背景:肾扩散加权成像(DWI)涉及微观结构和微循环,用扩散张量成像(DTI)量化,体素内不相干运动(IVIM),和混合模型。更好地理解它们的对比度可以增加特异性。
目的:用心脏相位和流量补偿(FC)扩散梯度波形测量DWI的调制。
方法:前瞻性。
方法:6名健康志愿者(年龄:22-48岁,五名女性),水幻影.
未经批准:3-T,具有二维回波平面成像的原型DWI序列,和双极(BP)或FC梯度。二维半傅立叶单发涡轮自旋回波(HASTE)。多相2D破坏梯度回波相位对比(PC)MRI。
结果:定性比较了BP和FC水信号衰减。在PC-MRI上观察肾动脉和速度。收缩压(峰值速度),舒张(末期稳定速度),并确定了收缩期前(峰值速度之前)阶段。在每个肾脏内基于相互信息的DWI回顾性自配准之后,和Marchenko-Pastur主成分分析(MPPCA)去噪,联合IVIM-DTI分析估计平均扩散率(MD),分数各向异性(FA),和来自组织扩散率(Dt)的特征值(λi),灌注分数(fp),和伪扩散率(Dp,Dp,轴向,Dp,径向),对于每个组织(皮质/髓质,分别在B0/FA上分段),阶段,和波形(BP,FC)。蒙特卡罗水扩散模拟辅助数据解释。
方法:混合模型回归研究了组织类型和脉冲序列之间的差异。单变量一般线性模型分析探讨了心脏相位之间的变化。在扩散指标和肾动脉速度之间测量Spearman相关性。统计学意义水平设定为P<0.05。
结果:水BP和FC信号衰减没有差异。对于λ1,发生了明显的脉冲序列依赖性,λ3,FA,Dp,fp,Dp,轴向,Dp,皮质和髓质放射状,和髓质λ2。除MD(收缩期[P=0.224];舒张期[P=0.556])外,所有指标的BP均存在明显的皮质/髓质差异。Dp发生了明显的相位依赖性,Dp,轴向,Dp,BP和髓质λ1的径向,λ2,λ3,FC的MD。FA与速度显著相关。蒙特卡罗模拟表明髓质测量与34μm小管直径一致。
结论:心脏门控和血流补偿调节肾脏扩散的测量。
方法:2技术效率阶段:2.
BACKGROUND: Renal diffusion-weighted imaging (DWI) involves microstructure and microcirculation, quantified with diffusion tensor imaging (DTI), intravoxel incoherent motion (IVIM), and hybrid models. A better understanding of their contrast may increase specificity.
OBJECTIVE: To measure modulation of DWI with cardiac phase and flow-compensated (FC) diffusion gradient waveforms.
METHODS: Prospective.
METHODS: Six healthy volunteers (ages: 22-48 years, five females), water phantom.
UNASSIGNED: 3-T, prototype DWI sequence with 2D echo-planar imaging, and bipolar (BP) or FC gradients. 2D Half-Fourier Single-shot Turbo-spin-Echo (HASTE). Multiple-phase 2D spoiled gradient-echo phase contrast (PC) MRI.
RESULTS: BP and FC water signal decays were qualitatively compared. Renal arteries and velocities were visualized on PC-MRI. Systolic (peak velocity), diastolic (end stable velocity), and pre-systolic (before peak velocity) phases were identified. Following mutual information-based retrospective self-registration of DWI within each kidney, and Marchenko-Pastur Principal Component Analysis (MPPCA) denoising, combined IVIM-DTI analysis estimated mean diffusivity (MD), fractional anisotropy (FA), and eigenvalues (λi) from tissue diffusivity (Dt ), perfusion fraction (fp ), and pseudodiffusivity (Dp , Dp,axial , Dp,radial ), for each tissue (cortex/medulla, segmented on b0/FA respectively), phase, and waveform (BP, FC). Monte Carlo water diffusion simulations aided data interpretation.
METHODS: Mixed model regression probed differences between tissue types and pulse sequences. Univariate general linear model analysis probed variations among cardiac phases. Spearman correlations were measured between diffusion metrics and renal artery velocities. Statistical significance level was set at P < 0.05.
RESULTS: Water BP and FC signal decays showed no differences. Significant pulse sequence dependence occurred for λ1 , λ3 , FA, Dp , fp , Dp,axial , Dp,radial in cortex and medulla, and medullary λ2 . Significant cortex/medulla differences occurred with BP for all metrics except MD (systole [P = 0.224]; diastole [P = 0.556]). Significant phase dependence occurred for Dp , Dp,axial , Dp,radial for BP and medullary λ1 , λ2 , λ3 , MD for FC. FA correlated significantly with velocity. Monte Carlo simulations indicated medullary measurements were consistent with a 34 μm tubule diameter.
CONCLUSIONS: Cardiac gating and flow compensation modulate of measurements of renal diffusion.
METHODS: 2 TECHNICAL EFFICACY STAGE: 2.