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Multi-site harmonization of 7 tesla MRI neuroimaging protocols

Clarke, William T., Mougin, Olivier, Driver, Ian D. ORCID:, Rua, Catarina, Morgan, Andrew T., Asghar, Michael, Clare, Stuart, Francis, Susan, Wise, Richard G. ORCID:, Rodgers, Christopher T., Carpenter, Adrian, Muir, Keith and Bowtell, Richard 2020. Multi-site harmonization of 7 tesla MRI neuroimaging protocols. NeuroImage 206 , 116335. 10.1016/j.neuroimage.2019.116335

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Increasing numbers of 7 T (7 T) magnetic resonance imaging (MRI) scanners are in research and clinical use. 7 T MRI can increase the scanning speed, spatial resolution and contrast-to-noise-ratio of many neuroimaging protocols, but technical challenges in implementation have been addressed in a variety of ways across sites. In order to facilitate multi-centre studies and ensure consistency of findings across sites, it is desirable that 7 T MRI sites implement common high-quality neuroimaging protocols that can accommodate different scanner models and software versions. With the installation of several new 7 T MRI scanners in the United Kingdom, the UK7T Network was established with an aim to create a set of harmonized structural and functional neuroimaging sequences and protocols. The Network currently includes five sites, which use three different scanner platforms, provided by two different vendors. Here we describe the harmonization of functional and anatomical imaging protocols across the three different scanner models, detailing the necessary changes to pulse sequences and reconstruction methods. The harmonized sequences are fully described, along with implementation details. Example datasets acquired from the same subject on all Network scanners are made available. Based on these data, an evaluation of the harmonization is provided. In addition, the implementation and validation of a common system calibration process is described.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Psychology
Publisher: Elsevier
ISSN: 1053-8119
Date of First Compliant Deposit: 15 January 2020
Date of Acceptance: 4 December 2019
Last Modified: 04 May 2023 20:19

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