Repository: https://github.com/JSIERO/ClinicalASL
Author: Jeroen Siero, UMC Utrecht
Contact: j.c.w.siero@umcutrecht.nl
Release Date: 2025-06-24
Version: v1.0.3

Official ClinicalASL processing pipeline for quantitative multi-delay ASL MRI data — designed for clinical use with PACS export and visual reporting.

• DICOM to NIfTI conversion
• Look-Locker correction
• Motion correction
• Outlier removal
• Quantitative perfusion parameter estimation:
  • Cerebral Blood Flow (CBF)
  • Arterial Arrival Time (AAT)
  • Arterial Transit Artefacts (ATA)
  • Cerebrovascular Reactivity (CVR)
• Export of results as NIfTI, PNG, and DICOM (PACS-ready) formats.

Supports baseline / stimulus ASL protocols (acetazolamide/diamox, hypercapnia, breath-hold, etc.)

This software is provided for post-processing of ASL MRI data for research and clinical evaluation purposes.
It is not CE marked or FDA cleared

See INSTALL.md or follow instructions in the GitHub repository.

Example config file containing scan and analysis parameters: config/config_default.json
You can supply your own config.json per acquisition protocol.

example config/config_default.json:

{
    "version": "v1.1-MRI_DIAMOX_MDLL_preACZ_postACZ-2025",
    "ASL scan": "multi-delay Look-Locker",
    "tau": 2,
    "N_BS": 4,
    "readout": "2D",
    "labeleff": 0.85,
    "lambda": 0.9,
    "T1t": 1.3,
    "T1b": 1.65,
    "FWHM": 6,
    "outlier_factor": 2.5,
    "range_cvr": [-50, 50],
    "range_AAT": [0, 3],
    "range_ATA": [0, 125],
    "inference_method": "ssvb",
    "device": "cpu",
    "ASL_CONTEXT": ["baseline", "stimulus"],
    "context_study_tags": ["preACZ", "postACZ"],
    "dicomseries_description_patterns": ["*SOURCE*ASL*"]
}

• Python 3.11+
• QASL by Quantified Imaging (license key required)
• dcm2niix (v1.0.20230411 or newer)
• HD-BET (for brain extraction)
• ANTsPy v 0.5.4 (for image registration) - version 0.6.1 works bad!
• Additional Python packages (see requirements.txt)

Complete installation instructions are available in INSTALL.md.

# Clone repositories
git clone https://github.com/JSIERO/ClinicalASL.git
git clone https://bitbucket.org/quantified-imaging/qasl_setup.git

# Install QASL (requires license key)
cd qasl_setup
./qasl_setup --yes --key=<your-qasl-key>

# Set up environment
conda activate qi
conda install -n qi -c conda-forge pip dcm2niix

# Install HD-BET
git clone https://github.com/MIC-DKFZ/HD-BET.git
cd HD-BET
pip install -e .

# Install ClinicalASL requirements
cd ../ClinicalASL/python
pip install -r requirements.txt

## Running the pipeline
Example command line:

```bash
python run_pipeline.py /path/to/DICOM_INPUT /path/to/OUTPUT_FOLDER \
    --inference-method [vaby|ssvb] \
    --config /path/to/config.json

##Output Structure The pipeline generates:

• NIfTI images: CBF, AAT, CVR, ATA maps
• Quality control PNGs: Visualizations for review
• DICOM files: PACS-compatible outputs
• Log file: clinicalasl.log with processing details
• Configuration copy: config_used.json