Room: AAPM ePoster Library
Purpose: To create a temporally-robust MRI reconstruction method using Principal Component Analysis (PCA) suitable for real-time imaging and tumour contouring using a Linac-MR.
Methods: This project builds on past work in which PCA was used to reconstruct undersampled MRI dynamic frames based on a series of ~30 fully-sampled frames at the beginning of the session. While this technique was capable of reconstructing undersampled data, it was found that the reconstruction artifacts increase over time, as the principal components (PCs) were calculated based on the initial fully-sampled data. The work presented here introduces a method by which PCs can be calculated and updated based on a moving database of core k-space data. This core k-space data simply refers to central k-space (low-frequency) data that is acquired every frame (and never undersampled). The higher-frequency data is undersampled with a pseudo random distribution of phase encodes in each frame. The frames cycle through four different complementary random distributions to ensure every phase encode is sampled once every four frames. After each undersampled frame is acquired, the core data from the most-recent 60 frames is used to create a series of PCs that represent the time-dependent modulation of k-space. The most relevant PCs are then projected onto the sparsely-populated high-frequency data to fill in unsampled phase encodes for the most-recent frame by extrapolation.
Results: By calculating the artifact level in retrospectively undersampled lung images, the new reconstruction method results in images that better maintain their fidelity over time (2-4x smaller mean artifact level after 2 minutes), an improvement over the previous method. However, there are occasional spikes of high artifact which we are currently working on overcoming.
Conclusion: This method of MRI reconstruction appears to be robust over time, but further investigation will be needed to assess the cause of intermittent artifact spikes.
Funding Support, Disclosures, and Conflict of Interest: B.G.F is co-founder and chair of MagneTx Oncology Solutions