Improving contrast to noise ratio of resonance frequency contrast images (phase images) using balanced steady-state free precession.
Recent MRI studies have exploited subtle magnetic susceptibility differences between brain tissues to improve anatomical contrast and resolution. These susceptibility differences lead to resonance frequency shifts which can be visualized by reconstructing the signal phase in conventional gradient echo (GRE) acquisition techniques. In this work, a method is proposed to improve the contrast to noise ratio per unit time (CNR efficiency) of anatomical MRI based on resonance frequency contrast. The method, based on the balanced steady-state free precession (bSSFP) MRI acquisition technique, was evaluated in its ability to generate contrast between gray and white matter in human brain at 3T and 7T. The results show substantially improved CNR efficiency of bSSFP phase images (2.85±0.21 times at 3 T and 1.71±0.11 times at 7 T) compared to the GRE data in a limited spatial area. This limited spatial coverage is attributed to the sensitivity of bSSFP to macroscopic B(0) inhomogeneities. With this CNR improvement, high resolution bSSFP phase images (resolution=0.3×0.3×2 mm(3), acquisition time=10min) acquired at 3T had sufficient CNR to allow the visualization of cortical laminar structures in invivo human primary visual cortex. Practical application of the proposed method may require improvement of B(0) homogeneity and stability by additional preparatory scans and/or compensation schemes such as respiration and drift compensation. Without these additions, the CNR benefits of the method may be limited to studies at low field or limited regions of interest.
Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892-1065, USA. jonghoyi@mail.nih.gov
Jongho
J
Lee
Masaki
M
Fukunaga
Jeff H
JH
Duyn
D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*