title: Referenceless phase velocity mapping using balanced SSFP.
abstract: Phase contrast MRI (PC-MRI) is an established technique for measuring blood flow velocities in vivo. Although spoiled gradient recalled echo (GRE) PC-MRI is the most widely used pulse sequence today, balanced steady state free precession (SSFP) PC-MRI has been shown to produce accurate velocity estimates with superior SNR efficiency. We propose a referenceless approach to flow imaging that exploits the intrinsic refocusing property of balanced SSFP, and achieves up to a 50% reduction in total scan time. With the echo time set to exactly one half of the sequence repetition time (TE = TR/2), we show that non-flow-related image phase tends to vary smoothly across the field-of-view, and can be estimated from static tissue regions to produce a phase reference for nearby voxels containing flowing blood. This approach produces accurate in vivo one-dimensional velocity estimates in half the scan time compared with conventional balanced SSFP phase-contrast methods. We also demonstrate the feasibility of referenceless time-resolved 3D flow imaging (called "7D" flow) in the carotid bifurcation from just three acquisitions.
authors.affiliation: Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, California, USA. jfnielse@umich.edu
authors.forename: Jon-Fredrik
authors.initials: JF
authors.lastname: Nielsen
authors.forename: Krishna S
authors.initials: KS
authors.lastname: Nayak
mesh_terms: D000465:Algorithms; D001783:Blood Flow Velocity / Q000502:physiology*; D002339:Carotid Arteries / Q000502:physiology*; D002560:Cerebrovascular Circulation / Q000502:physiology*; D005240:Feasibility Studies; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012212:Rheology / Q000379:methods*; D012680:Sensitivity and Specificity