The MR transverse relaxation rate,
, has been widely used to detect iron and myelin content in tissue. However, it is also sensitive to macroscopic
B0 inhomogeneities. One approach to correct for the
B0 effect is to fit gradient-echo signals with the three-parameter model, a sinc function-weighted monoexponential decay. However, such three-parameter models are subject to increased noise sensitivity. To address this issue, this study presents a two-stage fitting procedure based on the three-parameter model to mitigate the
B0 effect and reduce the noise sensitivity of
measurement in the mouse brain at 7T. MRI scans were performed on eight healthy mice. The gradient-echo signals were fitted with the two-stage fitting procedure to generate
. The signals were also fitted with the monoexponential and three-parameter models to generate
and
, respectively. Regions of interest (ROIs), including the corpus callosum, internal capsule, somatosensory cortex, caudo-putamen, thalamus, and lateral ventricle, were selected to evaluate the within-ROI mean and standard deviation (SD) of the
measurements. The results showed that the Akaike information criterion of the monoexponential model was significantly reduced by using the three-parameter model in the selected ROIs (
p = 0.0039–0.0078). However, the within-ROI SD of
using the three-parameter model was significantly higher than that of the
in the internal capsule, caudo-putamen, and thalamus regions (
p = 0.0039), a consequence partially due to the increased noise sensitivity of the three-parameter model. With the two-stage fitting procedure, the within-ROI SD of
was significantly reduced by 7.7–30.2% in all ROIs, except for the somatosensory cortex region with a fast in-plane variation of the
B0 gradient field (
p = 0.0039–0.0078). These results support the utilization of the two-stage fitting procedure to mitigate the
B0 effect and reduce noise sensitivity for
measurement in the mouse brain.
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