APPIAN (Automated Pipeline for PET Image ANalysis) is an open-source automated software pipeline for analyzing PET images in conjunction with MRI. The goal of APPIAN is to make PET tracer kinetic data analysis easy for users with moderate computing skills and to facilitate reproducible research. The pipeline begins with the reconstructed PET image and performs all analysis steps necessary for the user to be able to take the outputs and run her statistical tests of interest.
APPIAN also uses a structural brain image (e.g., T1 MRI), images derived from this structural image (e.g., brainmask), and linear transformation file from MRI native to MNI152 space. CIVET is designed to extract surface meshes representing the cortical grey matter and can be used in conjuction with APPIAN. It can be freely used through the CBRAIN online platform (sign-up is required, but free). If CIVET is not used, users must provide the necessary T1 MRI derived files.
The APPIAN pipeline is implemented in Python using the Nipype library. Although the core of the code is written in Python, the pipeline can use tools or incorporate modules written in any programming language. The only condition is that the tools must be capable of being run from a command line with well-defined inputs and outputs. In this sense, APPIAN is language agnostic.
APPIAN is currently only available through Docker. Docker is a platform for creating containers that package a given software in a complete filesystem that contains everything it needs to run and ensures that the software can always be run in the same environment. This means that all of the dependencies needed by APPIAN are within its Docker container (no need to fumble about trying to compile obscure libraries). However, it also means that you will need to install Docker before proceeding. Don’t worry it’s very easy (except maybe for Windows). For a guide to installing Docker on Ubuntu, Debian, Mac, Windows.
Once docker is installed, simply run the following command on your command line terminal:
docker pull tffunck/appian:latest
That’s it, APPIAN is installed on your computer.
For those interested in extending or contributing to APPIAN please check out our developer guide.
Users seeking more information can check the user guide.
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Funck, T., Larcher K., Toussaint, P.J., Evans, A.C., Thiel, A. (2018). APPIAN: Automated Pipeline for PET Image Analysis. Frontiers in Neuroinformatics. 12, 64. https://doi.org/10.3389/fninf.2018.00064
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APPIAN automated QC paper (coming soon)
If you get stuck or don't know how to get started please post on our google groups. We would be delighted to help in whatever way we can.
https://groups.google.com/forum/#!forum/appian-pet
Thomas Funck, PhD Candidate (thomas.funck@mail.mcgill.ca)
Kevin Larcher, MSc Eng.
Paule Joanne Toussaint, PhD
Copyright 2017 Thomas Funck, Kevin Larcher
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