Steady-state imaging techniques for functional brain MRI.

摘要

Since its inception in the early 1990s, functional Magnetic Resonance Imaging (fMRI) has become a primary research tool for human brain research. The fMRI technique has revealed several important findings regarding human brain function: from the retinotopic map in the visual cortex to the resting-state network. Currently, the prevalent approach in data acquisition for fMRI is a single shot echo-planar imaging based gradient-echo protocol, which optimizes the spin dephasing effects from the Blood Oxygenation Level Dependent (BOLD) contrast. Despite its widespread use, this method suffers from significant imaging artifacts, including low spatial resolution and low signal-to-noise ratio (SNR) due to an intrinsic contrast mechanism that necessitates a long echo time.; As an alternative approach to the conventional functional imaging method, we have developed a new method, "transition-band SSFP fMRI". This method, which is based on a steady-state imaging technique (balanced SSFP), possesses high SNR efficiency, providing the possibility of a high-resolution, low-distortion fMRI. Unfortunately, the functional contrast becomes sensitive to both spatial and temporal resonance frequency deviations, limiting its applicability. To overcome these shortcomings, we have proposed two new techniques. The first is an interleaved center frequency scan to compensate for spatial off-resonance. The second is real-time B0 shift tracking to compensate for temporal off-resonance. By applying these techniques, improved high-resolution transition-band SSFP fMRI results have been attained.; Another interesting aspect of the transition-band SSFP fMRI method is that functional contrast exists in both magnitude and phase. Hence, the conventional magnitude-based data analysis method no longer fully exploits the data. To incorporate the missing phase activation into the activation map, a novel complex data analysis method based on a T2-test combined with the generalized linear model (GLM) have been developed as a new data analysis approach for fMRI.; In addition to these new techniques, the signal characteristics of small-flip-angle balanced SSFP have been investigated to understand the spin dynamics. A new interleaf ordering method is proposed to reduce phase errors and image artifacts induced from different interleaves.