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genfi-to-bids – Conversion of the GENFI to BIDS

Current Data Freeze versions processed by the converter

Currently, the converter supports only GENFI Data Freeze 6 (DF6) and Data Freeze 7 (DF7) imaging and clinical data. Support for Data Freeze 8 (DF8) is planned for the next release.

Description reproduced from the GENFI webpage

The Genetic Frontotemporal dementia Initiative (GENFI) is a group of research centres across Europe and Canada with expertise in familial FTD, and is co-ordinated by Professor Jonathan Rohrer at University College London. GENFI is the largest genetic FTD consortium to date and currently consists of sites across the UK, Netherlands, Belgium, France, Spain, Portugal, Italy, Germany, Sweden, Denmark, Finland and Canada. The aim of the study is to understand more about genetic FTD, particularly in those who have mutations in the progranulin (GRN), microtubule-associated protein tau (MAPT) and chromosome 9 open reading frame 72 (C9orf72) genes. GENFI investigates both people who have developed symptoms and also people who have a risk of developing symptoms in the future because they carry an abnormal genetic mutation. By studying these individuals who are destined to develop the disease later in life we can understand the development from the very earliest changes. The key objectives of GENFI are therefore to develop markers which help identify the disease at its earliest stage as well as markers that allow the progression of the disease to be tracked. We are now collaborating closely with other similar studies around the world through the FTD Prevention Initiative. Through this worldwide initiative we are working with pharmaceutical companies to help design clinical trials for genetic FTD.

Dependencies

If you only installed the core of Clinica, this pipeline needs the installation of the dcm2niix DICOM to NIfTI converter.

Supported modalities

Please note that this converter currently processes the following modalities :

  • T1W
  • T2W
  • DWI
  • Fieldmaps
  • rsfMRI

Downloading GENFI

To download GENFI in a way that you can convert it, you need to make sure of two things: - Only select the "simplify downloaded archive structure" in download data options. - Select only "DICOM" in "Select Image Data" section "Scans Format".

Using the converter

The converter can be run with the following command line:

clinica convert genfi-to-bids [OPTIONS] DATASET_DIRECTORY BIDS_DIRECTORY

where:

  • DATASET_DIRECTORY is the path to the original GENFI imaging directory, whose content should look like:

    DATASET_DIRECTORY
├── C9ORF001-01-MR00
│   ├── 1
│   ├── 11
│   ├── 12
│   └── 13
├── C9ORF001-11
│   ├── 1
│   ├── 2
│   ├── 4
│   ├── 5
│   ├── 6
│   ├── 7
│   ├── 8
│   └── 9
└── GRN001-01-MR00
    ├── 1
    ├── 10
    ├── 8
    └── 9

  • BIDS_DIRECTORY is the path to the output directory where the BIDS-converted version of GENFI will be stored, whose content should look like:

    BIDS_DIRECTORY
├── dataset_description.json
├── participants.tsv
├── README
├── sub-C9ORF001
│   ├── ses-01
│   │   ├── anat
│   │   │   ├── sub-C9ORF001_ses-01_run-01_T1w.json
│   │   │   ├── sub-C9ORF001_ses-01_run-01_T1w.nii.gz
│   │   │   ├── ...
│   │   ├── dwi
│   │   │   ├── sub-C9ORF001_ses-01_run-01_dwi.bval
│   │   │   ├── sub-C9ORF001_ses-01_run-01_dwi.bvec
│   │   │   ├── ...
│   │   ├── func
│   │   │   ├── sub-C9ORF001_ses-01_task-rest_run-01_bold.json
│   │   │   └── sub-C9ORF001_ses-01_task-rest_run-01_bold.nii.gz
│   │   └── sub-C9ORF001_ses-01_scans.tsv
│   ├── ses-11
│   │   ├── ...
│   └── sub-C9ORF001_sessions.tsv
├── sub-GRN001
│   ├── ses-01
│   │   ├── ...
│   └── sub-GRN001_sessions.tsv
└── ...

    Sessions respect the naming convention used in GENFI clinical data. In particular, for ses-XY, X represents the GENFI phase, and Y represents the visit number.

Data freeze version detection

The data freeze version is automatically detected by the converter.

  • OPTIONS:
    • --clinical-data-dir/-cdd is the path to the directory containing the clinical data files (tabular .xlsx files). These files are distinct from the clinical data fields, which correspond to the column names defined within the tabular files. Allows the user to automatically extract mandatory clinical data fields from the tabular files and add them to participants.tsv and sessions.tsv. Mandatory clinical data fields are the following :
      • For participants.tsv : blinded_code, blinded_family, blinded_site, gender.
      • For sessions.tsv : age_at_visit, date_of_assessment, diagnosis, education, ftld-cdr-nm-global, genetic_group, genetic_status_1, genetic_status_2, visit.
        All the remaining clinical data fields are optional and automatically added through the use of the -full flag.
    • --clinical-data-txt/-cdt is a txt file containing the additional clinical data fields the user wants. The available data can be retrieved from the specification file full_specs.csv, located in the Clinica installation directory at :
      clinica_path/clinica/converters/genfi_to_bids/specifications/full_specs.csv.
      The .txt file should be written one field per line such as in the example below : 
      diagnosis_1
diagnosis_1.1
diagnosis_2
diagnosis_3
diagnosis_4
diagnosis_5
diagnosis_child1
diagnosis_child2
digit_symbol
disinhibition
dob
drc_qc
drug_history
...
      If the -full flag is used, this option is considered redundant and will be ignored.
    • -gif allows the user to add all the clinical data fields related to the imaging volumes (GIF, Geodesic Information Flow) to session.tsv. The added clinical data fields also include the mandatory ones.
    • -full allows the user to add all clinical data fields (mandatory, GIF, and the remaining optional ones) to sessions.tsv.

Note

In order to improve the readability, the BIDS subject ID is the genetic group concatenated with the original GENFI ID and is defined as follows:

sub-GRN/C9ORF/MAPT+ original numerical ID of the subject

Example

If the original subject ID is 0001, the final BIDS ID will be sub-GRN0001.

Citing this converter in your paper

Example of paragraph:

The GENFI data have been curated and converted to the Brain Imaging Data Structure (BIDS) format [Gorgolewski et al., 2016] using Clinica [Routier et al.; Samper-González et al., 2018].

Tip

Easily access the papers cited on this page on Zotero.

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