Cited by 264Dementia and Cognitive Impairment ResearchMedical Image Segmentation TechniquesAlzheimer's disease research and treatments

Changes in hippocampal volume and shape across time distinguish dementia of the Alzheimer type from healthy aging

Wang, Lei, Swank, Jeffrey S., Glick, Irena E., Gado, Mokhtar H., Miller, Michael I., Morris, John C., Csernansky, John G.·2003·NeuroImage

Abstract

Rates of hippocampal volume loss have been shown to distinguish subjects with dementia of the Alzheimer type (DAT) from nondemented controls. In this study, we obtained magnetic resonance scans in 18 subjects with very mild DAT (CDR 0.5) and 26 age-matched nondemented controls (CDR 0) 2 years apart. Large-deformation high-dimensional brain mapping was used to quantify and compare changes in hippocampal shape as well as volume in the two groups of subjects. Hippocampal volume loss over time was significantly greater in the CDR 0.5 subjects (left = 8.3%, right = 10.2%) than in the CDR 0 subjects (left = 4.0%, right = 5.5%) (ANOVA, F = 7.81, P = 0.0078). We used singular-value decomposition and logistic regression models to quantify hippocampal shape change across time within individuals, and this shape change in the CDR 0.5 and CDR 0 subjects was found to be significantly different (Wilks's lambda, P = 0.014). Further, at baseline, CDR 0.5 subjects, in comparison to CDR 0 subjects, showed inward deformation over 38% of the hippocampal surface; after 2 years this difference grew to 47%. Also, within the CDR 0 subjects, shape change between baseline and follow-up was largely confined to the head of the hippocampus and subiculum, while in the CDR 0.5 subjects, shape change involved the lateral body of the hippocampus as well as the head region and subiculum. These results suggest that different patterns of hippocampal shape change in time as well as different rates of hippocampal volume loss distinguish very mild DAT from healthy aging.

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Crossref · 10.1016/s1053-8119(03)00361-6

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  • The predominance of atrophy in CA1 (and to a lesser extent in the subiculum) in patients with clinical AD or aMCI has already been shown in vivo using a variety of neuroimaging approaches.

    “Using a variety of neuroimaging approaches such as radial atrophy (Frisoni et al., 2006), large-deformation high-dimensional brain mapping (Wang et al., 2003), voxel-based morphometry (Chételat et al., 2008) or manual delineation (Mueller et al., 2010), the predominance of atrophy in CA1 (and to a lesser extent in the subiculum) in patients with clinical AD or aMCI has already been shown in vivo.”

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Authors
Wang, L., Swank, J. S., Glick, I. E., Gado, M. H., Miller, M. I., Morris, J. C., & Csernansky, J. G.
Affiliations
  • Washington University in St. Louis (US)
  • Johns Hopkins University (US)
Corresponding author
Wang, Lei
Venue
NeuroImage
Publisher
Elsevier BV
Published
2003-10
Volume
20
Issue
2
Pages
667-682
ISSN
1053-8119 (ISSN-L)
OpenAlex
W1976154578
Cited by
263
References
64
Citations by year
2026: 4 · 2025: 4 · 2024: 6 · 2023: 4 · 2022: 4 · 2021: 11 · 2020: 9 · 2019: 12 · 2018: 8 · 2017: 9 · 2016: 11 · 2015: 14 · 2014: 17 · 2013: 12 · 2012: 12
FWCI
6.94
Type
journal article
Language
en
Open access
closed
Locations
  • NeuroImage (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • American Health Assistance Foundation
  • University of Washington
  • National Institutes of Health (1 P41 RR15241-01A1, AG 03991, MH 62130, MH/AG 60883)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
Keywords
Alzheimer's disease, hippocampal atrophy, mild cognitive impairment, healthy aging, hippocampal subiculum, hippocampal head
MeSH terms
Aged, Aging, Algorithms, Alzheimer Disease, Female, Hippocampus, Humans, Image Processing, Computer-Assisted, Longitudinal Studies, Magnetic Resonance Imaging, Male, Psychiatric Status Rating Scales, Regression Analysis, Sex Characteristics, Disease Progression

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