PURPOSE: 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). THEORY AND 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. CONCLUSION: 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.
PURPOSE: 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). THEORY AND 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. CONCLUSION: 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: Jason P Stockmann; Clarissa Z Cooley; Bastien Guerin; Matthew S Rosen; Lawrence L Wald Journal: J Magn Reson Date: 2016-04-08 Impact factor: 2.229