aDWI-BIDS: an extension to the brain imaging data structure for advanced diffusion weighted imaging

• DOI: 10.48550/arxiv.2103.14485
• Publication Date: 2021-01-01
• Authors: Gholam, James; Szczepankiewicz, ...; Tax, Chantal M. W.; Mueller, Lars; Kopanoglu, Emre; Nilsson, Markus; Aja-Fernandez, Sa...; Griffin, Matt; Jones, Derek K.; Beltrachini, Leandro
• Keywords: 03 medical and health sciences; 0302 clinical medicine; Image and Video Processing (eess.IV); FOS: Electrical engineering, electronic engineering, information engineering; FOS: Physical sciences; Medical Physics (physics.med-ph); Electrical Engineering and Systems Science - Image and Video Processing; Physics - Medical Physics

Diffusion weighted imaging techniques permit us to infer microstructural detail in biological tissue in vivo and noninvasively. Modern sequences are based on advanced diffusion encoding schemes, allowing probing of more revealing measures of tissue microstructure than the standard apparent diffusion coefficient or fractional anisotropy. Though these methods may result in faster or more revealing acquisitions, they generally demand prior knowledge of sequence-specific parameters for which there is no accepted sharing standard. Here, we present a metadata labelling scheme suitable for the needs of developers and users within the diffusion neuroimaging community alike: a lightweight, unambiguous parametric map relaying acqusition parameters. This extensible scheme supports a wide spectrum of diffusion encoding methods, from single diffusion encoding to highly complex sequences involving arbitrary gradient waveforms. Built under the brain imaging data structure (BIDS), it allows storage of advanced diffusion MRI data comprehensively alongside any other neuroimaging information, facilitating processing pipelines and multimodal analyses. We illustrate the usefulness of this BIDS-extension with a range of example data, and discuss the extension's impact on pre- and post-processing software.