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The Amsterdam Ultra-high field adult lifespan database (AHEAD): A freely available multimodal 7 Tesla submillimeter magnetic resonance imaging database.
- Source :
-
NeuroImage [Neuroimage] 2020 Nov 01; Vol. 221, pp. 117200. Date of Electronic Publication: 2020 Aug 01. - Publication Year :
- 2020
-
Abstract
- Normative databases allow testing of novel hypotheses without the costly collection of magnetic resonance imaging (MRI) data. Here we present the Amsterdam Ultra-high field adult lifespan database (AHEAD). The AHEAD consists of 105 7 Tesla (T) whole-brain structural MRI scans tailored specifically to imaging of the human subcortex, including both male and female participants and covering the entire adult life span (18-80 yrs). We used these data to create probability maps for the subthalamic nucleus, substantia nigra, internal and external segment of the globus pallidus, and the red nucleus. Data was acquired at a submillimeter resolution using a multi-echo (ME) extension of the second gradient-echo image of the MP2RAGE sequence (MP2RAGEME) sequence, resulting in complete anatomical alignment of quantitative, R <subscript>1</subscript> -maps, R <subscript>2</subscript> *-maps, T <subscript>1</subscript> -maps, T <subscript>1</subscript> -weighted images, T <subscript>2</subscript> *-maps, and quantitative susceptibility mapping (QSM). Quantitative MRI maps, and derived probability maps of basal ganglia structures are freely available for further analyses.<br /> (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)
- Subjects :
- Adolescent
Adult
Aged
Aged, 80 and over
Atlases as Topic
Databases, Factual
Female
Globus Pallidus diagnostic imaging
Humans
Male
Middle Aged
Red Nucleus diagnostic imaging
Substantia Nigra diagnostic imaging
Subthalamic Nucleus diagnostic imaging
Young Adult
Globus Pallidus anatomy & histology
Magnetic Resonance Imaging
Neuroimaging
Red Nucleus anatomy & histology
Substantia Nigra anatomy & histology
Subthalamic Nucleus anatomy & histology
Subjects
Details
- Language :
- English
- ISSN :
- 1095-9572
- Volume :
- 221
- Database :
- MEDLINE
- Journal :
- NeuroImage
- Publication Type :
- Academic Journal
- Accession number :
- 32745682
- Full Text :
- https://doi.org/10.1016/j.neuroimage.2020.117200