title: Improved SNR in linear reordered 2D bSSFP imaging using variable flip angles.
abstract: This article presents a variable flip-angle approach for balanced steady-state free precession (bSSFP) imaging, which allows increases in signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) while keeping specific absorption rate (SAR) constant or reduces SAR for given CNR and SNR. The gain in SNR is achieved by utilizing the higher signal in the transient phase. Flip-angle variation during the echo train is realized using a trigonometric function with M steps (ramp length). Variation is combined with a linear k-space reordering such that outer parts of k-space are sampled using a lower flip angle alpha(min), while the central part of k-space is acquired with a higher flip angle alpha(max). No additional preparation or dummy cycles are applied prior to data acquisition. Several variation schemes with different starting flip angles alpha(min) and ramp length M are considered. For example, using alpha(min)=1 degrees and M=96, alpha(max) can be set to 47 degrees without exceeding SAR limits at 3 T and gaining up to 50% in SNR, while, conventionally, alpha=34 degrees is the maximal possible flip angle. Resolution seems unaffected in volunteer imaging. In all cases, no transient artifacts due to flip-angle variation were observed. This article demonstrates the use of flip-angle variations in bSSFP to increase SNR and CNR while keeping SAR constant, which is especially important at higher field strengths. Flip-angle variation can also be combined with other methods such as parallel imaging techniques for further SAR reduction.
authors.affiliation: Department of Diagnostic Radiology, Medical Physics, University Hospital Freiburg, Freiburg, Germany. dominik.paul@uniklinik-freiburg.de
authors.forename: Dominik
authors.initials: D
authors.lastname: Paul
authors.forename: Maxim
authors.initials: M
authors.lastname: Zaitsev
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016014:Linear Models; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008954:Models, Biological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity