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Mitigating the impact of flip angle and orientation dependence in single compartment R2 * estimates via 2‐pool modeling
Author(s) -
Milotta Giorgia,
Corbin Nadège,
Lambert Christian,
Lutti Antoine,
Mohammadi Siawoosh,
Callaghan Martina F.
Publication year - 2023
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.29428
Subject(s) - biological system , voxel , exponential function , imaging phantom , orientation (vector space) , compartment (ship) , robustness (evolution) , flip angle , myelin , materials science , molecular physics , statistical physics , chemistry , computer science , physics , mathematics , optics , biology , mathematical analysis , neuroscience , magnetic resonance imaging , geology , geometry , artificial intelligence , medicine , biochemistry , oceanography , radiology , gene , central nervous system
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‐ andθ $$ \uptheta $$ ‐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 singleR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimate per voxel. In this work, we investigated how the multi‐compartment nature of tissue microstructure affects single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates. Methods We used 2‐pool (myelin and non‐myelin water) simulations to characterize the bias in single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates. Based on our numeric observations, we introduced a linear model that partitionsR 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. ResultsR 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‐compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.