Synopsis
Tensor based morphometry (TBM) is a class of deformation based morphometry (DBM) methods that is traditionally performed on T1-weighted images (T1W). Here, we investigate the sensitivity of TBM by comparing the results of TBM, based on T1W and diffusion tensor imaging (DTI) data in patients diagnosed with SPG11, a neurological condition with a known genetic basis. TBM based on T1W and diffusion data captured the volumetric changes along the corpus callosum,which is a known characteristic of SPG11 patients, but does not fully explain the disorder. In contrast, only DTI-TBM identified volumetric changes in several association and projection pathways suggesting greater sensitivity of DTI-TBM.Purpose
Voxelwise
analysis of diffusion tensor data is a common practice in investigating group
differences1,2. Typically, the image data of each subject are
registered to a common space and a voxelwise comparison is performed on
diffusion derived metrics using statistical methods. Alternatively one could analyze the deformation
fields that map individual images from their native space to the common space.
This approach is generally known as deformation based morphometry (DBM) and
more specifically as tensor based morphometry (TBM) when the Jacobian of the transformation
matrix is used to measure local changes3,4. TBM has traditionally
been applied to structural MRI images such as T1W (T1W-TBM) to measure local
changes in volume5,6, however, rarely has been applied to diffusion
MRI data (DTI-TBM)7,8. We
hypothesize that TBM based on deformation fields obtained by tensor-based
registration of diffusion data would be more sensitive than T1W-TBM to volume
changes in specific white matter pathways.
We, therefore, tested the
sensitivity of T1W-TBM and DTI-TBM in detecting neuroanatomical differences
between healthy controls and a group of patients with the SPG11 type of
hereditary spastic paraplegia (HSP). SPG11
HSP is characterized by progressive spasticity and lower limb weakness as well
as other neurological problems including mental retardation and dysartria9,10. The most common MRI reported findings in
SPG11 HSP are thin corpus callosum and periventricular white-matter T2
hyperintensities9,10. We hypothesized DTI-TBM
may be able to identify thinning of other white matter pathways, which may
account for the complex clinical pattern found in these patients.
Materials & Methods
Five
subjects diagnosed with SPG11 and 24 age-matched controls without any history
of neurological disorders were included in the study. All participants were
scanned on a Philips 3T system with a 32-channel head coil. The DTI data were
acquired with a single-shot Spin-Echo EPI sequence (TR: 4700 ms, TE:80 ms, 80
slices, acceleration factor: 2 with isotropic voxel size of 2.2mm3). A multi-shell DTI protocol composed of 76 DWI
volumes was employed (b-values: 0, 300, 1100 s/mm2) with the 1100
s/mm2 shell comprising of 32 diffusion directions. Additionally, a
MPRAGE 3D T1-weighted sequence (TR: 8.2 ms, TE: 3.8 ms, voxel size: approximately
1x1x1 mm) was obtained.
For the T1W-TBM analysis, separate
T1W templates were created using the ANTS software11, one template
for the SPG11 subjects and one for the control group (Figure 1). The SPG11 T1W template was then registered to
the control T1W template and the deformation field was generated.
The diffusion-weighted
data were pre-processed using the TORTOISE pipeline12 to reduce the
effects of motion, eddy current, and EPI distortions and tensor fitting was
performed using nonlinear tensor estimation.
For the DTI-TBM analysis, separate templates for the SPG11 and control
groups were created using the nonlinear tensor registration software, DTI-TK13
(Figure 1). Subsequently, the SPG11
template was registered to the control template and the deformation field was generated.
The log of the determinant
of the Jacobian was calculated for both the T1W and DTI deformation fields. A value of log of determinant of the Jacobian > 0 implies local expansion
(bright areas in Figures 2-3), whereas values < 0 implies local shrinkage
(dark areas in Figures 2-3).
Results
Figures
2 and 3 show the result of the Jacobian maps based on T1W-TBM and DTI-TBM respectively. The Jacobian map based on T1W images captures
the shrinkage of genu and splenium of the corpus callosum in the patient
population, which has been reported previously
9,10. However, the atrophy is more pronounced in
the maps obtained by the diffusion data. Figures 2 and 3 show that the Jacobian
maps based on DTI-TBM detected thinning of white matter structures that are not
evident on T1W Jacobian maps. Thinning
affected commissural pathways (tapetum), association pathways (inferior-fronto-occipital-fasciculus,
arcuate fasiculus), optic radiations, and projection pathways (corticospinal
tract, posterior limb of the internal capsule).
Conclusion
Analysis
of the Jacobian maps of deformation fields from DTI data revealed that in
addition to the corpus callosum other white matter pathways including
association, projection, and commissural fibers are affected in SPG11. These
findings may help us better understand the complex clinical manifestations of
this disease. In general our findings
suggests that performing tensor based morphometry analysis using diffusion
tensor MRI data for registration is a promising approach to detect hypoplasia
or atrophy of selected pathways in affected patient populations. One can essentially seed in a region of high
atrophy and construct the full white matter pathway. When atrophy is severe, assessing group
differences using deformation based analysis may be more appropriate than direct
voxelwise analysis of diffusion metrics which would be suffering from severe
partial volume contamination.
Acknowledgements
This work was supported by Intramural Research Programs of NICHD. Salary support for CT was provided by funding from the Department of Defense in the Center for Neuroscience and Regenerative Medicine.References
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