fMRIPrep anatomical image processing error

[yoonji.lee]

Summary of what happened:

Has anyone encountered this kind of issue when processing T1w images with FreeSurfer? I ran recon-all using Freesurfer 7.3.2 and fed the images to fMRIPrep 25.1.4. The images look identical to those generated when recon-all is run directly within fMRIPrep.

Command used (and if a helper script was used, a link to the helper script or the command generated):

PASTE CODE HERE

Version:

25.1.4

Environment (Docker, Singularity / Apptainer, custom installation):

PUT ENVIRONMENT HERE

Data formatted according to a validatable standard? Please provide the output of the validator:

PASTE VALIDATOR OUTPUT HERE

Relevant log outputs (up to 20 lines):

PASTE LOG OUTPUT HERE

Screenshots / relevant information:

Spatial normalization


And below is the boilerplate text from the FMRIPrep summary report:

Anatomical data preprocessing
: A total of 1 T1-weighted (T1w) images were found within the input
BIDS dataset. The T1w image was corrected for intensity
non-uniformity (INU) with N4BiasFieldCorrection [@n4], distributed with ANTs 2.6.2
[@ants, RRID:SCR_004757], and used as T1w-reference throughout the workflow.
The T1w-reference was then skull-stripped with a Nipype implementation of
the antsBrainExtraction.sh workflow (from ANTs), using MNI152NLin2009cAsym
as target template.
Brain tissue segmentation of cerebrospinal fluid (CSF),
white-matter (WM) and gray-matter (GM) was performed on
the brain-extracted T1w using fast [FSL (version unknown), RRID:SCR_002823, @fsl_fast].
Brain surfaces were reconstructed using recon-all [FreeSurfer 7.3.2,
RRID:SCR_001847, @fs_reconall], and the brain mask estimated
previously was refined with a custom variation of the method to reconcile
ANTs-derived and FreeSurfer-derived segmentations of the cortical
gray-matter of Mindboggle [RRID:SCR_002438, @mindboggle].
A T2-weighted image was used to improve pial surface refinement.
Brain surfaces were reconstructed using recon-all [FreeSurfer 7.3.2,
RRID:SCR_001847, @fs_reconall], and the brain mask estimated
previously was refined with a custom variation of the method to reconcile
ANTs-derived and FreeSurfer-derived segmentations of the cortical
gray-matter of Mindboggle [RRID:SCR_002438, @mindboggle].
Volume-based spatial normalization to two standard spaces (MNI152NLin2009cAsym, MNI152NLin6Asym) was performed through
nonlinear registration with antsRegistration (ANTs 2.6.2),
using brain-extracted versions of both T1w reference and the T1w template.
The following templates were were selected for spatial normalization
and accessed with TemplateFlow [24.2.2, @templateflow]:
ICBM 152 Nonlinear Asymmetrical template version 2009c [@mni152nlin2009casym, RRID:SCR_008796; TemplateFlow ID: MNI152NLin2009cAsym], FSL’s MNI ICBM 152 non-linear 6th Generation Asymmetric Average Brain Stereotaxic Registration Model [@mni152nlin6asym, RRID:SCR_002823; TemplateFlow ID: MNI152NLin6Asym].
Grayordinate “dscalar” files containing 91k samples were
resampled onto fsLR using the Connectome Workbench [@hcppipelines].

---

[Steven]

Hi @yoonji.lee,

In the future, please use the Software Support post category and template to provide information about your post. You can see I edited in for you this time, and you can edit your post to add the missing information.

I also noticed the two screenshots you posted were at X=0, or the midline of the brain. It is common for brain masks to look odd near the midline. Are they okay elsewhere in the brain? Does this happen for all subjects?

Best,
Steven