Page Last Updated: October 10, 2025
Magnetic Resonance Spectroscopy (MRS)🔗
Magnetic Resonance Spectroscopy (MRS) provides measures of biochemicals involved in neuronal metabolism, neurotransmission, and oxidative stress. These measures enable researchers to interrogate biochemical mechanisms underlying the structural, functional, and behavioral trajectories. HBCD is the first study of this magnitude to include MRS in a comprehensive pediatric neuroimaging protocol through the development of Integrated Short-TE and Hadamard Multi-Sequence, or ISTHMUS (Hui et al., 2024).
Release Data🔗
MRS release data include file-based (raw and processed data files in modality-specific formats) data. See the Data Structure Overview for a full explanation of these data types.
- Raw BIDS stored under subject- and session-specific
mrs/folders - Processed derivatives generated by the OSPREY-BIDS pipeline
MRS files include metabolite (*_svs.nii.gz) and water reference (*_ref.nii.gz) data acquired via short-echo-time (TE = 35 ms; acq-shortTE) and HERCULES (spectral-edited, TE = 80 ms; acq-hercules). The JSON sidecar files include the dimensions of the NIfTI-MRS data array, holding different coil elements in dimension 5 and different transients in dimension 6. See BIDS Conversion Procedures.
hbcd/
|__ rawdata/
|__ sub-{ID}/
|__ ses-{V0X}/
|__ mrs/
|__ sub-{ID}_ses-{V0X}_acq-shortTE_run-{X}_svs.nii.gz (+JSON)
|__ sub-{ID}_ses-{V0X}_acq-shortTE_run-{X}_ref.nii.gz (+JSON)
|__ sub-{ID}_ses-{V0X}_acq-hercules_run-{X}_svs.nii.gz (+JSON)
|__ sub-{ID}_ses-{V0X}_acq-hercules_run-{X}_ref.nii.gz (+JSON)
Only the HERCULES/ file tree is displayed below. The unedited/ files generally follow similar naming conventions, with some exceptions (e.g., the BIDS field acq-shortTE is used instead of acq-hercules).
hbcd/
|__ derivatives/
|__ osprey/
|__ sub-{ID}/
|__ ses-{V0X}/
|__ HERCULES/
| |__ PreOspreyLocalizerReg/
| | |__ figures/
| | |__ <aal|c1|c2|c3>reference_seg_aligned_to_localizer.nii.gz
| | |__ reference_<img|seg>_aligned_to_localizer.nii.gz
| | |__ registration_summary.json
| | |__ transform_mat.npy
| | |__ readme.txt
| |
| |__ QuantifyResults/ (ALL +JSON)
| | |__ <diff1|diff2|sum>_AlphaCorrWaterScaledGroupNormed_Voxel_1_Basis_1.tsv
| | |__ <diff1|diff2|sum>_AlphaCorrWaterScaled_Voxel_1_Basis_1.tsv
| | |__ <diff1|diff2|sum>_CSFWaterScaled_Voxel_1_Basis_1.tsv
| | |__ <diff1|diff2|sum>_TissCorrWaterScaled_Voxel_1_Basis_1.tsv
| | |__ <diff1|diff2|sum>_amplMets_Voxel_1_Basis_1.tsv
| | |__ <diff1|diff2|sum>_rawWaterScaled_Voxel_1_Basis_1.tsv
| | |__ <diff1|diff2|sum>_tCr_Voxel_1_Basis_1.tsv
| |
| |__ Reports/
| | |__ reportFigures/
| | |__ sub-{ID}-report.html
| |
| |__ SegMaps/
| | |__ TissueFractions_Voxel_1.tsv (+JSON)
| | |__ sub-{ID}_ses-{V0X}_acq-hercules_svs.nii_space-scanner_Voxel-1_label-CSF.nii.gz
| | |__ sub-{ID}_ses-{V0X}_acq-hercules_svs.nii_space-scanner_Voxel-1_label-GM.nii.gz
| | |__ sub-{ID}_ses-{V0X}_acq-hercules_svs.nii_space-scanner_Voxel-1_label-Tha.nii.gz
| | |__ sub-{ID}_ses-{V0X}_acq-hercules_svs.nii_space-scanner_Voxel-1_label-WM.nii.gz
| |
| |__ VoxelMasks/
| | |__ sub-{ID}_ses-{V0X}_acq-hercules_svs_space-scanner_mask.nii.gz
| |
| |__ LogFile.txt
| |__ QM_processed_spectra.tsv (+JSON)
| |__ SummaryMRSinMRS.md
| |__ subject_names_and_excluded.tsv (+JSON)
| |__ wrapper_settings.mat (+JSON)
|
|__ unedited/
Data Acquisition🔗
The MRS acquisition protocol was optimized to maximize signal-to-noise across multiple low-concentration metabolites while maintaining an acquisition time (TA) under 9 minutes. The MRS acquisition centers on a single voxel Point-RESolved Spectroscopy (PRESS) (Bottomley, 1987) localization (30×23×23 mm^3) in the bilateral thalamus, with SVS localizer acquisitions to define the ROI. The ISTHMUS sequence incorporates a short TE (35 ms) unedited block at the beginning of the sequence for optimal measurement of high concentration metabolites, including N-acetylasparte, followed by an advanced Hadamard encoded spectral editing scheme (Oeltzschner et al., 2019) to derive reliable and reproducible measures of the low-concentration metabolites.
The primary metabolites measured for HBCD include:
- N-acetylaspartate (NAA): a marker of neuronal mitochondrial metabolism
- Glutamate and γ-aminobutyric acid (GABA): the principal excitatory and inhibitory neurotransmitters
- Glutathione (GSH): the most abundant antioxidant involved in protection against reactive oxygen species in the human brain
Additional metabolites measured include NAA, lactate, ascorbate, creatine, myo-inositol, glutamine, and total choline (Oeltzschner et al., 2019).
One limitation to the incorporation of MRS into human connectome studies is proper control for scanner drift. Because MRS relies on the frequency of the measured signals, uncorrected frequency drift during data acquisition is very detrimental to data quality, as it changes the contribution of coedited signals as well as editing efficiency (Harris et al., 2014). To mitigate drift, an innovative approach was taken to incorporate interleaved water referencing (Edden et al., 2016) for real-time frequency correction, implemented on the Philips platform at the outset of HBCD, and in Y3 for Siemens and GE.
Data Processing🔗
HBCD MRS data are processed with a customized automated pipeline based on OSPREY (Oeltzschner et al., 2020; Zöllner et al., 2023) - see the OSPREY-BIDS documentation. Derivatives include quality control metrics and metabolite estimates (ratios to creatine and water, with and without tissue correction). See the list of OSPREY derivatives included in the release above.
References🔗
Bottomley, P. A. (1987). Spatial localization in NMR spectroscopy in vivo. Annals of the New York Academy of Sciences, 508(1), 333–348. https://doi.org/10.1111/j.1749-6632.1987.tb32915.x
Edden, R. A. E., Oeltzschner, G., Harris, A. D., Puts, N. A. J., Chan, K. L., Boer, V. O., Schär, M., & Barker, P. B. (2016). Prospective frequency correction for macromolecule-suppressed GABA editing at 3T. Journal of Magnetic Resonance Imaging, 44(6), 1474–1482.. https://doi.org/10.1002/jmri.25304
Harris, A. D., Glaubitz, B., Near, J., John Evans, C., Puts, N. A. J., Schmidt-Wilcke, T., Tegenthoff, M., Barker, P. B., & Edden, R. A. E. (2014). Impact of frequency drift on gamma-aminobutyric acid-edited MR spectroscopy. Magnetic Resonance in Medicine, 72(4), 941–948. https://doi.org/10.1002/mrm.25009
Hui, S. C. N., Murali-Manohar, S., Zöllner, H. J., Hupfeld, K. E., Davies-Jenkins, C. W., Gudmundson, A. T., Song, Y., Yedavalli, V., Wisnowski, J. L., Gagoski, B., Oeltzschner, G., & Edden, R. A. E. (2024). Integrated Short-TE and Hadamard-edited Multi-Sequence (ISTHMUS) for advanced MRS. Journal of Neuroscience Methods, 409(110206), 110206. https://doi.org/10.1016/j.jneumeth.2024.110206
Oeltzschner, G., Saleh, M. G., Rimbault, D., Mikkelsen, M., Chan, K. L., Puts, N. A. J., & Edden, R. A. E. (2019). Advanced Hadamard-encoded editing of seven low-concentration brain metabolites: Principles of HERCULES. NeuroImage, 185, 181–190. https://doi.org/10.1016/j.neuroimage.2018.10.002
Oeltzschner, G., Zöllner, H. J., Hui, S. C. N., Mikkelsen, M., Saleh, M. G., Tapper, S., & Edden, R. A. E. (2020). Osprey: Open-source processing, reconstruction & estimation of magnetic resonance spectroscopy data. Journal of Neuroscience Methods, 343(108827), 108827. https://doi.org/10.1016/j.jneumeth.2020.108827
Träber, F., Block, W., Lamerichs, R., Gieseke, J., & Schild, H. H. (2004). 1H metabolite relaxation times at 3.0 tesla: Measurements of T1 and T2 values in normal brain and determination of regional differences in transverse relaxation. Journal of Magnetic Resonance Imaging, 19(5), 537–545. https://doi.org/10.1002/jmri.20053
Zöllner, H. J., Davies-Jenkins, C. W., Lee, E. G., Hendrickson, T. J., Clarke, W. T., Edden, R. A. E., Wisnowski, J. L., Gudmundson, A. T., & Oeltzschner, G. (2023). Continuous automated analysis workflow for MRS studies. Journal of Medical Systems, 47(1), 69. https://doi.org/10.1007/s10916-023-01969-6