The Amyloid Imaging to Prevent Alzheimer’s Disease Prognostic and Natural History Study (AMYPAD-PNHS) multimodal magnetic resonance imaging (MRI) dataset provides open-access longitudinal MRI data of 2759 cognitively normal or mild cognitive impairment individuals to enhance generalizability and comparability between future neuroimaging studies.
Abstract
The Amyloid Imaging to Prevent Alzheimer’s Disease Prognostic and Natural History Study (AMYPAD-PNHS) multimodal magnetic resonance imaging (MRI) dataset provides open-access longitudinal MRI data of 2759 cognitively normal or mild cognitive impairment individuals, encompassing (micro-)structural, physiological, and functional MRI sequences from 10 European parent cohorts. Processed and raw images, and image-derived (endo-)phenotypes, are organized in Brain Imaging Data Structure (BIDS) standards and accessible upon request, to enhance generalizability and comparability between future neuroimaging studies. This dataset supports preclinical Alzheimer’s disease (AD) and aging-related research by enabling robust multimodal analyses of neurodegeneration, microvascular pathology, and structural and functional connectivity changes, facilitating advanced investigations into preclinical AD mechanisms, informing early intervention strategies and allowing reproducible and centralized neuroimaging (endo-)phenotyping.
OBJECTIVES
This study explored whether distinct Alzheimer's disease (AD) structural atrophy subtypes exhibit divergent functional profiles.
DESIGN
A cross-sectional multimodal neuroimaging and electrophysiological study.
SETTING
Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China....
Dong Xu, Huanhuan Zhang, Zhiyan Piao et al.· International Psychogeriatri...· 0 citations
Bomarker-confirmed AD comprised internally reproducible atrophy trajectories with distinct cognitive, vascular, and molecular profiles and may complement fluid biomarkers and conventional volumetry for patient stratification and prognosis.
Chen-Hui Mao, Yu-Yue Qiu, Bo Li et al.· NeuroImage· 0 citations
Purpose Brain ageing involves interrelated changes in molecular processes, neuroinflammatory mechanisms, brain macro- and microstructure, sleep physiology, and cognition. The 50 to 70 years age range represents a critical transition period, in which these subtle alterations may precede measurable cognitive decline and...
Antoine Jacquemin, Ji-Qing Huang, N. Beliy et al.· bioRxiv· 0 citations
These findings, replicated in four diverse and independent datasets, support imaging-based subtyping as a scalable and clinically translatable approach for capturing heterogeneity in AD pathophysiology and associated cognitive trajectories.
A. Metz, Cassandra Polizzi, R. Moqadam et al.· medRxiv· 0 citations
Current limitations of standardisation, reproducibility, and external validation that remain prerequisites before quantitative VCID imaging achieves formal regulatory biomarker qualification are outlined.
Jose Federico Ojeda-Esparza, D. Botta, A. Fitsiori et al.· British Journal of Radiology· 0 citations
It is suggested that MRI-derived measures of cortical thickness, tissue volumes, BPV, and BPF provide useful structural biomarkers of AD and emphasize the importance of considering voxel geometry and segmentation methodology when evaluating neuroimaging biomarkers.