Convex Gradient Optimization for the Free Running Framework

Motivation: Designing optimal gradient waveforms is a convex problem. They must satisfy gradient hardware constraints, physiological constraints, and being time-optimal. Goal(s): By shortening TE, we are more robust to motion artifact and less vulnerable to field inhomogeneities. By shortening TR and consequently TA, we can potentially minimize banding artifacts and obtain shorter scan time, increasing motion artifact robustness. Approach: The gradient optimized method “GrOpt” was integrated directly into free-running 3D-radial-bSSFP and GRE acquisitions at 3TResults: We achieved 14.0 %, 5.7% and 5.4% reduction in TE, TR and TA for bSSFP and 25.1%, 6.6% and 6.5% reduction in TE, TR and TA for GRE, . Impact: In 3D-radial-bSSFP, CVX achieves 14.0%, 5.7% and 5.4% reduction in TE, TR and TA, respectively. In 3D-radial-GRE, 25.1%, 6.6% and 6.5% reduction in TE, TR and TA was obtained, reducing the effect of inhomogeneities, motions, eddy current and scan time.