Navigator-based correction pipelines

Standard navigator processing that has been developed for brain imaging is not sufficiently robust in the spinal cord due to the following:

• Higher in-plane variability in the field distribution
• Signal-to-noise ratio (SNR) is lower
• Larger variations in signal contribution from different receiver coils compared to most anatomical regions

To face these challenges, we developed:

• SNR weighted averaging of the navigator profile
• mean phase removal to recenter the phase distribution and reduce wrapping
• A fast Fourier transform (FFT) and spatial region selection step. This consists of applying a one-dimensional Fourier transform to each navigator profile and considering for the phase estimate only the data points in a certain spatial interval centered on the spinal cord.
• Phase unwrapping function for the navigator estimates using the respiratory trace recording.

These features are combined in multiple pipelines as shown in the figure.

The available pipelines are:

• k_nav is the k-space navigator processing commonly used for brain imaging, optimized with SNR weighted averaging and mean phase removal.
• FFT_nav that includes an additional FFT and spatial region selection step compared to k_nav.
• unwrap includes the phase unwrapping algorithm and makes use of the respiratory belt recordings.

MRINavigator is designed to be flexible and multiple analysis parameters are tuneable. It is possible to select the correction pipeline and parameters using the params dictionary. For more information check the Get started or API pages. Alternatively start julia from the command line, and type ? to enter the help REPL mode. Then enter

help?> defaultNavParams

Listed below are the main features and parameters the user can select and modify:

• The Spinal cord toolbox (SCT) can be used to locate the spinal cord centerline position (params[:comp_centerline] = true). To do this the reference data, which are fully sampled, are reconstructed combining the coils, and saved in NIfTI format (params[:reconstruct_map] = true). The user can also manually locate the centerline if the automatic algorithm fails, selecting params[:trust_SCT] = false. Alternatively, the center of the image will be used (params[:use_centerline] = false).
• The interval width for the region selection after the FFT step can be adjusted (params[:FFT_interval] = type number in millimeters).
• The unwrap function can be applied both to the FFT and the k nav pipelines. To do this type params[:corr_type] = "FFT_unwrap" or params[:corr_type] = "knav_unwrap".