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 microstructure
1
is crucial to establish novel atlases of the cortex
in vivo.
Diffusion MR microscopy
2,3 has proven to be a useful tool to
investigate the cytoarchitecture of brain tissues, and recent models
like NODDI
4 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
development
5,6 or progression of diseases
7,8. 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 f
intra and a higher OD in the cortex.
Fig.2 illustrates the pipeline used to extract surface maps of
f
intra at the vertex scale at individual and group levels, showing
that f
intra patterns remain similar on both hemispheres, but present
differences within the same hemisphere. Fig.3 shows the
mean/median/stddev maps of f
intra 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 gender
12, 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
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