Asymmetries of the dendrite density in cortical areas assessed by diffusion MR microscopy using NODDI
Achille Teillac1,2,3, Sandrine Lefranc2,3,4, Edouard Duchesnay2,3,4,5, Fabrice Poupon2,3,4, Maite Alaitz Ripoll Fuster1,2,3, Denis Le Bihan1,2,3, Jean François Mangin2,3,4,5, and Cyril Poupon1,2,3,5

1CEA NeuroSpin / UNIRS, Gif-sur-Yvette, France, 2Université Paris-Saclay, Orsay, France, 3France Life Imaging, Orsay, France, 4CEA NeuroSpin / UNATI, Gif-sur-Yvette, France, 5http://cati-neuroimaging.com/, Gif-sur-Yvette, France

Synopsis

In this study, we investigated the dendrite density in cortical areas with diffusion MR microscopy using the NODDI model and showed, on a population of healthy volunteers, significant differences between left and right hemisphere, correlated with their supported brain functions.

Purpose

Understanding the correlation between brain functions and tissues microstructure1 is crucial to establish novel atlases of the cortex in vivo. Diffusion MR microscopy2,3 has proven to be a useful tool to investigate the cytoarchitecture of brain tissues, and recent models like NODDI4 give the opportunity to probe the dendrite density within the cortex in vivo. Moreover, few studies have been published to demonstrate its potential to probe the modifications occurring during normal development5,6 or progression of diseases7,8. In this work, we establish a novel atlas of the dendrite density in the healthy volunteer and we investigate their asymmetries in cortical areas between left and right hemispheres.

Methods

Acquisition - 71 right-handed healthy volunteers were scanned on a 3T MRI system using a dedicated protocol9 including: a) a MPRAGE sequence to obtain a T1-weighted anatomy (1mm isotropic; TE=2.98ms; TR=2.3s); b) a multiple-shell diffusion-weighted SE-EPI sequence (1.7mm isotropic; TE=117ms; TR=14s; 10 b-values (300-3000s/mm2) along 20 directions + 10 scans at b=0s/mm2); c) a fieldmap calibration to remove distorsions.

Individual NODDI maps – Individual DW dataset were preprocessed using Connectomist9 to remove imaging artifacts, thus enabling accurate matching of DW and T1-weighted data using rigid registration. Individual NODDI maps were computed using Connectomist (fig1): the intracellular fraction (fintra) referring to the space bounded by the membranes of neurites, their orientation dispersion (OD), the Bingham concentration parameter (K), and the CSF fraction (fiso).

Individual and group pial and white surfaces – T1-weighted MR scans were processed using FreeSurfer et aparc.a2009s10 to extract individual pial and white matter surfaces. Homologue vertices between pial/white surfaces and between individuals allow to easily navigate between surfaces. Cortex parcelation was done using the aparc.a2009s Destrieux atlas11 defining 152 regions.

Dendrite density maps – The correspondence of vertices allowed to extract a distribution of fintra for each vertex by sampling the matched fintra map along the segment defined by each pair of ( pial, white ) vertices (fig2). Maps of local distributions of fintra were computed and statistics were inferred to build maps of mean, standard deviation (stddev) and median of fintra at the vertex level (fig2). To obtain distributions of fintra at the scale of cortical areas, the distributions obtained for vertices included in the area were merged together to form a global distribution from which statistics were established, providing a microstructural signature of this area (fig3).

Evaluation of left/right asymmetries - the signed differences of mean fintra between left and right cortical areas were computed for all the areas and subjects, and a t-test was performed to evaluate the L-R asymmetry of fintra for each region.

Results and discussion

Fig.1 depicts T1-weighted and NODDI individual maps, clearly showing a lower fintra and a higher OD in the cortex. Fig.2 illustrates the pipeline used to extract surface maps of fintra at the vertex scale at individual and group levels, showing that fintra patterns remain similar on both hemispheres, but present differences within the same hemisphere. Fig.3 shows the mean/median/stddev maps of fintra obtained for cortical areas at individual and group levels. Fig.4 provides a table of t-tests performed on L-R mean differences for all the regions. False Discovery Rate correction was applied to correct for multiple comparisons, yielding 44 significant areas: 26 corresponding to a higher dendrite density on the left hemisphere and 18 on the right hemisphere. Fig.5 provides renderings of the significant regions: 1) the primary sensorimotor cortex depicts a higher dendrite density in the left hemisphere, which is in perfect adequation with the right handedness of the group; 2) the superolateral part of the temporal lobe supporting the auditory and langage networks depicts a higher dendrite density in the left hemisphere, which fits with the left localization of this function; 3) on the contrary, the occipital lobe supporting the visual cortex depicts a higher dendrite density in the right hemisphere to be confronted to the comparisons done according to the gender12, as well as the fusiform area processing color/face/body/word recognition; 4) the superior frontal gyrus, involved in self-awareness also depicts a higher dendrite density in the right hemisphere.

Conclusion

In this work, we demonstrated that diffusion MR microscopy, using the NODDI model, opens promising perspectives for the investigation of the cortical areas dendritic composition in vivo. For a population of right-handed subjects, we showed that the established asymmetries between L-R hemispheres are in good agreement with the lateralization of the underlying brain functions.

Acknowledgements

No acknowledgement found.

References

1: Zilles et al, 2010.Nature.Rev.Neurosc.11(2):139-145; 2: Assaf et al, 2008. MRM 59(6):1347-54; 3: Alexander D, 2008. MRM 60(2):439-48; 4: Zhang et al, 2012. Neuroimage 61(4):1000-16; 5: Kunz et al 2014. Neuroimage 96:288-299; 6: Chang et al, 2015. PloS One 10(6):e0123656. 7: Winston et al, 2014. Epilepsy Res. 108(2):336-9; 8: Billiet et al, 2015. Neurobiol. Aging 36(6):2107-21; 9: Assaf et al, 2013. Neuroimage 80:273-82; 10: Fischl B, 2012. Neuroimage 62(2):774-81; 11: Destrieux et al, 2010. Neuroimage 53(1):1-15; 12: Amunts et al, 2007. J.Neurosci.27(6):1356-64.

Figures

Individual T1-weighted and NODDI quantitative maps

Processing pipeline used to get individual and group statistics of the dendrite density (fintra) mapped onto the cortical surface

Processing pipeline used to get individual and group statistics of the dendrite density (fintra) within cortical regions

t-tests performed for a right-handed population of 71 subjects to infer cortical regions showing significant differences between left and right mean dendrite density (fintra) (significant FDR corrected p-values are highlighted in bold)


3D representation of cortical regions depicting a significant difference of dendrite density (fintra) between left and right hemispheres.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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