Schmidt Johannes F M, Wissmann Lukas, Manka Robert, Kozerke Sebastian
Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.
Magn Reson Med. 2014 Jul;72(1):68-79. doi: 10.1002/mrm.24894. Epub 2013 Jul 31.
In this study, an iterative k-t principal component analysis (PCA) algorithm with nonrigid frame-to-frame motion correction is proposed for dynamic contrast-enhanced three-dimensional perfusion imaging.
An iterative k-t PCA algorithm was implemented with regularization using training data corrected for frame-to-frame motion in the x-pc domain. Motion information was extracted using shape-constrained nonrigid image registration of the composite of training and k-t undersampled data. The approach was tested for 10-fold k-t undersampling using computer simulations and in vivo data sets corrupted by respiratory motion artifacts owing to free-breathing or interrupted breath-holds. Results were compared to breath-held reference data.
Motion-corrected k-t PCA image reconstruction resolved residual aliasing. Signal intensity curves extracted from the myocardium were close to those obtained from the breath-held reference. Upslopes were found to be more homogeneous in space when using the k-t PCA approach with motion correction.
Iterative k-t PCA with nonrigid motion correction permits correction of respiratory motion artifacts in three-dimensional first-pass myocardial perfusion imaging.
在本研究中，提出了一种具有非刚性帧间运动校正的迭代k-t主成分分析（PCA）算法，用于动态对比增强三维灌注成像。
使用在x-pc域中针对帧间运动校正的训练数据，通过正则化实现迭代k-t PCA算法。使用训练数据和k-t欠采样数据的合成图像的形状约束非刚性图像配准来提取运动信息。该方法通过计算机模拟对10倍k-t欠采样进行了测试，并应用于因自由呼吸或屏气中断而受呼吸运动伪影影响的体内数据集。将结果与屏气参考数据进行比较。
运动校正后的k-t PCA图像重建解决了残留的混叠问题。从心肌提取的信号强度曲线与屏气参考曲线接近。发现使用具有运动校正的k-t PCA方法时，上升斜率在空间上更均匀。
具有非刚性运动校正的迭代k-t PCA允许在三维首过心肌灌注成像中校正呼吸运动伪影。
