K-Space Energy Spectrum Analysis for Echo-Planar Imaging
The work of this project is a collaboration designed to improve the quality and spatial accuracy of echo-planar imaging (EPI) to derive accurate quantitative information from EPI-based medical research and clinical diagnostic information.
One of the fastest MR imaging techniques, EPI has been popularly applied to various dynamic studies that require high temporal-resolution, such as functional MRI (fMRI), contrast-enhanced imaging, and MR-based interventional procedures. EPI data quality is usually degraded by various artifacts, such as geometric distortions and susceptibility signal loss, however. Furthermore, the sensitivity of EPI to susceptibility field inhomogeneities renders it less than reliable in EPI-based longitudinal studies. To improve EPI, several studies have focused on quality improvement and artifact reduction, yet they reported EPI artifact reduction methods that required time-consuming field mapping scans, and, therefore, were not practical for clinical scans and EPI-based interventional MRI procedures.
To improve EPI in a way that doesn't require a field mapping procedure or pulse sequence modification, NCIGT researchers are using a novel k-space energy spectrum analysis to quantify k-space energy distribution, susceptibility field gradients, spatially-dependent echo time values and artifact levels directly from acquired EPI data. Using this approach, various EPI artifacts (e.g. distortions and Gibb's ripple artifact) can be effectively removed. Furthermore, the developed k-space energy spectrum analysis will be applied to design an optimal acquisition strategy for phase-encoded 3D parallel EPI with an improved signal-to-noise ratio and reduced motion related artifact. The team also plans to apply the proposed methods to reanalyze the previously acquired fMRI data and retrospectively improve the longitudinal reproducibility of grouped activation. Results of this collaborative work will be made available to the MRI community to benefit other research groups in their EPI-based quantitative studies or retrospective use of EPI data.
Use of K-space Energy Spectrum Analysis To Improve MRI-Based Temperature Mapping
The k-space energy spectrum analysis algorithm is also the basis for a new phase mapping and unwrapping method that eliminates susceptibility-induced phase wraparounds to improve MR's ability to measure temperature-induced phase changes in critical regions. MR measures temperature changes using T2-weighted MR imaging phase values. MRI phase values also contain information such as the susceptibility field gradients near air-tissue interfaces. Using the new method, post-processing steps following MRI having to do with susceptibility field gradients will not be an issue. Such a development is particularly helpful in instances in which subjects move during MRI's dynamic imaging time points, a situation that has made the post-processing elimination of susceptibility-induced phase wraparounds very challenging in the past.
Back to Research Projects.
- Chen N, Oshio K, Panych L. Improved image reconstruction for partial Fourier gradient-echo echo-planar imaging (EPI). Magn Reson Med. 2008 Apr;59(4):916-24. PMID: 18383294.
- Chen N, Oshio K, Panych L. Application of k-space energy spectrum analysis to susceptibility field mapping and distortion correction in gradient-echo EPI. Neuroimage. 2006 Jun;31(2):609-22. PMID: 16480898.