Fmriprep > 1 lesion

fmriprep

#1

Hi all,

Thanks for making such wonderful tools for neuroimaging analysis–it makes all ofour lives so much easier :slight_smile:

The workflow page for fmriprep (http://fmriprep.readthedocs.io/en/latest/workflows.html#t1w-t2w-preprocessing) says that a lesion mask will be used for ANTs registration. How does fmriprep handle individuals who may have more than 1 lesion mask? Should the lesion masks be added together and then binarized?

Thanks!


#2

Hi Kito,

According to the documentation,

Lesion masks should be binary NIfTI images (damaged areas = 1, everywhere else = 0) in the same space and resolution as the T1 image, and follow the naming convention specified in BIDS Extension Proposal 3: Common Derivatives (e.g. sub-001_T1w_label-lesion_roi.nii.gz).

As you’ve stated, putting them together in one map and binarizing sounds like a good solution.

-jon


#3

Got it - thanks Jon!


#4

Hi Jon,

I tried to run fmriprep with and without the lesion included in my “anat” directory labeled as “sub-01_T1w_label-lesion_roi.nii.gz”. I used the same command for both, and when I run it excluding the lesion, all of the output files are in the correct place, and I get a sub-01 html output as well, but when I include the lesion file, I only get the following outputs:

├── logs
│   ├── CITATION.html
│   ├── CITATION.md
│   └── CITATION.tex
└── sub-01
    └── anat
        ├── sub-01_T1w_brainmask.nii.gz
        ├── sub-01_T1w_label-aparcaseg_roi.nii.gz
        ├── sub-01_T1w_label-aseg_roi.nii.gz
        ├── sub-01_T1w_preproc.nii.gz
        ├── sub-01_T1w_space-orig_target-T1w_affine.txt
        └── sub-01_T1w_target-fsnative_affine.txt

And here are the last few lines out the log (with the lesion):

  [Node] Finished "fmriprep_wf.single_subject_01_wf.func_preproc_task_AO_run_03_wf.bold_reg_wf.bbreg_wf.bbregister".
180807-00:42:15,244 nipype.workflow INFO:
 [Node] Finished "_midthickness1".
180807-00:42:21,882 nipype.workflow INFO:
 [Node] Finished "_midthickness0".

Should I not be running the same command when including a lesion file? I was under the impression that it would include the lesion mask for registration as long as the lesion was in BIDS compatible format…

Thanks!


#5

Hi @kito,

Is the command finishing when you see _midthickness0 as the final line of the log? It may be that the normalization step is taking longer than usual with the lesion ROI. (@danlurie may have an estimate of how long to expect a normalization to take.)

Chris


#6

Thanks for your response Chris!

Hmm I’m running it on a remote/screen, but I tried using the $? command and it returned 1, so I’m guessing the command didn’t finish… (Do you think I just need to wait longer?)


#7

If you have a prompt, then it stopped, and you should see more of an error message. You can try re-running, if you’ve lost your logs; it should pick up where it left off and print full error logs. Errors should also show up in the report.


#8

Hi Chris,

So I re-ran the same command again, but it actually doesn’t produce any error messages but gives me a prompt. It also doesn’t produce a report. (I’m rerunning again now to get the log piped into a text file so I can send that over when it’s done).

I can also send over my test case if that would be helpful.

Thanks!


#9

Sure. I can see if I can reproduce.


#10

Thanks!

Here’s the link to the (1) subject data I was trying to run

https://drive.google.com/file/d/1inmsYLr5av29_hVZ9swTySxF3p3SZXCz/view?usp=sharing

and I was running with this command:

docker run -ti --rm -v /home/kito/Learning/fmriprep/bids_compatible/LHS_data:/data:ro -v /home/kito/Learning/fmriprep/fmriprep_AON_LHS/:/out -v /home/kito/.licenses/freesurfer/license.txt:/opt/freesurfer/license.txt poldracklab/fmriprep:latest /data /out/out participant


#11

Your sub-01_T1w_label-lesion_roi.nii.gz is actually an uncompressed NIfTI. That’s going to cause problems. You can fix this with:

mv sub-01_T1w_label-lesion_roi.nii.gz sub-01_T1w_label-lesion_roi.nii
gzip sub-01_T1w_label-lesion_roi.nii

That may not be the only issue, so I’ll fix this on my end, as well, and run fmriprep. (I’ll be using the latest, version 1.1.4.)


#12

Lesion images are assumed to be the same size and orientation as the T1w image. Here you have a 256x208x256 T1w image and a 254x208x154 lesion image.

$ nib-ls sub-01_T1w.nii.gz sub-01_T1w_label-lesion_roi.nii 
sub-01_T1w.nii.gz               int16 [256, 208, 256] 1.00x1.00x1.00
sub-01_T1w_label-lesion_roi.nii uint8 [254, 208, 154] 1.00x1.00x1.00

#13

Ah - yes. Thank you for catching that!

I tried re-running it with the corrected lesion file, and it runs all the way through without errors… though when I look at the results side by side with the one ran without the lesion mask, it seems to look the same, and the output html/methods sections were identical.

I will try re-running it both ways again with a brain with a larger lesion.