivariate analysis
Principal component analysis
Scaled subprofile model
Voxel-based morphometry
Content Type
Thesis or Dissertation
Description
Objective: This study aims to identify and validate a gray matter volume network in patients with Alzheimer's disease (AD).
Methods: To identify a disease-related network, a principal component analysis-based algorithm, Scaled Subprofile Model, was applied to gray matter volume data derived from structural T1-weighted magnetic resonance imaging of the training sample that consisted of nine patients with AD (women, four; dementia, seven; mild cognitive impairment, two; age, 66.7 ± 8.8 [mean ± SD] years) with positive 18F-flutemetamol amyloid positron emission tomography and eight age-matched healthy controls obtained on-site. The network expression scores were calculated by topographic profile rating in the validation sample obtained via the Open Access Series of Imaging Studies and comprised 12 patients with AD dementia (women, four; age, 70.0 ± 3.7 years) and 12 age-matched healthy controls.
Results: A significant network from the training sample, for which subject expression differed between the groups (permutation test, P = 0.006; sensitivity and specificity, 100%; area under the curve, 1), was identified. This network was represented by the principal components 1, 2, and 3 and showed a relative decrease in the inferior parietal lobule including angular gyrus, inferior temporal gyrus, premotor cortex, amygdala, hippocampus, and precuneus. It significantly differed between the groups with a sensitivity, specificity, and area under the curve of 83%, 91%, and 0.85, respectively, in the validation sample (P = 0.003).
Conclusions: An AD-related gray matter volume network that captured relevant regions was identified in amyloid positron emission tomography-positive patients and validated in an independent sample.
Journal Title
Journal of the Neurological Sciences
ISSN
0022510X
18785883
NCID
AA00703265
AA11534024
Publisher
Elsevier
Volume
440
Start Page
120344
Published Date
2022-07-19
Remark
内容要旨・審査要旨・論文本文の公開
本論文は,著者Munkhzaya Chuluunbatの学位論文として提出され,学位審査・授与の対象となっている。
EDB ID
DOI (Published Version)
URL ( Publisher's Version )
FullText File
language
eng
TextVersion
ETD
MEXT report number
甲第3793号
Diploma Number
甲医第1597号
Granted Date
2024-03-22
Degree Name
Doctor of Medical Science
Grantor
Tokushima University
departments
University Hospital
Medical Sciences