实时运动校正与相位补偿结合，提升3D EPI功能成像稳定性
Servo navigation and phase equalization enhanced by run-time stabilization (PEERS) for 3D EPI time series
- 通过短轨道导航与线性扰动模型实现实时运动与相位波动校正
- 相比传统方法，信噪比提升最高达30%，静止状态仍提升10%
- 自动无须人工干预，适合对运动敏感的3D fMRI研究
目的：通过实时稳定与数据驱动的回顾性相位校正协同，提升时间分辨的分段3D EPI成像质量。方法：在分段3D EPI序列中引入基于短轨道导航和线性扰动模型的伺服导航，实现刚体运动及整体相位/频率波动的实时校正；同时利用时间序列重复结构进行回顾性相位校正，消除残余相位与频率偏移。该联合方法称为相位等化增强的实时稳定（PEERS）。结果：在体模与活体上验证，伺服导航有效降低原始数据中的运动干扰，维持时间序列间k空间一致性；回顾性相位等化显著消除相对于导航信号的逐帧相位与频率偏移，归因于涡流与编码振动。该方法降低对实时频率控制精度要求，支持使用短导航。相比传统体积重对齐，当运动较小时，信噪比提升最高达30%；在受试者刻意保持静止时，仍可提升约10%。回顾性相位等化明显优于仅依赖导航估计的相位校正。结论：伺服导航实现3D EPI fMRI高精度实时运动校正，短导航粗频率跟踪由精确的回顾性频率与相位校正补充。全自动化、自校准的PEERS为3D fMRI提供高效即插即用的运动与相位校正方案。
原文摘要 · Abstract (English)
Purpose: To enhance time-resolved segmented imaging by synergy of run-time stabilization and retrospective, data-driven phase correction. Methods: A segmented 3D EPI sequence for fMRI time series is equipped with servo navigation based on short orbital navigators and a linear perturbation model, enabling run-time correction for rigid-body motion as well as bulk phase and frequency fluctuation. Complementary retrospective phase correction is based on the repetitive structure of the time series and serves to address residual phase and frequency offsets. The combined approach is termed phase equalization enhanced by run-time stabilization (PEERS). Results: The proposed strategy is evaluated in a phantom and in-vivo. Servo navigation is found to diminish motion confound in raw data and maintain k-space consistency over time series. In turn, retrospective phase equalization is found to eliminate shot-wise phase and frequency offsets relative to the navigator, which are attributed to eddy-currents and vibrations from phase encoding. Retrospective phase equalization reduces the precision requirements for run-time frequency control, supporting the use of short navigators. Relative to conventional volume realignment, PEERS achieved tSNR improvements up to $30\%$ for small motion and in the order of $10\%$ when volunteers tried to hold still. Retrospective phase equalization is found to clearly outperform phase correction based solely on navigator-based frequency estimates. Conclusion: Servo navigation achieves high-precision run-time motion correction for 3D EPI fMRI. Coarse frequency tracking based on short navigators is supplemented by precise retrospective frequency and phase correction. Fully automatic and self-calibrated, PEERS offers effective plug-and-play motion and phase correction for 3D fMRI.
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