摘要
目的探讨3.0T水脂分离梯度回波序列在一次屏息内完成定量分析肝脏脂肪的可行性及其参数优化。方法利用GE Signa HDx 3.0T MR系统对自制体模及42名受检者行迭代最小二乘法非对称采集水脂分离(IDEAL)梯度回波序列和单体素1 H-MRS,通过分析接收带宽(BW)、翻转角(FA)和矩阵(Matrix)的变化对体模脂肪定量分析的影响,确定以IDEAL梯度回波行脂肪定量分析的最优成像参数;以1 H-MRS测定的脂肪含量为参考标准,采用Spearman相关分析对IDEAL梯度回波序列测得数据进行相关性分析。结果应用IDEAL梯度回波序列行体模脂肪定量分析时,BW和FA对结果的影响较大;BW为200kHz、FA为12°时,体模脂肪定量分析结果与MRS的关联性最佳(r=0.997,P<0.05),在此条件下,应用IDEAL梯度回波序列和1 H-MRS测得的肝脏脂肪含量分别为(9.48±5.42)%和(10.13±8.06)%,二者呈正相关(r=0.872,P<0.05)。结论经参数优化的IDEAL梯度回波序列可在一次屏息内定量分析肝脏脂肪含量;成像时需合理调整FA和BW。
Objective To observe the feasibility of liver fat quantification using iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) gradient echo imaging at 3.0T MR system, and to optimize its imaging parameters. Methods IDEAL gradient echo imaging and single voxel 1H-MRS of phantoms and 42 healthy volunteers were performed on a GE Signa HDx 3.0T MR system. Fat quantification deviations caused by variation of flip angle, bandwidth and matrix were analyzed to optimize IDEAL gradient echo imaging parameters. Taking 1H-MRS as reference standards, the accuracy of liver fat fraction obtained by parameter-optimized IDEAL gradient echo imaging was evaluated using Spearman statistical method. Results Fat quantification results varied with the changes of bandwidth and flip angle. The best results of liver fat fraction were achieved under the condition of flip angle 12°, along with bandwidth 200 kHz, and the correlation of phantoms fat quantification between IDEAL gradient echo imaging and MRS was very good (r=0.997, P〈0.05). The mean liver fat fraction of 42 subjects obtained with MR imaging and MRS was (9.48±5.42)% and (10.13±8.06)% ( r=0.872,P〈0.05). Conclusion IDEAL gradient echo imaging with the optimized parameters is feasible to apply in clinical for quantification of liver fat fraction during one breath, with a fine tuning of flip angle and bandwidth.
出处
《中国医学影像技术》
CSCD
北大核心
2014年第3期457-461,共5页
Chinese Journal of Medical Imaging Technology
基金
北京大学人民医院研究与发展基金资助项目(RDC2013-02)
关键词
梯度回波序列
迭代最小二乘法非对称采集水脂分离
体模
脂肪定量
Gradient-Echo Imaging
Iterative decomposition of water and fat with echo asymmetry and least-squares esti-mation
Phantom
Fat quantification