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

PURPOSE: The effective transverse relaxation rate ([Formula: see text]) 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 ([Formula: see text]) complicate interpretation. The α‐ and [Formula: see text] ‐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 [Formula: see text] estimate per voxel. In this work, we investigated how the multi‐compartment nature of tissue microstructure affects single compartment [Formula: see text] estimates. METHODS: We used 2‐pool (myelin and non‐myelin water) simulations to characterize the bias in single compartment [Formula: see text] estimates. Based on our numeric observations, we introduced a linear model that partitions [Formula: see text] 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: [Formula: see text] 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 [Formula: see text] estimates.