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NIfTI‐MRS : A standard data format for magnetic resonance spectroscopy
Author(s) -
Clarke William T.,
Bell Tiffany K.,
Emir Uzay E.,
Mikkelsen Mark,
Oeltzschner Georg,
Shamaei Amirmohammad,
Soher Brian J.,
Wilson Martin
Publication year - 2022
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.29418
Subject(s) - computer science , file format , dicom , standardization , data sharing , image file formats , metadata , interoperability , software , data file , documentation , data dictionary , neuroinformatics , health informatics tools , workflow , data format , information retrieval , world wide web , database , data science , informatics , computer hardware , programming language , artificial intelligence , operating system , medicine , alternative medicine , pathology , electrical engineering , image (mathematics) , engineering
Purpose Multiple data formats in the MRS community currently hinder data sharing and integration. NIfTI‐MRS is proposed as a standard spectroscopy data format, implemented as an extension to the Neuroimaging informatics technology initiative (NIfTI) format. This standardized format can facilitate data sharing and algorithm development as well as ease integration of MRS analysis alongside other imaging modalities. Methods A file format using the NIfTI header extension framework incorporates essential spectroscopic metadata and additional encoding dimensions. A detailed description of the specification is provided. An open‐source command‐line conversion program is implemented to convert single‐voxel and spectroscopic imaging data to NIfTI‐MRS. Visualization of data in NIfTI‐MRS is provided by development of a dedicated plugin for FSLeyes, the FMRIB Software Library (FSL) image viewer. Results Online documentation and 10 example datasets in the proposed format are provided. Code examples of NIfTI‐MRS readers are implemented in common programming languages. Conversion software, spec2nii , currently converts 14 formats where data is stored in image‐space to NIfTI‐MRS, including Digital Imaging and Communications in Medicine (DICOM) and vendor proprietary formats. Conclusion NIfTI‐MRS aims to solve issues arising from multiple data formats being used in the MRS community. Through a single conversion point, processing and analysis of MRS data are simplified, thereby lowering the barrier to use of MRS. Furthermore, it can serve as the basis for open data sharing, collaboration, and interoperability of analysis programs. Greater standardization and harmonization become possible. By aligning with the dominant format in neuroimaging, NIfTI‐MRS enables the use of mature tools present in the imaging community, demonstrated in this work by using a dedicated imaging tool, FSLeyes, for visualization.