title: Sparsity transform k-t principal component analysis for accelerating cine three-dimensional flow measurements.
abstract: Time-resolved three-dimensional flow measurements are limited by long acquisition times. Among the various acceleration techniques available, k-t methods have shown potential as they permit significant scan time reduction even with a single receive coil by exploiting spatiotemporal correlations. In this work, an extension of k-t principal component analysis is proposed utilizing signal differences between the velocity encodings of three-directional flow measurements to further compact the signal representation and hence improve reconstruction accuracy. The effect of sparsity transform in k-t principal component analysis is demonstrated using simulated and measured data of the carotid bifurcation. Deploying sparsity transform for 8-fold undersampled simulated data, velocity root-mean-square errors were found to decrease by 52 ± 14%, 59 ± 11%, and 16 ± 32% in the common, external, and internal carotid artery, respectively. In vivo, errors were reduced by 15 ± 17% in the common carotid artery with sparsity transform. Based on these findings, spatial resolution of three-dimensional flow measurements was increased to 0.8 mm isotropic resolution with prospective 8-fold undersampling and sparsity transform k-t principal component analysis reconstruction. Volumetric data were acquired in 6 min. Pathline visualization revealed details of helical flow patterns partially hidden at lower spatial resolution.
authors.affiliation: Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.
authors.forename: Verena
authors.initials: V
authors.lastname: Knobloch
authors.forename: Peter
authors.initials: P
authors.lastname: Boesiger
authors.forename: Sebastian
authors.initials: S
authors.lastname: Kozerke
mesh_terms: D000328:Adult; D000465:Algorithms; D001783:Blood Flow Velocity / Q000502:physiology; D003326:Coronary Circulation / Q000502:physiology*; D003627:Data Interpretation, Statistical; D005260:Female; D064368:Healthy Volunteers; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D008297:Male; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D012212:Rheology / Q000379:methods*; D012680:Sensitivity and Specificity; D055815:Young Adult