PDF(Pubmed)
Abstract：
The MR transverse relaxation rate, R2*, 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 R2* 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 R2corr_t*. The signals were also fitted with the monoexponential and three-parameter models to generate R2nocorr* and R2corr*, 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 R2* 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 R2corr* using the three-parameter model was significantly higher than that of the R2nocorr* 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 R2corr* 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 R2* measurement in the mouse brain.
摘要：
MR横向弛豫率，R2*,已广泛用于检测组织中铁和髓鞘含量。然而,它对宏观的B0不均匀性也很敏感。校正B0效应的一种方法是用三参数模型拟合梯度回波信号，sinc函数加权单指数衰减。然而,这样的三参数模型受到增加的噪声灵敏度。为了解决这个问题，这项研究提出了基于三参数模型的两阶段拟合程序，以减轻B0效应并降低7T小鼠大脑中R2*测量的噪声敏感性。对八只健康小鼠进行MRI扫描。用两阶段拟合程序拟合梯度回波信号以生成R2corr_t*。信号还与单指数和三参数模型拟合以生成R2nocorr*和R2corr*，分别。感兴趣的地区（ROI），包括胼胝体,内囊,体感皮层,caudo-putamen,丘脑,和侧脑室,被选择来评估R2*测量的ROI内平均值和标准偏差(SD)。结果表明,在选定的ROI中使用三参数模型,单指数模型的Akaike信息准则显著降低(p=0.0039-0.0078)。然而,使用三参数模型的R2corr*的ROI内SD显着高于内囊中的R2nocorr*，caudo-putamen,和丘脑区（p=0.0039），部分原因是三参数模型的噪声灵敏度增加。采用两阶段装配程序,在所有ROI中，R2corr*的ROI内SD显著降低7.7-30.2%，除了B0梯度场的平面内快速变化的体感皮层区域（p=0.0039-0.0078）。这些结果支持利用两阶段拟合程序来减轻B0效应并降低小鼠脑中R2*测量的噪声敏感性。
