Smith, E.E., Biessels, G.J., De Guio, F. et al. (46 more authors) (2019) Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, 11. pp. 191-204. ISSN 2352-8729
Abstract
Introduction
Many consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease.
Methods
Surveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis.
Results
A framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness-neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository.
Conclusions
The HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2019 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer’s Association. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Cerebrovascular disease; Stroke; Dementia; Magnetic resonance imaging; Radiology |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 20 Nov 2019 09:14 |
Last Modified: | 20 Nov 2019 09:14 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.dadm.2019.01.002 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:153344 |
Download
Licence: CC-BY-NC-ND 4.0