mri2mrs repository is developed by Tashrif Billah and Isaiah Norton.

Table of Contents

• Combination of MRI and MRS
• Project flowchart
• Citation
• Installation
  • 1. Dependencies
  • 2. Setup environment
  • 3. MATLAB
  • 4. Clone repository
• Usage
• Tests
  • 1. git-lfs
  • 2. Download data
  • 3. Run tests
  • 4. Test results
• Example execution
• Parsing output

Table of Contents created by gh-md-toc

Combination of MRI and MRS

Project flowchart

(Implemented rightmost column)

Citation

If you use our software in your research, please cite as below:

Billah, Tashrif; Norton, Isaiah; Pasternak, Ofer; Combining diffusion MRI and MRS, https://github.com/pnlbwh/mri2mrs, 2018, DOI: 10.5281/zenodo.2576656

Installation

You need a Linux workstation to install and run the mri2mrs command line module.

1. Dependencies

mri2mrs command line module depends on external commands like unu, DWIConvert, ants etc. To build those commands on your machine, follow installation instruction 1,2,3, and 5 (upto and including ./pnlpipe std setup).

2. Setup environment

Next, we need to make the external commands available to system path:

cd path/to/software/dir
cd BRAINSTools-bin-*
chmod +x env.sh
./env.sh

3. MATLAB

Install MATLAB (it requires a license). An instruction for installing MATLAB on linux is available here.

4. Clone repository

Now that all the dependencies are solved, you can clone the mri2mrs repository and start using it.

git clone https://github.com/pnlbwh/mri2mrs.git
cd mri2mrs

If the above steps are successful, help message will be correctly displayed: ./mri2mrs.py --help

Usage

Calculates brain and white matter volumes given an MRS (Magnetic Resonance Spectroscopy)
label map and a T1 image registered in the space MRS.
Dependencies on bet, fslmaths, fast, fslswapdim, fslstats, ConvertBetweenFileFormats, matlab, Slice.
Uses Ofer's MATLAB code (SIEMENS machine) for creating MRS region mask.

Usage:
    mri2mrs.py [SWITCHES] 

Meta-switches:
    -h, --help                          Prints this help message and quits
    --help-all                          Prints help messages of all sub-commands and quits
    -v, --version                       Prints the program's version and quits

Switches:
    -b, --betThreshold VALUE:str        threshold for bet mask creation; the default is 0.3
    -c, --caseID VALUE:str              case ID; required
    -i, --input VALUE:ExistingFile      a T1 image registered in the space of magnetic
                                        resonance spectroscopy (nrrd or nifti); required
    -m, --mask                          turn on this flag to mask the T1 image before running
                                        the pipeline. When turned on, a mask is created and the
                                        T1 image is multiplied by the mask before running
                                        further steps
    -o, --out VALUE:str                 output directory where files created during the
                                        pipeline are saved (if already exist, it will be
                                        deleted and recreated); required
    --rdaFile VALUE:ExistingFile        an rda file from the scanner defining coordinates of
                                        the ROI (acg, agm, ltemp, pcg, pwm etc.); required
    --roi VALUE:str                     region of interest (ROI) name (acg, agm, ltemp, pcg,
                                        pwm etc.); required

Tests

See the following instruction to run tests upon successful installation of mri2mrs and dependencies:

1. git-lfs

Test data is managed by git-lfs. One time installation of git-lfs per machine is required. Install git-lfs as follows:

Download git-lfs command line extension

tar -xzvf git-lfs-linux-*
install.sh
git lfs install

2. Download data

Now download the test data: git lfs pull --exclude=

3. Run tests

Finally, you should be able to run test as follows:

cd test_data
../mri2mrs.py -i Test_SAG_MPRAGE_1mm_isoa.nii --rdaFile MRS_tha_press.rda -c Test --roi tha -o ./mri2mrs.test -m

4. Test results

You should see the following output:

ROI volume:4200.0
CSF volume:0.0
WM volume:4172.0
GM volume:28.0

Example execution

./mri2mrs.py \
-i /rfanfs/pnl-zorro/projects/VA_AcuteTBI/MRIData/RegisteredT1/BIO_0002-registeredT1.nrrd \
--roi pcg -c BIO_0002 -m \
--rdaFile /rfanfs/pnl-zorro/projects/VA_AcuteTBI/MRIData/MRS_VA_AcuteTBI/BIO_0002/BIO_0002_pcg_press.rda \
-o ./mri2mrsOutput

Parsing output

In python3:

with open('logFileName') as f:
    volume= [line.split(':')[1] for line in f.read().split('\n') if "attr" in line]

You can also do float(volume) if necessary.

The attr you want to grab are ROI, GM, WM, CSF while the logFileName is your log text file.

In shell:

volume=`grep "attr" logFileName | awk -F ":" '{print $2}'`