Han Paul Kyu, Park Sung-Hong, Kim Seong-Gi, Ye Jong Chul
Bio Imaging and Signal Processing Lab, Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea ; Magnetic Resonance Imaging Lab, Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea.
Magnetic Resonance Imaging Lab, Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea.
Biomed Res Int. 2015;2015:131926. doi: 10.1155/2015/131926. Epub 2015 Aug 27.
Conventional functional magnetic resonance imaging (fMRI) technique known as gradient-recalled echo (GRE) echo-planar imaging (EPI) is sensitive to image distortion and degradation caused by local magnetic field inhomogeneity at high magnetic fields. Non-EPI sequences such as spoiled gradient echo and balanced steady-state free precession (bSSFP) have been proposed as an alternative high-resolution fMRI technique; however, the temporal resolution of these sequences is lower than the typically used GRE-EPI fMRI. One potential approach to improve the temporal resolution is to use compressed sensing (CS). In this study, we tested the feasibility of k-t FOCUSS--one of the high performance CS algorithms for dynamic MRI--for non-EPI fMRI at 9.4 T using the model of rat somatosensory stimulation. To optimize the performance of CS reconstruction, different sampling patterns and k-t FOCUSS variations were investigated. Experimental results show that an optimized k-t FOCUSS algorithm with acceleration by a factor of 4 works well for non-EPI fMRI at high field under various statistical criteria, which confirms that a combination of CS and a non-EPI sequence may be a good solution for high-resolution fMRI at high fields.
传统的功能磁共振成像（fMRI）技术，即梯度回波（GRE）回波平面成像（EPI），在高磁场下对由局部磁场不均匀性引起的图像失真和退化很敏感。已提出诸如扰相梯度回波和平衡稳态自由进动（bSSFP）等非EPI序列作为一种替代的高分辨率fMRI技术；然而，这些序列的时间分辨率低于通常使用的GRE-EPI fMRI。一种提高时间分辨率的潜在方法是使用压缩感知（CS）。在本研究中，我们使用大鼠体感刺激模型，测试了k-t FOCUSS（一种用于动态MRI的高性能CS算法）在9.4 T下用于非EPI fMRI的可行性。为了优化CS重建的性能，研究了不同的采样模式和k-t FOCUSS变体。实验结果表明，在各种统计标准下，加速因子为4的优化k-t FOCUSS算法在高场非EPI fMRI中表现良好，这证实了CS与非EPI序列的组合可能是高场高分辨率fMRI的一个良好解决方案。
