The goal of bloodstream is to provide a simplified and automated pipeline for processing BIDS blood data for PET. The bloodstream package is based on functions found in kinfitr, but strings them together into a blood processing pipeline, producing a parameterised report as well as processed blood derivatives.
For a short introduction to processing blood data for PET, as well as tutorial for how to use bloodstream, I've recorded an explainer video, which should help you get started.
You can install the development version of bloodstream like so:
remotes::install_github("mathesong/bloodstream")You can also use this package as a standalone dockerised BIDS app as described below.
In order to call bloodstream, you need to specify a studypath and a configpath.
-
The
studypathis the location of the BIDS data, e.g.../ds004230(relative or full paths are allowed). -
The
configpathis the path to thebloodstreamconfiguration file, which specifies the modelling choices which you will make as a user. To create a configuration file, go to the bloodstream configuration web app, fill in the fields as required, and download the JSON configuration file. Theconfigpathspecifies the location of the downloaded config file, e.g.../config_test_analysis.json. If left blank, then the blood data will simply be combined using linear interpolation.
The pipeline can then be called as follows:
library(bloodstream)
bloodstream(studypath, configpath)It will generate the following outputs:
- A report showing all the code and functions used, as well as plots before and after modelling.
... and for all individual PET measurements, the following
- Tabular tsv output (
*_inputfunction.tsv) containing the estimated interpolated data which can be used for modelling. - JSON sidecar accompanying the tabular tsv data (
*_inputfunction.tsv). - Model configuration JSON files, containing the models used and the AIF fit parameters if applicable (
*_config.json).
The file docker/dockerfile can be used to create a container that can run bloodstream.
To build the container, run:
cd docker
docker build -t bloodstream . --platform linux/amd64
To run bloodstream using the Docker container, you need to mount the directory containing your BIDS dataset. Then you can run the container on your dataset as below.
docker run -v /path/to/bids_data/:/data/ bloodstream
Note, that we have not provided a config.json file, and so bloodstream will simply make use of a default procedure using linear interpolation only, and not make use of any more advanced modelling routines.
If you would like to make use of a config.json file (which can be created using the web app), then you should place the generated JSON file into a directory within the BIDS directory named /path/to/bids_data/code/bloodstream/ and name it with a title beginning with config_. Then you can direct bloodstream to this filename as an input argument as follows:
docker run -v /path/to/bids_data/:/data/ bloodstream config_pf_bpr.json
Once complete, all outputs from the bloodstream analysis will be located in the /path/to/bids_data/derivatives directory.
Until there is a preprint or publication about bloodstream, please just specify that "bloodstream was used for blood analysis, which is a blood processing pipeline built around kinfitr [REF]".
To cite kinfitr, please cite at least one of the following:
An introduction to the package:
Matheson, G. J. (2019). Kinfitr: Reproducible PET Pharmacokinetic Modelling in R. bioRxiv: 755751. https://doi.org/10.1101/755751
A validation study compared against commercial software:
Tjerkaski, J., Cervenka, S., Farde, L., & Matheson, G. J. (2020). Kinfitr – an open source tool for reproducible PET modelling: Validation and evaluation of test-retest reliability. EJNMMI Res 10, 77 (2020). https://doi.org/10.1186/s13550-020-00664-8