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nifd-to-bids – Conversion of Neuroimaging in Frontotemporal Dementia (NIFD) to BIDS

Description reproduced from the NIFD's LONI Image & Data Archive (IDA) webpage

NIFD is the nickname for the frontotemporal lobar degeneration neuroimaging initiative (FTLDNI, AG032306), which was funded by the NIA and NINDS to characterize longitudinal clinical and imaging changes in FTLD. The imaging and clinical methods are the same for NIFD and for the 4-Repeat Tauopathy Neuroimaging Initiative (4RTNI), which is also available for download from LONI. Controls for NIFD are the same controls as those collected for 4RTNI.

Dependencies

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

Downloading NIFD

In order to use the converter, you will need to download both the images and the clinical data for NIFD.

First, you will have to register to the LONI Image & Data Archive (IDA), a secure research data repository, through the submission of an online application form. Once your access is granted, head to the NIFD projects's page and login using your credentials.

Downloading the imaging data

To download the imaging data:

  1. Press Download and select Image collections in the menubar below.

  2. Select the Advanced Search tab and configure the appropriate search criteria for your collection. Please, ensure only NIFD is selected under the PROJECT/PHASE section of the form. MRI should be selected in the Modality section by default. Select PET and leave the selector to OR to download PET imaging data in addition to MRI.

  3. Once all search criteria have been selected, press SEARCH at the bottom of the form. Your search results should be presented in a new tab named Advanced Search Results.

  4. Select the desired subjects and scans using the tick boxes displayed in the form or press Select All in the top right corner. Press Add To Collection to create a new collection from your selection and give it a name. This name will be used as a stem for future downloads.

  5. Select the Data Collections tab and find your collection within the My Collections tree on the left-hand side.

  6. Click the CSV button to download the collection metadata in tabular form.

  7. Select the whole collection by ticking All and press Advanced Download. A download summary should be displayed with the name of the collection, the number of items selected and a dropdown menu to select different groups of file. Depending on the size of the collection, it is advised to download the collection in 5 or 10 files instead of 1 as default.

  8. Upon completion of the download process, create a new folder and move the collection metadata file as well as the content of the archive(s) into it.

Downloading the clinical data

To download the clinical data, press Download, select Study Data, tick NIFD Clinical Data and press download. Once downloaded, you may move this file to the same location where the imaging data are stored or somewhere else.

Supported modalities

Currently, the modalities supported by our converter are:

  • T1-weighted MRI
  • T2-weighted FLAIR MRI
  • Fluorodeoxyglucose (FDG) PET
  • Pittsburgh compound B (PiB) PET
  • Clinical data and survey (MMSE, CDR, ...)

Using the converter

The converter can be run with the following command line:

clinica convert nifd-to-bids [OPTIONS] DATASET_DIRECTORY CLINICAL_DATA_DIRECTORY BIDS_DIRECTORY

where:

  • DATASET_DIRECTORY is the path to the original NIFD images' directory;
  • CLINICAL_DATA_DIRECTORY is the path to the directory where the following clinical data files are located: NIFD_Clinical_Data_2017_final_updated.xlsx, DataDictionary_NIFD_2017.10.18.xlsx and idaSearch_all.csv;
  • BIDS_DIRECTORY is the path to the output directory, where the BIDS-converted version of NIFD will be stored.

Citing this converter in your paper

Example of paragraph:

The NIFD data have been curated and converted to the Brain Imaging Data Structure (BIDS) format [Gorgolewski et al., 2016] using Clinica [Routier et al., 2021].

Tip

Easily access the papers cited on this page on Zotero.

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