Image distortion correction for MRI in low field permanent magnet systems with strong B-0 inhomogeneity and gradient field nonlinearities

Koolstra, K.; O'Reilly, T.; Bornert, P.; Webb, A.

doi:doi:10.1007/s10334-021-00907-2

Objective To correct for image distortions produced by standard Fourier reconstruction techniques on low field permanent magnet MRI systems with strong B-0 inhomogeneity and gradient field nonlinearities. Materials and methods Conventional image distortion correction algorithms require accurate Delta B-0 maps which are not possible to acquire directly when the B-0 inhomogeneities also produce significant image distortions. Here we use a readout gradient time-shift in a TSE sequence to encode the B-0 field inhomogeneities in the k-space signals. Using a non-shifted and a shifted acquisition as input, Delta B-0 maps and images were reconstructed in an iterative manner. In each iteration, Delta B-0 maps were reconstructed from the phase difference using Tikhonov regularization, while images were reconstructed using either conjugate phase reconstruction (CPR) or model-based (MB) image reconstruction, taking the reconstructed field map into account. MB reconstructions were, furthermore,...Show moreObjective To correct for image distortions produced by standard Fourier reconstruction techniques on low field permanent magnet MRI systems with strong B-0 inhomogeneity and gradient field nonlinearities. Materials and methods Conventional image distortion correction algorithms require accurate Delta B-0 maps which are not possible to acquire directly when the B-0 inhomogeneities also produce significant image distortions. Here we use a readout gradient time-shift in a TSE sequence to encode the B-0 field inhomogeneities in the k-space signals. Using a non-shifted and a shifted acquisition as input, Delta B-0 maps and images were reconstructed in an iterative manner. In each iteration, Delta B-0 maps were reconstructed from the phase difference using Tikhonov regularization, while images were reconstructed using either conjugate phase reconstruction (CPR) or model-based (MB) image reconstruction, taking the reconstructed field map into account. MB reconstructions were, furthermore, combined with compressed sensing (CS) to show the flexibility of this approach towards undersampling. These methods were compared to the standard fast Fourier transform (FFT) image reconstruction approach in simulations and measurements. Distortions due to gradient nonlinearities were corrected in CPR and MB using simulated gradient maps. Results Simulation results show that for moderate field inhomogeneities and gradient nonlinearities, Delta B-0 maps and images reconstructed using iterative CPR result in comparable quality to that for iterative MB reconstructions. However, for stronger inhomogeneities, iterative MB reconstruction outperforms iterative CPR in terms of signal intensity correction. Combining MB with CS, similar image and Delta B-0 map quality can be obtained without a scan time penalty. These findings were confirmed by experimental results. Discussion In case of B-0 inhomogeneities in the order of kHz, iterative MB reconstructions can help to improve both image quality and Delta B-0 map estimation.Show less

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Image distortion correction for MRI in low field permanent magnet systems with strong B-0 inhomogeneity and gradient field nonlinearities