Closed-loop control of k-space sampling via physiologic feedback for cine MRI.

Area of Science:

• Medical Imaging
• Cardiovascular MRI
• Image Reconstruction

Background:

• Segmented cine cardiac MRI achieves high resolution but suffers from suboptimal k-space sampling due to fixed trajectories.
• Predefined k-space segmentation limits the efficiency and uniformity of data acquisition.

Purpose of the Study:

• To develop and evaluate an autonomous, closed-loop control system for radial k-space sampling (ARKS) to enhance sampling uniformity in cardiac MRI.
• To optimize k-space sampling strategies for improved cardiac image quality.

Main Methods:

• Implemented a closed-loop system that autonomously selects radial k-space sampling trajectories during live segmented cine MRI.
• Assessed sampling uniformity and cardiac phase detection in vivo using ECG data from 10 normal subjects.
• Compared ARKS to random, uniformly distributed, and golden angle trajectories using k-space uniformity and point spread function (PSF) measurements.

Main Results:

• The autonomous trajectory improved k-space sampling uniformity by 15±7% and main lobe PSF signal intensity by 6±4% compared to golden angle sampling.
• The system prescribed radial view angles faster than the scan repetition time (TR), increasing mean uniformity by 10±11% and reducing variability by 44±12%.
• ARKS demonstrated superior k-space uniformity and reduced image ringing compared to predetermined golden angle sampling.

Conclusions:

• The closed-loop ARKS approach enables near-uniform radial sampling in segmented acquisitions, outperforming predetermined golden-angle sampling.
• This method can increase sampling efficiency or decrease the temporal footprint of cardiac MRI acquisitions.
• The closed-loop framework shows potential for application in patients with complex heart rhythms.