目的:评估肝脏中跨场强和具有不同梯度硬件的MR扫描仪的体素内不相干运动(IVIM)定量的可重复性和叶间一致性。
方法:进行了Cramer-Rao下界优化,以确定优化的单极和运动鲁棒2D(b值和一阶运动矩[M1])IVIM-DWI采集。11名健康志愿者接受了肝脏扩散MRI检查,其中每个优化的采集在三个MRI扫描仪中获得五次。对于每个数据集,IVIM估计(扩散系数(D),伪扩散系数(d1*$${d}_1^{\\ast}$$和d2*$${d}_2^{\ast}$$),血流速度SDs(Vb1和Vb2),和灌注分数[f1和f2])使用两种信号模型(伪扩散和M1依赖性物理模型)在有和没有T2校正(fc1和fc2)和三种拟合技术(基于三指数感兴趣区域的完整和分段拟合以及血流速度SD分布拟合)。使用受试者内部和成对变异系数(CVw和CVp)比较了方法的可重复性和叶间一致性,配对样本t检验,和Bland-Altman分析.
结果:使用运动鲁棒2D(b-M1)数据采集的组合,具有T2校正的M1相关物理信号建模,和血流速度SD分布拟合,多扫描仪再现性,CVw中位数=5.09%,11.3%,9.20%,14.2%,D为12.6%,分别为Vb1、Vb2、fc1和fc2,叶间一致性与CVp=8.14%,11.9%,8.50%,49.9%,和42.0%,分别,已实现。
结论:最近提出了先进的IVIM收购,信号建模,和拟合技术可以促进肝脏中可重复的IVIM定量,根据建立用于检测的基于IVIM的定量生物标志物的需要,分期,和疾病的治疗监测。
OBJECTIVE: To evaluate reproducibility and interlobar agreement of intravoxel incoherent motion (IVIM) quantification in the liver across field strengths and MR scanners with different gradient hardware.
METHODS: Cramer-Rao lower bound optimization was performed to determine optimized monopolar and motion-robust 2D (b-value and first-order motion moment [M1]) IVIM-DWI acquisitions. Eleven healthy volunteers underwent diffusion MRI of the liver, where each optimized acquisition was obtained five times across three MRI scanners. For each data set, IVIM estimates (diffusion coefficient (D), pseudo-diffusion coefficients ( d 1 * $$ {d}_1^{\\ast } $$ and d 2 * $$ {d}_2^{\\ast } $$ ), blood velocity SDs (Vb1 and Vb2), and perfusion fractions [f1 and f2]) were obtained in the right and left liver lobes using two signal models (pseudo-diffusion and M1-dependent physical) with and without T2 correction (fc1 and fc2) and three fitting techniques (tri-exponential region of interest-based full and segmented fitting and blood velocity SD distribution fitting). Reproducibility and interlobar agreement were compared across methods using within-subject and pairwise coefficients of variation (CVw and CVp), paired sample t-tests, and Bland-Altman analysis.
RESULTS: Using a combination of motion-robust 2D (b-M1) data acquisition, M1-dependent physical signal modeling with T2 correction, and blood velocity SD distribution fitting, multiscanner reproducibility with median CVw = 5.09%, 11.3%, 9.20%, 14.2%, and 12.6% for D, Vb1, Vb2, fc1, and fc2, respectively, and interlobar agreement with CVp = 8.14%, 11.9%, 8.50%, 49.9%, and 42.0%, respectively, was achieved.
CONCLUSIONS: Recently proposed advanced IVIM acquisition, signal modeling, and fitting techniques may facilitate reproducible IVIM quantification in the liver, as needed for establishment of IVIM-based quantitative biomarkers for detection, staging, and treatment monitoring of diseases.