摘要
目的对比双指数弥散模型和弥散峰度模型对正常前列腺组织的弥散加权成像在1.5 T不同b值分段下的拟合效果。材料与方法采集11例健康男性前列腺T2加权成像和弥散加权磁共振的多b值成像,从0到3000 s/mm2中选取31个b值,将两个弥散模型对弥散加权信号原始数据作曲线拟合,根据曲线拟合计算的拟合信号强度值与原始图像采集的信号值的差值大小,选取对某个模型该差值都较小的对应的连续多个b值,组成一个分段,该模型则为此b值分段最优的拟合模型。结果在所有b值数据的整体拟合中,双指数弥散模型调整后的决定系数R2大于弥散峰度模型。b值在500~1000 s/mm2时,弥散峰度模型的均方根误差比双指数弥散模型更小;b值在0~500 s/mm2和1000~3000 s/mm2时,双指数弥散模型的均方根误差比弥散峰度模型更小。结论双指数弥散模型和弥散峰度模型对正常前列腺的弥散加权成像在不同的b值下的拟合优度不同,不同b值分段具有不同的最优拟合模型,将两个模型结合起来对前列腺弥散加权成像进行分析可能会为临床的诊断提供更多的帮助。
Objective:To compare the fitting behavior of biexponential diffusion model and diffusion kurtosis model (DKI) on diffusion-weighted imaging (DWI) of healthy prostate at different b-values at 1.5 T.Materials and Methods:T2-weighted imaging and DWI of prostate was performed on 11 healthy man with 31 b-values ranging from 0 to 3000 s/mm2. The DWI signals were iftted into two diffusion models. The continuous b-values with smaller deviation between the signal intensities of iftted curves of one model and the acquired original data can be combined into one section. The best iftting model could be selected for the b-values sections.Results:The adjusted R2 of the full b-values for biexponential diffusion model was bigger than that for DKI. The RMSE of DKI was smaller than biexponential model with b-values from 500 to 1000 s/mm2, and the RMSE of biexponential diffusion model was smaller than DKI with b-values ranging from 0 to 500 s/mm2 and from 1000 to 3000 s/mm2.Conclusion:For DWI of prostate, biexponential diffusion model and DKI behaviors diversely on the goodness of iftting at different b-values. The different b-values sections can be iftted best with different diffusion models. It may potentially provide more help for clinical diagnosis when combining the biexponential diffusion model and DKI.
出处
《磁共振成像》
CAS
CSCD
2015年第8期631-635,共5页
Chinese Journal of Magnetic Resonance Imaging
基金
国家自然科学基金项目(编号:81371537)
关键词
双指数弥散模型
弥散峰度模型
前列腺
弥散磁共振成像
磁共振成像
Biexponential diffusion model
Diffusion kurtosis model
Prostate
Diffusion magnetic resonance imaging
Magnetic resonance imaging