Sophie Sébille1, Romain Valabregue1, Anne-Sophie Rolland1, Chantal François1, and Eric Bardinet1
1Brain and Spine Institute, CNRS UMR 7225 - INSERM U 1127 - UPMC-P6 UMR S 1127, Paris, France
Synopsis
We
applied super-resolution TDI, as a tool to gain spatial resolution
using post-processing methods, to one healthy individual to highlight
the fine details of the anatomical fibers tracts in the brainstem. A
1.25 mm isotropic diffusion data acquired in
vivo at 3T was used to
calculate a 0.2 mm isotropic TDI map. We demonstrated that the
super-resolution TDI clearly improved the spatial resolution, as well
as the emphasis on different contrast information. These maps can be
of help to anatomists to explore the brainstem complex organization
by identifying subject-specific tracts.Introduction
Precise knowledge of the mesencephalic brain regions
made possible neurosurgical procedures such as deep brain stimulation
(DBS) of the subthalamic nucleus to treat motor symptoms in
Parkinson's disease. Since then, area of interest for DBS is
growing and point out new brain areas located in the brainstem1.
However little is known about connections and spatial orientation of
brainstem pathways due to a lack of precise atlases based on
myelin-stained sections.
Imaging studies using diffusion MRI have shown the
potential of this technique to identify structures and tracts in the
basal ganglia2 and the brainstem3. Brainstem
fiber tracts were indeed highlighted with ex vivo MRI
acquisition at 11.7T (scanning time: 62 hours) providing a spatial
resolution of 0.255 mm3.
Achieving such a resolution in vivo is not
realistic, even with ultra-high field MR scanners. Nevertheless, a
technique known as super-resolution track-density imaging (TDI) was
developed4 and validated5 as a tool to gain
spatial resolution using post-processing methods.
Purpose
We evaluated
super-resolution TDI of
in vivo diffusion data acquired at 3T
in 30 minutes as a tool to be used to accurately describe the
complexity of human brainstem subject-specific fiber tracts.
Methods
We used diffusion MRI acquired at 3T
(1.25 mm isovoxel size) from one healthy individual included and
preprocessed in the Human Connectome Project6.
Probabilistic tractography was run in subject-specific native space
using MrTrix software package and its constrained spherical
deconvolution technique by randomly seeding throughout the brainstem
(segmented with the FreeSurfer recon-all pipeline). The
relevant parameters were: number of tracks = 10 000 000, maximum
angle between steps = 45°, 0.1 mm step-size, any track with length <
6.25 mm was discarded, lmax = 10, termination criteria: exit the
brain or when the FA amplitude was < 0.1.
We applied the SIFT
method7 to the reconstructed fiber tracks in order to
improve the biological accuracy of the reconstruction (from 10 000
000 to 4 000 000 streamlines).
Directionally-encoded colour (DEC)
super-resolution TDI maps were generated by calculating the number of
tracks in each element of a grid. A salient point of the TDI mapping
is that the grid element is made smaller than the acquired voxel
size, generating a final map at a much higher resolution than the
original DWI data. In our study, we used a 1.25 mm isotropic source
diffusion data to calculate a 0.2 mm isotropic TDI map with the
display of local fiber directionality.
To evaluate the improvement
provided by TDI in comparison to fractional anisotropy (FA), we draw
two inclusions ROIs on the same FA and TDI slices and then
reconstructed a branch of the pontocerebellar fibers in each case.
Results
Fig. 1 and Fig. 2 show the DEC
super-resolution TDI maps and corresponding conventional FA maps. A
clear amelioration of the spatial resolution is achieved by
super-resolution, as well as the emphasis on different contrast
informations. Major pathways were identified by their
inferior-superior orientations (blue in Fig. 1) including the
corticospinal tract, medial lemniscus and medial longitudinal
fasciculus. TDI maps from Fig. 1 provided striking contrasts to
delineate the fiber bundles of the corticospinal tract (blue) from
the pontocerebellar fibers (red). Fig. 2 further illustrates the
anatomical complexity of the fiber tracts shed light on TDI maps at
different sagittal plans. The superior cerebellar peduncle was
distinctly delineated with its anterio-posterior orientation (green).
Fig. 3 shows that the reconstructed
branch of the pontocerebellar fibers by segmenting ROIs on TDI
instead of FA allows more precise and detailed results. In
particular, the reconstructed tract from the FA ROIs clearly deviates
to a more rostral branch of the pontocerebellar fibers while TDI
provides an anatomically consistent tract.
Conclusion
With this study we demonstrated that
super-resolution TDI maps can provide accurate and useful anatomical
information with an exquisite level of details in the brainstem
region from in vivo 3T diffusion data. Therefore,
anatomists can used these maps as a 3D microscope to explore the
brainstem complex organization by identifying subject-specific tracts
in healthy humans.
This technique will be a useful resource for
clinical research applications once the scanning time needed will be
acceptable for patients. In addition, this method will be used in our
future studies in order to guide seed/target ROI definition in
tractography investigations of the brainstem, to help in the
stimulation of white matter pathways with DBS and to better
understand neurostimulation interventions in treating a broad range
of neurological disorders.
Acknowledgements
This
work received funding from the programs 'Institut
des neurosciences translationnelle' ANR-10-IAIHU-06 and
'Infrastructure d’avenir en Biologie
Santé' ANR-11-INBS-0006.
Data
were provided by the Human Connectome Project, WU-Minn Consortium
(Principal Investigators: David Van Essen and Kamil Ugurbil;
1U54MH091657) funded by the 16 NIH Institutes and Centers that
support the NIH Blueprint for Neuroscience Research; and by the
McDonnell Center for Systems Neuroscience at Washington University.
References
1.
Kringelbach ML, Jenkinson N, Owen SL, Aziz TZ. Translational
principles of deep brain stimulation. Nature. 2007;8:623-35
2. Draganski
B, Kherif F, Klöppel S, Cook PA, Alexander DC, Parker GJ, Deichmann
R, Ashburner J, Frackowiak RS. Evidence for segregated and
integrative connectivity patterns in the human Basal Ganglia. The
Journal of Neuroscience. 2008;28:7143-52
3. Aggarwal
M, Zhang J, Pletnikova O, Crain B, Troncoso J, Mori S. Feasibility of
creating a high-resolution 3D diffusion tensor imaging based atlas of
the human brainstem: a case study at 11,7T. NeuroImage.
2013;74:117-27
4. Calamante
F, Tournier JD, Jackson GD, Connelly A. Track-density imaging (TDI):
Super-resolution white matter imaging using whole-brain track-density
mapping. NeuroImage. 2010;53:1233-1243
5. Calamante
F, Tournier JD, Heidemann RM, Anwander A, Jackson GD, ConnellyA.
Track density imaging (TDI): validation of super resolution property.
NeuroImage. 2011;56(3):1259-66
6. Essen V,
Smith SM, Barch DM, Behrens TE, Yacoub E, Ugurbil K. The WU-Minn
Human Connectome Project : An overview. NeuroImage. 2013;80:62-79
7. Smith RE,
Tournier JD, Calamante E, Connelly A. SIFT: Spherical-deconvolution
informed filtering of tractograms. NeuroImage. 2013;67:298-312