Mitigating the impact of flip angle and orientation dependence in single compartment R2* estimates via 2-pool modeling
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Mitigating the impact of flip angle and orientation dependence in single compartment R2* estimates via 2-pool modeling. / Milotta, Giorgia; Corbin, Nadège; Lambert, Christian; Lutti, Antoine; Mohammadi, Siawoosh; Callaghan, Martina F.
in: MAGN RESON MED, Jahrgang 89, Nr. 1, 01.2023, S. 128-143.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
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TY - JOUR
T1 - Mitigating the impact of flip angle and orientation dependence in single compartment R2* estimates via 2-pool modeling
AU - Milotta, Giorgia
AU - Corbin, Nadège
AU - Lambert, Christian
AU - Lutti, Antoine
AU - Mohammadi, Siawoosh
AU - Callaghan, Martina F
N1 - © 2022 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.
PY - 2023/1
Y1 - 2023/1
N2 - PURPOSE: The effective transverse relaxation rate ( R 2 * $$ {\mathrm{R}}_2^{\ast } $$ ) 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 $$ \uptheta $$ ) complicate interpretation. The α- and θ $$ \uptheta $$ -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 * $$ {\mathrm{R}}_2^{\ast } $$ estimate per voxel. In this work, we investigated how the multi-compartment nature of tissue microstructure affects single compartment R 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.METHODS: We used 2-pool (myelin and non-myelin water) simulations to characterize the bias in single compartment R 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates. Based on our numeric observations, we introduced a linear model that partitions R 2 * $$ {\mathrm{R}}_2^{\ast } $$ 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 * $$ {\mathrm{R}}_2^{\ast } $$ 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 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.
AB - PURPOSE: The effective transverse relaxation rate ( R 2 * $$ {\mathrm{R}}_2^{\ast } $$ ) 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 $$ \uptheta $$ ) complicate interpretation. The α- and θ $$ \uptheta $$ -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 * $$ {\mathrm{R}}_2^{\ast } $$ estimate per voxel. In this work, we investigated how the multi-compartment nature of tissue microstructure affects single compartment R 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.METHODS: We used 2-pool (myelin and non-myelin water) simulations to characterize the bias in single compartment R 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates. Based on our numeric observations, we introduced a linear model that partitions R 2 * $$ {\mathrm{R}}_2^{\ast } $$ 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 * $$ {\mathrm{R}}_2^{\ast } $$ 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 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.
KW - Magnetic Resonance Imaging/methods
KW - Reproducibility of Results
KW - Myelin Sheath/chemistry
KW - Brain/diagnostic imaging
KW - Water/analysis
U2 - 10.1002/mrm.29428
DO - 10.1002/mrm.29428
M3 - SCORING: Journal article
C2 - 36161672
VL - 89
SP - 128
EP - 143
JO - MAGN RESON MED
JF - MAGN RESON MED
SN - 0740-3194
IS - 1
ER -