Welcome to petprep_extract_tacs’s documentation!

Overview

This BIDS App is designed to extract time activity curves (TACs) from PET data. The workflow has options to extract TACs from different regions of the brain, and it uses the Brain Imaging Data Structure (BIDS) standard for organizing and describing the data. This README will guide you through how to use the app and the various options available. The workflow requires that freesurfer’s recon-all was already executed for these subjects, and exist as a ‘freesurfer’ directory inside the derivatives directory for the given BIDS dataset.

Features

  • BIDS compliant PET data input and output

  • Time Activity Curve extraction from various brain regions

  • Options for both surface and volume-based extractions including smoothing options

Requirements

  • Python 3.9+

  • FreeSurfer v. 7.3.2

  • MATLAB RUNTIME (sudo fs_install_mcr R2019b when FreeSurfer is installed)

Installation

Clone the repository and install the required packages:

git clone
git clone https://github.com/mnoergaard/petprep_extract_tacs.git
cd petprep_extract_tacs
pip install -e .

The package is also pip installable and can be installed using the following command

pip install petprep-extract-tacs

Quickstart

After installation, you’ll need to have your data organized according to the BIDS standard. Once that’s in place, you can run the app like this:

petprep_extract_tacs /path/to/your/bids/dataset /path/to/output/dir --n_procs 4 --wm

Alternatively, you can run the code directly with Python using the run.py entrypoint:

python3 run.py /path/to/your/bids/dataset /path/to/output/dir --n_procs 4 --wm

This will run the app on your BIDS dataset and save the output to the specified directory. Additional region-specific and smoothing options can be specified as detailed below.

For more detailed usage see the usage_page section.

Contents:

Indices and tables