Rational approximation of golden angles: Accelerated reconstructions for radial MRI

Area of Science:

• Magnetic Resonance Imaging (MRI)
• Medical Physics
• Image Acquisition

Background:

• Golden ratio sampling offers flexible temporal resolution and k-space coverage in MRI.
• However, irrational angles in golden ratio sampling complicate point-spread function (PSF) precomputation and data processing.

Purpose of the Study:

• To develop a novel radial sampling scheme, rational approximation of golden angles (RAGA), combining golden ratio advantages with equidistant pattern simplicity.
• To overcome the processing complexities associated with irrational increments in golden ratio sampling.

Main Methods:

• Mathematical derivation of RAGA sampling theoretical properties.
• Numerical computation and comparison of sidelobe-to-peak ratios (SPR) against golden ratio sampling.
• Implementation in the BART toolbox and a radial gradient-echo sequence, with feasibility demonstrated in phantom and cardiac imaging.

Main Results:

• RAGA sampling closely approximates golden ratio sampling in terms of PSF and SPR.
• RAGA simplifies reconstruction by allowing consistent equidistant trajectories across frames with varying sampling masks.
• Encoded spoke angles as indices streamline data processing compared to golden ratio methods.

Conclusions:

• RAGA sampling successfully merges the benefits of golden ratio sampling with enhanced data processing simplicity.
• This method is a valuable advancement for dynamic and quantitative MRI, improving workflow efficiency.