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  Synthetic quantitative MRI through relaxometry modelling

Callaghan, M., Mohammadi, S., & Weiskopf, N. (2016). Synthetic quantitative MRI through relaxometry modelling. NMR in Biomedicine, 29(12), 1729-1738. doi:10.1002/nbm.3658.

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 Creators:
Callaghan, Martina1, Author
Mohammadi, Siawoosh1, 2, Author
Weiskopf, Nikolaus1, 3, Author           
Affiliations:
1Wellcome Trust Centre for Neuroimaging, University College London, United Kingdom, ou_persistent22              
2Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany, ou_persistent22              
3Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205649              

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Free keywords: Magnetization transfer; Relaxometry; Synthetic quantitative MRI
 Abstract: Quantitative MRI (qMRI) provides standardized measures of specific physical parameters that are sensitive to the underlying tissue microstructure and are a first step towards achieving maps of biologically relevant metrics through in vivo histology using MRI. Recently proposed models have described the interdependence of qMRI parameters. Combining such models with the concept of image synthesis points towards a novel approach to synthetic qMRI, in which maps of fundamentally different physical properties are constructed through the use of biophysical models. In this study, the utility of synthetic qMRI is investigated within the context of a recently proposed linear relaxometry model. Two neuroimaging applications are considered. In the first, artefact-free quantitative maps are synthesized from motion-corrupted data by exploiting the over-determined nature of the relaxometry model and the fact that the artefact is inconsistent across the data. In the second application, a map of magnetization transfer (MT) saturation is synthesized without the need to acquire an MT-weighted volume, which directly leads to a reduction in the specific absorption rate of the acquisition. This feature would be particularly important for ultra-high field applications. The synthetic MT map is shown to provide improved segmentation of deep grey matter structures, relative to segmentation using T1 -weighted images or R1 maps. The proposed approach of synthetic qMRI shows promise for maximizing the extraction of high quality information related to tissue microstructure from qMRI protocols and furthering our understanding of the interrelation of these qMRI parameters.

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Language(s): eng - English
 Dates: 2016-08-172016-03-172016-09-162016-10-18
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1002/nbm.3658
PMID: 27753154
PMC: PMC5132086
Other: Epub 2016
 Degree: -

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Project name : Non-invasive in vivo histology in health and disease using Magnetic Resonance Imaging (MRI) / HMRI
Grant ID : 616905
Funding program : FP7 (ERC-2013-CoG)
Funding organization : European Research Council
Project name : -
Grant ID : MO 2397/1‐1
Funding program : -
Funding organization : Deutsche Forschungsgemeinschaft
Project name : -
Grant ID : 091593/Z/10/Z
Funding program : -
Funding organization : Wellcome Trust

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Title: NMR in Biomedicine
Source Genre: Journal
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Pages: - Volume / Issue: 29 (12) Sequence Number: - Start / End Page: 1729 - 1738 Identifier: ISSN: 0952-3480
CoNE: https://pure.mpg.de/cone/journals/resource/954925574973