Brain Advance Access originally published online on May 3, 2006
Brain 2006 129(7):1859-1871; doi:10.1093/brain/awl100
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Probabilistic diffusion tractography: a potential tool to assess the rate of disease progression in amyotrophic lateral sclerosis
1 Department of Headache, Brain Injury and Neurorehabilitation, Institute of Neurology, University College London UK 2 Department of Neuroinflammation, Institute of Neurology, Royal Free and University College Medical School University College London, UK 3 Department of Clinical Neurosciences, Royal Free and University College Medical School University College London, UK 4 The National Hospital for Neurology and Neurosurgery London, UK 5 Centre for Functional Magnetic Resonance Imaging of the Brain, Department of Clinical Neurology, University of Oxford, The John Radcliffe Hospital, Oxford London, UK 6 Medical Statistics Unit, London School of Hygiene and Tropical Medicine London, UK
Correspondence to: Dr Olga Ciccarelli, Department of Headache, Brain Injury and Neurorehabilitation, Institute of Neurology, University College London, Queen Square, London WC1N 3BG, UK E-mail: o.ciccarelli{at}ion.ucl.ac.uk
The goal of probabilistic tractography is to obtain a connectivity index along a white matter pathway that reflects fibre organization and is sensitive to pathological abnormalities contributing to disability. Here, we present the development of voxel-based connectivity measures along the tractography-derived corticospinal tract (CST). We investigated whether these connectivity measures are different in patients with amyotrophic lateral sclerosis (ALS) and correlate with the rate of disease progression. We also investigated whether fractional anisotropy (FA), which reflects directional coherence of fibre tracts, is reduced in the CST of ALS patients and relates to disease progression rate. Thirteen patients with probable or definite ALS and 19 healthy subjects were studied. The probabilistic tractography algorithm segmented the bilateral CST, along which FA and connectivity values were obtained. To take into account the asymmetric distribution of connectivity values, two summary statistic measures that focused on voxels with higher connectivity values were selected and then used in the analysis, together with the mean connectivity and the mean FA. To complete the analysis, the same summary measures for FA were included. Differences in all these indices between patients with moderate or rapid disease progression rate and controls were investigated using linear regression, adjusted for age and white matter fraction. The association between FA or connectivity in the CST and the disease progression rate was assessed using linear regression. Patients with a rapid disease progression rate had significantly lower summary connectivity measures than controls in the left CST, but there was only a borderline statistical difference in mean connectivity. Patients with rapid progression had a significantly lower mean FA, and any other FA measure, in both CSTs than controls. When only patients were considered, strong associations between the rate of disease progression and all the connectivity measures in the left CST were found (P-values between P < 0.001 and P = 0.002, partial correlation coefficients between –0.90 and –0.82). However, there was no evidence of an association between disease progression rate and any of the FA measures in the bilateral CST. Our findings suggest that FA and connectivity provide complementary information, since FA is sensitive to the detection of all the group differences, whereas the summary connectivity measures correlate with disease progression rate. The development of such connectivity measures raises their potential as markers of disease progression in ALS, and provides guidance for their use in other neurological diseases.
Key Words: tractography; diffusion; ALS; progression; connectivity
Abbreviations: ALS, amyotrophic lateral sclerosis; CST, corticospinal tract; DTI, diffusion tensor imaging; FA, fractional anisotropy; WMF, white matter fraction
Received October 6, 2005. Revised March 17, 2006. Accepted March 27, 2006.
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  O. Ciccarelli, C.A. Wheeler-Kingshott, M.A. McLean, M. Cercignani, K. Wimpey, D.H. Miller, and A.J. Thompson Spinal cord spectroscopy and diffusion-based tractography to assess acute disability in multiple sclerosis Brain, August 1, 2007; 130(8): 2220 - 2231. [Abstract] [Full Text] [PDF]
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