Department of Human and Information Science, School of Information Science and Technology, Tokai University.
BioView, Inc.
Magn Reson Med Sci. 2022 Mar 1;21(2):372-379. doi: 10.2463/mrms.mp.2021-0126. Epub 2022 Feb 16.
To extract the status of hydrocephalus and other cerebrospinal fluid (CSF)-related diseases, a technique to characterize the cardiac- and respiratory-driven CSF motions separately under free breathing was developed. This technique is based on steady-state free precession phase contrast (SSFP-PC) imaging in combination with a Stockwell transform (S-transform).
2D SSFP-PC at 3 T was applied to measure the CSF velocity in the caudal-cranial direction within a sagittal slice at the midline (N = 3) under 6-, 10-, and 16-s respiratory cycles and free breathing. The frequency-dependent window width of the S-transform was controlled by a particular scaling factor, which then converted the CSF velocity waveform into a spectrogram. Based on the frequency bands of the cardiac pulsation and respiration, as determined by the electrocardiogram (ECG) and respirator pressure sensors, Gaussian bandpass filters were applied to the CSF spectrogram to extract the time-domain cardiac- and respiratory-driven waveforms.
The cardiac-driven CSF velocity component appeared in the spectrogram clearly under all respiratory conditions. The respiratory-driven velocity under the controlled respiratory cycles was observed as constant frequency signals, compared to a time-varying frequency signal under free breathing. When the widow width was optimized using the scale factor, the temporal change in the respiratory-driven CSF component was even more apparent under free breathing.
Velocity amplitude variations and transient frequency changes of both cardiac- and respiratory-driven components were successfully characterized. These findings indicated that the proposed technique is useful for evaluating CSF motions driven by different cyclic forces.
为了提取脑积水和其他与脑脊液(CSF)相关疾病的状态,开发了一种技术,可分别在自由呼吸下对心脏和呼吸驱动的 CSF 运动进行特征描述。该技术基于稳态自由进动相位对比(SSFP-PC)成像与斯托克韦尔变换(S-变换)相结合。
在 3T 下应用 2D SSFP-PC,在中线矢状位的一个层面上测量头尾向 CSF 速度(N=3),分别在 6、10 和 16 秒呼吸周期和自由呼吸下进行测量。S-变换的频率相关窗口宽度由特定的比例因子控制,然后将 CSF 速度波形转换为声谱图。基于心电图(ECG)和呼吸压力传感器确定的心脏搏动和呼吸的频率带,应用高斯带通滤波器对 CSF 声谱图进行滤波,以提取时域心脏和呼吸驱动的波形。
在所有呼吸条件下,心脏驱动的 CSF 速度分量在声谱图中清晰可见。在受控呼吸周期下,呼吸驱动的速度表现为恒定频率信号,而在自由呼吸下则表现为时变频率信号。当使用比例因子优化窗口宽度时,在自由呼吸下,呼吸驱动 CSF 成分的时间变化更加明显。
成功地对心脏和呼吸驱动成分的速度幅度变化和瞬态频率变化进行了特征描述。这些发现表明,所提出的技术可用于评估不同周期性力驱动的 CSF 运动。