bioRxivNeurosciencePreprint
Improving magnetic resonance spectroscopy in the brainstem periaqueductal grey using spectral registration
Abstract
PurposeFunctional understanding of the periaqueductal grey (PAG), a clinically relevant brainstem region, can be advanced using proton magnetic resonance spectroscopy (1H-MRS). However, the PAGs small size and high levels of physiological noise are methodologically challenging. This study aimed to (1) improve 1H-MRS quality in the PAG using spectral registration for frequency and phase error correction, (2) investigate whether spectral registration is particularly useful in cases of greater head motion and (3) examine metabolite quantification using literature-based or individual-based water relaxation times. MethodsSpectra were acquired in 33 healthy volunteers (50.1 years, SD=17.19, 18 females) on a 3T Philipps MR system using a point-resolved spectroscopy sequence optimized with very selective saturation pulses (OVERPRESS) and voxel-based flip angle calibration (effective volume of interest size: 8.8x10.2x12.2 mm3). Spectra were fitted using LCModel and signal-to-noise ratios (SNR), N-acetylaspartate peak linewidths and Cramer-Rao lower bounds (CRLBs) were measured after spectral registration and after minimal frequency alignment. ResultsSpectral registration improved SNR by 5 % (p=0.026, median value post-correction: 18.0) and spectral linewidth by 23 % (p<0.001, 4.3 Hz), and reduced the metabolites CRLBs by 1-15 % (ps<0.026). Correlational analyses revealed smaller SNR improvements with greater head motion (p=0.010) recorded using a markerless motion tracking system. Higher metabolite concentrations were detected using individual-based compared to literature-based water relaxation times (ps<0.001). ConclusionThis study demonstrates high-quality 1H-MRS acquisition in the PAG using spectral registration. This shows promise for future 1H-MRS studies in the PAG and possibly also other clinically relevant brain regions with similar methodological challenges.
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Motion-Corrected Structural Realignment and Quantitative Voxel Targeting in Magnetic Resonance Spectroscopy
Cassia Low Manting, Atsushi Takahashi, … Eva‐Maria Ratai·Imaging NeurosciencePeer-reviewed·Jan 1, 2026
- Magnetic Resonance Spectroscopy Spectral Registration Using Deep Learning
David J. Ma, Yanting Yang, … Jia Guo·Journal of Magnetic Resonance ImagingPeer-reviewed·Jul 4, 2023
- Spatiospectral image processing workflow considerations for advanced MR spectroscopy of the brain
L. Y. Cai, S. N. Del Tufo, … B. A. Landman·bioRxiv·Sep 7, 2023
- ORYX-MRSI: A Fully-Automated Open-Source Software for Three-Dimensional Proton Magnetic Resonance Spectroscopic Imaging Data Analysis
Sevim Dincer Cengiz, Muhammed Yildirim, … Esin Öztürk-Işık·bioRxiv·Nov 12, 2021
- Quantitative metabolic reference for healthy human cerebrum derived from group averaged 9.4T 1H MRSI data
Andrew Martin Wright, Theresia Ziegs, A Henning·bioRxiv·Apr 4, 2024
- MRSIPrep: A Standardized Post-Quantification Framework for Preprocessing Whole-Brain Magnetic Resonance Spectroscopic Imaging
Federico Lucchetti, Edgar Céléreau, … Paul Klauser·bioRxiv·Sep 16, 2026