HIPLAY7 – myelin_content

myelin_content – compute a myelin proxy (R1 value) for the grey matter and the white matter in differents regions of the hippocampus and the cortex

Overview

This program performs four steps and will create one folder for each step :

1. Inputs : Extracts the needed inputs from the acquisition folder. Results save as nifti format (.nii)
2. B1_correction : Computes a corrected R1 map from B1+ inhomogeneities, using the information from a B1 map and the uniform T1 given by the MP2RAGE sequence. Results save as nifti format (.nii)
3. Segmentation : Performs a cortical and hippocampal parcellation using Freesurfer based on a uniform and denoised T1w image given by the MP2RAGE sequence. Results save as freesurfer format (.mgz).
4. Results : Computes an average R1 value in each cortical and hippocampal regions. Results save as .txt files.

Getting Started

Prerequisites

This program requires the following softwares and libraries :

• Python (version 3.7)
  Libraries :
  • nibabel
  • scipy
  • matplotlib
  • dicom2nifti
• FSL 6.0
• Freesurfer V.6

WARNING: This program requires to have access to the folder "Acquisition" and "I2BM" of Neurospin.

Installation

• Open a terminal and paste the following sentence : pip install git+https://github.com/mathrip/HIPLAY7#egg=HIPLAY7 Press enter. Your package will be installed.
• Open your default setup file (.bashrc) : gedit ~/.bashrc Add the following lines in the .bashrc (do not change anything else) :

export FREESURFER_HOME=/i2bm/local/freesurfer-6.0.0
source $FREESURFER_HOME/SetUpFreeSurfer.sh

Close the terminal

• Open a new terminal, you should see Setting up environment for FreeSurfer/FS-FAST (and FSL). Your hiplay package is ready to be used.

Usage

To launch the script, run
myelin_content <DATE_NIP> <output_path> [optional arguments]

where :

• <DATE_NIP> : the acquisition date in format yyyymmdd and the patient NIP. Correspond to subject identifier
• <output_path> : the path to the output folder
• --noseg (optional) : use this flag if you do not want to perform cortical and hippocampal parcellations. The program will only compute the first two steps.

Exemple :
myelin_content 20190719_mr331057 /home/Documents/Hiplay_results --noseg

Notes :

• The whole process can take up to 40h for images resolution of 0.75mm iso.
• This program has been only test for Linux users.
• For more information about the inputs/outputs data, please refers to the functions description within the python script.
• You can set up your own paths to freesurfer and fsl in the myelin_content script if you do not want to use the default ones.

Authors

Mathilde RIPART (Neurospin, CEA)

Other contributors of the programm : Aurélien Massire (Neurospin, CEA)

References

For any use of this code, the following paper must be cited :

[1] Natalia Zaretskaya et al, Advantages of cortical surface reconstruction using submillimeter 7 T MEMPRAGE, 2018, NeuroImage 165

[2] JE Iglesias, A computational atlas of the hippocampal formation using ex vivo, ultra-high resolutionMRI: Application to adaptive segmentation of in vivo MRI, Neuroimage, 2015

[3] A.Massire et al, High-resolution multi-parametric quantitative magnetic resonance imaging of the human cervical spinal cord at 7T, NeuroImage, 2016

[4] M.Jenkinson et al, Improved Optimisation for the Robust and Accurate Linear Registration and Motion Correction of Brain Images, NeuroImage, 2002