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  Mitigating the impact of flip angle and orientation dependence in single compartment R2* estimates via 2-pool modeling

Milotta, G., Corbin, N., Lambert, C., Lutti, A., Mohammadi, S., & Callaghan, M. F. (2023). Mitigating the impact of flip angle and orientation dependence in single compartment R2* estimates via 2-pool modeling. Magnetic Resonance in Medicine, 89(1), 128-143. doi:10.1002/mrm.29428.

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 Creators:
Milotta, Giorgia1, Author
Corbin, Nadège1, 2, Author
Lambert, Christian1, Author
Lutti, Antoine3, Author
Mohammadi, Siawoosh4, 5, Author           
Callaghan, Martina F1, Author
Affiliations:
1Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, United Kingdom, ou_persistent22              
2Centre de Résonance Magnétique des Systèmes Biologiques, Université de Bordeaux, France, ou_persistent22              
3Département des Neurosciences Cliniques, Laboratoire de Recherche en Neuroimagerie (LREN), Centre hospitalier universitaire vaudois, Lausanne, Switzerland, ou_persistent22              
4Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany, ou_persistent22              
5Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205649              

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Free keywords: R2* mapping; T2*; VFA; Mono-exponential; Multi-compartment; Single compartment
 Abstract: Purpose: The effective transverse relaxation rate ( R∗2 ) is influenced by biological features that make it a useful means of probing brain microstructure. However, confounding factors such as dependence on flip angle (α) and fiber orientation with respect to the main field ( θ ) complicate interpretation. The α- and θ -dependence stem from the existence of multiple sub-voxel micro-environments (e.g., myelin and non-myelin water compartments). Ordinarily, it is challenging to quantify these sub-compartments; therefore, neuroscientific studies commonly make the simplifying assumption of a mono-exponential decay obtaining a single R∗2 estimate per voxel. In this work, we investigated how the multi-compartment nature of tissue microstructure affects single compartment R∗2 estimates.


Methods: We used 2-pool (myelin and non-myelin water) simulations to characterize the bias in single compartment R∗2 estimates. Based on our numeric observations, we introduced a linear model that partitions R∗2 into α-dependent and α-independent components and validated this in vivo at 7T. We investigated the dependence of both components on the sub-compartment properties and assessed their robustness, orientation dependence, and reproducibility empirically.


Results: R∗2 increased with myelin water fraction and residency time leading to a linear dependence on α. We observed excellent agreement between our numeric and empirical results. Furthermore, the α-independent component of the proposed linear model was robust to the choice of α and reduced dependence on fiber orientation, although it suffered from marginally higher noise sensitivity.


Conclusion: We have demonstrated and validated a simple approach that mitigates flip angle and orientation biases in single-compartment R∗2 estimates.

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Language(s): eng - English
 Dates: 2022-07-082022-02-242022-08-082022-09-262023-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1002/mrm.29428
Other: epub 2022
PMID: 36161672
 Degree: -

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Project name : -
Grant ID : 203147/Z/16/Z
Funding program : -
Funding organization : Wellcome Trust
Project name : -
Grant ID : 320030_184784
Funding program : -
Funding organization : Swiss National Science Foundation (SNSF)

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Title: Magnetic Resonance in Medicine
Source Genre: Journal
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Publ. Info: New York : Wiley-Liss
Pages: - Volume / Issue: 89 (1) Sequence Number: - Start / End Page: 128 - 143 Identifier: ISSN: 0740-3194
CoNE: https://pure.mpg.de/cone/journals/resource/954925538149