# pet-volume – Pre-processing of PET images for volume analyses¶

This pipeline performs several pre-processing steps on PET data in voxel space, which include:

• intra-subject registration of the PET image into the space of the subject’s T1-weighted MRI image using SPM;
• (optional) partial volume correction (PVC) using the PETPVC toolbox;
• inter-subject spatial normalization of the PET image into MNI space based on the DARTEL deformation model of SPM;
• intensity normalization using the average PET uptake in reference regions resulting in a standardized uptake value ratio (SUVR) map;
• parcellation into anatomical regions based on an atlas and computation of average values within each region. The list of available atlases can be found here.

## Prerequisite¶

You need to have performed the t1-volume-new-template or t1-volume-existing-template pipeline on your T1-weighted MRI images.

## Dependencies¶

• If you only installed the core of Clinica, this pipeline needs the installation of SPM and CAT12. You can find how to install these software packages on the installation page.

• If you want to apply partial volume correction (PVC) on your PET data, you will need to install PETPVC, which depends on ITK. More information on the installation page.

## Running the pipeline¶

The pipeline can be run with the following command line:

clinica run pet-volume bids_directory caps_directory group_id

where:

• bids_directory is the input folder containing the dataset in a BIDS hierarchy.
• caps_directory acts both as an input folder (where the results of the t1-volume-* pipeline are stored) and as the output folder containing the results in a CAPS hierarchy.
• group_id is the id of the group that is associated to the DARTEL template that you had created when running the t1-volume-* pipeline.

Pipeline options:

• -pet: type of PET image to process. Possible values are fdg and av45. Default value is fdg.
• -smooth: a list of integers specifying the different isomorphic full width at half maximum (fwhm) in millimeters to smooth the image. Default value is: 0, 8 (both without smoothing and with an isomorphic smoothing of 8 mm)
• -pvc_fwhm: TSV file containing the fwhm_x, fwhm_y and fwhm_z of the PSF for each PET image. More explanation below.

Partial volume correction

To correct for partial volume effects, the pipeline uses the region-based voxel-wise (RBV) correction implemented in the PETPVC toolbox. You need to specify in a TSV file the full width at half maximum (FWHM), in millimeters, of the point spread function (PSF) associated with your data, in the x, y and z directions. For instance, if the FWHM of the PSF associated with your first image is 8 mm along the x axis, 9 mm along the y axis, and 10 mm along z axis, the first row of your TSV file will look like this:

participant_id    session_id     fwhm_x    fwhm_y    fwhm_z
sub-CLNC0001      ses-M00        8         9         10
sub-CLNC0002      ses-M00        7         6         5
sub-CLNC0003      ses-M00        6         6         6


Note

The arguments common to all Clinica pipelines are described in Interacting with clinica.

Tip

Do not hesitate to type pipeline --help to see the full list of parameters.

## Outputs¶

Results are stored in the following folder of the CAPS hierarchy: subjects/sub-<participant_label>/ses-<session_label>/pet/preprocessing.

The main output files are:

• <source_file>_space-T1w[_pvc-rbv]_pet.nii.gz: PET image registered into the T1w native space.

• <source_file>_space-Ixi549Space[_pvc-rbv]_suvr-<label>_mask-brain[_fwhm-<X>mm]_pet.nii.gz: standard uptake value ratio (SUVR) PET image in MNI space, masked to keep only the brain, and optionally smoothed.

• atlas_statistics/<source_file>_space-<space>[_pvc-rbv]_suvr-<label>_statistics.tsv: TSV files summarizing the regional statistics on the labelled atlas <space>.

Note

The [pvc-rbv] label indicates whether the PET image has undergone partial value correction (region-based voxel-wise method) or not.

The full list of output files from the pet-volume pipeline can be found in the The ClinicA Processed Structure (CAPS) Specification.

## Describing this pipeline in your paper¶

Example of paragraph:

Theses results have been obtained using the pet-volume pipeline of Clinica. This pipeline first performs intra-subject registration of the PET image into the space of the subject’s T1-weighted MRI image using SPM. [The PET image is corrected for partial volume effects using the PETPVC toolbox.] The PET image is then spatially normalized into MNI space using the DARTEL deformation model of SPM, and intensity normalized using the average PET uptake in a reference region ([pons | pons + cerebellum]). Finally, the PET image is parcellated into anatomical regions based on an atlas, and average values are computed within each region.