A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer’s disease

Marianna Inglese; Neva Patel; Kristofer Linton-Reid; Flavia Loreto; Zarni Win; Richard J. Perry; Christopher Carswell; Matthew Grech-Sollars; William R. Crum; Haonan Lu; Paresh A. Malhotra; the Alzheimer’s Disease Neuroimaging Initiative; Eric O. Aboagye

doi:10.1038/s43856-022-00133-4

Communications Medicine (Jun 2022)

A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer’s disease

Marianna Inglese,
Neva Patel,
Kristofer Linton-Reid,
Flavia Loreto,
Zarni Win,
Richard J. Perry,
Christopher Carswell,
Matthew Grech-Sollars,
William R. Crum,
Haonan Lu,
Paresh A. Malhotra,
the Alzheimer’s Disease Neuroimaging Initiative,
Eric O. Aboagye

Affiliations

Marianna Inglese: Department of Surgery and Cancer, Imperial College London
Neva Patel: Department of Nuclear Medicine, Imperial College NHS Trust
Kristofer Linton-Reid: Department of Surgery and Cancer, Imperial College London
Flavia Loreto: Department of Brain Sciences, Imperial College London
Zarni Win: Department of Nuclear Medicine, Imperial College NHS Trust
Richard J. Perry: Department of Brain Sciences, Imperial College London
Christopher Carswell: Department of Clinical Neurosciences, Imperial College NHS Trust
Matthew Grech-Sollars: Department of Surgery and Cancer, Imperial College London
William R. Crum: Department of Surgery and Cancer, Imperial College London
Haonan Lu: Department of Surgery and Cancer, Imperial College London
Paresh A. Malhotra: Department of Brain Sciences, Imperial College London
the Alzheimer’s Disease Neuroimaging Initiative
Eric O. Aboagye: Department of Surgery and Cancer, Imperial College London

DOI: https://doi.org/10.1038/s43856-022-00133-4
Journal volume & issue: Vol. 2, no. 1
pp. 1 – 16

Abstract

Read online

Inglese et al. develop a predictive model that computes multi-regional statistical morpho-functional mesoscopic traits from T1-weighted magnetic resonance imaging scans. Their model reliably discriminates people with Alzheimer’s disease-related pathologies from those without.

Published in Communications Medicine

ISSN: 2730-664X (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Medicine
Website: https://www.nature.com/commsmed/

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