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  Error quantification in multi-parameter mapping facilitates robust estimation and enhanced group level sensitivity

Mohammadi, S., Streubel, T., Klock, L., Edwards, L., Lutti, A., Pine, K., et al. (2022). Error quantification in multi-parameter mapping facilitates robust estimation and enhanced group level sensitivity. NeuroImage, 262: 119529. doi:10.1016/j.neuroimage.2022.119529.

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 Creators:
Mohammadi, Siawoosh1, 2, Author           
Streubel, Tobias1, 2, Author           
Klock, Leonie3, Author
Edwards, Luke1, Author           
Lutti, Antoine4, Author
Pine, Kerrin1, Author           
Weber, Sandra3, Author
Scheibe, Patrick1, Author           
Ziegler, Gabriel5, 6, Author
Gallinat, Jürgen3, Author
Kühn, Simone3, 7, Author
Callaghan, Martina F.8, Author
Weiskopf, Nikolaus1, 9, Author           
Tabelow, Karsten10, Author
Affiliations:
1Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany, ou_persistent22              
2Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_2205649              
3Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Germany, ou_persistent22              
4Laboratoire de Recherche en Neuroimagerie (LREN), Centre hospitalier universitaire vaudois, Lausanne, Switzerland, ou_persistent22              
5Institute of Cognitive Neurology and Dementia Research, Otto von Guericke University Magdeburg, Germany, ou_persistent22              
6German Center for Neurodegenerative Diseases, Magdeburg, Germany, ou_persistent22              
7Lise Meitner Group for Environmental Neuroscience, Max Planck Institute for Human Development, Berlin, Germany, ou_persistent22              
8Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, United Kingdom, ou_persistent22              
9Felix Bloch Institute for Solid State Physics, University of Leipzig, Germany, ou_persistent22              
10Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany, ou_persistent22              

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Free keywords: Multi-parameter mapping; Quantitative MRI; Error propagation; Signal-to-noise ratio; Robust estimate
 Abstract: Multi-Parameter Mapping (MPM) is a comprehensive quantitative neuroimaging protocol that enables estimation of four physical parameters (longitudinal and effective transverse relaxation rates and , proton density , and magnetization transfer saturation ) that are sensitive to microstructural tissue properties such as iron and myelin content. Their capability to reveal microstructural brain differences, however, is tightly bound to controlling random noise and artefacts (e.g. caused by head motion) in the signal. Here, we introduced a method to estimate the local error of , and maps that captures both noise and artefacts on a routine basis without requiring additional data. To investigate the method's sensitivity to random noise, we calculated the model-based signal-to-noise ratio (mSNR) and showed in measurements and simulations that it correlated linearly with an experimental raw-image-based SNR map. We found that the mSNR varied with MPM protocols, magnetic field strength (3T vs. 7T) and MPM parameters: it halved from to and decreased from to by a factor of 3-4. Exploring the artefact-sensitivity of the error maps, we generated robust MPM parameters using two successive acquisitions of each contrast and the acquisition-specific errors to down-weight erroneous regions. The resulting robust MPM parameters showed reduced variability at the group level as compared to their single-repeat or averaged counterparts. The error and mSNR maps may better inform power-calculations by accounting for local data quality variations across measurements. Code to compute the mSNR maps and robustly combined MPM maps is available in the open-source hMRI toolbox.

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Language(s): eng - English
 Dates: 2022-07-202021-12-292022-08-012022-08-012022-11-15
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1016/j.neuroimage.2022.119529
Other: epub 2022
PMID: 35926761
 Degree: -

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Project name : -
Grant ID : 616905
Funding program : -
Funding organization : European Research Council
Project name : -
Grant ID : 681094
Funding program : Horizon 2020
Funding organization : European Union
Project name : -
Grant ID : 15.0137
Funding program : -
Funding organization : Swiss State Secretariat for Education, Research and Innovation (SERI)
Project name : -
Grant ID : TRR 169/C8, SFB 936/C7
Funding program : -
Funding organization : German Research Foundation (DFG)
Project name : -
Grant ID : ERC-2016-StG-Self-Control-677804
Funding program : -
Funding organization : European Union
Project name : -
Grant ID : 203147/Z/16/Z
Funding program : -
Funding organization : Wellcome Centre for Human Neuroimaging
Project name : -
Grant ID : 320030_184784
Funding program : -
Funding organization : Swiss National Science Foundation

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 262 Sequence Number: 119529 Start / End Page: - Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166