Compressed sensing velocity encoded phase contrast imaging: Monitoring skeletal muscle kinematics. Issue 1 (11th December 2019)

• Record Type: Journal Article
• Authors: Malis, Vadim; Sinha, Usha; Sinha, Shantanu
• Is Part Of: Magnetic resonance in medicine. Volume 84:Issue 1(2020)
• Page Start: 142
• Page End: 156
• Publication Date: 2019-12-11
• Subjects: compressed sensing -- multicoil temporal compressed sensing reconstruction -- muscle strain rate tensor -- muscle velocity -- velocity encoded MRI; Nuclear magnetic resonance -- Periodicals; Electron paramagnetic resonance -- Periodicals; 616.07548
• DOI: 10.1002/mrm.28100
• Languages: English
• ISSNs: 0740-3194

Abstract

Abstract : Purpose: This study implements a compressed sensing (CS) 3‐directional velocity encoded phase contrast (VE‐PC) imaging for studying skeletal muscle kinematics within 40 s. Methods: Independent variable density random sampling in the phase encoding direction for each temporal frame was implemented for various combinations of CS‐ factors and views per segment. CS reconstruction was performed for the combined multicoil, temporal datasets using temporal Fourier transform followed by temporal principal component analysis sparsifying transformations. The method was tested on a flow phantom and in vivo, on velocity and strain rate of the medial gastrocnemius muscle of 11 subjects performing isometric contractions. Results: For the flow phantom, velocity from 8 undersampled sequences matched very well with the flowmeter values over a range of velocities spanning in vivo muscle velocities. Bland‐Altman plots of the peak strain rate eigenvalues comparing 7 undersampled sequences was in good agreement with the reference (full k‐space) scan. CS‐ factor of 4 combined with views per segment of 4 (scan times reduced by 4) yielded images with no visual artifacts allowing and yielded velocities and strain rate maps in the lower leg muscle in 40 s. Conclusion: This study shows that a reduction in scan time of velocity encoded phase contrast imaging up to a factor of 4 is possible using the proposed CS reconstruction.