David Neil Manners1, Claudia Testa1, Stefania Evangelisti1, Stefano Zanigni1, Mariagrazia Popeo2,3, Caterina Tonon1, and Raffaele Lodi1
1Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy, 2Istituto Italiano di Tecnologia, Rovereto, Italy, 3Center for Neurosciences and Cognitive Systems, University of Trento, Rovereto, Italy
Synopsis
We
performed
an along tract analysis of the cortico-spinal tract in a group of healthy
subjects using a probabilistic tractography algorithm. We were able to evaluate
CST reconstruction along the tract using appropriate performance metrics, based
on the congruence of fibre paths in the subject population, and the presence or
absence of fibre tracks identified as originating from the precentral gyrus. The
method was compatible with clinical protocols given spatial definition and
tract localization obtained. Introduction
MR tractography holds the promise of deriving
neuroanatomical information from non-invasive MR studies, but its performance
in practice is usually difficult to verify. Going beyond the simplest DTI
tensor model is probably essential. Probabilistic tractography has been used
for a number of years, but protocols for use in clinical scanners must still be
optimized on a tract-by-tract basis. In the current study we aimed to develop
an appropriate protocol for defining the cortical spinal tract (CST) for
clinical examination.
Methods
Twenty-five
healthy adult subjects (13 females), with an age range 20-83 years (mean 38),
were recruited, and underwent MR scanning using a 1.5 Tesla GE Signa system. A
T1-weighted axial volumetric image was acquired using the FSPGR sequence (25.6
cm2 FOV; 1 mm isotropic voxels) and axial diffusion-weighted images
using a single-shot SE-EPI sequence with FOV 32x32 cm, 3 mm slice-thickness,
in-plane resolution 128x128, b-value = 900 s mm-2, and 64
diffusion-weighted directions + 7 unweighted scans. The protocol was approved
by the local Ethics Committee and written informed consent was obtained from
all participants.
Cortical parcellation/labelling of the volumetric
images was performed by Freesurfer1. Volumetric images and
associated labels were aligned to DWI volumes using FSL/FLIRT, followed by
nonlinear deformation2. Basic DWI processing was performed using the FMRIB software library (http://www.fmrib.ox.ac.uk/fsl), applying bedpostx and probtrackx for probabilistic tractography3. The starting
point of the CST (seedmask) was
identified using voxels labelled by Freesurfer as lying within the precentral
gyrus, separately for left and right sides. In addition fibres were constrained
to pass through the posterior limb of the internal capsule (PLIC) (waypoint) and thence to the pons
(termination mask). The result of the tractography was a voxelwise estimate for
CST connectivity (fibre count).
All subject data was linearly aligned to the FMRIB58
FA template. Voxels that contained average fibre numbers of at least 0.4%
maximum were used to define a consensus CST mask. For each side of the brain, fibre
count images were resampled to yield exactly 100 slices in the z-direction to
cover the distance from the pons to the upper limit of the precentral gyrus.
To identify protocol parameters that might improve
tract definition, two operational variables were defined as quality metrics for
each subject:
i) False negative
rate (FNR) – false negative voxels within the seedmask without emergent fibres / all seedmask voxels;
ii) False discovery
rate (FDR) – false positive voxels containing fibres but lying outside the
consensus mask / all fibre-containing voxels.
Two methods of thresholding the fibre count, to reduce
FDR, were tested – per subject thresholding, and slicewise thresholding,
considering that the main course of the CST runs superior-inferior from the
motor cortex to the pons. Several normalisation parameters were considered, and
the best threshold level was side to minimize FNR and FDR.
Results
Slicewise total fibre numbers are shown in Figure 1. The
pattern is qualitatively similar for all subjects: numbers increases from the
highest slice reaching a peak around the level of the PLIC, before falling to a
low value as the tract descends to the midbrain, with the voxel maximum fibre
number showing a roughly inverse pattern, conditioned by the relative number of
fibres originating at or above a given level. A performance curve for different
threshold values is shown in Figure 2. The expected FNR/FDR trade-off is
observed, starting from mean FNR 0.30 ± s.d. 0.13 and FDR 0.37 ± 0.13 for threshold=0. Slicewise thresholding is slightly better. False positive/negative results
are demonstrated in Figure 3 for a typical subject.
Discussion
Methods
for performing tractography of the CST have recently been examined
4,
and no single method was found to be definitely superior. Probabilistic tractography
naturally generates streamlines that are unlikely to correspond to neuronal
fibres, and so a method for culling false fibres is needed. Constraining fibre
paths to pass through the PLIC and pons produces an adequate performance if combined
with a fibre number threshold. The number of fibres in each slice (Figure 1) is
determined mainly by the number of seed voxels above, and the compactness of
the fibre tract (demonstrated by the maximum fibre number). Allowing for this slicewise
variation marginally improves tract delineation, especially with a high threshold
(Figure 3), and is thus useful for defining the main part of the tract below
the corona radiata. At and above this level, additional methods will be
required, especially in the lateral portions of the corona radiate and centrum
semiovale, which lie on the same level as the more medial tract and are readily
culled with a slicewise threshold.
Acknowledgements
No acknowledgement found.References
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