Compartment-based k-t principal component analysis enabled a net acceleration factor of 8 while keeping stroke volume error below 5%, permitting aortic flow imaging in a single breathhold.
The proposed compartment-based k-t PCA method allows for highly accelerated phase-contrast MRI flow measurements with minimal error in stroke volume, enabling rapid assessment of aortic flow.
The applicability of cine blood flow measurements in a clinical setting is often compromised by the long scan times associated with phase-contrast imaging. In this work, we propose an extension to the k-t principal component analysis method and demonstrate that by definition of spatial compartment-dependent temporal basis functions, significant improvements in reconstruction accuracy can be achieved relative to the original k-t principal component analysis and k-t SENSE formulations. Using this method, it is shown that prospective nominal undersampling of up to 16 corresponding to a net acceleration factor of 8 including training data acquisition can be realized while keeping the error in stroke volume below 5%. As a practical application, the acquisition of cine flow data in the aorta is demonstrated permitting assessment of two-dimensional velocity images and pulse wave velocities at 100 frames per second in a single breathhold per slice.
Giese et al. (Mon,) conducted a other in Cine blood flow measurements. Compartment-based k-t principal component analysis vs. Original k-t principal component analysis and k-t SENSE formulations was evaluated on Reconstruction accuracy and error in stroke volume. Compartment-based k-t principal component analysis enabled a net acceleration factor of 8 while keeping stroke volume error below 5%, permitting aortic flow imaging in a single breathhold.