PETPrep

https://petprep.readthedocs.io/en/latest/
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PETPrep is a robust, BIDS-compliant preprocessing pipeline for positron emission tomography (PET)...
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### Install PETPrep with pip (bare-metal)

Source: https://petprep.readthedocs.io/en/latest/installation.html

Installs PETPrep in a manually prepared Python 3.10+ environment with pip. This method is not recommended; containers are preferred. External dependencies (FSL, ANTs, AFNI, C3D, FreeSurfer, PETPVC, bids-validator, connectome-workbench) must be installed separately and available in $PATH.

```bash
$ python -m pip install petprep

```

--------------------------------

### Install petprep-docker wrapper with pip

Source: https://petprep.readthedocs.io/en/latest/_sources/installation.rst.txt

Installs the petprep-docker wrapper using pip. This is the recommended way to run PETPrep with Docker.

```bash
$ python -m pip install petprep-docker
```

--------------------------------

### Check Docker installation with docker info

Source: https://petprep.readthedocs.io/en/latest/usage.html

Check that Docker is installed and running before using the PETPrep Docker wrapper.

```bash
docker info

```

--------------------------------

### Install petprep-docker wrapper with pip

Source: https://petprep.readthedocs.io/en/latest/installation.html

Installs the petprep-docker wrapper via pip. Requires about 30 GB free space because the image is 24 GB; Docker's default settings may not use the last 10% of disk.

```bash
$ python -m pip install petprep-docker

```

--------------------------------

### Install PETPrep with pip in bare-metal environment

Source: https://petprep.readthedocs.io/en/latest/_sources/installation.rst.txt

Installs PETPrep in a manually prepared Python 3.10+ environment using pip. This method is not recommended; containers are preferred.

```bash
$ python -m pip install petprep
```

--------------------------------

### Run petprep-docker command-line

Source: https://petprep.readthedocs.io/en/latest/_sources/installation.rst.txt

Runs the petprep-docker command-line as if running petprep on a bare-metal installation. The command-line options are the same as for bare-metal.

```bash
$ petprep-docker <input_bids_path> <derivatives_path> <analysis_level> <named_options>
```

--------------------------------

### PETPrep HMC command examples

Source: https://petprep.readthedocs.io/en/latest/_sources/usage.rst.txt

Example commands for configuring head motion correction in PETPrep. The first sets FWHM to 8 and start time to 60 seconds. The second fixes the initial frame to index 10. The third disables automatic memory safeguards. The fourth disables HMC entirely.

```bash
$ petprep /data/bids_root /out participant --hmc-fwhm 8 --hmc-start-time 60
```

```bash
$ petprep /data/bids_root /out participant --hmc-init-frame 10 --hmc-init-frame-fix
```

```bash
$ petprep /data/bids_root /out participant --hmc-memory-policy off
```

```bash
$ petprep /data/bids_root /out participant --hmc-off
```

--------------------------------

### Run PETPrep with Apptainer

Source: https://petprep.readthedocs.io/en/latest/installation.html

Runs PETPrep via Apptainer, binding input data, output directory, and FreeSurfer license, then passing the BIDS-Apps arguments and options. The example uses participant or group analysis level, a participant label, the FreeSurfer license file, and a work directory.

```bash
$ apptainer run \
 --bind /path_to_data:/data:ro \
 --bind /path_to_output:/out \
 --bind /path_to_freesurfer/license.txt:/license \
 /path_to_sif/petprep.sif /data /out participant or group \
 --participant-label sub-ID \
 --fs-license-file /license \
 --work-dir /out/work

```

--------------------------------

### Check PETPrep version

Source: https://petprep.readthedocs.io/en/latest/installation.html

Checks the installed PETPrep version.

```bash
$ petprep --version

```

--------------------------------

### Check PETPrep version

Source: https://petprep.readthedocs.io/en/latest/_sources/installation.rst.txt

Checks the PETPrep installation by displaying the version information.

```bash
$ petprep --version
```

--------------------------------

### Initialize PET reference workflow (init_raw_petref_wf)

Source: https://petprep.readthedocs.io/en/latest/_sources/workflows.rst.txt

Initializes the PET reference image workflow. The strategy is selected via the --petref option, with 'auto' as the default. The workflow estimates a reference image for a PET series according to the requested strategy.

```python
from petprep.workflows.pet.reference import init_raw_petref_wf
wf = init_raw_petref_wf()
```

--------------------------------

### Confounds metadata JSON example

Source: https://petprep.readthedocs.io/en/latest/outputs.html

Example of the metadata JSON file (desc-confounds_timeseries.json) that accompanies each confounds TSV file. It shows entries for aCompCor components, including fields like CumulativeVarianceExplained, Mask, Method, Retained, SingularValue, and VarianceExplained. The 'dropped_0' entry has Retained false, indicating it is not saved in the data file for denoising.

```json
{
  "a_comp_cor_00": {
    "CumulativeVarianceExplained": 0.1081970825,
    "Mask": "combined",
    "Method": "aCompCor",
    "Retained": true,
    "SingularValue": 25.8270209974,
    "VarianceExplained": 0.1081970825
  },
  "dropped_0": {
    "CumulativeVarianceExplained": 0.5965809597,
    "Mask": "combined",
    "Method": "aCompCor",
    "Retained": false,
    "SingularValue": 20.7955177198,
    "VarianceExplained": 0.0701465624
  }
}
```

--------------------------------

### Pull or build pre-built PETPrep image (Docker/Apptainer)

Source: https://petprep.readthedocs.io/en/latest/_sources/installation.rst.txt

Shows alternative ways to obtain a pre-built PETPrep image: pulling the Docker image (with a platform-specific variant for linux/amd64) or building an Apptainer SIF from the Docker image. The latest image is available at https://github.com/nipreps/petprep/pkgs/container/petprep.

```bash
$ docker pull ghcr.io/nipreps/petprep:main
```

```bash
$ docker pull --platform=linux/amd64 ghcr.io/nipreps/petprep:main
```

```bash
$ apptainer build petprep.sif docker://ghcr.io/nipreps/petprep:main
```

--------------------------------

### Run PETPrep via Apptainer with bind mounts

Source: https://petprep.readthedocs.io/en/latest/_sources/installation.rst.txt

Runs PETPrep via Apptainer with bind mounts for input data, output directory, and FreeSurfer license. The command includes participant/group analysis level, participant label, FreeSurfer license file, and work directory options.

```bash
$ apptainer run \
 --bind /path_to_data:/data:ro \
 --bind /path_to_output:/out \
 --bind /path_to_freesurfer/license.txt:/license \
 /path_to_sif/petprep.sif /data /out participant or group \
 --participant-label sub-ID \
 --fs-license-file /license \
 --work-dir /out/work
```

--------------------------------

### Example confounds TSV table

Source: https://petprep.readthedocs.io/en/latest/outputs.html

Example TSV table of extracted confounding time series. Each row corresponds to one time point in the PET time series. Columns include csf, white_matter, global_signal, std_dvars, dvars, framewise_displacement, t_comp_cor_*, a_comp_cor_*, non_steady_state_outlier, and motion parameters (trans_x, trans_y, trans_z, rot_x, rot_y, rot_z).

```text
csf white_matter  global_signal std_dvars dvars framewise_displacement  t_comp_cor_00 t_comp_cor_01 t_comp_cor_02 t_comp_cor_03 t_comp_cor_04 t_comp_cor_05 a_comp_cor_00 a_comp_cor_01 a_comp_cor_02 a_comp_cor_03 a_comp_cor_04 a_comp_cor_05 non_steady_state_outlier00  trans_x trans_y trans_z rot_x rot_y rot_z
682.75275 0.0 491.64752000000004  n/a n/a n/a 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 -0.00017029 -0.0  0.0
669.14166 0.0 489.4421  1.168398  17.575331 0.07211929999999998 -0.4506846719 0.1191909139  -0.0945884724 0.1542023065  -0.2302324641 0.0838194238  -0.032426848599999995 0.4284323184  -0.5809158299 0.1382414008  -0.1203486637 0.3783661265  0.0 0.0 0.0207752 0.0463124 -0.000270924  -0.0  0.0
665.3969  0.0 488.03  1.085204  16.323903999999995  0.0348966 0.010819676200000001  0.0651895837  -0.09556632150000001  -0.033148835  -0.4768871111 0.20641088559999998 0.2818768463  0.4303863764  0.41323714850000004 -0.2115232212 -0.0037154909000000004  0.10636180070000001 0.0 0.0 0.0 0.0457372 0.0 -0.0  0.0

```

--------------------------------

### init_pet_fit_wf workflow initialization

Source: https://petprep.readthedocs.io/en/latest/_sources/workflows.rst.txt

Initializes the PET fit workflow (init_pet_fit_wf) with a mock configuration and a single PET file. This is used to generate the workflow graph for the PET fit sub-workflow.

```python
from petprep.workflows.tests import mock_config
from petprep import config
from petprep.workflows.pet.fit import init_pet_fit_wf
with mock_config():
    pet_file = config.execution.bids_dir / 'sub-01' / 'pet' \
        / 'sub-01_task-mixedgamblestask_pet.nii.gz'
    wf = init_pet_fit_wf(pet_series=[str(pet_file)])
```

--------------------------------

### petprep-docker command-line usage

Source: https://petprep.readthedocs.io/en/latest/usage.html

Command-line usage for the petprep-docker wrapper. Shows positional arguments (bids_dir, output_dir, analysis_level) and named options including wrapper and developer options.

```text
usage: petprep-docker [-h] [--version] [-i IMG] [-w WORK_DIR]
                      [--output-spaces [OUTPUT_SPACES ...]]
                      [--fs-license-file PATH] [--fs-subjects-dir PATH]
                      [--config-file PATH] [-d PATH [PATH ...]]
                      [--use-plugin PATH] [--bids-database-dir PATH]
                      [--bids-filter-file PATH]
                      [--patch PACKAGE=PATH [PACKAGE=PATH ...]] [--shell]
                      [--config PATH] [-e ENV_VAR value] [-u USER]
                      [--network NETWORK] [--no-tty]
                      [bids_dir] [output_dir] [{participant}]

```

--------------------------------

### Extract thalamus mask as reference region

Source: https://petprep.readthedocs.io/en/latest/_sources/usage.rst.txt

Example command to extract a thalamus mask for use as a reference region, specifying the segmentation method and region indices.

```bash
$ petprep /data/bids_root /out participant \
    --seg gtm --ref-mask-name thalamus --ref-mask-index 10 49
```
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