Iterative k-t Principal Component Analysis with Nonrigid Motion Correction for Dynamic Three-Dimensional Cardiac Perfusion Imaging

作者：Schmidt Johannes F M; Wissmann Lukas; Manka Robert; Kozerke Sebastian^*

来源：Magnetic Resonance in Medicine, 2014, 72(1): 68-79.

DOI：10.1002/mrm.24894

• cardiac perfusion
• motion correction
• respiratory motion
• nonrigid motion correction

Purpose: 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.
Methods: 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. Results: 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.
Conclusions: Iterative k-t PCA with nonrigid motion correction permits correction of respiratory motion artifacts in three-dimensional first-pass myocardial perfusion imaging.

• 出版日期2014-7