Introduction

MR imaging of the cortical structure in vivo is challenging, due to its complex microstructure and its heterogeneity across the brain¹. Hardware and software advances in MRI have enabled unprecedented spatial resolution in vivo, thereby providing a valuable window into cortical grey matter microstructure^2,3. Magnetization-prepared two inversion-contrast rapid gradient echoes sequence (MP2RAGE) provides both a uniform T1w contrast and a T1 map corrected for the proton density, T2* contrast, and B1 inhomogeneities⁴ at ultra-high field^5,6. In this study, we propose a novel approach to analyze the organization of the cerebral cortex using a partial volume estimation applied to MP2RAGE uniform maps acquired at 7T.

Method

We acquired MP2RAGE images on a whole body 7T MRI research scanner (Siemens Healthcare, Erlangen, Germany) in 10 healthy subjects (8 women/2 men; age=33.9±9.5years) at high spatial resolution (0.75x0.75x0.9mm³). One subject underwent an additional 7T MP2RAGE at ultra-high spatial resolution acquisition (0.35mm³ isotropic). We used FreeSurfer to perform cortical segmentation on MP2RAGE uniform images in each subject⁷ and then – to each cortical region – we applied a novel algorithm to estimate tissue concentration in each voxel. The algorithm operates using a model that describes the intensity of each voxel as the sum of GM, WM and CSF characteristic intensities, weighted by their respective local concentrations⁸. We initialized tissues characteristic intensities based on average tissue intensities. Our analysis focused on 3 brain regions known to exhibit high histological diversity in its constituents (peri-calcarine, pre-central and post-central).

Results

The algorithm identified 3 “tissue combinations” that exhibited a similar spatial distribution over all cortical areas: (i) an outer layer constituted by GM/CSF-like partial volume intensities, (ii) a central layer constituted by GM only, (iii) and an inner layer with voxels that show a mix of GM and WM-like intensities (Figure 1). Different spatial extents of those 3 layers were observed when the peri-calcarine region was compared to the pre-/post-central regions (Figures 1, 2). In fact, the proportion of voxels belonging to the outer layer slightly changed across the 3 regions (25% in the peri-calcarine; 25% in the pre-/post-central areas; 15% in the whole brain, Figure 1). In addition, the inner layer, which is just 2-3 voxels thick in the peri-calcarne area, doubled in size in a specific area of the pre-central region (Figure 2.B). The central layer (voxels with GM concentration>80%) appeared as a thin line of 1-2 voxels in part of the pre-central and peri-calcarine regions (Figure 2.A,B), or as a larger band of 3-4 voxels in other areas of the pre-central and peri-calcarine regions (Figure 2.A,B,C). The analysis of ultra-high resolution MP2RAGEs showed the 3 layers with the same patterns observed at 0.75mm, but also revealed a very particular pattern in the peri-calcarine, with a high concentration of WM-like signal inside the central layer (Figure 2.C).

Discussion and conclusion

We have applied a new partial volume estimation algorithm to sub-millimeter MP2RAGE images, which identified 3 layers (outer, central, inner) in a cohort of healthy subjects. The properties of the outer layer (i.e. T1 signal that is higher than GM and lower than CSF) are compatible with the loose structure (i.e. sparseness of neuronal component) of the layers 1 to 3 in the brain cortex (supragranular layers⁹). The middle layer is constituted by T1 signal that are typical of a compact GM structure, such as the one characterizing layers 4 to 5 in the cerebral cortex. Interestingly, at 0.35 mm³ resolution, we have also identified a band resembling to the inner layer (mix of GM and WM-like intensities) that is located where the Stria of Gennar has been histologically described¹⁰. Future work will focus on exploiting the current approach to study the impact of neuro-inflammatory and neurodegenerative pathologies on the 3 layers microstructure.

Acknowledgements

No acknowledgement found.

References

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