Chih-Chien Tsai1,2, Sher Li Oh3, Chiung-Mei Chen4, Yih-Ru Wu4, Maria Valdes Hernandez5,6, Jur-Shan Cheng7, Yao-Liang Chen8, Yi-Ming Wu8, Yu-Chun Lin8, and Jiun-Jie Wang1,2,9,10
1Department of Medical imaging and Radiological Science, Chang-Gung University, Taoyuan City, Taiwan, 2Healthy Aging Research Center, Chang Gung University, Taoyuan City, Taiwan, 3Nanyang Technological University, Singapore, Singapore, 4Department of Neurology, Chang Gung Memorial Hospital, Taoyuan City, Taiwan, 5Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom, 6Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom, 7Clinical Informatics and Medical Statistics Research Center, Chang-Gung University, Taoyuan City, Taiwan, 8Department of f Medical Imaging and Intervention, Chang Gung Memorial Hospital, Taoyuan City, Taiwan, 9Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University/Chang Gung Memorial Hospital, Taoyuan City, Taiwan, 10Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Taoyuan City, Taiwan
Synopsis
Microstructure
damage in white matter might be linked to regional and global atrophy in
Huntington Disease. Fixel-based analysis (FBA) has recently emerged as a useful
fiber-specific tool for examining white matter structure, which could be an
important contributor to the pathogenesis of Huntington’s disease. Therefore, we
investigate the utility of FBA as a biomarker for disease progression. Our
findings indicated the reductions in FBA occurs in major white matter tracts,
which was closely co-localized with the regions of increased diffusivity in basal
ganglia. FBA analysis is effective in studying white matter tractography and
fiber changes in Huntington’s Disease.
INTRODUCTION
Huntington’s Disease is
an autosomal dominant genetic disease that results in progressive
neurodegeneration. Study has revealed extensive grey and white matter atrophy
in the brains of patients with Huntington’s Disease [1].
Large-scale longitudinal MRI cohort studies focused mainly on identifying
biomarkers of Huntington’s Disease that can indicate disease progression before
and after clinical diagnosis throughout different stages [2;
3; 4].
Diffusion
MRI is often used as a non-invasive method of observing microstructural and
macrostructural alterations in grey and white matter over time. Analysis of
changes in water diffusion in patients with Huntington’s Disease might provide
insight on the changes that the brain undergoes as the disease progresses. In
Huntington’s Disease, the severity of motor impairments is often found to be
correlated to volume loss in the basal ganglia, particularly in the nucleus
accumbens, caudate nucleus, putamen, and globus pallidus [5].
Widespread white matter neurodegeneration has been observed in longitudinal
studies of Huntington’s Disease patients, especially in the corpus callosum and
the internal capsule [6],
cingulum and striatal projection [7].
We therefore hypothesize that the atrophy that takes place in subcortical regions,
in particular the basal ganglia, in patients of Huntington’s Disease, is
associated with the damage of white matter tracts linking the affected
subcortical regions. METHODS
We used connectivity-based fixel enhancement and
fixel-based analysis [8] to study white matter tractography and diffusivity in
12 Huntington’s Disease patients and 16 healthy unrelated controls.
We used a 3T MR scanner from Siemens. T1 -weighted
magnetisation-prepared rapid acquisition gradient echo and diffusion weighted
images were obtained. The imaging parameters for T 1 -weighted images were as
follows: repetition time (TR) / echo time (TE) = 1700 ms / 2.63 ms, number of
slices = 160, voxel size = 1×1×1 mm 3 , inversion time = 900 ms, flip angle = 9º,
matrix size = 224× 256, field of view= 224× 256 mm 2 , and slice
thickness = 1 mm. Diffusion weighted images were acquired using a spin-echo
echo planar imaging sequence with the following parameters: TR / TE = 5200 ms /
92 ms, voxel size = 2× 2× 3 mm 3 , matrix size = 128× 128, number of slices = 13,
slice thickness = 3 mm, and b-value = 0 and 1000 s/mm 2 . The diffusion
weighted gradients were applied along 12 non-collinear directions.
Clinical assessment of Huntington’s Disease severity
was conducted using the Unified Huntington’s Disease Rating Scale (UHDRS) and
cognitive decline was evaluated using the Mini-Mental State Examination (MMSE).
The correlation between image metrics and results from
the patients’ clinical assessment using their UHDRS scores was evaluated using
Spearman’s rank correlation coefficient. In all tests, significance was reached
at a threshold of p ≦0.005 after correction for multiple comparisons using Bonferroni
correction. General linear model and non-parametric permutation testing were used
to identify group differences in FD, FC, and FDC with significance
level p ≦0.05 [9]. Bonferroni correction was used to
account for multiple comparisons.RESULTS
Patients
showed reduced fixels located in widespread white matter, noticeably in the
forceps minor, major, and corona radiata white matter fibers in the corpus
callosum, and in the corticospinal fibers and middle thalamic radiation in the
posterior limb of the internal capsule (Figure 1). In
addition, reduced FDC and FC were observed in the corticospinal tract in
Huntington’s Disease patients compared to healthy control participants (Figure 2). Figure 3 shows the co-localization
of significant differences in FDC, FC, and FD of white matter fibers and tensor-derived
indices of subcortical grey matter regions. It can be observed that the
affected white matter tracts, such as the internal capsule and corpus callosum,
are closely positioned to these subcortical regions of interest.DISCUSSION
This study sought to
investigate white matter microstructural differences in patients with
Huntington’s Disease using fixel-based analysis. Compared to the healthy
control participants, the main findings in patients include: 1) between-group
differences in fixel-derived indices, noticeably located bilaterally in the
corpus callosum and internal capsule, 2) reduced FDC and FC along the
corticospinal tract, and 3) increased FC in the fornix, despite reduction in
FDC and apparent fiber density. The affected regions, including the corpus
callosum and the internal capsule, are in line with those in morphometry
studies [1].
The axonal degeneration in these regions and other major tracts such as the
superior longitudinal fasciculus and uncinate fasciculus might explain why
Huntington’s Disease affects multiple regions of the brain with such widespread
effects on motor and cognitive functions. Our study might provide additional
image-based evidence that axonal degeneration is likely to occur over the
manifestation of Huntington’s Disease.CONCLUSION
Fixel-based analysis could provide new information on white matter tracts affected in patients affected by Huntington’s Disease, and therefore is potentially helpful in the development of potential new therapeutic interventions.Acknowledgements
The presents work
was supported by the Imaging Core Laboratory of the Institute for Radiological
Research and the Center for Advanced Molecular Imaging and Translation. The
authors thank the Neuroscience Research Center (Chang Gung Memorial Hospital)
and the Healthy Aging Research Center (Chang Gung University) for their
invaluable support. This work was also supported by the UK Dementia Research
Institute which receives its funding from DRI Ltd, funded by the UK Medical
Research Council (MRC), Alzheimer’s Society and Alzheimer’s Research UK. References
[1] N.Z. Hobbs, S.M. Henley, G.R. Ridgway, E.J. Wild, R.A. Barker,
R.I. Scahill, J. Barnes, N.C. Fox, and S.J. Tabrizi, The progression of
regional atrophy in premanifest and early Huntington's disease: a longitudinal
voxel-based morphometry study. Journal of Neurology, Neurosurgery &
Psychiatry 2010; 81 756-763.
[2] J.S. Paulsen, Functional imaging in Huntington's disease.
Experimental neurology 2009; 216 272-277.
[3] S.J. Tabrizi, R. Reilmann, R.A. Roos, A. Durr, B. Leavitt, G.
Owen, R. Jones, H. Johnson, D. Craufurd, and S.L. Hicks, Potential endpoints
for clinical trials in premanifest and early Huntington's disease in the
TRACK-HD study: analysis of 24 month observational data. The Lancet Neurology
2012; 11 42-53.
[4] J.F. Domínguez D, G.F. Egan, M.A. Gray, G.R. Poudel, A.
Churchyard, P. Chua, J.C. Stout, and N. Georgiou-Karistianis, Multi-modal
neuroimaging in premanifest and early Huntington’s disease: 18 month
longitudinal data from the IMAGE-HD study. PloS one 2013; 8 e74131.
[5] E.M. Coppen, M. Jacobs, A.A. van den Berg-Huysmans, J. van der
Grond, and R.A. Roos, Grey matter volume loss is associated with specific clinical
motor signs in Huntington's disease. Parkinsonism & Related Disorders 2018;
46 56-61.
[6] H.D. Rosas, D.S. Tuch, N.D. Hevelone, A.K. Zaleta, M. Vangel,
S.M. Hersch, and D.H. Salat, Diffusion tensor imaging in presymptomatic and
early Huntington's disease: Selective white matter pathology and its
relationship to clinical measures. Movement disorders: official journal of the
Movement Disorder Society 2006; 21 1317-1325.
[7] G.R. Poudel, J.C. Stout, A. Churchyard, P. Chua, G.F. Egan, and
N. Georgiou-Karistianis, Longitudinal change in white matter microstructure in
Huntington's disease: the IMAGE-HD study. Neurobiology of disease 2015; 74
406-412.
[8] D.A. Raffelt, J.D. Tournier, R.E. Smith, D.N. Vaughan, G.
Jackson, G.R. Ridgway, and A. Connelly, Investigating white matter fibre
density and morphology using fixel-based analysis. Neuroimage 2017; 144 58-73.
[9] T.E. Nichols, and A.P. Holmes, Nonparametric permutation tests
for functional neuroimaging: a primer with examples. Human brain mapping 2002;
15 1-25.