Minyoung Kim, Inpyeong Hwang, Seung Hong Choi, Jaeseok Park, Taehoon Shin
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引用次数: 0
摘要
速度选择性(VS)磁化准备在非对比度增强(NCE)磁共振血管造影(MRA)中大有可为,它能通过一次三维采集直接生成正血管造影对比度。然而,现有的 VS-MRA 方法存在一个问题,即在一定速度(称为速度视场(vFOV))周围存在混叠饱和,这会导致动脉中出现不希望出现的信号丢失。本研究旨在开发一种新版 VS 准备脉冲序列,以克服传统 VS 准备中的混叠饱和问题。利用激发曲线是激发 k 空间采样的傅立叶变换这一事实,我们通过相应缩放梯度脉冲对 k 空间进行非均匀采样,使混叠激发在速度上扩散。变密度采样函数经过数值优化,使速度通带信号的平均值最大化,同时使其方差最小化。通过布洛赫模拟验证了优化的可变密度 VS 磁化,并将其应用于健康受试者的外周 NCE MRA。体内实验表明,所提出的可变密度 VS-MRA 显著降低了传统 VS-MRA 中观察到的动脉信号损失,更高的动脉信噪比(58.50 ± 14.29 vs. 55.54 ± 12.32;p<0.05)证明了这一点。
Variable-density velocity-selective magnetization preparation for non-contrast-enhanced peripheral MR angiography.
Velocity-selective (VS) magnetization preparation has shown great promise for non-contrast-enhanced (NCE) magnetic resonance angiography (MRA) with the ability to generate positive angiographic contrast directly using a single 3D acquisition. However, existing VS-MRA methods have an issue of aliased saturation around a certain velocity, known as velocity field-of-view (vFOV), which can cause undesired signal loss in arteries. This study aimed to develop a new version of the VS preparation pulse sequence that overcomes the aliased saturation problem in conventional VS preparation. Utilizing the fact that an excitation profile is the Fourier transform of excitation k-space sampling, we sampled the k-space in a non-uniform fashion by scaling gradient pulses accordingly to have aliased excitation diffused over velocity. The variable density sampling function was numerically optimized to maximize the average of the velocity passband signal while minimizing its variance. The optimized variable density VS magnetization was validated through Bloch simulations and applied to peripheral NCE MRA in healthy subjects. The in-vivo experiments showed that the proposed variable density VS-MRA significantly lowered arterial signal loss observed in conventional VS-MRA, as evidenced by a higher arterial signal-to-noise ratio (58.50 ± 14.29 vs. 55.54 ± 12.32; p < 0.05) and improved artery-to-background contrast-to-noise ratio (22.75 ± 7.57 vs. 20.60 ± 6.51; p < 0.05).