In addition to influencing the tissue longitudinal relaxation time (T1) because of its macromolecular content, myelin affects water diffusivity in the brain[1,2]. Beyond white matter (WM), myelin is present in cortical grey matter (GM), where it plays a key role in neuroplasticity[3]. We hypothesized that R1 (1/T1), a proxy of myelin content in the tissue, is significantly related to diffusion metrics highly sensitive to GM microstructure derived from the advanced three-compartment model, Soma And Neurite Density Imaging (SANDI)[4] in healthy volunteers (HV).
Twenty HV (11F, age=28±4y) underwent diffusion-weighted imaging (DWI) with varying gradient strengths and quantitative R1-mapping (MP2RAGE) at 3T (Siemens). DWI preprocessing included denoising, correction for susceptibility artifacts, and eddy-current distortions. R1 and SANDI metrics (described and depicted in Fig.1) were derived, and their correlation was analysed in MATLAB. Voxels with cell density (fsoma)>0.1 were retained ensuring brain parenchyma selection. The HCP and the ICBM-DTI-81 atlas were used respectively for GM and WM parcellation[5,6]. Pearson’s correlation was evaluated, correcting for multiple comparisons (Bonferroni).
Scatterplots between R1 and SANDI metrics are shown in Fig.2. Across-regions, R1 correlated negatively with fsoma (r=-0.51) and cell size (Rsoma, r=-0.47) in GM, suggesting that less myelinated areas are rich in larger neurons, which agrees with metabolic findings[3]. In WM, R1 correlated positively with neurite diffusivity (Din) and density (fneurite) with r=0.62,0.43, respectively, due to myelin delineating the neurite diffusion compartment. In summary, the original hypothesis was verified in the absence of myelin degeneration. Future studies can explore this relationship in demyelinating diseases.
References
[1] J. P. Mottershead et al., «High field MRI correlates of myelin content and axonal density in multiple sclerosis–a post-mortem study of the spinal cord», J Neurol, vol. 250, fasc. 11, pp. 1293–1301, nov. 2003, doi: 10.1007/s00415-003-0192-3.
[2] Jones Derek K., Diffusion MRI: Theory, Methods, and Applications, Oxford University Press, 2010, doi: 10.1093/med/9780195369779.002.0005.
[3] M. F. Glasser, M. S. Goyal, T. M. Preuss, M. E. Raichle, e D. C. Van Essen, «Trends and properties of human cerebral cortex: correlations with cortical myelin content», Neuroimage, vol. 93 Pt 2, pp. 165–175, giu. 2014, doi: 10.1016/j.neuroimage.2013.03.060.
[4] M. Palombo et al., «SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI», NeuroImage, vol. 215, p. 116835, lug. 2020, doi: 10.1016/j.neuroimage.2020.116835.
[5] M. F. Glasser et al., «A multi-modal parcellation of human cerebral cortex», Nature, vol. 536, fasc. 7615, pp. 171–178, ago. 2016, doi: 10.1038/nature18933.
[6] S. Mori et al., «Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template», Neuroimage, vol. 40, fasc. 2, pp. 570–582, apr. 2008, doi: 10.1016/j.neuroimage.2007.12.035.
Figure 1. Group average parametric maps. Parametric maps of R1 and SANDI metrics normalized to MNI space and averaged across all subjects. R1 = 1/T1, relaxation rate; fneurite = signal intensity fraction of neurite compartment; fsoma = signal intensity fraction of cellular compartment; fextra = signal intensity fraction of extra-cellular compartment; Rsoma = average size of cellular bodies; Din = diffusivity of the intra-neurite compartment; De = diffusivity of the extra-neurite compartment. The different slices correspond to axial sections at different Z-coordinates (Z = 31, 38, 48, 58, 68) in MNI space.
Figure 2. Scatter plots of SANDI metrics vs R1 in Grey and White Matter (GM and WM, respectively). The Pearson’s correlation coefficient between R1 and SANDI metrics quantified in GM and WM regions is indicated. Regions exceeding the 20th percentile in voxel count were retained to minimize residual uncorrected noise. The significance level p is indicated (corrected p-value threshold=0.0083). Each marker represents, for a different brain region, the median across subjects of the regional median of the parameter. Error bars are standard errors (median absolute deviations/squared root of number of subjects). Markers and regression lines are shown in blue and red for GM and WM, respectively. Shaded areas represent 95% confidence intervals.
Acknowledgements
European Union-Next Generation EU- Italian Ministry of University and Research (MUR), Research National Program (PNR) and Projects of National Relevance (PRIN), Project Code: 2022BERM2F, Project Title: “Mapping Mitochondrial Function and Oxygen Metabolism in the Human Brain with Magnetic Resonance Imaging.” Funding call No. 104 of 02.02.2022, Concession decree No. 1065 of 18.07.2023 adopted by MUR, ERC Panel LS7 “Prevention, Diagnosis and Treatment of Human Diseases”. CUP: D53D23013410001;
European Union-NextGenerationEU- Italian Ministry of University and Research (MUR), National Plan for Recovery and Resilience (PNRR) and Projects of National Relevance (PRIN), Project Code: P20225AEEE, Project Title: “Hybrid PET-MRI to simultaneously probe brain metabolism and cerebrovascular function in neurodegenerative diseases.” Funding call No. 1409 of 14.09.2022, Concession decree No. 1369 of 01.09.2023 adopted by MUR, ERC Panel LS7 “Prevention, Diagnosis and Treatment of Human Diseases”. CUP: D53D23021480001;
European Union-NextGenerationEU- Italian Ministry of University and Research (MUR), National Plan for Recovery and Resilience (PNRR) and Projects of National Relevance (PRIN), Project Code: P2022ESHT4, Project Title: “Advancing MRI biomarkers of brain tissue microstructure and energetics in Multiple Sclerosis.” Funding call No. 1409 of 14.09.2022, Concession decree No. 1367 of 01.09.2023 adopted by MUR, ERC Panel LS5“Neuroscience and Disorders of the Nervous System”. CUP: D53D23019210001;
European Union – NextGenerationEU under the National Plan for Recovery and Resilience (PNRR), Mission 4 Component 2 – M4C2, Investment 1.5 – Call for tender No. 3277 of 30.12.2021 Italian Ministry of Universities Award Number: ECS00000041, Project Title: “VITALITY – Innovation, digitalization and sustainability for the diffused economy in Central Italy,” Concession Decree No. 1057 of 23.06.2022 adopted by the Italian Ministry of University and Research. CUP D73C22000840006.
European Union – Next Generation EU under the National Plan for Recovery and Resilience (PNRR), Project Title: “MNESYS (PE0000006) – A Multiscale integrated approach to the study of the nervous system in health and disease,” Concession Decree No. 1553 of 11.10.2022 adopted by the Italian Ministry of University and Research.
EB has received funding from the European Union’s Horizon Europe research and innovation programme under the Marie Skłodowska – Curie Grant Agreement No. 101066055 – acronym HERMES. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.
MP is supported by the UKRI Future Leaders Fellowship (MR/T020296/2).
AC is partially supported by Fondo per la Promozione e lo Sviluppo delle politiche del Programma Nazionale per la Ricerca – di cui a DM 737/2021 emanato dal MUR.
EB is supported by Doctorate School of the Gabriele D’Annunzio University.
