PT  - JOURNAL ARTICLE
AU  - Trinkle, Scott
AU  - Wildenberg, Gregg
AU  - Kasthuri, Narayanan
AU  - Rivière, Patrick La
AU  - Foxley, Sean
TI  - Model-free analysis in the spectral domain of postmortem mouse brain EPSI reveals inconsistencies with model-based analyses of the free induction decay
AID  - 10.1101/2022.02.24.481824
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.02.24.481824
4099  - http://biorxiv.org/content/early/2022/02/25/2022.02.24.481824.short
4100  - http://biorxiv.org/content/early/2022/02/25/2022.02.24.481824.full
AB  - Purpose Dysmyelinating disorders lead to abnormalities in myelin structure that produce detectable effects in an echo-planar spectroscopic imaging (EPSI) signal. To estimate the voxel-wise proportion of myelin, data are typically fit to compartmental models in the time domain. This work characterizes limitations in these models by comparing high-resolution water spectra measured in postmortem fixed mouse brains to spectra predicted from time-domain models fit to the same data, specifically by comparing spectra from control and shiverer mice, a model for dysmyelination.Methods Perfusion-fixed, resected control (n = 5) and shiverer (n = 4) mouse brains were imaged using 3D EPSI with 100 µm isotropic resolution. The free induction decay (FID) was sampled every 2.74 ms over 192 echoes and Fourier transformed to produce water spectra with 1.9 Hz resolution. FIDs were also fit to two biophysical models and the resulting fits were converted to spectra with a Fourier transform. Spectral asymmetry was computed and compared before and after fitting the data to models.Results Spectra derived from both models did not show the magnitude of asymmetric broadening observed in the raw data. Correlations between data- and model-derived asymmetries and estimated frequency shifts are weak, leading to a reduction in spectral sensitivity to changes in white-matter structure after fitting the data to models.Conclusion The results demonstrate spectral inconsistencies between biophysical model predictions and measured data, promoting the further incorporation of spectral analysis methods to develop and benchmark new model-based approaches.Competing Interest StatementThe authors have declared no competing interest.