Spiral fMRI

This project presents a spiral-based functional Magnetic Resonance Imaging (fMRI) sequence. It allows dynamic T2* weighed contrast with a high temporal resolution and shorter total acquisition time [1].

This Pulseq [2][3] version is a "translation" of the original one based in TOPPE [4] and it demonstrates the feasibility of porting sequences between these two open-source and vendor-independent frameworks. It has also been implemented in a cross-vendor manner.

Check the Wiki for more information.

Dependencies

1. PyPulseq>=1.2.1
2. numpy>=1.16.3
3. matplotlib>=3.0.3

Quick Demo

Please note: You need to install Pulseq interpreter on your system before running any Pulseq sequence. Visit their GitHub page and specifications document for more information.

1. Create the environment:

   After cloning the respository, create a virtual environment, activate it and install the specified dependencies.

   # Windows
   py -m pip install --user virtualenv # install vitual environment package
   py -m venv <virtual_environment_name> # create a virtual environment in the project directory
   .\<virtual_environment_name>\Scripts\activate # activate it
   pip install -r requirements.txt # install the required packages
   
   # Mac/Linux
   python3 -m pip install --user virtualenv 
   python3 -m venv <virtual_environment_name> 
   source <virtual_environment_name>/bin/activate 
   pip install -r requirements.txt 
   

   Go to PyPulseq's GitHub page to learn more about this tool for pulse sequence design.

2. Open getparams.py and check the acquisition parameters

   Note that the sequence implementation has been valited with the default parameters. A different combination of values would affect the resulting images.

   Change the system limits if you need to. We have tested our implementation with these limits:

   # system limits
   gamma = 42576000 # Hz/T
   sysSiemens = {'gamma': gamma, 'max_grad': 32, 'grad_unit': 'mT/m', 'max_slew': 130, 'slew_unit': 'T/m/s',
                'grad_raster_time': 10e-6, 'rf_raster_time': 1e-6}

   For example, gradient and slew rate limits are not the same for GE and Siemens.

   

3. Run spiral_fmri_pypulseq.py. It will give you the .seq file that will be played on the scanner.

   seq.write("spiral_PRESTO.seq")

4. Go to the MR room and play it!

Contributing and Community guidelines

This repository adheres to a code of conduct adapted from the Contributor Covenant code of conduct. Contributing guidelines can be found here

References

1. van Gelderen, P., Duyn, J. H., Ramsey, N. F., Liu, G., & Moonen, C. T. (2012). The PRESTO technique for fMRI. NeuroImage, 62(2), 676–681. doi:10.1016/j.neuroimage.2012.01.017

2. Ravi, K. S., Potdar, S., Poojar, P., Reddy, A. K., Kroboth, S., Nielsen, J. F., Zaitsev, M., Venkatesan, R., Geethanath, S. (2018). Pulseq-Graphical Programming Interface: Open source visual environment for prototyping pulse sequences and integrated magnetic resonance imaging algorithm development. Magnetic Resonance Imaging, 52, 9-15. doi:10.1016/j.mri.2018.03.008.

3. Layton, K. J., Kroboth, S., Jia, F., Littin, S., Yu, H., Leupold, J., Nielsen, J., Stöcker, T. and Zaitsev, M. (2017), Pulseq: A rapid and hardware‐independent pulse sequence prototyping framework. Magn. Reson. Med., 77: 1544-1552. doi:10.1002/mrm.26235

4. Nielsen, J. F., & Noll, D. C. (2018). TOPPE: A framework for rapid prototyping of MR pulse sequences. Magnetic resonance in medicine, 79(6), 3128–3134. doi:10.1002/mrm.26990