Pre-CAT is a preclinical CEST-MRI data analysis toolbox and Streamlit webapp. Pre-CAT was originally designed for processing cardiac and abdominal CEST acquisitions using the radial FLASH sequence described by Weigand-Whittier et al., but has been expanded for use with all ParaVision 6/7 CEST acquisitions.
⚠ Note:
Pre-CAT scripts rely on ParaVision method files with specific variable names. Pre-CAT is guaranteed to work with the cestsegCSUTE sequence, and should work with any CEST sequence based on the PV 6/7 MT module. Pre-CAT will not work with PV 360 acquisitions using the new CEST module. This may change in the future.
Pre-CAT processes and displays Z-spectra, Lorentzian difference plots, pixelwise maps, and field maps. Processed data is also saved in organized pickle files for downstream tasks.
A pre-prepared Conda environment is available in the environment.yml file. To install the environment, run:
conda env create -f environment.yml
conda activate pre-catFinally, BART is also required. Please download the most recent version and follow the instructions in the README file for installation.
⚠ Note for Mac Users:
If you're using an M1 Mac, please follow the MacPorts version of the installation instructions forBART.
After activating the included Conda environment, navigate to the Pre-CAT directory and run:
streamlit run app.pyIn-depth instructions are included in the Streamlit interface.
For users unfamiliar with murine and cardiac anatomy, instructions for cardiac ROI prescriptions are included here.
To test Pre-CAT with example data, you can download the provided dataset here.
Please use the Issues section to report bugs or ask questions.
You are also welcome to contact me directly with any issues or questions at: jweigandwhittier[at]berkeley[dot]edu.
Please add [Pre-CAT] to the subject line of your email.
Please cite the associated publications when using Pre-CAT:
Weigand-Whittier J., Wendland M., Lam B., et al. Ungated, plug‐and‐play preclinical cardiac CEST‐MRI using radial FLASH with segmented saturation. Magn Reson Med (2025). https://doi.org/10.1002/mrm.30382
If you are using CEST-MRF analysis features, please also cite:
Vladimirov N., Cohen O., Heo H.Y., et al. Quantitative molecular imaging using deep magnetic resonance fingerprinting. Nat Protoc (2025). https://doi.org/10.1038/s41596-025-01152-w