This repository contains materials and tools to support the implementation and use of the "Free Waveform" (FWF) MRI pulse sequence. The sequence is a diffusion-weighted spin-echo that facilitates the execution of user-defined gradient waveforms for the purposes of tensor-valued diffusion encoding and other methods that require arbitrary modulation of the gradients.
Siemens
The sequence is shared via Siemens Teamplay by Filip Szczepankiewicz.
Check the list of compiled variants to see if the sequence is available for your system.
For other questions, please contact me at [email protected].
Philips
Please contact Maarten Versluis at Philips Healthcare ([email protected]).
United Imaging
Please contact Weiguo Zhang at United Imaging ([email protected]).
Bruker
An implementation for TopSpin, by Daniel Topgaard at Lund University, is available here.
An implementation for ParaVision, by Mathew Budde at Medical College of Wisconsin, is available here.
Siemens
Instructions for sequence installation and setup are found here.
Philips, GE and United Imaging
Instructions for installation and setup are provided by the vendor.
Designing the experiment [Review paper]
The design of the gradient waveforms (b-tensor shapes) and the signal sampling schemes (b-values, rotations etc.) must be considered when setting up he experiment. A comprehensive review of the factors that need be considered is found here. In general, the design is informed by the hardware, the intended analysis technique and the organ/subject characteristics. Below, we have collected tools and examples related to the experimental design.
Waveform design
A framework for numerical gradient waveform optimization was published by Sjölund et al. and is available on GitHub. This framework also includes concomitant gradient compensation, motion encoding compensation, as well as cross-term compensation.
Example sampling schemes
Examples of sampling schemes appropriate for a given combination of organ and analysis technique are found in the SamplingSchemes folder.
Postprocessing can be done using regular tools developed by the diffusion MRI community. Special care is however needed for correction of distortions due to eddy currents and subject movement to avoid artefacts (see Nilsson et al., 2015).
This can be done with e.g. the mddMRI framework and eddy tool from FSL although special conditions apply (see this note).
We have published an extensive framework in open source for the analysis of data encoded by b-tensors and more. Please refer to these instructions for the setup of analysis pipelines, and the interpretation of model parameters.
Example of analysis pipeline