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Personalizing progressive changes to brain structure in Alzheimer's disease using normative modeling

Verdi, Serena ; Rutherford, Saige ; Fraza, Charlotte ; Tosun, Duygu ; Altmann, Andre ; Raket, Lars Lau LU orcid ; Schott, Jonathan M. ; Marquand, Andre F. and Cole, James H. (2024) In Alzheimer's and Dementia 20(10). p.6998-7012
Abstract

INTRODUCTION: Neuroanatomical normative modeling captures individual variability in Alzheimer's disease (AD). Here we used normative modeling to track individuals’ disease progression in people with mild cognitive impairment (MCI) and patients with AD. METHODS: Cortical and subcortical normative models were generated using healthy controls (n ≈ 58k). These models were used to calculate regional z scores in 3233 T1-weighted magnetic resonance imaging time-series scans from 1181 participants. Regions with z scores < –1.96 were classified as outliers mapped on the brain and summarized by total outlier count (tOC). RESULTS: tOC increased in AD and in people with MCI who converted to AD and also correlated with multiple non-imaging... (More)

INTRODUCTION: Neuroanatomical normative modeling captures individual variability in Alzheimer's disease (AD). Here we used normative modeling to track individuals’ disease progression in people with mild cognitive impairment (MCI) and patients with AD. METHODS: Cortical and subcortical normative models were generated using healthy controls (n ≈ 58k). These models were used to calculate regional z scores in 3233 T1-weighted magnetic resonance imaging time-series scans from 1181 participants. Regions with z scores < –1.96 were classified as outliers mapped on the brain and summarized by total outlier count (tOC). RESULTS: tOC increased in AD and in people with MCI who converted to AD and also correlated with multiple non-imaging markers. Moreover, a higher annual rate of change in tOC increased the risk of progression from MCI to AD. Brain outlier maps identified the hippocampus as having the highest rate of change. DISCUSSION: Individual patients’ atrophy rates can be tracked by using regional outlier maps and tOC. Highlights: Neuroanatomical normative modeling was applied to serial Alzheimer's disease (AD) magnetic resonance imaging (MRI) data for the first time. Deviation from the norm (outliers) of cortical thickness or brain volume was computed in 3233 scans. The number of brain-structure outliers increased over time in people with AD. Patterns of change in outliers varied markedly between individual patients with AD. People with mild cognitive impairment whose outliers increased over time had a higher risk of progression from AD.

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author
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author collaboration
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Alzheimer's disease, disease progression, longitudinal serial magnetic resonance imaging, mild cognitive impairment, neuroimaging, normative modeling
in
Alzheimer's and Dementia
volume
20
issue
10
pages
15 pages
publisher
Wiley
external identifiers
  • pmid:39234956
  • scopus:85203298445
ISSN
1552-5260
DOI
10.1002/alz.14174
language
English
LU publication?
yes
id
28ff9c53-a5c9-42f9-832c-17aacf771134
date added to LUP
2024-12-13 12:00:19
date last changed
2025-07-12 05:04:55
@article{28ff9c53-a5c9-42f9-832c-17aacf771134,
  abstract     = {{<p>INTRODUCTION: Neuroanatomical normative modeling captures individual variability in Alzheimer's disease (AD). Here we used normative modeling to track individuals’ disease progression in people with mild cognitive impairment (MCI) and patients with AD. METHODS: Cortical and subcortical normative models were generated using healthy controls (n ≈ 58k). These models were used to calculate regional z scores in 3233 T1-weighted magnetic resonance imaging time-series scans from 1181 participants. Regions with z scores &lt; –1.96 were classified as outliers mapped on the brain and summarized by total outlier count (tOC). RESULTS: tOC increased in AD and in people with MCI who converted to AD and also correlated with multiple non-imaging markers. Moreover, a higher annual rate of change in tOC increased the risk of progression from MCI to AD. Brain outlier maps identified the hippocampus as having the highest rate of change. DISCUSSION: Individual patients’ atrophy rates can be tracked by using regional outlier maps and tOC. Highlights: Neuroanatomical normative modeling was applied to serial Alzheimer's disease (AD) magnetic resonance imaging (MRI) data for the first time. Deviation from the norm (outliers) of cortical thickness or brain volume was computed in 3233 scans. The number of brain-structure outliers increased over time in people with AD. Patterns of change in outliers varied markedly between individual patients with AD. People with mild cognitive impairment whose outliers increased over time had a higher risk of progression from AD.</p>}},
  author       = {{Verdi, Serena and Rutherford, Saige and Fraza, Charlotte and Tosun, Duygu and Altmann, Andre and Raket, Lars Lau and Schott, Jonathan M. and Marquand, Andre F. and Cole, James H.}},
  issn         = {{1552-5260}},
  keywords     = {{Alzheimer's disease; disease progression; longitudinal serial magnetic resonance imaging; mild cognitive impairment; neuroimaging; normative modeling}},
  language     = {{eng}},
  number       = {{10}},
  pages        = {{6998--7012}},
  publisher    = {{Wiley}},
  series       = {{Alzheimer's and Dementia}},
  title        = {{Personalizing progressive changes to brain structure in Alzheimer's disease using normative modeling}},
  url          = {{http://dx.doi.org/10.1002/alz.14174}},
  doi          = {{10.1002/alz.14174}},
  volume       = {{20}},
  year         = {{2024}},
}