Skip to content

A workflow to allow Freesurfer recon-all to run on brain image with gliomas

License

Notifications You must be signed in to change notification settings

KUL-Radneuron/KUL_VBG

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

62 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

KUL_VBG

A workflow to allow Freesurfer recon-all to run on brain images with large lesions. VBG is a bash script tested in Mac OSX, Ubuntu 18.0 and CentOS.

The first commit on this repository corresponds to the version of the workflow used in the preprint "Virtual brain grafting: Enabling whole brain parcellation in the presence of large lesions. Radwan et al., 2020, DOI: https://doi.org/10.1101/2020.09.30.20204701, available via: https://www.medrxiv.org/content/10.1101/2020.09.30.20204701v1). This work was published in Neuroimage, 2021 available here: https://doi.org/10.1016/j.neuroimage.2021.117731

Updated Dependencies: a) ANTs v2.3.1 and ANTsX scripts b) FSL v6.0 c) MRtrix3 v3.0.2-64-g3eadb340 d) HD-BET f) Freesurfer v6.0 e) FastSurfer

Inputs:

Obligatory: 1- Input to -S flag (subject/participant name in BIDS convetion, without the leading sub-). 2- A nifti format T1 WI of a subject (input to -a flag) 3- Binary lesion mask (lesion = 1, background = 0) integer nifti format (input to -l flag) 4- Indicate lesion mask space (input to -z flag) N.B. the specified lesion mask must have the same dimensions and transform as the input T1 WI.

Optional: 1- Specify location of intermediate processing and output folders (-m and -o flags) 2- Specify number of parallel workers used (input to -n flag) 3- Specify type of filling (default = uVBG, to activate bVBG use the -t flag) 4- Specify age group of participant (default = adult, to activate pediatric friendly mode specify the -p flag) 5- To run parcellation specify the after the lesion filling is finished, specify the -P flag with input 1=Freesurfer, 2=FastSurfer, 3=FastSurfer/FreeSurfer hybrid 6- Verbose mode = -v

Examples:

- Using the unilateral VBG approach and HD-BET for brain extraction, input data is in BIDS format with only 1 session, using FreeSurfer for parcellation
KUL_VBG.sh -p pat001 -b -n 6 -l /fullpath/lesion_T1w.nii.gz -z T1 -o /fullpath/output -B 1 -P 1 -v

- Using the bilateral VBG approach and HD-BET for brain extraction, input data is not in BIDS, using FastSurfer for parcellation
KUL_VBG.sh -p pat001 -a /fullpath/sub-PT_T1w.nii.gz -n 6 -l /fullpath/lesion_T1w.nii.gz -z T1 -o /fullpath/output -t -B 1 -P 2 -v

Purpose:

The purpose of this workflow is to generate a lesion filled image, with healthy looking synthetic tissue in place of the lesion
Essentially excising the lesion and grafting over the resulting defect in the T1 MR image space.

Required arguments:

-S:  BIDS participant name (anonymised name of the subject without the "sub-" prefix)
-b:  if data is in BIDS
-l:  full path and file name to lesion mask file per session
-z:  space of the lesion mask used (only T1 supported in this version)
-a:  Input precontrast T1WIs

Optional arguments:

-s:  session (of the participant)
-t:  Use the VBG template to derive the fill patch (if used, template tissue is used alongside native tissue to create the donor brain)
-E:  Treat as an extra-axial lesion (skip VBG bulk, fill lesion patch with 0s, run FS and subsequent steps)
-B:  specify brain extraction method (1 = HD-BET, 2 = ANTs-BET), if not set ANTs-BET will be used by default
-P:  Run parcellation (1 = FreeSurfer recon-all, 2 = FastSurfer)
-p:  In case of pediatric patients - use pediatric template (NKI_under_10 in MNI)
-m:  full path to intermediate output dir
-o:  full path to output dir (if not set reverts to default output ./lesion_wf_output)
-n:  number of cpu for parallelisation (default is 6)
-v:  show output from mrtrix commands
-h:  prints help menu

Notes:

- Input flags -b and -a are mutually exclusive, if your data is in BIDS use -b, and if not then specify exact path and name for the patient's T1.nii.gz 
- In case of trouble with HD-BET see lines (1140 - 1170)
- You need a high resolution T1 WI and a lesion mask in the same space for VBG to run
- If you end up with an empty image, it is possible you have a mismatch between the T1 and lesion mask
- The lesion mask can be generated with any lesion segmentation tool.
- The lesion mask needs to specific to the lesion with voxel values=1 encoding the lesion and 0 for the healthy tissue.

Installation instructions:

- Clone this repository, add the installation directory to your path in Bash shell.
- Ensure that all dependencies are met, FastSurfer is only required if you will use it for parcellation (i.e. with -P 2 or -P 3)

About

A workflow to allow Freesurfer recon-all to run on brain image with gliomas

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 3

  •  
  •  
  •  

Languages