Tedana multi echo data processing - fmriprep outputs

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1

Hi,
I used tedana combine/denoise the multi echo data pre-processed using fMRIprep. Why do some parts of the brain are missing in TEDANA output? TEDANA command used ,

tedana -d sub-13023_ses-1_task-Insight1_run-01_echo-1_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz sub-13023_ses-1_task-Insight1_run-01_echo-2_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz sub-13023_ses-1_task-Insight1_run-01_echo-3_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz -e 10.8 28.68 46.56 --out-dir insight1

Here are the three echos(after fMRIPrep pre-processed)

S13023_echo3
S13023_echo3.png1336×652 20.5 KB
S13023_echo2
S13023_echo2.png1337×653 22.3 KB
S13023_echo1
S13023_echo1.png1346×651 28.5 KB
![dn_ts_OC|690x334]

TEDNA output : (upload://m1Ii8beCTdDwCoUD2W2ztY0FyKy.png)

Thank you
Sameera

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dn_ts_OC

Here is the TEDANA output

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Hi @sameera2004 –

Unfortunately, we don’t recommend this pipe-lining of the two methods – the distortion correction applied in fMRIPrep invalidates the calculation of the T2* map that underlies tedana’s optimal combination and denoising procedures. Instead, we recommend using files from the fMRIPrep working directory. Please see this thread for more details: Combining fmriprep with ME-ICA from tedana

HTH,

Elizabeth

4

Hi,

I would also add that from my experience feeding in minimally processed images to tedana, as @emdupre, suggests can also result in tedana cutting off some of brain (mostly subcortical). One way I have circumvented this issue is by feeding in an explicit mask to tedana using -m.

Best

1 Like
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Hi @emdupre and @gspitz,

Thank you so much for your replies. Yes it worked when I run TEDANA from the fMRIprep working directory and providing the mask.(–mask)

nii
dn_ts_OC.nii.png1341×663 20.1 KB

Best Regards
Sameera

1 Like
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Happy to hear this worked for you ! Thanks for following up, @sameera2004 :smile:

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Hi @emdupre,

I have another question regarding these TEDANA outputs (dn_ts_OC.nii).

Do I need to run one more time fMRIprep for these TEDANA output to perform regression with the denoised data? Is there a easy way to do this? Because I need to prepare them again in BIDS format etc to run fMRIprep?

Thank you

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@emdupre

So it’s basically adapting the fmriprep t2smap command for tedana, right?

Found in:
‎⁨scratch/fmriprep_wf⁩/single_subject_SUBJECT_wf⁩/func_preproc_task_TASKNAME_echo_1_wf⁩/ ⁨bold_t2smap_wf⁩/t2smap_node⁩/command.txt

I see that this command is using skull stripped files while the python script at https://github.com/ME-ICA/tedana-reliability-analysis/blob/master/collect_fmriprep.ipynb refers to non-skullstripped files in a different location. As the images in both locations seem to have the same values within the mask area, I assume that there are no other transformations applied.

Furthermore, it seems that the input will be masked anyway using Nilearn’s compute_epi_mask.