Flexible kt-GRAPPA-initiated compressed sensing reconstruction approach for accelerated dual-venc 5D flow imaging

Motivation: Dual-venc 5D flow has been proposed to capture an increased dynamic range of hemodynamics over both the cardiac and respiratory cycles. However, scan time is prohibitively long. Goal(s): We propose a novel reconstruction method for accelerated dual-venc 5D flow that uses kt-GRAPPA-initiated compressed sensing to enable nearly 50% reduction in scan time. Approach: We retrospectively simulated dual-venc 5D flow acceleration in N=8 healthy volunteers. Kt-GRAPPA kernels were trained on reference data and applied to fill undersampled velocity encodes before input to compressed sensing. Results: Kt-GRAPPA-initiated compressed sensing had <10% error in flow measurements with double the acceleration compared to standard dual-venc 5D flow. Impact: The proposed reconstruction method enables accelerated dual-venc 5D flow with approximately 50% reduction in scan time, increasing feasibility for a clinical setting. Potential applications include detailed analysis of cardiovascular hemodynamics over the respiratory cycle in patients with congenital heart disease.