QSMxT-Brainlife

This is the Brainlife App implementation of QSMxT - an end-to-end software toolbox for Quantitative Susceptibility Mapping (QSM) that automatically reconstructs and processes large datasets in parallel using sensible defaults. See the QSMxT Brainlife App page here.

What is QSM?

QSM is a form of quantitative MRI that aims to measure the magnetic susceptibility of objects. Susceptibility maps are derived by post-processing the phase component of the complex MRI signal, usually from a 3D gradient-echo (3D-GRE) acquisition. QSM has many applications, mostly in human brain imaging of conditions such as traumatic brain injuries, neuroinflammatory and neurodegenerative diseases, ageing, tumours, with emerging applications across the human body and in animals.

Inputs

The QSMxT Brainlife App takes a magphase datatype as input, which includes both the magnitude and phase components of an MRI acquisition as NIfTI files, and associated JSON sidecars.

Outputs

The QSMxT Brainlife App produces a qsm datatype as output in NIfTI format, with voxel values measured in parts-per-million (ppm).

Authors

The QSMxT Brainlife App was developed by Ashley Stewart, with a wider group contributing to the underlying QSMxT toolbox and original publication.

Copyright (c) 2022 brainlife.io The University of Texas at Austin

Funding Acknowledgement

brainlife.io is publicly funded by the following:

Citations

1. Stewart, A. W., Robinson, S. D., O’Brien, K., Jin, J., Widhalm, G., Hangel, G., ... & Bollmann, S. (2022). QSMxT: Robust masking and artifact reduction for quantitative susceptibility mapping. Magnetic resonance in medicine, 87(3), 1289-1300. https://doi.org/10.1002/mrm.29048
2. Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y

Running the App

On Brainlife.io

You can find QSMxT at brainlife.io and execute it via the "Execute" tab.

Running Locally (on your machine)

1. git clone this repo.
2. Inside the cloned directory, create config.json with something like the following content with paths to your input files. For multi-echo data, you may use multiple elements in the mag, phase, mag-json, and phase-json lists:

{
    "mag": ["/home/ashley/repos/qsmxt-brainlife/bids/sub-1/anat/sub-1_echo-1_part-mag_MEGRE.nii"],
    "phase": ["/home/ashley/repos/qsmxt-brainlife/bids/sub-1/anat/sub-1_echo-1_part-phase_MEGRE.nii"],
    "mag-json": ["/home/ashley/repos/qsmxt-brainlife/bids/sub-1/anat/sub-1_echo-1_part-mag_MEGRE.json"],
    "phase-json": ["/home/ashley/repos/qsmxt-brainlife/bids/sub-1/anat/sub-1_echo-1_part-phase_MEGRE.json"],
    "cli-params": "",
    "premade": "fast"
}

3. Launch the App by executing main

./main

Sample Datasets

If you don't have your own input files, you can generate them using the qsm-forward package, which conveniently exists in Brainlife App form via the QSM Data Generator Brainlife App.

Output

All output files will be generated inside the current working directory (pwd), inside a specifc directory called out_dir.

Dependencies

This App requires curl, singularity, and the md5sum command to run.