Abstract
In 3D gradient echo magnetic resonance imaging (MRI), strong field gradients B0macro are visually observed at air/tissue interfaces. At low spatial resolution in particular, the respective field gradients lead to an apparent increase in intravoxel dephasing, and subsequently, to signal loss or inaccurate R2* estimates. If the strong field gradients are measured, their influence can be removed by postprocessing. Conventional corrections usually assume a linear phase evolution with time. For high macroscopic gradient inhomogeneities near the edge of the brain and at the paranasal sinuses, however, this assumption is often broken. Herein, we explored a novel model that considers both linear and stochastic dependences of the phase evolution with echo time in the presence of weak and strong macroscopic field inhomogeneities. We tested the performance of the model at large field gradients using simulation, phantom, and human in vivo studies. The performance of the proposed approach was markedly better than the standard correction method, providing a correction equivalent to that of the conventional approach in regions with high signal to noise ratio (SNR > 10), but appearing more robust in regions with low SNR (SNR < 4). The proposed technique shows promise to improve R2* measurements in regions of large susceptibilities. The clinical and research applications still require further investigation.
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