Kim Sang-Hoon, Kang Chang-Ki
School of Medicine, Kyungpook National University, Daegu, Republic of Korea.
Department of Radiological Science & Neuroscience Research Institute, Gachon University, Incheon, Republic of Korea.
Magn Reson Imaging. 2016 Feb;34(2):120-6. doi: 10.1016/j.mri.2015.10.015. Epub 2015 Oct 24.
To investigate a method of dual k-space unaliasing by Fourier-encoding the overlaps using the temporal dimension (DUNFOLD), a novel technique for high temporal resolution 3D functional brain imaging.
Two different methods of unaliasing by Fourier-encoding the overlaps using the temporal dimension (UNFOLD), excitation UNFOLD (XUNFOLD) and acquisition UNFOLD, were merged to obtain a DUNFOLD. The feasibility of the DUNFOLD technique was examined by using a phantom and comparing its result to that of the previous XUNFOLD method. A high temporal resolution 3D functional brain imaging study was also performed, focusing on the microvascular response. Three different temporal resolutions, 20s, 10s and 5s, were tested with a spatial resolution of 0.6(3) mm3 to evaluate the method. The vascular regions of interest were selected for data analysis.
The DUNFOLD method achieved a temporal resolution approximately four times greater than those of the UNFOLD and XUNFOLD methods, without apparent signal degradation. The vascular responses in the visual cortex were obtained with high spatiotemporal resolution by using the DUNFOLD method during visual stimulation. For small vessels, the percentage change in the signal reached 18%.
The proposed DUNFOLD method yields a temporal resolution higher than those of the previous UNFOLD and XUNFOLD methods. The conclusions are likely to be important for functional imaging studies, especially those targeting cerebral vascular responsiveness.
研究一种通过利用时间维度对重叠部分进行傅里叶编码来实现双k空间去混叠的方法(DUNFOLD),这是一种用于高时间分辨率三维脑功能成像的新技术。
将两种不同的通过利用时间维度对重叠部分进行傅里叶编码来实现去混叠的方法(UNFOLD),即激发去混叠(XUNFOLD)和采集去混叠,合并以获得DUNFOLD。通过使用体模并将其结果与先前的XUNFOLD方法的结果进行比较,来检验DUNFOLD技术的可行性。还进行了一项高时间分辨率三维脑功能成像研究,重点关注微血管反应。在空间分辨率为0.6(3)mm³的情况下,测试了三种不同的时间分辨率,即20秒、10秒和5秒,以评估该方法。选择感兴趣的血管区域进行数据分析。
DUNFOLD方法实现的时间分辨率比UNFOLD和XUNFOLD方法高约四倍,且无明显信号衰减。在视觉刺激期间,通过使用DUNFOLD方法以高时空分辨率获得了视觉皮层中的血管反应。对于小血管,信号的百分比变化达到了18%。
所提出的DUNFOLD方法产生的时间分辨率高于先前的UNFOLD和XUNFOLD方法。这些结论可能对功能成像研究很重要,尤其是针对脑血管反应性的研究。