Pseudo multishot echo-planar imaging for geometric distortion improvement

NMR Biomed. 2023 May;36(5):e4885. doi: 10.1002/nbm.4885. Epub 2022 Dec 16.

Abstract

Conventional echo-planar imaging (EPI) uses a radiofrequency pulse for excitation and a prolonged echo train to sample k space, while off-resonance and T2 * decay effects caused by magnetic susceptibility variation accumulate within each echo, leading to geometric distortion. Multishot EPI methods, which divide k space into segments, can shorten the effective echo spacing and reduce the distortion on EPI images. But multiple shots cost longer scan time and render susceptibility to motion. In this study, we propose a new "multishot" EPI method termed pseudo multishot EPI (pmsEPI), in which phase-encoding lines are segmented as in multishot EPI but are collected within a single shot. With the magnetization divided into different pathways via interleaved excitation instead of refocusing in a single long echo train, the total phase error accumulation is reduced in each segmented acquisition, thereby improving distortion of the resultant EPI image. The performance of the pmsEPI method is demonstrated by phantom and in vivo brain experiments on a 3-T scanner. The experimental results show that the distortion displacements of pmsEPI acquisition compared with conventional EPI decrease by 50% with two pseudo shots and 66% with three pseudo shots, validating the ability of the method to obtain images with reduced distortion in a single shot, although magnetization splitting may induce more than 40% SNR loss and minor artifacts. Specifically, the ability of pmsEPI in diffusion-weighted imaging with different trajectory options is highlighted, and the flexibility is demonstrated in a single-shot blip up and down acquisition.

Keywords: EPI; distortion; multishot.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artifacts
  • Brain / diagnostic imaging
  • Diffusion Magnetic Resonance Imaging* / methods
  • Echo-Planar Imaging* / methods
  • Head
  • Image Processing, Computer-Assisted / methods
  • Motion