A program for multi-format conversion of in vivo MRS to the NIfTI-MRS format.
This program was inspired by the imaging DICOM to NIfTI converter dcm2niix developed by Chris Rorden. All MRS(I) orientations are tested with images converted using dcm2niix. I consider the combination of images converted using dcm2niix and displayed in FSLeyes the de facto standard.
If you use spec2nii or the NIfTI-MRS format in your work please cite:
`Clarke WT, Bell TK, Emir UE, Mikkelsen M, Oeltzschner G, Shamaei A, Soher BJ, Wilson M. NIfTI-MRS: A standard data format for magnetic resonance spectroscopy. Magn Reson Med. 2022. doi: 10.1002/mrm.29418.`
Visualisation of MRS data converted by spec2nii to NIfTI-MRS can be carried out with a recent (>0.31.0) version of FSLeyes. A FSLeyes plugin for NIfTI-MRS is now available:
- Gitlab,
conda install -c conda-forge fsleyes-plugin-mrs,pip install fsleyes-plugin-mrs.
conda install -c conda-forge spec2nii
or
pip install spec2nii
Miniconda can be installed by following the instructions on the Conda website. To create a suitable environment run the following three commands after installing Conda.
conda create -c conda-forge -n my_env python=3.8
conda activate my_env
conda install -c conda-forge spec2nii
This table lists the currently supported formats. I have very limited experience with Philips and GE formats. Please get in touch if you are willing to help add to this list and/or supply validation data.
| Format | File extension | SVS | MRSI | Automatic orientation |
|---|---|---|---|---|
| Siemens Twix | .dat | Yes | † | Yes |
| Siemens DICOM | .ima / .dcm | Yes | Yes | Yes |
| Siemens RDA | .rda | Yes | Yes | Yes |
| Philips | .SPAR/.SDAT | Yes | No | Yes |
| Philips | .data/.list | Yes | No | Yes |
| Philips DICOM | .dcm | Yes | No | Yes |
| GE | .7 (pfile) | Yes | Yes | Yes (WIP) |
| UIH DICOM | .dcm | Yes | Yes | Yes |
| Bruker | 2dseq | Yes | Yes | Yes |
| Bruker | fid | Yes | Yes | Yes (WIP) |
| Varian | fid | Yes | No | No (WIP) |
| LCModel | .RAW | Yes | No | No |
| jMRUI | .txt | Yes | No | No |
| jMRUI | .mrui | Yes | No | No |
| ASCII | .txt | Yes | No | No |
† Partial handling - see section on Twix pathway for MRSI handling.
spec2nii is called on the command line, and the conversion file type is specified with a subcommand.
The -f and -o options specify output file name and directory respectively for all formats.
If -j is specified the NIfTI MRS header extension will also be generated as a JSON side car file.
By default, spec2nii generates NIfTI files using the NIfTI-2 header format. Use the --nifti1 option to generate files using the NIfTI-1 format.
Manual overrides can be provided for incorrectly interpreted required header fields, namely SpectrometerFrequency, ResonantNucleus and dwell-time, by using the --override_frequency, --override_nucleus, and --override_dwelltime command line options.
spec2nii auto FILE will attempt an automatic conversion of the following formats: Twix, RDA, SPAR/SDAT, GE p-file, DICOM. Note that many features of the individual converters are not implemented in this automatic pathway. This feature should be regarded as somewhat experimental. For finer-grained control see the specific subcommands listed below.
Call spec2nii twix -v FILE to view a list of contained MDH flags. -m can be used to specify which multi-raid file to convert if used on VE data.
Call with the -e flag to specify which MDH flag to convert. e.g.
spec2nii twix -e image FILE
Twix format loop variables (e.g. Ave or ida) can be assigned to specific NIfTI dimensions using the -d{5,6,7} command line options. NIfTI MRS dimension tags (e.g. DIM_COIL) can be specified using the -t{5,6,7} command line options.
As spec2nii is not a reconstruction program, it cannot convert MRSI data. Far too little information is held in the twix headers to reconstruct arbitrary k,t-space data. However, if passed a file containing MRSI data spec2nii will attempt to create an empty NIfTI-MRS file with the correct orientation information, data shape, and header information. This empty file can then have data inserted from an offline reconstruction routine.
spec2nii dicom DCM_FILE_or_DIR
NIfTI MRS dimension tags (e.g. DIM_COIL) can be specified using the -t command line argument.
spec2nii rda RDA_FILE
Compatible with CSI and SVS data. Validated to be the same data and orientation information as DICOM output on VE baselines.
spec2nii uih DCM_FILE_or_DIR
NIfTI MRS dimension tags (e.g. DIM_COIL) can be specified using the -t command line argument.
spec2nii ge FILE
spec2nii philips SDAT_FILE SPAR_FILE
Two optional arguments are available for the SPAR/SDAT pathway:
-t/--tagsallows the user to specify the dimension tags for each of the higher dimensions (up to three).-s/--shapeallows the user to perform Numpy style reshaping of multiple transients. By default (without specifying a shape) all transients will be listed in a single 5th dimension.
Must be provided along side a matching SPAR file.
spec2nii philips_dl DATA_FILE LIST_FILE SPAR_FILE
spec2nii philips_dcm DCM_FILE_or_DIR
NIfTI MRS dimension tags (e.g. DIM_COIL) can be specified using the -t command line argument.
Generates separate reference file if present.
Both classic and enhanced DICOM is handled. Well tested on the vendors' own PRESS and MEGA-PRESS sequence.
spec2nii bruker -m 2DSEQ 2DSEQ_FILE_or_DIR
spec2nii bruker -m FID FID_FILE_or_DIR
Use the -d option to dump the header files (method and acqp for fid, visu_pars for 2dseq) into the header extension.
Additional filters can be added by defining additional queries using the -q flag.
Bruker conversion is powered by the BrukerAPI package written by Tomas Psorn.
spec2nii varian /path/to/fid.fid
where fid.fid is a Varian fid directory containing a fid and procpar file.
Use the -d option to dump the procpar header file contents into the header extension.
Use the -t option to set an alternative dimension tag for the 6th dimension (default = DIM_DYN).
Note that the varian file format is very flexible -- the binary fid itself essentially is a long 2D list of (complex_points * everything_else), and the current code makes several significant assumptions about how that should be interpreted and reshaped.
In particular, if you are using a sequence derived from something different to either spuls, s2pul, press, or steam, it is quite likely that this will not work. Edit varian_importer.py and add cases based on your seqfil as appropriate.
It is assumed that the comment parameter should be the patient's name.
(Further bells and whistles pending; Written by Jack J. Miller [email protected])
Conversion from processed formats. All take an optional -a argument to specify a text file containing a 4x4 affine matrix specifying orientation information.
The text format requires additional information, namely imaging frequency in MHz and bandwidth in hertz.
spec2nii raw -a AFFINE_FILE FILE
spec2nii jmrui -a AFFINE_FILE FILE
spec2nii text -a AFFINE_FILE -i imaging_freq -b bandwidth FILE
Anonymise the NIfTI-MRS file. All standard-defined keys marked as sensitive will be removed. User defined parameters marked as private_ will also be removed. Use the -v flag to view the removed header keys. The -r argument may be used (repeatedly) to remove additional keys from the header extension manually.
spec2nii anon FILE
Dump the NIfTI headers and header extension to Stdout.
spec2nii dump FILE
Produce a json file containing the header extension as a separate file from a NIfTI-MRS file.
spec2nii extract FILE
Overwrite the header extension in a NIfTI-MRS file using a separate json formatted file.
spec2nii insert FILE JSON_FILE
This program was written by Will Clarke, University of Oxford. Contributions to add new file formats or improve existing ones are very welcome. Please fork the repository and request changes using a merge (pull) request. I ask that test data and tests are included with any submission.
Particular thanks go to Tomáš Pšorn for contributing the Bruker interface, and to Jack Miller for the Varian interface.
Elements of the Varian reader come from NMR glue, if you use the varian components in your research please cite J.J. Helmus, C.P. Jaroniec, Nmrglue: An open source Python package for the analysis of multidimensional NMR data, J. Biomol. NMR 2013, 55, 355-367. doi: 10.1007/s10858-013-9718-x
Some GE test data comes from the BIG GABA dataset which was funded by NIH grant R01 EB016089. Please see Mikkelsen M et al. Big GABA: Edited MR spectroscopy at 24 research sites. NeuroImage 2017;159:32–45. doi: 10.1016/j.neuroimage.2017.07.021 for more information.