Loecher Michael, Ennis Daniel B
Department of Radiology, Stanford University, Stanford, California, USA.
Department of Radiology, VA Palo Alto Health Care System, Palo Alto, California, USA.
Magn Reson Med. 2025 Mar;93(3):1104-1116. doi: 10.1002/mrm.30336. Epub 2024 Oct 14.
Phase contrast MRI (PC-MRI) is used clinically to measure velocities in the body, but systematic background phase errors caused by magnetic field imperfections corrupt the velocity measurements with offsets that limit clinical utility. This work aims to minimize systematic background phase errors in PC-MRI, thereby maximizing the accuracy of velocity measurements.
The MRI scanner's background phase errors from eddy currents and mechanical oscillations were modeled using the gradient impulse response function (GIRF). Gradient waveforms were then numerically optimized using the GIRF to create pulse sequences that minimize the background phase errors. The pulse sequences were tested in a static phantom where the predicted response could be compared directly to the measured background velocity. The optimized acquisitions were then tested in human subjects, where flow rates and background errors were compared to conventional PC-MRI.
When using the GIRF-optimized gradient waveforms, the predicted background phase was within 0.6 [95% CI = -3.4, 5.4] mm/s of the measured background phase in a static phantom. Excellent agreement was seen for in vivo blood flow values (flow rate agreement = 0.96), and the background phase was reduced by 78.8 18.7%.
This work shows that using a GIRF to model the effects of magnetic field imperfections combined with numerically optimized gradient waveforms enables PC-MRI waveforms to be designed to produce a minimal background phase in the most time-efficient manner. The methodology could be adapted for other MRI sequences where similar magnetic field errors affect measurements.
相位对比磁共振成像(PC-MRI)在临床上用于测量体内流速,但由磁场缺陷引起的系统性背景相位误差会以偏移量干扰流速测量,从而限制了其临床应用。本研究旨在最小化PC-MRI中的系统性背景相位误差,从而最大限度地提高流速测量的准确性。
利用梯度脉冲响应函数(GIRF)对MRI扫描仪中来自涡流和机械振荡的背景相位误差进行建模。然后使用GIRF对梯度波形进行数值优化,以创建能最小化背景相位误差的脉冲序列。在静态体模中对脉冲序列进行测试,在该体模中可以将预测响应与测量的背景流速直接进行比较。然后在人体受试者中对优化后的采集进行测试,将流速和背景误差与传统PC-MRI进行比较。
使用GIRF优化的梯度波形时,在静态体模中预测的背景相位与测量的背景相位相差在0.6 [95%置信区间 = -3.4, 5.4] mm/s以内。体内血流值显示出极好的一致性(流速一致性 = 0.96),背景相位降低了78.8±18.7%。
本研究表明,利用GIRF对磁场缺陷的影响进行建模,并结合数值优化的梯度波形,能够以最省时的方式设计PC-MRI波形,从而产生最小的背景相位。该方法可适用于其他受类似磁场误差影响测量的MRI序列。