Weird brain mask from ASLPrep

lei_wei · November 5, 2025, 7:46pm

Summary of what happened:

I tried running ASLPrep on several subjects, but the brain masks it produced were all very strange. In contrast, when I applied BET directly, the results were correct.

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

BIDS=/gs/gsfs0/users/BIDS/HP
OUT=/gs/gsfs0/users/ASL_out
WORK=/gs/gsfs0/users/ASL_work
FS_DIR=/gs/gsfs0/users/BIDS/freesurfer  
FS_LICENSE=/gs/gsfs0/users/BIDS/freesurfer/license.txt
IMG=~/toolbox/aslprep/aslprep-25.1.0.sif
SUB=sub-003
mkdir -p "$OUT" "$WORK"
singularity run --cleanenv \
  -B "$BIDS":/bids:ro \
  -B "$OUT":/out \
  -B "$WORK":/work \
  -B "$FS_DIR":/fsdir \
  -B "$FS_LICENSE":/license.txt \
  "$IMG" \
  /bids /out participant \
  --participant-label "$SUB" \ 
  --nprocs 8 \
  --omp-nthreads 8 \
  --mem 32GB \
  --basil \
  --output-spaces T1w \
  --fs-license-file /license.txt \
  --fs-subjects-dir ${FS_DIR} \
  --fs-no-reconall

Version:

25.1.0

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

Singularity

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):

My first asl volume is M0, but second is a dummy scan. I just set the seconde line as noRF

volume_type
m0scan
noRF
label
control
label
control
label
control
label
...

Here is my json file for ASL

{
        "Modality": "MR",
        "MagneticFieldStrength": 3,
        "ImagingFrequency": 123.248,
        "Manufacturer": "Siemens",
        "ManufacturersModelName": "Prisma",
        "BodyPartExamined": "HEAD",
        "PatientPosition": "HFS",
        "SoftwareVersions": "syngo MR E11",
        "MRAcquisitionType": "3D",
        "SeriesDescription": "tgse_pcasl_Multi_Delay_ve11e_3.5iso_default",
        "ProtocolName": "tgse_pcasl_Multi_Delay_ve11e_3.5iso_default",
        "ScanningSequence": "EP",
        "SequenceVariant": "SK",
        "ScanOptions": "FS",
        "SequenceName": "tgse3d1_2268",
        "ImageType": ["ORIGINAL", "PRIMARY", "ASL", "NONE", "ND", "MOSAIC"],
        "NonlinearGradientCorrection": false,
        "SeriesNumber": 10,
        "AcquisitionTime": "15:47:2.145000",
        "AcquisitionNumber": 1,
        "SliceThickness": 3.5,
        "SpacingBetweenSlices": 3.5,
        "SAR": 0.103204,
        "EchoTime": 0.03168,
        "RepetitionTime": 4.35,
        "FlipAngle": 120,
        "RFGap": 0.00036,
        "MeanGzx10": 6,
        "ArterialSpinLabelingType": "PCASL",
        "M0Type": "Included",
        "RepetitionTimePreparation": 4.35,
        "LabelingDuration": 0.7,
        "PostLabelingDelay": 1.8,
        "BackgroundSuppression": true,
        "LabelingEfficiency": 0.85,
        "ArterialSpinLabelingType": "PCASL",
        "AcquisitionVoxelSize": [
                3.5,
                3.5,
                3.5     ],
        "PartialFourier": 1,
        "BaseResolution": 64,
        "ShimSetting": [
                4321,
                -1983,
                5074,
                576,
                72,
                187,
                14,
                35      ],
        "TxRefAmp": 216.302,
        "PhaseResolution": 0.984375,
        "ReceiveCoilName": "HeadNeck_64",
        "ReceiveCoilActiveElements": "HC3-6",
        "PulseSequenceDetails": "%CustomerSeq%\\tgse_pcasl_ve11e",
        "CoilCombinationMethod": "Sum of Squares",
        "ConsistencyInfo": "N4_VE11E_LATEST_20181129",
        "MatrixCoilMode": "SENSE",
        "RepetitionTimePreparation": 4350,
        "PercentPhaseFOV": 100,
        "PercentSampling": 98.4375,
        "EchoTrainLength": 63,
        "PhaseEncodingSteps": 63,
        "AcquisitionMatrixPE": 63,
        "ReconMatrixPE": 64,
        "PixelBandwidth": 3125,
        "DwellTime": 2.5e-06,
        "PhaseEncodingDirection": "j-",
        "ImageOrientationPatientDICOM": [
                1,
                0,
                0,
                0,
                0.999781,
                -0.0209424      ],
        "ImageOrientationText": "Tra>Cor(-1.2)",
        "InPlanePhaseEncodingDirectionDICOM": "COL",
        "ConversionSoftware": "dcm2niix",
        "ConversionSoftwareVersion": "v1.0.20220720"
}

Screenshots / relevant information:

tsalo · November 6, 2025, 3:05pm

This is definitely the most common issue ASLPrep users have. Unfortunately, I haven’t come up with a good solution. If you are able to create your own brain mask in ASL reference space, you can place it in a derivatives dataset and pass that into ASLPrep. ASLPrep’s fit/apply approach should grab the brain mask and use it instead of creating a new (bad) one. If you just replace the mask file in your current ASLPrep derivatives and re-run ASLPrep while passing in those derivatives via the --derivatives parameter, that should work.

lei_wei · November 6, 2025, 7:24pm

Hi
Thanks for your reply.
I replaced sub-002_ses-1_desc-brain_mask.nii.gz in the previous derivatives folder and re-ran ASLPrep pointing --derivatives to that directory. ASLPrep detects the preprocessed T1w and the brain mask but it still generates a new mask during the perfusion workflow.

BIDS=/gs/gsfs0/BIDS/HP
NEWOUT=/gs/gsfs0/ASL_out_rerun
WORK=/gs/gsfs0/BIDS/ASL_work
FS_DIR=/gs/gsfs0/BIDS/freesurfer
FS_LICENSE=/gs/gsfs0/BIDS/freesurfer/license.txt
IMG=~/toolbox/aslprep/aslprep-25.1.0.sif
SUB=002
PREV=/gs/gsfs0/BIDS/ASL_out 

singularity run --cleanenv \
  -B "$BIDS":/bids:ro \
  -B "$NEWOUT":/out \
  -B "$WORK":/work \
  -B "$FS_DIR":/fsdir \
  -B "$FS_LICENSE":/license.txt \
  -B "$PREV":/prevderiv:ro \
  "$IMG" \
  /bids /out participant \
  --participant-label "$SUB" \
  --derivatives /prevderiv \
  --nprocs 8 --omp-nthreads 8 --mem 32 \
  --basil \
  --output-spaces T1w \
  --fs-license-file /license.txt \
  --fs-subjects-dir /fsdir \
  --scorescrub \
  --fs-no-reconall

ASLprep tried to use the preivious derivatives but still generated a new wrong mask

251106-14:05:22,147 nipype.workflow IMPORTANT:
         Building ASLPrep's workflow:
           * BIDS dataset path: /bids.
           * Participant list: ['002'].
           * Run identifier: 20251106-140504_dc6d068d-3ba7-452b-b5cb-f87a4459c330.
           * Output spaces: T1w.
           * Searching for derivatives: {'prevderiv': PosixPath('/prevderiv')}.
           * Pre-run FreeSurfer's SUBJECTS_DIR: /fsdir.
251106-14:05:48,550 nipype.workflow INFO:
         ANAT Found preprocessed T1w - skipping Stage 1
251106-14:05:48,554 nipype.workflow INFO:
         ANAT Found brain mask
251106-14:05:48,557 nipype.workflow INFO:
         ANAT Skipping Stage 2
251106-14:05:48,557 nipype.workflow INFO:
         ANAT Skipping Stage 3
251106-14:05:48,557 nipype.workflow INFO:
         ANAT Found discrete segmentation
251106-14:05:48,557 nipype.workflow INFO:
         ANAT Found tissue probability maps
251106-14:05:48,557 nipype.workflow INFO:
         ANAT Stage 4: Found pre-computed registrations for {'MNI152NLin2009cAsym': {'forward': '/prevderiv/sub-002/ses-1/anat/sub-002_ses-1_from-T1w_to-MNI152NLin2009cAsym_mode-image_xfm.h5', 'reverse': '/prevderiv/sub-002/ses-1/anat/sub-002_ses-1_from-MNI152NLin2009cAsym_to-T1w_mode-image_xfm.h5'}}
251106-14:05:48,557 nipype.workflow INFO:
         ANAT Skipping Stages 5+
251106-14:06:08,113 nipype.workflow INFO:
         Collected run data for /bids/sub-002/ses-1/perf/sub-002_ses-1_asl.nii.gz:
aslcontext: /bids/sub-002/ses-1/perf/sub-002_aslcontext.tsv
m0scan: null
sbref: null

251106-14:06:08,772 nipype.workflow INFO:
         No single-band-reference found for sub-002_ses-1_asl.nii.gz.
251106-14:06:08,870 nipype.workflow INFO:
         Found HMC aslref - skipping Stage 1
251106-14:06:08,872 nipype.workflow INFO:
         Found motion correction transforms - skipping Stage 2
251106-14:06:08,872 nipype.workflow INFO:
         No fieldmap correction - skipping Stage 3
251106-14:06:08,872 nipype.workflow INFO:
         Found coregistration reference - skipping Stage 4
251106-14:06:08,875 nipype.workflow INFO:
         Found coregistration transform - skipping Stage 5
251106-14:06:12,65 nipype.workflow INFO:
         ASLPrep workflow graph with 228 nodes built successfully.

Is there an additional file I shoud put into the previous folder ?
The mri_synthstrip in freesurfer works fine for my M0 brain extraction, can I just call the function within the container ?

tsalo · November 10, 2025, 8:28pm

That’s unfortunate. @mattcieslak and I will spend Thursday and Friday this week trying to figure out what’s going wrong with the brain masks. Hopefully we’ll be able to push a fix soon after that.