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Alzheimer's disease heterogeneity revealed by neuroanatomical normative modeling.
Loreto, Flavia; Verdi, Serena; Kia, Seyed Mostafa; Duvnjak, Aleksandar; Hakeem, Haneen; Fitzgerald, Anna; Patel, Neva; Lilja, Johan; Win, Zarni; Perry, Richard; Marquand, Andre F; Cole, James H; Malhotra, Paresh.
Affiliation
  • Loreto F; Department of Brain Sciences Faculty of Medicine Imperial College London London UK.
  • Verdi S; Centre for Medical Image Computing Medical Physics and Biomedical Engineering University College London London UK.
  • Kia SM; Dementia Research Centre UCL Queen Square Institute of Neurology London UK.
  • Duvnjak A; Donders Centre for Cognitive Neuroimaging Donders Institute for Brain Cognition and Behaviour Radboud University Nijmegen The Netherlands.
  • Hakeem H; Department of Cognitive Neuroscience Radboud University Medical Centre Nijmegen The Netherlands.
  • Fitzgerald A; Department of Psychiatry Utrecht University Medical Center Utrecht The Netherlands.
  • Patel N; Department of Brain Sciences Faculty of Medicine Imperial College London London UK.
  • Lilja J; Department of Brain Sciences Faculty of Medicine Imperial College London London UK.
  • Win Z; Department of Brain Sciences Faculty of Medicine Imperial College London London UK.
  • Perry R; Department of Nuclear Medicine Imperial College Healthcare NHS Trust London UK.
  • Marquand AF; Hermes Medical Solutions Stockholm Sweden.
  • Cole JH; Department of Nuclear Medicine Imperial College Healthcare NHS Trust London UK.
  • Malhotra P; Department of Brain Sciences Faculty of Medicine Imperial College London London UK.
Alzheimers Dement (Amst) ; 16(1): e12559, 2024.
Article in En | MEDLINE | ID: mdl-38487076
ABSTRACT

INTRODUCTION:

Overlooking the heterogeneity in Alzheimer's disease (AD) may lead to diagnostic delays and failures. Neuroanatomical normative modeling captures individual brain variation and may inform our understanding of individual differences in AD-related atrophy.

METHODS:

We applied neuroanatomical normative modeling to magnetic resonance imaging from a real-world clinical cohort with confirmed AD (n = 86). Regional cortical thickness was compared to a healthy reference cohort (n = 33,072) and the number of outlying regions was summed (total outlier count) and mapped at individual- and group-levels.

RESULTS:

The superior temporal sulcus contained the highest proportion of outliers (60%). Elsewhere, overlap between patient atrophy patterns was low. Mean total outlier count was higher in patients who were non-amnestic, at more advanced disease stages, and without depressive symptoms. Amyloid burden was negatively associated with outlier count.

DISCUSSION:

Brain atrophy in AD is highly heterogeneous and neuroanatomical normative modeling can be used to explore anatomo-clinical correlations in individual patients.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Alzheimers Dement (Amst) Year: 2024 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Alzheimers Dement (Amst) Year: 2024 Type: Article