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PET_Volume

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Alexandre Routier edited this page Jul 22, 2020 · 9 revisions

pet-volume – Volume-based processing of PET images

This pipeline performs several 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 [Thomas et al., 2016];
  • inter-subject spatial normalization of the PET image into MNI space based on the DARTEL deformation model of SPM [Ashburner, 2007];
  • 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 pipeline on your T1-weighted MR images.

Dependencies

  • If you only installed the core of Clinica, this pipeline needs the installation of SPM12 and CAT12. You can find how to install these software packages on the third-party page.

  • If you want to apply partial volume correction (PVC) on your PET data, you will need to install PETPVC 1.2.4, which depends on ITK 4. More information on the third-party 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_tracer: 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.

!!! note "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 clinica run pet-volume --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) specifications](../../CAPS/Specifications/#pet-volume-volume-based-processing-of-pet-images).

Going further

Describing this pipeline in your paper

!!! cite "Example of paragraph:" Theses results have been obtained using the pet-volume pipeline of Clinica [Routier et al; Samper et al., 2018]. 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 [Thomas et al., 2016]. 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 average PET uptake is computed for a set of regions obtained from different atlases in MNI space [Tzourio-Mazoyer et al., 2002, 2015; Joliot et al., 2015; Hammers et al., 2003; Gousias et al., 2008; Shattuck et al., 2008; CAT12].

!!! tip Easily access the papers cited on this page on Zotero.

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