K-space energy spectrum analysis for echo-planar imaging R21-EB005690
The goal of this collaboration between the NCIGT and Duke University is 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 inhomogenieties 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 re-analyze 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.
In the past year, researchers applied KESA to improve the scan efficiency of 3D EPI. The phantom and human data illustrate that, using KESA, the susceptibility signal loss in 3D T2*-weighted EPI can be effectively compensated. Compared with previously reported 3D compensation approaches, such as 3D z-shim, the anatomic resolvability is improved in KESA based susceptibiity compensation. Researchers have further developed KESA to correct artifacts in spiral imaging. Using the spiral-version KESA the susceptibility field gradients can be calculated from the spiral-fMRI data without the need for extra field mapping scan. The derived information can then be applied to remove the blurring artifact in spiral imaging. Also, researchers integrated KESA with SSFP imaging, enabling banding-artifact-free SSFP imaging. The SSFP k-space data can be decomposed, guided by KESA, to enable multi-scheme image reconstruction to eliminate destructive interferences among signals from different coherent pathways.
More about this collaboration appears under 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.