Linewidth-related bias in modelled concentration estimates from GABA-edited 1H-MRS

J-difference-edited MRS is widely used to study GABA in the human brain. Editing for low-concentration target molecules (such as GABA) typically exhibits lower signal-to-noise ratio (SNR) than conventional non-edited MRS, varying with acquisition region, volume and duration. Moreover, spectral lineshape may be influenced by age-, pathology-, or brain-region-specific effects of metabolite T2, or by task-related blood-oxygen level dependent (BOLD) changes in functional MRS contexts. Differences in both SNR and lineshape may have systematic effects on concentration estimates derived from spectral modelling. The present study characterises the impact of lineshape and SNR on GABA+ estimates from different modelling algorithms: FSL-MRS, Gannet, LCModel, Osprey, spant and Tarquin. Publicly available multi-site GABA-edited data (222 healthy subjects from 20 sites; conventional MEGA-PRESS editing; TE = 68 ms) were pre-processed with a standardised pipeline, then filtered to apply controlled levels of Lorentzian and Gaussian linebroadening and SNR reduction. Increased Lorentzian linewidth was associated with a 2-5% decrease in GABA+ estimates per Hz, observed consistently (albeit to varying degrees) across datasets and most algorithms. Weaker, often opposing effects were observed for Gaussian linebroadening. Variations are likely caused by differing baseline parametrization and lineshape constraints between models. Effects of linewidth on other metabolites (e.g., Glx and tCr) varied, suggesting that a linewidth confound may persist after scaling to an internal reference. These findings indicate a potentially significant confound for studies where linewidth may differ systematically between groups or experimental conditions, e.g. due to T2 differences between brain regions, age, or pathology, or varying T2* due to BOLD-related changes. We conclude that linewidth effects need to be rigorously considered during experimental design and data processing, for example by incorporating linewidth into statistical analysis of modelling outcomes or development of appropriate lineshape matching algorithms. Highlights ![Graphical Abstract][1] Graphical Abstract To assess the degree to which aspects of linewidth, lineshape and SNR may confound GABA+ estimates, a collection of in-vivo datasets were quantified with six modelling algorithms, with linebroadening and SNR varied experimentally. Most algorithms showed a strong association between GABA+ estimate and Lorentzian linebroadening (2-5% decrease per Hz), with weaker effects for Gaussian broadening. This indicates a potentially significant confound in cases of differing relaxation parameters between groups or experimental conditions. ### Competing Interest Statement The authors have declared no competing interest. * BOLD : blood oxygen level dependent Cho : Choline Cr : Creatine diff difference (edited) spectrum FD : frequency domain FID : Free Induction Decay (time-domain MRS signal) FWHM : linewidth full width at half maximum G(+)[MBR] : Synthetic spectral models, see section 2.3 GABA : γ-aminobutyric acid GABA+ : total edited signal at 3 ppm; GABA with underlying coedited signals Gln : Glutamine Glu : Glutamate GPC : glycerophosphorylcholine GSH : glutathione HLSVD : Hankel-Lanczos singular value decomposition i.u. : institutional units Lac : Lactate LBgauss : Gaussian linebroadening factor LBlorentz : Lorentzian linebroadening factor LCM : linear combination modelling LLWF : Linear line-width factor, see section 2.5 MAD : Median Absolute Deviation MAE : Mean Absolute Error MEGA-PRESS : Mescher–Garwood point-resolved spectroscopy mI : myo-inositol MRS : Magnetic Resonance Spectroscopy MSD : Mean Signed Difference NAA : N-acetyl aspartate NAAdiff : NAA measured from the difference spectrum NAAG : n-acetylaspartylglutamate PCh : phosphorylcholine PCr : phosphocreatine pholm : Holm-Bonferroni adjusted p-value punc : Uncorrected p-value R1-3 : adopted rejection criteria; see methods section 2.1.2 SD : Standard Deviation SNR : Signal-to-Noise Ratio T2* : Effective transverse relaxation rate tCroff : total creatine measured from the edit-OFF sub-spectrum TD : time domain VPC : Variance Partition Coefficients [1]: pending:yes