title: Parametric analysis of the spatial resolution and signal-to-noise ratio in super-resolved spatiotemporally encoded (SPEN) MRI.
abstract: OBJECTIVE
  Spatiotemporally Encoded (SPEN) MRI is based on progressive point-by-point refocusing of the image in the spatial rather than the k-space domain through the use of frequency-swept radiofrequency pulses and quadratic phase profiles. This technique provides high robustness against frequency-offsets including B0 inhomogeneities and chemical-shift (e.g., fat/water) distortions, and can consequently perform fMRI at challenging regions such as the orbitofrontal cortex and the olfactory bulb, as well as to improve imaging near metallic implants. This work aims to establish a comprehensive framework for the implementation and super-resolved reconstruction of SPEN-based imaging, and to accurately quantify this method's spatial-resolution and signal-to-noise ratio (SNR).
  
  
  METHODS
  A stepwise formalism was laid-out for calculating the optimal experimental parameters for SPEN, followed by analytical analysis of the ensuing SNR and spatial-resolution versus conventional k-space encoding. Predictions were then confirmed using computer simulations and experimentally.
  
  
  RESULTS
  Our findings show that SPEN is governed by the same fundamental signal-processing principles as k-space encoding, leading to similar averaging properties, and ultimately similar spatial-resolution and SNR levels as k-space encoding.
  
  
  CONCLUSIONS
  Presented analysis is applicable to general multidimensional SPEN designs and provides a unified framework for the analysis of future SPEN and similar approaches based on quadratic phase encoding.
authors.affiliation: The Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York, University School of Medicine, New York, New York, USA.
authors.forename: Noam
authors.initials: N
authors.lastname: Ben-Eliezer
authors.forename: Yoav
authors.initials: Y
authors.lastname: Shrot
authors.forename: Lucio
authors.initials: L
authors.lastname: Frydman
authors.forename: Daniel K
authors.initials: DK
authors.lastname: Sodickson
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D062211:Spatio-Temporal Analysis
keywords: Frequency-swept pulses; non-Fourier methods; signal-to-noise ratio; spatiotemporal encoding; super-resolution